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+There are little epidemiological data on the impact of persistent organic pollutants (POPs) and endocrine disruptors on mammographic density (MD), a strong predictor of breast cancer. We assessed MD in 116 non-Hispanic white post-menopausal women for whom serum concentrations of 23 commonly detected chemicals including 3 polybrominated diphenyl ethers (PBDEs), 8 per- and polyfluoroalkyl substances (PFASs), and 12 polychlorinated biphenyls (PCBs) had been measured. Linear regression analyses adjusting for potential confounders were used to examine the associations between the levels of the chemical compounds, modeled as continuous and dichotomized (above/below median) variables, and square-root-transformed MD. None of the associations were statistically significant after correcting for multiple testing. Prior to correction for multiple testing, all chemicals with un-corrected p-values < 0.05 had regression coefficients less than zero, suggesting inverse associations between increased levels and MD, if any. The smallest p-value was observed for PCB-153 (regression coefficient for above-median vs. below-median levels: −0.87, un-corrected p = 0.008). Neither parity nor body mass index modified the associations. Our results do not support an association between higher MD and serum levels of PBDEs, PCBs, or PFASs commonly detected in postmenopausal women.The impact of persistent organic pollutants (POPs) on breast cancer has been of interest due to the estrogenic and endocrine disruptive properties of certain chemicals in this class [1,2], although the epidemiological evidence for this has been mixed.Polychlorinated biphenyls (PCBs), a class of compounds consisting of over 200 different chlorinated aromatic hydrocarbons, are the most extensively studied POPs in relation to breast cancer risk. The manufacture of PCBs was banned in most countries during the 1980s. However, PCBs are still commonly detected in the general US population, both in blood [1,3] and in breast and abdominal adipose tissue [4,5]. PCBs were classified as a known human carcinogen (group 1) by the International Agency for Research on Cancer (IARC) based on sufficient evidence for carcinogenicity for malignant melanoma [2,6]. The evidence for breast cancer was considered limited. Nearly all studies investigating a summary measure of total PCBs did not find a positive association with breast cancer risk [7,8,9,10,11]. Because the endocrine-disrupting properties of PCB congeners are diverse and sometimes conflicting (e.g., weakly estrogenic, anti-estrogenic, and anti-androgenic) [1,7], others have investigated congener-specific associations. A 2016 meta-analysis of congener-specific associations suggested that certain PCB congeners (PCB-99, PCB-183, PCB-187) are associated with increased risk of breast cancer [5].Data on other classes of POPs such as polybrominated diphenyl ethers (PBDEs) and per- and poly-fluoroalkyl substances (PFASs) remain scarce and inconsistent [12,13,14,15,16,17,18,19,20,21,22]. Five studies using post-diagnostic samples have investigated serum or adipose-level PBDEs in relation to breast cancer risk [12,14,15,16,22]. Whereas positive associations were reported for a few PBDE congeners such as BDE-47, BDE-100, and BDE-153 in an area in China highly contaminated from electronic waste recycling [12], and suggestive positive associations were reported for BDE-47 in Alaska Native women [15] and young Canadian women [22], two studies conducted among general populations in California [14,16] reported no associations. Results on PFASs have also been mixed, with studies reporting positive associations for five PFAS compounds among Greenland Inuits [20], weak positive association for a PFAS compound perfluorooctane-sulfonamide (PFOSA) and non-significant inverse association for another PFAS compound among Danish women [17], and a positive association with estrogen receptor-positive breast cancer for perfluorooctane sulfonate (PFOS) in French women [21]; in addition, no associations were found for perfluorooctanoic acid (PFOA) in two studies conducted in an area near a chemical plant [18,19], nor for six PFAS compounds commonly detected in the general population in California [13]. Little is known about the role of these chemicals with respect to pathological changes along the cancer development pathway or cancer treatment. A major limitation common to many of these studies is the use of post-diagnostic samples for cases [13,14,15,16,20,22], with some studies using post-treatment samples [13,14].Mammographic density (MD) is a measure of the relative amounts of epithelium and stroma in the breast and is one of the strongest known predictors of breast cancer risk [23,24,25]. Compared to women with little or no density (<5%), women with extremely dense breasts (>75%) are at 4–5 times increased risk of breast cancer [25]. MD has been associated with established risk factors of breast cancer such as having fewer children, later menopause, and receiving estrogen and progestin combined hormone therapy [26,27,28]. For these reasons, MD has been used as an early marker of breast cancer in clinical trials [29,30] and etiological studies of breast cancer [31,32,33,34,35,36]. A cross-sectional study investigating the associations between breast cancer risk factors and MD can provide useful insights into their roles in breast cancer [31,32]. We investigated the association between serum levels of POPs and MD, a strong risk factor for breast cancer, using data from control participants in a breast cancer case–control study nested in the California Teachers Study (CTS) [13].Study Participants: Study participants were drawn from control participants of a breast cancer case–control study nested in the CTS [13]. The CTS is a prospective cohort of 133,479 female California public school professionals who returned a mailed questionnaire in 1995–1996 and provided information on various breast cancer risk factors [37]. The case–control substudy comprised 902 invasive breast cancer cases diagnosed between 1 January 2006 and 1 August 2014 aged less than 80 years at diagnosis and 858 controls drawn from a probability sample of at-risk CTS participants frequency-matched to cases by age at baseline (5-year age groups), race/ethnicity, and the region of residence (regional cancer registry of California) [13]. These substudy participants completed an interview-administered questionnaire and provided blood samples between October 2011 and August 2015. For the current study, with a target sample size of 160, we sent a study invitation letter along with a consent form, a Health Insurance Portability and Accountability Act (HIPAA) authorization form, and a survey to update information on breast cancer risk factors to 254 women selected from 331 postmenopausal substudy participants between the ages of 60 and 80 years, whose laboratory assays were completed or in process (i.e., samples transported to the laboratory) as of July 2015. Of the 331 women, all 83 nulliparous and 171 of the 248 parous women were invited. Nulliparous women were over-sampled because we were particularly interested in identifying environmental risk factors in this at-risk group. Non-respondents were contacted by a follow-up mail and up to two telephone calls. After excluding 22 women who did not have mammograms taken within 5 years, 155 women (67%) participated during the recruitment phase between January 2015 and August 2015. Reasons for non-participation were refusals (n = 19) and no response during the recruitment phase (n = 57).Data collection and MD assessment: Participants mailed back a signed informed consent, an HIPAA form, and a completed questionnaire on important covariates such as height, weight (current, 5 years ago, 10 years ago), menopausal status, hormone therapy (HT), location and year of recent mammogram screenings. Mammograms were collected for all 155 women. After excluding 15 mammograms presenting technical difficulties, one of the authors (GU) assessed MD for 140 mammograms using the USC Madena software, a validated computer-assisted method to quantitatively assess MD [30,38,39]. In brief, GU assessed the absolute density of each mammogram, and a research assistant trained by EL assessed the total area of the breast. MD was calculated as the percentage of the absolute density divided by the total area of the breast. Reader reproducibility was excellent (r = 0.98; 37 random duplicates). All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Institutional Review Boards at the Cancer Prevention Institute of California (2010-017), the State of California Health and Human Services Agency (12-09-0732), the University of Southern California (HS-14-00627), and the University of California San Francisco (18-25344).Laboratory measurements: Blood samples were processed within hours of collection, and the separated serum stored at −20 °C until analysis. Laboratory methods for the measurement of serum levels of PBDEs, PFASs, and PCBs were described previously [13,16,40]. Briefly, PCBs and PBDEs were measured using automated solid-phase extraction (SPE) and gas chromatography (GC)/high-resolution mass spectrometry (HRMS); PFASs were measured using an online SPE–liquid chromatography–tandem MS (SPE–LC–MS/MS) method. PCB and PBDE chemical levels were lipid-normalized and expressed in units of ng/g lipid. For results below the laboratory limit of detections (LODs), we used LOD/2. In the statistical analyses, we only included the 23 chemicals with detection frequency of 75% or higher: 3 PBDEs, 8 PFASs, and 12 PCBs (Table S1).Statistical Analysis: Analyses were restricted to 116 non-Hispanic white women due to the small numbers for each of the other race/ethnic subgroups (African Americans, Hispanics, Asians/Pacific Islanders, unknown race). The association between each chemical (above vs. below median) and square-root-transformed MD was examined using multivariable linear regression, adjusting for age, body mass index (BMI) (kg/m2), parity (0, 1−2, 3+, non-full-term pregnancy), and estrogen–progestin combined hormone therapy use (never, former, current) at the time of mammography. Additional analyses that adjusted for the type (manufacturer) of the mammography systems (Hologic, GE, other), modeled the serum levels as continuous variables, and used untransformed MD did not change the results; thus, these variables were not used in the final model. We conducted stratified analyses by parity, BMI (≥25 vs. <25 kg/m2), and estrogen–progestin combined hormone therapy (never or ever used) and calculated p values for the interactions by introducing product terms and conducting Wald tests. The p-values were corrected for multiple testing using the Bonferroni method.The characteristics of the study participants are presented in Table 1. Mean age at mammogram and mean age at blood draw were 69.2 years and 67.9 years, respectively. Only 7% of participants were using estrogen–progestin combined hormone therapy at the time of mammogram. For approximately half of the participants (47%), the collected mammogram was taken within one year of blood draw.Of the 23 chemicals analyzed, the smallest p-values were observed for PCBs 153 (p = 0.008) and 138 (p = 0.010), but these associations did not remain statistically significant after Bonferroni correction (Table 2 and Table S1). We did not observe significant associations in subgroups by parity, BMI, or estrogen–progestin combined hormone therapy (EPT) use, or evidence of effect modification. The regression coefficients for all chemicals with un-corrected p-values < 0.05 were less than zero, suggesting inverse associations between their increased levels and MD, if any. For example, in the overall analyses, only PCB-138 and PCB-153 were associated with MD with a p-value < 0.05 before correcting for multiple testing. The regression coefficients observed for PCB-138 and PCB-153, i.e., −0.81 and −0.87, respectively, indicate that women with above-median concentrations of these two chemicals had a similar but slightly lower MD compared to women with below-median concentrations. Similarly, in the subgroup-specific analysis among parous women, the regression coefficients for the two chemicals associated with a p-value < 0.05 before multiple testing correction, namely, PCB-203 and PCB-74, were also less than zero (−0.78 and −0.99), indicating an inverse association, if any. All p-values for the interactions with parity, BMI, or EPT use were >0.05 before correcting for multiple testing.MD is a strong risk factor for breast cancer and increases in response to exogenous hormone use in postmenopausal women [30,38]. Despite biological plausibility, our results in postmenopausal women provide little evidence of associations between serum levels of PBDEs, PFASs, or PCBs and MD. Only one prior study has investigated the association between PCBs and MD. Among 106 post-menopausal women in Canada, 21 of the 24 tested PCB congeners were not associated with MD, and the other 3 congeners (PCB-153, 183, and 196) showed inverse associations, with p-values of 0.03, 0.004, 0.04 (not corrected for multiple testing), which are directionally consistent with our results [41]. PBDEs and PFASs have not been investigated in relation to MD.Whereas the data on MD are sparse, substances in these chemical families (PBDEs, PFASs, PCBs) have been studied with respect to breast cancer risk. Results on PCBs in relation to breast cancer risk are inconsistent with the null findings in relation to MD ([41] and the current study). In a congener-specific meta-analysis, PCB-99, PCB-183, and PCB-187 were associated with increased risk of breast cancer, although the data were from a relatively small number of case–control studies [5]. It is possible that these PCBs increase breast cancer risk through a mechanism other than increasing MD.Previous studies on PBDEs have been limited and reported mixed findings. Although one study of the adipose levels of PBDEs in a contaminated area in China reported a positive association for BDE-47, BDE-100, and BDE-153 [12], these associations were not observed in the general population in California [16] or in studies using serum samples in the CTS [14] or among Native Alaskan women [15]. A recent study of young (age <45 years) Canadian women, the Ontario Environment and Health Study, reported a positive association for BDE-47, which was statistically significant only among premenopausal women (RR = 1.73, 95% CI = 1.02–2.94) [22]. In other studies, more than half of case patients were postmenopausal (~55% in [12,15,16]; ~95% in [14]). Studies reporting no associations [14,15,16] did not separately present results among premenopausal women; however, the sample sizes for premenopausal women in these studies were limited (N of premenopausal case patients ranged from 29 to 43) [14,15,16]. Each of these studies has several limitations, including modest sample sizes (number of case patients ranging from 75 to 209) [12,15,16], the fact of being hospital-based case–control studies that comprised control participants with benign breast disease [12,15,16] or diseases unrelated to breast cancer and who underwent surgery [12], which raises concerns for over-matching, or the fact of relying on post-diagnostic samples of breast cancer patients [12,14,15,16,22]. Case patients from the Ontario Environment and Healthy Study (n = 305) were identified from the Ontario Cancer Registry, thus many of these samples are likely to have been collected after cancer treatment [22].Samples from the CTS study which had the largest sample sizes (n = 902 case patients) were collected on average 35 months after diagnosis and treatment [14]. Although our group did not observe any indication of changes in PBDE levels according to the time interval between diagnosis and sample collection [14], it remains unknown whether breast cancer treatment impacts PBDE levels [14]. Results from a prospective study using pre-diagnostic samples will provide additional insights into the effects of PBDEs. Alternatively, it is also possible that PBDEs increase breast cancer risk in young premenopausal women [22] or in women living in highly contaminated areas [12]. Nonetheless, our null findings provide support that PBDEs may not be strong risk factors of breast cancer among postmenopausal women in the general population.Similarly, PFASs were not, or were at most inversely, associated with breast cancer risk in the CTS [13]. The only published prospective study of diverse classes of PFASs (16 PFASs) used serum samples collected during pregnancy in Danish women and also reported no associations or non-significant inverse associations between those PFASs and premenopausal breast cancer risk, except for a weak positive association observed for perfluorooctane-sulfonamide (PFOSA) [17]. Another prospective study nested in the French E3N (Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l’Education Nationale) cohort investigated two compounds, PFOS and PFOA, and did not observe significant associations with overall breast cancer; however, there was a significant positive linear association between one of the compounds (PFOS) and the risk of estrogen receptor-positive subtype of breast cancer [21]. PFOS levels in the E3N study were much higher than the levels in the CTS (median levels among controls: 17.3 ng/mL and 6.95 ng/mL, respectively) [21]. PFOA was also investigated in two studies in a contaminated area in North Carolina using an ecological study design [19] or mathematically estimated PFOA levels [18], both reporting no associations [18,19]. These findings are in contrast to significant positive associations reported among Greenland Inuits for a summed concentration of 16 PFASs as well as 5 individual PFAS compounds including PFOA, perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluorohexane sulfonic acid (PFHxS), and perfluorooctane sulfonic acid (PFOS) [20]. The median serum levels of some (PFNA, PFDA, and PFOS), although not all (PFOA and PFHxS), of these PFAS compounds were much higher (~2 fold to ~5 fold) among the Greenland Inuits control women compared to the levels in the CTS [13]. This may have contributed to the conflicting findings. In particular, the median level of PFOS in Inuits was 18.2 ng/mL, similar to the level in the E3N study (17.3 ng/mL) [21]. Effect modification by polymorphisms in genes involved in estrogen metabolism such as CYP17A1 -34T/C (rs743572) and COMT Val158Met (rs4680) has been proposed [42,43]; however, the modifying effects of these polymorphisms were not consistent across PFAS compounds or across studies, and frequencies of alleles potentially associated with increased susceptibility to PFASs among Inuits [42] were only slightly higher (rs4680 Met allele) or even lower (rs743572 T allele) in Inuits than in European women [42,44]. Taken together, findings from these studies and our own study suggest that PFAS compounds do not substantially increase breast cancer risk or MD, at least in postmenopausal women. Reasons for the discrepancies in Inuit women as well as a positive finding for PFOSA exposure during pregnancy in Danish women [17] warrant further study.Our study has several limitations, and our results need to be interpreted with caution. Our chemical measurements were based on blood samples collected at approximately the same times of the outcome (MD) measurement and were restricted to postmenopausal women. Therefore, the measured chemical levels may not represent etiologically relevant exposure. Our study cannot address the question whether elevated levels of these chemicals in earlier time periods with different hormonal milieux, such as childhood, puberty, premenopausal period or menopausal transition, are associated with MD and with breast cancer risk. Additional studies in younger women need to be conducted before excluding POPs and PFASs as risk factors in the general population. The suggestion that POPs may cause reproductive abnormalities in women [45], which is related to breast cancer risk, should also be further studied. Our results are also limited by the relatively small sample size and the inclusion of only non-Hispanic white women. However, our statistical power is similar to or greater than that of the only other study on PCBs with a similar sample size (n = 106) [41], and no studies have been conducted on PBDEs and PFASs in relation to MD.Findings from our cross-sectional study do not support a positive association between PCBs, PBDEs, and PFASs and MD among postmenopausal women.The following are available online at https://www.mdpi.com/1660-4601/17/2/606/s1. Supplementary Table (Table S1): Associations between each chemical (above vs. median) and square-root-transformed percent mammographic density (PMD) in all women (n = 116) and in women divided by parity, BMI, estrogen–progestin combined hormone therapy use.Conceptualization, E.L., S.H., P.R. and D.D.; Data curation and exposure and outcome assessment, E.L., G.U., S.H., M.W., Y.W., J.-S.P., M.P., D.D. and P.R.; Statistical analysis, E.L., A.K. and C.T.; Writing–Original Draft Preparation, E.L., A.K., S.H. and P.R.; Writing–Review & Editing, G.U., C.T., M.W., Y.W., J.-S.P., M.P. and D.D; Funding Acquisition, E.L., P.R. and D.D. All authors have read and agreed to the published version of the manuscript.This research was supported by the California Breast Cancer Research Program grant number 20IB-0114 and 16ZB-8501. The parent study (the California Teachers Study) was supported by the National Cancer Institute of the National Institutes of Health under award numbers U01-CA199277; P30-CA033572; P30-CA023100; UM1-CA164917; and R01-CA077398. E.L. was supported by a Career Catalyst Grant CCR15333900 from Susan G. Komen Foundation while part of this research was conducted. The APC was funded by Susan G. Komen Foundation.The authors would like to thank the California Teachers Study Steering Committee that is responsible for the formation and maintenance of the Study within which this research was conducted. A full list of California Teachers Study team members is available at https://www.calteachersstudy.org/team. The authors also express their appreciation to Weihong Guo, Hyoung-Gee Baek, Erika Houtz, Suhash Harwani, and Oscar Waifung Cheung for their contributions to the laboratory analysis.The authors declare that they have no conflicts of interest.Characteristics of 116 postmenopausal non-Hispanic white participants included in this study.Association between square-root-transformed mammographic density (%) and chemicals in all participants and in any of the subgroups based on parity and BMI. Results are presented for chemicals with a p-value < 0.05 in any of the subgroup or overall analyses before correcting for multiple testing *.* All analyses were adjusted for age (continuous), BMI (continuous), parity (0, 1−2, 3+), and estrogen–progestin combined hormone therapy use (never, former, current). ¶ Linear regression coefficient representing differences in √ mammographic density for women with each chemical level above median vs. below median. † p values corrected for multiple testing using the Bonferroni method; § p values not corrected for multiple testing.

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+Even if the epidemic of malignant pleural mesothelioma (MPM) is still far from being over worldwide, the health effects of regulations banning asbestos can be evaluated in the countries that implemented them early. Estimates of MPM future burden can be useful to inform and support the implementation of anti-asbestos health policies all around the world. With this aim we described the trends of MPM deaths in Italy (1970–2014) and predicted the future number of cases in both sexes (2015–2039), with consideration of the national asbestos ban that was issued in 1992. The Italian National Statistical Institute (ISTAT) provided MPM mortality figures. Cases ranging from 25 to 89 years of age were included in the analysis. For each five-year period from 1970 to 2014, mortality rates were calculated and age–period–cohort Poisson models were used to predict future burden of MPM cases until 2039. During the period 1970–2014 a total number of 28,907 MPM deaths were observed. MPM deaths increased constantly over the study period, ranging from 1356 cases in 1970–1974 to 5844 cases in 2010–2014. The peak of MPM cases is expected to be reached in the period 2020–2024 (about 7000 cases). The decrease will be slow: about 26,000 MPM cases are expected to occur in Italy during the next 20 years (2020–2039). The MPM epidemic in Italy is far from being concluded despite the national ban implemented in 1992, and the peak is expected in 2020–2024, in both sexes. Our results are consistent with international literature.Malignant mesothelioma is one of the worst legacies of asbestos exposure, causing an estimated figure of 27,000 deaths per year worldwide [1,2]. As malignant pleural mesothelioma (MPM) is mainly caused by asbestos exposure [3], incidence and mortality for this disease are often used as a marker of previous exposures to asbestos. The observation of increasing trends of MPM occurrence provided a clear alarm regarding the impact of asbestos exposure [4], while the analyses of trends have been used to evaluate the effects of reducing asbestos exposure in the population during more recent periods [4,5,6]. Given the long time that usually elapses between first exposure to asbestos and development of MPM, several industrialized countries that banned asbestos a long time ago are now approaching the peak of MPM cases [7,8,9,10,11] or have reached it in the recent past [12,13,14]. In other countries, where the widespread use of asbestos was common until recently or is even still occurring [15], the increase in MPM incidence is expected to last for many decades [16].Incidence of MPM in Italy rose constantly over the past decades, reaching one of highest rates in the world. [5,6,17,18,19]. Italy banned asbestos extraction, use, and commercialization in 1992 (Italian Law 257/92) and it is thus important to monitor the trend of MPM occurrence to detect the effects of such a ban. The large number of MPM cases expected in the next years is of particular concern due to the extremely poor prognosis of this condition and the current lack of effective therapeutic options [20].In spite of several studies that previously tried to forecast the MPM burden [4,5,6,21], it is still unknown how long the MPM epidemic will last, both worldwide and in the countries that banned asbestos use [13,22,23]. In particular, it is not clear how slow will be the reduction of MPM mortality, once that peak will be reached. Up-to-date predictions of the future trend of MPM are thus necessary to inform public health interventions. The aim of the present paper is to describe the observed number of MPM deaths in Italy during the period 1970–2014 and to provide predictions of the number of deaths expected in the next decades. Predictions are provided separately by gender as the pattern of asbestos exposure is likely to be different, with occupational exposure playing a larger role in men and domestic/environmental exposure being more relevant for women, respectively [24]. Data were collected from the Italian National Statistical Institute (ISTAT). A specific death code for MPM was not available until 2003, when the tenth revision of the International Classification of Diseases was implemented in Italy. Thus, the annual number of MPM deaths in the period 1970–2002 was estimated by applying a correction factor to the number of deaths for pleural cancers (ICD codes: VIII revision: 163.0–163.0; IX revision: 163.0–163.9; X revision: C38.4, C45.0, C45.9) recorded in each year, as proposed by Ferrante and colleagues [25]. ISTAT mortality data were not available for 2004, thus missing data were calculated by interpolation of data from 2003 and 2005.The present analysis was restricted to cases aged between 25 and 89 years of age, as MPM is extremely rare before 25 and diagnosis less certain after 89 years of age. We estimated MPM mortality rates for men and women for each five-year period from 1970 to 2014. Mortality rates by age at death, year of death, and birth cohort were plotted separately for men and women. We used Poisson age–period–cohort (APC) models to forecast MPM future trends [26]. Logarithm of person-years (py) was set as the offset in each model. Actual (1970–2014) and predicted (2015–2039) population data, stratified by year, gender, and age, were obtained by the National Institute of Statistics website (http://demo.istat.it/index_e.html). Gender-specific age, period, and cohort regression coefficients were then applied to population data to calculate projections of the numbers of cases of MPM and their 95% prediction intervals (PIs) for the years 2015–2039. PIs were computed using a bootstrap method proposed by Yang and colleagues [27].A likelihood ratio (LR) test was used to compare the APC model with nested models (i.e., age–cohort and age–period models). An overall comparison among nested and not-nested models was also carried out using the Akaike Information Criterion (AIC). Data management and statistical analyses were performed with the APC R software package [28].During the period 1970–2014, a total number of 28,907 MPM deaths were observed, 20,245 (70.0%) among men and 8662 (30.0%) among women. MPM deaths increased constantly over the study period, ranging from 856 cases in 1970–1974 to 4275 cases in 2010–2014 among men, and from 500 cases in 1970–1974 to 1569 cases in 2010–2014 among women (Table 1.) The men-to-women ratio also increased, shifting from 1.73 in 1970–1974 to 2.72 in 2010–2014. MPM was uncommon under 45 years of age. During the study period, a constant decrease of the percentage of cases under 45 years of age was observed in both genders (5.02% to 0.58% and 7.06% to 0.57%, in men and women respectively). More than 80% of MPM cases in both sexes were aged 60 or older.MPM rates increased constantly over time in both genders, reaching in 2014 a maximum of 3.99 per 100,000 person-years (py) in men and 1.34 per 100,000 py in women (Table 1). In addition, mortality rates increased by age within each birth cohort (Figure 1 and Figure 2 and Tables S1 and S2). Among women, rates were much lower than in men, being usually one third or less. In men, the highest rate (17.9 per 100,000) was observed in birth cohort 1930–1934 among people aged 80–84, while rates over 10 per 100,000 were observed in those born from 1910 to 1940 (Figure 1 and Table S1). The highest rate in women was observed in the birth cohort 1930–1934 (80–84 years of age, 5.3 per 100,000 py), and rates exceeding 4 per 100,000 py were observed in those born between 1895 and 1939 (Figure 2 and Table S2). Compared to previous years, a steep increase in MPM rates among those aged 60 or older was observed in both genders from 2000 onwards (Table 1 and Figure 1). In the period 1970–1999, on average, the yearly increase in MPM rates was about 4.5% and 1.2% in men and in women, respectively. These figures increased to 10.0% among men and 2.7% among women in 2000–2014.The age–period–cohort (APC) model provided the best fit to the data. However, age–cohort (AC) provides a very similar fit, and predictions of APC and AC models were almost identical (Table 2, Figures S1 and S2).Observed (1970–2014) and predicted (2015–2039) numbers of MPM by gender are reported in Figure 3. About 19,500 and 6700 MPM cases are expected among men and women, respectively, by the next 20 years (2020–2039) in Italy. The peak of MPM cases is expected to occur during the 2020–2024 period for both genders, with about 5200 and 1800 MPM cases among men and women, respectively. The decrease following this peak will be slow: the predicted number of MPM cases in 2035–2039 will be about 80% of that expected during the peak (Figure 3). The decrease will be similar among the two genders, with a rather constant men-to-women ratio from 2015 to 2039, ranging between 2.89 and 2.98.This study evaluated the evolution of the MPM epidemic in Italy, providing both observed (1970–2014) and predicted mortality (2015–2039) figures, based on national mortality statistics provided by the Italian National Institute of Statistics (ISTAT). Our results suggest that the number of MPM cases is still increasing, with a predicted peak of more than 7000 deaths in the period 2020–2024.Although the trend of the number of MPM deaths was constantly increasing along the 1970–2014 period, a further acceleration was observed since the end of the 1990s. This rise could be due to several factors, in particular to the large use of asbestos in Italy that occurred between the 1950s and the first half of the 1970s. Indeed, different authors showed that the risk of developing MPM is mainly related to exposure occurring three to four decades before [29]. The improvement of MPM diagnostic accuracy could also have played some role in this trend. Studied conducted in other countries reported a yearly 5% decrease of misdiagnosis of MPM starting from the 1990s [4,14,18,30].According to our predictions, the peak in MPM cases is expected in the next few years (2020–2024), followed by a plateau and a slow decrease in the following decades. Notably, the predicted number of MPM cases from 2020 to 2039 (about 26,000) is very similar to the number of cases observed so far. This would imply that a substantial part of the MPM epidemic in Italy is still to come. However, it should be also considered that the models used for the present predictions could not completely capture the effects of the implementation of the asbestos ban in 1992. As the effects of such a ban are expected to become evident 30 to 40 years after its enforcement, the number of MPM cases that will be observed in the next few years will be relevant to provide accurate information on the future trends. As MPM is a disease that is more common among subjects aged >60 years, changes in the age structure of the population can substantially affect the predictions of future number of MPM as well. Thus, an increase of MPM cases could occur in an aging population even if age-specific incidence rates remain constant or decrease. A similar phenomenon has been recently observed in an age–period–cohort analysis of incidence data in the United States [14]. Finally, our predictions do not assume any future improvement in the prognosis of MPM, which is presently poor [31]. Any effective new treatment for MPM becoming available in the next years may reduce the future number of MPM deaths. Our study is one of the first to provide MPM forecasts for women. It is noteworthy that the men-to-women ratio showed a continuous increasing trend over 1970–2014 (from 1.73 in 1970–1994 to 2.72 in 2010–2014), with a larger increment after 1995. The largest absolute difference between cases in males and females (2706 cases) was observed in 2010–2014. However, the men-to-women ratio is predicted to remain rather constant in the future, suggesting that the shape of the future decreasing trend of MPM will be similar in both sexes. Also recent Italian incidence data depict a constant men-to-women ratio [32], thus contributing to corroborate our results. Our results are consistent with those from Italian studies conducted both at regional [19,33,34] and national [8] levels. In particular, previous predictions by Marinaccio et al. [8] for the male population, obtained by applying AC and APC models, suggested a peak of 890 annual deaths in the period 2020–2024. Analyzing incident cases of malignant mesothelioma (all sites) in the Lombardy region (northwest Italy) using an age–cohort model, Mensi et al. [19] found that the peak is expected around 2019. Conversely, the study by Girardi and colleagues in the Veneto region estimated a peak in the incidence of MPM cases in 2010 [33]. However, it should be also noted that, following the peak, this study predicted a plateau in MPM cases until 2026, thus partially overlapping with the national predictions.Different studies suggest that national mortality data probably underestimate the actual number of mesotheliomas due to misdiagnosis, non-diagnosis, or lack of reporting [35,36]. Interestingly, extrapolations from the Global Burden of Disease (GBD) data suggest a substantially larger number of mesothelioma deaths in Italy than reported from the National Office of Statistics [37]. Although it is not clear how much of this apparent discrepancy is due to real misclassification, we note that the increasing temporal trend in MPM deaths that we observed is completely consistent with the one highlighted by GBD data [37]. In fact, the pattern of mesothelioma death rates by birth cohort and age observed in our data is similar to that estimated by other data sources, such as the same GBD database [37].Worldwide, several studies tried to forecast the future burden of MPM. [4,5,6,21]. In Great Britain, Hodgson and colleagues predicted the MPM peak in the period 2011–2015 [7]. More recent studies substantially confirmed this prediction, placing the peak around 2016–2017 [9,38]. Several Nordic European countries show a pattern similar to Great Britain. In Denmark and the Netherlands, the peak of male MPM cases was predicted in 2015 and 2017, respectively [39,40]. Sweden is a notable exception, where the peak in MPM deaths was observed already in the 1990s [13], although a recent study seems to indicate a new increase in the number of deaths from mesothelioma after 2000 [37]. According to the most recent predictions, the number of MPM cases in Spain will increase at least until 2020 [41]. U.S. men have probably already reached the peak of MPM cases during the 2002–2007 period, although the MPM epidemic is predicted to last at least until 2042 [42]. In Canada, the peak of male MPM cases is predicted to be reached in 2020 [43]. In Brazil [44], the number of MPM cases is predicted to increase until 2026, while in Japan and South Korea the peak is expected around 2030 [16,45].Differences in the period of maximum burden of MPM cases are largely determined by past national consumption of asbestos and the implementation of bans of its usage [29]. This inference is also supported by asbestos consumption models, where the gap between the peak of asbestos use and that of MPM cases is estimated to be about 30 to 40 years [7,8,41,43,44,45,46]. In our case, the Italian ban implemented in 1992 is probably starting just now to show its positive effects. Future studies will be useful to thoroughly evaluate the effect of the Italian asbestos ban and its efficacy in terms of MPM death reduction.In general, the decrease of the number of MPM cases following the peak is generally predicted to be a slow process, with a large amount of cases expected after the peak. The case of Great Britain is a notable exception, given that all authors agreed on a rapid decrease of MPM cases following the peak [7,9,38]. The reason of the peculiar trend of Great Britain is presently unknown and warrants further investigations.Our study predicts a slow decrease of MPM deaths following the peak. This picture is of particular concern for its clinical and preventive implications. Caring for MPM patients (irrespective of them being former asbestos workers or not) has to be viewed as a long-term program, which requires strong support for research for improving therapeutic options and for finding suitable and reliable markers allowing for an early diagnosis. Finally, compensation for occupational MPM has to be extended towards future decades, and remediation for environmental sources of exposure has to be strengthened to prevent further asbestos exposure and also to evaluate and manage the issue of asbestos in place, which at present is still an open question due to the lack of reliable data at the national level.Our results are consistent with the literature data highlighting that the MPM epidemic in Italy is still far from being concluded, despite the national ban implemented in 1992. Predictions of the future burden of disease could help to rationally program interventions devoted to the care of MPM patients, remediation of asbestos-contaminated sites, and compensation for occupational MPMs.The following are available online at https://www.mdpi.com/1660-4601/17/2/607/s1, Figure S1: Predictions by AC and APC models for men, Italy. 1970–2039, Figure S2: Predictions by AC and APC models for women, Italy. 1970–2039; Table S1: Mortality rates of malignant pleural mesothelioma (x 100 000 person-years) in men by birth cohort and age at diagnosis. Italy. 1970–2014. Table S2: Mortality rates of malignant pleural mesothelioma (x 100 000 person-years) in women by birth cohort and age at diagnosis. Italy. 1970–2014. Table S3: APC predictions and detailed data for 5-year categories.Conceptualization,  E.O., J.B., C.R.N., M.B., D.C., A.M., C.M., and F.B.-A.; methodology, J.B., C.R.N., and F.B.-A.; software, J.B., and C.R.N.; formal analysis, J.B, and C.R.N.; investigation, E.O., J.B., C.R.N., M.B., D.C., A.M., C.M., and F.B.-A.; resources, J.B, and F.B.-A.; data curation, J.B., M.B.; writing—original draft preparation, E.O.; writing—review and editing, E.O., J.B., C.R.N., M.B., D.C., A.M., C.M., F.B.-A.; visualization, E.O, J.B, and C.R.N.; supervision, A.M, D.C., C.M, and F.B.-A.; funding acquisition, F.B.-A.”, please turn to the CRediT taxonomy for the term explanation. Authorship must be limited to those who have contributed substantially to the work reported. All authors have read and agree to the published version of the manuscript. This research was supported and partially funded by INAIL (Italian Workers Compensation Authority) research triennial plan of action 2016–2018, project BRIC n. 59.E.O., D.C., C.M., and F.B-A. served as consultants for the court in trials concerning asbestos-related diseases.This study is based on population aggregate data, and does not require ethical approval.Malignant pleural mesothelioma death rates (×100,000) by age and birth cohort. Men, Italy, 1970–2014.Malignant pleural mesothelioma death rates (×100,000) by age and birth cohort. Women, Italy, 1970–2014.Observed and predicted number of cases of malignant pleural mesothelioma, with 95% predicted intervals. Age–period–cohort model, Italy, 1970–2039.Pleural mesothelioma deaths and mortality rates (×100,000 person-years) by age and period, Italy, 1970–2014.Mortality rates for malignant pleural mesothelioma. Age–Period–Cohort analysis. Comparisons of different models.AIC: Akaike Information Criterion. LR: Likelihood ratio. NA: not applicable.

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+In sub-Saharan Africa, many families travel to collect water and store it in their homes for daily use, presenting an opportunity for the introduction of fecal contamination. One stored and one source water sample were each collected from 45 households in rural Kenya. All 90 samples were analyzed for fecal indicator bacteria (E. coli and enterococci) and species-specific contamination using molecular microbial source tracking assays. Human (HF183), avian (GFD), and ruminant (BacR) contamination were detected in 52, two, and four samples, respectively. Stored water samples had elevated enterococci concentrations (p < 0.01, Wilcoxon matched pairs test) and more frequent BacR detection (89% versus 27%, p < 0.01, McNemar’s exact test) relative to source water samples. fsQCA (fuzzy set qualitative comparative analysis) was conducted on the subset of households with no source water BacR contamination to highlight combinations of factors associated with the introduction of BacR contamination to stored water supplies. Three combinations were identified: (i) ruminants in the compound, safe water extraction methods, and long storage time, (ii) ruminants, unsafe water extraction methods, and no soap at the household handwashing station, and (iii) long storage time and no soap. This suggests that multiple pathways contribute to the transmission of ruminant fecal contamination in this context, which would have been missed if data were analyzed using standard regression techniques.Access to safely-managed drinking water services has been steadily improving throughout the world [1]. The World Health Organization (WHO)/United Nations Children’s Fund (UNICEF) Joint Monitoring Program (JMP) for Water, Sanitation and Hygiene (WASH) defines a safely-managed drinking water service as one that is located on premises, available when needed and free from contamination [2]. Still, in 2015, 2.1 billion people, or approximately 29% of the global population, did not have access to a safely-managed drinking water service, including 76% of the population in sub-Saharan Africa [2]. The majority there (50% of the population) must travel to collect drinking water from a communal but improved source, storing it in their homes for daily use. The remainder (26% of the population) use unimproved sources like surface water or unprotected springs [2].In the cases where water is stored in the household for later use, drinking water can become contaminated after collection from the source, resulting in a significant decline in quality [3,4,5]. Contamination can be introduced to stored water by hands or fomites entering the water [3,6,7]. Contamination of stored water is more severe when storage vessels are earthenware containers [4] or left uncovered [3], although safe storage vessels with a narrow mouth, lid, and tap have been shown to reduce contamination and improve health outcomes [8]. Point of use (as opposed to point of delivery) water treatment methods have been suggested to protect the quality of water consumed; however, long-term and reliable use of these types of treatment methods is needed to protect health [9]. Overall, there is a lack of understanding of how various household attributes and human behaviors affect stored water quality. Although studies in Tanzania [10], Peru [11], and Bangladesh [12] all reported contamination of stored drinking water supplies, none identified pathways of contamination that would describe a majority of contamination events. In addition, a recent study of stored water quality in rural and peri-urban Tanzania [13] explored how various factors (e.g., human behavior and household and water characteristics) were associated with stored water quality. However, the resultant models could only explain a small amount of variance in the water quality measurements [13], comparable to the models used in other studies. In the present study, we apply a qualitative modelling approach, fuzzy set qualitative comparative analysis (fsQCA), to explore how various combinations of household and environmental attributes combined with human behaviors are associated with stored water contamination. This will provide additional insight into the complexities of fecal contamination transmission in household settings, particularly if contamination is being transmitted via multiple pathways.fsQCA has several advantages over standard regression methods [13]. For example, it does not require the analyst to specify the interactions between the causal conditions a priori. Therefore, fsQCA does not rely on the analyst’s preconceived notions about the relationships in order to identify complex interactions among the causal conditions that give rise to the outcome. It also does not assume causal symmetry, i.e., the conditions leading to the absence of the outcome are not presumed to be the opposite of those leading to its presence. fsQCA also allows for meaningful categories of values for the causal condition relative to the outcome to be coded explicitly. This removes irrelevant variation in the indicator and minimizes the influence of outlier cases in the analysis. fsQCA has been used to identify complex relationships in renewable energy [14], online shopping and marketing [15], organizational performance [16], and, recently, WASH, where it was used to study combinations of community, program, and external conditions associated with the long-term sustainability of rural water supply programs [17]. The present study is a unique, but fitting, application of fsQCA to explore combinations of factors associated with the introduction of fecal contamination to environmental water samples.Globally, microbial guidelines for drinking water quality are based on concentrations of FIB (fecal indicator bacteria) including E. coli, enterococci, and total and fecal coliforms [18]. FIB are used as water quality indicators because they are present in high concentrations in sewage and feces [19] and are relatively inexpensive to measure compared to pathogens. Conceptually, FIB concentrations should be high when fecal pathogens are present and thus their high concentrations in drinking water should indicate that exposure to fecal pathogens is likely. Some studies have found positive associations between FIB concentrations in drinking water and adverse health outcomes [20,21]. However, other studies have shown either a lack of correlation between FIB and pathogen presence in drinking water [22,23,24] or a lack of association between human health outcomes and FIB concentrations in drinking water [7,25,26]. Differing results among studies might suggest that the conceptual model does not consider important sources or fate processes that differentially affect FIB and pathogens in drinking water. For example, FIB can come from a variety of sources other than human feces or sewage including non-human animals, and health risks vary by fecal sources [27]. Non-human animal feces do not contain human viruses, an important etiology of waterborne illness [27]. Host-associated fecal indicators have been proposed as a means for identifying different types of animal fecal contamination in water [28,29,30]. Host-associated fecal indicators are typically detected using molecular biological methods like PCR (polymerase chain reaction). Their use to identify sources of fecal contamination is referred to as MST (microbial source tracking). While MST methods have been used within high-income countries to identify sources of environmental contamination [31], they have rarely been applied in low- and middle-income countries [6,12,32,33,34,35,36,37].This study was conducted among households enrolled in a large-scale randomized controlled trial of water, sanitation, handwashing, and nutrition interventions in rural Kenya (WASH Benefits Kenya). The trial found that the water intervention (chlorination) improved microbial water quality as measured by E. coli, but none of the interventions reduced E. coli contamination on child hands or on sentinel toy balls [38], and none of the interventions reduced child diarrhea or improved child growth [39]. The study investigators concluded that the interventions were not able to sufficiently reduce fecal contamination in the household environment [40]; one potential explanation is that animal feces were a substantial source of fecal contamination in study households [38]. This study uses MST to investigate the animal hosts that contribute fecal contamination to stored and source water supplies collected from a subset of study households. In addition, fsQCA is used to identify combinations of causal conditions that lead to the introduction of fecal contamination to the household stored water supply.Water and fecal samples were collected from a subset of households enrolled in the WASH Benefits Kenya study [39]. All the households that participated in the present study were visited during baseline data collection for the main trial between 26th August and 6th Sept 2013 [41]. Villages were eligible for enrollment if they were rural (defined as having <25% of residents living in rental houses, <2 gas/petrol stations and <10 shops) [41], relied largely on communal water sources, had unimproved sanitation facilities, and were not participating in any ongoing WASH or nutrition programs [39]. The households are located in rural areas of Kakamega county in western Kenya (0°17′01.5′′ N, 34°45′04.5′′ E, map of households previously published [42]), which are populated mainly by subsistence farmers [41].Fecal samples were collected to validate molecular MST targets for the study area. Fecal samples were collected from chickens (n = 20), cows (n = 20), goats (n = 20), dogs (n = 17), sheep (n = 20) and humans (n = 19), which represent the animals most common in the area [43]. The non-human fecal samples were collected from household-owned animals throughout the study areas using a sterile fecal specimen collection container with a spoon built into the cap. Field staff were trained on host identification of fecal specimens. More than 2 g of feces was collected from each pile sampled, with care taken to avoid including soil. Although efforts were made to target fresh feces that appeared to be deposited within the past day, the precise age of each specimen was unknown. Human fecal samples were collected from adult females (ages 18–45 years) and male and female children aged under 2.5 years to achieve variation in age and gender. A stool sample kit, consisting of a sterile stool collection tube with scoop, aluminum foil, and gloves, was left with the household and then collected the next day. The households which supplied fecal samples are different from those that supplied the water samples (described below). Collected samples were stored in coolers on ice and transported to a local laboratory for processing.Aliquots of equal mass from between two to four individual fecal specimens of the same animal type were combined to form a 2.0 g composite as indicated in Table S1. Molecular grade water (Thermo Fisher Scientific, Waltham, MA, USA) was added to the composite samples to make 20 mL fecal slurries in DNA-sterile 50 mL centrifuge tubes (Fisher Scientific, Hampton, NH, USA). The concentrations of E. coli and enterococci were enumerated via membrane filtration of dilutions of the slurries through Millipore HABG 047 S6 0.45 μm pore size filters (Fisher Scientific) and placing them on MI and mEI selective media (EPA methods 1604 [44] and 1600 [45], respectively). Samples were processed at multiple dilutions to ensure that the number of colonies on plates was between 10 and 500 CFU [46]. In addition, 2 mL of the slurry was membrane filtered through 0.4 μm pore size polycarbonate filters (Isopore Millipore Filter, Fisher Scientific) for molecular analysis. The filter was treated with 0.5 mL of RNAlater solution and allowed to sit atop the filter for 5 min before it was vacuum filtered through. The filters were then stored in microcentrifuge tubes with glass beads (Generite, North Brunswick, NJ, USA) at −20 °C until transport to a US-based laboratory (within 1 month). Filters of avian fecal samples were heat treated (after treatment with RNAlater) at 74 °C for 30 min prior to transport according to United States Department of Agriculture regulations. Samples were then stored at −80 °C until DNA extractions were performed in 2014. One fecal composite per animal source type was processed in duplicate to assess intrinsic assay variability. Lab process blanks were created each field sampling day using molecular grade water (i.e., diluent of the slurries).Locally trained enumerators visited each of 45 study households to interview the primary female caregiver in Kiswahili and make observations about WASH behaviors and infrastructure in the household. All respondents provided free and informed consent to participate. Enumerators recorded observed household water sources, sanitation facilities, hand washing facilities, and animal presence within the home and compound. Enumerators also collected self-reported handwashing behaviors, water treatment and extraction methods, household building material, and drinking water storage time from the respondent. All baseline survey data were recorded using a netbook laptop, with the survey programmed in Blaise (Westat USA, Rockville, MD, USA). The study was conducted in accordance with the declaration of Helsinki, with the study protocol approved by the Committee for the Protection of Human Subjects at the University of California, Berkeley (protocol number 2011-09-3654), the institutional review board at Stanford University (IRB-23310), and the scientific and ethics review unit at the Kenya Medical Research Institute (protocol number SSC-2271) [39].At the same time as the household survey, enumerators collected stored drinking water samples from the households. The enumerator asked the respondent to collect water as they normally would for drinking and deposit the water sample directly into a sterile Whirl-pak (Nasco, Fort Atkinson, WI, USA) sample bag (approximately 500 mL volume). On the same day as the household survey, a separate team of enumerators collected a water sample directly from the source where the stored water had been collected (as reported by the respondent) and recorded the water source type (i.e., borewell, shallow well, spring, or piped water). After collection, water samples were stored in a cooler on ice, transported to a local lab, and processed within 12 h of collection. E. coli and enterococci were enumerated in 100 mL volumes of the water samples using membrane filtration with 0.45 μm pore size HA filters (Millipore, Burlington, MA, USA) on MI and mEI selective media (EPA standard methods 1604 [44] and 1600 [45], respectively). Results are presented as concentrations in units of CFU (colony forming units) per 100 mL. If the plate count was too numerous to count (i.e., greater than ~500 CFU), then 500 CFU/100 mL was used as a substitution for the counts. In addition, 100 mL volumes of the water samples were membrane filtered, transported, and stored using the same protocol as with the fecal samples. DNA extractions were performed in 2018. Lab process blanks were processed each field sampling day using molecular grade water.In the US-based laboratory, DNA was extracted from the fecal sample filters using the commercial DNA EZ extraction kit (Generite). Ten to twenty samples were extracted at a time, and an extraction blank (i.e., reagents only, with no sample filter included) was created with each extraction set. The following MST Taqman qPCR (quantitative PCR) assays were performed on the fecal sample DNA extracts: HF183 taqman [47], BacHum [48], humM2 [49], BacCow [48], Rum2Bac [50], and BacR [51]. An avian SYBR green assay termed GFD was also performed [52]. Cycling parameters and primer and probe concentrations were as described in the referring manuscript of each assay. The master mixes used for the MST assays are shown in Table S2.DNA from the water samples were extracted from their filters using the commercial DNA EZ extraction kit (Generite). Between 5 and 23 samples were extracted at a time, with an extraction blank (i.e., no sample filter included) created with each extraction set. The following qPCR assays were performed on the water sample DNA extracts: HF183 Taqman [47], BacR [51] and Avian SYBR green GFD [52] following the same protocols as for the fecal samples. These were the best performing assays for human, ruminant, and avian species, respectively, based on the validation study.Plasmid standards required for each assay were either purchased from IDT (San Jose, CA, USA) or extracted from plasmid-carrying E. coli grown from existing stock using the commercial QIAprep Spin Miniprep Kit (Qiagen, Valencia, CA, USA). The concentrations of plasmid standards were quantified using Nanodrop (Thermo-Scientific, Wilmington, DE, USA). Each qPCR plate processed included a standard curve run in triplicate with concentrations of standard (Table S2) ranging from 101 copies per μL of DNA extract to 105 copies per μL of DNA extract. Each reaction contained 2 μL of DNA extract. Triplicate no-template controls were included with each 96-well plate. All fecal samples were processed in triplicate and all water samples were processed in duplicate.For each assay, a master standard curve was created by combining the standard curves from individual qPCR plates. CT (mean cycle threshold) values were assigned using 0.03 as the fluorescence threshold for all assays. The master standard curve was used to calculate molecular marker concentrations in samples using the sample’s CT. A sample was considered detected within the ROQ (range of quantification) if the sample’s mean CT value corresponded to a concentration between 101 copies per μL DNA extract and 105 copies per μL DNA extract. If the sample had a mean CT value that corresponded to fewer than 10 copies per μL DNA extract, the sample was reported as DNQ (detected but not quantifiable). If the sample had a concentration above 105 copies per μL DNA extract, then the sample was decimally diluted until its concentration was within the ROQ. If the sample had an undetermined CT value for both replicates, then the sample was reported as a ND (non-detect). For the fecal samples, if two out of three of the reactions were undetermined, the sample was reported as a ND. Water sample results within the ROQ were reported as the average number of molecular marker copies detected per mL of water sample; if one out of two reactions was undetermined, the sample was reported as a ND unless the other reaction was within the ROQ, in which case the sample was reported as a DNQ. A modified spike and dilute method was used for assessing inhibition in the water and fecal samples. Specific details are in Appendix A.MST assay validation was conducted using quantitative and binary methods following the approach outlined by Boehm et al. [53]. For the quantitative analyses, the chosen metric was the concentration of MST molecular marker detected in a fecal composite sample normalized by the number of enterococci colonies formed, i.e., copies per CFU ENT. For an MST assay to be labeled as sufficiently sensitive, the median concentration of the MST molecular marker in the target host feces (that is, the feces of the targeted animal host) should be greater than 10 copies per CFU ENT. Ten copies per CFU ENT represents a 100 mL environmental sample having 100 CFU ENT/100 mL if the filtered sample yielded 100 μL of eluent (i.e., 1 CFU ENT/μL of eluent) after DNA extraction and had a lowest detectable concentration of 10 copies/μL DNA extract (therefore 10 copies/CFU ENT) in the qPCR reaction. An MST assay was considered specific if the concentration of the MST marker in all non-target host feces samples were lower than the lowest concentration detected in a target host fecal sample, with only concentrations detected within the ROQ considered as described previously [53].A binary analysis of MST assay performance was also conducted on the basis of the presence/absence of the molecular marker in the sample. A fecal sample was considered positive for an MST marker if it returned DNQ or ROQ but considered negative if it returned ND. The sensitivity::
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+		reported as a percentage, is the fraction of positive target samples tested (i.e., true positives) over the total number of target samples processed. The specificity:
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+        reported as a percentage, is the fraction of negative non-target samples identified (i.e., true negatives) over the total number of non-target samples processed. An 80% threshold was set for an assay to be labelled sensitive and/or specific [53].Water quality indicators (i.e., MST molecular markers and FIB) were used in various analyses in binary (presence/absence) and continuous form (concentration of the molecular marker in the water sample). When continuous variables were used for FIB data, substitutions for NDs were necessary because the data were log10-transformed [12]. As such, NDs for FIB (E. coli and enterococci) were replaced with 0.5 CFU per 100mL water sample.Statistical analyses included the Wilcoxon matched pair and rank sum tests and the McNemar’s exact test. The Wilcoxon matched pair and McNemar’s tests were used to assess trends in both the MST molecular markers and FIB indicators by assessing the paired source and stored water samples from households, whereas the Wilcoxon rank sum test was used to identify correlations between the MST molecular markers and FIB indicators used in the study. Wilcoxon tests were conducted because the data were not normally distributed, while the McNemar’s exact test was conducted because the sample size of households was small. When tests used binary data for the presence of MST molecular markers, a marker was considered present if it was detected in a sample (i.e., ROQ or DNQ). p values below 0.05 were considered statistically significant. All analyses were implemented in R.To identify relationships between ruminant contamination in stored water and combinations of household behaviors and characteristics, an fsQCA approach was employed using the fsQCA3.0 software downloaded from fsqca.com. The household sample for the fsQCA analysis was drawn from the 45 study households for which stored and source water samples were available for FIB and MST analyses. The 33 households ultimately included in the fsQCA analysis were those with no detected ruminant contamination, i.e., BacR molecular marker, in the source water supply. This choice was made to focus on the identification of factors that are associated with post-supply introduction of contamination.The conceptual model, shown in Figure 1, shows four causal conditions that are theorized to be associated with the outcome of introduction of ruminant fecal contamination (indicated by detection of BacR) to a household’s stored water supply. The outcome and causal conditions used for the fsQCA analysis are described in Table 1, which lists each construct, its definition, its theoretical relevance to the conceptual model, its hypothesized effect on the outcome, the indicator used to measure it, and how it is scored as input to the fsQCA analysis. Indicators were chosen for their validity and reliability as proxies for the construct based on prior experience given the constraints that data had to be complete for all households and heterogenous. The indicator was considered sufficiently heterogenous if there were no more than 85% of households reporting the same value [54,55].The causal conditions and shorthand descriptions of their indicators are: the presence of ruminants in the household’s broader compound (“Ruminants”), unsafe water extraction methods where water was obtained from the storage receptacle by dipping hands or an object as opposed to being poured (“Unsafe Extraction”), the opportunity for introduction of contamination due to long storage time in the household after collection (“Long Storage Time”), and the lack of preventative measures against the introduction of contamination by hands by having neither soap nor water at the household’s handwashing station (“No Soap”). In addition to being an indicator for the construct of prevention of contamination by hands, soap may also serve as a combined indicator of wealth and education since it could reflect both knowledge that handwashing is important and having the means to afford soap. This was demonstrated by intermediate analysis steps, with details provided in Appendix B.To conduct the fsQCA analysis, a .csv file was created with the columns showing the causal and outcome conditions and the rows listing the values of their indicators for each included household. The indicators of the causal and outcome conditions for each case (household) were coded with values ranging between 0 and 1. A value of zero for an indicator signifies that the household is ‘fully out’ of the set of households with that characteristic, whereas a value of 1 for an indicator signifies that the household is ‘fully in’ the set of households with that characteristic [54]. A value between the two therefore suggests that a case is more ‘in’ than ‘out’ of the set if larger than 0.5 and vice versa if smaller than 0.5, with 0.5 the score of maximum ambiguity. The results of the analysis are combinations that are evaluated in terms of their consistency and coverage [54], where:
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+        Consistency and coverage scores above 0.8 are conventional thresholds for establishing combinations [54].A necessary condition implies that all cases exhibiting contamination have the causal condition present. A sufficient condition is that there is contamination whenever that causal condition is present, but that there may be cases of contamination where the condition is not present.fsQCA places an emphasis on ensuring that differences in the coded values reflect meaningful and substantive variation, with indicator values pre-processed from survey data to reflect the coding scheme described in Table 1. For example, it is less important to capture the precise number of ruminants that live in a compound than it is to group the number of ruminants into herd sizes that represent differential fecal contamination risks. However, given the lack of existing literature for what meaningful variation may be across the indicators, most causal conditions were coded as binary, i.e., as either 1 or 0. Indeed, the only construct for which the indicator was coded in a continuous manner with values along a spectrum from 0 to 1 was the opportunity for the introduction of contamination (i.e., length of time water has been stored in home). Previous literature indicates that storing water for a period of 24 h substantially increases the probability of contamination being introduced [11]. As such, “Long Storage Time” was coded as 0.95 if 24 h had elapsed since collection to represent being fully in the set of households where storage time was likely to be associated with contamination. “Long Storage Time” was coded as 0.05 if an hour had elapsed to represent being fully out of the set, and as 0.5 if 4.5 h had elapsed to represent maximum ambiguity. The fsQCA software then scored all other storage time lengths with respect to these three set data points [54] using the calibrate sub-function of the Compute function as detailed in Appendix B.Thus, the fsQCA analysis conducted had detection of the BacR molecular marker in the household’s stored water supply as the outcome condition and “Ruminants”, “No Soap”, “Unsafe Extraction”, and “Long Storage Time” as the causal conditions hypothesized to be most associated with this outcome. Further analysis details are presented in Appendix B.Fecal composites and water samples were processed alongside 19 process blanks. All process blanks were free from contamination when subjected to FIB enumeration and the 7 MST assays. DNA extractions from the fecal composites and water samples generated five and 10 extraction blanks respectively, which were processed in duplicate and all free from contamination when subjected to the three chosen MST assays. Thirty-five inhibition tests using water and fecal DNA extracts showed no inhibition. Data from the standards were combined to generate master curves (Figure S1) with a LLOQ (lower limit of quantification) of 10 copies per mL water sample for each assay.Of the seven MST assays tested, the BacR, HF183 and Avian GFD assays were found to be effective at detecting and distinguishing ruminant, human, and avian fecal contamination, respectively, in Western Kenya. All were specific in the quantitative analysis and 100% sensitive in the binary analysis, as shown in in Table 2. These MST assays were selected to analyze the water samples.Of the human-associated fecal assays (HumM2, HF183, and BacHum), none met the quantitative sensitivity criterion, i.e., none had the median concentration of the MST molecular marker in human feces as being greater than 10 copies per CFU ENT (Figure 2). However, all three assays had a wide range of target detection that crossed this threshold, with 80% or more of the human fecal composite samples returning positive (i.e., were detected within the ROQ) and therefore meeting the binary sensitivity criterion (Table 2). Still, heterogeneity in the detection of the target meant that it was sometimes not detected even with a composite sample from 4 individuals, as can be seen with BacHum. The HF183 assay satisfied the quantitative specificity criterion because concentrations of the molecular marker in all non-human fecal composites were below those in the human ones, whereas this was not true of the HumM2 and BacHum assays. None of the assays met the binary specificity criterion, i.e., fewer than 80% of non-human fecal composites correctly returned a negative result. As such, HF183 was identified as the most effective of the human-associated assays tested.Of the ruminant-associated assays, all three (Rum2Bac, BacR and BacCow) satisfied both the quantitative and binary sensitivity criteria, having a range of detection of the ruminant target spanning more than four orders of magnitude, with the lowest concentration of target around the 10 copies per CFU ENT threshold. However, only Rum2Bac and BacR met the quantitative specificity criterion and only BacR fulfilled the binary specificity criterion. As such, BacR was identified as the most effective ruminant-associated assay tested. In addition, although the Avian GFD assay did not meet either the quantitative sensitivity or binary specificity criteria, it did meet the quantitative specificity and binary sensitivity criteria and was thus deemed to have acceptable performance for use on environmental samples.The 45 households from which source and stored water samples were collected had an average household size of 5, with the mother most commonly having completed primary school (Table 3). Nine percent (9%) of households had electricity, 42% owned bicycles, and 76% owned mobile phones. All households had access to a toilet facility, with 47% of households having access to private sanitation, with the remaining sharing their toilet with anywhere between one and five additional households (mean: 2.2). However, only 4% of all facilities were classified as improved sanitation based on the JMP definition; this definition requires that private latrines have a concrete slab [2] that few in our study did.Forty-seven percent (47%) of households self-reported that they owned ruminants, 31% dogs, and 76% chickens. There was variation in the prevalence of the MST molecular markers in the water samples across study households. Avian GFD was detected in 2% of all samples (2 of 90), HF183 in 4% (4 of 90), and BacR in 58% (52 of 90). The BacR MST molecular marker was prevalent and found in the stored and/or source water samples of 91% of households (41 of 45), or 27% of source water samples (12 of 45) and 89% of stored water samples (40 of 45). When detected, log10-transformed copies per 100 mL water sample of Avian GFD were between 2.1 and 6.9, HF183 were between 2.5 and 2.9, and BacR were between 2.1 and 4.6. There were no bivariate associations between the self-reported presence of animals in the compound and the detection of MST markers (see Appendix C).Observed household water sources included borewells (2.2%), streams (2.2%), protected dug wells (8.9%), unprotected dug wells (2.2%), protected springs (73.3%), and unprotected springs (11.1%). Springs are sources where water comes from the subsurface and is accessible at the ground level without any further technology or intervention, whereas wells are dug to groundwater. Protected springs and wells had a concrete lining, whereas unprotected versions did not. For water treatment, 13% of households self-reported that they treat their water regularly by using methods including bottled chlorine, boiling, sieving it through cloth, or using a Lifestraw filter. However, only 4% of households self-reported having treated the stored water from which a sample was taken. There was extensive contamination of both stored and source drinking water with E. coli and enterococci (Figure 3). Ninety-five percent of water samples (93% of source and 98% of stored) had E. coli detected in the 100 mL sample with a median of 33 CFU/100 mL; 85% (75% of source and 95% of stored) had enterococci detected in the 100 mL sample with a median of 11 CFU/100 mL.Our study found evidence of ruminant fecal contamination and enterococci introduced into a household’s drinking water post-collection from the source. When analyzing stored and source water sample pairs matched by household, the BacR molecular marker was detected in stored water but not in source water for 64% of households, with the reverse occurring in only 2% of households. The difference was statistically significant (Table 4, McNemar’s exact test, p < 0.01). Similar analysis using FIB as the dependent variable showed that the stored water samples had significantly higher log10-transformed enterococci concentrations (Figure 3, Wilcoxon matched-pairs, p < 0.01) relative to the source water samples, with median values in the source and stored water samples of 7 and 26 CFU/100 mL, respectively.There was no significant difference in concentrations of E. coli between source and stored water (Figure 3, Wilcoxon matched-pairs, p = 0.25), with median values of 37 and 20 CFU/100 mL respectively. No statistically significant difference was found in the occurrence of HF183 (Table 4, McNemar’s exact, p = 0.5) or Avian GFD (Table 4, McNemar’s exact, p = 0.5) targets between source and stored water samples. Conducting the analyses with only the subset of households with springs as their water source (the most common source) did not change the results (Appendix D).Across all water samples, BacR presence was positively associated with enterococci concentrations (Wilcoxon rank sum, p < 0.01) whereas it was not associated with E. coli concentrations (Wilcoxon rank sum, p = 0.95). Neither E. coli (Wilcoxon rank sum, p = 0.89) nor enterococci (Wilcoxon rank sum, p = 0.48) concentrations were associated with the presence of Avian GFD contamination. However, both E. coli and enterococci concentrations were positively and significantly associated with HF183 presence (Wilcoxon rank sum, p < 0.05 for both).There were three combinations of household and human behavioral factors that resulted in the contamination of clean source water with ruminant feces during household storage. First, if ruminants were present in the household compound, safe water extraction methods were used, and water storage time was long (5 h or more). Second, if ruminants were present in the compound, unsafe water extraction methods were used, and there was no evidence of both soap and water at the household handwashing station. Third, if water storage time was long and there was no evidence of both soap and water at the household handwashing station.Figure 4 illustrates these combinations and provides the consistency score for each. The overall coverage score of 0.91 relates to the fraction of households that have BacR contamination in their stored water supply and have conditions that fulfil at least one of the three combinations (26 of 28 households). In addition, the overall consistency score of 0.92 relates to the fraction of households with conditions that satisfy at least one of the three combinations and have BacR contamination in their stored water supply (26 of 28 households). For more details on score calculations, see Appendix B. A Tosmana diagram that shows the full solution space, the cases in each part of the space, as well as combinations associated with BacR contamination is shown in Figure S2.Microbial contamination was widespread in the water tested in this study. The majority of source and stored water samples collected in this study had E. coli and enterococci detected. This is higher than the WHO recommended levels of 0 CFU/100 mL for drinking water. We found evidence that ruminant fecal contamination was introduced post-collection from the water source. Nearly all stored water samples contained ruminant contamination (88%), whereas only 26% of the source water samples had ruminant feces detected. Ruminant feces can contain a number of zoonotic pathogens including Campylobacter, non-typhoidal Salmonella, Cryptosporidium, and Toxoplasma gondii [56,57,58], thus exposure to ruminant feces could present a health risk. Given that ruminant ownership was so common (~50% of households own a ruminant), and that their feces are used for household building material and fuel for fire in the study area, it is perhaps unsurprising that their feces often contaminate the water. However, exposure to ruminant feces as a transmission pathway for enteric illness is underexplored in the WASH field. Similar results regarding the high prevalence of ruminant contamination has been reported for households in rural and urban/peri-urban informal settlements in Bangladesh [12] and Tanzania [10]. In addition, Barnes et al. [59] showed an association between domestic animal presence/ownership and household drinking water contamination. Additional work should be done to assess the prevalence of zoonotic pathogens in waters contaminated by ruminant feces and how the persistence of the ruminant target varies relative to pathogen persistence in different environmental media (e.g., water and soil).Although human contamination was positively associated with FIB contamination in drinking water collected within our study, human feces appears to be a secondary contributor of FIB contamination relative to ruminant feces. All study households reported access to a latrine. However, only 4% of those toilets fell into the category of “improved”, primarily because the rest lacked a concrete slab (i.e., surface that is easily cleanable) or were shared with multiple households. Despite this, only 4% (4 of 90) of the water samples contained the human-associated marker HF183 at concentrations above our detection limit of 50 copies per 100 mL (assuming a theoretical detection limit of 1 copy of target per qPCR reaction). The maximum concentration of the HF183 target detected in the water samples was 800 copies/100 mL, which, based on the range of concentrations of the HF183 target per culturable enterococci colony in human feces in the validation study, would correspond to between 80 and 800 CFU human fecal ENT per 100 mL of water. We found limited evidence of avian fecal contamination in drinking water (2% of samples) despite the majority of households owning chickens (76%). Prior work in rural Bangladesh, with similar animal ownership, found 10% of households with avian contamination in drinking water, compared to 0% of households with human contamination and 33% of households with ruminant contamination in water [12].fsQCA yielded three distinct combinations of household and behavioral factors that led to ruminant contamination of clean source waters during storage in the home. The existence of three combinations suggests that there is no single way that stored water becomes contaminated with ruminant feces in the study population. The combinations revealed no necessary conditions. That is, none of the causal conditions are individually sufficient to result in contamination. This implies that multiple factors need to be collectively present for ruminant fecal contamination to occur. Ruminant presence in the compound was not a necessary condition for ruminant fecal contamination of a household’s stored water supplies as it was only included in two of the three combinations. Presumably, ruminant feces could be transferred into the household, for example, from a neighbor’s compound or due to widespread use of ruminant feces as building material. Somewhat counterintuitively, the use of ‘safe’ extraction methods in our study population was associated with ruminant fecal contamination of stored water if there were also ruminants in the compound and long water storage time. This suggests that safe extraction methods, defined to be when water is poured from the storage receptacle, may also introduce contamination during decanting, potentially due to biofilms on the storage container wall becoming dislodged or contamination along the rim of the container being washed along. Finally, the lack of both soap and water at the household handwashing station appeared as a factor in two of the three combinations. Evidence of soap served as an indicator for hand washing, thus lack of soap suggests reduced hand washing by the household. Handwashing with soap is especially critical in preventing food and water contamination [7] by ruminants [60], can reduce diarrheal disease risk by between 40% and 65% [61,62], and can protect against exposure to enteric zoonoses found in animal waste [63]. Although good hand hygiene is particularly protective at certain critical times [59], self-reported handwashing rates in this study population were only 20% before food preparation, 27% before eating, 20% before feeding children, 42% after cleaning children, and 76% after using the toilet.The fsQCA methodology employed here offers benefits over average-effects-based analytical techniques (e.g., regression) to identify risk factors of fecal contamination in water. Striving to identify important behaviors or contextual factors that influence contamination transmission with average-effects-based techniques may lead to erroneous inference and misguided intervention design if there are in fact multiple combinations of contextual factors and behaviors that result in contamination. Often the failure of an intervention to produce the hypothesized impact is attributed to the intervention targeting the wrong pathway. However, it may be the case that the intervention successfully disrupts one pathway of contamination but fails to tackle other dominant pathways. No ‘necessary’ factors (i.e., a factor required for a case to have the outcome) were identified in the present study, highlighting the benefits of the fsQCA approach. The fsQCA methodology does not require a priori knowledge of these complex relationships and can identify multiple causal pathways that may lead to an outcome. Figure 4 identifies these pathways without providing insight on the sequence of events, if any, associated with contamination within these pathways.There are several limitations of this work. The sampling scheme of this study means that the source water sample was collected at a later time than when the household collected their stored water, which was sampled. If a source exhibits temporal variation in quality, it could mean that the source water may have been of a different quality when the household visited as compared to when the enumerator visited. Water and fecal samples were also transported to the US for molecular analysis. Nucleic acid concentrations may decay during the transport process, although treatment with RNAlater was done to minimize decay. Nonetheless, since all samples were treated in the same way, there should be no systematic bias that would impact the comparison between households and between stored and source water. In addition, limited variation in values for indicators such as the use of dung in building their houses (in 43 of 45 households) and water treatment methods (43 of 45 households did not treat the tested stored water sample) meant that these indicators had to be excluded from the fsQCA analysis. Therefore, we were not able to evaluate these indicators as risk factors for ruminant contamination in stored water in our study. In addition, the quantitative sensitivity of the Avian GFD assay was very low (orders of magnitude lower than the sensitivity threshold), meaning that high concentrations of avian feces would need to be present in water in order for the target to be detected. Thus, avian contamination may be present in the water but not detected due to the limitations of the assay. Further work to develop a more sensitive avian assay is warranted, given increased concerns around poultry feces management in low-income country settings [56,64].Our study provides evidence that ruminant contamination is widespread in household water supplies, and in many cases, despite safe storage and extraction practices. This highlights an underexplored health risk in the WASH field, given the potential for zoonotic disease transmission. Further work to understand the uses and handling practices of ruminant feces would yield insight to important exposure pathways, where water may just be one of many. This knowledge could inform the expansion of typical WASH interventions [65,66,67] to include safe contact with animals [59] and the safe disposal of animal waste [68,69]. Efforts to reduce exposure to ruminant feces would need to account for the fact that ruminants are also important nutritionally, financially, and culturally [70,71]. Conditions in this study are common throughout sub-Saharan Africa and Southeast Asia, where ruminant feces are used as a fuel or building material [72]. Understanding the sources and pathways of drinking water contamination remains a necessary step in reducing the risk of human exposure to fecal contamination.Our study found evidence of post-supply contamination of drinking water with ruminant feces, highlighting the utility of molecular MST assays for understanding the extent of transmission of species-specific fecal contamination in household environments. Given the number of zoonotic pathogens that can be found in ruminant feces, its presence in drinking water implies a public health risk. Further research to understand the extent of zoonotic pathogen carriage in animals in different environmental contexts is warranted to draw robust public health conclusions from contamination data. Studies to assess the persistence of the molecular targets in different environmental media compared to zoonotic pathogens would also help more precisely define the health risks associated with target detection.fsQCA was used to identify three combinations of causal conditions associated with the introduction of ruminant fecal contamination to household drinking water after collection from a source, with no necessary or sufficient factors being identified. Of particular note was that ruminant presence in the household was not a necessary condition and that safe extraction methods was a causal condition in one contamination pathway. This suggests that ruminant feces are widespread in the study area and methods perceived to be safe are insufficient to prevent contamination. This study represents a novel application of fsQCA and reveals limitations of standard regression techniques for understanding complex phenomena such as the various transmission pathways of fecal contamination in household environments. Additional studies to understand household behaviors and practices related to animal feces will help inform effective and culturally appropriate feces and water management strategies.The following are available online at https://www.mdpi.com/1660-4601/17/2/608/s1. Table S1: Number and types of fecal samples collected, Figure S1: Master curve plots for the Avian GFD, BacR and HF183 assays generated from qPCR runs, Table S2: Methods for MST assays used in this study, Figure S2: Tosmana diagram showing the number of households that have each combination of the causal conditions and their consistencies with the outcome condition.Conceptualization, A.B.B., J.D., A.J.P. and A.H.; Data curation, L.H.; Formal analysis, L.H.; Funding acquisition, A.B.B., J.D., A.J.P. and A.H.; Methodology, L.H., A.B.B., J.D. and A.H.; Project administration, A.J.P., M.W., M.M. and A.H.; Writing—original draft, L.H., A.B.B. and A.H.; Writing—review & editing, L.H., A.B.B., J.D., A.J.P., M.W., M.M. and A.H. All authors have read and agreed to the published version of the manuscript.This research was partially funded by Global Development grant OPPGD759 from the Bill & Melinda Gates Foundation, the Stanford Center for African Studies, and the Stanford Graduate Fellowship.We thank the households who participated in the trial, the fieldworkers who collected the data for the study, the lab technicians who helped with sample processing, and the managers who ensured that everything ran smoothly.The authors declare no conflict of interest.To assess inhibition, a modified ‘spike and dilute’ method was used [46,73]. One fecal composite per animal source type as well as five randomly chosen water samples were processed to test for inhibition for each MST assay. Both the fecal composites and water samples were processed at two different 10-fold dilution levels, and each dilution was spiked with a different concentration of standard. For instance, the water, chicken, duck, dog, and cow samples were processed undiluted as well as at a 1:10 dilution. The undiluted sample was spiked with 104 copies per μL standard and the 1:10 diluted sample was spiked with 103 copies per μL standard.If, after the DNA extraction process, a sample had a DNA concentration in the eluent greater than 100 ng DNA/μL, the DNA concentration in the sample was considered too high to be processed undiluted. In these instances, the two different ten-fold dilution levels instead became 1:10 and 1:100. For the ruminant-specific assays, DNA concentrations in the eluent of the ruminant fecal samples (i.e., cow, goat, and sheep) warranted further dilution to a third (1:1000) dilution level. Thus, the ruminant samples were processed at 1:10, 1:100, and 1:1000 dilutions for the ruminant assays, and spiked with 104, 103 and 102 copies per μL standard respectively. All samples tested for inhibition were processed in duplicate. If the difference in mean CT values between the two dilutions was greater than 2, the more concentrated sample tested was considered uninhibited [46].Calibration of the indicator for Long Storage Time was conducted in the software with the following equation:
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+		where TimeCol is the respondent’s self-reported survey response of how long ago their current household stored water supply was collected.After all conditions, causal and outcome, are scored, a truth table is generated using the Truth Table Algorithm function under the Analyze tab such that cases are aggregated based on the scores of their causal conditions, as shown in Table A1. For ease of inspection, each causal condition is scored by the software in a binary fashion in the truth table even if it is otherwise coded fuzzy in the analysis; i.e., all scores above 0.5 are shown as 1, all scores below 0.5 shown as 0, with no scores of exactly 0.5 permitted. Scores that are not Boolean impact the raw consistency metrics. For example, if there are two households with scores of 1 across all causal conditions as well as the outcome, the consistency score would be 1. However, if these households had differed in the outcome, with one showing contamination and the other not, the consistency score would be 0.5. If both households showed contamination and were identical in all other respects bar having one causal condition that was fuzzy, the consistency score would be close to but not 1.Truth table showing the number of households who have various combinations of the causal conditions chosen.The Venn diagram in Figure A1 helps better visualize the full range of combinations of causal conditions described by the households in this study, as well as the number of cases there are for each combination. However, it does not show the number of cases within each combination of causal conditions that are positive or negative with respect to the outcome.Venn diagram showing the number of households who have various combinations of the causal conditions chosen.Two elements of further input are required to code the outcome variable for each configuration of causal conditions represented by the household data before combinations associated with the outcome condition can be determined. This is because there may be multiple cases that have the same configuration of causal conditions but different outcomes. However, the software requires that each configuration has a definitive outcome, positive or negative, regardless of the variation between cases. The first element of input is the minimum number of cases (households) that are required before a given set of causal conditions in the truth table is included in the process of deriving combinations that are associated with BacR contamination. This was set to 1 in this analysis. The second element of input is the minimum raw consistency score necessary to set the outcome condition for that combination of causal conditions to 1. A widely accepted threshold is 0.8 [54], which was also adopted here. Establishing these thresholds via the Delete and Code function under the Edit tab of the Edit Truth Table window enables the software to compute the various combinations associated with the outcome condition.These inputs allow the analyst to continue with the analysis to determine combinations of causal conditions associated with the outcome. When conducting Standard Analyses (the analysis tool in the software used to compute combinations without placing further constraints on the solution such as minimizing positive cases, negative cases, don’t care cases, and remainders), each causal condition was listed such that ‘they should contribute to BacR when cause is present’ because this is how the coding scheme was set up given their hypothesized effects. (In situations where the hypothesized effect is unknown, the ambiguous option of ‘present or absent’ can be chosen, as can the option of ‘absent’ when the hypothesized effect is associated with the absence of a causal condition.)To assess soap as a proxy measure, sensitivity analyses were conducted, where poverty and a lack of education were added as causal conditions in the fsQCA analysis initially separately and then together. The combinations of causal conditions did not substantively change for any of the situations: When poverty was added independently, it only changed one combination by replacing the presence of ruminants, itself an indicator that is often linked to higher socioeconomic status. When a lack education was added independently, it appeared in a combination with a lack of soap and unsafe extraction methods, suggesting that a lack of education may also be reflected in having fewer resources. Including both a lack of education and poverty resulted in the same combinations as simply including poverty alone. As such, it was not deemed necessary to include separate indicators for poverty and a lack of education in the analysis.There was no statistical association shown from bivariate tests between the self-reported presence of avian species or ruminants in the compound at the time water was collected and the associated MST molecular marker in household stored water samples (p = 1 for Avian-GFD; p = 0.58 for BacR). 31 of the 34 households (91%) that had ruminants in the compound had BacR contamination detected in their stored water sample, whilst 9 of the 11 households (82%) that did not detected similar contamination. On the other hand, 37 of the 39 households that owned poultry (95%) did not have Avian GFD in their stored water sample, whilst all 6 households that did not showed the same contamination. These data are reported in Table A2 and Table A3.Self-reported presence of avian species with detection of Avian GFD molecular marker in stored water.Self-reported presence of ruminants with detection of BacR molecular marker.As shown in Figure A2, the quality of source water as evaluated by FIB metrics varied by source type, with quality broadly worsening in the following order: piped/borehole, spring, well. The order differed mildly depending on whether the water was evaluated for E. coli or enterococci. Given this variation, the same source and stored water analysis was conducted for the subset of households whose source was a spring since springs were the most common water source. However, the result and its significance were unchanged: there were significantly higher levels of enterococci but no E. coli in stored relative to source water.Boxplots of the log10-transformed concentrations of E. coli (left) and Enterococci (right) in household source water samples, stratified by type of source. The midline of the box represents the median of the data, with the upper and lower bounds of the box showing the first and third quartile. The whiskers show the extremes of the data that is within 1.5 times the interquartile range. Any data points outside this range are plotted as outlier circles.Conceptual model of the interconnected factors that are associated with the introduction of ruminant contamination to a household’s stored water supply.Concentrations of MST assay molecular marker copies per culturable ENT in fecal material, which represents the ratio of species-specific bacteria (target copies) to fecal indicator bacteria (CFU ENT). Higher concentrations suggest that species-specific contamination can be detected with less feces in the water sample as measured by ENT. Fecal samples are from chickens, ducks, cows, goats, sheep, dogs, and humans. Humans, ruminants (cows/goats/sheep), and avian species (chicken/ducks) are the target fecal sources for these assays. The human assays tested are humM2, HF183, and bachum, the avian assay tested is avianGFD, and the ruminant assays tested are rum2bac, bacR, and baccow. At the bottom of the molecular marker copy scale, samples that had the MST molecular marker DNQ or ND are plotted. The black line marks the sensitivity threshold of 10 copies per CFU ENT. This would represent the threshold of detection in the qPCR process for samples containing 1 CFU ENT, the smallest unit of contamination above WHO guidelines.Boxplots of the concentrations (CFU/100mL) of E. coli (left) and enterococci (right) in the source and stored water samples. The midline of the box represents the median of the data, with the upper and lower bounds of the box showing the first and third quartile. The whiskers show the extremes of the data that are within 1.5 times the interquartile range. Any data points outside this range are plotted as outlier circles (one outlier for E. coli concentration in source water).Combinations of causal conditions that are associated with the BacR molecular marker being detected in a household’s stored water supply, their consistency scores, and the number of households they explain. Each line type represents one combination; there are three in total: (i) ruminants + safe extraction + long storage time, (ii) ruminants + unsafe extraction + no soap, and (iii) long storage time + no soap. A household’s contamination may be explained by more than one combination.Measurement Table and Summary of Indicators for fsQCA.Sensitivity and specificity of the MST source-specific assays as concluded from the binary analysis, and whether assay is deemed sensitive or specific based on binary and quantitative metrics.Household characteristics (n = 45).MST molecular marker detection in paired source and stored water samples (n = 45 households). Households returning the same result for both samples have concordant pairs, whereas those with only one of their water samples showing contamination have discordant pairs.

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+The aim of this study is to experimentally assess the effects of an intervention program through a video game called “Aislados” for the improvement of subjective well-being, mental health and trait emotional intelligence of a sample of adolescents (n = 187). We used well-established measures with appropriate psychometric properties. The study used a quasi-experimental design of pre-test/post-test repeated measurements with a control group. First, a multivariate analysis of variance (MANOVA) and then descriptive analyses and variance analyses (ANOVAs) were carried out by the adolescents randomly assigned to the experimental and control conditions. Then, a multivariate analysis of covariance (MANCOVA) was performed on the study’s variables as a whole. Descriptive and covariance analyses of the post-test scores were carried out (ANCOVAs post-test, co-varying pre-test scores), in order to demonstrate the impact of the program. The effect size was reckoned (Cohen’s d). The results confirm statistically-significant differences in: Health-Related Quality of life, positive affect and mental health. The study provides an effective intervention tool which has been experimentally validated. The overall results allow for emphasizing the importance of the implementation of programs aimed at encouraging social and emotional learning throughout adolescence as protective resources in fostering emotional and behavioral adjustment in adolescents.The aim of education is the integral development of the personality of the students, promoting cognitive, personal and social competencies. Therefore, schools should not only promote the academic growth of students but also their personal growth [1,2]. Some associations with a global impact (e.g., Collaborative for Academic, Social, and Emotional Learning – CASEL, World Health Organization – WHO) emphasize the importance of social competence and social-emotional well-being in the development of children and adolescents [3].The European Council considers personal and social skills and learning to learn as key competencies for a successful life in society and of equal importance to the other seven key competencies such as digital or multilingual competencies [4]. Research has shown that the promotion of social and emotional skills in educational contexts provides benefits to adolescent students (e.g., [5]), including a critical aspect during the whole period of schooling, such as academic performance [6,7]. Domitrovich et al. [8] have defined social and emotional learning (SEL) as a process through which social-emotional competence develops in five domains: self-awareness, self-management, social awareness, relationships skills, and responsible decision making [1]. The programs which purpose is to develop SEL focus on these five competencies [9]. Weissberg et al. [9] show how SEL also promotes intrapersonal, interpersonal and cognitive competencies for cognitive development.In addition, the WHO defines SEL as a collection of life skills [10] and, therefore, is conceived as a potential protective factor and promoter of mental health [11]. In the same way, SEL programs are one of the most successful interventions to promote the integral and positive development of students [1]. The fundamental purpose of SEL is the promotion of the quality of life and well-being of people [8,12]. Promoting the social and emotional well-being of young people is a determining factor in their positive development, which allows them to achieve positive results in school, work and in life in general [1].The evaluation of the effectiveness of the SEL programs shows positive results on academic achievement of the students, on mental health, on psychological and social adjustment and on positive behaviors in health [1,3,8,9,13,14]. Taylor et al. [15] conclude that participants obtained better results than the control group on socio-emotional skills and indicators of psychological well-being. Thesefindings show that programs based on SEL have a similar impact on children and adolescents [8]. For the aim of this study, it must be pointed out that mental health problems in secondary school are considered as serious public health issues. At that age, mental problems can limit student’s abilities to develop positive relationships to their environment and, in this way, can also limit their academic and social performance. In this regard, some studies prove that SEL key competencies can prevent such student difficulties [16,17].Among the different strategies that can be used to introduce and teach social emotional learning skills to kids and young people, games are a good option to create fun environments to engage them in learning activities that help kids become more self-aware, develop positive relationships, show empathy towards others, manage emotions, use self-control, resolve conflicts, and make positive decision [18]. Insofar as most today games for kids are electronic games, it is also a good strategy to deploy that game strategies using software technologies. Video games are one of the most popular recreational activities among young people nowadays [19]. Exploring the boundaries between use and abuse of video games, it can be found studies that point out the negative and positive psychological impact of video games. The negative impact of video games on the psychological well-being and social life of gamers [20] has been proven by studies that associate poor quality interpersonal relationships, dissatisfaction with life and loneliness with the use and abuse of video games [21,22]. Other studies show correlations between video game abuse and emotional and behavioral problems in young people [23] including poor sleep [24], depression and anxiety [25]. In the other hand, this negative impact of video games has been questioned in recent studies [26,27,28] that are focused on the potential of video games to improve cognitive and social learning. In this regard, some data indicates that the use of video games in gamification strategies can positively affect learning and teaching processes [29,30,31,32] and cognitive, motivational, emotional and social processes [33]. Those results show how educational technologies can offer a new path for the development of emotional skills that are, indeed, a new challenge for traditional learning strategies. In this sense, video games and computer simulations based on physical activity are nowadays widely used as innovative strategies for training several sports. For instance, there are some evidences that prove how video games based on physical activity have positive effects on self-appreciation or well-being [34], as well as on general mood [35]. Those computational games are becoming a new sport discipline by itself, becoming a field of study into sports psychology, and generating new ideas for the treatment of psychological problems. For instance, computer videogames, smartphone applications and more developed similar tools, as immersive virtual reality environments, are being studied nowadays as therapeutic resources for emotional problems related to anxiety [36]. The development of such computational environments of augmented reality could also promote improvements on important academic areas for adolescents as writing [37], math [38] or language learning [39].Focusing on emotional intelligence (EI) and well-being, the use of video games among adolescents, like popular Pokemon Go, has been confirmed as a tool for the enhancement in selective attention, concentration and sociability [21] and, in this way, improving cognitive performance and EI. Other studies conclude that good strategies involving video games and computer simulations can improve life satisfaction and prosocial behavior reducing the probability of suffering emotional problem [40,41]. Consequently, it has been previously justified the aim of this study, that is to say, the analysis of the possible benefits of the use of video games by children and adolescents in more detail, specifically in the context of educational strategies for improving EI, subjective well-being, health and life satisfaction.There are examples of successfully application of video games educational strategies for the improvement of socioemotional skills. For instance, the application of the video game “Spock” show how the emotional intelligence capacity [42] and the psychosocial adjustment [43] have been improved on experimental groups of adolescents. In addition, D’Amico [44] has shown the efficacy of the training performed with that kind of software improving performance in emotional tasks in a group of children with ages ranging from 8–12.The current study presents an intervention program called “Aislados” that considers the theoretical assumptions of Social and Emotional Learning (SEL) by using video games as an educational tool. “Aislados” is an educational program for middle and high school students developed in 2016 by the Interdisciplinary Service of Attention to Drug Dependencies (in Spanish, SIAD) and founded by National Spanish Plan against Drug addictions (http://www.aislados.es/ financed by the Government Delegation for the National Plan on Drugs). It has been designed as a protective resource for adolescents by means of improving their psychological well-being and empowering them to avoid young risk behaviors related to addictions, violence or emotional disorders. This strategy has been recently proven by the evidences that show how emotional indicators like self-esteem, quality of interpersonal relationships, control of life events, and management of negative emotions, can lead to depression and social and educational impairment, becoming an important risk factor for substance misuse [45,46]. Following innovative gamification strategies, as video games and role-playing games, they designed a framework for teaching social, cognitive and emotional skills (life-skills). Both games, video game and role-playing game, are based in the same principles and educational structure and has to be completed by educational sessions driven by teachers. Video game and role-game are educational strategies very suitable for SEL interventions as stated by Weissberg et al. [9] when they point out how important is to apply and improve motivational strategies for those interventions. “Aislados” video game consists of a set of virtual characters deployed in an imaginary boat traveling to some newly discovered islands (a descriptive video can be seen at https://www.youtube.com/watch?v=I6N41WREYbY&list=PLLrCXpyb6EFLnQWoDScEc33VsUqPE-5kx&index=3 (Spanish with English subtitles available through YouTube translation). The player interacts with those characters getting involved in conversations to get information for task achievement or solving riddles that are included in the video game. Thus, the “Aislados” video game provides a virtual environment where the main goal of students is to reach a full understanding of the character’s personalities and emotional states, developing positive affect towards characters and deploying emotional intelligence to understand the problems and situations involved at every conversation or interaction. Very interestingly, those activities are being held individually by students, in a way that makes more interactions possible and a more flexible environment for each student to develop their own emotional strategies to solve game tasks, which is an opportunity for the personalization of the learning process of this type of socio-emotional competencies. The intervention program is complemented through explicit instruction (sessions) by teachers for full understanding of emotional situations and decisions taken by players (students) during the game. Thus, the idea that SEL-based programs should encourage activities both inside and outside the classroom, including reaching the community, is emphasized [1]. “Aislados” is focused on improving social competence and social-emotional well-being in adolescents and young people, the nuclear objectives of the associations that promote SEL. In this regard, an indicator of social-emotional well-being is subjective well-being (SWB): the cognitive component (satisfaction with life) and the affective component (positive and negative affect) [47,48]. The cognitive component of SWB (CWB) is based on beliefs and judgments about one’s life [49]. While the affective component of well-being (AWB) implies an individual hedonistic balance, that is, how often do people experience positive and negative emotions [48].Currently psychological research is interested in the study of how positive psychological variables affect personal development [50]; this is the theoretical framework named as positive psychology [51]. Among the positive psychological variables, one of the most scientifically supported is emotional intelligence [52,53]. Despite the controversies surrounding the concept of emotional intelligence [54] it can be defined as the set of individual differences in the identification, expression, use, comprehension and regulation of one’s own emotions and emotions [55]. Emotional intelligence has also close relationships with the SWB and physical and mental health variables [56,57]. Specifically, emotional intelligence as a trait has the highest positive correlations with SWB [58]. These cited studies prove that an efficient management of the components of emotional intelligence can promote positive emotional states and a reduction of negative emotional states, promoting a greater SWB [57].In sum, the aim of research is to assess the effects of this intervention program for the improvement of SWB, mental health and trait emotional intelligence among a sample of Spanish adolescents of middle and high school age. We adopted a quantitative approach to explore the following specific hypotheses regarding the impact of “Aislados” Program on Spanish adolescents: (1) It will enhance the SWB; (2) It will increase mental health (MH); (3) It will increase trait EI (TEI).The sample has been made up of 187 adolescents, aged 12 to 17 (M = 13.82 SD = 1.62). A non-probabilistic sampling was used, but subjects are assigned at random to the experimental (n = 97) and control (n = 90) condition in the pre-test stage. The data were provided by middle and high school students (53% girls). All students took part voluntarily in this study. The intervention was a scheduled activity during their timetable. This study was carried out in accordance with the Declaration of Helsinki and ethical guidelines and was approved by the Research Ethics Committee of the UNED. Participants’ parents gave informed written consent and adolescents gave verbal assent. Moreover, special permissions where given by the school management team.Parental consent was used as the main inclusion criterion. Some students were excluded according to the following exclusion criteria: (a) students previously removed from school for disciplinary reasons; (b) students with special educational needs related to intellectual disability; and (c) students not attending at least 75% of the intervention programme sessions. In this study, we used well-established measures with appropriate psychometric properties (see Table 1).This self-report version contains 10 items to assess subjective Health-Related Quality of Life (HRQL) and well-being; it provides an index of global HRQoL covering physical, psychological and social facets. It is related to the cognitive component of well-being. The questionnaire can be completed by children and adolescents aged from 8 to 18 years. Questions are on 5-point Likert scales from “never” to “always” or from “not at all” to “extremely”. SWLS is a short 5-item self-report questionnaire where people judge whether their life is satisfying on a 7-point rating scale, from 1 = strongly disagree to 7 = strongly agree. The scale provides a global measure of life satisfaction. It is related to the cognitive component of well-being.PANAS is a self- reported adjective checklist designed for the assessment of 20 different feelings and emotions. It contains two subscales with ten items each, representing two constructs: positive affect (i.e., active, attention, determined, excited, inspired, interested…) and negative affect (i.e., afraid, guilty, hostile, irritable, upset). It is related to the affective component of well-being. Participants used a 5-point scale ranging from 1 = ‘‘very slightly or not at all’’ to 5 = ‘‘extremely’’.MH-5 is one of the subscales of the SF-36 Health Questionnaire. MH-5 is a short 5-item self-report questionnaire that assesses general mental health, specifically depressive and anxious symptomatology in the past month. It is related to the cognitive component of well-being. Participants respond to a 6-point rating scale, ranging from 1 (always) to 6 (never). It is a self-report inventory designed to measure global trait emotional intelligence which contains 30 items, with Likert scale response options ranging from (1) “Completely disagree” to (7) “Completely agree”. The measure provides a total score which is obtained by adding up the 30 items. The study followed a quasi-experimental design of repeated measures (pre-test and post-test) including a control group, where following variables were assessed: Health-Related Quality of Life (KIDSCREEN), Satisfaction with Life (SWLS), Positive Affect (PA) and Negative Affect (NA), Mental Health (MH), Trait Emotional Intelligence (TEI). Students were requested to complete anonymously the measures mentioned before. All participants were assured that the data would be kept confidential and would be used for research purposes only. Specifically, the participants of the experimental group were informed of the purpose of the investigation.At first, the tests were applied to the experimental and control groups. Subsequently, the intervention program was implemented in experimental groups during the school day and within school schedule. In the following academic year, after the evaluation of the effects of the program, the control group participated in the program in the same way as experimental group; within the Tutorial Action Plan of the Guidance Department, whereby activities usually focus on social skills and guidance, personal, academic and professional. Specifically, the intervention consisted of 28 h-long sessions, with duration of 55 min each, carried out weekly during a school year. The sessions were carried out during the tutoring hour in secondary education (weekly timetable). The program was implemented by secondary teachers who voluntarily decided to participate in “Aislados” training. After the intervention, in the post-test stage, pretest measures were administered again to the experimental and control groups. Control groups received the same intervention after the study.Teachers received official training supported by the Department of Education through a 10-h workshop about the implementation of the program. In addition, weekly coordination meetings were held to agree on the development of each of the sessions in class, as well as the explanation of the instructions of the video game to the students (during the tutorial coordination time).The video game “Aislados” is inspired by the four elements that facilitate the implementation of programs according to The Collaborative for Academic, Social, and Emotional Learning (CASEL): (1) Sequenced (connected and coordinated activities to foster skills development); (2) Active (active forms of learning to help students master new skills); (3) Focused (containing a component that emphasizes developing social and emotional skills); (4) Explicit (targeting specific social and emotional skills) [7].The “Aislados” video game includes interactive activities that aim to improve socio-emotional skills. The video game presents hypothetical situations that require the implementation of intrapersonal and interpersonal competencies. Students have to decide which answer alternative is most appropriate for the situation. Its primary objective is to improve teenagers’ emotional intelligence skills such as self-esteem, assertiveness and decision making, in order to manage their social life improving health and well-being and avoiding addictions and violence. Program sessions are detailed in Table 2.First, a multivariate analysis of variance (MANOVA) was performed with total pretest scores from the variables included in the study in order to confirm the possible pretest difference in the variables, as a whole, between experimental group participants and control group participants. Second, in order to determine the program’s effect, descriptive and variance analyses (ANOVAs) were carried out with each one of the scores obtained for the instruments used during the pretest phase. Third, having confirmed the homogeneity of the two groups a priori, and in order to determine whether the change was significantly different in experimental group versus control group participants, a multivariate analysis of covariance (MANCOVA) was performed on the study’s variables as a whole. Besides, descriptive analyses and analyses of covariance were performed on posttest scores (posttest ANCOVAs co-varying for pretest scores), in order to analyze the impact of the program for every variable of the study. Lastly, the effect size was analyzed (Cohen’s d) (small < 0.50; moderate 0.50–0.79; large ≥ 0.80) [67].Results obtained in the pretest or basal evaluations are first presented, followed by the results for evaluating the impact of the “Aislados” Program in the variables studied. The pretest MANOVA results did not reveal statistically significant differences between the groups prior to the intervention, Wilks’ Lambda, Λ = 0.472, F (5182) = 0.742, p = 0.241, with a small effect size (η2 = 0.088, r = 0.10).Results from the ANOVAs in the pretest phase (see Table 3) showed that before initiating the “Aislados” Program there were no statistically significant differences between experimental and control groups in any of the variables studied.Results from the pretest-posttest MANCOVA revealed significant differences between the two conditions, Wilks’ Lambda, Λ = 1.414, F (5, 182) = 4.373, p = 0.004, with an average effect size (η2 = 0.348, r = 0.30). Analyses of covariance (ANCOVAs) were subsequently performed on the pretest-posttest scores in each one of the variables in the experimental and control groups. The results are shown in Table 3. As it can be seen, the results from the posttest ANCOVAs (co-varying the pretest scores) showed that participants in the experimental group significantly increased scores in Health-Related Quality of Life, Positive Affect and Mental Health. In addition, a small effect size was found for Health-Related Quality of Life (d = 0.22), Positive Affect (d = 0.38) and Mental Health (d = 0.29).The present study analyses the effects of video game intervention program called “Aislados” for the improvement of SWB, mental health and trait emotional intelligence among a sample of Spanish adolescents of middle and high school age. There is a growing body of literature on SEL intervention programs; these studies provide evidence that SEL competencies can be beneficial to students, whether in or out of school [68]. However, there is limited evidence about the impact of intervention programs by using video game and develop this kind of competencies in learning environments among adolescents and young people.Results showed statistically significant differences between adolescents that received the intervention compared to those that did not participate in the program. Differences between both groups refer to some variables that were assessed. Then, the findings show that “Aislados” produced improvements in experimental group participants in terms of the following variables: (1) a significant increase in health-related quality of life, related to the cognitive component of SWB (CWB); (2) a significant increase in positive affect, related to the affective component of well-being (AWB); (3) a significant increase in mental health; (4) There are no significant improvements in trait emotional intelligence.First, these results support the effectiveness of the “Aislados” program in improving of some SWB components, partially confirming hypothesis 1. The results are consistent with those found in other studies which have shown efficacy of SEL programs to improve SWB in children and adolescents [1,3,5,15]. These findings provide empirical evidence that reinforce the fundamental purpose of the SEL in the promotion of the quality of life and well-being of people [8,12]. A possible explanation for these results may be that the training of socio-emotional skills is a necessary factor to improve SWB due to its benefits in psychosocial adjustment [15]. Furthermore, the results confirm an improvement in positive affectivity, while the program has not had a positive impact on the reduction of negative affectivity. The “Aislados” program is aimed at improving social and emotional skills understood as protective resources, but reducing negative factors is not a specific aim of this program. In fact, positive and negative affect are independent dimensions; then, the reduction of NA does not depend on the increase of PA [69,70]. In the same way, these positive results in SWB are in line with others found in similar studies using video games [34,41]. A possible reason of these results is the inclusion of activities which are varied, attractive and contextualized to the educational stage it is aimed for in the “Aislados” videogame. Last, we believe that group activities and exchange among participant students may have a very positive influence in the results. Second, the results confirm hypothesis 2 and reveal that the “Aislados” program would improve participants’ mental health (MH). These findings are similar to those found in various meta-analysis and research studies that show improvements in mental health, as well as the reduction of emotional problems through the implementation of SEL-based programs [1,8,9]. From our point of view it is likely that the subjective perception of mental health is a factor related to SWB and the improvement of certain emotional problems and, therefore, it is logical to think that both variables can be susceptible to improvement through this type of interventions.Finally, the results fail to confirm hypothesis 3, which stated that the “Aislados” program would improve participants’ trait EI (TEI). The data do not match that obtained in other studies finding that EI increases when students participate in a video game [40,42]. These results can be explained by the characteristics of the program, because it does not specifically aim to the development of EI, although it includes tasks and sessions about this matter. However, the “Aislados” video game requires that the players can interpret the emotions of the different characters in the situations to which they are exposed. In this sense, Teique-ASF, is a short version that offers a global score and, therefore, does not allow assessing the different dimensions of the IE independently; thus, the understanding of emotions has not been able to be evaluated accurately.It is important to point out some research limitations; first, regarding the generalizability of the results, obtained in a specific sample of secondary students from Spain. Furthermore, future studies should consider involving university students. Also, the study could be replicated in international contexts. In sum, although preliminary but promising, further research with the “Aislados” program is required to replicate and extend these findings and to test its application with larger and more diverse samples of students. A limitation of the present study refers to the critique of the heterogeneity of interventions that claim to be based on SEL and the possible comparison of results [71]. This means that research to promote the efficacy of SEL should be interpreted with caution due to the differences between them. However, our results confirm that through the “Aislados” video game based on SEL the quality of life, positive affect and mental health (crucial aspects in SEL) of the participating students have been improved.In addition, it is advisable to carry out a long-term follow-up evaluation in order to examine whether the “Aislados” program effects were maintained over time [13,72].Despite of limitations, the results show that the program produced a positive effect, promoting an increase in SWB and providing benefits in the quality of life related to health, positive affect and mental health in adolescents. Regarding the future lines of research, it would be convenient to evaluate the effect of “Aislados” on other variables such as socio-educational adaptation, social competence, interpersonal relationships or academic performance. For future studies, it would be necessary to examine the Aislados program’s effects on health-related quality of life (HRQOL) in line with other findings related to internet addiction and other online activities [73].Likewise, it would be advisable to consider the possibility of investigating the influence of socio-emotional competencies and the psychological characteristics of the teachers who apply the intervention program.In view of the results, we want to highlight the importance of implementing programs during adolescence and youth to promote emotional and behavioral adjustment to improve both personal growth and well well-being. Those results can also improve academic performance and prevent/reduce of risky personal behaviors and act as protective resources for coping daily demands. Those are conclusions related to the significant increase of SWB, mental health and trait emotional intelligence that has been proved by the analytical study.Taken together, the findings reported in this study mainly support the importance of implementing programs to promote crucial social and personal competencies in the citizens of the future. Education administrators need to apply innovative strategies for teaching those new competencies related to social and emotional skills. In this regard, “Aislados” video game and its related intervention program have been proved as an effective educational strategy for that purpose. This educational program has been implemented in several educational activities in and out of school and is currently implemented in two countries Spain and Dominican Republic in the context of educational projects. Empirical evaluations of these experiences are being held to a better understanding on how this can help students belonging to different cultural contexts to develop skills related to SEL and to prevent health problems.Conceptualization, J.C., L.L. and R.F.; Formal analysis, J.C.; Investigation, J.C., L.L. and R.F.; Methodology, J.C. and L.L.; Supervision, J.C.; Writing—original draft, J.C., L.L. and R.F.; Writing—review & editing, J.C., L.L. and R.F. All authors have read and agreed to the published version of the manuscript.This research received no external funding.“Aislados” is a program designed by the Interdisciplinary Service for Attention to Drug Addiction, is part of the National Drug Plan Program and has been funded by the Ministry of Health, Consumption and Social Welfare of Spain.The authors declare no conflict of interest.Reliability evidences.Note. α = Cronbach’s Alpha; CR = Composite reliability, AVE = Average Variance Extracted; Ω = McDonald’s Omega index.Sessions Schedule.Pretest and posttest measures for experimental and control groups.Note. (1) HRQL: Health-Related Quality of Life; SWL: Satisfaction with Life; PA: Positive Affect; NA: Negative Affect; MH: Mental Health; TEI: Trait Emotional Intelligence; (2) p= p-value; (3) d = Cohen´s effect size. (4) Experimental group: n = 97, Control group: n = 90.

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+Straining is an attenuated form of mobbing, in which the continuity of vexatious actions is not driven by a discriminatory intent. With the objective of testing the possible moderating role of personality in the relationship between perceptions about straining at work and individual consequences, a correlational design research involved 374 healthcare workers (HCWs) from two Italian hospitals. The following questionnaires were administered: (1) Short Negative Acts Questionnaire (S-NAQ), to assess discriminative actions at work); (2) the Italian version of the Big Five Inventory (BFI-10 scale), to assess personality factors; (3) Occupational Stress Indicator (OSI), to measure psychological and physical health. Regression analysis and Structural Equation Models (SEM) were computed in order to test the relationships between variables. Perceived straining showed significant correlations with both psychological and physical health. Conscientiousness was inversely proportional to work-related bullying (WB), as agreeableness was to personal bullying (PB). Emotional stability was negatively correlated with all the three component scales of S-NAQ: WB, PB, and social bullying. The results seem to confirm that straining perceptions especially elicit, through emotional stability, psychological consequences. As regards the role of emotional stability in risk perceptions, it seems management has to pay thorough attention to personal factors in organizational perceptions and to straining actions.Changes in the labor market, evolution of production processes, new technologies, and competitiveness on a global scale have significantly transformed the work environment and demands on workers [1,2]. Some of these transformations may be associated with negative consequences on the psychophysical health of workers [3].Literature on the dysfunctions of work organizations and their subsequent degenerative manifestations is huge, and it is therefore difficult to find a way amongst clearly vexatious phenomena such as mobbing or bullying and stress situations that are rather related to strategic, environmental, or relational conditions [4].Judicial references [5] as well as literature references [6,7] seem to clearly indicate the need to pay attention to a series of work situations that are detrimental to the dignity of workers (demotion, de-skilling, isolation, degenerated conflicts, etc.) [8] and that are currently classified as straining and not attributable to other degenerative phenomena.Workplace bullying is the systematic, repetitive, and intended undesirable behavior of one employee or group of employees targeting another employee or group of employees. Such behavior might consist of public humiliation and condemnation, social segregation, verbal exploitation, intimidation, inaccurate allegations, ignoring someone for a long period of time, and repeated reminders of someone’s errors. Workplace bullying is also referred to as abuse in the workplace, mobbing, harassment, and mistreatment. Often, bullying is a reflection of a systemic malfunction of a given institution rather than of direct personal animosities. Considering the spread of the phenomenon and the adverse effects it generates for both victim employees and employer, research on workplace bullying is thriving [9,10,11].The focus of institutions and the scientific community on occupational health and safety is progressively increasing, leading to a continuous regulatory evolution and the development of good practices in safety and prevention, with the aim of reducing costs for businesses and the society.Within this frame, this study aimed to explore the impact that perceptions of being a victim of straining actions at work have on individual consequences and the role of personality in the interpretation of negative actions and in its impact on a person.The term straining derives from the verb “to strain” which means “to become stretched, to experience pressure, or to make something do or experience this” and refers to a phenomenon of both psychological and legal value, mainly resulting from an organizational conflict [12]. Straining is a psychological condition halfway between mobbing and simple occupational stress [10]: it is in fact a type of “forced” stress, i.e., higher than that related to the nature of work and targeting a victim (or a group of victims) in an intentional and discriminatory way, so as to cause a permanent worsening of the working condition of the worker, even before impacting his/her psychophysical health [13,14].Straining is an attenuated form of mobbing, in which the continuity of vexatious actions, deliberately imposed by the hierarchical superior, does not show a discriminatory intent [12]. The interest in straining stems from the need to give a precise name and a specific compensation profile to situations of work discomfort, which nevertheless risk being unfairly bypassed as they do not fall within the definition of mobbing [12].For a conduct to be defined as straining, even a single action is sufficient, provided its effects are long-lasting, as in the case of demotion or relocation [14,15,16,17].The victim of straining is at a disadvantage compared to the strainer and must have suffered at least one negative action that has an effect at the occupational level in the long term and in a constant manner [18,19].In addition to the affinities with mobbing, the term straining is also very close to the verb “to stress”: in a situation of straining, the aggressor will systematically tend to make his/her victim fall into a specific condition of stress; in this case, the type of stress could be defined as higher than the stress of work and of normal organizational interactions [20,21].Therefore, and as initially said, straining, which according to some interpretations would be placed halfway between occupational stress and mobbing, in some situations becomes a prodromal phenomenon of mobbing [18,22]. When we talk about straining, we can distinguish different protagonists: as in mobbing, there are actors, victims, and spectators [13].In the literature, overall, straining is associated both with forms of occupational stress due to poor work organization and with forms of forced stress resulting from discriminatory acts [23,24,25,26].Numerous papers have sought to investigate organizational and role factors that are related to adverse health outcomes and other occupational outcomes [27,28,29,30]. Part of the literature has focused instead on individual variables and personality traits in order to understand if and how the worker’s personality could affect the perceived negative actions and the impact these have on well-being [31,32,33,34,35,36,37,38].Some studies, on the other hand, have focused on the exploration of personality characteristics associated with the role of victim or mobbing agent [31], such as, for instance, personality disorders: paranoid, narcissistic, borderline traits would be more likely associated with the mobber profile; vice versa, profiles of whining, sad, rigid, prickly personality would be more frequently associated with people who perceive themselves as victims of mobbing or straining [20,39,40].Overall, the contribution of mobbing researches does not seem to clarify the personality differences between victims and non-victims [41]. In fact, if on the one hand some personality traits (anxiety, depression, somatization, etc.) are more frequently found in victims of mobbing [36,38,42,43,44,45], other studies show a rather limited role of personality characteristics in situations of conflict at work [29,30,46,47,48].As far as straining is concerned, some indications point out that it can have strong negative effects on the victim’s personality and, more specifically, on conscientiousness, friendliness, and open-mindedness [38]. The victim’s personality traits, therefore, could represent the outcomes of negative actions perceived at work rather than the causes of the harassment suffered [49,50,51].Although some studies have focused on the contribution and role of personality factors in relation to mobbing actions’ effects on health consequences, very few researches have explored the effects of straining, mediated through personality, on HCWs.Healthcare works (HCWs) are one of the categories of workers that are most at risk of work-related stress [52]. According to the survey conducted by the European General Practice Research Network (2019) on a group of 100,000 doctors operating in 12 countries, Italian doctors showed stress rates (43%) almost twice as high as the average stress rate of their European colleagues (22%).The Medscape Lifestyle Report, produced by the Medscape National Physician Burnout, Depression & Suicide [53] scientific portal, focused primarily on burnout and depressive symptoms and on how they affect the activity of HCWs and their approach to the patient. In this report, 15,000 U.S. white coats from 29 different specializations were interviewed, and 50% stated that burnout significantly affects the quality of care offered to patients.This is the case of “hostile or sporadic discriminatory actions, lacking the continuity requirement, and exerting effects that are continuous in time”. Among these: “groundless deprivation of work tools; assignment of tasks that are not compatible with the personal condition of the worker; unjustified displacement to a distressing site; underestimation of the work delivered by the worker”.Reviewing the literature, on the one hand there is a definite need to more accurately investigate the effect of straining actions (in terms of duration and intensity) on the psychophysical health of workers; on the other, the need to test the role of personality factors in the interpretation of negative actions and in its impact on the individual [41].Straining is an attenuated form of mobbing that does not show continuity of vexatious actions. However, actions not only are stressful but also lead to enduring and constant consequences that may indeed cause serious psychosomatic, psychophysical, or psychic disorders to the worker. Straining intentionally targets one or more people in a discriminatory way, and the victim suffers at least one action exerting a negative effect on his/her work environment. The worker, in a constantly inferior position in relation to the strainer, is subject to hostile actions, though limited in number and distant in time (i.e., not tout court compliant with mobbing parameters), that produce a negative, constant, and permanent change of the work situation and may likely affect the right to health, as stated by law. Such “stressful” situations can give rise to a condition which, due to its characteristics, severity, personal or professional frustration, or other specific circumstances, can presumably lead to damage, i.e., straining, even without proof of a precise persecutory aim [12].When compared with mobbing, straining may result from even a single discriminatory action when the effect is permanent and existing (absence of systematicity)—whereas mobbing requires discriminatory actions to occur at least a few times a month for at least six months—and from a single type of action (absence of variability)—whereas mobbing requires at least two categories of hostile actions of the Leymann Inventory of Psychological Terrorism (LIPT) to occur. Therefore, mobbing creates a situation of conflict due to persecution, while straining generates a situation of forced stress due to discrimination [12].Taking previous studies as a reference [42,54,55] and highlighting the link between straining and mobbing as the occurrence of negative actions causing devastating consequences for the employees, we decided to test the potential mediation effect of personality on the relationship between perception of straining at work and consequences in terms of health (physical and psychological) in a sample of HCWs.Moreover, referring to literature results [54,56,57,58], this paper aims to investigate the role of some demographic variables (gender, age, marital status, schooling) and organizational variables (structure, area, position) in the emergence of a discriminatory conduct and its consequences.Starting from the abovementioned observations, this research aims to verify the impact that straining actions have on the psychophysical health of workers and the role of personality in the interpretation of negative actions and in its impact on the psychophysical health of an individual.In this vein, we designed a correlational study with a sample of HCWs to measure the following variables: straining perceptions and personality and individual consequences (psychological and physical). For the personality structure, we referred to the Big Five model [59,60] that identifies five principal personality factors (openness, neuroticism, extraversion, agreeableness, conscientiousness) and successfully used it to explore the impact of personality on behaviors, dispositions, and attitudes in different contexts [61,62,63].Extending the literature indications to the relationship between Big Five personality traits and behaviors at work [55,64,65,66], as well as to the effect of negative actions on health and personality [42,54], we designed a research model (see Figure 1) intended to verify the following hypotheses (Hp): Personality traits have an effect on individual consequences (Hp1); Since openness (Hp1a) and agreeableness (Hp1b) are expected to be positively related to individual consequences, extraversion (Hp1c), conscientiousness (Hp1d), and emotional stability (Hp1e) are negatively related to individual consequences (Hp1b); Negative act perceptions (personal bullying, social and work-related bullying) are positively related to individual consequences (Hp2a), while straining duration is negatively related to individual consequences (Hp2b).More specifically, we wanted to test the hypothesis that personality has a mediation role in the relationship between perceptions of straining at work and individual consequences (Hp3).Finally, we wanted to test the effect of demographical and job factors on S-NAQ, personality, and individual consequences (Hp4) (see Figure 1).This research is part of a project aimed at evaluating organizational stressors and was commissioned by the peer departments of two public hospitals, co-partners of the project.In this study, 416 (100%) HCWs of the two hospitals were invited by the management to complete a questionnaire during working hours, after attending a brief training about stress at work; 10% (n = 42) of them refused to participate in the survey, which, therefore, was administered to 374 workers (response rate 90%). Workers were invited by the researcher to participate on a voluntary basis and were informed about the aim of the study. All participants signed an informed consent form before taking part in the study.Respondents were asked not to mention their name or the name of their organization anywhere in the questionnaire, in order to ensure privacy and anonymity. Data were collected in November 2018 in one hospital and in March 2019 in the other. The Internal Review Board (IRB) of the Department of Educational Sciences—University of Enna, Italy, approved the research (23/11/2018). All the data were processed according to the EU General Data Protection Regulation (GDPR).Of the 374 HCWs, 55% (n = 207) were females, and 45% (n = 167) were males. Table 1 and Table 2 highlight the main sample and sub-samples characteristics. Age ranges: 51–60 (31%), 41–50 (24%), 31–40 (23%), <30 years (12%), and >60 (9%); 43% (n = 160) of HCWs had a degree; 56% (n = 210) of HCWs were married, and 26% (n = 96) were single; 65% (n = 243) of HCWs had children; 49% (n = 184) of HCWs were nurses, and 45% (n = 169) were physicians. The mean length of service was 18.9 ± 12.1 years; 81% (n = 302) of the participants declared to have a permanent contract, and more than half of them 74% (n = 276) were on shift work, with an approximate daily service of 7 h (7.1 ± 1.3 h).Big Five Inventory—Italian Short Version (BFI-10) [67]. Personality was measured with a total of 10 items rated on a response scale ranging from 1 (completely disagree) to 5 (fully agree). Dimensions of the Italian BFI-10 are measured with 2 items each: agreeableness (AGR), conscientiousness (COS), emotional stability (EMS), extroversion (EXT), openness (OPEN). We re-phrased some items to reflect direct statements. An example is “Tends to find fault with others and does a thorough job”. Cronbach’s alpha = 0.85.Short Negative Actions Questionnaire (S-NAQ)—Italian Version [68,69]. The S-NAQ is one of the most widely used instruments to evaluate any form of negative behavior [30,31,32,33,34,35,36,37,38,39,40,41]. All items in the NAQ-R scale are developed in behavioral terms, with no reference to bullying or harassment. The total score was intended as a measure of the power of the perceived straining. The number of suffered discriminatory actions was measured with a total of 9 items with a three-factor structure, namely, work-related bullying (WB), personal bullying (PB), and social bullyng (SB), rated on a 5-point response scale ranging from 1 (never) to 5 (always). Examples are, “They raised their voice” or “He was the target of instinctive rage attacks, and they have constantly criticized his work and his commitment”. Cronbach’s alpha = 0.91.The perceived duration of the negative actions was intended as a measure of the straining duration and was assessed with 1 item, rated on a 9-point response scale ranging from 1 (never) to 9 (for over 5 years).Occupational Stress Indicator—Italian Version [70,71]. Psychological consequences were assessed with the PSYT sub-scale of the Individual Consequences of Stress dimension of the Occupational Stress Indicator (OSI); 18 items were rated on a 6-point response scale ranging from 1 (completely false) to 6 (absolutely true). Examples of PSYT items are, “During the day, there are moments when you feel worried, upset, useful, confident”. We re-phrased some items to reflect direct statements. Cronbach’s alpha = 0.77.Physical consequences were assessed with the PHIT sub-scale of the Individual Consequences of Stress dimension of the OSI; 18 items were rated on a 6-point response scale ranging from 1 (completely false) to 6 (absolutely true). Examples of PHIT items are, “Did you notice any symptoms over the last 6 months, such as lack of appetite, headache, or noise?”. The response scale ranged from 1 (hardly ever) to 6 (almost always). Cronbach’s alpha = 0.92.Socio-Demographic Variables. Participants were asked to provide information on socio-demographic characteristics, such as gender, age, school grade, education, marital status, and work details, including type of contract (such as long-term or fixed-term contract), working hours (full time or part-time), work position, shift work, seniority, hours of service per day.In order to verify the hypotheses, correlation and regression analyses with SPSS 21.0 were conducted. Moreover, the research intended to test the hypothesis that personality has a mediation role in the relationship between perceptions about straining at work and individual consequences, using structural equation modeling analysis. Confirmatory factor analysis (CFA) with SEM via maximum likelihood estimation methods (along with the indicators’ covariance matrix) were used to evaluate the measurement and structural models concerning study variables and their associations, through AMOS 22 statistical package. With regard to the models’ goodness-of-fit evaluation, we relied on both absolute and relative goodness-of-fit indices. In addition, in order to refer to the chi-square and the degrees of freedom to evaluate possible significant differences between alternative nested models, we reported the following indices: root-mean-square error of approximation (RMSEA; acceptable values lower than 0.08;) [72] standardized root-mean-square residual (SRMR; acceptable values lower than 0.08;) [73] comparative fit index (CFI) and incremental fit index (IFI), for which scores higher than 0.90 are acceptable [74,75]. All study variables were measured through a single questionnaire; we addressed common method variance and response bias according to methods outlined by Podsakoff et al. [76]. Different scale endpoints and formats for the predictor and criterion measures were used in order to reduce method biases caused by commonalities in scale endpoints and anchoring effects. Moreover, we randomly inserted items into the questionnaire, and the scales were graphically separated from each other. Finally, two slightly different versions of the questionnaire, containing a different scales’ sequence (and mixed through the 2 different sub-samples), were used for data collection.To corroborate this research aimed at verifying the impact that straining actions have on the psychophysical health of a sample of HCWs and the role of personality in the interpretation of negative actions and in its impact on the psychophysical health of individuals, a confirmatory factor analysis was performed.Dysfunctions of work organizations and the subsequent negative actions related to psychological and physical consequences in health care professionals are relevant concerns for the scientific community concerned with occupational health and safety, considering that, in Europe, this sector employs about 10% of the entire workforce [34].In order to evaluate possible violations of the assumptions of normality, linearity, and multicollinearity, initial analyses (including Mahalanobis distance, and skeweness/kurtosis indices) were implemented (Table 3).Table 4 reports the zero-order correlations among the variables of the study. The analysis of the different measurement models was conducted in order to assess the construct validity of the study measures using CFA.Regarding the nine items of S-NAQ, CFA supported a three-factor—WB, PB, and SI—structure (χ2 = 79.21, df = 30, p < 0.001, χ2/df = 2.64, CFI (comparative fit index) = 0.940, GFI (goodness of fit index)= 0.946, SRMR = 0.038, RMSEA = 0.103, IFI = 0.941), and the composite reliability (CR) value was satisfactory (CR = 0.83).CFA did not support the assumed five-factor structure of the 10-item BFI, because of its unsatisfactory model fit and its unacceptable factor loading of items of some specific scales (AGR and OPEN). Exploring other factor solutions of BFI with 10 items, a nearly acceptable result supported by CFA was a three-factor structure (χ2 = 161.7, df = 18, p < 0.001; GFI = 0.926; CFI = 0.908, TLI = 0.844, SRMR = 0.044, RMSEA = 0.097, IFI = 0.843), but with the AGR and OPEN items saturating on other expected factors and with not acceptable internal consistency (Cronbach’s alpha < 0.60). The best factor solution was highlighted by CFA for the one-factor solution of the 10-item BFI: χ2 = 79.21, df = 30, p < 0.001, χ2/df = 2.64; GFI = 0.938; CFI = 0.890, SRMR = 0.08, RMSEA = 0.071, IFI = 0.897), although it revealed a sufficient reliability (CR = 0.69). Considering the results, we proceeded to test measurement models with six items, excluding the OPEN and AGR sub-scales. CFA supported the assumed three-factor structure of the six-item BFI (EXT, COS, EMS), with an excellent model fit (χ2 = 31.17, df = 12, p < 0.001, χ2/df = 2.59; GFI = 0.989; CFI = 0.9670, SRMR = 0.08, RMSEA = 0.039, IFI = 0.942 and excellent factor loadings). The openness and agreeableness scales were excluded in the following analyses.Confirmatory factor analyses revealed a two-factor structure for the OSI PSYT and PHIT consequences: χ2 = 1417.8, df = 559, p = 0.000, χ2/df = 2.53; GFI = 0.943; CFI = 0.910, SRMR = 0.062, RMSEA = 0.067, IFI = 0.902). Composite reliability was good (CR = 0.73).The correlation analysis (see Table 4) clearly showed that only a few personality factors are related to psychological and physical consequences. Moreover, the regression analysis highlighted that emotional stability is the only Big Five subscale that clearly predicts both individual consequences (F (1, 374) = 42.90; p < 0.001; R2 = 0.103; ß = −0.268). This seems to stress that only specific personality factors have an impact on individual consequences. However, the assumed direction of the relationship between personality and consequences was confirmed for emotional stability (negative, Hp1e), conscientiousness (negative, Hp1d), and extraversion (negative, Hp1c). Overall, even if many of the sub-hypothesis were partially confirmed, the results corroborated the macro hypotheses Hp1 only for emotional stability; because of these results and because of the parallel lack of relationship with straining measures, only emotional stability was considered as a personality factor in the subsequent analysis.The multiple regression analysis (see Table 5) highlighted that straining intensity predicts psychological (F (1, 374) = 28.09; p < 0.001; R2 = 0.098; ß = −0.281) and physical consequences (F (1, 374) = 73.24; p < 0.001; R2 = 0.17; ß = 0.544). Straining duration slightly predicted psychological consequences (F (1, 374) = 20.28; p < 0.001; R2 = 0.05; ß = −0.053) and physical consequences (F (1, 374) = 32.13; p < 0.001; R2 = 0.08; ß = −0.083). Analyzing the different sub-scales of S-NAQ with multiple regression analysis, the results highlighted that personal straining, compared to social and work straining, is the best predictor both for psychological consequences (F (1, 374) = 156.09; p < 0.001; R2 = 0.085; ß = 0.280) and physical consequences F (1, 374) = 26.99; p < 0.001; R2 = 0.17; ß = 0.407).The initial analysis also revealed that demographic and organizational variables (sex, age, tenure, and professional role) were not substantially related to the study variables, with the exception of gender (with males coded as 1, and females coded as 2).Regression showed gender differences only for physical consequences: women reported significantly higher physical symptoms compared with men (t = −3.57, p < 0.001; physical consequences: men = 1.97; women = 2.33) assessed with the PHIT sub-scale of the Individual Consequences of Stress dimension of the OSI. Smaller subjective age differences in physical consequences (r = 0.133; p = 0.05) were found. The analysis underlined that schooling has a slight significant effect on both psychological and physical consequences.The Structural Equation Models (SEMS) allow to test the set of relationships described by a theoretical model through the analysis of the deviation or fit between the model supported by data and an ideal one.In order to test if the effect of perceived straining on individual consequences is mediated by personality, starting from the initial model (Figure 1) and taking into account regression analysis, we developed a model (Model 1) with straining perceptions (intensity and duration) as independent variables and emotional stability and individual consequences as dependent variables.The model contained all the possible relationships between the described model’s variables. Fit indices were not acceptable: χ2/df = 41.17; RMSEA = 0.327; CFI = 0.893; NFI (Normed Fit Index) = 0.893; NNFI (Non-Normed Fit Index) = 0.826; SRMR = 0.049.We then revised the model, removing non-significant relationships (straining duration on psychological and physical consequences) (Model 2). The fit indices were overall acceptable: RMSEA = 0.088; CFI = 0.924; NFI = 0.942; SRMR = 0.060; χ2/df = 14.3, p < 0.001. The path diagram is shown in Figure 2.Overall, the effect of straining power on consequences was mediated by emotional stability (indirect β on psychological consequences = 0.21, p < 0.001; indirect β on physical consequences = 0.34, p < 0.001); the effect of straining duration on consequences was mediated by emotional stability (indirect β on psychological consequences = 0.08, p < 0.001; indirect β on physical consequences = 0.14, p < 0.001) (Table 6).Thus, straining perceptions predicted emotional stability, which in turn determined better consequences. Straining explains only 8% of the variance of psychological consequences and 17% of the variance of physical consequences, while, together with emotional stability, it explains respectively 15% (for psychological consequences) and 26% (for physical consequences) of the variance. Altogether, SEM results seem to confirm that straining perceptions especially impact, through emotional stability, psychological consequences.The profound changes that have affected the occupational world in recent years have contributed to the emergence of new risk situations for the health and safety of workers [77,78,79,80].In a highly precarious and highly conflictual work environment, workers’ situations of psychophysical discomfort tend to grow exponentially, undermining not only the physical integrity of a worker but, above all, his/her balance and emotional stability [81,82].The focus of research on negative actions at work has progressively shifted from strictly organizational models to models that take into account dynamics and social interactions between workers, and subjective, inter-subjective, and cultural aspects that are involved in the processes of perception of straining, mobbing, and work-related stressors [12].Straining is defined as a situation of attenuated mobbing, characterized by isolated but repeated actions over time that lead the worker to suffer constant stress and a progressive debasement of his/her working position [12,13].The aim of straining is to marginalize the worker, often considered as an inconvenience or a hindrance to the career of the preferred people. The repercussions that such types of conduct produce on the subject are numerous and potentially very serious: from medium-level psychophysical disorders to more complex forms of depression and identity disorders.However, few in the literature have investigated the effects of straining on health and the possible role of personality factors [10,41]. In this scenario, the role played by the personality factors of the straining victim is currently much debated and still far from being clarified, although it is the subject matter of many researches.In general, research shows that personality factors can play the role of mediators in the relationship between the adverse situation experienced and the stress response, but that a specific profile of the mobbing victim cannot be described [10,30,33].Generally, our study found support in other works for the research hypotheses and is in line with the scientific literature [27,83,84,85] regarding the identification of the variables that are mostly involved in degenerative events in the workplace [86].Emotional stability has been examined and recognized as a personality representation in human mind [59]. Under the paradigm of the self-organizational theory, emotional stability indicates whether a complex emotional system can automatically maintain its equilibrium efficiently. It was suggested to include two dimensions: threshold of emotional response and emotional recovery from the methodology of self-organizations [60].Threshold of emotional response represents the sensitivity of the emotional response, i.e., whether the individual experiences chaotic emotions (e.g., upset, anxiety, panic) easily. From the perspective of the evolutionary aspect, affect is an indicator attracting intentions on the adaptiveness of behaviors. Threshold of emotional response will determine whether an emotional system can be easily disordered [64].The analyses conducted showed that HCWs are at risk of discriminatory actions. Straining intensity and duration predict psychological consequences and physical consequences. Our results highlighted that personal bullying, i.e., negative actions defined as attacks against the person (such as reputational aggressions), is the most frequent form of violence and the best predictor of both psychological and physical consequences to the HCWs who took part in this study; it tends to increase with the years of service (p = 0.012) and to consolidate the social and marital status (single, married).Regarding the individual personality variables, conscientiousness is inversely proportional to WB, and agreeableness to PB. The effect of straining power on consequences is mediated by emotional stability. Emotional stability negatively correlates with the three component scales of S-NAQ: WB, PB, and SB. The role of the SB, as regards the correlation with outcomes in both the psychological and the physical health of HCWs, and the possible effect of mediation on the relationship between straining and consequences on psychological and physical health, appears, however, somewhat scaled down [87,88,89,90].The results of this research should, in this sense, be considered in the light of some methodological limitations. This study is among the first to investigate the phenomenon of straining in healthcare professionals also in relation to personality traits. The references, in this case, were very poor and not intercountry, thus it was difficult to improve the discussion.Data, in this sense, showed that only emotional stability is a personality factor that predicts individual consequences related to psychological and physical health. This seems to underline that only specific personality factors have an impact on individual consequences, and only emotional stability was considered in the subsequent analysis.Some limitations need to be addressed in future research. The results should be interpreted with caution because of the type of sample and its size, which was not large enough; they may be generalized only to HCWs working in the same type of structure (public healthcare establishment). It will therefore be appropriate to extend this research to other types of workers and organizations. Drawbacks of the present study derive from getting results from a single sample, therefore they might not reflect attitudes and concern in other samples, even though the results are comparable to those observed in other surveys. Secondly, the information produced from this study is descriptive and correlational, and causation cannot be inferred.Moreover, the personality measurement model did not provide the necessary reliability characteristics, and a significant part of the results might have been affected by this problem. In the future, it will certainly be useful to validate these results using samples from different work domains or to test differences between clinical (victims of straining) and non-clinical samples. The analysis of the different variables (organizational and personality) involved in straining and its effects must certainly be expanded through meticulous studies and tools. Future researches should better explore the role of personality (mediation, moderation, outcomes, etc.) in the perception of straining actions and in the effects on the individual.Several indications in the literature have shown that, apart from socio-demographic factors and personality traits, circumstantial emotional states especially condition the perception of risk at work [78,79]. Some authors have described risk perception as a cognitive process mediated by an emotional component: emotions would represent heuristics (or mental shortcuts) that allow people to assess risks in a way that is certainly not rational, but functional [80,81,91]. Clearly, these temporary emotional states are mainly conditioned—and somehow managed—by our personality structure, but it will be the task of future research to clarify the weight of the different variables in the perception of negative actions and work-related stressors.The discontinuous and flexible nature of contemporary work requires companies to develop forms of intervention aimed at the development of individual and interpersonal resources that are able to support workers in coping with situations of stress and difficulty at work.When it comes to straining, as well as mobbing, part of the literature considers that the onset of many degenerative processes in the workplace is related to the personality traits of the victim [36,43,44,45]. This has led to a proliferation of works with a focus on the search for psychological traits typical of the victim and the aggressor [87,92,93]. As far as mobbing is concerned, for instance, several studies have identified MMPI, the Minnesota Multiphasic Personality Inventory profiles of victims [38,42], but only few papers have used Big Five profiles.The overall results, in line with the scientific literature, show that HCWs suffer in the workplace especially in terms of personal discrimination, which has an impact on their psychophysical health. Comparing discriminating actions with personality traits, emotional stability, among all, correlates negatively with the three component scales of S-NAQ.As to the practical consequences of this study, it seems clear that all these assumptions take on a remarkable role. Our results indicate that straining may cause major consequences also on job security, in terms of health and safety of workers and their performance. In managing straining behaviors, the management should implement training and monitoring policies that take account of individual differences, arranging ad hoc interventions and outlining a framework of risks that defines their borders within the company. In practice, the planning of straining risk interventions should focus on group activities that have a greater impact on individual behavior and, when they are able to increase the internal cohesion of work groups, can allow a greater prevention of conflicts and of the propensity for straining behaviors.All authors have read and agree to the published version of the manuscript T.R. and V.R. conceived and designed the experiments; F.V., P.S., E.C., A.S. done through questionnaires to target groups investigation; M.B. analyzed the data; C.L. and A.D.G. contributed analysis tools; V.R. critically reviewed the manuscript; T.R. and M.B. wrote the paper.This research received no external funding.The authors declare no conflict of interest.Research model and main hypotheses (Hp).Path diagram of the tested model.Description of the sub-samples.Description of the sample.Descriptive statistics for different scales of the study. S-NAQ: Short Negative Acts Questionnaire.Zero-order correlations among the different scales of the study.* p < 0.05; ** p < 0.01; *** p < 0.001.Multiple regression of S-NAQ different sub-scales as predictor of health consequences.*** p < 0.001.Standardized path coefficient (regression weights).** p < 0.01; *** p < 0.001.

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+Air pollution exposure has been linked to modifications of both extracellular vesicle (EV) concentration and nasal microbiota structure (NMB), which might act as the respiratory health gatekeeper. This study aimed to assess whether an unbalanced NMB could modify the effect of particulate matter (PM) exposure on plasmatic EV levels. Due to two different NMB taxonomical profiles characterized by a widely different relative abundance of the Moraxella genus, the enrolled population was stratified into Mor− (balanced NMB) and Mor+ (unbalanced NMB) groups (Moraxella genus’s cut-off ≤25% and >25%, respectively). EV features were assessed by nanoparticle tracking analysis (NTA) and flow-cytometry (FC). Multivariable analyses were applied on EV outcomes to evaluate a possible association between PM10 and PM2.5 and plasmatic EV levels. The Mor− group revealed positive associations between PM levels and plasmatic CD105+ EVs (GMR = 4.39 p = 0.02) as for total EV count (GMR = 1.92 p = 0.02). Conversely, the Mor+ group showed a negative association between exposure and EV outcomes (CD66+ GMR = 0.004 p = 0.01; EpCAM+ GMR = 0.005 p = 0.01). Our findings provide an insight regarding how a balanced NMB may help to counteract PM exposure effects in terms of plasmatic EV concentration. Further research is necessary to understand the relationship between the host and the NMB to disentangle the mechanism exerted by inhaled pollutants in modulating EVs and NMB.Extracellular vesicles (EVs) are powerful and not yet fully understood biological effectors shared between domains of life [1].Several biological molecules have been identified to be carried into the EVs, such as DNA, small RNA, and non-coding RNA, including also miRNAs of different size [2,3], proteins, and other soluble factors [4], which are internalized by recipient cells after either EV interaction through surface-expressed ligands or endocytosis [5]. Different studies have underlined that EVs are involved in numerous biological and pathological processes, which span from immune system modulation [6,7], cancer [8], metabolic diseases [9], atherosclerosis [10], and development of chronic obstructive pulmonary disease (COPD) to allergic airway inflammation [11]. It has been found that EV production could be influenced and involved in response to volatile pollutant exposure, including particulate matter (PM) [12,13].PM is defined as the heterogeneous mixture of both organic and non-organic particles, which derives from several sources and generally is sorted due to particle aerodynamic diameter into PM10 and PM2.5 (diameter ≤10 µm or ≤2.5 µm, respectively). According to the World Health Organization, exposure to PM has been linked to an increased morbidity and mortality, primarily caused by cardiovascular disease [14,15]. In addition, both short-term and long-term exposure to PM have been associated with the worsening of respiratory conditions and diseases in both adults and children [16,17]. As a function of the inhalation process, PM firstly interacts with the nares mucosa, which is the closest respiratory system (RS) compartment to the external environment, producing a local inflammatory reaction [18]. It has been widely documented, along with RS, that nares harbor a variety of commensal symbiont and pathobiont microorganisms, which, taken together, constitute the nasal microbiota community (NMB) [19,20].Inhabiting the entire nares surface by niche-specific microorganism, including bacteria, the NMB acts as a gatekeeper to respiratory health, probably impeding respiratory pathogens from setting up an infection [21]. In addition to competitive exclusion function, NMB might also have a role in the anatomical development of the respiratory tract, as well as in the maturation and tolerance of the local immunity [22,23]. However, the continuous exposure of the NMB to large amounts of airborne particles, including PM, can alter the bacterial community composition towards an unstable one that might not be able to resist pathogen overgrowth and to maintain the physiological cross-talk existing with the host, resulting in an alteration of the immune state.According to these above-mentioned considerations, we recently reported that PM10 and PM2.5 levels of the 3rd day preceding sampling (Day 3) were inversely associated with the majority of analyzed bacterial taxa, except for the Moraxella genus. Moreover, two clearly different taxonomical profiles were recognized within the analyzed population, identifying two groups: one characterized by an even community and another widely dominated by the Moraxella genus [24]. Therefore, according to the relative abundance of the Moraxella genus, we stratified the enrolled subjects into the Mor− and Mor+ groups (the Moraxella genus’s cut-off was ≤25% and >25%, respectively), which were characterized by a heterogeneous and an unbalanced NMB, respectively.The aim of the present study was to evaluate the possible role of NMB in determining plasmatic EV secretion level differences in response to short-term PM exposure levels in a stratified healthy population characterized by two distinct NMB profiles.Detailed methodological descriptions, including both NMB and EV analyses, as well as subject recruitment, were formerly reported in (Mariani et al., 2017) and (Bonzini et al., 2017; Ferrari et al., 2019), respectively [24,25,26].Briefly, the involved study population was composed of 51 healthy volunteers recruited between November 2014 and March 2015 by an ad hoc developed announcement posted on the SPHERE Project website (http://users.unimi.it/sphere). In addition, all subjects also filled in a questionnaire collecting exhaustive personal information, including anthropometric characteristics, education, area of residence, job position and location, time spent commuting in traffic, alcohol consumption, smoking habits, drugs, and pre-existing medical conditions.PM exposure assessment was accomplished using a miniaturized personal sampling device (Personal Cascade Impactor Sampler–PCIS, SKC Inc., PA, USA), retrieving both PM10 and PM2.5 level data during a 24 h period before sample collection. In addition, environmental concentrations of PM10 and PM2.5 of the day preceding the sample collection were also collected from the regional air quality monitoring network (ARPA Lombardia, Milan, Italy) in order to integrate and compare with the ones collected from PCIS.Each subject underwent a blood drawing and a nasal swab to perform EV and NMB analyses, respectively. Isolation, purification, and characterization of EVs were performed by following the Minimal information for studies of extracellular vesicles (MISEV) 2018 guidelines [27]. Briefly, ethylenediaminetetraacetic acid EDTA-treated blood was centrifuged at 1200× g for 15 min at room temperature to obtain platelet-free blood plasma, which was further centrifuged following a three-step centrifugation protocol (1000, 2000, and 3000× g for 15 min at 4 °C), and finally ultracentrifuged to obtain an EV-rich pellet (110,000× g for 75 min at 4 °C). The EV-rich pellet was then resuspended with 500 µL triple-membrane filtered phosphate-buffered saline PBS, and flow-cytometry (FC) and nanoparticle tracking analyses (NTA) were conducted to assess EV-size distribution, concentration, and EV-origin, using a specific panel of fluorochromes-conjugated antibodies as previously reported, and detailed at http://bit.ly/2sCN9vy [28].NMB analysis, starting from DNA extraction and amplification from the collected nasal swabs, was carried out through a metabarcoding approach targeting the 16S rRNA V3-V4 hyper-variable regions using the Illumina Miseq sequencing platform, and both upstream and downstream analyses performed on sequencing output were achieved using the default setting suggested in the QIIME 1.9.1 pipeline [24,29]. To confirm the taxonomical composition difference between the two, analyzed group principal coordinate analyses (PCoA) were performed, applying the weighted UniFrac normalized distance metric using QIIME 1.9.1 software.Plasma was used to quantify tumor necrosis factor alpha (TNF-α) cytokine by the Luminex xMAP®-based technology (MYRIAD RBM, Inc., Austin, TX, USA). When the concentration was below the lower limit of quantification (LLOQ), data were replaced by half of the lower limit of quantification (LLOQ/2).Descriptive statistics were performed on all variables. Categorical data are presented as frequencies and percentages. Continuous variables are expressed as the mean ± standard deviation (SD) or as the median and interquartile range (Q1–Q3), as appropriate.Multivariable linear regression models were applied to evaluate the association between EV count and Moraxella group (Mor+ vs. Mor−). EV concentrations showed skewed distributions and were naturally log-transformed to achieve normal distribution. For each EV size, we estimated geometric means adjusted for age, gender, smoking habits, and BMI in the Mor+ and Mor− group. Due to the high number of comparisons, we used a multiple comparison method based on Benjamin–Hochberg false discovery rate (FDR) to calculate the FDR P-value. To display the results of the analyses, we used a series graph for EV mean concentrations of each group and a vertical bar chart to represent FDR p-values and p-values. For the two graphs, the X axis was the size of EVs. The same linear regression model was applied to evaluate the association between TNF-α and total EV.The role of Moraxella relative abundance as a possible modifier of the association between PM exposures and EV count parameters was evaluated, and the multivariable linear regression models were adjusted for age, gender, smoking behavior, and BMI. We observed whether the effect of PM exposure on EV count differed, depending on the Moraxella levels stratifying population in two groups (Mor− and Mor+) using 25% of Moraxella relative abundance as cut-off, and separate multivariable linear regression models were applied.Continuous variables were tested for normality and linearity. Then PM exposure data were log-transformed (base 10) to satisfy linearity assumption, and EV counts were log-transformed (base e) to achieve a normal distribution. Effects were thus expressed as geometric mean ratio (GMR) with 95% confidence interval (CI), which corresponds to the exponential of the β regression coefficient when the dependent variable is on the log-scale. GMR indicates the number of times the outcome changes for a 10 times (log10 unit) increase in PM concentration.Linear regression coefficients in the Mor+ and Mor− subject groups were estimated by this equation:(1)ln(EV)= α+ β1log10(PM2.5)+ β2AGE+ β3SEX+ β4SMOKE+ β5BMIThe whole series interaction was tested by adding interaction term (categorical Moraxella * PM) to the multivariable models.Statistical analyses were performed with SAS software (version 9.4; SAS Institute Inc., Cary, NC, USA).Among the 51 subjects, a DNA yield sufficient to perform NMB analysis was retrieved for only 40 samples (78%). Interestingly, almost half of the subjects characterized by an insufficient DNA yield were current smokers. The main characteristics of the 40 subjects are listed in Table 1. Participants’ mean age was 48.6 ± 8.4 years, and females represented 57.5% of subjects, while 62.5% of the study subjects were never smokers and 12.5% were classified as current smokers.PM exposure data measured by PCIS were compared with the data estimated by ARPA monitoring stations (MS). The observed PM10 and PM2.5 median values measured by MS did not diverge from those retrieved by PCIS (PM10: 46.8 µg/m3 vs. 45.1 µg/m3, respectively; PM2.5: 34.0 µg/m3 vs. 36.1 µg/m3, respectively; Wilcoxon test for equality of medians: p = 0.28 for PM10 and p = 0.48 for PM2.5). Moreover, the correlation between the two different PM collection sources was assessed and the results of the Spearman’s rho test were statistically significant (PM10: Spearman’s r = 0.59; PM2.5: r = 0.68; both p < 0.001). The PCoA showed that the enrolled population was clustered into two distinct groups based on its NMB taxonomical composition, defining the Mor− and the Mor+ groups, especially based on PC1 scores when the weighted UniFrac normalized distance metric was applied (Figure 1). In addition, the dissimilarity between the analyzed group was statistically supported by an ANOSIM R value of 0.83 (p = 0.001)As we considered EV size characterized by NTA, the mean EV size values were 224.88 and 215.6 nm for Mor− and Mor+ groups, respectively (p-value for differences >0.1). Modal EV size values span from 169.9 nm for the Mor− group and 157.36 nm for the Mor+ one.As we are aware that the information on mean and mode might not be exhaustive, we further compared the two groups in terms of distribution of mean vesicle concentrations for each size (Figure 2). In the upper part of the figure, we reported for each EV size (from 30 to 700 nm) the mean concentration calculated in each group. The Mor+ and Mor− subjects’ size distributions were similar, as confirmed by the lower part of the plot, which reports the p-values and FDR p-values obtained comparing Mor+ vs. Mor−.In order to verify the effect of plasmatic EV concentration in modifying the inflammatory state, multivariable linear regression analysis between total EV count and TNF-α, as an example of a pro-inflammatory cytokine, adjusted for age, sex, smoking behavior, and BMI, was performed. The total count of plasmatic EVs was positively associated with the plasmatic concentration of TNF-α (GMR = 1.035, p = 0.023) (Figure 3).To assess whether and how an unbalanced NMB profile may modify the response to PM10 and PM2.5 exposure in terms of plasmatic EV count, the 40 subjects were stratified, according to Moraxella genus relative abundance, into Mor− (n = 30) and Mor+ (n = 10) groups (Moraxella genus relative abundance ≤25% and >25%, respectively).Multivariable analyses computed on both FC and NTA outcomes showed (Figure 4), among Mor− subjects, positive associations between PM2.5 exposure and both endothelial-derived (CD105+) (GMR = 4.39 p = 0.02) and EV total count (GMR = 1.92; p = 0.02). By contrast, negative associations were identified for the Mor+ group between PM2.5 exposure and neutrophil-derived EVs (CD66+) (GMR = 0.004; p = 0.01) and between PM2.5 exposure and epithelium-derived EVs (EpCAM+) (GMR = 0.005; p = 0.01).Both groups exhibited a significant––albeit opposite––association between PM2.5 exposure levels and monocyte-derived EVs (CD14+) (Mor−: GMR = 5.34; p = 0.04/Mor+: GMR = 0.04; p = 0.02).Focusing on platelet-derived EVs (CD61+), both the Mor− and Mor+ groups followed the previously mentioned EV association direction when PM2.5 exposure was considered, even though no statistical associations were clearly identified. We repeated our analysis for PM10 exposure effects and observed consistent trends for the previously described outcomes (except for EpCAM+ EVs, which did not present any clear association with PM10 exposure) (Supplementary Table S1).In this study, we investigated the effects of short-term PM exposure on plasmatic EV levels in a healthy population, stratified into Mor− and Mor+ groups according to NMB Moraxella genus relative abundance, in order to assess the possible role played by the nasal bacteria community as a factor of susceptibility or resistance to the widely known adverse-inhaled pollutant effects.In one study, we showed that exposure to PM can affect the microbiota community [24]. These changes lead to modifications of the indigenous bacterial community, perturbing the structure and the relationships existing between the different species of the microbiota and potentially modifying the equilibrium between the bacteria community and the host, which often leads to unhealthy conditions [30,31]. In addition, PM exposure can trigger inflammatory response [32], worsen chronic conditions spread all over the body sites, and also heighten the risk for acute and chronic diseases [33,34,35,36,37,38]. Several epidemiological studies showed how the effects exerted by PM exposure on human health can be attributed, at least in part, to plasmatic EV modifications, which include variations in the transcriptomic and proteomic content, as well as in the circulating amount of different EV types [39,40,41,42,43]. In addition, documentation shows that PM exposure may trigger EV release in a dose-dependent manner [41], inducing the release of proinflammatory cytokines such as IL6 and TNF-α [44].In agreement with this evidence, we observed a positive association between the total plasmatic EV count and TNF-α level, considering the whole enrolled population. This observed increment of TNF-α could be caused by a partially enhanced EV activity in response to the acute inflammatory response induced by PM exposure [44].In the Mor− group, the positive associations between both PM10 and PM2.5 levels and plasmatic EV could be partially explained by the presence of a heterogeneous NMB. Interestingly, both CD14+ and CD105+ EVs were the most abundant ones, probably due to the fact that, after deposition on alveolar epithelium, PM can be phagocyted by macrophages, pass through the alveolar–capillary membrane, and directly interact with pulmonary endothelium [45], stimulating these sources of EVs production.By contrast, Mor+ subjects showed a negative association between measured PM10 and PM2.5 exposures and EV derived from neutrophils, epithelium, and macrophages.Despite the uncertain role exerted by EVs in the inflammatory processes, such as after PM exposure, an increasing number of studies highlight the possible mitigative role of the above- mentioned EVs during inflammation [46]. In particular, CD105+ EVs could probably promote vascular regeneration, either through a specific interaction or through miRNA delivering into recipient cells. Indeed, it has been found that CD105+ EVs-carried miRNA-222 may contribute to weaken inflammatory effects modulating the endothelial expression of ICAM-1 [47], as well as for the PCSK9 protein, which has been related as a biomarker for different cardiovascular negative conditions [48].An inflammatory regulating behavior has been also identified for CD14+ EVs that in the respiratory tract may contribute to control both cytokine signaling and IFNγ-induced activation of signal transducer and activator of transcription (STAT), which is responsible for enhancing the expression of proinflammatory genes (STAT-dependent genes) [49].Similarly to the above-mentioned evidence, one report determined that small EVs might be able to prevent macrophages activation through the M1-proinflammatory phenotype after stimulation with LPS, in both in vitro and in vivo models, suggesting a possible anti-inflammatory role exerted by EVs [50].Together, these findings suggest that the group with a balanced nasal bacteria community seems to have a more reactive response to PM insults, in contrast to the Mor+ group, considering the amount of plasmatic EVs. This different behavior identified for the Mor+ subjects could be addressed to the unbalanced Moraxella-dominated NMB, which might modify the protective function provided to the host against inhaled pollutant effects.In contrast with these considerations, it was observed that PM exposure was linked to an increased concentration of phosphatidylserine-enriched EVs released from different cell types. These EVs alter the phagocytes’ efferocytotic activity [41], which has been linked to the worsening of pathological conditions such as atherosclerosis and chronic obstructive pulmonary disease [51,52]. In addition, through biological pathway analysis, PM exposure seems to modify EV-encapsulated miRNA involved in the maintenance of health [12,42,53].Thus, merging the aforementioned and our previous results [24], the nasal bacterial community could be considered as the first compartment targeted by PM exposure inflammation, as well as a sort of filter between the host and the external environment, which might alter the peripheral effects exerted by air pollution exposure in terms of plasmatic EV levels. This study has limitations. First, we were not able to discriminate through FC the EV belonging to the different bacterial strains, which could be affected by PM exposure in terms of plasmatic concentration and also involved in the immune state regulation. Second, we considered only NMB, although other microbiota compartments, such as the gastrointestinal one, could be modified by PM exposure and contribute to the total EV cargo circulating through the human body. However, since the primary aim of this study was to assess how the microbiota modifies the variation of plasmatic EVs induced by short-term PM exposure, we focused our attention on the nasal bacterial community, considering it as the first target of PM exposure.To the best of our knowledge, this is the first study specifically addressing the role of NMB in determining differences in plasmatic EV secretion levels in response to short-term PM exposure levels in healthy subjects.Future studies will be carried out on a larger population, with the purpose of a deeper characterization of the NMB components, understating the relationship between the host and the nasal bacteria community and how it could react to air pollution exposure. A focused insight into EV contents will be performed in order to clarify if a different plasmatic concentration of EVs could be also linked to different transported biomolecules, as well as the characterization of the bacterial secreted EVs, which taken together may be informative of physiological changes exerted by PM exposure.The following are available online at https://www.mdpi.com/1660-4601/17/2/611/s1, Table S1: Association between PM exposure and different classes of EV, stratifying subjects by their Moraxella genus relative abundance into Mor− (≤25%) and Mor+ (>25%) group.Conceptualization, V.B., M.B. and A.C.P.; methodology, V.B. and J.M.; formal analysis, J.M., C.F. and M.C.; investigation, A.C. and L.P.; resources, V.B.; data curation, C.F. and J.M.; writing––original draft preparation, J.M., L.F. and C.F.; writing––review and editing, V.B., L.F., M.B.; visualization, J.M., L.F. and C.F.; supervision, L.F. and V.B.; project administration, V.B.; funding acquisition, V.B. All authors have read and agreed to the published version of the manuscript.This study was supported by the EU Programme “Ideas” (ERC-2011-StG 282413) to principal investigator Professor Valentina Bollati.We thank Enrico Radice for database development and preparation. V.B. received support from the EU Programme “Ideas”, European Research Council (ERC-2011-StG 282413).The authors declare no conflicts of interest.Each participant signed a written informed consent, approved by the Ethic Committee of the Fondazione Ca’Granda–Ospedale Maggiore Policlinico approval number 1425), in accordance with the Helsinki Declaration principles.Principal coordinate analyses (PCoA) plot made using the normalized weighted UniFrac distance metric. Each dot corresponds to a single subject belonging either to Mor− (green dot) or Mor+ (red dot). The variance explained by each axis is given in parentheses. Dissimilarity between group was statistically tested applying the ANOSIM method.Extracellular vesicle (EV) size distribution in the Mor− and Mor+ groups. Panel (A): * Reported geometric means were adjusted for age, sex, BMI, and smoking habits. Plots showing for each group (Mor− and Mor+) the distribution of mean vesicle concentrations for each size. Panel (B): vertical bar charts represent FDR and p-value for each size comparison; the red line indicates p-value = 0.05.Association between total EVs and TNF-α. The multivariable linear regression model was adjusted for age, gender, smoking behavior (Never smoker, Former smoker, Current smoker), and BMI.Association between EV outcomes and PM2.5 exposure. Mor+ and Mor− subjects were represented by crosses and circles, respectively. Scatterplots of EV (103/mL PL) vs. PM2.5 (below) levels (µg/m3). Covariate-adjusted geometric mean ratios and corresponding 95% confidence intervals (GMR (95%CI)) in EV estimated per log10-unit increase in PM are shown. Subjects were stratified according to their Moraxella genus relative abundance into the Mor− (≤25%) and Mor+ (>25%) group. Total EV count obtained via nanoparticle tracking analysis (NTA). EV fraction counts performed via flow-cytometry (FC) analysis.Characteristics of the study participants in the Mor− and Mor+ groups.Continuous variables are expressed as mean ± standard deviation (SD) or as median (first quartile–third quartile) if not normally distributed; discrete variables are expressed as counts (%).

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+In health-promoting interventions, a main difficulty is that low socioeconomic status (SES) groups especially seem to experience barriers to participation. To overcome this barrier, the current study focused on the success factors and obstacles in the process of supporting low-SES families in becoming partners, while carrying out small-scale activities based on their needs. A retrospective case study design was used to construct a timeline of activities organized by and together with low-SES families based on mainly qualitative data. Next, key events were grouped into the four attributes of the resilience activation framework: human, social, political, and economic capital. The following key lessons were defined: professionals should let go of work routines and accommodate the talents of the families, start doing, strive for small successes; create a functional social network surrounding the families, maintaining professional support over time as back-up; and create collaborative governance to build upon accessibility, transparency and trust among the low-SES families. Continuous and flexible ‘navigating the middle’ between bottom-up and top-down approaches was seen as vital in the partnership process between low-SES families and local professional partners. Constant feedback loops made the evaluation points clear, which supported both families and professionals to enhance their partnership. The unequal distribution of health between individuals from low socioeconomic status (SES) groups and middle-to-high SES groups, so-called health disparities, remains a major challenge in health promotion [1,2]. Globally, a higher morbidity and mortality have been reported among socially disadvantaged groups [3]. Besides physical health outcomes, low-SES groups also score worse on mental and social health outcomes. These groups often show lifestyle behaviors that help them cope with their stressful life situation, while at the same time exposing themselves to negative health effects and making their situation worse [4]. A positive mediating effect on the relation between SES and overall health was found to be a person’s lifestyle [5]. Health improves through the lifestyle choices that individuals make, e.g., engaging in physical activity, having social interactions and enhancing stress management skills [5]. Especially for low-SES groups, the benefits of enhancing their physical, mental and/or social health are considered to be a key step to closing the health gap [4]. The main difficulty is that low-SES groups especially seem to experience barriers in terms of participating in activities to support their general health [6,7]. Due to the daily issues they perceive, they carry a high mental burden, depleting their cognitive energy to take part in health-promoting programs and act upon health-related goals [8,9]. Despite the many well-intended health promotion programs, the broader living situation and the needs of the low-SES groups are often inadequately taken into account, and therefore these programs often show low participation by members of the low-SES group and high levels of drop out [2]. It is still a challenge to expend more effort to include low-SES groups in the community engagement process of developing, implementing, and evaluating health promotion programs from the very beginning [10]. The higher level of involvement of, and partnership with, the low-SES groups implies a central focus on their needs, and balancing between top-down knowledge and processes introduced by professionals and bottom-up perceived needs and work processes of low-SES groups [11]. With the idea of making low-SES families an equal partner and involving them in health-promoting activities from the beginning, the Vaals Meets project was developed. Half a year before the project started, eight low-SES families took part in a photovoice study to define their needs [12]. They were asked to make pictures of daily issues and opportunities they perceived to improve their quality of life. The photovoice study led to four themes relevant to low-SES families: 1. meeting each other, 2. helping each other, 3. feeling safe, and 4. being mobile. The themes supported the desire of the families to be independent and self-resilient. It was interesting that the themes were not specifically focused on health but revealed the importance of first tackling their basic needs before opportunities could arise to enhance their health status [12]. These four themes formed the basis of Vaals Meets, in which families were supported with organizing small-scale activities and cooperating with formal and informal community partners, with the aim to strengthen their feeling of independence and self-resilience. These small-scale activities focused on upstream determinants of health, such as exploring your own talents or enhancing social support. Over the long term, they are expected to have a trickle-down effect on the families enacting them, encouraging them to accomplish greater steps in independence and self-resilience and eventually reach a better health status [13].This paper focuses on the process to support low-SES families in becoming equal and active partners in carrying out small-scale activities based on their needs. The overall aim was to define success factors and obstacles that were encountered while partnering with the low-SES families in the organization of small-scale activities. Consequently, we aimed to synthesize key principles in the process to strengthen the position of low-SES families in health promotion development.Through participatory action research (PAR), all activities carried out by low-SES families were carefully monitored to create a better understanding of their reactions, perceptions and feelings [14,15]. Feedback loops were created and stimulated by the participatory researcher to accelerate processes in the system. We used a retrospective case study design. A timeline of activities reconstructed by the researcher, the families and the two key stakeholders (activation broker and policy maker) provided insight into the events and variables that changed over time. Each activity included in the timeline was accompanied by a core description of the situation. By using a relativism paradigm, we placed a focus on describing, exploring and giving meaning to the events that happened. This helped us to understand key principles in the process of engaging low-SES families [16]. An inductive process was used to compose the timeline. As a next step, an abductive process [17] was used to synthesize the key lessons learned by using a theory that fitted well to the events described on the timeline.From April 2016 to February 2018, the study took place in the municipality of Vaals, a small town located in the southernmost part of the Netherlands, near the border with Germany and Belgium. The municipality has approximately 10,000 citizens, of mainly Dutch origin, and a moderate to low SES. Consequently, its citizens have a poorer health status, a shorter life expectancy, more mental health issues, and an unhealthy lifestyle compared with the average Dutch population [18]. Accompanying issues such as living in poverty and experiencing stress were also frequently described [18,19]. The Public Health Service Southern Limburg, Maastricht University, and the municipality of Vaals, provided support for this study. We performed the study in accordance with the Code of Conduct for Health Research of the Dutch Federation of Biomedical Scientific Societies.In the process of analyzing the events on the timeline, the resilience activation framework (RAF) [20] was used to categorize the lessons learned. The RAF approached resilience as a process in which the capacity to withstand or recover from disturbances that threaten the existing quality of life is created on an individual and/or community level. Within RAF, four attributes on the individual and community levels explained the presence of capital that remained underutilized, making resilience to flourish impossible: human, economic, social, and political capital. Moderate-to-high SES groups were expected to be able to use their capital, e.g., good health and a positive mindset (human capital), savings (economic capital), a strong social network (social capital), and access to people in leadership positions (political capital). Low-SES groups were expected to have lower capacity levels of capital, making it harder to gain resilience. In the analysis phase of our study, we focused on explaining and understanding changes with these attributes. In the process of recruiting the low-SES families, an intermediary, a so-called activation broker, played a central role. The broker was familiar to the local citizens and had good contacts with professional partners. The personal contacts she had made the recruitment process successful for the Photovoice study (July 2015–January 2016). From the ten family members who participated in this needs assessment phase, eight members decided to continue. By using a snowball sampling technique, participants fostered recruitment of more families. To create engagement from the community as a whole, formal and informal partners, including other citizen groups, were welcomed to work together with the families in creating activities focused on the earlier defined needs. From the 220 low-SES families in Vaals [21], twelve low-SES families with various backgrounds, e.g., single-parent families, complete families, and families from Dutch and other origins, actively participated during the study period. More families, approximately 40, were mainly engaged as visitors during the activities organized by these families.The involvement and facilitation of low-SES families during the planning phase and organization of their own activities was a central aspect of the community engagement approach. After defining the most important needs and accompanying themes with the families, the professionals (activation broker, policy maker, and researcher) and the families decided that it was time to become active. Workgroups were created by the professionals in which the families started to prepare, discuss, organize, and evaluate small-scale activities, with their support. Besides these professionals and the low-SES families, connections with other formal and informal partners were sought in the community with the aim of creating a collaborative partnership. A policy maker at the tactical level from the municipality of Vaals played an important role at the nexus of local policy, the broker, the researcher, and the family’s needs to actually realize activities. This achieved a professional cooperation between policy, practice, and research. The small-scale activities, accompanying processes, and results of the workgroups were monitored and evaluated by the researcher and used as input for new small-scale activities. This study mainly involved the use of different types of qualitative research instruments to gather data. First, during the multiple workgroup sessions organized with the families, optional activities, minutes of the discussion, and agreements made by the researcher, the broker, and the families were discussed. The researcher took notes about the group process. Second, during the actual small-scale activities organized by the families, the researcher undertook observations and made notes as well. These observations and notes mainly focused on success factors and learning points to enhance self-resilience among the families, but also included some quantitative outcomes such as number of visitors. All activities were evaluated during the meetings with the families, and successes were mentioned (and celebrated). Finally, twice in the research period a focus group interview was held in which actively involved low-SES families at that point were invited and asked to describe their experiences with the approach, what they considered good, where there was room for improvement, and what goals they wanted to achieve in the upcoming period. After this interview, the families, broker, and researcher had dinner together. All data gathered from observations, minutes of meetings, process notes and observation of meetings, events, and focus group interviews were organized with Nvivo software to create the timeline with activities [22]. After creating the complete timeline of all described activities, the researcher (LP) worked together with the project team members (MW and JM) who were closely involved in the PAR research trajectory to complete the timeline and structure the timeline activities into attributes within the RAF. By creating a complete timeline and reconstructing essential supportive and hindering attributes in the participatory process, we synthesized key lessons. During the first year from July 2016 to July 2017, the families received relatively intense support from the broker and/or researcher (Figure 1). During the final half-year (July 2017–February 2018), families more often took the lead independently. This indicated a change from a top-down approach by the professionals to more bottom-up input from the families. The constant feedback loops created enhancements in the human, social, and political capital, with the largest growth being observed in human capital. Changes over time in all types of community capital will be discussed separately below, concluding with key lessons learned that implied a navigation between top-down and bottom-up approaches (Table 1).To enhance the human capital, the broker’s and researcher’s training support for low-SES families offered them the skills they needed to organize small-scale activities. Professionals, the broker and researcher, first had to assist and encourage families to take the lead in their activities. Gradually, this top-down support was only needed as a back-up, and therefore adjusted. The families contributed from bottom-up to the community’s human capital by providing their ‘expert knowledge’ to the activities, since they best knew what their community needed. A transition from top-down to more bottom-up became visible. It took some time for the families to become an actively involved partner and to successfully realize small-scale activities. Time was needed to bridge the gap between the professionals’ partnership approach and that of the families in making preparations and organizing small-scale activities. Professionals used a ‘talking-approach’ whereas the families used a ‘doing-approach’. A ‘brilliant failure’ after many ‘talking’ sessions was the idea of the food closet (see Timeline) that never materialized and faded out. According to the municipality, the proposal was never perceived as sufficiently and thoroughly explained in order to start implementation. Realizing small-scale activities showed families about personal growth throughout the preparations and organization. They first focused on the things that might go wrong, were more insistent on actually starting with the activities themselves, and waited for approval from the broker/researcher. It is likely that professionals reinforced this due to their actions at the beginning. For example, the researcher kept sending families of the Preventing Food Waste Workgroup back home with new questions to answer, and during the first meeting with community partners (i.e., community council members, the local police officer, and the youth worker), the partners decided that the families should start with a neighborhood consultation, before organizing a neighborhood party. During the final half-year, the families acted as really involved partners, showing the capabilities to lead their own activities. Successful small-scale activities were considered beneficial to a more positive mindset. Pessimism seemed to have changed into positivism. The families saw opportunities for themselves and their community and started to work more independently, while professionals noticed the growth in their capabilities. Difficulties were also encountered, e.g., dealing with some setbacks and the relatively long policy procedure for the food closet proposal, which made expectation management from the broker and researcher important to keep the families going. Eventually, the families felt able to carry out this type of activity themselves and were willing to be part of a more consistent initiative. Concerning the professionals, we saw the necessity to have a flexible and openminded attitude and focus directly on the preferred activities of the families, while providing support and facilitation, as an equal partner. As a second form of capital, social capital, seemed to grow during the study period. The workgroups created a new social network for the families, by working towards a common goal. Recruiting new families and community partners remained the major difficulty. The broker played a necessary role in recruiting more families, while also including other citizens and partners in the community to create a broader partnership within the workgroups. Although initiated in a top-down manner, the broker’s broad network and contacts enabled her to strengthen the families’ network. This created a supportive network surrounding the families to fall back on. Due to the equal partnership and leading position of the families created in the workgroups, their status on the social hierarchy seemed to increase. The families were proud of their work and the realized partnerships. All partners and visitors to their small-scale activities complimented the families. Most families were not familiar with each other before the project. During the photovoice phase, they quickly became companions due to their mutual understanding of each other’s situations. For the researcher and the broker, it was important to create trust to start partnering as well. The broker was already familiar with the families and seemed to gain the status of ‘coworker’ faster than the researcher. The Neighborhood Workgroup with the support of the broker had greater resilience steps at the start, compared to the researcher’s group (Preventing Food Waste Workgroup). The perceived social support that the families received from their partnering families, the researcher, the broker, other citizens, and neighborhood partners was described as pleasant and helpful by the families. Having fun and enjoyment was important to the families, as did celebrating successes together. Although the families made great progress in strengthening social partnerships, the back-up, mostly from professionals, to facilitate processes (e.g., assist in the application for the permits for the flea market and neighborhood party) was found to be important. Maintained functional support was important for the families to share successes, but also to receive support when issues were encountered over time. The third form of capital, political capital, seemed to be enhanced by the close involvement of the policy maker that mostly facilitated the small-scale activities by the families. For example, during the neighborhood scan, the recommendation letter written by the families was already provided with feedback by the policy maker. Most suggestions made by the families were facilitated or turned into actions by the municipality. Conversely, the government also caused delay, due to the lengthy political process. The government can actually make or break a societal initiative. Collaborative governance was found to be important, as the government, the families, and other involved citizens and partners had to communicate well and work together to achieve successes that they could not achieve on their own. In this strategy the whole societal network of a municipality can be included, with the government being just one of the partners within the network. The close connection that the families had with the person in a ‘leadership’ position at the municipality was mainly helpful. The families appreciated the presence of the policy maker during the partner meetings to explain the input from the municipality. It showed the engagement and involvement of the municipality to the families, something they seemed to miss before. Although the policy maker was very outreaching and accessible for all families, the moment when the municipality had to say ‘no’, the families seemed to fall back in an ‘I told you so’ attitude. The municipality was depicted as non-collaborative, ‘controlling’, or ‘holding back progress’. A high level of involvement, openness, and transparency of the responsible policy maker, but also the ability to communicate about what is realistic, was seen as being important to maintain the families’ trust. Finally, financial resources were made available for the small-scale activities from external funding of the Vaals Meets project. The families first intended to make some illogical choices according to the professionals, e.g., wanting to buy electric devices such as a coffee machine and kettle for the flea market. Subsequently, a focus was placed on sustainable and affordable options, such as borrowing the electronic devices, something the families seemed to be good at.Before starting in Vaals Meets, most families had already received individual guidance from professionals at the community level, e.g., via social work, the credit bank, or the activity broker. The partnership seemed to support the families to become even more active in the neighborhood. Some families found employment during the study period. This had a positive influence on their income. It is hard to state the influence of Vaals Meets on the economic capital achievements of the families, because the nature of the research design did not focus on finding causal relations. However, we do expect that the equal partnership and the small-scale successes contributed to some extent to the ability of the families to find a job again.The current study aimed to define key lessons learned in the partnering process between professionals, e.g., the involved broker and researcher, and low-SES families. The organization of small-scale activities was used as a means to strengthen the position of low-SES families and create an equal partnership. With all the key lessons learned, a flexible and adaptive ‘navigating the middle’ route was seen as vital: governance needs to navigate between bottom-up processes with families in the lead and top-down approaches (led by the expertise of e.g., the broker and researcher) [23]. During the project period, a transition became visible that characterized families in becoming more self-resilient and independent, while the professionals, broker and researcher, had to be flexible to stay supportive and facilitating. Constant feedback loops, primarily created by the participatory researcher, produced insight into the process of partnering together, learning together, but also failing together. Over time, this supported both the families and the professionals to enhance their partnership, and a gradual growth became visible in the competences, autonomy, and relatedness of the families to take the lead [24]. At the final half-year, the empowered families clearly had their leading position and explained having the confidence to organize activities mainly by themselves. In terms of the collaboration between the low-SES families and the professionals, namely the broker and the researcher, a particular learning curve was evident. Although the professionals were in place to support and facilitate the partnership with the families by adding beneficial expert knowledge and skills to fulfill their mission [25], it seemed that the routinely used, professional, top-down approaches were not beneficial to discover the families’ talents. The first period mainly focused on meetings to talk and discuss topics, write recommendations and proposals to the municipality, and organize partner meetings. The families were not used to this way of working, talking, and writing. Gradually, they became more involved and learned from the activities [25,26]. An ongoing transition towards an equal partnership, empowerment, growth in optimism and self-resilience appeared when the families were able to start doing, e.g., planning and organizing activities, and to see and celebrate their results [26]. The utilization of the families’ strengths, with a focus on partnering with families based on their passions while giving them the actual recognition for their input, was seen as important [27]. It may have created a growth mindset among the families. The idea that their abilities are not fixed and can be developed may have had an enhancing effect on their self-resilience and partnership [28]. Although all stakeholders may have struggled to navigate the middle at the start, their human capital flourished during the study period due to the enhanced levels of participation.The social networks of the families grew. Within this process, the broker ensured that the social support of the families was not only structural, when significant others were available, but also functional, when the families actually perceived the support as helpful and mutual [29]. The broker’s broad network made it relatively easy to connect the families with neighborhood partners and other citizens to create a stronger network to fall back upon. The broker was a trusted and familiar face to the families, since some of them already received individual support and because she had been active in the municipality for four years. Where the researcher struggled at the start to gain this level of trust, the broker succeeded in bringing the families, other citizens, and partners together, indicating the crucial role of the broker [30]. Although creating the structural networks was mainly done by the broker via a top-down approach, the functionality of the network, e.g., the shared mission and the companionship that arose and the fun they had together as described by the families, happened as a bottom-up process in which the families and partners collaborated and were empowered [26]. However, it is important to realize that the broker remained vital as a back-up for the network connections to be maintained [31,32]. Traditionally, governments tend to take a more top-down controlling perspective, making families often ‘afraid’ to collaborate or ‘suspicious’ [33,34]. The close connection with the municipality in Vaals Meets also provided the opportunity for the government to change its governance style into collaborative governance. The municipality became ‘just another partner’ for the families to work together with. The families mostly appreciated the input from the policy maker, and now and then visiting meetings and being present at small-scale activities was valued. Key concepts, such as accessibility, transparency, and trust seemed to be enhanced during the study period [35]. This might have reduced the gap between policy and practice. The top-down perspective with which proposals and activities of the families were ‘judged’ about ‘what are the benefits?’ made way for a more balanced, constructive approach with the policy maker as one of the supporting partners empowering the families, while helping them in making their plans realistic. Making them meet in the ‘middle’.A major strength of this study was the participatory design in which the researcher had the possibility to focus on an equal partnership with the families. This helped her to get more insight into the needs of the families, in addition to the needs already gathered during the photovoice study. Second, by retrospectively reconstructing all activities, key moments could be selected that directly or indirectly seemed to influence the partnership with the families. By creating the helicopter view using the timeline methodology, key lessons learned could be synthesized. Third, the inclusion of different data sources and the member checks with the broker, policy maker, and families during the study period were helpful in creating a complete overview of all activities and key lessons. Finally, although the number of families that took an active role in the partnership was relatively low, many more low-SES families were reached during the small-scale activities. One limitation is that we did not gather information about the number of families that might have been indirectly supported because of their partnership with the families in our project. Secondly, the partnership process was carried out with families, professionals, and other partners within only one municipality. The generalizability may be limited, since these partnerships are expected to be context specific. However, we tried to increase the generalizability by searching for and elaborating on the principles, functions, and key lessons to support future participatory approaches. Finally, we do realize that the RAF might seem to be a too basic tool, since it only includes four forms of capital. Though, we selected RAF because it really supported us to categorize what we learned from the partnership process and to stay close to the basic needs of the families found during the photovoice study. Besides, we also interpreted the four types of capital relatively broadly in order to ensure that we could capture the key lessons learned.In practice, many initiatives are undertaken in which partnering with the community is an important element. However, these local partnerships are often not evaluated, making the process behind successes and failures often a ‘gut feeling’. More participatory research is needed to better understand processes that underlie sustained partnerships in the area of community engagement [34].For practice, we encourage professionals working with citizens to focus on making the step to partnership with the community. Communities should not only be involved, collaboration and empowerment should be the aim of the partnership [26]. While working together on topics that are important to the target group, opportunities will arise to enhance their situation and improve their overall health and well-being. Partnership in developing, implementing, and evaluating activities can restore power imbalances and support a mutual interest among all partners and therefore attain shared benefits.This study showed the clear need for professionals to continuously and flexibly ‘navigate the middle’ between bottom-up and top-down approaches in creating equal partnerships with low-SES families. During the small-scale activities carried out together with and by the families in this study, we found six key lessons helpful in enhancing the partnership and finding this balance. The moment that the professionals were able to stop using professional work routines, became flexible, accommodated the talents of the families, and started doing, a shift in human, social, and political capital became evident. A supportive social network surrounding families, while maintaining professional back-up over time, was needed to enable the families to become more resilient and empowered. On a governmental level, the creation of an open, transparent, and involved communication with a focus on collaborative governance was seen as helpful in maintaining trust among the target group. In this study, the professionals were supported with finding an optimal partnership balance between the bottom-up input of the families’ talents that increased over time and the top-down input of the professionals’ expertise. Optimizing this balance seemed to reduce barriers for low-SES families, enabling them to participate. Conceptualization, L.P., S.K. and M.J.; methodology, L.P., S.K. and M.J.; software, L.P.; validation, L.P.; formal analysis, L.P.; investigation, L.P.; resources, L.P.; data curation, L.P.; writing—original draft preparation, L.P.; writing—review and editing, L.P., S.K. and M.J.; visualization, L.P.; supervision, S.K. and M.J.; project administration, L.P., S.K. and M.J.; funding acquisition, S.K. and M.J. All authors have read and agreed to the published version of the manuscript.The work was supported by FNO (Fonds NutsOhra) under grant 31963254N.We thank Veja Widdershoven for her support in transforming the timeline into Microsoft Visio.The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.Timeline.Key lessons learned for professionals working in community partnerships.

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+The aim of the present study is to verify the knowledge of risks and complications of oral piercings, and to observe the main complications associated with piercings, using a sample from central Italy of patients wearing intraoral piercings. Through piercing and tattoo studios selected randomly in Rome, Latina and Campobasso, and a tattoo and piercing convention in Latina, a group of 387 individuals with oral piercings were selected and asked to complete an anonymous questionnaire. After filling in questionnaires, 70 individuals of the 387 selected agreed to be visited to allow the observation of the integrity of their teeth and gums (especially close to the oral piercing), oral hygiene conditions, piercing cleaning, bad habits and gingival recession. Among the respondents, 46.8% said they had not been informed about these risks, 48.5% claimed not to clean the piercing, 70.6% stated that they had not been made aware of gingival problems that can arise, 60.4% subjects stated that they were not informed about the complications of piercings concerning teeth, 52.8% had insufficient oral hygiene conditions, 42% showed signs of generalised gingivitis, 20% had 3–4 mm recessions and 22% had tooth fracture(s) due to piercing. From this study, it emerged that oral piercings can represent a risk to oral health and that there is a widespread lack of awareness of the complications and correct methods of maintaining oral piercings. Periodic checks by both dentists and dental hygienists, for patients with oral piercings, could play a decisive role in preventing, intercepting and treating the complications that they can cause.Piercing is a practice that consists of piercing parts of the body such as ear lobes, nose, eyebrows, navel, nipples and genitals, to insert rings, earrings and piercings. Piercing is a custom that has tribal origins. Since ancient times, it has been used as a form of body decoration, both for purely aesthetic reasons and for ritual reasons, or to affirm one’s belonging to a particular class or ethnic group. Today, piercing is very popular among adolescents and young adults as a manifestation of self-expression [1,2]. Several authors have reported the occurrence of undesirable consequences, both minor and important, following skin or mucosal perforation, or due to the constant presence of piercings, both oral and perioral. In 2005, De Moor et al. [3] listed the oral and perioral complications related to the presence of tongue and lip piercings, declaring how fundamental the figure of the dentist was in convincing young people to remove these harmful ornaments [3]. In 2012, studies by Plessas et al. [4] and Ziebolz et al. [5] highlighted dento-periodontal complications caused by piercings in the oral cavity. From these two studies, it emerged how piercings on the tongue led to dental defects, with increased enamel abrasions and dental fractures, and with the presence of gingival recessions on a periodontal level [4,5]. Vozza I et al. [6] showed that out of a total of 225 young people who were asked to complete a questionnaire about the oral and systemic complications of oral piercings, 53.7% had not been informed about the risks associated with piercings [6]. The literature also reports how oral piercing can be a possible vector for the transmission of viruses such as HIV, HAV, HBV, HCV, HSV and the Epstein–Barr virus (EBV) [6], as well as causing bacterial pathologies such as Neisseria-induced endocarditis, Streptococcus viridans and Ludwig’s Angina [7]. Late complications can lead to bifid tongue, atypical trigeminal neuralgia, soft tongue tissue lesions and hypertrophic keloid lesions [7]. The aim of the present study is to verify the knowledge of risks and complications of oral piercings in a sample from central Italy of patients wearing intraoral piercings, as well as to observe the main complications associated with piercings. In the present study, through randomly selected piercing and tattoo studios in Rome, Latina and Campobasso, and a tattoo and piercing convention in Latina, a group of 387 individuals with oral piercings were selected and asked to complete an anonymous questionnaire. Information was sought on their knowledge of oral complications related to the insertion and the presence of piercings in the oral cavity. All the individuals that agreed to fill the questionnaire received a consent form and a cover letter that provided information on the objective of the study. Selection of the patients was dependent only on attendance at the studios or the convention previously cited and socioeconomic status, but not on race, religious beliefs or education.The questionnaire provided was available both in print and online. Names were not recorded on the questionnaire, to ensure anonymity. The study protocol complied with the guidelines of the 1975 Declaration of Helsinki. The ethical authorization was granted by the Research and Ethics Committee of the Sapienza University of Rome.After filling in the questionnaires, 70 healthy individuals of the 387 selected agreed to be visited. The 70 subjects (18.1%) comprised 53 women and 17 men and were aged between 18 and 40.The visit, carried out by a single previously trained and calibrated operator at the ASL clinic in Cisterna (Latina), consisted of observing the integrity of teeth and gums, especially close to oral piercings; oral hygiene conditions; piercing cleaning; bad oral habits; and gingival recession. To avoid potential information bias, a clarification was made to the participants that the study would not have any impact on the eventual treatment they sought. Intraoral examinations on all patients were done with the naked eye, using an overhead operating light and a standard mouth mirror. Piercing-related pathology (i.e., tooth fractures, inflammation, infections and chronic lesions) were recorded. The information obtained from the questionnaires was captured in an electronic database, which was verified and validated. Responses to the questions in each category were summarised by calculating the percentages of responses in the respective categories.By completing the questionnaire, it was possible to gather a lot of useful data from the 387 selected subjects who participated in the study. There was a higher percentage of individuals aged between 20 and 29 who submitted the questionnaire (64.4%), while 21.1% of individuals were aged between 16 and 19, and only 13.9% were aged between 30 and 39 (Table 1).Of the 387 selected subjects, 189 (48.8%) reported having a high school diploma, 91 (23.5%) having graduated, 55 (14.2%) having attended a school environment until the age of 14, and 52 (13.5%) having other diplomas/qualifications. Among the other information obtained from the questionnaire, it emerged that 58% of the subjects claimed to be habitual smokers, while in relation to alcohol consumption, 80 subjects (20.6%) declared to be abstainers; 259 (66.9%) claimed to drink alcohol occasionally; and, finally, 48 (12.5%) declared they used alcohol regularly.It was also interesting to know if any of the subjects had ever undergone orthodontic treatment—228 (59%) subjects replied that they had undergone orthodontic treatment, while 159 (41%) subjects declared they had not.When patients were asked for information about oral hygiene habits, 219 (56.6%) of the subjects declared that they brushed their teeth at least twice a day; 119 (30.8%) subjects claimed to brush their teeth three times a day; and, finally, 46 (11.9%) subjects admitted to brushing their teeth only once per day. As for the use of dental floss, our survey showed that 307 (79.4%) subjects did not use dental floss, while 80 (20.6%) subjects claimed to use it regularly.Lastly, the questionnaire focused on the piercings. The results showed that 202 subjects (52.2%), in addition to oral piercings, also had piercings in other areas of the body, while the remaining 185 (47.8%) confirmed that they only had oral piercings. It was in the interest of this study to know where the selected subjects got their piercing done—247 (64%) subjects decided to go to a tattoo and piercing studio; 66 (17%) got their piercing done in a domestic environment; 38 (9.8%) opted for a jewellery store; and, finally, 21 (5.4%) performed self-piercing.Very important information collected from the questionnaire concerned the reason why these young people decided to get the piercing. Expressing their personality was reported by 117 (30.2%), 170 for aesthetic reasons (43.9%), 51 for erotic reasons (13.2%), 45 for fashion (11.6%) and four because of the influence of friends (1%). Furthermore, 53.2% said they were informed about the complications of piercings on their general health, while 46.8% said they had not been informed about them (Table 1).When asked about cleaning of the piercing, 188 subjects (48.5%) claimed not to clean the piercing, while 199 (51.5%) stated that they do so regularly (Table 2). With regard to the methods used for cleaning the piercing; 155 subjects (40%) used a brushing technique and an antimicrobial solution; 124 (32%) declared only using the antimicrobial solution; and, finally, 108 (28%) confirmed only using the brushing technique. Regarding the knowledge of possible gingival complications due to piercings, 273 subjects (70.6%) stated that they had not been made aware of gingival problems that can arise, while 114 subjects (29.4%) confirmed that they had been made aware of this. With regard to the dental field, 234 (60.4%) subjects stated that they were not informed about the complications of piercings concerning teeth, while 153 (39.6%) subjects claimed to have been informed of these complications (Table 2). Alongside completing the questionnaire, 70 subjects aged between 18 and 40 with one or more oral piercings were visited. During the visits, we wanted to consider the areas where the piercing was located and their oral hygiene conditions. The age group with the highest number of subjects visited was those aged 20–29, with a percentage of 80%; followed by the 30–39 age group, with a percentage of 10%; then the 16–19 age group, with a percentage of 7.5%; and, finally, the 40–49 age group with a percentage of 2.5%. Regarding the location of oral piercings, it should be pointed out that some subjects had more than one piercing present in the oral cavity. Our visits showed that 42 patients had piercings on their tongue, 17 on their lip (lower or upper) and 20 on their frenulum. We also wanted to identify whether the subjects visited had bad habits. All the sample patients taken into consideration had admitted to having one or more of the following bad oral habits: smoking, nail biting, playing with oral piercing using their tongue or making it bang against their teeth and lip biting. More precisely, 49 subjects reported regular smoking (70%), 40 (57.1%) confirmed constantly playing with the oral piercing, 24 subjects (34.3%) declared biting their nails and 25 admitted biting their lips (35.7%). When the oral hygiene condition of each patient were examined, 15 subjects (21.4%) showed good oral hygiene condition, 18 (25.7%) barely sufficient, and 37 (52.8%) had insufficient oral hygiene condition. Precisely for this reason, most of the subjects visited had gingivitis, either localised or generalised. In 31 subjects (44%), the presence of localised gingivitis was observed, almost always close to their piercing, while 29 patients (42%) showed signs of generalised gingivitis. Only 10 patients did not present the classic signs of gingival inflammation (14%). Table 2 Another complication evaluated during visits was the presence of gingival recession. Almost all subjects examined showed at least one gingival recession. Recessions of about 1–2 mm were found in 46 subjects (65%); 3–4 mm recessions in 14 subjects (20%); and, finally, 10 subjects (15%) showed gingival recessions of 5–6 mm (Table 3). A part-gingival recession was found (Figure 1), as well as other oral complications such as a tongue lesion and thickening of the frenula (Figure 2). Among the subjects visited, 22% showed a fractured tooth (Figure 3). The fractures, as reported by patients, were caused by continuous playing with the piercing, which led to dental elements being repeatedly hit. The teeth most compromised by the presence of piercings were the molars, but incisors and premolars were also seriously damaged.The results of our study suggest that, despite the increasing number of young people becoming interested in body art, there is still not enough awareness of the complications that piercing involves. As demonstrated in a study by Vozza I et al. [8] in 2015, these problems are still not known well by the piercers themselves, whose hours of professional training differ from region to region. No correlation between age or school education and oral complications occurred in our study. From the data found through the questionnaire, it emerged that many piercers do not always inform their clients about what may be the general complications related to piercing. Specifically, many of them are unable to tell customers about the complications that piercings can cause to teeth, such as fractures, and gums, such as gingival recession or frenula thickening, as well as how to clean them, which is of vital importance in order to prevent gingivitis or periodontitis [9]. Consequently, the dentist and the dental hygienist have to deal with the task of informing their patients with piercings of the aforementioned information. The importance of the dental team was evaluated by Maspero C. et al. [10] in 2014. Our study confirmed information found in literature [11,12,13,14] describing how oral piercings are the cause of a series of complications, such as dental abrasions, dental fractures, gingival recessions and loss of attachment of periodontal tissues, but also problems related to temporomandibular joint, as stated by Mejersjö in 2016 [15]. It is therefore necessary to establish education programs in schools between dentistry students and dentists themselves, in order to prevent the aforementioned complications reported, respectively, by Silk H et al. [16], Junco P et al. [17] and McGeary SP et al. [18].From this study, it emerged that oral piercings can represent a risk to oral health, as found by Maitland I et al. [19]. There is a widespread lack of awareness regarding the complications and correct methods of maintaining oral piercings, as confirmed in the literature, among dental students [20]. Compared to our previous study on adolescents and young adults [6], lack of knowledge was surveyed among older individuals, comparing results of questionnaires to patients wearing oral piercings and directly visited. In light of our research, it is clear that projects regarding oral health and prevention, together with periodic checks by both dentists and dental hygienists, for patients with oral piercings can play a decisive role in preventing, intercepting and treating the complications that they can cause. Further studies will be necessary in order to establish a statistical correlation between oral piercing and oral complications that consider age, sex and education.Conceptualization, I.V. and L.O.; methodology, F.C., I.V., L.O.; investigation, C.S. and V.G.; data curation, C.S., V.G.; writing—original draft preparation, F.C. and D.C.; writing—review and editing, F.C. and D.C.; supervision, I.V. and L.O. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors declare no conflicts of interest.Clinical gingival recession.Tongue lesion and thickening of frenula.Fractured upper central incisor.Characteristics of the sample, resulting from the administration of 387 questionnaires.Level of knowledge of piercing management, resulting from the administration of 387 questionnaires.Periodontal conditions of the sample collected after clinical examination of 70 subjects.

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+The beneficial effect of physical activity (PA) on the brain has been well established. Both acute and regular PA can boost a range of cognitive functions and enhance mood and mental health. Notably, the effect of acute PA on the brain and cognitive functions is generally found to be dose-dependent, in terms of both the amount and intensity of the exercise episode. In contrast, in the case of regular PA, the literature has primarily focused on the amount of exercise, and limited studies have assessed the influence of the exercise intensity. Since PA in higher intensity causes more extensive, more powerful, and longer-lasting neurobiological changes, it may prove more beneficial to cognitive functions and mental health. In the present study, we set out to test this hypothesis by employing a battery of questionnaires and laboratory tests with a sample of young adults. We found that more frequent vigorous- and moderate-intensity PA rather than walking (considered low to moderate intensity) was associated with better cognitive and mental health measures. Meanwhile, compared with no moderate- to vigorous-intensity physical activity (MVPA) at all, as few as 1~2 days per week (lasting at least 10 min each time) of MVPA was associated with a variety of benefits, particularly related to coping with challenging situations. In light of the neurobiological literature, the present study speaks to the value of moderate- to vigorous- rather than low-intensity PA in enhancing cognitive functions and mental health.The beneficial effect of physical exercise or physical activity (PA) on the brain has been well established. Both acute and regular PA can boost a range of cognitive functions and enhance mood and mental health [1,2,3,4,5]. For instance, a single bout of aerobic exercise such as treadmill running enhances working memory [6], inhibitory control capacity [7], attentional orienting [8], creativity [9], and positive moods [10]. Regular PA conducted several times a week, such as running and popular sports, can promote cognitive development [11,12], slow cognitive aging [13], buffer stress response [14], and prevent [15] and treat [16] depression.Furthermore, the beneficial effect of PA is generally considered dose-dependent, such that greater amount and higher intensity of exercise is associated with more enhanced outcomes, for instance, cognitive functions [17]. However, a closer look at the literature suggests this dose-dependent effect in terms of both amount and intensity has only been formally tested in acute but not regular PA (see [17,18] on cognitive functions; see [19] on adult neurogenesis in animals, i.e., mice). In the case of regular PA, the literature has primarily focused on the amount (or frequency and duration) of exercise (see [20] on cognitive functions, i.e., dementia; see [14] on stress resilience; see [15,21,22] on depression or general mental health), and only limited studies have assessed the influence of exercise intensity (see [23,24] on depression).Since PA performed in higher intensity causes more extensive, more powerful, and longer-lasting neurobiological changes, it may prove more beneficial to brain functions. Indeed, a single bout of vigorous- rather than low-intensity cycling has been reported to increase the peripheral level of brain-derived neurotrophic factor (BDNF) [25]. BDNF is a member of the neurotrophin family of growth factors that support the production, growth, differentiation, and survival of neurons. Peripheral BDNF can pass the brain–blood barrier and benefits the brain through, for instance, enhancing neurogenesis in the dentate gyrus of the hippocampus [5]. Similarly, an episode of moderate to vigorous running but not low-intensity walking increases circulating endocannabinoids [26], which pass the brain–blood barrier, act as a neurotransmitter believed to contribute to “runner’s high”, and have analgesic and anti-anxiolytic effects ([26]; see [27] for a study conducted in mice). Lastly, PA at vigorous intensity is more effective at increasing aerobic capacity or fitness [28], the latter being linked to higher cognitive functions [29] and lower stress response [30] (for a review, see [4]).Therefore, we hypothesized that frequent PA at moderate and vigorous rather than low intensity exerts greater benefit to cognitive functions and mental health. In the present study, we set out to test this hypothesis in a sample of young adults using a battery of questionnaires and laboratory tests. Investigating this hypothesis also allows us to propose more specific recommendations or guidelines for public health promotion in young adults.This research was part of a larger study, the aim of which was to predict mental health status using high-level brain functions. Data collected at baseline of the study were used for analysis here. The study was approved by the Institutional Review Board of Yamaguchi University Hospital (approval code: H2019-043-2). Participants were recruited via numerous posters displayed in the university community. The inclusion criteria were being 20–39 years old at the time of the visit, and the exclusion criteria were (a) having any self-reported mental health diseases, (b) receiving medical examinations due to suspicion of any mental health diseases, (c) being suspected of mental health diseases by the research staff and then diagnosed as having a mental health disease by the Mini-International Neuropsychiatric Interview conducted by a psychiatrist, or (d) being unable to answer the questionnaires and perform the laboratory tests for this study due to severe physical conditions or other reasons. Fifty-eight subjects agreed to participate in this study and provided written informed consent after receiving a detailed explanation of the study.Subjects first answered questions about their demographic characteristics, including gender, age, occupation, and educational level.To evaluate PA, we used the short-form International Physical Activity Questionnaire (IPAQ) [31]. IPAQ measures the number of days and duration of PA that was conducted for at least ten minutes each time at vigorous intensity, moderate intensity, and walking during the last seven days, respectively. Here, PA at vigorous intensity refers to those that take hard effort to conduct and make people “breathe much harder than normal”. Examples include heavy lifting, fast bicycling, and singles tennis. PA at moderate intensity refers to those that take moderate effort and make people “breathe somewhat harder than normal”. Examples include carrying light loads, swimming at a regular pace, and doubles tennis. Walking is evaluated separately from PA at vigorous and moderate intensity in IPAQ, but is generally considered low to moderate in intensity.In the present study, we employed two different methods generated by the IPAQ to evaluate PA. First, we categorized the participants into one of three levels of PA, Low, Moderate, or High, based on one summary indicator, total weekly PA Metabolic Equivalents (MET-minutes, hereafter referred as total PA), as suggested by the developers of the IPAQ. Total PA was calculated by weighting the reported minutes per week within each activity category by a MET energy expenditure estimate assigned to each activity category (8 for vigorous, 4 for moderate, and 3.3 for walking). High PA level is defined as meeting either of two criteria: (a) vigorous intensity activity on >3 days/week and accumulating at least 1500 MET-minutes/week; or (b) >7 days of any combination of walking, moderate-intensity, or vigorous-intensity PA achieving at least 3000 MET-minutes/week. Moderate PA level is defined as meeting any of the following three criteria: (a) 3 days of vigorous-intensity activity of at least 20 min/day; (b) 5 days of moderate-intensity activity or walking of >30 min/day; or (c) 5 days of any combination of walking, moderate-intensity or vigorous-intensity PA achieving at least 600 MET-minutes/week. Those who neither meet the Moderate nor the High criteria were categorized as Low PA level.Second, we employed the intensity-specific frequency, that is, the number of days per week performing activities at each intensity, respectively, in our analysis. Although the first method of evaluating PA (in terms of Low, Moderate, and High PA levels) has been widely used in the literature, it is actually not a very good representative of exercise intensity. Subjects who walk and do moderate PA several days a week and much time each day without doing much vigorous activity can be categorized to High PA level. Therefore, to differentiate the effect of PA at different intensities, we also employed the intensity-specific frequency in our analysis. Another strength of this method is that it allows us to give specific recommendations about the minimum days of intensity-specific PA per week that can bring cognitive and/or mental benefits, the approach of which has been frequently employed in the literature [14,20]. To give the general public specific recommendations, we also combined the frequency of moderate- and vigorous-intensity PA to form a new measure, the frequency of moderate- to vigorous-intensity physical activity (MVPA).Creativity. We used a paper-based quiz composed of insight tasks to evaluate creativity. This included two matchstick arithmetic problems [32], the nine-dot puzzle, and a coin puzzle [33]. Subjects had 5 minutes to complete each task (the two matchstick arithmetic problems were treated as one task). After completing the quiz, subjects were asked whether they had seen any of the tasks. It was found that seven subjects have read the first matchstick arithmetic problem and all but two of the 58 subjects correctly solved this problem. Therefore, the first matchstick arithmetic problem was deleted from the quiz. The total number of solved tasks of the remaining three was used as the creativity score (range 0~3). After excluding subjects that have read any of the remaining tasks, data of 49 subjects were available for the final analysis.Working memory. We used a computer-based n-back task (n = 1, 2) to assess working memory. The task was programed by Jörn Alexander Quent after [34] using MATLAB and Psychtoolbox 3 (the code is available at [35]). In this task, participants were shown a sequence of visual stimuli (random shapes) and had to judge each time whether the current stimulus was identical to the one presented n positions back in the sequence. The shapes were shown in black and presented centrally on a gray background for 500 milliseconds (ms) each, followed by a 2500 ms interstimulus interval. Participants were asked to press a predefined key for targets as fast as they can, and no response was required for non-targets. Participants were tested on 1- and 2-back levels in that order, with each level presented for two consecutive blocks, and one block consisted of 20 + n stimuli and contained 6 targets and 14 + n non-targets each. Following the signal detection theory, a discriminability score indicating the overall performance of subject at discriminating targets from non-targets was calculated for 1- and 2-back separately for each subject [36]. The discriminability score (d) and response time (in ms) were used for data analysis.Mindful attention. We used the Japanese version [37] of the Mindful Attention Awareness Scale (MAAS) [38]. The MAAS is a 15-item (1–6 Likert scale) self-report questionnaire assessing individual differences in the frequency of mindful states over time.Trait measures: the following trait-like dimensions of mental health were evaluated.Emotional contagion. We used the Japanese version [39] of the Emotional Contagion Scale (ECS) [40], a 15-item self-report questionnaire, to assess individual differences in susceptibility to emotional contagion of love, happiness, anger, and sadness.Emotion regulation. We used the Japanese version [41] of the Emotion Regulation Questionnaire (ERQ) [42], a 10-item self-report questionnaire, to assess individual differences in their use of two emotion regulation strategies, reappraisal and suppression. Reappraisal, or cognitive reappraisal, refers to a form of cognitive change that reinterprets a potentially emotion-eliciting situation. Suppression, or expressive suppression, refers to a form of response modulation that inhibits ongoing emotion-expressive behaviors.Coping. We used the Japanese version [43] of the Brief Coping Orientation to Problems Experienced Inventory (COPE) [44], a 28-item self-report questionnaire, to assess individuals’ tendency to employ 14 coping strategies, including active coping, planning, positive reframing, acceptance, humor, religion, using emotional support, using instrumental support, self-distraction, denial, venting, substance use, behavioral disengagement, and self-blame.Behavioral inhibition and behavioral activation. We used the Japanese version [45] of the Behavioral Inhibition System and Behavioral Activation System scales (BIS/BAS) [46], a 24-item self-report questionnaire, to assess four biological personality traits of BIS, drive, fun seeking, and reward responsiveness. The BIS measures individuals’ response to aversive stimuli such as anxiety, fear, and worry. Drive measures the degree to which individuals pursue appetitive goals. Fun seeking measures the tendency to seek new, potentially rewarding experiences. Reward responsiveness measures positive responses to reward or preferred outcomes.Trait anxiety: We used the Y-2 subscale of the Japanese version of the State–Trait Anxiety Inventory (STAI) to assess trait anxiety. Note that the two subscales of the STAI were administered together following Depression, see below.State measures: the following state-like dimensions of mental health were evaluated.Depression. We used the Japanese version [47] of the Beck Depression Inventory-II (BDI-II) [48], a 21-item self-report questionnaire, to assess a range of depressive symptoms that occurred within the past two weeks.State anxiety. We used the Y-1 subscale of the Japanese version [49] of the State–Trait Anxiety Inventory (STAI) [50], a 40-item self-report questionnaire, to assess state and trait anxiety.Perceived stress. We used the Japanese version [51] of the Perceived Stress Scale (PSS) [52], a 10-item self-report questionnaire, to assess perceived psychological stress in the past month.Psychological wellbeing. We used the Japanese version [53] of the Ryff’s Psychological Well-being Inventory [54], an 84-item self-report questionnaire, to assess six domains of psychological wellbeing: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance. Autonomy measures self-determination and independence. Environmental mastery measures the sense of mastery and competence in managing one’s environment. Personal growth measures the feeling of continued development. The domain positive relations with others evaluates to what extent one has warm, satisfying, and trusting relationships with others. Purpose in life evaluates to what extent one has goals in life and a sense of direction. Self-acceptance evaluates to what extent one possesses a positive attitude towards the self.The statistical analysis was done with IBM SPSS Statistics 25.0 (IBM Corp. in Armonk, NY, USA) and MATLAB R2018b (The MathWorks, Inc., Natick, MA, USA). Pearson correlation analysis was used to evaluate associations between exercise measures (i.e., intensity-specific frequency) and other variables (age, cognitive functions, and mental health). The Chi-square test was used to evaluate whether there was an association between PA level and gender and between PA levels and the two frequencies of MVPA. Linear regression was used to evaluate to what extent exercise measures can predict outcome variables, with or without adjusting for covariates such as gender and age. One-way Analysis of Variance (ANOVA) was used to determine whether there were any differences in outcome variables between subjects at the three PA levels (Low, Moderate, and High), with or without gender and age as covariates (conducted as a general linear model). Bonferroni adjustment was used for post hoc comparison. Student’s t-test was used to compare differences between two groups means. The level of statistical significance was set at p < 0.05.The sample consisted of 24 male and 34 female subjects, with a mean age of 22.4 years (standard deviation (SD) 2.40 years). Fifty-six (98.3%) were undergraduate students, 1 was a graduate student, and 1 was working in a hospital as a healthcare provider. Regarding PA, cognitive functions, and mental health, the score (Mean ± SD) of each measure is shown in Table 1.Subjects categorized as Low, Moderate, and High PA level numbered 14, 29, and 15, respectively. Subjects conducted 3.64 ± 2.40 days/week of walking, 1.50 ± 1.74 days/week of moderate intensity PA, and 1.26 ± 1.62 days/week of vigorous intensity PA, all of which lasted for at least 10 min each time. As shown in Figure S1, males conducted vigorous intensity PA more often than females (2.00 ± 1.98 vs. 0.74 ± 1.05 days per week, t(32.23) = 2.859, p < 0.01). No other significant difference in or association with exercise measures was found for gender and age (see Figures S1 and S2).We first compared the outcome variables across different PA levels using one-way ANOVA and found four significant differences: active coping (F(2,55) = 3.91, p = 0.026) and behavioral disengagement (F(2,55) = 4.90, p = 0.011) for coping, BAS drive (F(2,55) = 6.66, p = 0.003), and personal growth (F(2,55) = 3.71, p = 0.031) of psychological wellbeing. As shown in Figure 1, post hoc comparisons suggested that compared with those at Low PA level, subjects at High PA level had a significant higher level of active coping, BAS drive, and personal growth, and low level of behavioral disengagement (p < 0.05). Similarly, compared with those at Moderate PA level, subjects at High PA level had a significant higher level of BAS drive (p < 0.05). PA level-wise scatter plots of other nonsignificant outcome variables are available in Figure S3.The group difference for behavioral disengagement (F(4,53) = 2.84, p = 0.033 for the model, F = 4.69, p = 0.013 for PA levels), BAS drive (F(4,53) = 4.10, p = 0.006 for the model, F = 7.74, p = 0.001 for PA levels), and personal growth (F(4,53) = 3.97, p = 0.007 for the model, F = 4.85, p = 0.012 for PA levels) across the three PA levels remained significant after controlling gender and age by fitting a general linear model.We confirmed there was a significant correlation between the frequency of walking and the frequency of vigorous-intensity activity (r = −0.288, p < 0.05). More days of walking was associated with fewer days of vigorous-intensity activity per week. Given this correlation, we next entered the frequency of each intensity activity into a linear regression model to determine what intensity activities contribute to the outcome variables while controlling other intensity activities.We fitted linear regression models with only the frequencies of different intensity activities as independent variables (Model 1) and including gender and age as covariates (Model 2). Model 1 could significantly predict six outcome variables, including 2-back d of the 2-back working memory task, active coping, denial, and behavioral disengagement of coping, and autonomy and personal growth of psychological wellbeing. Four remained significant after controlling gender and age. The results are shown in Table 2.Therefore, higher frequency (i.e., more days per week) of vigorous-intensity PA predicts more active coping, less behavioral disengagement, greater autonomy, and increased personal growth. Whereas higher frequency of moderate intensity PA predicts less behavioral disengagement, higher frequency of walking predicts more denial with a trend towards significance. Notably, in predicting personal growth, the standardized coefficient of the frequency of vigorous intensity PA was bigger than that of age (0.404 vs. 0.270). The results of other nonsignificant outcome variables for model 1 and model 2 are shown in Table S1.To give the general public specific recommendations, we created another measure, that is, the frequency of MVPA. The number of subjects conducting 0 to 7 days of MVPA per week was 13, 7, 9, 6, 9, 6, 5, and 3 in that order.We first checked the correlation between the frequency of MVPA and outcome variables, and the results are shown in Table 3. As can be seen, as the frequency of MVPA increased, subjects’ performance on the 2-back task became better, they used active coping and acceptance more often and denial and behavioral disengagement less often, showed greater drive and responsiveness to rewarding outcomes, and had fewer state anxiety symptoms and increased personal growth.As the association between the frequency of MVPA and outcome variables seems linear, we next asked what is the minimum days that subjects have to conduct MVPA per week in order to make a difference in any outcome variables. As the number of subjects conducting 0 to 7 days of MVPA per week was 13, 7, 9, 6, 9, 6, 5, and 3 in that order, we combined subjects conducting 1 and 2 days of MVPA per week to a single group (i.e., 1~2 days of MVPA per week, n = 16) and compared it with subjects conducting 0 days of MVPA per week (n = 13). As shown in Figure S4, the two groups did not differ in their total PA (883.6 ± 929.3 vs. 1770.2 ± 1880.8 MET-minutes/week, t(27) = −0.203, p = 0.840). Nor did they differ in their proportion of different PA levels (χ² (2) = 0.842, p = 0.656).On average, subjects conducting 1~2 days of MVPA per week did 0.50 ± 0.63 days of vigorous-intensity PA (45.63 ± 67.13 min/day), 1.06 ± 0.85 days of moderate-intensity PA (66.25 ± 69.37 min/day), and 3.75 ± 1.92 days of walking (59.06 ± 62.96 min/day). In contrast, subjects conducting 0 days of MVPA per week walked 4.77 ± 2.62 days per week (49.46 ± 40.07 min in total).We then compared the outcome variables of these two groups using Student’s t-test. Outcome variables that demonstrated a significant between-group difference (p < 0.05) were plotted in Figure 2. As can be seen, compared with those with no MVPA, subjects conducting 1~2 days of MVPA were more easily affected by happiness, more likely to use reappraisal for emotion regulation, more likely to use active coping, positive reframing, and religion, and less likely to use behavioral disengagement for dealing with challenging situations.In the present study, we employed two different methods to evaluate PA, PA levels and intensity-specific frequency. Our results showed that compared with those at Low PA level, subjects at High PA level used active coping more often and behavioral disengagement less often, and demonstrated greater drive for rewards and more advanced personal growth. Most of these results, except active coping, remained significant after controlling gender and age. These results suggest that a greater amount of PA is associated with more matured psychological coping strategies in the face of negative situations [55,56], enhanced appetitive motivation, which is often compromised in psychiatric disorders [57,58], and superior psychological development and wellbeing [59].However, the categorization of PA levels based on the proposed criteria is not without its limitations. As we have introduced, High PA level is defined as meeting either of two criteria: (a) vigorous-intensity activity on >3 days/week and accumulating at least 1500 MET-minutes/week; or (b) >7 days of any combination of walking, moderate-intensity, or vigorous-intensity PA achieving at least 3000 MET-minutes/week. From the categorization criteria, we could infer that vigorous-intensity PA in particular may be responsible for the above benefits, although one cannot be sure if that is the case. Individuals may be categorized as High PA level simply due to their greater amount of moderate-intensity PA and walking, with few vigorous-intensity PA. In other words, we cannot tease apart the contribution of PA at different intensities. This limitation is further emphasized by our observation that the frequency of walking is negatively associated with that of vigorous-intensity PA. Therefore, the sensitivity of PA levels in capturing the true amount of PA may have been compromised and confounded by combining the measure of walking with that of vigorous-intensity PA. In order to investigate what intensity PA contributes greater benefits, it is necessary to employ intensity-specific measures.For this purpose, in the present study, we employed intensity-specific frequencies, that is, days conducting one specific intensity of PA per week. After controlling gender and age, we found it was vigorous-intensity PA that brought various psychological benefits. More frequent vigorous-intensity PA was associated with more frequent use of active coping and fewer use of behavioral disengagement for coping with challenging situations. It was also associated with greater self-perceived autonomy and personal growth. Notably, in predicting personal growth, the contribution of the frequency of vigorous-intensity PA was much bigger than that of age (standardized coefficient 0.404 vs. 0.270). More frequent moderate-intensity PA was also associated with fewer use of behavioral disengagement. In contrast, the frequency of walking was not associated with any of the outcome variables we investigated.These results confirm our hypothesis and are consistent with the neurobiological literature that moderate- to vigorous- rather than low-intensity PA causes extensive, powerful, and long-lasting physiological changes, which account for the cognitive and psychological enhancing effects of PA [25,26,27]. Therefore, our results go beyond previous reports that regular PA enhances mental health [14,15,21,22] by specifying that it is moderate- to vigorous-intensity PA, rather than low- to moderate-intensity walking, that is responsible for this benefit.To give the general public specific recommendations on the frequency of PA, we combined the frequency of moderate and vigorous intensity PA and created a new measure, the frequency of MVPA. With MVPA, we observed significant associations with cognitive functions and state anxiety. Thus, individuals with more frequent MVPA performed better on a 2-back working memory task. They could better differentiate targets from non-targets. Meanwhile, they also demonstrated fewer symptoms of state anxiety. These results are in line with a large amount of reports that PA conducted regularly enhances cognitive functions and mental health [11,12,13,14,15,16]. Rather than low- to moderate-intensity walking, our results indicate that it is MVPA that exerts these benefits.We next compared subjects who conducted 1~2 days per week (lasting at least 10 minutes each time) of MVPA with those with no MVPA to investigate whether this minimum frequency of MVPA can bring any cognitive and/or mental health benefits. Compared with those with no MVPA, we found that subjects conducting 1~2 days of MVPA were more easily affected by happiness, more likely to use reappraisal for emotion regulation, more likely to use active coping, positive reframing, and religion, and less likely to use behavioral disengagement for dealing with challenging situations. In other words, mere 1~2 days of MVPA per week may bring people more positive emotions and more mature coping strategies [55,56,60].Note that subjects conducting 1~2 days of MVPA did not differ from those conducting no MVPA in terms of their total PA (MET-minutes/week) or proportion of different PA levels. This again supports the argument that rather than the total amount, more intense PA is preferred. In our study, on average, subjects conducting 1~2 days of MVPA did 0.5 days × 45.63 min/day = 22.82 min of vigorous- and 1.06 days × 66.25 min/day = 70.23 min of moderate-intensity PA per week. This amount of PA is below the level recommended by the World Health Organization for adults [61] of doing at least 150 min of moderate-intensity, or 75 min of vigorous-intensity PA per week, or any equivalent combination of the two.A limitation of our study is the employment of the short- instead of the full-form IPAQ to evaluate PA. Consequently, we could not make differentiation of various PA domains, that is, PA conducted during work versus during transportation, for housework, or for recreation. Previous research suggests that different domains of PA may have distinct effects on mental health [62]. A second limitation of our study is our sample size is rather small and we conducted multiple tests for some forty dependent variables. Given the explorative nature of our study, we did not perform corrections of the alpha level to control the false discovery rate, and this may have increased the number of false positives. Future research with bigger sample size is required to validate our results by further correcting the alpha level based on established procedures.A third limitation is the cross-sectional design of this study. The cross-sectional design does not allow us to make firm causal inferences on the associations we identified. It is possible that subjects with higher cognitive functions, more mature coping strategies, and better mental health may be more likely to engage in MVPA. Furthermore, our sample was primarily university students, which does not allow us to generalize our findings to older people or people from other settings. Future research should investigate whether our findings hold in a prospective context and other settings and whether interventions with as few as 1~2 days of MVPA cause meaningful cognitive and mental health changes.In a sample of young adults, more frequent vigorous- and moderate-intensity PA rather than walking (considered low to moderate intensity) was associated with better cognitive and mental health measures. Meanwhile, compared with no MVPA at all, as few as 1~2 days per week (lasting at least 10 minutes each time) of MVPA was associated with a variety of benefits related particularly to coping with challenging situations. In light of the neurobiological literature, the present study speaks to the value of moderate- to vigorous- rather than low-intensity PA in enhancing cognitive functions and mental health.The following are available online at https://www.mdpi.com/1660-4601/17/2/614/s1, Figure S1: Gender differences in exercise measures; Figure S2: Associations between age and exercise measures; Figure S3: Comparison of outcome variables across different PA levels; Figure S4: Comparison of total PA and the proportion of different PA levels between subjects conducting 1~2 days of MVPA per week and those conducting no MVPA; Table S1: Additional linear regression results using intensity-specific frequencies to predict cognitive functions and mental health.Conceptualization, C.C. and S.N.; methodology, C.C. and K.H.; software, T.N., I.K., and C.C.; validation, I.K. and K.H.; formal analysis, T.N. and C.C.; investigation, T.N., I.K., C.C., and M.H.; resources, C.C., T.M., and M.H.; data curation, T.N., I.K., C.C. and M.H.; writing—original draft preparation, T.N., I.K., and C.C.; writing—review and editing, T.N., I.K., C.C., T.M., K.H., H.L., H.Y., and S.N.; visualization, I.K., C.C. and H.L.; supervision, C.C.; project administration, C.C. All authors have read and agreed to the published version of the manuscript.This research received no external funding.C.C. is the author of Fitness Powered Brains. The other authors declare no conflict of interest related to this study.Comparison of active coping (a), behavioral disengagement (b), BAS drive (c), and personal growth (d) across different PA levels. n = 14, 29, and 15 for Low, Moderate, and High PA level, respectively. Each circle represents one data point from a single subject. Color indicates different PA levels. The black line connects the three PA levels at their mean value, and the vertical bar drawn on the mean value represents SD of subjects at that PA level. — indicates a significant between-group difference (p < 0.05) as suggested by post hoc comparisons. PA, physical activity; BAS, Behavioral Activation System.Comparison of happiness (a), reappraisal (b), active coping (c), behavioral disengagement (d), positive reframing (e), and religion (f) between subjects who conducted 0 (n = 13) versus 1~2 days (n = 16) of MVPA per week. Happiness is a submeasure of emotional contagion (ECS); reappraisal is a submeasure of emotion regulation (ERQ); the remaining are submeasures of coping (COPE). Each circle represents one data point from a single subject. Color indicates different groups. The black line connects the two groups at their mean value, and the vertical bar drawn on the mean value represents SD of subjects in that group. Student’s t-test, all p < 0.05 except happiness, p = 0.056 and reappraisal, p = 0.050. MVPA, moderate- to vigorous-intensity physical activity.The score of each measure in this study. n = 49 for creativity and n = 58 for all other measures.SD, standard deviation; PA, physical activity; MAAS, Mindful Attention Awareness Scale; ECS, Emotional Contagion Scale; ERQ, Emotion Regulation Questionnaire; COPE, Coping Orientation to Problems Experienced Inventory; BIS/BAS, Behavioral Inhibition System and Behavioral Activation System scales; BDI-II, Beck Depression Inventory-II; STAI, State–Trait Anxiety Inventory; PSS, Perceived Stress Scale; PWI, Psychological Well-being Inventory.Linear regression results using intensity-specific frequencies to predict measures of coping and psychological wellbeing.1 Unstandardized and standardized coefficients are shown outside of and in the brackets, respectively. 2 Male and female are coded as 1 and 2, respectively. ** p < 0.01; * p < 0.05; + p < 0.06. Significant standardized coefficients are shown in bold.Pearson correlations between the frequency of MVPA (moderate- to vigorous-intensity physical activity) and outcome variables. n = 49 for creativity and n = 58 for all other measures.** p < 0.01; * p < 0.05. Significant correlation coefficients are shown in bold.

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+Enteric fever is a foodborne infectious disease caused by Salmonella enterica serotypes Typhi and Paratyphi A, B and C. The high incidence in low income countries can increase the risk of disease in travelers coming from high income countries. Pre-travel health advice on hygiene and sanitation practices and vaccines can significantly reduce the risk of acquiring infections. Although the majority of the cases are self-limiting, life-threatening complications can occur. Delayed diagnosis and cases of infections caused by multi-drug resistant strains can complicate the clinical management and affect the prognosis. More international efforts are needed to reduce the burden of disease in low income countries, indirectly reducing the risk of travelers in endemic settings. Surveillance activities can help monitor the epidemiology of cases caused by drug-susceptible and resistant strains.In the context of a globalization process, travels can pose a threat to the health of millions of persons worldwide. Outbreaks and epidemic episodes of transmissible diseases (e.g., Ebola, Zika, Middle East respiratory syndrome, etc.), potentially associated with travel of population groups, have raised the attention of supranational and national governments based on their mortality, morbidity, and impact on the sustainability of country and regional healthcare systems. Migration waves and business or holiday travels might be the epidemiological driver of several infectious diseases in low incidence geographical areas: involvement of numerous contagious and susceptible individuals, as well as rapid transfer of patients through modern transportation means, might create the epidemiological conditions for an unforeseen outbreak. Infectious diseases, rare in some geographic areas, can occur and rapidly spread in the context of unprepared national healthcare systems.In addition, the number of international travelers is increasing globally and will be presumptively 1800 million by 2030 [1]. In total, 1326 million and 1401 million international travelers were recorded in 2017 and 2018, respectively. Between 2007 and 2011, infectious diseases were diagnosed in 42,173 travelers coming from Asia (32.6%), Sub-Saharan Africa (26.7%), and Latin America and the Caribbean (19.2%). Some of the infectious diseases were systemic (e.g., malaria, dengue, and enteric fever) and about one-third were caused by gastro-intestinal pathogens (e.g., Campylobacter spp., Salmonella spp., and Shigella spp.) [2,3]. Whereas a decreasing trend of incident malaria has been recorded from 2000 to 2015, incidence of enteric and dengue fever has not changed overtime [4].Enteric fever, which includes Typhoid and Paratyphoid fever, is an infectious disease caused by Salmonella enterica serotypes Typhi and Paratyphi A, B and C. Their foodborne transmission, frequently associated with poor hygiene conditions and inadequate sanitation, favors outbreaks in low income countries [5]. Based on the most recent global estimates, ≥21 million incident cases and 222,000 typhoid-related deaths occur annually [6]. Improved sanitation and living conditions, as well as treatment of drinking water, have significantly contributed to decrease the incidence of enteric fever in high income countries (e.g., those located in Western Europe and North America). The Indian subcontinent and Southeast Asia show the highest annual incidence of typhoid fever (>100 cases per 100,000 cases annually), followed by Southern Africa (10–100 per 100,000 cases annually) [7,8]. In a recent meta-analysis conducted by Marchello and Colleagues [9], Africa and Asia were identified as high-endemic countries for typhoid fever, although a decreased trend in incidence was documented after 2000. Moreover, in low-resource areas, such as Tanzania, Myanmar, and Republic Democratic of Congo (DRC), S. typhi represents the leading cause of bloodstream infections in young children. In particular,>70% of cases occurred in children <10 years old and ~30% in <5 years old in DRC during 2015–2017. However, in high income countries, typhoid fever is one of the most frequently diagnosed vaccine-preventable diseases in returned international travelers and migrants coming from high incidence countries [10,11].It has been estimated that the incidence rate of typhoid fever in travelers to high-endemic countries is 3–30 cases per 100,000 travelers [12].A retrospective study carried out in the Netherlands from 1997 to 2014 found that the majority (59.6%) of patients with imported typhoid fever traveled in Asia (e.g., Indonesia (19.8%) and India (19.6%)), and Morocco (13.3%). A declining annual attack rate (i.e., annual incidence of imported cases to number of travelers in a geographical area) for all geographical destinations, with the only exception of India, has been described [13].The more frequently affected age group was 25–29 years according to the findings of a survey performed in Australia, which confirmed East and South Asia as the highest risk geographical areas for individuals visiting their country of birth [14].Similar findings were confirmed by a Greek study which highlighted the risk of traveling in the Indian subcontinent during 2004–2011 (83.3% of the cases of travel-associated enteric fever), especially in VFR (Visiting Friends and Relatives)-travelers, whose disease is associated with longer stay, exposure to contaminated water and food, and difficult access to pre-travel medical services due to language and cultural barriers, as well as to lower rates of vaccination against travel-related preventable infections, including typhoid vaccine [15,16]. Similarly, a retrospective study conducted in Qatar, between 2005 and 2012, reported 356 cases of typhoid fever, of whom 96.9% had traveled abroad, mainly in the Indian subcontinent [17]. Over 70% of typhoid fever cases in Europe are acquired abroad and frequently caused by strains with marked antibiotic resistance profile [18,19].In Italy, where typhoid fever was endemic in the first half of the last century, the mean annual notification rate was 127.6 cases during2007–2016. Although all cases were successfully treated, an unequal distribution of incident cases in the population group aged 25–44 years was found, likely linked to their travel habits [20].When traveling from high- to low- and middle-income countries, the risk of infectious diseases is higher in VFR-travelers, followed by travelers for other reasons. Migrants from low income countries represent a vulnerable population group at highest risk of respiratory, vector- and food-borne diseases owing to the higher circulation of microorganisms in their country of origin. Moreover, the higher risk could depend on long periods of stay in the country of origin, often in remote rural areas where the healthcare infrastructures are poor, and on close contact with the local population, as well as on consumption of local food and water [21]. Frequent travels from/to high incidence countries increase the probability of acquiring infections, such as those caused by Mycobacterium tuberculosis, HIV, Plasmodium spp., and Salmonella spp. Ten years of surveillance in the UK demonstrated lower rates of enteric fever in UK-born vs. migrant populations. Migrants from South Asian countries are at highest risk of enteric fever (80% of the migrant cases) [22].Another group at highest risk includes persons involved in humanitarian staffing (e.g., missionaries, medical, and humanitarian workers): their length of stay is long and their travel destinations are low income countries where the incidence of the above-mentioned infectious diseases is high. Nevertheless, the Global TravEpi Network (GTEN) data in US showed an appropriate pre-travel care and vaccination, over 90% of coverage, for hepatitis A, typhoid, and yellow fever [23].Although epidemiological data revealed that the occurrence of typhoid fever cases in high-income countries is a rare event and the awareness, as well as the knowledge, of the disease is poor, up-to-date estimates of typhoid fever incidence could be useful in supporting prevention and vaccination national strategies. Moreover, it should be helpful to identify groups at high risk of infection to plan adequate preventive strategies. In addition, based on the poor specificity of typhoid fever symptoms, the potential diagnostic delay could increase the risk of a rapid spread in low-incidence areas.A non-systematic, narrative review to retrieve the scientific evidence on imported enteric (i.e., typhoid and paratyphoid) fever diagnosed in high income countries was carried out to describe relevant clinical and public health features. The search engine PubMed was used to select peer-reviewed articles, published from 1January 2013 to 30 October 2019. References of the selected manuscripts were carefully assessed to detect important articles not included in the primary search. No detailed selection criteria were adopted to choose the articles. The following keywords were used to find articles on imported enteric fever-related diagnosis, therapy, epidemiology, and prevention: “typhoid fever”, “enteric fever”, and “travel”. In total, 207 records, published between January 2013 and October 2019, were found. Based on titles, abstracts, and full-texts, 71 (34.3%) studies were deemed suitable. Twenty-three (32.4%) were focused on epidemiological characteristics of enteric fever, fourteen (19.7%) on vaccines, fourteen (19.7%) on antimicrobial resistance of Salmonella spp. serotypes, ten (14.1%) on population groups at higher risk of acquiring typhoid fever, and ten (14.1%) on diagnosis and treatment.The risk of typhoid fever and non-typhoidal Salmonella invasive infections is highest in infants, young children, and young adults with underlying comorbidities, including severe anemia, malaria, malnutrition, and HIV infection [24]. Moreover, recent reports from the international travelers agency showed that immunocompromised travelers, who usually follow the same itineraries of immunocompetent persons, visit countries at high risk of infections but the risk of developing travel-related diseases is five times higher if compared with that of immunocompetent persons [25].However, data on groups at risk of acquiring typhoid infections are controversial and scant. Gordon showed that the immunological status cannot be associated with an increased risk or poor outcome. However, invasive diseases caused by non-typhoidal salmonellae are more frequently diagnosed in immunocompromised persons (e.g., persons with HIV/AIDS) [26]. Likewise, a study conducted in Africa did not find differences in HIV-positive patients and controls in the clinical presentation and outcomes of typhoid fever cases [27]. In contrast, Gotuzzo and Colleagues [28] found a rate of typhoid fever 25 times higher in HIV-positive patients than in the general population.With the remarkable increased number of travelers from high-income countries during the last two decades, it was estimated that 1.9 million children traveled overseas every year from the United States; similarly, a significant increase of travelers (1.7 fold) was shown in Greece from 2004 to 2008 [29]. A high proportion of enteric fever cases was described in children aged 0–14 years (>26% in 2018) [30], mainly attributed to tourism and VFR-travels. Zhou and Colleagues highlighted an increased rate of childhood enteric fever in a large tertiary care center in Canada during 1985–2013, with several cases caused by Salmonella paratyphi A and B and by bacterial strains resistant to first-line antibiotics [31]. In Australia, 87% of the childhood cases were acquired mainly in Southeast Asia, with an annual increasing incidence from the period 2001–2005 (13 cases per year) to the period 2011–2015 (38 cases per year) [32]. Similar data were described in France, where children aged <18 years accounted for one-third of enteric fever patients, with 61% of the infections acquired in Africa [33].Pre-travel counseling focused on hygiene and preventive measures could help reduce the risk of infection in individuals younger than two years, who cannot be immunized with the currently available vaccines [29].Infections can be averted with vaccines and hygiene-related recommendations. However, adherence to pre-travel advice, including the vaccination, is poor.Since 2008, the World Health Organization has advocated the control of typhoid fever based on vaccine-related strategies. Bill and Melinda Gates Foundation launched in 2017 a partnership called “Typhoid Fever Vaccine Acceleration Consortium (TyVAC)”, mainly focused on children living in high endemic areas, to increase the prescription of the typhoid conjugate vaccine in Africa and Asia [34].Currently, three typhoid vaccines are available:Live attenuated oral vaccine Ty21aPurified Vi capsular polysaccharide injectable vaccinePurified Vi polysaccharide conjugated parenteral vaccineLive attenuated oral vaccine Ty21aPurified Vi capsular polysaccharide injectable vaccinePurified Vi polysaccharide conjugated parenteral vaccineThe effectiveness of the current vaccination strategies in travelers depends on several variables, such as previous immunizations, type, and length of travel. Poor awareness on the high risk of foodborne diseases in low- and low-middle-income countries can increase the pool of individuals with a vaccine hesitancy.Surveys conducted in EU/EEA countries showed that hepatitis A is the first vaccine administered to Swiss (53%) and Italian (63%), travelers, followed by tetanus–diphtheria in Swiss (45.6%) and typhoid-fever vaccine in Italian (44.6%) travelers. Moreover, travel destinations can increase the request of pre-travel care (e.g., India and Thailand chosen for pleasure or business) [35,36]. Furthermore, low vaccine uptake and inappropriate precautions adopted by VFR-travelers was associated with a highest incidence of foodborne diseases [36,37].A Greek survey focused on the administration of typhoid fever vaccines showed that a high proportion (44.2%) of travelers to India accepted the prescription of a vaccine, in comparison with a lower percentage of individuals traveling to Africa (~31%) [37].Ty21a live attenuated vaccine, developed from attenuated Ty2 strains of S. typhi, does not confer protection after a single dose; three doses administered in alternate days in persons living in endemic countries and four doses in travelers are usually recommended to elicit adapted mucosal immunity (IgA antibodies), whose duration lasts ~7 years in 60–70% of the vaccinated cases [38,39]. Half of typhoid fever cases could be prevented until three years after vaccination [40].Purified Vi capsular polysaccharide vaccine, administered in one single dose, is associated with a high immunogenicity (80–95%) in adults and children older than two years; nevertheless, Anwar and Colleagues reported a preventive effect between one third and one half of the cases in the first two years after the vaccination and no clear benefits after three years [41]. Moreover, an acceptable immunogenicity and safety profile was shown when co-administered with yellow-fever and quadrivalent meningococcal vaccines [42], as well as in children and HIV-positive individuals [38]. A second dose is recommended after three years [39].Purified Vi polysaccharide vaccine can be conjugated to toxoids (Vi-diphtheria, Vi-Tetanus, and Vi-recombinant diphtheria CRM197) to increase IgG levels [38]. Two-year post-vaccination effectiveness was87% [36,43]. A single randomized trial in Indian children aged between six months and 12 years did not clarify the efficacy of two doses of Vi-TT vaccine one year after administration [40].A real-life survey in Germany described an adverse event rate of 28.6% (fatigue, pain, headache, pyrexia, myalgia, and swelling), increased after concomitant immunization with other vaccines(i.e., rabies, typhoid, and yellow fever vaccines) [44].A US military study showed more adverse events in individuals exposed to the polysaccharide Vi vaccine in comparison with those exposed to the oral vaccine, although rash and diarrhea were more incident in the latter group [45].Fever and pain at the injection site were incident using parenteral vaccines [40].Several studies suggested a cross-protection against S. paratyphi A, B and C with the administration of the oral vaccine Ty21a (common O- and Vi-antigens) [38], even if a study which recruited US military personnel described a weak immunity against S. paratyphi A [46].Primary prevention based on the available vaccines cannot be implemented in youngest children: the purified Vi capsular polysaccharide vaccine is not recommended in children aged <2 years for its poor immunogenicity; the live attenuated oral vaccine Ty21a is not well tolerated in children aged under five years [47].A recent review on the efficacy of the currently available vaccines confirmed that Ty21a and Vi polysaccharide vaccines can reduce the incidence of infections in adults and children aged >2 years [40].The clinical management of typhoid fever in travelers has significantly changed during the last two decades following the widespread distribution of MDR bacteria and the increased number of international travels in endemic countries, including high-risk individuals (e.g., children, immunocompromised patients, pregnant women, and elderly people) [48]. Although illness in travelers is usually not severe and self-limiting, urgent therapy can be needed to avoid life-threatening complications; then, a rapid diagnosis and therapy in returning travelers is key to avoid fatal consequences [49]. The information on the type of travel, including the collection of details such as accommodation and activities, as well as pre-travel immunization, could help in the differential diagnosis (e.g., malaria and dengue). The most prevalent symptoms in the case of typhoid infections are fever, diarrhea, vomiting, abdominal pain, and headache [31,50]. However, the specificity is poor and they can be attributed to other viral or bacterial agents, in both children and adults. Moreover, higher level of C-reactive protein can be also found in case of dengue and malaria. Typhoid fever is commonly characterized by gastrointestinal disorders [51,52,53] and, moreover, bradycardia (88%), and eosinopenia (63%) [54]. Empirical therapy is needed in the case of severe symptoms and when a rapid diagnosis cannot be performed.As recommended by the international guidelines [24], a definitive diagnosis of typhoid fever requires cultural or molecular methods, with specimens collected ideally before the administration of an antimicrobial therapy. Blood is the preferred specimen. Although serologic tests are frequently requested, several studies highlighted their poor specificity and sensitivity. Antimicrobial susceptibility testing is strongly recommended for clinical (prescription of a tailored antibiotic therapy) and public health (surveillance) purposes.Epidemiological investigations are key for the identification of the source case and of the contagious patients. Serotyping carried out by slide agglutination method and the characterization of the genomic profile using Pulsed Field Gel Electrophoresis (PFGE) and Multi Locus Sequence Typing (MLST) are recommended to confirm epidemiological links during a suspected outbreak.In the era of multidrug resistant strains, the adoption of antimicrobial susceptibility testing is necessary to guide the choice of the most appropriate therapy, improving the clinical management, preventing relapse and the chronic carrier status. Europeans Committee on Antimicrobial Susceptibility Testing (EUCAST) and Clinical and Laboratory Standards Institute (CLSI) recommend the use of the following antibiotics to be tested in vitro for infections caused by S. typhi and S. paratyphi: ampicillin, chloramphenicol, cotrimoxazole, ciprofloxacin, ceftriaxone, and azithromycin (Table 1).Patients are usually treated with oral antibiotics, antipyretic, and supportive therapy. Parenteral antibiotics are prescribed in complicated cases or when gastro-intestinal symptoms are persistent. Ciprofloxacin (15 mg/kg) for 5–7 days is prescribed in the case of moderate symptoms caused by fully susceptible isolates [55]. With the emergence of multidrug resistant strains, the first line treatment was represented by third generation cephalosporins, such as cefixime (20 mg/kg, max 200 mg) for 10–14 days. Alternative drugs are chloramphenicol (50–75 mg/kg/day) for 14–21 days, trimethoprim-sulfamethoxazole (8 mg/kg/day) for 14 days, or amoxicillin (75–100 mg/kg/day) for 14 days [56]. Cases of severe enteric fever, characterized by delirium, stupor, coma, or obtundation, can be successfully treated with corticosteroids (e.g., intravenous dexamethasone at an initial dose of 3 mg/kg, followed by 1 mg/kg every six hours for two days) [57].In the case of typhoid fever, the World Health Organization recommends notification to national authorities and drug susceptibility testing.Until multidrug resistant strains emerged and spread in the second half of the 1980s, chloramphenicol, ampicillin, and co-trimoxazole were considered the first-line therapy of typhoid fever globally [58]. The indiscriminate use of antibiotics, particularly in low-income areas, has favored the selection and spread of antimicrobial resistant strains [59].The first outbreak caused by chloramphenicol-resistant S. typhi occurred in Mexico in 1972, followed by notifications in other endemic areas (i.e., South Asia andAfrica) [60]. Moreover, ~66% of isolates in European countries [17], shows decreased susceptibility to ciprofloxacin, although it was considered in the past as first therapeutic choice [61] by the World Health Organization guidelines. In U.S., during 2016–2018, 5/29 cases of typhoid fever in patients who recently traveled to Pakistan were caused by extensively drug resistant strains [18].Data of the US antimicrobial monitoring system showed that >60% of the isolates had a reduced susceptibility to ciprofloxacin and nalidixic acid, as well as alarming increasing trends of resistance of S. typhi and paratyphi A [62] (Table 2).Britto and Colleagues systematically reviewed historical trends of drug resistance to first-line antimicrobial therapy in typhoid fever (1973–2018, for 13,833 isolates) (Table 3).The majority were isolated in South Asia (63.2%), Africa (15%), and Southeast Asia (12.8%). Moreover, during 2006–2015, a significant increasing trend of drug resistance was described for the nalidixic acid and fluoroquinolones [63].The increasing rate of S. typhi isolates resistant to quinolones, ampicillin, and cotrimoxazole prompted a policy change in terms of antibiotic prescription, mainly focused on third-generation cephalosporines [31,32]. Strains of multi-drug resistant (MDR) Salmonella typhi with the haplotype H58 were found worldwide, and accounted for multiple outbreaks in endemic countries and single cases in international travelers. Moreover, Klemm and Colleagues [64] detected several resistance genes (extended-spectrum β-lactamase genes, and ESBLs) in extensively-drug resistant strains, previously detected in other enteric bacteria [65]. Resistance is mainly associated with cumulative mutations in quinolone resistance-determining regions (QRDR) encoding DNA gyrase (gyrA and gyrB genes) and topoisomerase (parC and parE genes) [61,66]. A recent study, which analyzed >500 isolates of S. typhi, found that the reduced susceptibility to fluoroquinolones is frequently (85%) associated with point mutations in the QRDR; however, the prevalence can vary depending on the geographical area:95% in South Asia, 43% in EastAfrica, and 27% in WestAfrica. Strains resistant to ciprofloxacin were mainly collected from patients diagnosed in India, accounting for 23% of the total Indian cases [67].Qnr-family genes, which are responsible of plasmid-mediated quinolone resistance, confer resistance to nalidixic acid and are recommended as a surrogate marker of decreased susceptibility to ciprofloxacin [66].Recent reports from high-income countries described trends of decreased susceptibility for several antimicrobial drugs [61,66,68]: ciprofloxacin-resistant strains were 63%, 55.6%, and ~43% in Italy, Switzerland, and Spain, respectively. Antimicrobial resistance is frequently reported in USA where 69% of strains isolated between 2008 and 2012 were resistant to nalidixic acid or showed reduced susceptibility to ciprofloxacin, 12% were MDR, and 10% showed extensive drug resistance [69]. Furthermore, the poor antimicrobial susceptibility was found in both S. parathypi and S. typhi isolates; drug resistance to quinolones was detected in 66.7% and 20% isolates of S. paratyphi and S. typhi, respectively [68].Third generation cephalosporins (e.g., ceftriaxone) are successfully prescribed for infections caused by ciprofloxacin-resistant strains; alternatively, meropenem and aztreonam can be administered, even if the clinical breakpoint for aztreonam is not currently available [70]. Furthermore, 354 isolates of S. typhi collected in the Netherlands showed resistance to ciprofloxacin and azithromycin, reducing the availability of effective therapeutic options, mainly in travelers with acquired infections in endemic settings [71].On this basis, World Health Organization recommends the management of sporadic cases of typhoid fever diagnosed in high-income countries be performed in reference centers, where a comprehensive assessment, including the complete drug susceptibility testing, could be carried out [24].The present narrative review highlights that typhoid fever is an important clinical and public health issue in returning travelers. More international efforts and cooperation activities should be planned to reduce the burden of foodborne diseases, including typhoid fever, in low- and middle-income countries, addressing the key role played by the global surveillance systems. In particular, reliable and real-time estimates of typhoid fever can help better assess the efficacy and cost-effectiveness of ad hoc activities realized in both low and high endemic countries. The knowledge of the healthcare workers on travel related-diseases should be improved, focusing on the importance of a rapid diagnosis, including a rapid drug susceptibility testing, for the identification of difficult-to-treat cases (e.g., patients with typhoid fever caused by multi-drug resistant strains).Primary prevention strategies and pre-travel health advices could decrease the risk of acquiring infections: improved awareness in community members could support and improve the adherence, mainly in highly susceptible groups (e.g., children and immunocompromised patients).Nevertheless, further epidemiological studies should be focused on the effectiveness of currently available vaccines in population groups poorly evaluated in studies and trials carried out in the past. International surveillance networks involving endemic countries are needed to rapidly detect the emergence and spread of drug-resistant bacteria and decrease the incidence of imported cases in high-income countries. The financial and economic impact of endemic diseases can be easily reduced improving hygiene conditions in constrained-resource countries; however, only the improvement of political and economic issues can be achieved with comprehensive interventions supported by the international community, which directly and indirectly can affect the epidemiology of life-threatening diseases.This research received no external funding.The authors declare no conflict of interest.Clinical breakpoints recommended by EUCAST and CLSI. (NA, Not Applicable).Antimicrobial resistance pattern for Salmonella ser. Typhi (No. of isolates = 336), Paratyphi A (No. of isolates = 88), 2015 (CDC-National Antimicrobial Resistance Monitoring System-2015).Proportion (%) of drug-resistant isolates of Salmonella typhi.

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+Diarrhoea contributes significantly to the under-five childhood morbidity and mortality worldwide. This cross-sectional study was carried out in a tertiary care hospital in Ujjain, India from July 2015 to June 2016. Consecutive children aged 1 month to 12 years having “some dehydration” and “dehydration” according to World Health Organization classification were eligible to be included in the study. Other signs and symptoms used to assess severe dehydration were capillary refill time, urine output, and abnormal respiratory pattern. A questionnaire was administered to identify risk factors for severe dehydration, which was the primary outcome. Multivariate logistic regression modeling was used to detect independent risk factors for severe dehydration. The study included 332 children, with mean ± standard deviation age of 25.62 ± 31.85 months; out of which, 70% (95% confidence interval [CI] 65 to 75) were diagnosed to have severe dehydration. The independent risk factors for severe dehydration were: child not exclusive breastfed in the first six months of life (AOR 5.67, 95%CI 2.51 to 12.78; p < 0.001), history of not receiving oral rehydration solution before hospitalization (AOR 1.34, 95%CI 1.01 to 1.78; p = 0.038), history of not receiving oral zinc before hospitalization (AOR 2.66, 95%CI 1.68 to 4.21; p < 0.001) and living in overcrowded conditions (AOR 5.52, 95%CI 2.19 to 13.93; p < 0.001). The study identified many risk factors associated with severe childhood dehydration; many of them are modifiable though known and effective public health interventions.Diarrhoea is the second leading cause of morbidity and mortality among under-5 (U-5) children worldwide [1,2,3]. Childhood diarrhoea results in the death of approximately, 700,000 U-5 children yearly, constituting almost 16% of global child death [2,3]. Apart from deaths, the grave consequence of diarrhoea in the first two years of life is its effect on growth, leading to stunting [4]. The morbidity of childhood diarrhoea is about 3 episodes per child per year, and childhood diarrhoea is concentrated in Southeast Asia and Sub Saharan Africa [1]. Controlling diarrhoeal diseases has been on the public health agenda since long. The World Health Organization (WHO)-led diarrhoeal disease control programme resulted in a steep reduction of 75% in mortality due to diarrhoea worldwide from the 1980s to 2008 [5]. However, since then, gains in the reducing mortality rates have been levelling [5]. In 2013, the WHO and the United Nations Children’s Fund (UNICEF) formulated the integrated Global Action Plan for Pneumonia and Diarrhoea (GAPPD), which outlines a framework for ending preventable child deaths due to diarrhoea and pneumonia by 2025 [1]. The GAPPD emphasises a ‘protect, prevent, and treat’ approach that integrates interventions with proven effectiveness [1].In India, steady progress has been made in reducing deaths in U-5 children, with total deaths declining from 2.5 million in 2001 to 1.5 million in 2012, with a mean rate of fall of around 3.7% annually [1,6]. Despite this reduction, in India, diarrhoea is the third most common cause of death in U-5 children and is responsible for 13% of deaths in this age group [2,7]. Thus, in India alone diarrhoea results in the death of an estimated 300,000 children each year [2,7]. In terms of diarrhoeal episodes per year, the morbidity data from the National Family Health Survey-4 (NFHS-4) in Madhya Pradesh (M.P.) province where the current study was conducted, found that, 9.5% of all U-5 children had suffered from diarrhoea in the 2 weeks prior to survey [8]. The province of M.P. has the highest burden of infant and childhood mortality in India [8].Despite its consequences on health and survival, the last decade has witnessed a reduction in research on childhood diarrhoea [5]. As an example, only a few studies on epidemiological and clinical risk factors in childhood diarrhoea from India, have been conducted [9,10,11,12,13], but the burden of diarrhoeal diseases remains high [14]. To achieve the goal of ending preventable deaths due to diarrhoea the WHO and UNICEF emphasise the need for more research focusing on identifying context-specific risk factors and interventions to control childhood diarrhoea [1]. Thus, the present study aimed to examine the demographic, socioeconomic, environmental, and clinical risk factors for diarrhoea in children aged less than 12 years in the city of Ujjain, M.P., India.This prospective observational study was conducted from July 2015 to June 2016. This study was approved by the Institutional Ethics Committee (IEC) of RD Gardi Medical College, Ujjain (IEC reference number 459/2014).The study was done in the pediatric ward of C.R. Gardi Hospital (CRGH), Ujjain. The CRGH is situated approximately six kilometers from Ujjain city and is a teaching hospital attached to R.D. Gardi Hospital (RDGMC). Department of Pediatrics in RDGMC has 90 beds out of the total 800 beds in CRGH. The hospital is managed by a charitable trust.Consecutive patients aged between 1 month and 12 years who were admitted for acute diarrhoea (up-to 14 days) to the paediatric ward were included in the study. The WHO definition of acute diarrhoea was used: i.e., passage of three or more loose stools (liquid or watery stool) for more than one day [1]. Children having “some dehydration” and “dehydration” according to WHO classification were eligible to be included in the study [15]. Other signs and symptoms used to assess severity of dehydration included capillary refill time, urine output and abnormal respiratory pattern [16]. Children treated in the last 24 h with intravenous fluids, children with persistent diarrhoea (>14 days), children living with human immunodeficiency virus/acquired immune deficiency syndrome, bloody diarrhoea, diarrhoea due to systemic infection, and diarrhoea during a course of antibiotic therapy were excluded from this study. Figure 1 shows the patient recruitment process.The following definitions were used for the present study: nuclear family was defined as a family that consisted of a married couple and their children occupying the same dwelling space [17]. A joint family comprised of more than one married couple and their children who lived together in the same household and shared a common kitchen [17]. Overcrowding was defined as a situation in which more people are living within a single dwelling than there is space for, so that movement is restricted, privacy secluded, hygiene impossible, rest and sleep difficult [17]. Breastfeeding was considered exclusive if the infant has received only breast milk from his/her mother or a wet nurse, or expressed breast milk, and no other liquids or solids [18]. Severe acute malnutrition (SAM) was assessed and managed in children between the ages of 6 months to 5 years according to the consensus statement by the Indian Academy of Paediatrics (IAP) [19]. A kutcha house was one with the walls and/or roof made of material such as un-burnt bricks, bamboos, mud, grass, reeds, thatch, loosely packed stones, etc. [20]. A pucca house is one, which has walls and roof made of burnt bricks/stones packed with lime or cement [20].The mother or caregiver accompanying the child fulfilling the inclusion criteria was interviewed by one of the research assistants using a predefined questionnaire (online supplementary data). Information was collected on demographics of the child and mother, relevant medical history, history of treatment received before hospitalisation, and environmental and personal hygiene-related risk factors for diarrhoea. Signs and symptoms of children included in the study was recorded at time of admission. Apart from the first author, two independent paediatric consultants assessed each admitted child and decided the management of the child.During the hospital stay, fluid management of all children were managed according to the IAP protocol for management of diarrhoea [21]. All children received Oral Rehydration Solution (ORS) and oral zinc as soon as oral intake was established [21].Data were entered into EpiData Entry (Version 3.1, EpiData Software Association, Odense, Denmark) and were analysed using Stata (Version 13.0, Statacorp. Texas, TX, USA). The Pearson chi-square test was used to evaluate the association of each risk factor with severe dehydration, and the results are reported as unadjusted odd ratios (OR). Stepwise multivariate logistic regression models, with backward elimination of predictor variables having a p value of more than 0.1 were used to develop the final model. In the final model, the p value of all predictor variables was less than 0.1, except for age and sex. Adjusted OR (AOR) and their 95% confidence intervals (CI) were then calculated. A p value of <0.05 was considered significant. Model discrimination was conducted using the C-statistics-receiver-operating-characteristics (ROC) curve, and model calibration was performed using Hosmer–Lemeshow ‘goodness-of-fit’ test [22].During the study period, 332 children (54% boys and 46% girls) with diarrhoea were enrolled. The mean age of children was 25.62 months (SD ± 31.85). Of the 332 children admitted with diarrhoea, 232 children were diagnosed to have severe dehydration and the remaining had “some dehydration” according to WHO classification. The prevalence of severe dehydration was thus 70% (95% CI 65 to 75). The signs and symptoms at the time of admission are shown in Table 1. None of the children included in the study died during the hospital stay.Although slightly more boys were admitted then girls there was no statistically significant difference in the prevalence of severe dehydration among the boys and girls. Most (74%) children belonged to younger age group of 1 month to 24 months. Children of illiterate mothers compared to children of literate mothers and children of working mothers compared to non-working mothers, had increased risk for severe dehydration (Table 2).Association severe dehydration with feeding-related factors, other factors in past one month-Vitamin A supplementation, measles and diarrhea are shown in Table 3. Presence of SAM, and if the child received vaccination on schedule were also associated with severe h = dehydration. Treatment-related factors like antibiotics, ORS and zinc, and home treatment for the present episode of diarrohea were significantly associated with severe dehydration (Table 3).The environmental and household sanitation conditions identified as risk factors are shown in Table 4.The independent risk factors for severe dehydration were: lack of exclusive breastfeeding in first six months of life, history of measles in the last one month, excessive crying, presence of malnutrition, receiving antibiotic in last 7 days, not receiving oral rehydration solution before hospitalization, not receiving oral Zinc before hospitalization, and living in overcrowded conditions (details in Table 5).The ROC of the final model was 0.8981 showing excellent model fit as a value more than 0.75 (and near one) predict excellent discrimination [22]. The Hosmer–Lemeshaw test showed that chi-square was 3.94 (p = 0.8626). A high p showing good model calibration [22]. This is the first study from central India and from the province of Madhya Pradesh to define risk factors for severe dehydration in children with acute watery diarrhoea. Despite measures to control the disease at national level in India the disease burden remains high [14].In our study, bivariate analysis revealed that children living in urban areas had a lower risk of severe dehydration than children living in rural areas. This may be due to presence of greater number of risk factors associated with diarrhoea among children living in urban areas [23,24]. However, increased risk of acute diarrhoea in rural areas has also been reported [25]. The most important underlying factors in both urban and rural areas are water, sanitation and hygiene (WASH)-related an include the faecal contamination of drinking water, the lack of personal hygiene especially during water handling, and inadequate hand washing after defecation [9,10,26,27]. The children of illiterate mothers have a nearly two-fold increased risk of severe dehydration in our study. Similar increased risk of diarrhoea has been reported in children born to illiterate mothers [5,28].It has been well documented that the morbidity of diarrhoea is the lowest in exclusively breastfed children, due to the protective effects of breast milk [1,29,30]. Bottle-feeding has been shown to be associated with diarrhoea in India as well as in other low-income countries [24,31]. In the present study, 84% of children received vitamin A supplementation. In our study, the association of vitamin A supplementation with severe dehydration was not statistically significant. However, evidence shows that vitamin A supplementation reduces diarrhoea mortality by 12% and significantly reduces morbidity due to diarrhoea and measles [32]. In our study, bivariate analysis results support that post-measles diarrhoea is an important complication of measles, and children with measles have a 1.29 times increased risk of severe dehydration. Acute diarrhoea has been reported in more than 50% of cases of complicated measles [33]. In our study, SAM was present in 33% of children; of these children, 79% had severe dehydration (p < 0.05). The presence of SAM, as defined by IAP’s weight-for-age classification, increases the risk of severe dehydration (Table 5). SAM can increase the severity of diarrhoea, particularly in wasted children, which may be due to the diminished immune response to infection [24]. In our study, according to bivariate analysis, the odds of severe dehydration increased when an antibiotic was prescribed to a child for the present episode of diarrhoea in the last 7 days. Moreover, patients who did not receive ORS and zinc had a higher risk of diarrhoea. Antibiotics are indicated only for a fraction of cases of acute diarrhoea but are prescribed to up to 70% of children with diarrhoea [34]. According to the NFHS-4 data for Ujjain district, 64% and 52% of U-5 children with diarrhoea received ORS in urban and rural areas, respectively. Compared with the NFHS-4 data, the ORS use rates in our study were 32% and 37% in rural and urban areas, respectively [8]. Moreover, according to the NFHS-4 data, 20% of U-5 children received zinc, which is comparable to the rate of 19% reported in our study [8].In our study, we explored the association of the type of household sanitation with severe dehydration. The absence of a toilet in the house, non-use of toilet, and practice of open-air defecation increased the risk of severe dehydration. In our study, 86% of households had a toilet facility. An increase in the number of toilets constructed at households and the use of toilets can be linked to the Swachh Bharat campaign initiated by the Government of India from 2nd October 2014 onwards [33]. The association of overcrowding with severe dehydration found in our study is probably a proxy for poor sanitation, lack of access to clean water, and inadequate personal hygiene, which are responsible for approximately 88% of childhood diarrhoea in India [24]. Moreover, in many places in India, child faeces are not disposed of safely [10,24,26]. Similar WASH-related environmental risk factors for diarrhoea have been reported recently from Mozambique, Tanzania and Nepal [9,35,36]. Environmental enteric dysfunction is now considered the most important causes of stunting in children with diarrhoea in low-middle-income countries [4,37]. The lack of hand hygiene is a universal risk factor for diarrhoea [38]. It has been estimated that proper hand washing practices can reduce the number of diarrhoeal episodes by more than one-third [38]. However, the best approach to promote hand hygiene among children remains elusive [39].The main strength of this cross-sectional study is that we collected both epidemiological and clinical data for risk assessment of severe dehydration in childhood admitted with acute diarrhoea, which is rare. The study also identified many modifiable risk factors for childhood diarrhoea, which can be used for planning community interventions. However, the study has certain limitations: the study did not ascertain the aetiology of diarrhoeal diseases in children, because it was not the primary study objective and also because of limited laboratory on-site capacity and the lack of affordable point-of-care diagnostics. A home visit to the children with diarrhoea could have helped us identify the contamination of household drinking water, but this was not thought to be feasible.Our study identified a multitude of risk factors for childhood diarrhoea, and many of them are modifiable. Promotion of breastfeeding, early identification and treatment of severe acute malnutrition, and treatment of diarrhoea with ORS and zinc in the household and community can reduce the risk for severe dehydration. Research should be conducted to identify effective interventions that can modify the identified risk factors. The implementation of such effective interventions may substantially reduce the morbidity and mortality of diarrhoea in this and similar resource-constrained settings.A.S.; A.M.; C.S.L.; and A.P. participated in the conception and design of the study. A.S. and A.M. collected the data. A.M. and A.P. did data management. A.P. supervised the data collection. A.S.; A.M. and A.P. performed the statistical analysis. A.S. and A.P. drafted the manuscript. A.S.; A.M.; C.S.L. and A.P. revised the paper critically for substantial intellectual content. All authors read and approved the final version. All authors have read and agreed to the published version of the manuscript.This study is funded by Uppsala Universitet’s L R Åkerhams post-doctoral scholarship in clinical research, obtained by Ashish Pathak. The funders had no role in study design, data collection, data analysis, decision to publish, or preparation of the manuscript.We are thankful to all the study participants for taking part in the study. We would also like to thank the Dean,  M. K. Rathore, and Medical Director, V. K. Mahadik, R. D. Gardi Medical College, Ujjain for the support that was provided us in undertaking the study.The authors declare no conflict of interest.Flow chart of the patient recruitment process.Signs and symptoms of the 332 children admitted with severe dehydration included in the study in Ujjain, India.a-WHO classification (Reference [15]); b-Other signs and symptoms used for classifying severe dehydration (Reference [16]); c-assessed in children till one year of age.Association of socio-demographic and birth-related risk factors with severe dehydration in 332 children hospitalized with diarrhoea.a = column percentage, b = row percentage, R-referenceAssociation of feeding, other past history and past treatment-related risk factors with severe dehydration in 332 hospitalized children.a = column percentage, b = row percentage, SAM = Severe acute malnutrition, ORS = Oral rehydration solution.Association of environmental and personal hygiene-related risk factors with presence or absence of severe dehydration in 332 hospitalized children.a = column percentage, b = row percentage.Multivariate analyses of socio-demographic, past treatment-related, environmental and sign and symptom-related risk factors for severe dehydration in 332 children hospitalized with diarrhoea.* Adjusted for age and sex, SAM = Severe Acute Malnutrition, ORS = Oral rehydration solution.

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+This study compared the relationship between social participation, including work, and incidence of functional decline in rural and urban older people in Japan, by focusing on the number and types of organizations older people participated in. The longitudinal data of the Japan Gerontological Evaluation Study (JAGES) that followed 55,243 individuals aged 65 years or older for six years were used. The Cox proportional hazards model was employed to calculate the hazard ratio (HR) of the incidence of functional decline over six years and the stratification of rural and urban settings. In this model, we adjusted 13 variables as behavioral, psychosocial, and functional confounders. The more rural and urban older people participated in various organizations, the more they were protected from functional decline. Participation in sports (HR: rural = 0.79; urban = 0.83), hobby groups (HR: rural = 0.76; urban = 0.90), and work (HR: rural = 0.83; urban = 0.80) significantly protected against the incidence of decline in both rural and urban areas. For both rural and urban older people, promoting social participation, such as sports and hobby groups and employment support, seemed to be an important aspect of public health policies that would prevent functional decline.A strategy of active ageing [1], by linking the key policy domains of employment, pension, retirement, health, and citizenship, provides a sound basis to respond to the challenges presented by population ageing [2]. In recent times, the practical challenge has been to open up the innovative policy spaces that might make active ageing not only thinkable but also achievable [3]. In European countries, the Active Aging Index (AAI) tool measures the untapped potential of older people for active and healthy aging across countries [4]. The AAI consists of four domains: employment, participation in society; independent, healthy, and secure living; and capacity and enabling environment for active ageing [4,5].The social participation of older people, one of the domains of AAI [4,5], is a key factor of “successful aging” [6] and an important element of “active aging” [7]. Social participation is one of the core indicators of “age-friendly cities” proposed by the World Health Organization in recent years [8]. When considering public health services in a rapidly aging society, social participation is highlighted as a modifiable target of health interventions.In many longitudinal studies, social participation has been reported as effective for health outcomes such as functional disability [9,10,11,12,13], cognitive disability [14,15,16], instrumental activities of daily living decline [17,18,19], and basic activities of daily living decline [20]. Among them, some studies focused on the number and types of organizations in which older people participated [10,13,16,17,18]. These studies suggested that older people who participate in more organizations are healthier than those who do not participate, and that the relationships between social participation and health varied according to the types of organization they participate in.However, these studies [10,13,16,17,18] do not consider two issues. First, these studies do not consider “work” as a kind of social participation. According to the Organization for Economic Co-Operation and Development (OECD) scoreboard for older workers, older workers aged 65–69 years increased from 20.3% to 25.5% between 2006 and 2016 and from 12.0% to 14.6% at age 70–74 years during the same period, in OECD member countries [21]. However, recommendations made by the Council on Aging and Employment Policies [22] encourage supporting the employment of older people. In AAI, work and social participation are separate domains, but these are also defined as the actual experience of active aging [4,5]. Considering these circumstances, it is necessary to include work in social participation in the analysis of the number and types of organizations in which older people participated. Second, these studies do not consider residential environments, such as rural and urban areas. Generally, older people living in rural areas suffer with more depression [23], lower levels of basic activities of daily living [20], and a higher risk of developing disability [24] compared to those living in urban areas. In addition, the life expectancy is shorter in rural areas, and the difference between urban and rural areas is widening [25]. Previous studies [13,26] showed that rural older people were less socially active than urban older people. However, previous studies state that bonding social capital comprising a connection between community members is often stronger among rural older adults, resulting in community strength [27,28]. In addition, environmental factors such as neighborhood socioeconomic status and access to services and transportation differ in rural and urban areas [29]. Furthermore, the relationship between social participation and health outcomes, such as depression [23] and self-rated health [26,30], also differs. These may be the reasons why rural older people are unhealthier than urban older people. The relationship between social participation and functional decline may differ between rural and urban areas; however, such a relationship has not been clarified.Thus, we aimed at clarifying whether there were differences between rural and urban areas in the relationship between social participation, including work, and incidence of functional decline. This study was conducted to inform public health policies that could prevent the need for long-term care of older individuals residing in rural and urban areas, which have different environmental factors.We used longitudinal data from the Japan Gerontological Evaluation Study (JAGES). JAGES is one of the few population-based gerontological repeated surveys in Japan focused on the social determinants of health and the social environment [31,32]. From August 2010 to January 2012, self-reported questionnaires were mailed to 95,827 community-dwelling independent individuals aged 65 years and older who were not eligible to receive benefits from public long-term care insurance services. They were randomly selected from 13 municipalities, including rural and urban areas. Overall, 62,418 people participated (response rate, 65.1%) in the survey called JAGES2010. They were followed up for about six years (minimum 5.2 years; maximum 6.4 years). Of the total respondents (response rate 65.1%), 54,539 (87.4%) were successfully linked to the incident records of long-term care insurance certification. We excluded 7223 responses for the following reasons: (i) missing information on address (n = 101) and activities of daily living (ADL) (n = 1482); and (ii) having physical or cognitive disabilities reported in their questionnaires (n = 988). Moreover, 4662 respondents in long-term care within two years were removed to avoid the possibility of reverse causality (i.e., the possibility that people who were at high risk of functional decline did not participate socially). The final number of participants in this analysis was 47,306.Ethical approval for the study was obtained from the Nihon Fukushi University Ethics Committee (application number: 10–05), the National Center for Geriatrics and Gerontology (application number: No. 992-2), and Chiba University Ethics Committee (application number: No. 2493).The dependent variable was the incidence of functional decline during the follow-up period. The incidence of functional decline was defined by medical certification for Long-Term Care Insurance. Certification of decline is based on the formal evaluation of the need for Long-Term Care according to uniform criteria applied throughout Japan, and comprises both a home-visit interview, as well as the written opinion of a primary physician [33]. This formal evaluation is based on a standardized multistep assessment of functional and cognitive impairments [33]. We obtained information on the certification of long-term needs, death, and moving out of the study area, from the long-term care insurance database maintained by the municipalities. These criteria for determining the onset of functional decline have been used in previous epidemiological studies [4,5,6].The independent variable was social participation. With reference to previous research [5], social participation was classified into the following six types: neighborhood groups (local community), hobby groups (hobby), sports groups or clubs (sports), industrial groups (industry), volunteer groups (volunteer), and senior citizen clubs (citizen). Furthermore, we considered work (work) as a form of social participation and therefore analyzed seven types of organizations in this study.Participation in organizations other than work was assessed by using the following question: “How often do you participate in the following clubs or groups?”. Participants were given the following choices: “almost every day”, “twice or thrice a week”, “once a week”, “once or twice a month”, “a few times a year” and “never”. The response was categorized as “yes” if individuals selected any of the five options from “a few times a year” to “almost every day”, and “no” if they selected “never”. Participation in work was assessed by using the following question: “What is your current working status?”. Participants were given the following choices: “working”, “retired and not working now” and “never had a job”. The response was categorized as “yes” if the participants answered “working”, and “no” if they answered “retired and not working now” or “never got a job”.The total number of types of organizations each participant participated in was tallied, and participation was categorized as 0 (no participation), 1, 2, or ≥3 organizations, or “missing”. If the response to participation in all organizations was missing, we deemed it as “missing” category in this analysis. The organizations particularly unique to Japan among the types named above are senior citizen clubs. Japan’s senior citizens clubs conduct a wide range of activities, including group activities such as sports, hobbies, cultural activities, and performing arts.Based on a previous study [10], sex, age, annual equivalized income, educational attainment, marital status, and self-reported medical conditions were considered potential confounding factors that may correlate with social participation and incidence of functional disability. In addition, behavioral, psychosocial, and physiological factors were also used as covariates and potential mechanisms influencing health and social participation. Smoking, alcohol consumption, daily walking time, and frequency of going outdoors were assessed as behavioral factors. Depression (Geriatric Depression Scale), emotional support, instrumental support, and frequency of meeting friends were assessed as psychosocial factors. Instrumental activity of daily living (IADL) was assessed as a functional factor. All variables were categorized as shown in Table 1 and set as dummy variables. A “missing” category was used in the analysis to account for missing responses to questions.The definition of functional urban areas from the OECD metropolitan database [34] was used to classify rural and urban settings. The definition of urban areas in OECD countries uses population density to identify urban cores, and travel-to-work flows to identify the hinterlands whose labor market is highly integrated with the cores. The methodology consisted of the three following main steps: (1) identification of core municipalities through gridded population data; (2) connecting noncontiguous cores belonging to the same functional urban area; and (3) identification of urban hinterlands. This methodology makes it possible to compare functional urban areas of similar size across different countries and classifies functional urban areas according to population size into the following four types: (1) small urban areas (with a population below 200,000 people); (2) medium-sized urban areas (with a population between 200,000 and 500,000); (3) metropolitan areas (with a population between 500,000 and 1.5 million); and (4) large metropolitan areas (with a population of 1.5 million or more). From the OECD’s four functional urban areas, all cities, including metropolitan and large metropolitan areas, were designated urban areas in this study, and all others were designated rural areas. In this study, eight municipalities were designated as rural, and five municipalities were designated as cities.First, we conducted a chi-square test to compare variables between rural and urban males and females. As the sample size in this study is very large, we calculated Cramer’s V as the effect size in addition to the p-value. The criteria for Cramer’s V are 0.1 for small, 0.3 for medium, and 0.5 for large. Second, the Cox proportional hazards model was employed to calculate the hazard ratios (HRs) and 95% confidence intervals (CI) of the incidence of functional decline over six years, stratified by rural, and urban settings. In each model, nonparticipation in an organization was set as the referent category. In the analysis of the number or types of organization older people participate in, we conducted a trend test. Further, six types of social participation were introduced in each model separately. The following two models of analysis were used: a regression analysis was performed with simultaneous forced entry of sex, age, equivalent income, educational attainment, marital status, and self-reported medical conditions as covariates (Model 1). Model 2 added the following confounding factors to Model 1: smoking, alcohol consumption, walking time, frequency of going outdoors, Geriatric Depression Scale, emotional support, instrumental support, frequency of meeting friends, and IADL. Finally, to confirm the robustness of our finding, we performed a complete case analysis, excluding patients missing any of the variables used in the analysis. STATA V.15 (Stata Corp, College Station, TX, USA) was used to conduct a statistical analysis, with a significance level of 5%.Table 1 presents the descriptive statistics of rural and urban variables. Of the 47,306 respondents included in the analyses, 21,921 were male and 25,385 were female. Of the 21,921 males, 6758 lived in rural and 15,163 lived in urban settings. Of the 25,385 females, 8375 lived in rural and 17,060 lived in urban settings. The average age of the rural and urban older people was 73.8 (standard deviation (SD), 5.9) and 73.3 (SD, 5.6) years, respectively. Of the respondents in rural and urban areas, 2399 (15.9%) and 4018 (15.3%) reported functional decline, respectively. The average tracking period was 2028.1 days (SD = 364.1) for rural and 1951.8 days (SD = 361.7) for urban older peoples. The comparison of variables across rural and urban areas revealed that there were many urban–rural differences. However, the sample size for this study was so large that even minor differences could result in statistical differences. In fact, Cramer’s V in the chi-square test between almost all variables was judged to be very small, and the realistic effect size was small. However, describing the difference between rural areas and cities when the effect size is 0.1 or more indicated that older people in rural areas had a lower equivalent income (p < 0.001), lower educational attainment (p < 0.001), and went outdoors less frequently (p < 0.001) than those in urban areas. Although the effect size was small, the distribution of the number of organizations in which older people participated differed between rural and urban areas (p < 0.001). When types of social participation were analyzed, rural older people participated a lot more in senior citizen clubs (p < 0.001) than urban older people. The distribution of participation in work differed between rural and urban areas (p < 0.001; Cramer’s V = 0.1); it was thought to be due to the missing category.Table 2 presents the results of a Cox proportional hazards model analysis of the different types of organizations and incidence of functional decline. In the crude model and Model 1, a “dose–response” relationship was seen both among rural and urban areas, with progressively lower HRs as the number of different types of organizations increased. In Model 2 for rural older people, the HRs were 0.94 (95% CI: 0.84–1.05) for participation in one, 0.85 (0.75–0.97) for participation in two, and 0.76 (0.67–0.86) for participation in three or more different types of organizations, with the significant difference disappearing only for participation in one type of organization. For urban older people, the HRs were 0.92 (95% CI: 0.85–0.99) for participation in one, 0.87 (0.80–0.96) for participation in two, and 0.82 (0.75–0.89) for participation in three or more different types of organizations, with the statistical significance for one or more different types of organizations. In other words, older people in urban areas were protected from functional decline through one type of participation. On the other hand, older people in rural areas required more than one type of participation, but older people in rural areas had lower HRs when participating in more than two types of organizations than older people in urban areas.The results of the complete case analysis are shown in Table S1. The results of the complete case analysis, excluding patients missing any of the variables used in the analysis were similar to those when the “missing” category was used in the analysis to account for missing responses to questions. The full modeling results in Model 2 were presented in Table S2. In this study, Model 2 added social networks such as emotional support, instrumental support, and frequency of meeting friends. Rural and urban older people who could not avail emotional support were not protective against functional decline compared with those who could avail it. Furthermore, urban older people who could not avail instrumental support were not protective against functional decline compared with those who could avail it, but this was not the case in rural areas. The frequency of meeting friends was not statistically significant in rural and urban areas.Table 3 presents the results of the Cox proportional hazards model analysis of the type of social participation and incidence of functional decline. Almost all types of organizational participation were strongly protective against functional decline, but senior citizen clubs had the opposite relationship in the crude model. Similarly, many types of organizational participation were protective against functional decline in Model 1. In Model 2 for rural older people, participation in hobbies (HR = 0.76; 95% CI: 0.68–0.85), sports (HR = 0.79; 95% CI: 0.69–0.89), work (HR = 0.83; 95% CI: 0.76–0.91), and local community (HR = 0.86; 95% CI: 0.77–0.95) was found to be protective against the incidence of decline. For urban older people, participation in work (HR = 0.80; 95% CI: 0.70–0.91), sports (HR = 0.83; 95% CI: 0.77–0.91), and hobbies (HR = 0.90; 95% CI: 0.84–0.97) was found to be protective against the incidence of decline.The results of the complete case analysis are shown in Table S3. In the complete case analysis for rural older people, the HR for participation in work and local community was below 1.00, but the statistical significance disappeared. Further, the results of the complete case analysis for urban older people, excluding patients missing any of the variables used in the analysis, were similar to those when the “missing” category was used in the analysis, to account for missing responses to questions. The full modeling results in Model 2 were presented in Table S4. The result of the social networks, such as emotional support, instrumental support, and frequency of meeting friends, added in Model 2, was similar to the analysis of the number of organizations.To the best of our knowledge, this is the first longitudinal study to compare the relationship between the number and type of organizations, including work, and incidence of functional decline in rural and urban areas separately.In all, two findings were obtained from this study: (1) a “dose–response” relationship was seen both among rural and urban areas, with progressively lower HRs as the number of different types of organizations increased; and (2) participation in sports, hobbies, and work were protective against incidences of decline in both rural and urban areas. In this study the classification of rural and urban areas is as proposed by the OECD. Previous studies have used population density and national classification; however this study adopted an international classification system. Even when classifying areas by population density, the results of this study were almost the same.The analysis of the number of organizations revealed the HRs of the number of types of organizations progressively decreased as the number of participating organizations. This supports previous studies, including those measuring other health outcomes [10,13,16,17,18]. In this study, HRs were lower when participated in two or more types of organizations in rural areas than in urban areas. The social relationships specific to rural areas may be the reason why older people living in these areas need to join more than one organization. Previous studies have indicated that bonding social capital comprising a connection between community members is often stronger among rural older adults, resulting in community strength [27,28]. In this study, participation in local community organizations was higher in rural areas than in urban areas. However, excessive bonding social capital tends to have negative effects [35]. According to the systematic review of the negative health effects of social capital [35], there are downsides to social capital that emerge in the context of strong bonding social capital, but not in weak bridging social capital. (1) Strong bonding ties impose heavy obligations on community members by following a dominant social hierarchy and social norms, and it exclude outsiders. (2) The lack of bridging SC is crucial in socioeconomically disadvantaged communities. (3) In such settings, the connection of members to outside sources of support is even more important. In closed communities, such as those in rural areas, participation in more organizations may improve bridging social capital. For the above reasons, older people in rural areas may benefit from participation in a greater number of organizations.Many types of organizational participation were protective against functional decline in Model 1, which included factors such as age, equivalent income, educational attainment, marital status, and self-reported medical conditions. However, in Model 2, factors such as behavioral, psychosocial, and functional confounders, as well as participation in sports, hobbies, and work, were protective against incidences of decline.This is the first longitudinal study to compare work with other community organizations by defining work as a type of social participation. Previous longitudinal studies focusing on the relationship between work and health outcomes among older people have examined work alone [20,36,37], and comparisons with other community organizations have been cross-sectional studies [38]. Given the current challenges posed by a rapidly declining birthrate and aging population, it is necessary to develop a social structure where many older people work [39]. Working support for older people is expected to contribute not only to a substantial increase in the labor force but also to a decrease in the number of older people requiring care [39]. This study showed that working support and improvement of working environment could be public health policies that would prevent the need for the provision of long-term care in rural and urban areas. In longitudinal studies of work and health outcomes [20,36,37], work is generally considered good for health. However, poor-quality work [36] is not good for health; therefore, additional analysis is necessary, since this research did not consider the type of work.The results indicating that participation in sports and hobby groups were protective against disability were similar to previous studies [10]. According to this result, a good public health policy would include local government provision of regular opportunities for social participation in sports and hobbies in both rural and urban areas. Participation in sports and hobby groups has also been reported to prevent other poor health outcomes [16,18,19]. Previous studies have shown that older people in rural areas were unhealthier than older people in urban areas [20,24,29,30], but in this study, there was no difference in the incidence of functional disability between older people in rural and urban areas. The reason may be that there was no difference in the urban–rural participation rates in sports and hobby groups among the participants of this study. Even in rural areas, promoting participation in groups such as sports and hobbies groups could prevent the incidence of functional decline. In Japan, the salon-type community intervention [40] has been implemented as one of the ways to promote social participation. These salons, managed by local volunteers, are held once or twice a month in communal spaces within walking distance of community members’ homes, and older people can meet and interact with others through enjoyable, relaxing, and sometimes educational programs [40]. Moreover, participation in local community organizations was only protective against decline in rural older people in this study. In the scoping review by Carver et al. [41], older people who lived in rural areas had many opportunities to engage in community-association activities, and through such social participation, a sense of belonging was created. They suggested that such social participation is important for achieving successful aging in rural areas.The preventive effects against functional decline of the number and types of social participation were almost the same among both rural and urban areas in this study. Quite a few studies on age-friendly cities showed that urban areas are suitable for active aging [42]. One of the reasons for that may be a larger quantity of amenities and possibilities for social interactions/organizations and easier access to those in urban areas compared to rural areas. It could be an effective intervention that older people move to urban areas when their health/physical ability starts to decline. Nowadays, the compact city, i.e., located in the rural city center, but short-distance from urban functions, trials have begun in Japan [43,44], and their effectiveness is expected to be verified.This study has two strengths. First, this is the first study to target older people in many municipalities, including rural and urban areas, in contrast to previous studies that only focused on the number and type of organization in which older people participated [10,13,16,17,18]. Second, the data used in this study was collected over a long period (about six years) and excluded respondents receiving long-term care within two years, thereby removing the possibility of reverse causality (i.e., the possibility that people who had a high risk of functional decline did not participate socially).This study had three limitations. First, we did not consider the frequency of social participation. It has been reported that the relationship between social participation and health outcomes differs depending on the frequency of social participation [16,18,38]. However, this research emphasized a comparison between rural and urban areas in line with a previous study [10]. Second, we did not consider the older people’s role of the organization they participated in, such as being a member or a leader. A leading role in an organization has an additional effect on social participation and health outcomes [15,45]. Finally, this study only focuses on the differences between rural and urban areas; however, there may be other environmental characteristics to consider. The NuAge Study showed environmental factors associated with social participation of older people vary by living areas, such as metropolitan, urban, and rural areas [29]. In Japan, it was reported that environmental factors such as access to facilities, shops, and parks and sidewalks were related to participation in sports groups [46]. Future longitudinal or interventional studies focusing on rural and urban environmental improvement will be needed.We compared the relationship between social participation, including work and incidence of functional decline in rural and urban older people, to inform public health policies that would prevent functional decline in older individuals residing in Japan. Participating in various organizations protected older people from functional decline, and, thus, it might be essential to facilitate the benefits of such participation to both rural and urban older people. Furthermore, participation in sports, hobbies, and work was protective against incidences of decline in both rural and urban regions. For both rural and urban older people, promoting social participation, such as sports and hobbies groups and employment support, seems to be an important aspect of public health policies that would prevent functional decline.The following are available online at https://www.mdpi.com/1660-4601/17/2/617/s1, Table S1: Complete case analysis: HRs for participation in one, two, and three or more different types of organizations, Table S2: The full modeling results for participation in one, two, and three or more different types of organizations in Model 2, Table S3: Complete case analysis: HRs for type of social participation (reference: nonparticipation in each organization), Table S4: The full modeling results for HRs for type of social participation (reference: nonparticipation in each organization).Conceptualization and methodology, K.I., T.T., and S.K.; validation, K.I. and T.T.; formal analysis, K.I.; data curation, T.T.; writing—original draft preparation, K.I.; writing—review and editing, T.T. and S.K.; supervision, S.J., Y.N., and K.K.; project administration, K.K. All authors have read and agreed to the published version of the manuscript. This study used data from JAGES (the Japan Gerontological Evaluation Study). This study was supported by Grant-in-Aid for Scientific Research (15H01972, 15H04781, 15H05059, 15K03417, 15K03982, 15K16181, 15K17232, 15K18174, 15K19241, 15K21266, 15KT0007, 15KT0097, 16H05556, 16K09122, 16K00913, 16K02025, 16K12964, 16K13443, 16K16295, 16K16595, 16K16633, 16K17256, 16K17281, 16K19247, 16K19267, 16K21461, 16K21465, 16KT0014, 17K04305, 17K34567, 17K04306, 25253052, 25713027, 26285138, 26460828, 26780328, 18H03018, 18H04071, 18H03047, 18H00953, 18H00955, 18KK0057, 18074040, 19H03901, 19H03915, 19H03860, 19K04785, 19K10641, 19K11657, 19K19818, 19K19455, 19K24060, 19K20909) from JSPS (Japan Society for the Promotion of Science); Health Labour Sciences Research Grants (H26-Choju-Ippan-006, H27-Ninchisyou-Ippan-001 H28-Choju-Ippan-002, H28-Ninchisyou-Ippan-002, H29-Chikyukibo-Ippan-001, H30-Jyunkankinado-Ippan-004, 18H04071, 19FA1012, 19FA2001) from the Ministry of Health, Labour and Welfare, Japan; the Research and Development Grants for Longevity Science from Japan Agency for Medical Research and development (AMED) (JP17dk0110027, JP18dk0110027, JP18ls0110002, JP18le0110009, JP19dk0110034, JP19dk0110037), the Research Funding for Longevity Sciences from National Center for Geriatrics and Gerontology (24-17, 24-23, 29-42, 30-30, 30-22); Open Innovation Platform with Enterprises, Research Institute and Academia (OPERA, JPMJOP1831) from the Japan Science and Technology (JST); a grant from the Japan Foundation For Aging And Health (J09KF00804), a grant from Innovative Research Program on Suicide Countermeasures (1-4), a grant from Sasakawa Sports Foundation, a grant from Japan Health Promotion & Fitness Foundation, a grant from Chiba Foundation for Health Promotion & Disease Prevention, the 8020 Research Grant for fiscal 2019 from the 8020 Promotion Foundation (adopted number: 19-2-06), a grant from Niimi University (1915010), grants from Meiji Yasuda Life Foundation of Health and Welfare. The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the respective funding organizations.We would like to thank the study participants. We would also like to thank Hanazato (Chiba University) for teaching us the classification of rural and urban settings.The authors declare no conflicts of interest.Baseline characteristics of respondents (2010–2012).HRs for participation in one, two, and three or more different types of organizations.HR: Hazard ratio; CI: confidence interval; Ref: reference. * p < 0.05. Model 1: Crude model + sex, age, equivalent income, educational attainment, marital status, and self-reported medical conditions. Model 2: Model 1 + smoking, alcohol consumption, walking time (per day), frequency of going outdoors, depression, emotional support, instrumental support, frequency of meeting friends, and IADL.HRs for type of social participation (reference: nonparticipation in each organization).HR: Hazard ratio; CI: confidence interval; Ref: reference. * p < 0.05. Model 1: Crude model + sex, age, equivalent income, educational attainment, marital status, and self-reported medical conditions. Model 2: Model 1 + smoking, alcohol consumption, walking time (per day), frequency of going outdoors, depression, emotional support, instrumental support, frequency of meeting friends, and IADL.

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+Ischemic stroke is the most common type of stroke, and early interventional treatment is associated with favorable outcomes. In the guidelines, thrombolytic therapy using recombinant tissue-type plasminogen activator (rt-PA) is recommended for eligible patients with acute ischemic stroke. However, the risk of hemorrhagic complications limits the use of rt-PA, and the risk factors for poor treatment outcomes need to be identified. To identify the risk factors associated with in-hospital poor outcomes in patients treated with rt-PA, we analyzed the electronic medical records of patients who were diagnosed with acute ischemic stroke and treated for rt-PA at Chang Gung Memorial Hospitals from 2006 to 2016. In-hospital death, intensive care unit (ICU) stay, or prolonged hospitalization were defined as unfavorable treatment outcomes. Medical history variables and laboratory test results were considered variables of interest to determine risk factors. Among 643 eligible patients, 537 (83.5%) and 106 (16.5%) patients had favorable and poor outcomes, respectively. In the multivariable analysis, risk factors associated with poor outcomes were female gender, higher stroke severity index (SSI), higher serum glucose levels, lower mean corpuscular hemoglobin concentration (MCHC), lower platelet counts, and anemia. The risk factors found in this research could help us study the treatment strategy for ischemic stroke.Ischemic stroke is the most common type of stroke, responsible for approximately 87% of all strokes worldwide [1], and it can cause loss of functions, such as speaking, moving, and reading. In Taiwan, according to statistics of the Ministry of Health and Welfare (MOHW), stroke fourth highest cause of death, and similar to the data published by the American Heart Association, approximately 70%–80% of stroke patients had ischemic stroke [2,3]. The guideline-recommended treatment for eligible patients with acute ischemic stroke is thrombolytic therapy using recombinant tissue-type plasminogen activator (rt-PA) to dissolve blood clots, which was approved by the U.S. Food and Drug Administration in 1996 for intravenous use within 3 h of stroke [4,5]. According to evidence, the guidelines completely describe the emergency evaluation and treatment with intravenous rt-PA therapies [6]. For instance, the guidelines recommend intravenous alteplase administration for selected patients who can be treated within 3 h or 3–4.5 h of ischemic stroke symptom onset. Physicians should review the criteria of use such as blood pressure of <185/110 mmHg and initial glucose levels of >50 mg/dL to determine patient eligibility [6]. The use of rt-PA is also limited by important contraindications, including coagulopathy, recent surgery, or stroke or head injury within the past 3 months [6].Previous studies indicate that treatment with rt-PA may effectively improve neurological deficits in patients with acute ischemic stroke [7,8]. Early rt-PA treatment promotes independence and increases quality-adjusted life years (QALY) for stroke victims [9]. The prescription of rt-PA between 3 and 4.5 h after onset improves the clinical outcome [10] and the functional recovery [11] in patients with acute ischemic stroke. For long-term outcome evaluation, a study indicated that patients with acute ischemic stroke treated with rt-PA experience longer survival, delayed hospital readmission, and shorter time to independence [12]. Furthermore, patients at high risk of symptomatic intracranial hemorrhage still benefit from alteplase [13]. In addition to the time-to-treatment, stroke severity and stroke subtype might also affect the benefit from rt-PA treatment [14]. However, treatment with rt-PA requires careful consideration of both the risks and benefits, as bleeding is the most common side effect, which may cause the underuse of rt-PA despite guideline recommendations [15,16,17,18,19,20,21]. Despite the low use rate, one research concluded that larger hospitals were more likely to administer rt-PA [20]. Further efforts to improve appropriate administration of rtPA should be encouraged.Previous studies used electronic medical records estimating risk factors associated with hemorrhage after rt-PA treatment. Patients diagnosed with hyperlipidemia, cardioembolism, severe stroke, or advanced age are at a higher risk of hemorrhaging, and the use of rt-PA should be considered carefully [22,23]. Under the condition that all patients are eligible for receiving rt-PA therapy based on the guidelines, only a few studies used both laboratory test results and medical history data to evaluate treatment outcomes [22,23,24]. However, using both laboratory test results and medical history data to identify the risk factors that lead to poor outcomes after rt-PA therapy in the general population still need to be explored [25].For patients given rt-PA after stroke onset, we sought to investigate the general risk factors associated with poor rt-PA treatment outcomes. Therefore, our study carried out an analysis for patients in favorable and poor outcome groups to determine what factors might be associated with in-hospital poor outcomes, mainly in-hospital death, intensive care unit (ICU) stay, and prolonged length of hospital stay (LOS). This study was conducted using the pooled electronic medical records (EMRs) from the Stroke Registry of the Chang-Gung Healthcare System (SRICHS) [26] and the Chang Gung Research Database (CGRD) from the Chang Gung Memorial Hospitals (CGMHs), the largest group of healthcare providers in Taiwan. We analyzed the EMRs of patients who were diagnosed with acute ischemic stroke at CGMHs between 2006 and 2016, including 7 branches of CGMHs located in Linkou, Taipei, Taoyuan, Keelung, Yunlin, Chiayi, and Kaohsiung from northern to southern Taiwan. Medical histories defined by the history of diagnosis based on international classification of diseases (ICD) codes and laboratory test results were used as the variables of interest to determine the risk factors. The Chang Gung Medical Foundation Institutional Review Board approved this study (IRB no. 107-1113C) and granted waivers for patient consent.This study included patients who had an emergency department visit for one of the top three diagnoses related to stroke (ICD-9-CM codes 433–436; ICD-10-CM codes I63, I65, I66, or I679) followed by hospitalization with a primary diagnosis of acute ischemic stroke (ICD-9-CM codes 433–434; ICD-10-CM codes I63) at CGMHs from 2006 to 2016 [27].Three criteria were used in our study to define poor outcomes, including in-hospital death, intensive care unit (ICU) stay, and prolonged hospitalization. The in-hospital death is one of the worst outcomes of clinical care and has been evaluated in multiple studies [28,29,30]. ICU stay and prolonged hospitalization indicate that the patients need critical care or more time to recover after receiving rt-PA therapy [28,29,30,31]. In-hospital death was defined by death in hospital or a care home recorded on the discharge statement. Note that 24 patients without discharge statement records were considered as cases without in-hospital deaths. In CGMH, most of the patients receiving rt-PA therapy were admitted in the ICU for follow-up for 2 days. Therefore, all the patients treated with rt-PA will have at least 2 days of ICU stay. To identify the patients who need ICU admission owing to poor outcome, we set a threshold of 2 days to exclude the patients who were admitted in the ICU only for follow-up. The last criterion was prolonged hospitalization. The period between hospital admission and hospital discharge in an episode of care was calculated as the LOS. We defined prolonged hospitalization as the LOS of >55 days. The 55-day threshold was defined by the 90th percentile of the LOS in our data set [32]. If the time period between two hospitalizations, emergency department visits, and outpatient visits related to stroke was less than 3 days (i.e., a 3-day persistence window), these two visits were merged into a single episode of care, which is a means to apply consistent rules for medical conditions to infer distinct episodes of care, according to a previous study [33]. Patients fulfilling one of the criteria were included in the poor outcome group, but patients who fulfilled none of the criteria were included in the favorable outcome group.Laboratory tests which were available in more than 80% of the ischemic stroke patients were included as a variable for further analysis: complete blood count (CBC), creatinine, sodium, alanine aminotransferase (ALT), blood glucose, and potassium levels. The glucose test can be performed using a traditional blood glucose test or finger stick blood glucose test. To include all the glucose test results, we collected both traditional and finger stick blood glucose test results to perform further analysis. Patients could have several laboratory tests during hospitalization. We only included laboratory tests that were collected within the stroke episode and those closest to the time before rt-PA treatment.To investigate medical histories, the Elixhauser comorbidity index developed by the Healthcare Cost and Utilization Project (HCUP) was applied to the diagnosis records [34]. We used the emr R package [35], a tool for integrating and processing EMRs, to evaluate the medical history variables for further analysis. This package can be used to group multiple ICD codes into a smaller number of clinically meaningful categories by the Elixhauser comorbidity classification. To exclude the medical histories that were recorded in only a few patients in our study population, we excluded the medical histories recorded in less than 5% of the patients in poor and favorable outcome groups. That is, we included the medical histories with more than 5% occurrence for the patients in poor or favorable outcome groups.We use the stroke severity index (SSI) as a measure of stroke severity. The study by Sung et al. confirmed that the claims-based SSI is a valid substitute for the national institute of health stroke scale (NIHSS) score for estimating the stroke severity of patients hospitalized for acute ischemic stroke [36]. We calculated billing codes of Taiwan’s National Health Insurance for the SSI and separated it into three severities: mild (SSI ≤ 5), moderate (5 < SSI ≤ 12), and severe (SSI > 12) stroke according to previous studies [36,37].Two sensitivity analyses were applied to evaluate the effect of the proposed outcome definition, and the method we used to group the laboratory test results. The first sensitivity analysis defined a poor outcome as in-hospital death or ICU stay. Furthermore, instead of using real values of the test results, in the second sensitivity analysis, we categorized laboratory test results as normal, high, or low in accordance with the applicable reference ranges. This method can evaluate the effect of grouping laboratory test results by means of the reference range. Univariable and multivariable analyses were conducted in both sensitivity analyses.We performed a descriptive analysis of the characteristics of the patients in the favorable and poor outcome groups. Continuous variables were summarized as means (standard deviations) or medians (interquartile ranges) and discrete variables were summarized as frequencies and percentages. The means and medians were tested using Student’s t-test or the Kruskal–Wallis test, respectively. Chi-square tests or Fisher’s exact tests were used for the univariate analysis of the categorical variables. We performed least absolute shrinkage and selection operator (Lasso) regression in the multivariable analyses, which can address multicollinearity and is also an automated variable selection method [38]. The demographic characteristics, laboratory test results, and medical histories, which were different between the poor and favorable outcome groups (p value < 0.1), were kept as dependent variables in the Lasso model. The analyses were performed in R (version 3.4.4, The R Foundation for Statistical Computing, http://www.r-project.org/, R Core Team, Vienna, Austria). All statistical tests were two-sided, and statistical significance was defined as p < 0.05.In total, 42,679 episodes of care from 29,378 patients were eligible for the study. Approximately 2% of patients (645 individuals) received rt-PA after acute ischemic stroke onset. Among them, at least one targeted laboratory test was given in 652 episodes of care (643 patients) before rt-PA (Figure 1). As shown in Figure 1, among the patients who were diagnosed with acute ischemic stroke and given rt-PA, 537 had favorable outcomes and 106 had poor outcomes. Table 1 describes the demographic characteristics and stroke severity of these patients. Compared with patients with favorable outcomes, patients with poor outcomes were more likely to be older and have higher SSIs. The standardized residuals of stroke severity are shown in Table S1. The distribution of sex was also different between the two groups. Among the laboratory test results, hemoglobin level, mean corpuscular hemoglobin concentration (MCHC), platelet counts, and glucose levels were different between patients with favorable and poor outcomes (Table 2). Higher glucose values, lower hemoglobin levels, lower MCHCs, and lower platelet counts were significantly associated with an increased risk of a poor outcome.The medical histories of the patients, defined based on the Elixhauser comorbidity classification, are summarized in Table 3. The two groups did not differ in terms of their medical histories (all p-values  >  0.05).We included laboratory test results and medical histories that were different (p-value < 0.1) between patients with favorable and poor outcomes and their demographic characteristics as independent variables in the Lasso model. Table 4 shows the model’s coefficients (lambda = 0.009326033). Only the important variables whose coefficient was not zero are shown. Variables that emerged as risk factors of poor treatment outcome for patients with acute ischemic stroke included patients who were female and had anemia, a more severe SSI, a higher glucose value, lower MCHC, and a lower platelet count.In the sensitivity analysis, we redefined a poor outcome as in-hospital death or ICU stay. There were 591 and 61 episodes in the new favorable and poor outcome groups, respectively. Compared with the univariate analysis of patient characteristics, the variables that were significantly different between the two groups were the same in this sensitivity analysis (Table S2). In the univariate analysis of the laboratory test results, higher glucose and potassium values were significantly associated with an increased risk of poor treatment outcome (Table S3). In contrast to the primary analysis (Table 2), the platelet counts not different, but the RBC counts and potassium levels were different between the two groups in this sensitivity analysis. The results of the medical histories are described in Table S4; only hypertension complicated by other diseases was associated with poor outcomes. The risk factor selected by Lasso in this analysis was SSI, whose coefficient was 0.146 and lambda was 0.1519911.In the second sensitivity analysis, we divided the laboratory test results into categories based on their reference ranges, and the univariate analysis results are shown in Table S5. This table shows that poor outcomes are associated with abnormal levels of hemoglobin, hematocrit, RBCs, and glucose. Above normal values of hemoglobin and glucose were more likely to result in a poor prognosis. Regarding risk factors, after transforming the laboratory test results, gender, SSI, hemoglobin, hematocrit, sodium, glucose, and a history of anemia were considered relevant factors selected by the Lasso method, as shown in Table S6. Similar to the primary analysis results, being female, having a higher SSI and glucose level, and anemia, were also found to be important features in this sensitivity analysis.Due to undesirable side effects, such as hemorrhaging, and low usage rates of rt-PA [39], it is essential to identify risk factors relative to treatment outcomes. We included demographic information, medical histories, and laboratory test results to determine the variables associated with the outcome of rt-PA therapy. Female patients, patients with anemia, patients with a higher SSI and glucose level, and lower MCHCs and platelet counts were more likely to have poor outcomes after receiving rt-PA. Stroke severity was selected as an important risk factor in the primary analysis and in the two sensitivity analyses. Anemia, female gender, and higher serum glucose levels were selected in the primary analysis and the sensitivity analysis, which grouped laboratory results based on their reference ranges. In the sensitivity analysis that used an alternative outcome definition, only SSI was kept in the Lasso model. The possible reason is that the number of episodes in the alternative poor outcome groups was only 61; the alternative poor outcome group was much smaller than the favorable outcome group.Previous studies have shown that stroke severity and serum glucose level had a significant influence on intracerebral hemorrhage after intravenous tissue plasminogen activator therapy [22,23,24,40], which was consistent with our findings, even though we used SSI as a substitute for NIHSS score as a measure of stroke severity. In addition to the glucose level, diabetes may be associated with poor outcome of rt-PA therapy [41,42]. One study found that in the diabetic subgroup, the glycated hemoglobin index was positively correlated with symptomatic intracranial hemorrhage [40]. Instead of focusing on a specific subgroup, we considered all the patients with acute ischemic stroke who were treated with rt-PA as study cases. In the general population, the glycated hemoglobin index test was performed in only a few patients; therefore, we only included the glucose level in laboratory assessments. A recent study used functional ambulatory status as an outcome to investigate the association between risk factors and outcomes in ischemic stroke patients who received rt-PA and were on antihypertensive medications [24]. In our study, we defined poor outcomes as in-hospital death, ICU stay, and prolonged LOS, which are different from the published study.Gender differences among patients with acute ischemic stroke who received rt-PA have been discussed in many studies [43,44,45,46,47,48,49,50,51]. A systematic review suggested that no gender difference existed in the outcome among patients treated with intravenous rt-PA [45]. The clinical outcome and the number of patients with a favorable outcome did not differ between women and men [50]. Few studies have reported that the usual gender difference in outcomes favoring men was not observed among patients treated with rt-PA [43,44,47,51]. However, similar to the findings of our study, few studies showed that women have a higher poststroke mortality, rate of disability, depression, and dementia, and poorer mRS (modified rankin scale) scores at discharge compared with men [48,49]. Gender differences in symptoms at presentation may create treatment delays for women [52]. The difference found in this study could possibly be explained by physiologic derangement not included in the dataset [14,50]. Similar to a previous study [46], we found that middle-aged women have a better outcome than middle-aged men, whereas at a more advanced age, men have a better outcome than women. However, the differences are not statistically significant. The gender differences among rt-PA therapy are still different across studies, and further research is required.Our study used the Lasso approach to select significant features in the multivariable analysis because there was a high correlation between MCHC, hemoglobin levels, and hematocrit levels. In addition, some studies reported that the regression coefficients in a stepwise selection model may have considerable bias [53,54]. Similarly, with stepwise regression, Lasso, which adds regularization to penalize the number of parameters in the model, prevents overfitting and prevents multicollinearity.The main feature of our study is that we considered the demographic characteristics, laboratory test results, and medical history for exploring the risk factors for poor outcomes after receiving rt-PA. Only a few studies include laboratory test results for rt-PA treatment outcome analysis and no study has investigated the associations between laboratory results and poor treatment outcome in the general population of patients with acute ischemic stroke; we found that glucose level, MCHCs, and platelet counts were associated with the treatment outcome. Moreover, because laboratory test results can be described as normal and abnormal, and the definition of treatment outcome can affect the analysis results, we also evaluated the effect of changing the definition of the variables. To address the problems mentioned above, we conducted sensitivity analyses to evaluate the effect of applying different outcome definitions and grouping the laboratory test results based on their reference ranges. Our results can provide prognostic information about using rt-PA for ischemic stroke.Our study has several limitations. First, the number of patients who were treated with rt-PA was only 643, due to the low usage of rt-PA, although we included 11 years of data and 42,679 acute ischemic stroke episodes. Second, Charlson comorbidities have often been used to measure comorbidities [55]. However, the Charlson comorbidity index only includes 17 comorbidity categories, and some important diseases related to rt-PA outcome evaluation, such as anemia, are not included in the Charlson comorbidity index. To extensively define and analyze the medical histories of stroke patients, we chose Elixhauser comorbidities index, which includes 30 comorbidity categories, to group the diagnoses [34,56]. Third, medical histories might be missing if patients do not have a related diagnosis in their EMR. However, in our study group, more than 70% of the patients had visited CGMH before having a stroke. Moreover, in-hospital EMRs alone should only be used to build a risk model in worst-case scenarios wherein unconscious patients are admitted to the emergency department and no additional information can be provided. Fourth, patients included in the study might be ineligible for rt-PA treatment based on the guidelines. In our study, we included all patients who were given rt-PA for ischemic stroke to ensure a sufficient number of cases and to reflect the conditions in the real world. Another limitation is that time-to-treatment data, which is known as a factor associated with outcomes, was not available in our dataset. A previous study concluded that thrombolytic therapy beyond the 4.5 h time window seems to be associated with a significant increase in mortality in clinical practice [25]. However, according to previous studies, the third quartile of onset-to-treatment time was less than 3 h in Taiwan [2,57], that is, only a small proportion of cases was treated beyond the 4.5 h time window. The other clinical features that are important in predicting the clinical outcome, such as the subtype of stroke [46], cerebral arterial recanalization [58], and the presence and site of occlusion [58] could not be extracted from our dataset. These data should be collected for further analysis, including for building predictive models. For the NIHSS value at admission [46], we used the SSI, a valid substitute for the NIHSS score [36], as a measure of stroke severity. We analyzed the risk factors that may be associated with unfavorable rt-PA treatment outcomes. Our findings demonstrated that female gender, higher serum glucose levels, lower MCHC, lower platelet counts, history of anemia, and severe stroke were the risk factors relevant to rt-PA treatment outcomes, and these findings could help us study the treatment strategy for acute-stage ischemic stroke.The following are available online at https://www.mdpi.com/1660-4601/17/2/618/s1, Table S1. The standardized residuals of stroke severity, Table S2. Univariate analysis of the patients in the sensitivity analysis–outcome definition. Table S3. Univariate analysis of the laboratory results in the sensitivity analysis–outcome definition. Table S4. Univariate analysis of the medical history variables in the sensitivity analysis–outcome definition. Table S5. Univariate analysis of laboratory categorical variables in the sensitivity analysis–transformed laboratory test results. Table S6. Risk factors identified by the Lasso model (lambda: 0.01072267) and their associated coefficients in the sensitivity analyses–transformed laboratory test results.Y.-J.T. and R.-F.H. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Y.-J.T., R.-F.H., S.-T.L., and T.-H.L. analyzed/interpreted the data, performed experiments, designed the study, and wrote the paper. Y.-L.L., C.-L.H., S.-W.L., C.-W.L., J.-D.L., T.-I.P., and T.-H.L. reviewed/edited the manuscript for important intellectual content and provided administrative, technical, or material support. Y.-J.T., S.-W.L., C.-L.H., and T.-H.L. obtained funding and supervised the study. All authors have read and agreed to the published version of the manuscript.This research was supported by Chang Gung Memorial Hospital (CMRPD3I0011), the Ministry of Science and Technology, Taiwan (MOST 108-2636-E-182-001, MOST 106-2632-H-182-001), and the Featured Areas Research Center Program within the Framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan (EMRPD1I0431, EMRPD1I0501, and EMRPD1I0481). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.Study flow diagram. rtPA: recombinant tissue-type plasminogen activator.Univariate analysis of the patient characteristics.* p < 0.05, *** p < 0.001, a IQR, interquartile range [first quartile, third quartile], b Q1–Q3, quartile 1–3, c Stroke severity index. SSI: stroke severity index.Univariate analysis of the laboratory results.* p < 0.05, ** p < 0.01, *** p < 0.001, a IQR, interquartile range [first quartile, third quartile], b Q1–Q3, quartile 1–3.Univariate analysis of the medical history variables.Risk factors identified by the Lasso model and their associated coefficients.a Stroke severity index 

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+The purpose of this study was to validate and adapt to the Spanish context of Physical Education, the Spanish version of the Scale of Basic Psychological Needs in the context of physical exercise, with the incorporation of novelty to the scale. The sample that took part in the study was 2372 people from 16 to 48 years old from the province of Almeria. In order to analyze the psychometric properties of the scale, several analyses have been carried out. The results have offered support both for the eight-factor structure and for the higher-order double model where the eight subscales are joined into two constructs called frustration and satisfaction. The structure of both models was invariant with respect to gender and age. Cronbach’s alpha values were above 0.70 in the subscales and scales; and adequate levels of temporal stability. In addition, the subfactors pertaining to the satisfaction of basic psychological needs positively predicted the intrinsic motivation for physical activity, while each of the subfactors of the frustration of psychological needs predicted it negatively. The results of this study provide evidence of the reliability and validity of the BPNS in the Spanish context of physical activity.In recent years, various studies in the field of physical activity and sport have shown the multiple benefits at the physical, cognitive, psychological, emotional, and social levels that are linked to the regular practice of physical activity [1,2]. In this sense, the regular practice of physical activity is linked to the reduction of heart problems, reduction of hypertension, stress, depression, and feelings of loneliness [3]. Despite these benefits, regular physical activity is still very low, with around 61% of the world’s population failing to reach the 300 min per week recommended by the World Health Organization [4]. For this reason, several studies have suggested that experiences linked to the practice of physical activity should be positive in order to encourage adherence [5]. Thus, it is especially important to understand both the negative and positive experiences people have had while practicing PA [6,7]. This study aims to adapt and validate to the Spanish context a scale with which to evaluate basic psychological needs in the area of physical exercise, incorporating novelty.From the Self-Determination Theory (SDT; [8]) it is suggested the existence of a series of psychological needs that are basic and present in all human beings. These needs are necessary for the psychological and social well-being and health of all people, promoting personal growth and development [9]. These basic psychological needs are represented by three essential factors: autonomy, which refers to the fact that people are agents of their own action without external impositions; competence, which refers to having a sense of ability and effectiveness in the action being carried out; and relationship, which refers to the feeling of being integrated into a social group of relevance to the individual [9,10]. However, at present several studies have justified and proposed the incorporation of a fourth basic psychological need called novelty [11,12]. This psychological need refers to the search for new experiences and sensations that have not been experienced or lived before and therefore deviates from the daily routine [13]. This need had previously been mentioned by Deci and Ryan [8] when they defined intrinsic motivation as the active commitment that people acquire with the actions that they find interesting and new and that represent an optimal challenge. This new psychological need is identified with exploration and spontaneous interest, assimilation and improvement as a form of cognitive, emotional and social development [8].The four basic psychological needs are interrelated, so that if one of them diminishes the others will also diminish [13,14]. Therefore, people who feel influenced when they make decisions, unable when they practice physical activity, excluded from the social reference group, and find the activities monotonous and repetitive, would experience a frustration of their basic psychological needs, which are related to the abandonment of activity, lack of commitment, deficits in interpersonal relationships, and, in short, the manifestation of maladaptive behaviors [15]. Conversely, if people feel autonomous when they make decisions, feel competent when they carry out their activities, accepted and integrated into their social reference group, and the activities turn out to be different and attractive, they will experience a satisfaction of psychological needs, which is related to the learning of new skills, commitment to learning, improvement of interpersonal relations and the manifestation of adaptive behaviours [16].At present, there are many studies from SDT, especially from the field of Physical Education (PE) classes, which have analyzed the relationship between novelty and the autonomous motivation of students. In this sense, a study carried out by Trigueros, et al. [17] has shown how those students in PE who had high levels of satisfaction of novelty also had high levels of autonomous motivation for PE classes showing that both factors are related. Thus, it is necessary for teachers to promote new and continuous experiences during the PE classes so that their students feel attracted and interested in order to increase the motivation of the students. From the field of physical activity, we have no record of studies that have considered this factor. However, there are some studies from the field of physical activity that have linked SDT to factors with similar characteristics to those described by the novelty such as: the search for new sensations [18], curiosity [19] and desire [20]. Although it is true that the approach that researchers have used of these variables is close to what has been defined as novelty, the focus of these investigations is different in terms of a possible establishment of a new basic psychological need (for a greater understanding, see González-Cutre, et al., [11]).Despite this dual validation of basic psychological needs, studies on them are highly fragmented. To such an extent that the study of the inexistence of a questionnaire that takes into consideration both aspects (see, [13,14,21,22]). In this sense, a study centred on psychological needs towards life and carried out by Longo, Alcaraz-Ibáñez and Sicilia [23] with university students showed the importance of uniting both valences in order to have a general vision of the influence of psychological needs and their effects.Based on this background, the objective that we propose is to adapt and validate the Basic Psychological Needs Scale (BNPS) to the Spanish context of physical exercise, incorporating the fourth novelty need. Joining in the same scale the satisfaction and frustration of the psychological needs in order to measure both the positive and negative side. The CFA of the proposed instrument is expected to provide adequate adjustment rates for the eight-factor correlated model and the higher-order model. Both models are expected to be invariant with respect to gender and age. In addition, the internal consistency of the factors and their temporal stability is expected to be adequate. A structural equation model will be made to show evidence of validity of the BPNS criteria by analyzing the predictive relationships of each of the psychological needs with respect to the intrinsic motivation for physical activity.A total of 2372 people between the ages of 16 and 48 (M = 28.39; SD = 12.30) taking part in physical activity in various sports centres in Andalusia.In addition, a different sample from the first one participated in the present study in order to carry out the temporal stability, which was made up of 871 persons between 17 and 51 years old (M = 27.65; SD = 9.68). This second group completed the scale on two occasions, with a time interval of two weeks between both data collection.A third independent sample of 2138 people aged 16–49 was used to analyse the predictability of the scale through a structural equation model.The sample used was non-probabilistic incidental, depending on those sports centres and people who had access to them.Satisfaction of basic psychological needs. The validated and adapted version of the Satisfaction of Basic Psychological Needs Scale was used in the exercise by Sánchez and Nuñez [21] whose factors are autonomy, competence, and relationship. The final scale comprises a total of 12 items distributed among the three factors that make up the scale: autonomy, competence, and relationship. In order to measure the satisfaction of novelty towards physical exercise, the items corresponding to the factor with the same name belonging to the scale of Satisfaction of Psychological Needs towards Physical Education classes of Trigueros, et al., [13] were adapted. This factor is made up of six items.Frustration of psychological needs. The adapted version of the Psychological Needs Frustration Scale was used in physical exercise (PNFS; [22]). The scale was preceded by the heading “In my PE classes...” and consists of 12 items, distributed equally among each of the factors that make up the scale (i.e., autonomy, competence, relationship with others). In order to measure the frustration of novelty, the items corresponding to the factor with the same name belonging to the scale of Frustration of Psychological Needs were adapted to the Physical Education classes of Trigueros, et al., [14]. This factor is made up of five items.Each of the above scales is of the Likert type, ranging from 1 (not true at all) to 7 (totally true).The factor with the same name from the Behaviour Regulation in Practice Questionnaire (BREQ-3) by González-Cutre, Sicilia and Alberto Fernández was used [24]. The scale was headed by the following heading, “I do physical exercise...” and the intrinsic motivation factor consisted of 4 items. The questionnaire is of the Likert type, ranging from 0 (nothing true) to 4 (totally true).Some sports centres were asked to collaborate in the research, so that they could allow us to reach the people who come to the sports centre to do physical exercise and explain to them the objective of the study. In order to participate, it was necessary to fill out the informed consent form. When filling in the questionnaires, we insisted on the anonymity of the answers, emphasizing that they were being asked for their own opinions and that participation was voluntary. A member of the research group was present while people completed the questionnaires to answer any questions they might have. All ethical procedures for data collection were respected, taking about 20 min to complete the questionnaires.To analyze the psychometric properties of the BNPS towards physical exercise, a series of analyses were carried out in order to be able to determine its validity and reliability. Firstly, two confirmatory factor analyses (CFAs) were carried out in order to test the factor structure of the questionnaire. Then, a multi-group analysis was performed in relation to sex and age in order to determine if the questionnaire is understood in a similar way without age or sex being determinants. Subsequently, the statistical-descriptive analysis and the internal consistency analysis were carried out using Cronbach’s alpha in order to test the reliability of the instrument and a temporal stability analysis using a test-retest. Finally, a criteria analysis was carried out through a structural equation model, where each of the factors that make up the scale was related to the intrinsic motivation. The statistical packages SPSS 25.0 and AMOS 22.0 (IBM, Armonk, NY, USA) were used for the data analysis.The maximum likelihood estimation method was used along with the bootstrapping procedure for the AFC and the path analysis. In order to accept or reject the model tested, a set of adjustment indexes was taken into consideration [25]: Since χ2 is very sensitive to sample size, χ2/df was used and values below 3 were considered acceptable; IFC (Comparative Fit Index) and IFI (Incremental Fit Index) show a good fit with values equal to or higher 0.95; RMSEA (Root Mean Square Error of Approximation) plus its confidence interval (CI) at 90%, and SRMR (Standardized Root Mean Square Residual) are considered acceptable with values equal to or less than 0.06 and 0.08, respectively.The fit indices of the model tested (Figure 1) revealed the following settings: χ2 (532. N = 2372) = 1044.73, p < 0.001; χ2/df = 1.96; CFI = 0.95; IFI = 0.95; RMSEA = 0.052 (CI 90% = 0.046–0.057); SRMR = 0.032. Standardized regression weights ranged from 0.70 to 0.86 and were statistically significant (p < 0.001).Once the model was determined, a higher order model was tested (e.g., the eight first order factors converging into two higher order factors called frustration and satisfaction). The adjustment indices of this model are as follows (Figure 2): χ2 (551. N = 2372) = 958.04, p < 0.001; χ2/df = 1.74; CFI = 0.96; IFI = 0.96; RMSEA = 0.052 (CI 90% = 0.047–0.058); SRMR = 0.041. All standardized regression weights were significant (p < 0.001), with 0.85 for frustration of competence, 0.84 for frustration of autonomy, 0.72 for frustration of relatedness, 0.81 for frustration of novelty, 0.56 for satisfaction of competence, 0.82 for satisfaction of autonomy, 0.79 for satisfaction of relatedness, and 0.78 for satisfaction of novelty. As for the correlations between the higher order factors, they were −0.51, being statistically significant (p < 0.001).A multi-group analysis was carried out in order to find out whether the factor structure of the model is invariant with respect to gender and age. As shown in Table 1 and Table 2 for the eight-factor model, no significant differences were observed in the statistic χ2 between model 1 (non-constrained model) and model 2 (model with invariant measurement weights) and yes with respect to model 3 (invariant structural covariance models) and model 4 (invariant residual measures model). In addition, Table 1 and Table 2 show the adjustment rates for the six models compared within the higher-order two-factor structure. Likewise, no significant differences were found between model 1 and model 2 and whether there were significant differences between model 3, model 4 (structural covariance model), model 5 (structural invariant residuals model), and model 6 (invariant residual measures model). The differences between models 1 and 2 constitute a minimum criterion to be able to say that the factor structure of the questionnaire, a four-factor model and the higher order model, is invariant with respect to gender [26].In Table 3, the means, standard deviation and bivariate correlations are shown. The correlations reflected a positive association between those factors linked to each other and a negative association between the opposites. In addition, Table 3 shows that the internal consistency analysis reflected Cronbach’s alpha values greater than 0.70 [27,28] for each of the factors.In the temporal stability analysis, intra-class correlation coefficients (ICC) and their confidence intervals (CI) were calculated.In order to analyze the criterion validity of the BPNS, a structural equation model was made to analyze the predictability of the scale. The fit indices of the model tested (Figure 3) revealed the following fit indices: χ2 (51. N = 2138) = 147.67, p < 0.001; χ2/df = 2.89; IFC = 0.96; IFI = 0.96; RMSEA = 0.051 (CI 90% = 0.049–0.061); SRMR = 0.038.The present study aims to determine the validity of the factor structure, internal consistency, temporal stability and predictive validity of the BPNS towards physical exercise. The results have shown that the BPNS as an instrument with adequate validity and reliability to evaluate the positive and negative aspects of basic psychological needs towards physical exercise, also incorporating novelty. In this way, an effective tool is available that can help researchers and professionals to understand in greater depth the predictive effects of basic psychological needs on the adaptive and maladaptive behaviors of people who engage in any type of physical activity [29,30].The first CFA revealed that the factorial structure of the BPNS showed adequate adjustment rates for the eight-factor model, showing a positive relationship between those needs with the same root and a negative relationship between those needs with different roots. These results are similar to various studies that have been carried out to date [10,11,12,14], and are in line with the postulates of the SDT [5,8] where the reciprocity between each of the psychological needs is defended, also incorporating the novelty, continuing the path of previous studies (e.g., González-Cutre et al., [11]; Kashdan, and Silvia, [31]). As for the second CFA, the factor structure of the higher-order dual model revealed acceptable adjustment rates, showing a negative correlation between frustration and satisfaction. This model is interesting because it supports the use of an overall value composed of the mean of the sub-factors, which can be used by researchers to simplify models where several constructs are present. Furthermore, its use is justified since a study by Gagné, Ryan, and Bargmann [32] suggested that needs tend to function as a single “body” in different situations.On the other hand, the reliability and temporal stability analyses revealed acceptable adjustment rates for all eight subscales and higher order factors. As for the mutli-group analysis, it showed that the structure of the eight-factor model and the higher-order model of the BPNS were invariant with respect to gender and age. These results support the use of the questionnaire in future research where it is intended to compare means between boys and girls as well as between different ages.Finally, evidence of predictive validity for the scale was found through the structural equation model. This analysis showed that each of the factors pertaining to the satisfaction of basic psychological needs positively predicted the intrinsic motivation, while the frustration of basic psychological needs predicted it negatively. These results are similar to previous studies where satisfaction of psychological needs was positively related to intrinsic motivation [33,34] and frustration of psychological needs was negatively related to intrinsic motivation [35,36]. These relationships appear to support the postulates of SDT that the frustration of psychological needs may lead to the search for a collateral satisfaction that compensates for this feeling of frustration by producing a series of disadaptive consequences or inhibition that may be contrary to personal well-being, and conversely, the satisfaction of basic psychological needs is closer to adaptive behaviors and continued participation that promote personal well-being [37].Despite the results achieved by this study, a number of limitations should be highlighted. In this sense, future studies should continue to analyze the factorial structure of the questionnaire since the creation and/or adaptation of a questionnaire is a continuous process that requires an in-depth analysis of its functioning in different populations with equally different sociodemographic characteristics.BPNS towards physical this scale exercise offers researchers a valid and effective tool that can help measure people’s perceived basic psychological needs towards physical exercise. Moreover, it is in line with the postulates of the SDT and will allow further assessment of the contextual factors inherent to physical activity can undermine or promote psychological well-being by promoting personal development.Conceptualization, R.T.; Data curation, C.M.-A. and R.L.-L.; Formal analysis, J.M.A.-P.; Funding acquisition, J.F.Á.; Investigation, A.J.C.; Methodology, R.T.; Project administration, A.J.C.; Resources, J.F.Á., J.M.A.-P. and P.R.; Software, R.L.-L.; Visualization, R.T.; Writing—original draft, R.T.; Writing—review & editing, J.M.A.-P. and P.R. ’All authors have read and agreed to the published version of the manuscript.Convocatoria Ayudas a Transferencia de Investigación “Transfiere” 2018 (Ref. 001364).The authors declare no conflict of interest.Confirmatory factor analysis of the Basic Psychological Needs Scale (BPNS).Higher order confirmatory factor analysis of the BPNS.Structural equation model.Multi-group Gender Invariance Analysis.Note: Comparative Fit Index (CFI); Incremental Fit Index (IFI); Root Mean Square Error of Approximation (RMSEA); Standardized Root Mean Square Residual (SRMR); Confidence Interval CI; * p < 0.05; ** p < 0.01; *** p < 0.001.Multi-group Age Invariance Analysis.Note: ** p < 0.01; *** p < 0.001.Descriptive Statistics and Correlations between all BPNS Factors.Note: * p < 0.05; ** p < 0.01; *** p < 0.001.

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+On the basis of PM2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors.In recent years, with the rapid development of industrialization and urbanization, the consumption of energy resources has continued to increase, and China is now suffering from a relatively severe situation of air pollution [1,2]. Facing the increasing pressure for air pollution prevention, the Chinese government promulgated and implemented the most stringent atmospheric pollution action plan in China’s history: the Action Plan of Air Pollution Control (hereinafter referred to as “Ten Measures for Air”) on 12 September 2013 [3]. Then, the main cities such as Beijing, Shanghai, Wuhan, and Chengdu enacted the Action Plan to improve air quality. For the 74 key cities of China, annual average concentration of PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) dropped by 34.7%, from 72 μg/m³ in 2013 to 47 μg/m³ in 2017 [4]. Despite the overall improvement in air quality throughout the country, there are still 64.2% of cities in which the annual average concentration of PM2.5 exceeds China’s second-level environmental air quality standards (35 μg/m³). The current situation of PM2.5 pollution in China is therefore still concerning [4,5,6].Epidemiological studies show that PM2.5 has adverse effects on human health. For every 10 μg/m3 increase in PM2.5 concentration, the risk of all-cause, cardiopulmonary, and lung cancer mortality increased by approximately 4%, 6%, and 8%, respectively [7]. Even in areas with light air pollution and a more developed economy, the exposure to PM2.5 could increase the risk of resident mortality, and the strongest extra risk for death is increased by 0.74% (95% confidence interval (CI): 0.11–1.38%) for every 10 μg/m3 increase in PM2.5 concentration [8]. According to the 2015 Global Burden of Disease (GBD 2015) report, PM2.5 has become the fifth global death risk factor in the world, and the consequences of exposure to PM2.5 contributed to an estimated 4.2 million (95% uncertainty interval: 3.7–4.8 million) deaths globally [9]. Recently, in order to quantitatively evaluate the effects of air pollution prevention policy implementation, the health benefits of air quality improvement and their monetization values were studied in different countries on the basis of epidemiological studies [10,11,12,13,14,15]. Abel et al. quantified the health benefits of a 12% summertime (June, July, and August) reduction in baseload electricity demand in the United States on the basis of epidemiological studies and the corresponding reduction rate of PM2.5 (0.55%). Their results showed that the reduced exposure to PM2.5 annually avoided 300 premature deaths (95% CI: 60 to 580), valued at about USD 2.8 billion (USD 0.13 billion to USD 9.3 billion) [15]. In China, the implementation of Ten Measures for Air prevented about 60,213 residents from premature death, and the estimated increase in health benefits was approximately 54.97 billion Chinese yuan (RMB, 1 RMB = 0.1417 USD on 14 October 2019) [16]. Furthermore, Dai et al. quantitatively evaluated the public health benefits of Shanghai’s Clean Air Action Plan (2013–2017), and the results showed that the total health benefits realized by Shanghai were 11.841 billion RMB (95% CI: 50.24–178.19 billion RMB), accounting for 0.55% of Shanghai’s Gross Domestic Product (GDP) in 2013 (95% CI: 0.23%–0.82%) [17]. These studies suggested that global preventative PM2.5 pollution policies had public health effects and corresponding economic benefits to different extents.In February 2014, as one of the first-phase monitoring and implementation cities of the new standard (No. GB3095–2012), the only mega city in the six central provinces of China, and the capital of Hubei province, Wuhan issued the Air Improvement Action Plan (Plan; 2013–2017). The Plan deployed appropriate measures such as strengthening pollution prevention, optimizing industrial structures, innovating environmental management mechanisms, and strengthening information disclosure to improve air quality (details are shown in Table S1) [18]. Since the implementation of the Plan, the annual average concentration of PM2.5 was decreased from 94 μg/m3 in 2013 to 53 μg/m³ in 2017 (by 43.6% decrease). The number of days with excellent (0 < Air Quality Index (AQI) ≤ 50) or good ambient air quality (51 < AQI ≤ 100) in Wuhan from 2013 to 2017 were 160, 182, 192, 237, and 255 d, respectively, showing a growing annually tendency (Details about AQI are shown in Tables S2 and S3) [19,20]. To our best knowledge, no scholars have studied the health economic benefits of improving the air quality in Wuhan from 2013 to 2017. In order to provide a quantitative cost–benefit analysis of the Plan and synthetically improve corresponding local environmental policies, it was important to investigate the health economic benefits of reducing PM2.5 concentration in Wuhan.The major aims of this study were: (1) to estimate the annual average concentration of PM2.5 decrease in 13 districts in Wuhan from 2013 to 2017 by using monitoring data derived from nationally controlled sites and the Voronoi neighbor averaging (VNA) interpolation method; (2) to explore the avoided premature mortalities attributed to PM2.5 reductions for all districts in Wuhan on the basis of local demographic data, baseline all-cause mortality rate, and health impact functions; (3) to calculate the economic benefits of reducing PM2.5 concentration using the value of statistical life (VSL) method; (4) to evaluate the effectiveness and pitfalls of the Air Improvement Action Plan in Wuhan.The City of Wuhan, the provincial capital of Hubei Province, is an important industrial, science, and education base in China, a comprehensive transportation hub, a central Chinese tourism center city, and the core city of the Yangtze River Economic Belt. The city has a northern semitropical monsoon climate, and has four distinct seasons. The city has jurisdiction over 13 municipal districts with a total area of 8659.15 km2. Of these 13 municipal districts, Jiang’an District, Jianghan District, Qiaokou District, Hanyang District, Wuchang District, Qingshan District, and Hongshan District are central urban districts; while Dongxihu District, Hannan District, Caidian District, Jiangxia District, Huangpi District, and Xinzhou District are suburban districts. In recent years, the city has witnessed rapid urban expansion, and both the areas of built-up land and vegetation has increased [21]. In 2017, it had a population of over 10.89 million, regional GDP was 1341.03 billion RMB (ranking first in Central China), and the gross industrial output value above the designated size was 1443.33 billion RMB [22]. Moreover, the composition of primary, secondary, and tertiary industry was 3.0:43.7:53.3, and the per capita disposable income of residents was 38,642 RMB [22]. According to the official research in 2016 on the source identification of atmospheric particulate matter in Wuhan (http://www.hubei.gov.cn/gzhd/gzhd/hygq_49009/), results showed that the pollution contribution rates of industrial production, motor vehicle exhaust, coal burning, dust, and others (including biomass burning, living sources, agricultural sources) were 32%, 27%, 20%, 9%, and 12%, respectively. According to the statistics of the Wuhan Eco-Environment Bureau, in 2017, motor vehicles in Wuhan numbered 2.88 million, an increase of 11.27% compared to 2016 [23]. In recent years, days during which the city’s primary pollutant was PM2.5 accounted for more than 60% of the annual pollution days [19]. Facing the local pollution status of PM2.5 and its potential health exposure risk, it was of significance to scientifically assess, analyze and make a comprehensive management policy for relevant decision makers.This study obtained data of the nationally controlled ambient air quality monitoring sites from the Wuhan Environmental Status Bulletin (2013–2017) [19]. The layout of the national air control points of Wuhan Ambient Air Quality Monitoring is shown in Figure 1. Chenhu Qihao (S10) is a background site. On the basis of data from these sites, the annual average PM2.5 concentration of 13 districts in Wuhan was simulated by using the built-in Voronoi neighbor averaging (VNA) interpolation method of BenMAP-CE software [24].BenMAP-CE v1.4 was used to assess the health benefits of improving air quality in Wuhan, which is a health assessment tool for air pollution control designed by the US Environmental Protection Agency (EPA) and South China University of Technology [25,26]. The health impact function is used to assess changes in adverse health effects associated with changes in exposure to air pollution [27]. BenMAP-CE can generate the air quality map layer in the baseline scenario and control each scenario on the basis of its pollutant concentrations. Then, the air quality map layers in the above scenarios were matched with the map layer of the exposed population data. Furthermore, the health impact function is used to calculate the health benefits due to changes in pollutant concentration [28]. Since death is the most significant end point of various health effects related to PM2.5 pollution, this paper chooses all-cause death as the end point of health effects [29,30]. For this study, Equation (1) was used to evaluate the health benefits obtained by controlling the PM2.5 concentration in Wuhan [26].
+        (1)ΔY = Y0(1 − e−βΔPM2.5)∗Pop
+        where ΔY (person) is avoided premature deaths; Y0 (‰) is the baseline rate of all-cause death in 2017; β is the coefficient between PM2.5 concentration and health effects (concentration–response coefficient); Pop (person) is the exposed population in 2017 (details are in Table S4); and ΔPM2.5 (μg/m³) is the change of annual average concentration of PM2.5 between different years [31]. We chose 2013 as the baseline scenario and 2017 as the control scenario to calculate the premature deaths avoided by controlling PM2.5 pollution in Wuhan at the district level. The data of baseline all-cause mortality rate and the exposed population of Wuhan were obtained from Wuhan statistical yearbook [22]. By comparison with other classical epidemiological studies, we derived β from meta-analysis conducted by Hoek et al. because the study was multiregional meta-analysis and had clear health-effect endpoints [32]. According to the study of Hoek et al., the relative risk (RR) of all-cause mortality was 1.0600 (95% CI: 1.0400, 1.0800) per 10 μg/m³ of long-term exposure to PM2.5. Epidemiological studies linking PM2.5 exposure to all-cause mortality are shown in Table S5, and Supplementary Materials also state details about calculating β on the basis of epidemiological study results.Placing a monetary value on clean air can be essential for the evaluation of air quality improvement policies [33]. Economic benefits allow policy makers to assess the benefits of air pollution strategies from an economic perspective [34]. Monetization methods such as cost of illness (COI), the human capital approach (HCA), and willingness to pay (WTP) are often used to assess the health benefits of controlling air pollution. COI is used to calculate the cost of medical expenses caused by diseases. It is applicable to the calculation of small-scale and high-pollution areas, but it lacks accuracy for areas and cities with larger areas and more complicated pollution situations. HCA emphasizes damage caused by air pollutants to the capital embodied in workers. This method implies that the lives of the rich are more valuable to society than the lives of the poor. The value of the unemployed and the retired elderly is almost zero, and young people who die prematurely have a low value because they have not yet reached the working age and have no source of income when they die. HCA is largely contrary to our concept of sustainable development [35]. Based on the willingness to pay method, value of a statistical life (VSL) refers to the value that society is willing to pay to reduce a certain risk of death or prevent a member of society from an early death. Compared with the three methods above, VSL was selected due to its flexibility and operability [36]. The model for evaluating economic benefits by controlling PM2.5 is shown in Equation (2):(2)HBE = ΔY × VSL
+        where ΔY (person) is avoided premature deaths, VSL (million RMB/person) is the unit economic value of the health endpoint, and HBE is the sum of economic change of the health endpoint.VSL can be obtained in the following three ways. One is to obtain first-hand data of the study area. For example, Wang and Mullahy used the contingent valuation method (CVM) to assess the willingness to pay to reduce fatal risk by improving air quality in Chongqing, China [37]. The average annual income of 500 respondents was 490 US dollars, and its VSL was 34,458 US dollars. Hammitt and Zhou conducted a survey in Beijing, Anqing and the rural areas near Anqing in 1999, with VSL values ranging from 4000 US dollars to 17,000 US dollars [38]. Secondly, relevant VSL values are obtained through meta-analysis. For example, the research results of Xu et al. showed that air pollution-related VSL in China was about 0.86 million RMB, urban VSL was about 1.59 million RMB, and rural VSL was about 0.32 million RMB [39]. The third is the result transfer method, that is, the VSL of residents in the study area in the particular year can be obtained through formula conversion [27,40]. When limited by workforce and financial resources, this method could economically and effectively obtain the VSL of the designated year in a research area [14,27]. For reflecting differences in the average income levels, it is necessary to transfer the international estimates across countries and within a country over time [27]. The initial VSL of the result transfer method could be derived from meta-analysis, the CVM, or the results transferred by other studies [17,41,42]. Because the statistical caliber of “per capita disposable income” in statistical yearbooks of different regions slightly varies, this study converted the VSL of Shanghai residents in 2017 (4.22 million RMB) on the basis of the results of Dai et al. [17]. Then, the VSL of Wuhan residents in 2017 was calculated on the basis of the Equation (3):(3)VSLWH2017= 4.22 × (IWH2017ISH2017)e
+        where VSLWH2017 (million RMB/person) is the VSL of Wuhan residents in 2017; IWH2017 (RMB/person) and ISH2017 (RMB/person) are the per capita disposable income of Wuhan and Shanghai in 2017, respectively; and e is the elastic coefficient of WTP and is assumed to be 0.8. The number of the health impacts of PM2.5 concentration changes multiplied by the VSL of each individual were the economic benefits of controlling PM2.5 pollution in the study area.Annual average concentration changes of PM2.5 in Wuhan in 2013–2017 are shown in Table 1. Furthermore, on the basis of monthly average concentrations of PM2.5 in Wuhan, the highest and lowest values are shown in a boxplot in Figure S1. After the implementation of the Air Quality Improvement Action Plan, the annual average PM2.5 concentration in Wuhan significantly decreased, from 1.7 times to 0.5 times in excess of the national ambient air quality standard (35 μg/m³), and from 8.4 times to 4.3 times in excess of the air quality guidelines (AQG) set by the World Health Organization (WHO; 10 μg/m³) [43]. Although the implementation of the Plan had a good effect on reducing the PM2.5 exposure concentration in Wuhan, it is necessary to quantitatively assess the cost–benefit effects of its implementation and to further develop targeted improvement. Further comparison of the average annual PM2.5 concentration in the research area in 2013 and 2017 showed that the decrease in PM2.5 concentration in Wuchang District (46.7%), Jianghan District (46.0%), and Hanyang District (45.2%), Jiang’an District (44.8%), Qiaokou District (44.8%), Xinzhou District (44.8%), and Dongxihu District (44.2%) was above the city’s average (43.6%).On the basis of Equation (1), many researchers only compared the ΔPM2.5 in beginning and end of their studied time lag [29,44]. The number of avoided premature deaths due to PM2.5 reduction in Wuhan were shown in Table 2. The total number of avoided premature deaths in these four periods were 21,384 (95% CI: 15,004 to 27,255), accounting for 7.84% of the total deaths in Wuhan between 2013 and 2017. The avoided premature deaths in Huangpi District (2842 people), Wuchang District (2722 people), Hongshan District (2670 people), and Xinzhou District (2457 people) were all over 2000 people due to the decrease of PM2.5 concentration. Avoided premature deaths in seven central urban districts totalled 12,657, which was 1.45 times as many as in six suburban districts. In addition to the decrease of PM2.5 concentration, the above results were also related to the exposed population base of the study area.In 2017, the value of the statistical life of residents in Wuhan was 3.01 million RMB. Combined with the premature deaths avoided by the decrease of PM2.5 concentration by annual estimation, the economic benefits obtained in all districts of Wuhan between 2013 to 2017 were calculated and were shown in Figure 2. The economic benefits of controlling PM2.5 pollution in Wuhan were 64.35 billion RMB (95% CI: 45.15 to 82.02 billion, RMB), accounting for about 4.8% (95% CI: 3.4% to 6.1%) of the city’s GDP in 2017. To the authors’ best knowledge, the Wuhan government planned to invest 28 billion RMB to work on air pollution from 2013 to 2017 [45]. According to the assessment, the economic benefits were higher than the special funds set up by the Wuhan government to improve air quality. The economic benefits gained in the central urban districts were 38.09 billion RMB, which was 11.83 billion RMB more than the benefits in suburban districts. Economic benefits in D12 (Huangpi District, 8.55 billion RMB), D5 (Wuchang District, 8.19 billion RMB), D7 (Hongshan District, 8.04 billion RMB), D13 (Xinzhou District, 7.39 billion RMB), and D1 (Jiang’an District, 5.78 billion RMB) were more than the average level in Wuhan (4.95 billion RMB). Due to it having the smallest reduction in PM2.5 concentration and the smallest number of exposed people, the economic benefits obtained in D9 (Hannan District, 0.66 billion RMB) were obviously lower than the average level of the whole city.Compared with cities that did not implement similar policies to improve air quality between 2013 and 2017, Wuhan city witnessed a larger drop in annual average concentration of PM2.5. For example, the annual average PM2.5 concentration in Kunming, Urumqi, and Wuhan city decreased by 30.95% (from 42 to 29 μg/m³), 19.54% (from 87 to 70 μg/m³), and 43.6% (from 94 to 53 μg/m³) from 2013–2017, respectively. Perhaps this comparison could serve as an indication that a region with a policy to improve air quality may see a larger drop in PM2.5 concentrations than a region without such a policy. During the period of implementation of the Air Improvement Action Plan, Wuhan obtained great health economic benefits due to the control of PM2.5. However, on the basis of the impact of climate conditions, enterprise production cycles, and other factors on air quality, the following contents of the Plan could be improved. First, the Plan only focused on the decline of PM2.5 annual average concentration, and did not develop a control plan concerning quarterly, monthly, and daily PM2.5 average concentration. This would increase the risk of residents suffering from the acute effects of PM2.5 in the case of a pollutant concentration surge. Second, the plan only considered establishing stricter emission standards in the city’s areas at upwind direction (Jiang’an, Qingshan, Huangpi, and Xinzhou District) when formulating emission standards. On the basis of health economics, the densely populated areas (Wuchang and Hongshan District) also need to establish stricter emission standards.When evaluating the health benefits for controlling air pollution, one of the most important differences lies in the choice of control scenarios. Some scholars chose the ambient air quality standards (or a threshold value that does not produce health effects, or a concentration value at the clean level), others have simulated the pollutant concentrations as a control scenario on the basis of the assumed policy scenario, and others still used the actual concentrations of the evaluation years as a control scenario [10,16,46,47,48]. For example, Wu et al. took the target value of the first phase of the WHO interim target-1 (that is, China’s second-level environmental air quality standards, 35 μg/m³) as the control scenario to estimate premature deaths in China in 2013 and 2017, then subtracted the results of 2013 from the results of 2017 to obtain the number of premature deaths that could have been prevented by the implementation of the Air Pollution Prevention and Control Action Plan (2013–2017) [16]. We used the actual concentrations between 2013 and 2017 to calculate the PM2.5-related health benefits in Wuhan. This method could help to provide an overall estimation in the number of PM2.5-related avoided premature deaths in 2017 due to the Air Improvement Action Plan in Wuhan (2013–2017), and will avoid misunderstandings of the pathophysiological effects of air quality, as well as biases on short-term and long-term health impacts. In addition, Liu et al. divided 2010–2015 into five periods (2010–2011, 2011–2012, 2012–2013, 2013–2014, and 2014–2015) to evaluate the long-term health benefits of air quality improvement in China [46]. We employed a similar annual estimation method to calculate the health economic benefits since the implementation of the Air Improvement Action Plan in Wuhan—results are shown in Table S6 and Figure S2. Table S7 compares our results with other studies on the health economic benefits obtained in China during 2013 to 2017. Results vary for the study areas and estimation methods, but it is certain that the annual average concentration of PM2.5 in China has significantly decreased in recent years, which has led to greater health and economic benefits.There are several uncertainties and limitations in evaluating the health economic benefits of the Air Improvement Action Plan in Wuhan City. In order to improve the evaluation method of PM2.5-related health economic benefits and increase public trust in this method, we also discuss the following possible solutions to the limitations [49]. In particular: (1) The district-level all-cause mortality is set to be uniform. Because variations in urbanization and PM2.5 pollution vary in different districts of Wuhan, in order to better account for these factors, we used district-level population data and district-level PM2.5 data to calculate the health benefits of each district in Wuhan. Optimally, district-level estimates should use district-level baseline all-cause mortality data, but it is difficult to obtain the all-cause mortality data for each district in Wuhan. Therefore, the present assessment assumed that the baseline all-cause mortality rates of the population in each district were the same, which led to a certain deviation in the assessment results [50]. (2) Exposed population may be undercounted. Since the baseline all-cause mortality rate of the population in Wuhan statistical yearbook was calculated on the basis of deaths in the registered population, the registered population rather than the permanent population in Wuhan was regarded as the exposed population in this study, to ensure the consistency of statistical coverage [22]. This might partly underestimate the number of avoided premature deaths in Wuhan during 2013–2017 due to the reduction of PM2.5 concentration. On the one hand, we found that although PM2.5 concentrations have declined from 2013 to 2017, the baseline all-cause mortality rates in Wuhan have not declined during the same period [22]. Other studies showed similar results [46,48,51]. Perhaps the number of people who immigrated to Wuhan and became the registered population in 2017 had an obvious impact on the city’s population structure (http://www.whzc.gov.cn/html/2017-07/61.html)—this may have an impact on all-cause mortality (Table S8). In future research, other factors that could help to decrease the PM2.5-related deaths, such as improvements in the education of the people, the healthcare quality, system upgrades, nutrition types, and quality of life improvements also need to be explored. (3) The various health effects of PM2.5 only depends on mass concentration. Since the annual average concentration of PM2.5 in this study was obtained from the nationally controlled ambient air quality monitoring sites, indoor and outdoor exposure were not distinguished, and the chemical compositions of indoor and outdoor air were not analyzed. Meanwhile, distinguishing between indoor and outdoor exposure of the population and studying the harm of different chemical compositions of PM2.5 to human health are both the focuses and difficulties of future research [52]. With continuous research refinement, the management departments could cooperate with academic research institutions to develop a localized health effects database of residents’ air pollution exposure. In the future, accurate personal evaluation can be improved by analyzing a user-level population’s exposure on the basis of an intelligent Internet of Things.Due to the differences in PM2.5 pollution, exposed population, and per capita disposable income in the 13 districts of Wuhan, the health economic benefits obtained by controlling PM2.5 pollution in these districts were quite different. Wuchang District had the highest health economic benefits due to its large population base and significant decline in PM2.5 concentration. Because of a small population base and a smaller PM2.5 decrease than that of other districts, Hannan District had the lowest health economic benefits. The health economic benefits obtained by Wuchang District and Hannan District differed by 12-fold. For Wuhan, in terms of improving air quality, it is necessary to formulate an air quality compensation mechanism and establish hierarchical emission reduction standards and policies on the basis of air quality, population exposure, and economic development of each district.After the implementation of the Air Improvement Action Plan, the areas with a high annual average drop in PM2.5 concentrations were concentrated in central urban areas (except Qingshan district) and Dongxihu and Xinzhou districts in the suburban areas. Due to the implementation of the Air Improvement Action Plan, the total prevented deaths in Wuhan were 21,384 (95% CI: 15,004 to 27,255) during 2013–2017, and the economic benefits add up to 64.35 billion RMB (95% CI: 45.15 to 80.02 billion RMB), accounting for 4.8% (95% CI: 3.4% to 6.1%) of the total GDP of Wuhan in 2017. Health economic benefits were more significant in densely populated areas with a large decrease in PM2.5 concentration. The implementation of the Plan obviously helped to improve the air quality and ensure people’s benefits in Wuhan. Furthermore, on the basis of the district-level result variation, it is recommended to establish a district-level baseline of PM2.5 to assist the precise health economic benefits evaluation. Meanwhile, under integrated consideration of regional differences in socioeconomic development, population size, and environment capacity, it is necessary to establish hierarchical emission reduction standards, and formulate an urban air quality compensation mechanism encouraging an optimized regional industrial/natural layout.The following are available online at https://www.mdpi.com/1660-4601/17/2/620/s1, Table S1: Ten Major tasks of Air Improvement Action Plan in Wuhan City, Table S2: Individual Air Quality index (IAQI) with corresponding pollutant concentrations, Table S3: AQI value and description, Table S4: Exposed population and baseline all-cause mortality rate in Wuhan, Table S5: Epidemiological studies linking PM2.5 exposure to all-cause mortality, Table S6: Total Number of PM2.5-related avoided premature deaths in Wuhan from 2013 to 2017, Table S7: PM2.5-related health economic benefits studies in China during 2013 to 2017, Table S8: Population changes in Wuhan City from 2013 to 2017; Figure S1: Highest and lowest values of monthly average concentration of PM2.5 in Wuhan city during the period of 2015–2017, Figure S2: Economic benefits of PM2.5 concentration reduction in Wuhan from 2013 to 2017 by annual estimation.Z.Q. contributed to interpretation of the analysis. X.W. contributed to the study design and drafted the manuscript. F.L. organized this study, conducted the study design, and revised the manuscript. Y.L. revised the manuscript. X.C. prepared datasets. M.C. performed the data processing. All authors have read and agreed to the published version of the manuscript.This study was supported by the National Social Science Foundation of China (Youth Fund: 19CGL042), the Soft Science Project Foundation of Hubei Province (2018ADC144), the China Postdoctoral Science Foundation (2019M651884), the National Natural Science Foundation of China (71804196), the Fundamental Research Funds for Central University (2722020JCG067) and the Interdisciplinary Innovation Research Project (2722019JX002) from Zhongnan University of Economics and Law.The authors declare no conflicts of interest.Locations of national-controlling ambient air quality monitoring sites in Wuhan: (a) location of Wuhan in China; (b) administration boundary of Wuhan and spatial distribution of nationally controlled ambient air quality monitoring sites, (S10 is Chenhu Qihao (background site)); (c) detailed monitoring site locations on the land-use map of Wuhan urban areas.Economic benefits of PM2.5 concentration reduction in Wuhan between 2013 and 2017 (billion RMB). (D1), 5.78, 9% means that the economic benefit of Jiang’an District was 5.78 billion RMB, accounting for 9% of the total economic benefits of Wuhan.Annual average concentrations of PM2.5 in Wuhan from 2013 to 2017 (μg/m³).Total number of PM2.5-related avoided premature deaths in Wuhan between 2013 and 2017 (95% confidence interval).

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+The world is facing a number of challenges related to food consumption. These are, on the one hand, health effects and, on the other hand, the environmental impact of food production. Radical changes are needed to achieve a sustainable and healthy food production and consumption. Public and institutional meals play a vital role in promoting health and sustainability, since they are responsible for a significant part of food consumption, as well as their “normative influence” on peoples’ food habits. The aim of this paper is to provide an explorative review of the scientific literature, focusing on European research including both concepts of health and sustainability in studies of public meals. Of >3000 papers, 20 were found to satisfy these criteria and were thus included in the review. The results showed that schools and hospitals are the most dominant arenas where both health and sustainability have been addressed. Three different approaches in combining health and sustainability have been found, these are: “Health as embracing sustainability”, “Sustainability as embracing health” and “Health and sustainability as separate concepts”. However, a clear motivation for addressing both health and sustainability is most often missing.The world is facing a number of challenges related to food consumption. On the one hand, health effects related to lifestyle factors such as dietary habits, may lead to non-communicable diseases (NCD) causing the deaths of 41 million people each year, equivalent to 71% of all deaths globally, and also malnutrition with 462 million people being underweight [1,2]. Of the six WHO regions, Europe is the most severely affected by Non-Communicable Disease (NCDs), the four major NCDs—cardiovascular disease, diabetes, cancer, and respiratory diseases—together account for 77% of the burden of disease and almost 86% of premature mortality. Excess bodyweight and intake of energy, saturated fats, trans fats, sugar, and salt, as well as low consumption of vegetables, fruits, and whole grains are considered the leading risk factors [3]. According to malnutrition the demographic situation in Europe with a growing proportion of the population researching ever-increasing ages means increasing prevalence of disease and thereby increasing risk of disease-related malnutrition [4,5]. On the other hand, the environmental impact of food production and distribution is currently responsible for about 25–30% of total greenhouse gas emissions (GHGE) [6] and radical changes are called for to achieve a target of a maximum 2 °C t increase [7,8]. For the EU food and drink are responsible for 20–30% of various environmental impacts derived from private consumption when analysing the life cycle for all goods consumed within EU [9].Taken together, there is an urgent need to integrate health and environmental aspects both at an individual and a societal level, in order to achieve sustainability in food consumption in accordance with the United Nation’s (UN) sustainability goals (SDGs) [10]. The public/institutional meal plays an important role in striving for this goal [11], not only because it is responsible for a significant part of many people’s food consumption, but also through its normative influence on peoples’ food habits [12]. In Sweden alone, about 3 million public meals are served per day at an estimated cost of 20–25 billon SEK per year. These meals are regulated by a number of laws, such as the Educational Act, Social Services Act and the Public Procurement Act according quality and financing.In this paper, public meals are defined as meals taking place in institutional settings [11,13,14]. While the sustainability perspective has only recently been introduced as a research subject in the public meal arena, the health perspective is well established [8,15].The primary aim of this study is, therefore, to provide an explorative review of the scientific literature, focusing on European research including concepts of health and sustainability in studies of public meals.The specific research questions are:-In which public meal arenas has the combination of health and sustainability been addressed?-Which aspects of health and sustainability are primarily put forward?-How are health and sustainability associated and what are the motives for combining these factors?In which public meal arenas has the combination of health and sustainability been addressed?Which aspects of health and sustainability are primarily put forward?How are health and sustainability associated and what are the motives for combining these factors?Public meals appear in different arenas and in different forms, covering various needs [16]. The areas of focus in Sweden, as well in western society in general, have often been rational efficiency, and health and nutrition [17]. There are no common regulations for how public meals should be designed or financed. However, using the school lunch as an example, many countries have policies to provide nutritionally balanced meals reflecting the general food culture of the country [18,19,20].Sweden is one of the leading countries in Europe in terms of the number of public meals served daily and per capita [21]. There is a long history of serving meals free of charge in schools and preschools that started in 1945, and from 1974 free school meals have been served in all Swedish municipalities. The school meal was identified in Sweden early on as an arena for health actions as well as a way to achieve equality in health [22], reaching not only the children but also their parents. These meals have been shown to improve the diet of children [23,24]. In Figure 1, sectors serving public meals in Sweden are shown as an example, illustrating the large variety of public meal settings.Studies have also indicated the role of meals in relation to the health of patients in hospitals [25] and older adults in care homes [26]. These meals constitute one of the most basic parts of medical treatment with the aim of meeting specific nutritional requirements in relation to various medical conditions [27]. In this aspect, patient safety is of the utmost importance with regard to the quality of meals served in the healthcare context. In addition, there are sensory demands; the meals should be appetizing and also constitute an arena for social interaction. Studies have been conducted focusing on food and meals in relation to health among inmates in prison, where the problems of obesity and an unhealthy diet have been raised [28,29]. A study by Wangmo et al. [30] acknowledged the importance of nutritional interventions in prison aimed at improving health. Only a few studies have focused on food and meals in the military service as a public meal arena [31,32].Both “health” and “sustainability” are complex concepts and their meanings are not always consistent. Already in 1946, the World Health Organization (WHO) created a definition of health that aimed not only at focusing on the physical aspects but also the social and mental aspects of health. Even though this definition has been recurrently criticized for being too utopian, it is still referred to and has been awarded for its holistic approach to health.“Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” [36].The role of a healthy diet for the growth of children and the maintenance of health and prevention of disease is indisputable [15,37]. In relation to the social and mental aspects of health, studies have indicated that shared meals, and especially family meals, have positive effects [38,39]. Some studies have also investigated the role of the school meal on mental health, including levels of stress among the students [31], as well as the role of meals for well-being in care homes for elderly persons [40].In 1983, the United Nations created the World Commission on Environment and Development (Brundtland Commission), which defined sustainable development as:
+        “Meeting the needs of the present without compromising the ability of future generations to meet their own needs” [10].“Meeting the needs of the present without compromising the ability of future generations to meet their own needs” [10].In 1992, the first United Nations Conference on Environment and Development (UNCED) was held in which Agenda 21 was developed and adopted. When preparing for a follow up meeting, Rio+20 2012, Colombia proposed the idea of the SDGs, which was adopted by the United Nations Department of Public Information, 64th NGO Conference in Bonn, Germany. The resulting 17 SDGs and associated targets were adopted by all United Nations Member States in 2015. Many of the goals included health and the environment aspects.The EAT-report [8] from 2019 states:
+        “Without action, the world risks failing to meet the UN Sustainable Development Goals (SDGs) and the Paris Agreement, and today’s children will inherit a planet that has been severely degraded and where much of the population will increasingly suffer from malnutrition and preventable disease”.“Without action, the world risks failing to meet the UN Sustainable Development Goals (SDGs) and the Paris Agreement, and today’s children will inherit a planet that has been severely degraded and where much of the population will increasingly suffer from malnutrition and preventable disease”.An explorative review was conducted where scientific databases were searched for articles discussing the public meal in relation to both health and sustainability. The search string used is reported below and the used databases are given in Table 1. The criteria for selection of papers are given in Table 2.Search string for identification of relevant literature:(“Public meal” OR “public meals” OR “Institutional meal” OR “Institutional meals” OR “School meal” OR “School meals” OR “pre-school meal” OR “pre-school meals” OR “School lunch” OR “School lunches” OR “Workplace meal” OR “Workplace meals” OR “Institutional food” OR “Institutional catering” OR “Public restaurant” OR “Public restaurants” OR “Public sector meal” OR “Public sector meals” OR “Public food service” OR “Public food services” OR “School meal system” OR “School meal systems” OR “Public kitchen” OR “Public kitchens” OR “Food service” OR “Food services” OR “institutional fare” OR “Catering service” OR “catering services” OR catering OR Canteen OR Canteens) AND (Sustainability OR Sustainable) AND (Wellbeing OR Health).20 papers fulfilled the criteria and were thus included in this review (Table 3). These papers were further analysed for the following information:Aim;Public meal arena;Aspects of health;Aspects of sustainability;Motive for combining health and sustainability.Aim;Public meal arena;Aspects of health;Aspects of sustainability;Motive for combining health and sustainability.The selected articles and their characteristics are compiled in Table 3 and Table 4.The primary aim has been to provide an explorative review of the scientific literature focusing on European research, where both health and sustainability in relation to public meals have been addressed. In total, 20 articles were analysed, and these are presented in Table 3.By connecting Table 3 to Table 4 using the reference number, each reference may be easily identified. As shown in Table 4, the main public meal arena for discussing health and sustainability was the school, including preschool. School was the main arena in a total of 12 articles, a result also in line with previous studies, where the school has been the primary public meal arena investigated [61].Our findings show that social and mental aspects of health were found to be addressed in only a few articles, e.g., in terms of social equality and overall well-being and growth. In for example paper No 2 school meal programs increase knowledge and awareness of norms around sustainable consumption to meet challenges in both health and sustainability. In papers No 11 and 19 school meals are said to be a tool to improve health in children across ethnic and socioeconomic groups. (Table 2). Commonly, health was understood in terms of physical health only, focusing on a healthy diet and pointing to the urge to eat according to national dietary guidelines. It was illustrated, for example in papers No 3, 4 and 11, as intake of fruit and vegetables, other nutritious food, and an adequate energy intake, often in the context of overweight and obesity among children.Furthermore, sustainability was primarily dealt with in relation to environmental aspects, for example in paper No 5, 13, 14, 17 and 18; however, social and economic aspects were also mentioned in some of the selected articles, see No 1, 2, 3, 4, 6, 7, 10, 11, 15, 19 and 20. As in earlier studies [62,63], in selected papers for example No 11 and 13, sustainability was most often discussed in terms of food waste, but procurement and local production were also discussed in relation to both environmental and economic aspects in papers No 5, 10 and 15. The domination of the environmental aspect of sustainability has previously been criticized [64]. However, in this review, social and economic aspects were in papers No 6 and 10, to some extent, included primarily in terms of politics, welfare, and social justice, and to highlight the importance of including relevant actors (Table 4).The study showed the different approaches to health and sustainability as well as ways of combining these aspects. Three main approaches could be identified, which were evident in some studies as exemplified below, and less apparent in others. The approaches identified are:-Health as embracing sustainability, where health is the point of departure and where sustainability is included as part of health. This is emphasized in relation to health promotion initiatives and how these could also be more sustainable, claiming that health should embrace both aspects. This is the content of papers No 14 and 19 where health and nutritional aspects of school meals also would include sustainability in the form of agricultural improvements or effectiveness. In papers No 16 and 17 health promotion in canteens may promote sustainability through environmental thinking and behaviours. Paper No 3 claims that increased consumption of fruit and vegetables as a part of a healthy diet will have a positive impact on sustainability.-Sustainability as embracing health,where sustainability is in focus and where health should be seen as part of sustainability. This was for example illustrated when focusing on sustainable food procurement which is then also motivated by better nutrition in terms of knowing where the food comes from and how it is produced in papers No 5, 10 and 15 This is also exemplified in studies were environmental challenges are in focus, which thereby requires new sources of nutrition and healthy food. In these cases, health is considered as part of the concept of sustainability. Examples of this are paper No 1 and 6, where food consumption in schools is in focus and paper No 7, where restaurant meals were studied. In paper No 13 infant food and food waste were focused upon.-Health and sustainability as separate concepts, where the link between them was unspecified or undefined. This could be exemplified by the stated role of the school meal to tackle societal challenges related to health and sustainability, although separately which is seen in paper No 8, 9, 10, 12 and 20 In papers No 2, 4, 18 meals in schools and preschool were used as a pedagogical tool, the learning role of the meal was highlighted in these studies, which included learning about both health and sustainability. For example, when investigating portion size both health, in terms of obesity and overweight, and sustainability, related to food waste, were identified as important factors.Health as embracing sustainability, where health is the point of departure and where sustainability is included as part of health. This is emphasized in relation to health promotion initiatives and how these could also be more sustainable, claiming that health should embrace both aspects. This is the content of papers No 14 and 19 where health and nutritional aspects of school meals also would include sustainability in the form of agricultural improvements or effectiveness. In papers No 16 and 17 health promotion in canteens may promote sustainability through environmental thinking and behaviours. Paper No 3 claims that increased consumption of fruit and vegetables as a part of a healthy diet will have a positive impact on sustainability.Sustainability as embracing health,where sustainability is in focus and where health should be seen as part of sustainability. This was for example illustrated when focusing on sustainable food procurement which is then also motivated by better nutrition in terms of knowing where the food comes from and how it is produced in papers No 5, 10 and 15 This is also exemplified in studies were environmental challenges are in focus, which thereby requires new sources of nutrition and healthy food. In these cases, health is considered as part of the concept of sustainability. Examples of this are paper No 1 and 6, where food consumption in schools is in focus and paper No 7, where restaurant meals were studied. In paper No 13 infant food and food waste were focused upon.Health and sustainability as separate concepts, where the link between them was unspecified or undefined. This could be exemplified by the stated role of the school meal to tackle societal challenges related to health and sustainability, although separately which is seen in paper No 8, 9, 10, 12 and 20 In papers No 2, 4, 18 meals in schools and preschool were used as a pedagogical tool, the learning role of the meal was highlighted in these studies, which included learning about both health and sustainability. For example, when investigating portion size both health, in terms of obesity and overweight, and sustainability, related to food waste, were identified as important factors.Most often, a clear motivation for addressing or associating both concepts was lacking. When motivations were given, the need to include challenges related to both health and sustainability was put forward as them both relating to food behavior. This is clear in paper No 12 in which the role food scape is discussed in terms of impact and understanding of food behavior, but also in paper No 11 where school lunch was studied. Thereby, these studies also achieved a more holistic perspective. Another motive for combining health and sustainability was to gain a deeper understanding of the complexity of food behavior, which is seen in papers No 14, 19 and 20. According to the SDGs, WHO Non-communicable diseases country profiles 2018 [2], the UN Intergovernmental Panel on Climate Change (IPCC) [10] and the Lancet EAT report [8], there is an urgent need to increase scientific knowledge about how to embrace both health and sustainability aspects in the context of public meals.Public meals play an important role in influencing people’s food behavior as well as maintaining or improving health [25,26]. Although public meals follow us through most stages of life, from cradle to grave, they have been more or less scientifically overlooked [65]. During recent decades, the focus on sustainability has increased in public debate and policymaking, also putting public meals on the agenda as an important means of achieving both health benefits and sustainability in society [66,67]. Earlier research has generally taken the health aspects of catering in public meals as the point of departure, while sustainability has not been a focus. Since the SDGs were formulated in 2015, a more integrated approach has been put forward. The fact that food and meals are related to most SDGs supports the need for further research and practical efforts directed toward sustainability in the area of public meals.Based on the large number of meals served in public settings every day, these meals have the potential to target both health and sustainability challenges in relation to food and meals. It can be pointed out that the result of this study indicates an association rather than an integration between health and other concepts in all included articles, but especially in paper No 3, 5, 9, and 20. Additionally, health in terms of nutritional needs did not necessarily imply a positive environmental impact as discussed in paper No 10.It may be concluded that schools and hospitals are the most dominant arenas where both health and sustainability have been addressed in order to reach a more holistic perspective on food consumption of public meals. Three different approaches in combining health and sustainability have been found, which are: 
+      “Health as embracing sustainability”, “Sustainability as embracing health” and “Health and sustainability as separate concepts”.“Health as embracing sustainability”, “Sustainability as embracing health” and “Health and sustainability as separate concepts”.However, a clear motivation for addressing both health and sustainability is most often lacking.This review includes 20 articles, a rather low number explained partly by the European focus, which can be seen as a limitation. However, even if articles from outside Europe had been found, the non-European context may have been confusing in terms of public meals since, at present, a common definition of public meals is lacking. Another explanation is that the research area of sustainability is quite new, with the 17 UN SDGs only being adopted in 2015. Furthermore, the focus on school/pre-school meals could be regarded as a limitation, but from the literature search, it was obvious that this is the most well-documented arena in terms of public meals.The strength of the present study is its aim to explore studies covering the aspects of health and sustainability in the context of public meals at the same time. To our knowledge, this is the first paper with this focus. In conclusion, indicating an urgent need for research within all public meal arenas, between which conditions and challenges may vary, according to issues of health and sustainability. An increased number of publications also opens opportunities for systematic review analyses allowing the findings of separate papers to be compared and contrasted while providing a foundation for decision-making.Conceptualization, K.H., C.L., M.N., V.O., E.R., H.S. and K.W;  methodology, V.O. and E.R.; validation, E.R. and K.W.; formal analysis, K.H., C.L., M.N., V.O., E.R., H.S. and K.W.; investigation, K.H., C.L., M.N., V.O., E.R., H.S. and K.W.; writing—original draft preparation, K.H., C.L., M.N., V.O., E.R., H.S. and K.W.; writing—review and editing, A.M., M.N., E.R. and K.W.; visualization, V.O., E.R. and K.W.; project administration, K.W.; funding acquisition, K.W. All authors have read and agreed to the published version of the manuscriptThis research received no external funding. The APC was funded by The research environment MEAL (Food and Meals in Everyday Life), Kristianstad University, Sweden.The authors declare no conflict of interest.The figure illustrates different sectors serving meals to users. The sizes of the boxes correspond to the number of meals served in each arena, based on a Swedish context [33,34,35].Databases for search of papers.Criteria for inclusion of papers.The 20 articles on health and sustainability in public meals fulfilling the five criteria for inclusion in this study.Main content of the included articles.

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+Environmental regulation will affect social employment through corporate costs, technological innovation, industrial upgrading, and industrial transfer. To verify the effect of environmental regulation on social employment in different periods and under the intensity of environmental regulation, in this paper, environmental regulation is introduced as an influencing factor of social employment levels, based on China’s urban registration unemployment data from 1987 to 2017. A nonlinear smoothing autoregressive model is used to analyze the nonlinear long-term effect relationship between environmental regulation and social employment. The research results show that the relationship between environmental regulation and social employment does exhibit the characteristics of nonlinear transformation under different mechanisms, and the transformation speed is fast. The specific manifestation is that the environmental regulation has a restraining effect on social employment in the short term, and the environmental regulation has a promoting effect on social employment in the long term. Continued high-level environmental regulations will exacerbate the adverse impact of environmental regulations on social employment.Along with the slowdown of economic development and the fading of the demographic dividend in recent years, macroeconomic development under the ‘three-phase superposition’ has been facing the pressure of environmental protection and labor employment. According to the ‘13th Five-Year Plan’ toward national economic and social development, green development will be treated as the basic principle of China’s economic and social development during the ‘13th Five-Year’ period and even longer periods. As one of the primary methods to promote green development, environmental regulation is changing the track of economic growth by affecting the industrial restructuring and technological innovation, inevitably, having some impacts on social employment. Social employment refers to the activities of people with labor capacity and willingness to engage in various types of labor to obtain labor income; the workers provide goods and services to society through employment, while also obtaining labor income to provide material conditions for human survival. Social employment plays an important role in the sustainable development of society, and promotes the level of social employment, as one of the most essential goals of macroeconomic development, as well as the sustainable development of the Chinese economy. Overall, as one of the main factors influencing the social employment, what is the direction and intensity of the impacts of environmental regulation on employment? This paper intends to discuss the impact of environmental regulation on employment.With the emergence of environmental issues and the slowdown of economic growth, the impact of environmental regulation on macroeconomic growth has become the main focus of researchers. In recent years, due to the increasing importance of environmental protection, more and more scholars have focused on exploring the impact of environmental regulation on employment, and different conclusions have been drawn due to the diversity of research perspectives. As such, domestic and foreign studies on the impact of environmental regulation on employment will be discussed, among which domestic scholars have conducted detailed studies on the relationship between environmental regulation and employment from the perspectives of industry heterogeneity, industrial upgrading, regional heterogeneity, geographical division, and urban–rural dual structure, respectively. When regard to social employment, this is an activity in which members of society engage in various types of labor to obtain legal labor remuneration or income. In this paper, the economic significance of social employment is taken into consideration, that is, laborers receive labor income while providing goods and services to society.The views of foreign research are mainly divided into three categories. First, environmental regulation has a positive impact on employment. Roger H. Bezdek et al. (2008) found that environmental protection, economic growth, and employment creation are complementary and compatible based on environmental-related workload data at the US state level. Environmental protection creates jobs and replaces some employment, but overall the impact of environmental protection on employment is positive [1]. Second, environmental regulation has a negative effect on employment. Greenstone (2002) used the difference-in- difference (DID) method to show that the 1970 US Clean Air Act and the 1977 US Clean Air Act Amendment had a negative impact on employment; this law resulted in an decrease in GDP growth and an increase in social unemployment from 1973 to 1985 [2]. Third, the impact of environmental regulation on employment is uncertain. Jens Horbach and Klaus Rennings (2013) conducted surveys about community-level innovation from the perspective of enterprise and found that clean technology innovation can save costs and stimulate demand, thereby increasing employment, but water and air treatment technology innovations, dominated by high-end technology, have a negative impact on employment [3].Recently, quite a number of domestic scholars assume that there is a U-shaped curve between environmental regulation and overall employment. With the increase of environmental regulation, its impact on employment has gradually turned positive [4,5,6,7], however, China’s environmental regulation and employment are currently in the decline stage of the U-shaped curve. If the employment structure is divided according to the pollution level and technical level, it will be found that the heterogeneity of the industry leads to significant differences in the shape and position of the U-shaped curve [5].In heavily-polluting industries, there is a U-shaped relationship between environmental regulation and social employment. In moderate- and mildly-polluting industries, there is an inverted U-shaped relationship. The increase of labor cost share and the decrease of industrial monopoly degree will weaken the employment elasticity of environmental regulations [8]. For dirty industries, the impact of environmental performance on employment through technical effects is more significant, and thus, a win-win situation of ecological environment and employment stability will be achieved [9]. Environmental regulation has the strong endogeneity due to factors such as the employment level of the industry, the proportion of state-owned enterprises, the degree of foreign investment, and the amount of pollution emissions. Compared with the cleaning industry, environmental regulation has a greater impact on the employment of polluting industries [10]. Some scholars also assume that the correlation between environmental regulation and employment is not a simple U-shaped curve, but a complex nonlinear relationship, and that environmental regulation itself, industrial structures, and technological innovation have significant threshold effects [11].When environmental regulations are raised to a certain level, environmental regulation will promote employment in the industrial sector, and as the share of labor costs in the industrial sector rises, the impact of environmental regulation on employment will diminish [7].From the perspective of industrial upgrading effect of environmental regulation, the implementation of environmental regulation policies alone will reduce the scale of regional employment and will not promote the employment of high-skilled labor. However, when considering the effect of industrial changes caused by environmental regulations, the industrial upgrading effect of environmental regulations promotes the growth of demand for high-skilled labor, although it does not bring the increase of employment scale. On the whole, the industrial transfer effect of environmental regulations promotes the increase of employment scale nationwide [12]. At present, coordination and matching between industrial environmental regulation and industrial structure adjustment have not been realized, so the interaction effect between environmental regulation and industrial structure rationalization cannot bring about employment promotion [13].The heterogeneity of regional development is also an important factor affecting the relationship between the two. From the perspective of different labor income levels, due to the differences in industrial structure between regions, the employment effects of environmental regulations in different regions are also different; from the perspective of regions with different labor education levels, due to the regulation of enterprises and different levels of education labor, the effect is of a matching degree. The employment effect of environmental regulation in higher education and secondary education areas shows the effect of restraining and then increasing, and the environmental regulation in low education areas has a significant positive effect on employment [6]; divided by geographical area. From this perspective, the environmental regulations in the eastern region are more inclined to promote employment, while the central and western regions show a restraining effect on employment [7].Considering the existence of the urban–rural dual employment structure, due to the ‘air blow effect’ and the difference in the employment positions of migrant workers with different levels of human capital, environmental regulation will increase the employment demand for high-skilled and low-skilled migrant workers and reduce the employment needs of middle-skilled migrant workers, resulting the ‘polarization’ phenomenon in employment; with the gradual decline of the labor market segmentation, environmental regulation has changed from the perpetual effect on migrant workers to the promotion effect. In general, the negative impact of environmental regulation on the employment of urban migrant workers is greater than the employment of urban local labor [14,15,16].According to the above research, most scholars believe that there is a positive, negative, or U-shaped curve relationship between environmental regulation and employment, ignoring the dynamic relationship between environmental regulation and employment, that is, the linear relationship between environmental regulation and employment.This article believes that environmental regulation can affect social employment through various paths such as production costs, technological innovation, and industrial upgrades and transfers. However, considering that the completion of technological innovation by enterprises or the completion of industrial transformation and upgrading are all gradual processes, the impact of environmental regulation on social employment is long-term. At the same time, the impact of environmental regulation on different paths varies, so the impact of environmental regulation on social employment is nonlinear. The main innovations of this paper are as follows: Previous studies focusing on the impact of economic development on employment, this paper studies the impact of environmental regulations on social employment, and the smooth transition autoregressive (STR) model is used to analyze environmental regulations as well as the nonlinear relationship between residents’ employment. This paper can enrich relevant research in the field of environmental protection and employment. Among the impacts, the direct effect is mainly caused by the cost effect of environmental regulation, which changes the level of social employment, and the indirect effect is mainly caused by the technological innovation effect, industrial upgrading effect, and industrial transfer effect produced by environmental regulation.From the perspective of the cost effect of environmental regulation [17,18,19], ‘follow cost theory’ holds the idea that the government adopts preferential tax policies and market discipline-type environmental regulation means, such as administrative penalty tax on polluting industries, which will increase the three highs’ industry’s operating costs, and inhibit the scale expansion and market competitiveness of polluting industries, thus, causing the collapse of some enterprises due to unable to bear the cost pressure. Enterprises that intend to enter the polluting industry will also be rejected because of the high threshold of environmental regulation, which will reduce the employment space of high-polluting industries. The generation of cost pressure will also have the substitution effect between the pollution factor and the labor factor. When the cost pressure causes the price of the pollution factor to be higher than the labor factor price, the labor factor replaces the pollution element in the production market. At the same time, the government reduces the operating costs of green environmental protection enterprises through tax subsidies and other preferential policies and promotes green environmental protection enterprises to expand production scale and enhance their market competitiveness.From the perspective of the technological innovation effect of environmental regulation [20,21,22], the ‘innovation compensation theory’ holds that environmental regulation will encourage enterprises to carry out technological innovation in order to take the leading role in market competition. Under the pressure of environmental regulation, some enterprises realize that the effect of innovation compensation can enhance their competitive advantages, improve their production efficiency, expand their business scale, and enhance their employability. However, some enterprises may suffer large external shocks when facing the environmental regulation due to the fact that they fail to take advantage in the field of technological innovation of enterprises, as well as some other factors, such as insufficiency operating ability, weak financing ability, and poor innovation ability. In this way, the scale of production will shrink and even the enterprise itself will be eliminated out of the market as a result of the losses of labour force and the transfer of labour force. Judging from the effects of the current environmental regulation policies, environmental regulation policies have not provided sufficient motivation for green technological innovation [23].From the point of view of the industrial upgrading effect of environmental regulation [24,25,26], industrial upgrading can be divided into the improvement of industrial quality and efficiency caused by technological upgrading and can also be reflected in the adjustment and improvement of industrial structure. Environmental regulation encourages enterprises to upgrade their technology, thereby improving the efficiency of the industry, increasing the demand for highly skilled labor, and reducing the demand for low-skilled labor, causing a substitution effect of high-skilled labor for low-skilled labor. At the same time, heavy industries relying on resource consumption in the early stages of industrialization can no longer be the pillar of economic growth, and the industrial structure is transforming into high-tech industries, high-end manufacturing, and service industries, with the continuous improvement of environmental regulation. The change of industrial structure has reduced the number of labor positions in the polluting industry, while the employment opportunities of new environmentally-friendly industries and service industries increased.From the perspective of industrial transfer effect of environmental regulation [27,28,29], the eastern region has taken the lead in entering the stage of rapid development under the background of reform and opening-up. In addition, the eastern region has accumulated a solid material foundation with the rough and mad economic development mode. Compared with the central and western regions, the pillar industries of economic development in the eastern region seem to be more diversified, and the high-tech industries driven by innovation in the eastern region are relatively denser. On the contrary, the development of the central and western regions started relatively later, and the intensity of environmental regulation was relatively weak, thus, providing some opportunities and chances for the polluting industry to continue to survive and develop. When the cost of local upgrading in a region with strict environmental regulation is higher than the cost of regional transfer, environmental regulation will lead to the transfer of enterprises from a more environmentally regulated area to a more relaxed area of environmental regulation. The transfer of industries promotes the industrialization process for the transfer areas, and the transfer of the corresponding supporting industries also brings a large number of employment opportunities to the transfer areas. For the industrial relocation, the ‘three high’ industry’s move out and bankruptcy leads a series of results, such as the large loss of employment and the increase of unemployment rate. In addition, the transformation and upgrading of the industry in the emigration area force the enterprises to expand the investment in technology and capital as well as the demands for high-tech labor.In view of the complex relationship between environmental regulation and employment, the smooth transition regression model (STR) is taken into consideration to help the analysis. The STR model is a typical nonlinear model, which was first proposed by Granger and Terasvirta to describe the transition from one mechanism to another [30]. The smooth transition regression model is based on the linear model, and further developed according to the mechanism transformation theory, which is mainly used to describe the transition smoothing relationship between the two extreme mechanisms to explain the relationship and law between different economic phenomena.The standard form of the smooth transition regression (STR) model is as follows [31,32,33]:(1)yt=ϕ′zt+θ′ztG(γ,c,st)+μt,   t=1,…,T
+        (2)G(γ,c,st)={1+exp[−γ∏k=1kst−ck]}−1,γ>0
+        (3)G(γ,c,st)=1−exp[−γ(st−c)2],γ>0yt is the dependent variable, which is denoted by the urban registered unemployment rate in China. zt is the explanatory variable vector, which is a social factor that may affect the explanatory variables, where zt = (wt′,xt′)′, and wt′=(1,yt−1,…,yt−p)′ are lag p-order variable that interprets the variable yt, and xt′ = (x1t,…,xkt)′ are the lag variables of other exogenous variables. ϕ=(ϕ0,ϕ1,…ϕp) and θ=(θ0,θ1,…θm) are the linear and nonlinear parameter vectors of the STR model, respectively. The transformation function G(γ,c,st) is a continuous function between 0–1, and the function value relies on γ,c,st, while, st is a conversion variable, which can be either the part of zt, or an exogenous variable not included in zt. μt is an independent and identically distributed error sequence term. c=(c1,c2,…ck) represents the time or position of the state transition, which is the threshold value under different mechanisms. The smoothing parameter γ indicates that the speed converted from one mechanism to another when the interpreted variable is under the influence of the conversion variable. The transformation function G(γ,c,st) in the STR model usually has two forms. When G is present the same form as in Equation (2), it corresponds to the logistic smooth transition autoregressive (LSTR) model, and when G is in the same form as Equation (3), it corresponds to the exponential smooth transition autoregressive (ESTR) model.The K value in the LSTR model is usually 1 or 2 [31]. When K=1, the transfer function G is an odd function and is a monotonically increasing function of the conversion variable st, that is the LSTR1 model. Its general function form is:(4)G(γ,c,st)={1+exp[−γ(st−c1)]}−1, γ>0
+        when K=2, the transfer function G does not have monotonicity, and is symmetric about [c1+c22,G(c1+c22)], and when st=c1+c22, the function G takes the minimum value, that is the LSTR2 model.
+        (5)G(γ,c,st)={1+exp[−γ(st−c1)(st−c2)]}−1,γ>0,c1≤c2This paper selects the social employment level as the explanatory variable, denoted by the urban registered unemployment rate (EMP). The environmental regulation is selected as the core explanatory variable and is expressed by the environmental regulation intensity index (ER), and the ER is evaluated from the two perspectives including the environmental governance cost and governance performance. Environmental governance cost is measured by the two indexes; one is denoted by the proportion of the industrial pollution control investment to the industrial added value and the other one is denoted by the proportion of sewage charge collection amounts to industrial pollution. The governance performance is measured by the comprehensive utilization rate of industrial waste. Finally, under the help of the entropy weight method, the weight of each indicator of environmental regulation is calculated one by one, and the weighted value is considered as the environmental regulation intensity index.Considering that there are many factors influencing the level of social employment, the economic development level (RJGDP) and the industrial structure upgrade (CY) are selected as the control variables. The economic development level is measured by GDP per capita, and the level of the industrial structure upgrading is evaluated by the proportion of the tertiary industry’s output value to the total output value. Logarithms for the above variables were taken into consideration to reduce the occurrence of heteroscedasticity in the empirical analysis. The data of environmental regulation index, social employment level, and other economic data are all from the China Environmental Yearbook, China Environmental Statistics Yearbook, and China Statistical Yearbook. The empirical process is mainly implemented by the JMulTi software.The smoothness of the data is necessary for nonlinear testing and estimation. It can be seen from Table 1 that there is no unit root after the first-order difference between lnEMP and lnER, which is a stable time series. The cointegration test requires that the variables should be the same order and single, so there are EMP~(1), ER~(1). The co-integration test is performed on EMP and ER, and the test results are shown in Table 2 below, which show the long-term cointegration relationship between environmental regulation and unemployment, and that this relationship is stable. The co-integration equation is as follows:(6)ΔlnEMP−0.134697ΔlnER=0
+          (7)ΔlnEMP=0.134697ΔlnERAccording to the above co-integration equation, it can be shown that there is a positive correlation between environmental regulation and unemployment rate, which means that the strengthening of environmental regulation will reduce the level of social employment. It is economically consistent with China’s current stage of economic development, that is; most highly polluting and energy-consuming enterprises have been closed under the implementation of current environmental regulations, while new industries have not yet formed, and the ability to absorb employment is limited. In the sample interval, there is a positive correlation between environmental regulations and unemployment.When environmental regulation returns to the level of social employment, it is first necessary to judge whether environmental regulation has significant nonlinear transformation characteristics for social employment. The AIC and SC criteria in the vector autoregressive model (VAR) are used to select the lag order, and the lag order of the AR part is chosen to be two orders in here. The basic form of the model is as follows:(8)ΔlnEMP=0.0064+0.166ΔlnEMP(−1)−0.250914ΔlnEMP(−2)+0.009ΔlnER(0.168647) (1.145473) (−1.738710) (0.696597)+0.013ΔlnER(−1)+0.100ΔlnRJGDP−0.187ΔlnCY (1.083282) (0.421269) (−0.531677)R2=0.251213, AIC=−2.894279, SC=−2.561228, DW=1.181019After the adjustment, the model has low goodness-of-fit, but the fitting effect is not ideal. Therefore, it is tested whether there is a nonlinear relationship between environmental regulation and the employment level of residents, and whether the fitting effect of the model will be greatly improved after the transformation becomes a nonlinear relationship.According to the test results in Table 3, when the conversion variable is ΔlnER*, the probability of accepting the linear relationship hypothesis is 4.5991 × 10−3, which is less than 5%, so the hypothesis about the linear relationship between environmental regulation and employment level can be rejected. The alternative hypothesis, that there is a nonlinear relationship between the two factors, should be taken into consideration. Since the p value of F3 is the smallest among F4, F3, and F2, the corresponding form of the conversion function is LSTR2.It is necessary to estimate the parameters of the STR model after the determination of the conversion form of the function and the conversion variables. According to the systematic grid search method, the chosing of the initial estimate of c (location parameter) and γ (smoothing parameter) are performed by selecting different γ and c within a certain range so that the sum of squared residuals estimated by the STR model system is the smallest. As shown in Table 4, the interval of the smoothing parameter γ is set to be (0.50, 10), and the interval of the positional parameter c is (−3.38, 3.47) (the smoothing parameter interval and the position parameter interval are set based on the model system data change and the conversion variable empirical data range, respectively), and the value of γ and c are both 30, which constitutes a combined point of 30 × 30 (γ,c). All the two-dimensional space combination points are evaluated one-by-one to find the parameters with the smallest residual square sum as the initial estimate value for further optimization. The initial estimates of γ and c are shown in the table below. Figure 1 and Figure 2 are contour plots and plans, respectively, under the help of two-dimensional grid search method, and the plan is the inverse of the maximize residuals.The Newton–Paphson method is used to solve the maximum conditional relief function after the determination of the parameters and initial variables. The nonlinear equation parameters φ, θ, γ, and c for environmental regulation and employment levels can be obtained. Detailed results are shown in Table 5:The specific form of the LSTR2 model is as follows:(9)ΔlnEMP=−0.86499−18.48528ΔlnEMP(−1)+7.56604ΔlnEMP(−2)+1.5224ΔlnER−1.08339ΔlnER(−1)−5.79462ΔlnRJGDP−3.86579ΔlnCY+G(γ,c,ΔlnER)×[1.85518+42.47549ΔlnEMP(−1)−17.36590ΔlnEMP(−2)−0.78558ΔlnER+2.50626ΔlnER(−1)+13.78695ΔlnRJGDP+8.83928ΔlnCY]
+          (10)G(γ,c,ΔlnER)={1+exp[10.32112(ΔlnER−0.08791)(ΔlnER+0.21572)]}−1R2=0.796,AIC=−6.3193,SC=−5.5105According to the above results, the employment effect of environmental regulation shows a clear transition relationship. This shows the better performance of the LSTR2 model, that is to say, the model can better demonstrate the nonlinear relationship between environmental regulation and employment level, and the estimated coefficient of the model has strong significance.The nonlinear part obtains the positional parameters c1=−0.08791 and c2=0.21572, and the transfer function is c1+c22=0.063905. Therefore, when the conversion variable ΔlnER=0.063905, the transfer function is G=0, that is, the nonlinear portion does not exist. The model then only presents as the linear part:(11)ΔlnEMP=−0.86499−18.48528ΔlnEMP(−1)+7.56604ΔlnEMP(−2)+1.52240ΔlnER−1.08339ΔlnER(−1)−5.79462ΔlnRJGDP−3.86579ΔlnCYWhen it comes to the linear part of the model, it is clear that the unemployment rate coefficient is negative, and the government will respond to the current employment problem by taking out the corresponding employment policy in the next year, thereby, the unemployment rate may have a reduction. The policy can solve the unemployment problem in the short-term, but in the long run, the unemployment problem caused by the economic operation has a cumulative effect, so the coefficient of the unemployment rate lags behind the second period is positive. There is a positive correlation between ΔlnER and unemployment rate, with a coefficient of 1.52240, and it is tested at a significance level of 1%, which proves that the implementation of environmental regulation has a loss effect on social employment in the current period. The relationship between ΔlnER(−1) and unemployment rate is negative at a significance level of 1%, the result indicates that the environmental regulation lags behind the first phase has an expansion effect on social employment. By the way of technological innovation and the adjustment of industrial structures, such as paths to reduce the unemployment rate, namely, environmental regulation has a positive effect on employment for a long time. There is a negative correlation between per capita GDP and industrial structure upgrading and unemployment rate. That is, economic development and upgrading of industrial structure can effectively reduce unemployment and promote the improvement of social employment levels. The implementation of environmental regulations will also have a positive impact on economic growth, thereby promoting the level of social employment [34].When the conversion variable ΔlnER is equal to the critical value, that is, ΔlnER = −0.08791 or ΔlnER = 0.21572, the transfer function G = 1/2, and the model is in the transition state from the pure linear state to the nonlinear model. The basic form of the model is:(12)ΔlnEMP=0.0626+2.752465ΔlnEMP(−1)−1.11655ΔlnEMP(−2)+1.12946ΔlnER+0.16974ΔlnER(−1)+1.098855ΔlnRJGDP+0.55388ΔlnCYWhen switching variable Δ lnER < −0.08791 or Δ lnER > 0.21572; namely, the intensity of environmental regulation is decreased, and the speed of decrease is more than 8.41% [exp(0.08791) −1]; or when the intensity of environmental regulation is rapidly increased, and the speed exceeds 24.07% [exp(0.21572) −1], the nonlinear effects of environmental regulation on employment will change significantly. Then, the basic form of the model is:(13)ΔlnEMP=−0.86499−18.48528ΔlnEMP(−1)+7.56604ΔlnEMP(−2)+1.52240��lnER−1.08339ΔlnER(−1)−5.79462ΔlnRJGDP−3.86579ΔlnCY+G(γ,c,ΔlnER)×[1.85518+42.47549ΔlnEMP(−1)−17.36590ΔlnEMP(−2)−0.78558ΔlnER+2.50626ΔlnER(−1)+13.78695ΔlnRJGDP+8.83928ΔlnCY]When the conversion variable is satisfied with −0.08791<ΔlnER<0.21572, that is the slow process of environmental regulation, the transfer function value is small, and the conversion variable ΔlnER has small impact on the entire nonlinear part, environmental regulation and employment level (unemployment rate) will maintain the linear relationship. That is to say that environmental regulation will have a negative effect on the unemployment rate with the coefficient of 1.52240, indicating that environmental regulation will increase the unemployment rate, which is not conducive to the improvement of social employment level. The main reason is that the implementation of environmental regulation in the short term will have a phase-out effect on some ‘three high’ enterprises, and the green environmental protection industry in the incubation has not yet formed, resulting in the loss of social employment.The smoothing parameter of the model is γ=10.32112 (it is generally considered that the adjustment speed of the nonlinear part is faster when γ>10), indicating that the adjustment speed of the nonlinear part of the model is relatively faster, the conversion function G is an increasing function of the conversion variable ΔlnER, and the conversion function grows as the value of the variable grows, thus, the nonlinear part in the model has a greater influence on the level of social employment.Figure 3 is a time series diagram of the raw data and simulation data in the model. It can be seen from the following figure that the dynamic characteristics of the data fitted by the STR model have a high degree of coincidence with the dynamic characteristics of the original data, which indicates the effectiveness of the STR model. That is to say, the model can better fit the dynamic relationship between environmental regulation and employment.Figure 4 and Figure 5 show schematic diagrams of the model nonlinear function and the transfer function G(γ,c,ΔlnER). Figure 4 is the result of the transfer function in which ΔlnER is treated as the conversion variable. The horizontal axis represents the conversion variable ΔlnER and the vertical axis represents the conversion function G. It can be seen that the value interval of the conversion function G is 0–1, and the symmetry about ΔlnER=0.063905. Figure 5 is the time series diagram of the transfer function, and it clearly shows there are obvious phase characteristics between environmental regulation and social employment. Specifically, it can be divided into three stages: 1990–2004, 2005–2008, and 2009–present. Among them, the values of G in the two periods from 1990 to 2004 and 2009 to present are relatively small and show the linear performance. The lagging period of environmental regulation is negatively correlated with the unemployment rate, which indicates that such environmental regulation is conducive to the improvement of social employment in the long run. In 2005–2008, during the ‘Eleventh Five-Year Plan’ period, there was an obvious nonlinear characteristic between environmental regulation and social employment (G=1). At this time, the coefficient of ΔlnER is 0.73682, and the coefficient of ΔlnER(−1) is 1.42287. The coefficient of the environmental regulation lags from the first phase is changed from the negative value of the linear part (such as Equation (9)) to the positive value, demonstrating the positive correlation between the environmental regulation lag phase 1 and the social unemployment rate, which is unfavorable to the improvement of the social employment level. We assume that the change in the coefficient is mainly affected by the domestic environmental protection situation. The ‘Eleventh Five-Year Plan’ is the period in which China’s environmental protection situation has taken turns, and the ‘environmental storm’ has become the key word during the ‘Eleventh Five-Year Plan’ period. The five-year environmental plan is considered to be the best environmental plan for the past years at the government work evaluation meeting. During the ‘Eleventh Five-Year Plan’ period, the Ministry of Environmental Protection will not accept and approve the investment of more than 2.9 trillion yuan for 813 projects that do not meet the environmental protection requirements. At the same time, it will investigate and deal with heavy metal pollution, papermaking enterprises, sewage treatment plants, etc., and shut down more than 20,000 illegal sewage companies. The long-term and super-level improvement of environmental regulation has led to a large loss of social employment. Therefore, during the period, whether it is the current period of environmental regulation or the first period of lag, there is a significant positive correlation between the unemployment rate.In order to evaluate the stability of the model, the ADF and Philliips& Perron (PP) unit root test method is used to test the stability of the residual term of the regression model. The results of the test are shown in Table 6. The residual term of the regression model is a stable time series at a significance level of 5%, whether under the ADF test or the PP test.The ARCH-LM test method is used to test the heteroscedasticity of the model. The corresponding results are shown in Table 7. The chi-square statistic is 1.4168, the corresponding p value is 0.4924, and the F-statistic is 0.7492, the corresponding p value is 0.4839. The null hypothesis is accepted at a significance level of 10%, that is, there is no heteroscedasticity in the residual term.The results show that the impact of environmental regulation on the rate of unemployment presents a nonlinear conversion relationship according to different intensities of environmental regulation. In the short period, the correlation between environmental regulation and unemployment rate is positive, and environmental regulation will cause the loss of employment; in the long-term, the correlation between environmental regulation and unemployment rate is negative, and environmental regulation will cause the expansion of employment. At the same time, the long-term and high-intensity environmental regulation will contribute to the loss of social employment. In particular, long-term implementation of high-intensity environmental regulation policies will have a major influence on social employment, resulting in a significant reduction in employment.According to the research on the mechanism of the impact of environmental regulation on the employment of residents, this paper revealed that, from the perspective of the effects of cost, technological innovation, industrial upgrading, and industrial transfer, that the correlation between environmental regulation and employment is neither immutable nor a U-shaped relationship. Rather, the effects of environmental regulation on employment depends on the intensities of change on different periods of time. To verify this correlation, this paper used the STR nonlinear model to study the correlation between environmental regulation and social unemployment rates in China from 1987 to 2017. Studies have shown that the transition of nonlinear conduction of environmental regulation to social employment between different mechanisms appears smooth and continuous, and the transformation speed is accelerated.Environmental regulation is a factor that affects social employment. Environmental regulation will have a negative impact on the current levels of social employment. A lag in environmental regulation will have a positive impact on the current levels of social employment. With the sharp increase in the intensity of environmental regulations, the impact of lagging environmental regulations on the level of social employment has also changed from positive to negative. This result is strong proof of the negative impact of environmental regulations on China’s employment levels at present, especially the high-intensity environmental regulations during the ‘Eleventh Five-Year Plan’ period, which have created long-term job losses. However, this loss is only temporary. In the long run, the impact of environmental regulations on social employment is still positive.The coordinated development of environmental protection and social economy is an important issue for various countries in the world, especially for the developing countries to achieve sustainable economic and environmental development. In this work, it can be seen that environmental regulation will not adversely affect social employment in the long run in China’s practice, but will improve the level of social employment, indicates that environmental protection and green development are in line with the trend of economic and social development. Meanwhile, it is also found that the intensity of environmental regulations and economic development should be coordinated with each other. Otherwise, once the environmental regulations extend beyond the bearing capacity of social development in a certain period of time, the high-intensity environmental regulations will lead to the loss of social employment in a short time. Therefore, it is also necessary for other countries to implement environmental regulations in the process of economic development. However, the intensity of environmental regulations in each period should be adapted in accordance with the affordability of their own economic development. Economic development and social employment are especially indispensable in developing countries. Especially, environmental protection should be regarded as an important part in the process of economic development. Economies should be developed with the goal of protecting environment, as environmental protection helps to improve the development of economic and the level of social employment continuously. The two are interconnected and mutually reinforcing. Specifically, different countries and regions have different economic development stages and environmental conditions. As such, the following three aspects may be taken into consideration to help achieve the coordinated development of environmental regulations and social employment. First, improve the system design of environmental regulations. The use of public goods is inseparable from the government’s macro-control. As the coordinator of environmental protection and economic development, the government should make full use of its role in environmental protection. Second, the market should play a fundamental role in environmental protection. The profitability of the market and the public properties of environmental goods are not contradictory. When the environment weakens the profitability of an industry or a company, the public properties of the environmental goods will also diminish. Third, some supports should be given to innovations and entrepreneurships related to environmental protection.X.W. performed the experiments and wrote the paper. Q.Y. proposed the conceptualization and main steps of the research. N.H. analyzed the data and contributed analysis tools. All authors have read and agreed to the published version of the manuscript.The work is supported by Major Projects of the National Social Science Fund of China (Grant No.16ZDA045).The authors would like to thank Yongsong Wen, Lingmei Fu, Xiaoyi Wang for editing the language. The authors thank the anonymous referees for their constructive suggestions.The authors declare no conflict of interest.Plan of the grid search.Contour map of grid search.Original and fitted data time series diagram.Schematic diagram of the conversion function G.Time series diagram of the zone conversion.Augmented Dickey-Fuller test (ADF) stationarity test results.Johansen cointegration test.Conversion function test selection results.Note: F1, F4, F3, and F2 represent F statistics, respectively, and * represents the form of the optimal transition variable and conversion function determined by the STR model.Initial estimation results of smoothing parameters and positional parameters.LSTR2 model parameter estimation results.Residual stability test.ARCH-LM test (with two lags).

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+These authors contributed equally to this work.Background: Methicillin-resistant Staphylococcus aureus (MRSA) and Staphylococcus epidermidis (MRSE), the most prevalent causes of hospital-associated and community-associated infections, could exist on frequently touched surfaces. This study aims to determine the contamination prevalence and the characteristics of MRSA and MRSE isolated from secondary school environments. Methods: We collected environmental samples from ten secondary schools in Guangzhou city between October 2016 and January 2017. The samples were confirmed for MRSA and MRSE isolates by using biochemical tests and polymerase chain reactions. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disk diffusion method. Staphylococcal cassette chromosome mec (SCCmec) typing, toxin gene screening, and multilocus sequence typing (MLST) were performed to further characterize the isolates. Data were analyzed by two-sample proportion tests. Results: A total of 1830 environmental samples were collected. The prevalence of MRSA and MRSE contamination were 1.86% (34/1830) and 5.14% (94/1830), respectively. The proportions of multidrug resistance in both MRSA (58.82%) and MRSE (63.83%) isolates were high. Seven clonal complexes (CC) and 12 sequence types (ST) were identified, with the CC5 (35.29%) and ST45 (25.53%) being the most prevalent. We found that 44.12% of the MRSA isolates were community-acquired and the main type was ST45-SCCmec IV. We found that 5.88% and 32.35% of MRSA isolates were positive to Panton-Valentine leukocidin (PVL) and toxic shock syndrome toxin-1 (tst) gene, respectively. No MRSE isolate was positive to the toxin genes. Conclusion: Our findings raise potential public health concerns for environmental contamination of MRSA and MRSE in school environments. Surfaces of school environments may potentially provide a source for cross-contamination with these bacteria into the wider community.Methicillin-resistant Staphylococcus aureus (MRSA) is the leading cause of hospital-associated (HA) and community-associated (CA) infections ranging from minor skin and soft tissue infections to life-threatening pneumonia [1,2]. MRSA infections, particularly infections caused by multidrug-resistant (MDR) Staphylococcus aureus, are becoming more and more common in clinical facilities [3]. In addition, Staphylococcus epidermidis, a normal inhabitant of human skin and mucous membranes, has become a significant conditional pathogen in the hospital environment with resistance to antibiotics such as methicillin-resistant Staphylococcus epidermidis (MRSE) [4,5]. Methicillin-resistant isolates are resistant to most β-lactam antibiotics and multiple antibiotics, which can increase the mortality and health care costs of staphylococcal infections [6].Numerous studies have shown the role of the environment as a reservoir for pathogens, and proved that environmental contamination with an infection strain is a significant and independent risk factor in transmission [7,8,9]. There was increasing cross-over transmission with the blurring of the boundaries between HA- and CA-Staphylococci [10]. Methicillin-resistant Staphylococci (including MRSA and MRSE) have been found in communities, such as public transports [8,11], parks [12], beaches [13], and universities [14]. However, data on the epidemiology of methicillin-resistant Staphylococci in school environment is limited in China. Therefore, this study aims to elucidate the contamination prevalence, antimicrobial resistance, and molecular characteristics of methicillin-resistant Staphylococci in school environments in Guangzhou, China.This cross-sectional study was conducted in ten secondary schools in Guangzhou, China from October 2016 to January 2017. A stratified sampling process was conducted to choose secondary schools. First, all the secondary schools were divided into urban and rural categories. Then, five schools were selected from the urban region and five from the rural region using simple random sampling. The head teachers of the selected schools signed an informed consent form.The following places and locations/objects from each school were selected—classrooms (doorknobs, switches, desks, and chairs), toilets (doorknobs, switches, flush handles, and faucet handles), stairs (handrails), corridors (handrails), and playgrounds (balls, horizontal bars, and chairs). These locations were selected because they are frequently touched by students and teachers, and could easily be a reservoir for the organisms. In each school, we collected 183 samples, including 84 from classrooms, 54 from toilets, 15 from stairs, 15 from corridors, and 15 from playgrounds. A total of 1830 environmental samples were collected from these ten schools.Each environmental location/object was classified and numbered by the investigators before sampling. We also recorded the weather during sampling (including sunny, cloudy, and rainy day). Sterile cotton swabs moistened with 0.9% saline water were used to wipe surfaces of environmental objects. Then each swab was put into a sterile tube with 7.5% sodium chloride broth and transferred to the laboratory within 4 h for further experiments.Swabs were incubated at 37 ± 1 °C for 24 h and then transferred to mannitol salt agar (each liter containing 10g petone, 1g beef extract, 10g mannitol, 75g sodium chloride, 0.025g phenol red, and 14g agar) with inoculating loop for another 24h of incubation. The colonies which were grape-like clusters and gram-positive under the microscope were further screened for the catalase reaction, β-hemolysin, and tube coagulase test. Isolates were identified as Staphylococcus aureus (S. aureus) if they were positive for all the aforementioned tests as well as positive for the 16S rRNA and nuc genes [15]. Staphylococcus epidermidis (S. epidermidis) isolates were confirmed if they were negative for the tube coagulase test as well as positive for the 16S rRNA and epi genes [16]. The S. aureus and S. epidermidis isolates that were positive for the mecA gene and/or resistant to cefoxitin were identified as MRSA and MRSE, respectively.Antimicrobial susceptibility testing was conducted by the Kirby-Bauer disk diffusion method based on the Clinical and Laboratory Standards Institute guidelines, 2016 [17]. The following 12 antimicrobial agents were tested—penicillin, cefoxitin, erythromycin, trimethoprim-sulfamethoxazole, rifampicin, clindamycin, tetracycline, teicoplanin, chloramphenicol, gentamicin, moxifloxacin, and linezolid. The isolates that were resistant to ≥1 agent in ≥3 antimicrobial categories were classified as multidrug resistant (MDR) [18]. S. aureus ATCC25923 and S. epidermidis ATCC12228 (American Type Culture Collection) were used for the quality controls.All the S. aureus and S. epidermidis isolates were tested for the presence of toxin genes including toxic shock syndrome toxin-1 gene (tst), staphylococcal enterotoxins (sea, seb), and haemolysin gene (hla) by using multiplex polymerase chain (PCR) assay [19,20]. The S. aureus isolates were also tested for the Panton-Valentine leukocidin (PVL) genes [15] and the multilocus sequence typing (MLST) [21]. All the MRSA isolates were tested for the staphylococcal cassette chromosome mec (SCCmec) typing [22]. The nucleotide sequences of the primers and the size of the PCR products of genes can be found in Table S1. More details are available in our previous publication [23].The data were entered into a computerized database using Epidata 3.1 (EpiData Association, Odense, Denmark) and exported to Stata 15.0 (College Station, TX, USA) software for further statistical analysis. The significant difference between proportions of categorical variables was analyzed by using Pearson’s chi-squared test or Fisher’s exact test for small samples. Odds ratios (ORs) with 95% confidence interval (CI) were used to assess the antibiotic resistance risk between MRSA and MRSE isolates. The p value < 0.05 (two-sided) was considered statistically significant.The distribution of MRSA and MRSE isolates is shown in Table 1. The prevalence of MRSA and MRSE contamination were 1.86% (34/1830) and 5.14% (94/1830), respectively. The prevalence of MRSA contamination among different places were significantly different (χ2 = 12.84, p = 0.012). The highest prevalence of MRSA contamination was the classroom (3.10%), followed by the corridor, stair, and toilet, while no MRSA isolate was detected from the playground. There was no significant difference in the prevalence of MRSE contamination among different places or objects (p > 0.05). We also found that weather and area had no effect on the prevalence of MRSA (weather: χ2 = 2.220, p = 0.136; area: χ2 = 0.043, p = 0.836) or MRSE (weather: χ2 = 0.042, p = 0.837; area: χ2 = 0.035, p = 0.853) contamination.The proportions of antimicrobial resistance are shown in Figure 1. Both MRSA and MRSE isolates were with high proportions of resistance to penicillin, erythromycin, and cefoxitin. We found that the MRSA isolates were more likely to be resistant to penicillin (OR, 5.18; 95% CI, 1.15–23.32; p = 0.022) and rifampin (OR, 3.26; 95% CI, 1.35–7.90; p = 0.007) than the MRSE isolates. The MRSA isolates were less likely to be resistant to trimethoprim-sulfamethoxazole (OR, 0.16; 95% CI, 0.06–0.42; p < 0.001) than the MRSA isolates. Notably, 58.82% of the MRSA and 63.83% of the MRSE isolates were MDR. The predominant MDR pattern of the MRSA isolates was co-resistance to cefoxitin, erythromycin, and clindamycin, while the pattern of the MRSE isolates was co-resistance to erythromycin, cefoxitin, and trimethoprim-sulfamethoxazole (Figure 2). There was no significant difference in antibiotic resistance between the MDR-MRSA and MDR-MRSE isolates (OR, 0.81; 95% CI, 0.34–1.97; p = 0.61).Six clonal complexes (CCs) and 11 sequence types (STs) were found in the MRSA isolates. The most predominant CC was CC5 (35.29%, 12/34), followed by CC45 (23.53%, 8/34), CC30 (11.76%, 4/34), CC59 (8.82%, 3/34), and CC182 (2.94%, 1/34). Notably, the MRSA isolates with the same CC were from different places and different schools. From Figure 3 and Figure 4, we found that the three most predominant STs were ST45 (23.53%, 8/34), ST72 (14.71%, 5/34), and ST188 (11.76%, 4/34).As to virulence genes, only two CC5 MRSA isolates were positive for the PVL genes. We found that 32.35% of the MRSA isolates (11/34) were positive for the tst gene, and most of these 11 isolates were CC5 (23.53%, 8/34). Seven (20.59%) MRSA isolates were positive for the sea gene, 3 (8.82%) for the seb gene, and 27 (79.41%) for the hla gene. All the MRSE isolates were negative to the PVL, tst, sea, seb, and hla genes.Four SCCmec types were observed in 34 MRSA isolates (Figure 3), including type IV (38.24%, 13/34), V (5.88%, 2/34), II (2.94%, 1/34), and I (2.94%, 1/34), while 17 isolates (50.00%) were non-typeable (NT).To the best of our knowledge, this study contributes to the contamination prevalence, phenotypic and molecular characteristics of methicillin-resistant Staphylococci in the school environment in China. A total of 34 MRSA and 94 MRSE isolates were found from ten secondary schools in Guangzhou, China. The proportions of MDR in both MRSA and MRSE isolates were high. Diverse CCs and STs were found in the MRSA isolates. Most MRSA isolates were CA-MRSA and the main type was ST45-IV.The prevalence of MRSA (1.86%) contamination in this study was lower than studies conducted in high schools [24], universities [25], and public transports [8,26,27], but was higher than a study conducted in secondary schools in Canada (0.68%) [28]. The prevalence of MRSE (5.14%) contamination was lower than observed studies [14,29]. Differences in sampling methods, sampling techniques, and geographical locations could partially explain the variation of prevalence. Moreover, the prevalence of MRSA contamination in classrooms (3.10%) in this study was higher than observed studies [25,28]. This might be due to these areas being more frequently touched in classrooms than in other places.The patterns of antibiotic resistance in both MRSA and MRSE isolates were similar to observed studies [8,29], which also found high proportions of antibiotic resistance to penicillin, erythromycin, and cefoxitin. We found higher proportions of MDR in both MRSA (58.82%) and MRSE (63.83%) isolates in this study than previous studies [2,5,9], which might be due to the overuse of antibiotics by school students.The results of molecular characteristics further broadened our insights into the epidemiology of methicillin-resistant Staphylococci in a non-hospital environment. The main SCCmec types of MRSA isolates were IV and V, which shows most of them were CA-MRSA [27]. The results of the MLST show that ST45 was the most predominant type of MRSA isolates, similar to a previously published school environment study [30]. However, the most predominant CC type of MRSA isolates was CC5, which was reported to be one of the main CC types for HA-MRSA [31,32]. Thus, the results of SCCmec and MLST could indicate there was cross-transmission between the hospitals and communities. Additionally, some MRSA isolates from different schools/places/locations displayed identical molecular characteristics, also suggesting there was cross-transmission between the different places or/and schools.We found that 5.88% of the MRSA isolates were positive for PVL genes, which was higher than public transports [8]. We also found a higher proportion of tst gene (23.53%) in CC5 MRSA isolates than a hospital study (17.3%) [31]. No MRSE isolate was positive for toxin genes. These findings help demonstrate that the MRSA isolates are more virulent than MRSE isolates.Although this study contributes to the epidemiology of MRSA and MRSE contamination in the school environment in China, there are still some limitations. Firstly, we could not evaluate the dynamic change of isolates because of the cross-sectional design. Secondly, we could not elucidate the association between the school environment and students because we did not concurrently collect samples from the students, but we will consider it in future studies. Thirdly, due to the financial limitation we did not explore many more molecular characteristics for the MRSE isolates, which to some extent would lead to a limitation in elucidating the association between the MRSE and MRSA isolates.In conclusion, our findings raise potential public health concerns for the environmental contamination of MRSA and MRSE in the school environment. Surfaces of the school environment may potentially provide a source for cross-contamination with these bacteria into the wider community. Effective disinfection measures should be taken in the school environment so as to decrease and prevent methicillin-resistant Staphylococci contamination and transmission.The following are available online at https://www.mdpi.com/1660-4601/17/2/623/s1, Table S1. Nucleotide sequences of primers and size of PCR products (bp) of genes.Conceptualization, Y.W., J.L., T.Z., X.Y., and Z.Y.; data curation, T.Z.; formal analysis, Y.W., S.H., Y.L., and W.Z.; funding acquisition, X.Y., and Z.Y.; investigation, J.L. and T.Z.; methodology, Y.W., J.L., T.Z., X.Y., and Z.Y.; project administration, Z.Y.; supervision, X.Y., and Z.Y.; Writing—original draft, Y.W. and J.L.; Writing—review & editing, X.Y., and Z.Y. All authors have read the manuscript and approved the submitted version.This study was supported by the Science and Technology Planning Project of Guangdong Province (No. 2014A020213013) and the National Natural Science Foundation of China (No. 81973069, 81602901). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.The authors declare no conflict of interest.P: penicillin; E: erythromycin; FOX: cefoxitin; RD: rifampicin; DA: clindamycin; TE: tetracycline; TEC: teicoplanin; SXT: trimethoprim-sulfamethoxazole; C: chloramphenicol; GEN: gentamicin; MXF: moxifloxacin; LZD: linezolid; MDR: multidrug resistant. Antibiotic resistance rate of MRSA and MRSE isolates. Note: * There was a statistically significant difference, p < 0.05.Proportions of antibiotic resistance between MDR-MRSA and MDR-MRSE isolates.Clonal dendrogram and detailed information of MRSA isolates.Minimum spanning tree of sequence types of MRSA isolates.Distribution of places and objects on MRSA and MRSE isolates in secondary schools in Guangzhou, China.

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+‘Green exercise’ (being physically active within a natural environment) research has examined the influence of environmental setting on health and wellbeing-related exercise outcomes. However, it is not known whether social exercise settings influence green exercise-associated changes in mood, self-esteem, and connection to nature. This study directly compared outcomes of participating in green exercise alone compared to in a group. Using repeated measures, counterbalanced and randomized-crossover design, participants (n = 40) completed two 3 km runs around sports fields. These fields had a relatively flat grass terrain, predominant view of trees, and open grassland. On one occasion participants ran alone and on the other they ran in a group of 4–5 participants. Questionnaire measures of mood, self-esteem, and connection to nature were completed immediately pre- and post-run. Across all of the measures, two-way mixed ANOVAs found that there were statistically significant effects for time but not for time-by-condition interactions. The simplest interpretation of this finding is that social setting does not influence individuals’ attainment of the psychological outcomes of green exercise participation. However, we discuss the possibility that more complex processes might underpin this finding.Since 2003, green exercise research has examined the influence of environmental setting on health and wellbeing-related exercise outcomes. In comparison with equivalent forms of exercise in indoor or built environments and in laboratories while viewing environmental scenes [1], exercise in greenspaces has been shown to increase levels of directed attention [2,3,4], improve mood [4,5,6], reduce levels of frustration and arousal, increase levels of meditation [7], and improve self-reported mental health across 8 weeks [8]. Positive expectancy can enhance some of these acute effects of the environment [9]. Two popular psychological outcomes reported by research focussing on the importance of environmental setting are mood and self-esteem [10,11,12,13,14]. This is in part due to their importance to adherence via affect–intention relationships [15,16] and the role of self-esteem in physical-activity behaviours via perceived self-efficacy and control [17,18,19,20,21,22].A number of hypotheses, theories, and models have been proposed to explain the influences of the environment on exercise outcomes and the shaping of exercise behaviours [1]. While the biophilia hypothesis [23,24], stress-reduction theory [25], and attention-restoration theory [26] suggest the underpinnings of psychological responses to different types of environments (which researchers report to occur during exercise as well as at rest), the intertwining-pathways model of green exercise suggests that the reported outcomes of green exercise participation occur through two intertwined pathways comprising salutogenic effects of exposure to nature and behaviour-shaping effect of the environment [27]. More specifically, the ecological-dynamics perspective [28] describes that a dynamic interplay between the environment and individual continually reshape exercise experiences and thereby the associated outcomes, and that outcomes cyclically shape the interplay.Resonating with the two latter theories, individuals’ level of psychological connection to nature can influence the affective outcomes of green exercise participation—individuals who feel more connected report greater positive changes from pre- to post-exercise [10]. The ecological-dynamics perspective suggests that this occurs because a greater level of connection enhances the affordance for and likelihood of individuals engaging in a psychologically restorative interaction with a greenspace environment. Although the construction of a connection with nature is thought to be relatively stable in the short term, it is shaped by experience. Therefore, an immersive bout of green exercise might function to increase the reported level of connection.It is not known whether social exercise settings influence green exercise-associated changes in mood, self-esteem, or connection to nature. The majority of studies have examined psychological influences of exercise environments in individuals exercising alone [14,29,30,31], with a partner [32], in a group [33], or mass-participation events [10]. Studies on solo and group exercise have reported that greenspace environments enhance a range of psychological outcomes, such as increased positive and decreased negative mood/affect, directed attention, and enjoyment. This suggests that individual environment-level interactions associated with exercise seem likely to promote desirable psychological outcomes despite the varying impacts of social settings. However, the relative contributions of factors such as environmental and social settings to psychological outcomes are inter-related, transient, and dynamic. Psychological effects associated with social interactions during exercise might function to alter, detract from, or over-ride other pathways that are affected by exercise and environmental influence [27,32]. No studies have yet directly compared the outcomes of green exercise participation between the social settings of exercising alone and in a group. Indeed, across the exercise science literature, little research has been published that compares the affective outcomes of single acute bouts of exercising alone and in a group. Likely due to large individual differences in preferences, research has instead reported on explanations of individual preferences and the influence of social setting on motivation and adherence, often within prescribed exercise programmes.There is merit to examining whether social setting influences the outcomes of single bouts of green exercise running. This may serve as a preliminary indication of how social settings might be optimised in addition to the environmental setting in order to enhance wellbeing-related parameters. This study examined the influence of group settings on some commonly reported psychological outcomes of green exercise participation. Although this study was considered to be exploratory, for the sake of analysing data using hypothesis-driven procedures the hypotheses for each variable (mood, self-esteem, and connection to nature) were as follows—(i) increases would occur in both conditions from pre- to post-exercise and (ii) increases would be greater when participants exercised alone than when they exercised in a group.Participants (n = 40; 20 males, 20 females) were university students and staff and members of the public from the local area, aged 21–68 years (mean age 36.43 ± 11.33 years). Participants were recruited through posters and electronic advertisements and were not paid for their participation. This study was approved by the University Ethics Committee. All participants were screened for exercise-associated risks using a Physical Activity Readiness Quesitonnaire (no participants were excluded) and gave informed consent for their participation.The study design used a repeated-measures-counterbalanced and randomized-crossover design whereby participants completed two test occasions. On each occasion, participants completed a 3 km run. The only difference between conditions was that on one occasion they ran alone and on the other they ran in a group of 4–5 participants. On both test occasions participants completed composite questionnaires immediately pre- and post-run.Each run was at the participant’s self-selected pace and comprised two 1.5 km laps of university sports fields. These had a relatively flat grass terrain, predominant views of trees and open grassland, and some views of buildings in the distance. There was an abundance of wildlife on the route, including squirrels and birds. In addition to a verbal description from a researcher before each run, route directions were positioned every 100 meters along the route to ensure route adherence. The entire route was visible to the researchers, both for safety and to ensure adherence. The route distance was chosen so that the exercise would have a likely duration of 10–20 min, which is sufficient for promoting positive changes in an adult’s mental state [34,35]. This duration was also popular in previous research comparing outdoor green exercise with built, urban, or simulated non-green exercise [3,6,7,14,29,30,32,33].Age, sex, and data relating to the three measures of interest were collected via a composite questionnaire.The Rosenberg self-esteem scale is a validated and widely used ten-item measure of psychological wellbeing in physical-activity research [36,37,38]. Respondents indicated the extent to which they agreed with each of the ten statement items by ticking one of four boxes along a Likert scale from ‘strongly agree’ to ‘strongly disagree’. The associated scoring of each item was from 0 to 3 (creating an overall score of 0–30) [39]. Higher score values indicated better states of self-esteem.The connectedness to nature scale (CNS) is a “measure of individuals’ trait levels of feeling emotionally connected to the natural world” and consists of 14 items rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) [40]. To calculate the overall CNS score, item scores are summed (the total scale score ranges from 14 to 70) and then divided by 14 to give a minimum of 1 and a maximum of 5. Higher scores reflect a higher degree of affective connectedness to nature. A ‘state’ version (rather than trait) was created in order to assess the acute state of nature affiliation. This has been validated using undergraduate students and showed positive associations with environmental self-awareness, private self-awareness, ability to reflect, attentional capacity, and a negative association with public self-awareness [41]. The current study used a simplified version of the state-version CNS.The short version of the profile of mood states (POMS) [42,43] is comprised of six subscales—tension, depression, anger, vigour, fatigue, and confusion. Individuals completed the POMS by describing how they feel ‘right now’ via responses to 30 single-word mood-descriptor items along a five-point Likert-type scale. Each mood descriptor’s score ranges from 0 (‘not at all’) to 4 (‘extremely’). Raw scores were converted to ‘T scores’ as per McNair et al. [43]. Although individual subscales can be analysed alone, all subscales are interrelated and an overall mood score that accommodates this can be calculated by summing the negative subscale scores (tension, depression, anger, fatigue, and confusion) and subtracting the subscale score for vigour. This overall score is called total mood disturbance (TMD), with a greater score indicating a worse mood (minimum = 112; maximum = 282). Validity and reliability tests showed that the shortened version of the POMS is suitable for use in exercise contexts [44,45].For self-esteem and CNS, repeated-measures ANOVAs were conducted to assess the effects of time and possible time-by-condition interaction effects. A MANOVA was used for the POMS. An alpha level of 0.05 was used to indicate statistical significance. All analyses were conducted using SPSS version 25 (IBM Corp, Armonk, NY, USA).Mean temperature was very similar between group (11.4 ± 4.4 °C) and lone running (12.63 ± 2.70 °C) sessions. Across both conditions, the ambient temperature ranged from 6 °C (mostly cloudy) to 20 °C (mostly sunny).Time taken to complete the 3 km was highly similar between conditions (group mean= 15.48 ± 2.70 min, in the range of 11.50–19.17 min; alone mean = 15.59 ± 2.38 min, in the range of 12.01–21.00 min).For the CNS there was a large (η2 = 0.53 [46]) and statistically significant main effect on time (F1,39 = 43.48, p < 0.001) but not the time-by-condition interaction (F1,39 = 0.28, p = 0.60; η2 = 0.007).For self-esteem there was a large (η2 = 0.45 [46]) and statistically significant main effect on time (F1,39 = 32.19, p < 0.001) but not the time-by-condition interaction (F1,39 = 0.45, p = 0.50; η2 = 0.012).For the POMS, there was a large (η2 = 0.58) and statistically significant effect on time (F6,34 = 7.84, p < 0.001). There was a medium-sized (η2 = 0.124) but not statistically significant time-by-condition interaction effect (F6,34 = 0.81, p = 0.573).Univariate analysis showed that for all of the POMS subscales there were large and statistically significant effects for time (tension F1,39 = 35.20, p < 0.001; η2 = 0.474; depression F1,39 = 9.92, p = 0.003; η2 = 0.020; anger F1,39 = 10.35, p = 0.003; η2 = 0.21; vigour F1,39 = 14.64, p < 0.001; η2 = 0.273; fatigue F1,39 = 1.275, p = 0.266; η2 = 0.032; confusion F1,39 = 16.91, p < 0.001; η2 = 0.302). Mean and standard deviation values for each measure at pre- and post-run in each condition are shown in Table 1.The purpose of this study was to provide a preliminary examination of the influence of group settings on some commonly reported psychological outcomes of green exercise participation. The hypotheses were that for each variable (mood, self-esteem, and connection to nature) (i) increases would occur in both conditions from pre- to post-exercise; and (ii) increases would be greater when participants exercised alone than when they exercised in a group.Hypothesis (i) was supported across all variables, with large score improvements from pre- to post-exercise. For the measures of mood and self-esteem, this finding is consistent with previous green exercise research and literature [6,47,48,49]. Although beyond the scope of this study to examine, previous research has indicated many mechanisms underpinning the acute exercise-associated improvement in affect, such as the endorphin and monoamine hypotheses, secretion of other neurotransmitters, transient hypofrontality, distraction, and altered reactivity of the hypothalamic–pituitary–adrenal axis and other brain systems to stressors [50,51,52]. The CNS increase from pre- to post-exercise in both conditions is, to the authors’ knowledge, the first reporting of such a finding. It suggests that both group and lone green exercise participation could be employed as a means to increase public levels of nature connection. This is a key focus of conservation organisations given the links between connection to nature and pro-environmental attitudes and behaviours [53,54]. In addition to affective responses to exercise [15], enhanced connection to nature might also serve as motivation for future engagement in exercise behaviours.Hypothesis (ii) was not supported—improvements in each measure were similar between solo and group exercise. The simplest interpretation of this finding is that social setting does not influence an individual’s achievement of the psychological outcomes of green exercise participation. However, there may be more complex processes underpinning this finding. In line with the proposition of dual-mode theory [55], the relative contributions of social and environmental settings may have differed between conditions. It might be that social influences of the group setting functioned to positively influence the outcome parameters while simultaneously reducing the occurrence or potency of individual (physical) environment-level interactions, which within the ‘alone’ condition functioned unimpeded to promote the reported psychological outcomes. The opposite interpretation is also possible—the positive effects of exercise and/or the environment were simply far larger than any influences of social setting. Although the design of the current study does not allow for conclusions about such environmental effects, previous research has frequently reported that greenspaces promote greater psychological improvements compared to exercise in built (real or simulated) or indoor environments [1,2,4,5,6,7,8,9,10,14,32]. If environmental settings do indeed influence psychological outcomes in this way, considering the affective improvements observed, the current findings suggest that practitioners should not fear possible lessening impacts of group settings on the cited benefits of selecting nature/greenspace environments for boosting psychological outcomes.The current study builds on existing literature by using a robust design. However, further research should utilise a two-factor design to investigate how social and environmental settings may interact. Further research should also consider this research question in relation to other parameters previously reported within green exercise literature, such as directed attention, other affective states, and physiological and behavioural measures. A further limitation of this study was that data on participants’ preferences and usual behaviours regarding solo or group exercise were not collected. It is therefore not possible to know the extent to which individual differences in these factors were present and whether they may have been counterbalanced across the hypotheses and experimental design.Although the current study did not find that social setting influenced the dependent variables, it is important to note that our sample consisted primarily of healthy young to middle-aged adults who reported relatively positive pre-run scores. Testing the current hypotheses in different cohorts, such as those experiencing depression, poor mood, or low self-esteem, is of great interest to scientific understanding and health practitioners. To this point, the current study could be developed through further research to also examine possible longer-term effects of social setting on outcomes and adherence to green exercise participation. For example, in relation to dual-mode theory, how does a group setting influence the phenomenological experience and psychological outcomes of green exercise when participation becomes a frequently repeated behaviour?This study serves as a preliminary investigation of the possible importance of social setting in relation to previously reported affective outcomes of green exercise participation. No significant influence of social setting was found, offering a platform for debate over the interplay between environmental and social settings in relation to psychological experience and outcomes of exercise.Conceptualization, R.B., A.D. and I.C.; methodology, R.B., A.D. and I.C; formal analysis, M.R.; investigation, A.D.; writing—original draft preparation, M.R., A.D.; writing—review and editing, M.G.; supervision, R.B., I.C. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors declare no conflicts of interest.Mean ± standard deviation values for psychological measures.TMD: total mood disturbance; POMS: profile of mood states.

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+In Youth-led Participatory Action Research (YPAR), youth collaborate with academic researchers to study a problem, develop actions that align with their needs and interests, and become empowered. ‘Kids in Action’ aimed to develop actions targeting healthy physical activity and dietary behavior among, and together with, 9–12-year-old children as co-researchers. This paper presents the process evaluation of ‘Kids in Action’ based on eight focus groups with children (N = 40) and eight interviews with community partners (N = 11). Interview guides were based on empowerment theory and the RE-AIM framework, in order to evaluate the study on: empowerment, collaborations, reach, effectiveness, adoption, implementation, and maintenance. Transcripts were analyzed using evaluation and provisional coding. Both children and community partners perceived an increased awareness of healthy behaviors and an improvement in confidence, critical awareness, leadership and collaboration skills, which contributed to increased feelings of empowerment. Community partners valued child participation and the co-created actions. Actions were also well-perceived by children and they liked being involved in action development. The strong relationship of researchers with both children and relevant community partners proved an important facilitator of co-creation. Future studies are recommended to attempt closer collaboration with schools and parents to gain even more support for co-created actions and increase their effectiveness.Youth-led Participatory Action Research (YPAR) is a methodology in which academic researchers collaborate with youth to make improvements in their. Youth who participate in YPAR identify issues in their community that they want to improve, and through conducting research, find starting points to take action and make change happen [1,2]. They become change agents and build the power to improve their communities [3]. Youth are seldom involved as co-researchers [4], but as experts of their own lives, they can provide valuable insights into their community, lives, and behaviors [5]. In YPAR, youth participate in the research process as co-researchers. Reviews have shown that participating in YPAR can improve skills related to agency and leadership, research, social skills, critical and social consciousness, and increase knowledge about the research topic [6,7]. Moreover, youth can improve their feelings of empowerment [6,8]. In a general sense, empowerment refers to: “[…] the ability of people to gain understanding and control over personal, social, economic, and political forces in order to take action to improve their life situations” [3] (p. 152). As such, YPAR can also be beneficial for the community and local organizations [7]. Actions initiated by youth are more aligned with the needs and wishes of their community [9]. YPAR has mostly been applied in school-settings to address problems with education, social inequalities, health, or the physical and social environment [10,11]. To date, top-down developed health promotion interventions have generally shown disappointing effects. This is especially worrisome for youth from low socioeconomic positions (SEPs), because health inequalities have been maintained or increased [12]. YPAR may be the key for developing more effective actions that match the characteristics and health needs of this hard-to-reach group [6,7,13]. ‘Kids in Action’ is such a YPAR study, in which academic researchers collaborate with 9–12-year-olds (further named ‘children’) from a low SEP neighborhood in order to improve their physical activity and dietary behavior. ‘Kids in Action’ was initiated because of the high prevalence of health problems in this particular community. We hypothesized that YPAR would lead to better tailored and thereby more attractive and effective actions for this low SEP community [6,9]. Throughout the study we tried to collaborate with children on the level of shared decision making—i.e., level 6 of Hart’s children’s participation ladder [14]. The overall research aim of improving children’s lifestyle was decided upon by researchers, but during the rest of the study, children were actively involved as partners: By actively giving input through participatory meetings, conducting research, analyzing results, and implementing and evaluating actions [9]. Children became partners starting with the participatory needs assessment, where children, parents and community professionals identified two main needs that specified the aim of the current study (i.e., improve physical activity and dietary behaviors). To gain a deeper understanding of the more and less effective elements of actions, as well as facilitators and barriers for sustainable implementation [15,16], academic researchers conducted an extensive process evaluation. Children were not involved as partners in the process evaluation, because it was conducted over several years and we worked with different groups of children each year. Moreover, the extensive process evaluation would take too much time, which children needed to develop actions.Remarkably, few process evaluations of YPAR studies are published [17]. As participation of the target group in action development has recently gained increasing popularity, process evaluations of YPAR studies are urgently needed to gain insight into essential preconditions and challenges [18]. This article describes the qualitative process evaluation of ‘Kids in Action’ including the participatory process, the developed actions, and the outcomes of the study from the perspective of children and community partners. For a detailed description of the methodological process of combining YPAR with intervention mapping (IM) and how this was experienced by the researchers, we refer to Anselma et al. 2019b [19].Researchers from the Amsterdam UMC collaborated with the sports-based daycare ‘Kids Aktief’ (KA) from the commencement of this study and the application for funding. Together with the local government, it was decided to focus on one specific community in their district that would benefit most from a YPAR study aimed at stimulating a healthy lifestyle in children. When setting up the study, the policy makers invited the research team to join an existing community project group working on healthy lifestyles of children in the community. Textbox A describes the most important participants and community partners of this study. The ‘Kids in Action’ study consisted of two phases, of which phase 1 started in 2015 with a participatory needs assessment. Research was conducted in collaboration with children, and interviews were held with parents and professionals from the community project group. Results showed that low levels of physical activity and unhealthy dietary behavior were perceived as the main health problems that children in the community faced. Therefore, improving these behaviors in 9–12-year-old children became the focus of phase 2, which started in 2016 and lasted for 3 years [20,21]. The current paper evaluates the process of phase 2, where children were involved throughout the process of action development, implementation and evaluation, from doing background research to developing and evaluating actions. YPAR was combined with intervention mapping (IM), a stepwise approach to developed evidence-based actions, to structure the process of action development and relate children’s ideas to evidence-based behavior change strategies [19,22]. Children were involved throughout the IM-process as much as possible, with certain IM-steps being adapted to be suitable for children. Some theoretical tasks were performed by an IM expert panel as they required specific knowledge that would be difficult or too time-consuming to teach the children. The process of combining IM and YPAR was iterative and is described in detail in Anselma et al. 2019b [19].KA: Kids Aktief—Community organization part of the Planning group.Research team: M.A., M.C., T.A.YPAR group: Child-researchers plus one or two academic researchers from the Amsterdam UMC (one being M.A.). YPAR groups were called an Action Team in year one and two, and the Youth Council in year three.Action Team: In the first two years of the project, there was one YPAR group at each of four primary schools in the community, called an Action Team.Youth Council: In the third and last year of the project there was one YPAR group in the community with representatives of the four primary schools. The Youth Council was hosted by M.A. together with three community organizations, and facilitated by M.A. and a social worker from one of these organizations.Planning group: Academic researchers from the Amsterdam UMC, youth policy managers of the local government of the North of Amsterdam, KA, child-researchers from YPAR groups.Community project group: Academic researchers from Amsterdam UMC, policy makers from the local government in the North of Amsterdam with a focus on youth, KA, representatives of other organizations working with children in the neighborhood such as social workers, teachers and principals of primary schools, and staff of after-school daycare organizations.Respondents of interviews: Three school principals, two school teachers, two policy makers from the local government with a focus on youth, four social workers from community organizations working with youth.In the first year of phase 2 of the ‘Kids in Action’ study, we started a participatory group (YPAR group), called an Action Team, at each of the four primary schools in the community [21]. The Action Teams consisted of 6–8 children between 9–12 years old, who met weekly or every two weeks for 45–60 min. Children were recruited through the schools, and parents of participating children provided informed consent. Selection procedures varied per school and per year. For example, in the first year, at one school, all children could sign up; at two schools the meetings were held during school hours, therefore teachers selected children who could miss academic time; at another school, children who were part of the student council were invited to participate in the Action Team. Table 1 provides an overview of the members of the YPAR groups per year. Detailed information about the content of the meetings, the YPAR process and the developed actions is reported elsewhere [19]. In short, during the YPAR meetings, the Action Teams were trained in research skills and developed, implemented, and evaluated actions. In the first year, each Action Team conducted their own research to validate the findings of the participatory needs assessment. Program goals and performance objectives were developed and deliberated with the Action Teams. The Action Teams thought of ways to reach the goals, voted for the best ideas, and then further specified the ideas by making production and implementation plans. At the end of the first year, the developed actions were pilot-tested. At the beginning of the second year, new Action Teams were formed, with some children of the first year continuing their participation. One school decided not to participate in the second year because they chose to participate in another study. They decided to re-join the project in the third year. The three Action Teams in year two further implemented and evaluated the pilots of year one, but also worked on new actions. Table 2 provides an overview of the goals the Action Teams wanted to reach, the most popular initial ideas, and the developed actions.Instead of one Action Team per school, in the third year one Action Team was started with representatives of three schools, called the Youth Council. The principal researcher (Manou Anselma) hosted and facilitated the Youth Council together with representatives of three community organizations and trained them in facilitating child participation. One social worker of one of the community organizations co-facilitated the Youth Council with the principal researcher throughout the year, with the goal of hosting the Youth Council by herself with a new assistant the following years. This collaboration between Manou Anselma and the three community organizations ensured the continuation of child participation in the policy of community partners after the research project. Children from the three highest grades of the four schools in the community could sign up for the Youth Council, but from one school no children signed up. The aim and the process was similar to that of the Action Teams of the first two years, but the Youth Council focused more on community actions instead of school-based actions, and had a broader focus than health.Four main research questions guided the process evaluation: (1) How did children and community partners experience the participatory process and how will it be taken forward? (2) How did children and community partners experience the developed actions? (3) How did the involvement of children in decision making and community change, influence children’s health behavior and empowerment? (4) What are essential preconditions and challenges of YPAR?We conducted a qualitative process evaluation because we were mainly interested in experiences and processes instead of numbers. Data was collected through focus group interviews with children and individual interviews with community partners. M.A. led the interviews and focus groups while a research assistant took notes, kept time and made sure all topics of the interview guides were covered.The focus group interviews were held at the beginning and end of year two with the three Action Teams and at the beginning and end of year three with the Youth Council. No actions were developed in year one because the first year was mainly dedicated to completing the needs assessment. Therefore, the first focus groups took place at the beginning of year two. The focus groups had a semi-structured outline, where assignments were prepared beforehand and the facilitators asked guiding and clarifying questions. We used literature on empowerment theory to develop the protocol for the focus groups with children [3,23]. Through two group assignments where children had to think about actions in the community (details described below), the focus groups evaluated children’s individual, organizational, and community empowerment [3,21,23]. We used the definitions of Israel et al. [3], with ‘individual empowerment’ being defined as the children’s ability to make their own decisions and have control over their own life. We applied ‘organizational empowerment’ at the school level, and looked at whether schools enabled children to actively participate in decision making and whether schools were involved in community decision making. ‘Community empowerment’ was defined as the children’s and organizations’ ability to collectively reach the goals set for the community. The first assignment mainly assessed individual empowerment and awareness of the community. The Action Teams had to think of an action they wanted to implement and write down all the steps needed before implementing the action. For example, they were prompted to think about the goal of the activity, finances, getting approval, target group, promotion materials, etc. In the second assignment the children had to write down all activities and changes that had taken place in the community and at school in the last year. Of those activities and changes they identified if children were involved in the developmental process, how they felt about children being or not being involved, and how children’s opinions were valued. This second assignment assessed organizational and community empowerment. Because children’s participation and influence at school and in the community were assessed, the developed actions were also discussed. In the last focus group of the Action Teams, children could also bring friends to add information about empowerment of non-Action Team members.Towards the end of the study (May–June 2019), we reflected on ‘Kids in Action’ through individual interviews with the community partners who most closely worked together with the research team. The potential respondents were contacted via e-mail or phone. All community partners agreed to an interview, except for one teacher and one school principal who did not have time.The interviews with community partners were guided by the RE-AIM framework [24]. The RE-AIM framework aids structural evaluation of actions on five dimensions: reach, effectiveness, adoption, implementation, and maintenance [24]. ‘Kids in Action’ can be seen as a participatory process leading to a multicomponent action. In order to tailor RE-AIM to the participatory process of our project and to be able to answer our research questions, we adapted the interpretation of the five dimensions and added new dimensions such as empowerment, collaboration, and communication. Table 3 presents examples of questions from the interview guide. The interview guide consisted of seven sections: (1) Reach—which children participated in the actions and the YPAR groups; (2) Effectiveness—both of the perceived effectiveness of the actions on health behavior and the effectiveness of the YPAR method on, for example, empowerment; (3) Adoption—of the actions and the YPAR method in the schools and community project group; (4) Implementation—of the actions and the ‘Kids in Action’ study in the community; (5) Maintenance—of the actions, the perceived effects and the YPAR method; (6) Collaboration—with the principal researcher, KA, and within the community project group; (7) Communication—between the principal researcher, children, parents and community project group, and communication in general.The focus groups and all but one interview were audio recorded and transcribed by the academic researchers who conducted the interviews and focus groups in Dutch. One respondent did not feel comfortable with the audio recording, and therefore the assistant took extensive notes. The interviews were summarized and sent back to the respondents for a member check. M.A. coded and analyzed the transcripts of the focus groups and interviews, and the extensive summary of one interview, in ATLAS.ti. Empowerment theory was also used to develop a starting list of codes for empowerment [3,23] (Table 4), which was made by M.A. and checked by T.A. Provisional coding was used for everything related to empowerment, both in the focus groups and interviews. Extra codes could emerge and relations were derived from the data. We used evaluation coding as a basis to code topics other than empowerment, and combined this with several other coding methods such as magnitude coding, descriptive coding and emotions coding, to be able to differentiate between positive and negative items, to label emotions and experiences, and to be able to give value to the variety of materials [25]. M.A. conducted all coding and, where needed, consulted TA to resolve uncertainties. All analyses were conducted in Dutch and results were translated by M.A. for the current paper. Quotes that could serve as an example of, or explain a piece of text, were also selected and subsequently translated by M.A.Table 5 describes the characteristics of the focus groups. Most focus groups were divided over two sessions as the content did not fit within one session. Table 6 provides an overview of the respondents of the interviews and their occupation. The results are presented in the following themes: empowerment, becoming part of the project, collaboration, reach, effectiveness, adoption, implementation, and maintenance. The section ‘empowerment’ mainly consists of data from the focus groups with children, the other themes mainly consist of data from the individual interviews with community partners.Table 7 provides an overview of the coding scheme used for items related to RE-AIM and the YPAR process.AT1 and AT2 already had a good sense of community at the beginning of the year, took preferences of other children into account, and could think about the bigger picture [AT1, AT2]. For their idea to create signs that people had to clean up after their dogs, AT1 thought about financing, involving the community to increase awareness, promoting their cause in the community and impact: “But when you make a sign, people just walk by and do nothing. It has to draw attention. It should not be that you have woods or a park and you put up a sign and everybody just walks past it and doesn’t look at it.” [AT1]AT3 and the Youth Council started as new groups in the beginning of the school year and they had to get used to the participatory approach. It was more difficult for them to think about the bigger picture. AT3 could only think about their own individual network, for example by only inviting their friends to participate in actions and asking help of their own parents. They took the opinion and preferences of other children into account, but could not think of practical steps how to involve them. Also, the Youth Council was not aware of any community organizations they could ask for help. At the end of the year, their thought processes were much more clear and practical. The Youth Council was for example more aware of the costs of activities, e.g., using second hand materials, and AT3 had more fruitful discussions regarding how to develop activities and create realistic ideas.Children from all participatory groups indicated that they preferred to ask approval for an action quite early on in the process, to prevent investing much effort and time and then not getting permission to continue with it.Two principals described that in the beginning children started super enthusiastic and when they got an assignment they went all out and did not think about feasibility or practicalities [S1, S2]. During the year, they learned to take into account the bigger picture, for example, to include more people, cultures and viewpoints [C8].Most children mentioned that they learned more about healthy behavior, for example about physical activity guidelines and the importance of a healthy diet [AT1–AT3, YC]. They also learned to discuss within the group, collaborate with others and do research. Children really liked doing research, such as interviewing their peers and making pictures.One of the teachers observed that children of the Action Team became leaders in class as they felt important and more confident [S5]. Respondents also mentioned that children learned skills that could benefit them at school and outside of school, became more aware of themselves and the community, improved their collaborating skills and making democratic decisions, gained more confidence, and became representatives for other children in the community [S1, S5, C9]. “Before he [member of Action Team] never stood out, but he left school much more aware of his skills. That he can ask things, be critical to himself and to others. Also some of the other kids. I can remember two or three girls, they became more capable to find common objectives through collaboration. I’ve seen that in at least three or four kids.” [S1] S3 further mentioned that by participating in such a group where children had more space and attention, they developed and showed talents that may be missed in the classroom. Respondents especially enjoyed seeing the improvements in children who they at first did not expect to participate in such a group [S1, S3, C8]. C8 and C9 heard back from parents that their children were happier at home, were more talkative and had gained more confidence, through participating in the Youth Council [C8].Children of the Action Teams felt special because they were members of the Action Team, as indicated by one of the Action Team members being annoyed with one of the non-Action Team members, because she “did not understand the process”. Both Action Team and non-Action Team members felt they had participated in organizing activities [AT1, AT2]. Children liked actively working on developing and implementing activities most [AT1–AT3, YC]: “I liked everything but mainly implementing everything and sitting around the table and develop things and that you saw that children really liked it, such as the Olympics and making the dog-poo signs and asking questions in classrooms and the cooking workshops” [AT2]. Children liked being appreciated for the actions they had developed and believed they did important work for the community [AT3, YC]. They liked the activities they had developed, as activities organized by adults were ‘old-fashioned’ [AT2, YC]. The Youth Council felt that they could really add value as they had more and better ideas than adults: “Because children are more creative and think and look at things in a different way than adults, and because of that can make things more fun. And children can think in a smarter way than some adults when they are being difficult. They [adults] only think about one thing: what the problem is. But children can go around that and find a better solution.” Children mentioned that they felt strong, proud or ‘the boss’ when they helped to organize something [AT2, AT3], such as the Olympic sports tournament: “Because when we arrived I thought: God, I decided on this!” [AT3]. However, not all Action Teams felt ownership over the developed actions, such as AT2, who could not come up with all the actions they had helped to organize.One of the keys to the success of the project was that children liked participating in the participatory groups because they were given much freedom, they felt listened to and felt valued for their ideas, as well as seeing results from their involvement [S2, C8]. Because the activities were developed by children, they were also more supported by other children [S3].AT1 and AT2 were confident about doing everything themselves. If required, they sought help from the facilitator and other teachers of KA. AT1 did not want too much help, because: “It’s also not cool if somebody else does it while they are our ideas and we can also execute them ourselves.” At the end of the year were even more confident in talking to community organizations, potential sponsors, teachers or the principal: “Miss can I say something, I don’t think we need any help. And do you know why? Because we are [the Action Team]. We did a lot of things by ourselves.” They could easily think of ways of persuading others to help them, for example by telling the school principal that the ideas of the Action Team match the objectives of the school. They also discussed what they would do if the principal would not approve of their idea: they would just come up with another idea.AT3 needed much assistance at the beginning of the year in thinking about steps to take and how to execute them. At the end of the year they had more ideas and more confidence in executing them. In the Youth Council, most children felt they could do most things themselves, which was not always realistic. At the end of the year, they had become more realistic and for example said they could ask the local government for approval, but would like the facilitator to go with them.In all participatory groups children immediately started thinking about ideas for actions and implementation. Through the YPAR process they learned that there were multiple steps they had to take and thought of more feasible ideas and timelines [AT3, YC]. Children also noticed improvements in their self-efficacy. At the end of the year a boy of AT3 said he had learned to speak up more and a girl of AT2 who was shy at first, confidently said that she had administered questionnaires in several classrooms by herself. Teachers mentioned that children from the Action Teams had really developed during the year, dared to ask more questions of teachers and the principal, and have discussions with them [S1, S4, S5].Most children had positive relationships with their teachers, which was important to get their research done or actions implemented [AT1, AT2]. Mostly it was principals who played an important role in the project, because children had to ask permission to organize an activity at the school. The principals were always willing to talk with the children and explain why they supported an idea or not [S1, S2, S4]. Other day-to-day tasks were mostly handed over to teachers [S2, S4].It was felt that schools could be more involved in the community [G7, C9, C10], “because it [activities in the community] fails or succeeds based on the commitment of the schools” [S1]. S1 explained that if there was a community meeting where schools were invited, they were the only school that was present, which was considered to be a shame. The schools and the principals have an important role in the community, which was not considered as such by all schools [S1, G6, G7, C9–C11].The Action Teams mentioned that child participation in school decision making was low. AT3 felt that their opinion was often asked by the school, but they were upset because nothing was done with their opinion: “They ask our opinion, but then they don’t do what we asked. Then I just become angry.”. They felt that they were rarely taken seriously because they were children [AT1, AT3]. S1 acknowledged that adults often wrongly assume that children are not able to do certain things. At the end of the year, the Action Teams indicated that they had participated more in decision making at school, but that was mainly through the actions they had developed. AT3 described that when they wanted to fix something at the school playground, the principal organized a sponsored run for them to get the finances for making the playground improvements. At this school, two kids of the Youth Council also started an anti-bullying club that was very successful and had many members [YC].When an Action Team or the Youth Council had tasks that needed to be executed, the schools gave the children much responsibility with teachers/principals just guiding the process [S1, S3–S5, AT1]. However, the community partners said that the Youth Council came up with many ideas for actions for their schools, but that many were not supported and implemented by the school [C6–C11]. They would like schools to be more involved in the community and support the children’s work: “Children have fantastic ideas, but our organizations can’t implement them all. Schools are not involved, so at the end of the day children take their ideas home and nothing is being done with it” [C10].In the beginning of the year, children felt that they had more influence in decision making in the community than at school [AT1–AT3, YC]. AT3 had the least positive experiences in decision making with community organizations; at this school, fewer activities were organized by community organizations. At the Youth Council the children felt they had some say in activities of community organizations, but not much. When they were asked about activities where children did not participate in the development, it was “too much to write down”. One of the children explained that children should have more influence in decision making: “It is for the better, because we are also here and it is important that we can also make our voice heard. Not only adults can make good decisions, we as children can do that as well. That’s why we try to make our voice heard [through the Youth Council].”At the end of the year, all groups felt that children were more involved in community decision making, especially through the activities they had organized themselves. Also non-Action Team members felt they had a voice in decision making and were satisfied with the participation of children in the community [AT2]. The Youth Council became more aware of all the community organizations and also felt that the Youth Council was taken more seriously. During the year the local government often invited the Youth Council to meetings to include children’s point of view, which community partners appreciated. Despite this, some community partners were skeptical about how much of the children’s ideas were going to be implemented by the local government [C9–C11].Respondents’ reasons for participating in the project were because the project had similar goals to their school/organization or because it was decided for them on a higher level [S1, S2, G7, C9]. In the community all principals decided to join as it suited their schools’ policy and plans [S1–S4]: “Joining the project was something we consciously chose for as we saw it as added value.” [S3]. The policy makers further explained that the project related to their policies aiming to improve children’s health behavior and as it was a practical research that could strengthen the community [G6, G7]. The policy makers had successfully collaborated with KA before and because they were approached by them they were more inclined to agree.Most respondents did not have any expectations when joining the project [S1–S5, C9, C10]. They explained that the community had seen many projects passing by without any useable outcomes so they stopped having expectations: “We don’t have any expectations anymore and then any benefits that come from a project are perceived as a win” [S5]. S5 mainly hoped that children liked participating and with their enthusiasm could reach other children. C11 mentioned that she had high expectations of the Youth Council because it was hosted by so many community partners. The local government expected positive changes in the community because they knew KA as a hands-on organization and they were confident that research backed-up by them would be a good investment for them and the community [G6, G7]. Also, the grant application was judged to be comprehensive and substantial [G6, G7].All respondents were positive about the collaboration with the research team. However, some community partners and the research team had to get used to each other and their different ways of working [S2, G6]. “But what I mainly noticed is that if we as a school thought that something was not practical there was always room to talk about it and figure out: How can we do it in a better way?” [S2]. Some members of the community project group were a bit hesitant about collaborating with KA, mainly because in the beginning they were not aware of the goal of the project [G6–C9]. After that became clear and they realized the project only wanted to strengthen already existing work processes, strong collaborations were formed [G6–C9]. The community partners that co-hosted the Youth Council worked closely together with M.A. and appreciated the collaboration [G7–C9]: “I’ve never worked together with someone who… who I can trust, you know. I know that if I could not handle something, I was listened to and that was a huge support. No I really think you’re great. I am going to miss you. Really, really. You’re a person close to my heart” [C8]. C9 specifically appreciated that they were invited to participate in an action through which they received sports materials so the children at their organization could be more physically active. For them this was a perfect example of how different organizations and projects could strengthen each other [G6–C11]. This was sometimes a challenge in the community, as there were many organizations with their own agenda [C9–C11].Schools appreciated the regular contact with M.A. which helped them to stay updated and they appreciated the reminders if they forgot to respond [S1–S3]. Respondents liked the quick response via e-mail or telephone and that M.A. communicated ahead of time regarding the planning [S3–S5, C8–C10]. Every two months there was a meeting with the research team and the local government, where—without an agenda—the status and challenges of the project were discussed [G6]. This was valuable for the local government to stay updated and help out where needed, and was experienced as crucial for the strong collaboration between the local government and the project [G6, G7]. They explained that the research team could have asked more from them, for example, that they could have already from the beginning been involved in maintenance of the actions.M.A. led the research for four years, which meant that all children really got know her. This helped to get children involved and keep them involved in the project [S5–C11]: “It is a tool, having a familiar face in the community. If something is up with them, then they know who to go to and they know you are watching them and looking after them. Then I think, yeah, you know, we should use this more in such communities. Especially when I now look in this community, I think about the familiar faces working in the community” [G7]. Recruitment for participants was easier when the school principal encouraged teachers to recruit children [S1, S5], and when a researcher went from class to class to explain the research and hand out attractive leaflets for the actions [S3, G7, C10]. In the Youth Council children from various ethnic backgrounds participated and more boys than girls, which was a surprise [G6–C10]. It was considered a shame that not more children could participate, as more children could benefit from participating in such a project [C10]. Having one Action Team per school—versus one Youth Council—had the benefit that more children could participate [G7]: “But I don’t know how realistic it is to maintain that. If you indeed have one Youth Council in the [name community], that would be amazing.”Respondents did not know whether the actions indeed reached children with unhealthy behaviors [S1, S2]. All respondents were satisfied with the number of children that was reached, especially with the extracurricular sports activities, with about 60 children participating weekly, and in the Olympic sports tournament, where 350 children participated.The main perceived effect of the project was that children and parents became more aware of the importance of physical activity and healthy dietary behavior [S1–G6, C8, C9]. Real behavior change was more difficult to perceive and respondents were unsure if this was reached [S2–G7, C10]. Another important perceived effect was that children and community partners learned from the project (for children’s learning see Section 3.1) [S1, S5–C8]: “Well I at least became a lot more aware. Look, you actually have known your whole life that you need to give children a voice in things and that you have to actively involve children. And the entire education system of course has also developed from more whole-class teaching to a lot more interactive and together. But yes this should happen in more areas. That is the good thing about it, that even if you are old and grey [laughs] you can still learn certain things and develop” [S1]. C8 described that because they facilitated the Youth Council together with M.A., they learned much about how to work together with children in such a project. It was also mentioned that being involved in the project helped to place healthy behavior higher on the agenda and strengthen already existing policies [S2, S3, S5–G7, C9]. As the Action Teams and Youth Council were so successful, it served as an example to take child participation more seriously [G6–C8].Different factors facilitated the positive effects. First, because M.A. spent a considerable amount of time in the community and was always present at meetings within the community, a strong network was created including children, parents and community partners [G6, G7, C10]. In the beginning, community partners and policy makers perceived a good relationship with schools as being challenging, but the good relationship with schools became a strength [G6]. Second, the project was able to reach many children from the start, and those children were so enthusiastic that they spread the message to other children and parents [S2, S5–C8, C10]. Third, the research team and the collaborating partners really listened to the children, worked together with them on an equal level and took action [G6, C8]. Furthermore, most implemented actions were a success and created more support for healthy behavior and child participation in the community [G6–C9, C11]. Lastly, the strong collaboration with community partners was mentioned as a strength of this project [G6–C11]. For example, because the project was embedded within KA, there were always enough people available to help in executing actions and measurements. Therefore, these activities were not a burden for the school staff [S4].For children, community organizations, teachers and parents were their most important collaboration partners [AT1–AT3]. AT1 and S3 mentioned that parents of the parent committee at school were known for being involved in the community. They for example helped with activities at school and helped children with organizing activities. C8 explained that children participating in the Youth Council became very involved in the community and were often organizing/participating in community events. They proudly represented the Youth Council, and with that, inspired other children: “When children are involved in something as the Youth Council, they have more confidence and because of that they are happier and participate in more activities. They radiate this onto others. You know they draw more children to these activities, those kind of things. Those are all positive side-effects.” [C10]Generally, respondents from the schools mentioned that they were well informed and therefore knew about the goals and processes of the project [S1–S3, S5]. Some respondents mentioned that providing more updates [S1, S3–S5, C10] and more communication about the project within the schools [S2–S5], could have supported the adoption of the project: For example, the contact person within the school could share more information within the team and engage teachers in activities [S1–S3]. “As a teacher you sometimes have the feeling that you are less involved or don’t have an active role in a project. I didn’t really have the feeling that I had an active role. And now that I think about it, maybe I would have liked to have that. When the school is actively involved, it also becomes more of a school project” [S5]. Since schools have a busy program and a shortage of teachers, an extra project does not automatically receive attention [S1–S3]: “Sometimes we have to push teachers, because teachers do think it [the project] is important, but so many other things are also important” [S4]. Another factor hindering adoption at one school was a significant amount of change in the management [S5]. The successful implementation of actions may have supported adoption [S2, S3, G6] and involvement of teachers [S2].The schools mainly spoke about the process of the Action Teams of the first two years, as the Action Teams met at the school and organized mainly school-based actions [S3–S5]. The Youth Council met in a community center and therefore teachers felt less involved. S5 explained that one version was not better than the other, but the Youth Council was less visible for the school: “The first year I thought it was great; everything was clear. The kids came together and they told us what the meeting had been about. But that became a bit less in the last year. […] I have the feeling I did not see children participate as actively as in the first years and I didn’t see as many actions. But that could also be because the meetings were not in the school anymore.” The value of the Youth Council was that children learned to cooperate with children from other schools [S5, G7]. As the Youth Council was hosted by multiple community partners, there was much support for developing and implementing actions from the start [C10]. The Youth Council became very popular in the community and was invited to many community meetings [G6, C8–C10]. As a consequence, children had less time to work on the development and implementation of their own ideas, while that is what kept them involved and enthusiastic [S2, G6–C11]. Children mentioned that they would like to have a less busy schedule and the facilitators saw that children became less involved towards the end of the year [C8–C10].Some points for improvement were suggested in the process of collaborating with children. First, the Action Teams and Youth Council could involve more children in the decision making process, making it a project of all children instead of only the ones in the participatory groups. Second, it was considered a shame that one school did not participate in the Youth Council, due to extracurricular activities happening at that school at the same time as the Youth Council’s meetings [S4, C10]. For the following year the schedule of the Youth Council should be better suited to all schools. Third, the low parental involvement was mentioned as a point of improvement, but was acknowledged as a challenge and time investment [S3, S5, G7, C10, C11]: “Maybe we could have invested more in parent participation. I think that should also be a focus point for the Youth Council for next year. With the cooking classes we managed to have some parents present, but it is very difficult and you have to be lucky to find a mother who is interested. But it is definitely something we should focus on” [C11].C9 believed that the project definitely helped to create sustainable actions. Respondents mentioned that children were very enthusiastic about the developed activities. Two of the school principals explained that at the after-school sports activity at their school, more children joined every week and they were happy with this development [S2, S3]. That was also why it was so important that activities were continuous throughout the school year(s), so children and parents knew what to expect and where they could go [S1–S3].All schools were positive about the Olympic sports event that was organized for children from all schools in the community and they hoped that it would continue to be a yearly event. They mentioned that it brought schools and children together, which was good for the community. S3 was proud of the water policy that was successfully implemented at her school, despite children not being happy with this policy in the beginning. Also one of the boys who helped to implement the policy did not always adhere to it. But when the teachers told him “Hey, this was your idea!”, he acknowledged that and without discussion threw his juice away. Most schools did not know much about the cooking workshops, but heard positive stories from the children [S2–S5]. C8 was only involved in the project in the last year, but had heard about the project’s actions through parents, who were always very positive. Parents said they liked that the activities were within the community because that was exactly what was needed. In the beginning of the project G6 and G7 felt that it took a while before actions were implemented. When the research team explained the process of participatory research again it made them understand that this was a different process from how the local government usually works [G6, G7]. G6 and G7 suggested organizing some small activities in the beginning of the project: “Of course you should not do large activities, because yes first you want to know what they want, but you know, some small activities that children can influence and that you are going to organize. Then you involve the schools [and they feel] like, ok well ok, it is going well, everything is going well, it is a trustworthy organization. Then you’re accepted faster and other organizations have less cold feet to collaborate.” [G6]Children liked the implemented activities. In the Action Teams they mainly discussed the cooking workshops and Olympics, as most children had helped in the development. They liked the practical cooking workshops and going to the local garden [AT1, AT3]. They hoped that future cooking workshops would include more foods they liked and that everything was not super healthy. They also wanted to introduce food from their culture [AT1]. Most kids were also positive about the Olympics but it was also mentioned that there was a significant amount of cheating and rough play between schools, which they did not like [AT1, AT2]. Children were very proud of the signs that they made to clean up after your dog and that it was actually implemented by the local government. The Youth Council was positive and proud of the Youth Club center they created and hoped it would last for many years.Maintenance was an important topic for the respondents. They hoped that the line of work—both with the active participation of children and the actions—would continue. But all had doubts about how this would be taken forward. Mainly finances were a perceived barrier. S2 and S3 wanted to continue the extra sports activities at their schools, but questioned who was going to pay for it. Respondents mentioned that it could have helped sustainability of the actions if the research team would have pressed thinking about sustainability at an earlier stage [G6, G7, C11]. Some actions were taken up by community partners: the water policy that was introduced was sustainably implemented [S3, S4], some sports activities received extra funding [G6, G7], and the cooking classes and Youth Club center were taken up by community partners [G6–C11].The community network was perceived as a facilitator to continue working on child participation and healthy behavior [S1, C8–C11]. At different organizations in the community they valued child participation [G6–C8, AT1, AT2], and also at schools they were trying to incorporate participation in their curriculum [S1–S4]. The plan was to continue the Youth Council [G6, G7, C8–C11]. Respondents enjoyed seeing the children so passionate and involved in their community[G6-C8]. Acknowledging the investment in time, energy and budget, they considered it a challenge to find someone to take over the facilitation role of M.A. [C9–C11]: “It actually shocked me that you spent a full day a week on it [the Youth Council]. So I thought, yes, you know that’s actually quite a lot.” [C11]. The community partners co-hosting the Youth Council were also dependent on funding from the local government [G6–C11]. During the course of this study, participation of children was always on the agenda of the local government, who were therefore very supportive of the study and children’s activities [G6, G7]. But with someone else in charge of policy in the future, this may change [G6, G7, C9–C11].At the end of the interviews we asked the participants to pick three attributes that they valued most about ‘Kids in Action’. We presented eight items, but respondents could also add items themselves (Table 8). ‘Participation of children in decision making’, ‘the developed actions’ and ‘communication’ were mentioned most often.This study evaluated the process of the ‘Kids in Action’ study. An identified strength of ‘Kids in Action’ was the strong collaboration of researchers with both children and community partners. Through YPAR, children became empowered to take action in their own community, as also noted in previous studies [26,27,28]. We experienced that when working with this age group, a strong collaboration between children and adults is recommended. Children cannot execute all their ideas by themselves, but need the help of adults [29], i.e., the participatory group facilitators and relevant community partners. Community partners enjoyed discussing children’s ideas and working with them towards implementation. Because of the positive experience with children’s participation, community partners wanted to continue with this after the study. A recent review found that through being involved in YPAR, adults appreciated children’s abilities and valued their participation [11]. This is one of the most valued outcomes of this study, as we feel that children should not only participate in decision making during research. A precondition for—sustainable—participation in the community is training community partners to actively engage children in decision making, for example using readily available manuals on child participation [6]. In our study we trained the community partners who co-hosted the Youth Council, so they could continue facilitating children’s participation in the community.Children appreciated and enjoyed being part of action development, as it created the feeling that it was ‘their’ action. This feeling was shared by community partners who for example mentioned that the water policy was well supported at school because it was the children’s idea. Children felt the actions better-suited their interests because children had co-developed them. For example, the ‘dog-poo’ signs were appealing to children because they were drawn by children and colorful. A recent review also found that engaging youth in inquiry aided the research process, for example because youths can stimulate each other to participate in actions [11]. By developing and implementing actions together with children, ’Kids in Action’ tried to work on the level of participation of shared control and decision-making power between children and adults [14,27,28,30]. On this level children are taken seriously, they work on actions and see their own actions being implemented [18]. When children are involved in advocacy and organizing, this can lead to environmental outcomes such as changes in peer norms and program development [11]. It should be kept in mind that sharing power may not be possible for every decision [31]. To preserve scientific integrity and methodological quality, researchers need to guarantee adherence to guidelines regarding scientific integrity and methodology and in the case of our study align the developed actions with health behavior theories [19]. On the other hand, when children feel strongly about something that researchers do not recognize, children could be allowed to go through with it. Through YPAR children and researchers educate each other [28,29]. For example, with the cooking workshops, children wanted a combination of healthy and unhealthy foods, where the involved adults wanted to focus on healthy foods only. Through dialogue, children came to understand that the focus had to be on healthy foods as that was the goal of the project and children helped adults to design attractive leaflets and content of the workshops that would appeal to children, i.e., healthy meals that children enjoy. However, when children evaluated the actions, they seemed to had forgotten this process and felt they had been limited by the boundaries of healthy foods. This shows it is important to constantly reflect with the children on the goals of the study and together create a clear understanding of the responsibilities and rationale [18,28].Community partners perceived that ‘Kids in Action’ contributed to more awareness of children about healthy behavior though they doubted whether the actions had led to actual behavior change. School staff indicated that more involvement of parents might be necessary to reach behavior change, as children of this age are largely dependent on their parents in their health choices. In the present study, parents were involved in the needs assessment but they did not want to have an active role in action development. Future research should examine how parents can be motivated to actively participate in community-based research. According to all community partners the largest effect of ‘Kids in Action’ was realized on children’s empowerment. Reviews looking into outcomes of YPAR found similar results, with positive effects on agency and leadership, social, interpersonal, and cognitive skills [6,7]. It was interesting to see in the current study that children who had already participated in a YPAR group during the previous school year were more experienced in the YPAR process than children who just joined. They had already developed more critical thinking and awareness of the community and were more realistic in their ideas. Thus, including more children in the participatory process and for a longer time period—for example, by incorporating it in the school curriculum [30,32]—may lead to empowerment on a larger scale. Furthermore, to optimally develop children’s empowerment, the focus should not only be on the individual. According to empowerment theory, individual, organizational and community empowerment cannot be interpreted separately [3,23]. Therefore a systems approach, in which the system around the child is influenced would be optimal [23,28,33]. In the current study, children’s empowerment developed on an individual and community level, but less on the organizational level. A possible explanation for this is that by being part of the Action Team or Youth Council, children individually developed. Furthermore, community empowerment developed because they often collaborated with community partners who valued their opinion, also in decision making that was not related to ‘Kids in Action’. However, as schools stated from the beginning of the project that they were very busy and endured a shortage of teachers, we did not ask too much involvement from the schools throughout the project.Community partners mentioned many preconditions for a successful YPAR project, of which a close collaboration of researchers with children, KA, local government and community project group, was indicated as most important. Collaborations between academics and community organizations may provide an enabling environment for successful YPAR [34]. Crucial in ’Kids in Action’ was that the community partners were interested in child participation and understood the power dynamics between children and adults in YPAR, which helps gain support for such a study [18,35,36]. Community partners were willing to collaborate with children to develop their ideas for actions and when necessary integrate it in their organization’s policies. As mentioned before, schools were less involved during the study. A learning point was to have more open communication with schools about their role and expectations. Schools mentioned that they would have liked more updates and involvement during the project. In retrospect, we should have openly discussed their level of involvement instead of assuming that they were too busy to be involved. A precondition and also a major challenge for closely collaborating with children was to organize the meetings in such a way that children stayed interested and motivated, and maintaining a trustful relationship [36]. Tools such as icebreakers and creative assignments facilitated this, as well as having conversations unrelated to the research if children had something they needed to share [37]. We should also keep in mind to not ask too much from children, which some children experienced in the Youth Council. Future studies could create the research agenda and planning of the YPAR meetings together with children. Another precondition for YPAR—as experienced in all YPAR—is a considerable time investment of the principal researcher, the children and community partners, to be able to create close ties, hold regular participatory meetings, and co-develop and implement actions [35]. It also required high flexibility from researchers and the community project group, as YPAR remains an iterative approach dependent on many uncontrollable factors and school schedules [34,35].This study includes several strengths and limitations. Even though we included the views of different community partners, we only evaluated the study with those who were closely involved, which could have biased the results. Also, we did not include children in the initial design during the grant application phase. This could have benefited mutual understanding between researchers and children from the beginning, stating boundaries and discussing where concessions can be made [7,38]. However, applying for funding is a lengthy and uncertain process. Recruiting schools for a project planned in future school years that might not even get funded is challenging. Furthermore, we did not conduct the process evaluation with children as partners, because it did not fit the timeline of the study and would be an additional task and time investment for the children. Future YPAR studies may explore ways to evaluate the entire research process together with children as partners. This may provide additional relevant insights to strengthen YPAR studies. A limitation of the ‘Kids in Action’ study is the low involvement of parents and as a result we also did not include them in this process evaluation. For future studies with more resources and personnel, it would be valuable to also include parents. Furthermore, not all focus group interviews had the same depth. In some groups not all children participated fully, for example because they were tired or distracted, which negatively influenced their input in the assignments. A last limitation is that data was not independently coded by two researchers due to time constraints. The coding schemes were however checked by a second researcher, who was also consulted in case of uncertainties. A strength of this study is that through our different types of data and coding strategies, we managed to give value to much of the participant’s input, opinions and feelings. Second, this study provides much information about how to collaborate with children and community partners in YPAR, as all who closely participated in ‘Kids in Action’ were included in this study and shared their experiences. Third, the interview and focus group guides were based on the RE-AIM framework and empowerment theory, which gave structure to this process evaluation. Another strength is that focus groups were organized at the beginning and end of two school years, allowing to evaluate changes in children’s feelings of empowerment and experiences with YPAR. Moreover, in the first year, both children who did, and some children who did not participate in a YPAR group joined the focus groups. As empowerment was evaluated on different levels, an added strength is that it gives more insight into how the influence of YPAR on children’s empowerment was constructed.In the ‘Kids in Action’ project, actions to promote physical activity and healthy dietary behavior were developed, implemented and evaluated together with children from a low socioeconomic community. The project was well adopted in the community, which can be ascribed to the strong collaboration between researchers and community partners and the willingness of community partners to participate with children in action development. This led to co-created actions that suited children’s needs and interests and where possible were embedded in schools or other community partners. Maintenance of child participation and the developed actions after the study was strived for by community partners, but considered a challenge because of finances and politics. Children liked seeing the results of their weekly participation, and being involved in YPAR improved their empowerment. A recommendation for future research is to integrate child participation in policies of community organizations and schools, in order to reach more children. Closely collaborating with schools and parents can further benefit support for the co-created actions and increase the effects on health behaviors.M.A., M.C. and T.A. designed the project. M.A. coordinated and performed the data collection and analyzed the data, with assistance of T.A. when necessary. M.A. wrote the manuscript and T.A. and M.C. provided critical input and feedback. All authors read and approved the final manuscript.This study has been funded by FNO (grant number 101569). The authors want to thank all participating children and community partners for their effort and contributions to this study.The authors declare no conflicts of interest.Composition of Youth-led Participatory Action Research (YPAR) groups.Overview of goals, initial ideas, and the developed actions of the Action Teams (adapted from [19]).KA: Kids Aktief.Examples of questions asked during the interviews with professionals.Codes used for data related to empowerment [3,23].Number of children in the focus groups.N.A.: not applicable.Occupation and year since involvement of community partners interviewed.Codes used for data related to RE-AIM and the YPAR process.1 Related themes in results: A: Adoption; C: Collaboration; E: Effectiveness; G: General; I: Implementation; M: Maintenance; P: Becoming part of the project; R: Reach.Attributes of ‘Kids in Action’ that community partners valued most.

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+Background: Hallux valgus (HV) has been previously associated with psychological disorders. Thus, the purposes of this study were to associate kinesiophobia and pain intensity with HV deformity degrees, as well as predict kinesiophobia and pain intensity based on HV deformity and demographic features. Methods: A cross-sectional study was carried out recruiting 100 subjects, who were divided into HV deformity degrees, such as I-no HV (n = 25), II-mild (n = 25), III-moderate (n = 25), and IV-severe (n = 25) HV. Kinesiophobia total and domains (activity avoidance and harm) scores and levels were self-reported by the Tampa Scale of Kinesiophobia (TSK-11). Pain intensity was self-reported by the numeric rating scale (NRS). Results: Statistically significant differences (p < 0.01; η2 = 0.132–0.850) were shown for between-groups comparison of kinesiophobia total and domain scores (activity avoidance and harm) and levels, as well as pain intensity among HV deformity degrees. Post hoc comparisons showed statistically significant differences with a large effect size (p < 0.05; d = 0.85–4.41), showing higher kinesiophobia symptoms and levels and pain intensity associated with greater HV deformity degrees, especially for III-moderate and/or IV-severe HV deformity degrees versus I-no HV and/or II-mild deformity degrees. Both statistically significant prediction models (p < 0.05) for kinesiophobia (R2 = 0.300) and pain intensity (R2 = 0.815) were predicted by greater HV deformity degree and age. Conclusions: Greater kinesiophobia symptoms and levels and pain were associated with higher HV deformity degrees, especially severe and/or moderate HV with respect to no and/or mild HV. The kinesiophobia and pain intensity were predicted by greater HV deformity degree and age.The affectation of the toe body region may comprise up to 14% of the non-traumatic primary care consultations of the foot and ankle, being hallux valgus (HV) considered as one of the 10 most commonly documented non-traumatic conditions [1]. This condition may reach a prevalence of up to 23% in adults, showing an increase in female sex or higher age distribution [2]. HV may be defined as a complex deformity of the 1st metatarsophalangeal joint composed of great toe lateral drift and linked to joint subluxation [3]. Indeed, HV may impair quality of life related to foot health, increase depression, and alter muscle or connective tissue morphology of the plantar region, which seems to be linked to its degree of deformity [4,5,6,7].Several psychological disorders, such as depression or sociability and vigor linked to general health-related quality of life alterations, have been associated with musculoskeletal conditions, which may increase with greater age ranges [8,9,10,11,12,13]. In addition, musculoskeletal disorders of the lower limbs may alter body stability, showing a greater instability in older adults [14,15,16]. Combining both factors, kinesiophobia and pain intensity seem to play a key role in musculoskeletal disorders prognosis [17,18,19]. Among these conditions, patellofemoral pain has been linked to greater higher kinesiophobia levels [20]. Currently, there is a lack of research studies detailing kinesiophobia and pain intensity in subjects suffering from HV deformity. Pain and kinesiophobia, defined as fear of movement under a painful condition [21,22], could be linked to a greater HV deformity degree as the higher HV deformity has been related to a worse foot health-related quality of life, greater depression, and presence of foot posture, pressure patterns, and function alterations [4,5,6,7,23,24].Greater HV deformity degree has shown higher radiographic first metatarsophalangeal joint osteoarthritis severity in conjunction with physical and psychological conditions [4,5,6,7,23,24,25]. Thus, the purpose of this study was to find the association between kinesiophobia and pain intensity with HV deformity degrees. In addition, the secondary aim was to predict kinesiophobia and pain intensity based on HV deformity and demographic features. We hypothesized that higher kinesiophobia and pain intensity could be shown and predicted by a greater HV deformity degree.A cross-sectional study was performed according to the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) criteria [26]. Thus, kinesiophobia and pain intensity were compared under different HV deformity degrees. Furthermore, the ethics committee of Extremadura University (code: 175/2019) approved this research, and all subjects signed the informed consent form before the beginning of the study. Finally, the Helsinki declaration and all human experimentation rules were respected [27].Kinesiophobia score was used as the main outcome measurement to carry out the sample size calculation because prior lower limb musculoskeletal conditions were linked to higher kinesiophobia symptoms [20]. Kinesiophobia total score assessed with the Spanish validated version of the Tampa Scale of Kinesiophobia–11 items (TSK-11) [21,22] of a pilot study (n = 40 subjects) with 4 groups of HV deformity degree (n; TSK-11 mean ± SD), divided into I–no HV (n = 10 participants; 21.70 ± 5.41 points), II–mild (n = 10; 20.70 ± 4.62 points), III–moderate (n = 10; 22.60 ± 3.83 points), and IV–severe (n = 10; 24.80 ± 4.18 points) HV deformity degree, was used for the sample size calculation by the one-way, omnibus, and fixed-effects analysis of variance (ANOVA) F test using G*Power 3.1.9.2 software version. Indeed, a partial Eta-squared (η2) of 0.109, an effect size of 0.349, an α error probability of 0.05, a number of 4 groups, and a power (1-β error probability) of 0.80 were used for this sample size calculation procedure. Thus, a total sample size of 96 subjects, 24 for each group, was calculated with an actual power of 0.813. Finally, a total sample size of 100 subjects, 25 for each group, was included in the present study.A total sample of 100 subjects with different HV deformity degrees was recruited by a consecutive convenience sampling method in an outpatient clinic from March to November 2019 [4,5,6,7]. Inclusion criteria comprised subjects older than 18 years old, being healthy subjects for the control group classified as I degree–no HV presence (n = 25), as well as patients with HV deformity for cases groups, such as II degree–mild HV (n = 25), III degree–moderate HV (n = 25), and IV degree–severe HV (n = 25) [28,29].Systemic diseases, neurological conditions, arthritis, neoplasm, autoimmune pathology, vascular alterations, neuropathic disorders or radiculopathies, sprains, fractures, tendinopathies, surgeries, presence of dysmetria with length difference greater than 1 cm between both lower extremities, mental disorders, or cognitive conditions were considered as exclusion criteria according to the medical record [7,30].A specialized podiatrist carried out the HV deformity degree diagnosis by the Manchester Scale [28]. This tool might be considered as a non-invasive technique in order to measure the HV deformity degree using a standardized photograph set, divided into I degree (no HV), II degree (mild HV), III degree (moderate HV), and IV degree (severe HV). This scale showed an excellent inter-examiner repeatability (κ = 0.86) [29]. Also, excellent inter-examiner reliability and validity were shown for the HV angle between photographic measures and radiographs. Intraclass correlation coefficients (ICCs > 0.96) and the Pearson’s correlation coefficient (r = 0.96) were categorized as excellent. Despite this method was recommended in order to avoid the cost and radiation exposure secondary to radiographs, foot radiographs might be considered as the current standard in clinical practice, and thus HV angle clinical measurements have been recommended if it is not possible or necessary to perform radiographs [29].Demographic data comprised age (years), sex (female or male), body mass index (kg/cm2) [31], height (cm), weight (kg), and pain chronicity, measured as duration in months with painful HV [7,30].Kinesiophobia total score was considered as the main outcome measurement and evaluated with the Spanish validated version of the Tampa Scale of Kinesiophobia–11 items (TSK-11) [21,22]. Secondary outcome measures were activity avoidance and harm domains scores of kinesiophobia, as well as fear of movement or kinesiophobia levels categorized by the TSK-11 score [21,22], and the pain intensity score measured by the numeric rating scale (NRS) [32,33]. According to these scales, both tools were self-reported by the study’s subjects.The Spanish validated version of the TSK-11 was self-reported by all study’s subjects in order to detail kinesiophobia symptoms total scores, activity avoidance and harm domains scores of kinesiophobia, and levels fear of movement or kinesiophobia [21,22]. Kinesiophobia was considered as an adaptive response to the threat, which might consequently generate maladaptive or avoidance behaviors with an increase of fear and/or pain as well as activities limitation and/or fear of movement [34,35,36]. Future disability of a musculoskeletal condition might be predicted by fear or movement or kinesiophobia [34]. This scale was composed of total kinesiophobia symptoms score and two domains, including activity avoidance and harm under kinesiophobia. This scale was scored using 4 points Likert-type scale, indicating higher scores as an increase of fear of pain, movement, or damage. In addition, TSK-11 total scores were categorized into kinesiophobia levels of fear of movement, including no fear of movement (0–17 points), slight fear of movement (18–24 points), moderate fear of movement (25–31 points), severe fear of movement (32–38 points), and maximum fear of movement (39–44 points) [21,22]. Adequate psychometric properties were reported for this scale, showing an internal consistency with Cronbach’s α of 0.78, test-retest with ICC of 0.82, standard error of measurement with SEM of 3.16, responsiveness of −1.19, minimum clinical important difference with MCID of 4.80, and minimum detectable change with MDC of 5.60 [21,22,37,38,39].Pain intensity was measured by the NRS. This tool showed 11 points ranged from 0 (no pain) to 10 (highest pain intensity) points. Subjects were asked to mark the subjective pain intensity of the painful HV (Hallux valgus) by a finger on the scale composed of a graphic representation with 11 spaces. This scale was stated as a valid and reliable scale to evaluate subjective pain intensity in adults and older adults [32,33]. High convergent validity (0.79–0.95) was shown with respect to the VAS (Visual Analogue Scale) [40]. The MDC and MCID were set at 2 points for lower limb musculoskeletal conditions [41,42,43].The software version 24th of the Statistical Package for Social Sciences (from IBM Corp; Armonk, NY, USA) was utilized to carry out all data analyses by an α error of 0.05, a p-value < 0.05 as statistically significant, and a 95% confidence interval (CI).First, quantitative data analyses were performed by the Shapiro–Wilk test to determine normality distributions. Second, all data were described by the mean ± standard deviation (SD). Third, one-way analysis of variance completed with Bonferroni’s correction post hoc analyses was used to assess between-group differences for parametric data. Fourth, Kruskal–Wallis test completed with Bonferroni’s correction post hoc analyses were used to assess between-groups differences for non-parametric data. For outcome measurements, effect size was calculated by Eta-squared (η2) coefficients for comparisons among all groups, as well as Cohen’s d coefficients for comparisons between paired groups and categorized into very small effect size (d < 0.20), small effect size (d = 0.20–0.49), medium effect size (d = 0.50–0.79), and large effect size (d > 0.8) [44,45]. Finally, categorical data were described as frequency (n) and percentage (%). In addition, Chi-square tests were applied to assess differences among all groups.Furthermore, multivariate predictive analyses were performed by means of two linear regression models. Both models were carried out by the stepwise selection method; as well as R2 coefficients were determined to show the quality of adjustment [46]. The 1st linear regression model included demographic data, pain intensity (NRS), chronicity, and HV deformity degree as independent variables, as well as kinesiophobia total score (TSK-11) as the dependent variable. The 2nd linear regression model included demographic data, kinesiophobia total score, levels of fear of movement of kinesiophobia, activity avoidance, and harm domains of kinesiophobia (TSK-11), and HV deformity degree as independent variables, as well as pain intensity (NRS) as the dependent variable. F probability pre-established parameters ranged from pin = 0.05 to pout = 0.10, and p-values < 0.05 for statistical significance with a 95% CI were considered for these analyses.Statistically significant differences (p < 0.05) were shown for demographic data, except for weight (p = 0.608), showing that a higher HV deformity degree was associated with greater age, height, body mass index (BMI), and chronicity, as well as female sex (Table 1).Statistically significant differences (p < 0.001; η2 = 0.203) were shown for between-groups comparison of kinesiophobia total scores among HV deformity degrees by the one-way ANOVA test. Post hoc comparisons showed statistically significant differences with a large effect size (p < 0.05; d = 0.85–1.44), showing higher kinesiophobia symptoms for III-moderate and IV-severe HV deformity degrees with respect to I-no HV deformity degree, as well as for IV-severe HV deformity degree versus II-mild HV deformity degree. The rest of the post hoc comparisons did not show statistically significant differences (p < 0.05) (Table 2).Statistically significant differences (p < 0.001; η2 = 0.168) were shown for between-groups comparison for the activity avoidance domain of kinesiophobia among HV deformity degrees by the Kruskal–Wallis test. Post hoc comparisons showed statistically significant differences with a large effect size (p < 0.01; d = 0.86–1.34), showing higher activity avoidance kinesiophobia symptoms for IV-severe HV deformity degree with respect to I-no HV and II-mild HV deformity degrees. The rest of the post hoc comparisons did not show statistically significant differences (p < 0.05) (Table 2).Statistically significant differences (p = 0.002; η2 = 0.132) were shown for between-groups comparison for the harm domain of kinesiophobia among HV deformity degrees by the Kruskal–Wallis test. Post hoc comparisons showed statistically significant differences with a large effect size (p = 0.001; d = 1.07), showing higher harm kinesiophobia symptoms for IV-severe HV deformity degree with respect to I-no HV deformity degree. The rest of the post hoc comparisons did not show statistically significant differences (p < 0.05) (Table 2).Statistically significant differences (p < 0.001; η2 = 0.850) were shown for between-groups comparison for the pain intensity among HV deformity degrees by the Kruskal–Wallis test. Post hoc comparisons showed statistically significant differences with a large effect size (p < 0.001; d = 3.31–4.41), showing higher pain intensity for III-moderate and IV-severe HV deformity degree with respect to I-no HV and II-mild HV deformity degree. The rest of the post hoc comparisons did not show statistically significant differences (p < 0.05) (Table 2).Statistically significant differences (p = 0.007; χ2 = 22.556) were shown for between-groups comparison for the kinesiophobia levels of fear of movement among HV deformity degrees by the Chi-squared test, showing higher kinesiophobia levels with greater HV deformity degree, especially for moderate kinesiophobia level (Figure 1).Kinesiophobia total score (TSK-11) showed one statistically significant prediction model (R2 = 0.300) based on age (R2 = 0.271; β = +0.101; F[1,98] = 35.978; P < 0.001) and HV deformity degrees (R2 = 0.029; β = +1.050; F[1,97] = 4.033; P = 0.047), predicting higher kinesiophobia total scores based on greater age and HV deformity degree. Therefore, this prediction model excluded the rest of independent variables (P > 0.05) as the kinesiophobia total score (dependent variable) was not predicted by sex, height, weight, BMI, chronicity, and pain intensity (independent variables) according to the pre-established parameters for F probability (Table 3).Pain intensity (NRS) showed one statistically significant prediction model (R2 = 0.815) based on HV deformity degrees (R2 = 0.776; β = +0.276; F[1,98] = 339.076; P < 0.001) and age (R2 = 0.040; β = +1.050; F[1,97] = 20.782; P < 0.001), predicting higher pain intensity based on greater HV deformity degree and age. Therefore, this prediction model excluded the rest of independent variables (P > 0.05) as the pain intensity (dependent variable) was not predicted by sex, height, weight, BMI, kinesiophobia total scores, kinesiophobia activity avoidance and harm domain scores, and kinesiophobia levels of fear of movement (TSK-11) according to the pre-established parameters for F probability (Table 4).Despite higher HV deformity degree has been previously associated with psychological disorders [4,5,47], this study might be considered as the first cross-sectional study detailing greater kinesiophobia symptoms, total scores as activity avoidance and harm domains scores, as well as pain intensity associated with higher HV degree deformity, especially for severe and/or moderate HV deformity degrees with respect to non-presence of HV and/or mild HV deformity degrees. Indeed, moderate kinesiophobia level deformity showed a clear increase according to greater HV deformity degrees. Thus, pain and fear of movement under HV condition might be linked to III and IV deformity degrees compared to I and II deformity degrees according to prior studies associating greater HV deformity with worse quality of life related to foot health, higher depression, as well as foot posture, pressure patterns, and function alterations [4,5,6,7,23,24]. Our findings were in line with prior research studies detailing kinesiophobia and pain in different musculoskeletal conditions, such as patellofemoral pain [20], temporomandibular conditions [48], chronic fatigue syndrome and/or fibromyalgia [49], whiplash-associated conditions and/or low back pain [50], chronic mechanical neck pain [51], or migraine [52].In addition, our study showed that age and the HV deformity degree were shown as predictors for kinesiophobia symptoms and pain intensity. These findings were in accordance with prior studies reporting that psychological disorders were linked to musculoskeletal conditions, increasing this association with greater age distribution [8,9,10,11,12,13]. In addition, greater instability was shown in older adults under musculoskeletal disorders [14,15,16]. Finally, higher HV deformity was associated with worse physical and psychological factors [4,5,6,7,23,24].Future studies should propose interventions in order to reduce kinesiophobia and pain intensity in patients with HV, such as myofascial pain interventions [53,54], neural mobilization techniques [55], or surgical procedures [47]. In addition, other outcome measurements should be evaluated in order to determine the influence of HV mechanical soft tissue properties on pain and kinesiophobia, such as myofascial trigger points evaluation [56], sonoelastography [57], pressure pain threshold [58], or thermography [59]. Finally and most importantly, an x-ray should be included in future studies as the gold stand, as well as ultrasound imaging could be used in advance to decline other possible pathologies [29].The following limitations could be acknowledged in this study. Firstly, socio-economic, civil, or working status should be considered for future studies. In spite of the pain intensity of HV was measured by the NRS [32,33], pain location, distribution, or type (neurological or musculoskeletal) were not collected. Second, despite the presented prediction models determined the influence of demographic data on our findings, future studies should detail the influence of age ranges on kinesiophobia and pain intensity according to our multivariate regression analyses. Thirdly, pregnant women could influence the psychological status and should be considered in future research studies [60]. Finally, despite exclusion criteria were considered according to the medical record, imaging examination was not performed (i.e., ultrasound and/or x-ray) to rollout other underlying pathologies (i.e., Morton neuroma, stress fracture, metatarsal bursitis, and others), which should be included in future studies. In addition, foot x-ray might provide additional information about the other metatarsal angles, sesamoid displacement, or underlying pathologies [29].Greater kinesiophobia symptoms and levels and pain were associated with higher HV deformity degrees, especially severe and/or moderate HV with respect to no and/or mild HV. The kinesiophobia and pain intensity were predicted by greater HV deformity degree and age.Conceptualization, R.B.-d.-B.-V., M.E.L.-I., D.L.-L., C.C.-L., and V.M.-P.; Data curation, P.P.-L. and C.C.-L.; Formal analysis, R.B.-d.-B.-V., M.E.L.-I., D.R.-S., and C.C.-L.; Investigation, P.P.-L. and V.M.-P.; Methodology, P.P.-L., R.B.-d.-B.-V., M.E.L.-I., D.L.-L., D.R.-S., C.R.-M., C.C.-L., and V.M.-P.; Supervision, D.L.-L. and C.R.-M.; Writing—original draft, D.L.-L. and C.C.-L.; Writing—review and editing, P.P.-L., R.B.-d.-B.-V., M.E.L.-I., D.R.-S., C.R.-M., C.C.-L., and V.M.-P. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors declare no conflict of interest.Bar graph showing the kinesiophobia levels of fear of movement (TSK-11), such as no fear (0–17 points), slight (18–24 points), moderate (25–31 points), severe (32–8 points), and maximum (39–4 points) kinesiophobia levels among different HV deformity degrees. Abbreviations: HV, hallux valgus; TSK-11, Tampa Scale of Kinesiophobia–11 items.Demographic data among different HV deformity degrees.Abbreviations: BMI: body mass index; CI: confidence interval; HV: hallux valgus; SD: standard deviation. * Mean ± SD and one-way analysis of variance (ANOVA) were used. † Mean ± SD and the Kruskal–Wallis test were used. ‡ Frequency, percentage (%), and the Chi-squared test (χ2) were utilized. In all analyses, p < 0.05 (with a 95% CI) was considered statistically significant.Comparisons of outcome measurement scores among different HV deformity degrees.(d = 0.35)(d = 0.85)<0.001 (d = 1.44)0.928 (d = 0.38)(d = 0.89)0.353 (d = 0.60)(d = 0.23)0.127 (d = 0.87)(d = 1.34)0.392 (d = 0.39)(d = 0.86)0.851 (d = 0.48)0.599 (d = 0.46)0.205 (d = 0.62)(d = 1.07)(d = 0.16)0.177 (d = 0.60)0.530 (d = 0.43)0.420 (d = N/A)<0.001 (d = N/A)<0.001 (d = N/A)<0.001(d = 3.31)<0.001 (d = 4.41)1.000 (d = 0.55)Abbreviations: CI, confidence interval; d, Cohen d coefficient; HV, hallux valgus; η2, Eta-squared coefficient; N/A, not applicable; NRS, numeric rating scale; SD, standard deviation; TSK-11, Tampa Scale of Kinesiophobia–11 items. * Mean ± SD and one-way analysis of variance (ANOVA) completed with Bonferroni’s correction were used. † Mean ± SD and Kruskal-–allis test completed with Bonferroni’s correction were used. In all analyses, p < 0.05 (with a 95% CI) was considered statistically significant.Linear regression model for the kinesiophobia total score multivariate among HV deformity degrees.Abbreviations: HV, hallux valgus; TSK-11, Tampa Scale of Kinesiophobia–11 items. * Multiplay: HV deformity degrees (I degree (no HV) = 1; II degree (mild HV) = 2; III degree (moderate HV) = 3; IV degree (severe HV) = 4). † p-value < 0.05 for a 95% confidence interval was shown, ‡ p-value < 0.001 for a 95% confidence interval was shown.Linear regression model for the pain intensity multivariate among HV deformity degrees.Abbreviations: HV: hallux valgus; NRS: numeric rating scale. * Multiplay: HV deformity degrees (I degree (no HV) = 1; II degree (mild HV) = 2; III degree (moderate HV) = 3; IV degree (severe HV) = 4). ‡ p-value < 0.001 for a 95% confidence interval was shown.

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+This aim of this paper is to determine the relationship between the consumption of tobacco, cannabis, and alcohol (including drunkenness and binge drinking consumption patterns) in the previous 30 days by Spanish adolescents and the information that is available to adolescents on drug consumption. This cross-sectional study employed data from the Survey on Drug Use in Secondary Education in Spain (ESTUDES 2016), which was conducted on students aged 14 to 18 (n = 35,369). Contingency tables, mean comparison tests, and logistic regression analyses were conducted and prevalence ratios (PR) were obtained. The results show that the probability that an adolescent will smoke tobacco is associated with whether their mother and/or father smoke (PR: 1.30), whether some of their friends smoke (PR: 14.23), whether the majority of their friends smoke (PR: 94.05) and how well informed they perceive themselves to be (PR: 1.30). Cannabis use is mainly associated with whether most of their friends also use cannabis (PR: 93.05) and whether they are sufficiently informed regarding this consumption (PR: 1.59). Alcohol consumption is associated with whether their mothers drink regularly (PR: 1.21), whether most of their friends drink (PR: 37.29), and whether they are well informed (PR: 1.28). Getting drunk and binge drinking are associated with whether their friends have these behaviors (PR: 44.81 and 7.36, respectively) and whether they are sufficiently informed (PR: 1.23 for both behaviors). In conclusion, the consumption of these substances is more frequent among Spanish adolescents who believe that they are better informed and whose friends have similar patterns of consumption.The consumption of alcohol and other substances by adolescents is a public health issue in Spain. This is despite the fact that the ESTUDES survey (1994–2016) showed a decrease in the consumption of various substances. Data from the historical series of the survey show, for example, that the consumption of alcohol (always in the previous 30 days) dropped from 75.1% to 67% among Spanish teenagers between 1994 and 2016, while the consumption of cigarettes decreased from 31.1% to 23%. In the same period, the consumption of cannabis dropped from its historical maximum of 25.1% in 1994 to 13.1% in 2016. On the other hand, the use of other substances that, in the past, were consumed less, such as cocaine, has increased since 2010. For example, according to the last two surveys (that were conducted in 2014 and 2016), the prevalence of consumption of the following illegal substances increased slightly during those years: hypnosedatives (from 10.8% to 11.6%); new substances (from 2.8% to 3.1%); ecstasy (from 0.9% to 1.6%); amphetamines (from 0.9% to 1.2%); methamphetamine (from 0.5% to 1.0%); and, spice (from 0.6% to 0.7%). It is also important to note that the consumption of all illegal drugs is more widespread among men than it is among women, whereas the consumption of legal drugs, such as tobacco, alcohol, and hypnosedatives (with or without prescription), is more widespread among women.Some studies report that alcohol consumption by female adolescents in Spain significantly increased between 2006 and 2014 and that marijuana and alcohol consumption by friends were associated factors in this increase. Moreover, alcohol consumption increased with age and was more frequent at weekends than on school days. The variables that were associated with a greater probability of alcohol consumption were tobacco, marijuana (OR = 2.37; 95% CI: 2.08–2.72), and alcohol consumption (OR = 7.24; 95% CI: 6.42–8.16) by friends [1].That the consumption of alcohol, cigarettes and cannabis has not decreased still further might be due to the persistently low perception of their risk to people’s health (especially in regard to alcohol [2]), an issue that is related to perceived invulnerability [3,4,5,6]. The information paradox suggests that information might be less important than one believes when it comes to making decisions [7]. This could explain why Spanish adolescents who perceive themselves to be better informed have a higher prevalence of consuming these substances than those who believe that they are badly informed or only partly informed. Methods for tackling and preventing this problem of substance use have mainly focused on transmitting information from expert systems to younger members of the population. Some authors [8] distinguish between prescriptive and participatory models when it comes to introducing public policies that are aimed at preventing consumption. According to Romaní, the predominant model is the prescriptive one, even though it does not enable young people to participate very much in the design of such policies. However, other authors [9] stress the importance of allowing young people to become actively involved in discussions of the advantages and disadvantages of drug use (a ‘pros and cons’ exercise) and negotiate specific and realistic goals for reducing or eliminating their drug consumption. A review of 33 studies published between January 2010 and December 2014 identified several categories of intervention and prevention programs. Only four of these studies took into account a profile of their subjects before implementing their prevention programs. The review concluded that consumption patterns among adolescents should be taken into account when addressing primary prevention [10].There is evidence that no major transition towards more evidence-based interventions in prevention strategies has taken place in Europe [11]. The predominant approach in Spanish schools is universal prevention that is based on the provision of information. This approach includes specific days on which substance use is discussed and that involve the participation of experts, such as social workers, health professionals, and the police. It means that more systematized programs that incorporate a study plan are secondary, as are prevention programs that are aimed at groups at risk of consumption or that focus on so-called Brief Interventions [12] for users with mild-to-moderate consumption problems [13]. In Bukhart’s study of environmental prevention, it was found that adolescents begin to consume these substances influenced by environmental factors, mainly peer-group pressure and reference models [11]. Therefore, alcohol abuse in adolescents might be conditioned by family structure and the role of the adolescent’s father or mother. Specifically, perceived family affection acts as a protective factor against both alcohol consumption and peer group pressure for such consumption [14] and it provides a shared image between parents and adolescents regarding how alcohol should be consumed [15].This might partly explain the higher consumption of these substances among adolescents who believe they are perfectly or sufficiently informed.Some studies have shown how predisposition to consumption is stronger among young people, whose reference models are dependent consumers [16]. It has also been shown that the prevalence of alcohol and tobacco consumption is greater among adolescents whose friends have favorable attitudes to the consumption of those substances [17]. Other studies associate a higher consumption of alcohol among adolescents whose fathers, siblings, and especially their friends or best friends often drink [18,19,20]. The literature shows strong concordance between the poly-consumption (the consumption of several substances) of young people and that of their close references, i.e., if an adolescent’s reference is a poly-consumer, it is more likely that he or she will also be one [21]. Some studies stress the need to continue investigating attachment, especially among equals, as a risk and/or protective factor against drug use in adolescence [22]. With regard to poly-consumption, some authors believe that future investigations and interventions should consider social support as a vulnerability marker for the detrimental consequences of substance use and the risk of consumption disorders [23]. Some studies show that, among young Spanish adults (15–34 years old), the factors that are associated with the use of CBP (cannabis and other cannabis-based products), together with the abuse of TSSp (tranquilizers, sedatives, and sleeping pills), were a lack of education (OR 2.34), the consumption of alcohol (OR 7.2), tobacco (OR 6.3) and other illicit psychoactive drugs (OR 6.5), perceived non-health risk for the consumption of CBP and TSSp (OR 3.27), and perceived availability of CBP (OR 2.96) [24].In this paper, we take these considerations into account to determine whether significant differences exist in the prevalence of consumption among adolescents who report being better or worse informed regarding their consumption of these substances.This paper studies the extent to which teenagers perceive they are informed about substance use and the prevalence of substance consumption. This non-experimental study is descriptive, correlational, and cross-disciplinary, and it is based on a probabilistic sample of students in Spain aged between 14 and 18 (from the ESTUDES survey). Our main objectives are to describe the frequency and distribution of adolescent substance use and establish the possible relationship between the prevalence of consumption of various substances and the determinants of substance use (e.g., sex, age, perceived level of information, consumption by friends, etc.) in an adolescent population. The first sample units were secondary schools. The final observation units were students aged between 14 and 18 who were present at the time that the survey was conducted. The exclusion criteria were student ages over 18 and under 14. The field work was conducted throughout Spain between November 2016 and March 2017. Our main question was whether a relationship exists between being better or more informed regarding substance use and the prevalence of consumption. Our initial hypothesis was that adolescents’ self-perception regarding whether they are informed about substance use does not necessarily imply that their prevalence of consumption is lower. Confirming this hypothesis could open up new lines of research into, for example, the role that is played by the adolescents’ environment in their substance consumption (especially whether their friends are consumers). This quantitative cross-sectional study used data from the Survey on Drug Use in Spanish Secondary Education (ESTUDES 2016), which was conducted biannually throughout Spain, starting in 1994, as part of the National Plan on Drugs that was developed by the Spanish government’s Ministry of Health, Social Services and Equality. The Survey was funded and promoted by the Spanish Government Delegation for the National Drugs Plan (DGPNSD). Collaborating on the Survey were the governments of the Spanish autonomous communities (Autonomous Community Plans on Drugs and Departments of Education) and the Spanish Ministry of Education, Culture, and Sport. Consent to participate was established in two phases. First, the Departments of Education of the Spanish autonomous communities asked schools to participate in the survey. The schools that were selected then sent a letter to the parents or legal guardians of the adolescents asking for their permission to participate in the survey. This letter explained the survey’s objectives and schedule and stressed the absolute anonymity of the data collection and treatment procedures. Neither the schools nor the promoters of the survey were permitted to know who responded to the survey. After the schools had been selected, survey administrators were sent by the Spanish Observatory on Drugs and Addictions (OEDA) of the Government Delegation for the National Drugs Plan (DGPNSD) to meet with the schools’ principals to randomly select which classes would participate in the survey and establish how to collect the information. All students in the chosen classes completed a standardized, anonymous, and ‘self-administered’ questionnaire while using paper and pencil during their normal class time (45–60 min.). The students’ normal classroom teachers were advised not to be present during the survey so as not to compromise the students’ confidence in the anonymity of their responses. If the teachers were present, they were asked not to walk around the room, explain any survey content, or address the students while they were completing their questionnaire. OEDA survey administrators also ensured that the questionnaires were individually completed. After completing their questionnaires, the students inserted them into blank envelopes, which were then collected by the OEDA staff. The universe comprised students that were aged between 14 and 18 who were enrolled at schools or colleges. Sampling was conducted by cluster in two stages: in the first stage, 863 schools were randomly selected; in the second stage, 1726 classes were randomly selected from these schools and the questionnaire was administered to all students in those classes. The final sample comprised 35,370 teenagers. The maximum sample error for a confidence level of 95.5% and p = q = 0.5 was 0.5% for these Spanish 14–18-year-olds. The sample was weighted by the Spanish autonomous community, the public or private nature of the school, and the type of studies that they offered in order to adapt the proportionality of the sample to the universe (Table 1).From the initial selection of schools, 91.4% participated in the survey. The remaining 8.6% were replaced, mainly because they declined to collaborate or because they had a high percentage of students aged over 18. The number students present in the classrooms when the survey was administered was 36,371. In the various phases of the process, 1002 questionnaires had to be excluded, either because the respondents’ ages were not appropriate for the study or because the answers were either blank or lacked seriousness. Finally, the total number of questionnaires that were valid for the study was 35,370. The student response rate was 99.78% from the number of questionnaires that were collected and the number excluded for the reasons we have identified. Our statistical model for answering the main question and testing our hypothesis was as follows. At a first descriptive stage, we calculated the prevalence of adolescent substance use by age and sex and the percentages of adolescents who felt that they were well or poorly informed regarding substance use (see the Variables section for an explanation of the question to which the adolescents responded). Additionally, at this stage, we analyzed the adolescents’ responses to a question on the consequences of consumption in several situations. At the second stage of analysis, we used a chi-square test (in which age and sex were controlled) to calculate the possible associations between the prevalence of consumption and whether the adolescents felt they were well or poorly informed. At the third stage, we formulated logistic regression models to calculate the probabilities of consumption by considering variables, such as information and consumption in the adolescents’ environment (i.e., their father, mother, and friends).Chi-square tests (χ2) were conducted to determine the associations between, on the one hand, the consumption of alcohol (including the getting drunk and binge drinking aspects [25]), cigarettes, and hashish/cannabis, and, on the other, the subject’s perception of the information that they had available on drug use, their gender and age, the consumption of these substances by their mothers, fathers and friends, and their perception of the effects of their consumption. At this level of analysis, it was interesting to observe statistically significant relationships (p < 0.05) between categorical variables, particularly if the prevalence of consumption showed some kind of pattern regarding the perception of being better/worst informed, and if this relationship was maintained once sex and age were controlled for. For age and consumption, we used the comparison of means (t-test) for independent groups, while we used Cohen’s d for effect sizes [26,27,28]. Finally, we constructed separate logistic regression models for alcohol consumption, getting drunk, binge drinking (three models), tobacco consumption, and cannabis consumption (two models). The logistic models for alcohol consumption included the variables Mother regularly drinks, Father regularly drinks, some friends drink, and Most friends drink, as well as the variable on whether the adolescents perceived themselves to be well or poorly informed. The logistic models on tobacco and cannabis consumption also included the predictive variables Mother smokes (tobacco), Father smokes (tobacco), Some friends smoke (tobacco), and Most friends smoke (tobacco), as well as the variable on whether the adolescents perceived themselves to be well or poorly informed. The questionnaire includes a self-perception variable on how well-informed adolescents perceive themselves to be regarding substance use. This question is as follows: Do you feel sufficiently informed about the drugs issue? There were four response categories for this question: Yes, perfectly; Yes, sufficiently; Only partly; and, No, poorly. For the purposes of this article, the categories “Yes, perfectly” and “Yes, sufficiently” were combined to produce the response I believe I am sufficiently or perfectly informed. Similarly, the categories Only partly and No, poorly were combined to produce the response I believe I am partly or badly informed. In this way, the variable on the adolescents’ perception regarding how well-informed they are about substance consumption became a dichotomous variable.As well as this self-perception variable on how well-informed they feel about substance use, the adolescents were asked to respond to the following: “We would now like to know your opinion regarding the problems (health-related or otherwise) involved in engaging in the following behaviors: (a) smoking a packet of cigarettes every day; (b) smoking 1–5 cigarettes a day; (c) smoking electronic cigarettes; (d) drinking five or six beers or other alcoholic beverages at weekends; (e) drinking one or two beers or other alcoholic beverages every day; (f) drinking five or six beers or other alcoholic beverages every day; (g) taking tranquilizers/sedatives or sleeping pills habitually; (h) smoking hashish or marijuana (cannabis) occasionally; (i) smoking hashish or marijuana (cannabis) habitually; (j) taking powdered cocaine occasionally; (k) taking powdered cocaine habitually; (l) smoking base cocaine/crack occasionally; (m) taking ecstasy occasionally; (n) taking ecstasy habitually; (o) taking amphetamines or speed occasionally; (p) taking amphetamines or speed habitually; (q) taking hallucinogens (LSD, tabs or magic mushrooms) occasionally; (r) taking hallucinogens (LSD, tabs or magic mushrooms) habitually; (s) taking heroin occasionally; (t) taking heroin habitually; (u) injecting drugs occasionally; (v) taking GHB occasionally; (w) taking methamphetamine occasionally; (x) consuming magic mushrooms occasionally; and, (y) taking anabolic steroids occasionally. The response categories for all these consumption situations were: Few or no problems, A lot or quite a lot of problems, and Don’t know. In the results section, we graphically display the percentage of adolescents whose responses were Few or no problems and Don’t know to demonstrate the level of ignorance among adolescents with regard to substance use.Closed (yes/no) questions were also included to determine whether in the previous 30 days the adolescents: (a) had drunk any type of alcoholic beverage; (b) had smoked tobacco; and, (c) had used cannabis. These were all dichotomous variables. The adolescents were also asked whether in the previous 30 days they had engaged in modes of alcohol consumption, such as: (a) getting drunk and (b) binge drinking. Again, these were both dichotomous variables. Finally, included as dependent variables in several logistic regression models were cigarette, alcohol, and cannabis consumption and forms of consumption (getting drunk and binge drinking) (Table 2). For these analyses, we used Wald’s test and present the values of Exp (β) and their 95% confidence intervals, CI-Exp (β).In all these analyses, we tested whether gender and age play an important role in the prevalence of consumption, the perception the adolescents have about the level of information available, and the effects and problems that are associated with the consumption of these substances.In these analyses, we used the SPSS v. 2018 statistical package. The effect sizes were calculated while using the approach outlined on the Psychometrica website [29].In response to the question Do you feel sufficiently informed about the drugs issue? in the 2016 ESTUDES questionnaire, 66.7% of the adolescents replied that they were sufficiently or perfectly informed and 27% said that they were poorly or only partly informed, while 6.3% did not answer. Teenage girls believed that they were less and/or worse informed (33.7%) than teenage boys (23.9%) (χ2 = 399.8; p < 0.000; the effect size was low, i.e., d = 0.214). This difference increases with age: at 18 years the percentage points difference is 18 in favor of teenage boys (who believe they are well informed), while, at 14 years, this difference is nine percentage points (also in favor of teenage boys). For the sample as a whole, age 14 is when the lack of information is perceived to be greatest (by 31.5% of all adolescents). With regard to the age at which adolescents begin to consume these substances, 27.2% of adolescents who smoke smoked their first cigarette at the age of 14 and 22.9% did so at the age of 15, while 31.4% of those who drink drank their first alcoholic beverage at 14 and 23.6% did so at 15. We observe that a higher percentage of girls (52.1%) than boys (47.7%) started smoking between the ages of 14 and 15 when the data are disaggregated by sex. Similarly, a higher percentage of girls (56.7%) than boys (53.3%) had their first alcoholic drink between the ages of 14 and 15. With regard to adolescents who have been drunk, 27.3% got drunk for the first time at the age of 14, while 31.1% did so at the age of 15. Teenage boys and teenage girls did not present significant differences, even in the age at which they began to drink alcoholic beverages practically every week. Figure 1 shows the percentages of adolescents who stated that consumption implied few or no problems. The points indicate the percentage of adolescents who did not know how to reply to this question and the dashed line indicates the percentage of adolescents who reported that they were not sufficiently informed.A proportion of adolescents believed that low levels of consumption have no negative consequences on their health. For example, 27.5% believed that consuming 1–5 cigarettes a day implied hardly any problems, while the figures for drinking five or six beers or other alcoholic beverages at weekends, drinking one or two beers or other alcoholic beverages every day, smoking hashish or marijuana occasionally, and smoking electronic cigarettes were 36.2%, 39%, 37.3%, and 44.6%, respectively.Adolescents are more aware of the dangers involved in consuming less common substances, such as cocaine, ecstasy, heroin, and amphetamines, etc. Nevertheless, the percentages of non-responses due to ignorance about whether consuming such substances can be harmful to one’s health are high and a proportion of adolescents believes that occasionally consuming them has hardly any consequences on health at all. For cocaine, this figure is 17.2%, while those for ecstasy, amphetamines/speed, hallucinogens, heroin, magic mushrooms, anabolics, and methamphetamines are 14.6%, 14.1%, 14.3%, 13.3%, 12.2%, 10.7%, and 10.1%, respectively. Teenage boys, more than teenage girls, underestimate the consequences of consuming the most prevalent substances (cigarettes, alcohol, hashish/marijuana, and electronic cigarettes), especially when their consumption is habitual. For example, 7.8% of teenage boys, as opposed to 6.8% of teenage girls, believe that smoking a packet of cigarettes every day causes few or no problems. The figures for other substances are as follows: smoking electronic cigarettes, 45.1% (for boys) as opposed to 44.1% (for girls); drinking one or two beers or alcohol beverages every day, 41.3% as opposed to 36.7%; drinking five or six beers or alcohol beverages every day, 9.2% as opposed to 7.2%; smoking hashish/marijuana every day, 9.8% as opposed to 6.0%; taking powdered cocaine powder habitually, 3.4% as opposed to 2.5%; regularly taking ecstasy, 3.5% as opposed to 2.5%; taking amphetamines/speed habitually, 3.6% as opposed to 2.4%; and, taking hallucinogens habitually, 3.4% as opposed to 2.4%. In all cases, the differences between teenage boys and teenage girls are statistically significant (p < 0.001).The logistic regression model for the consumption (Yes/No) of tobacco in the previous 30 days enables correct estimation in 82.0% of cases (χ2 = 8375.4; p < 0.001), with Nagelkerke R2 estimating an adjustment value of 0.356. The probability that an adolescent had smoked tobacco in the previous 30 days when either their mother or father (or both) are smokers was 1.30 times higher than for adolescents whose parents do not smoke (CI = 1.21–1.39; d = 0.145). For adolescents, most of whose friends smoke, the probability was 94.0 times higher (CI = 79.3–111.1; d = 2.504), while if only some of their friends smoke, the probability was 14.2 times higher (CI = 12.04–16.82). The odds ratio corresponding to the level of information shows that the probability that an adolescent will have smoked tobacco when they believe they are well informed is 1.30 times higher than when they believe that they are not so well informed (CI = 1.21–1.39). In the model for hashish/marijuana consumption (Table 3), estimation is correct in 88.6% of cases (χ2 = 6937.4; p < 0.001; Nagelkerke R2 = 0.370). The probability that an adolescent will have consumed hashish/marijuana in the previous 30 days increases when their mother is a smoker (OR = 1.29; CI = 1.19–1.40: d = 0.1404) or their father is a smoker (OR = 1.15; CI = 1.05–1.24; d = 0.077), and especially when some of their friends consume hashish/marijuana (OR = 16.32; CI = 14.46–18.41; d = 1.539) or most of their friends do (OR = 93.05; CI = 80.55–107.5; d = 2.499). The probability that those who believe they are sufficiently informed will have consumed tobacco or hashish/marijuana is 1.59 greater (CI = 1.45–1.75; d = 0.2557), in each case, than for those who believe that they are not so well informed. We observe that the prevalence relationship is stronger if the majority of the adolescent’s friends smoke in the group who feel better informed (OR = 54.44; CI = 43.11–68.74) than in the group who feel worse informed (OR = 40.10; CI = 27.47–58.55) when consumption is controlled for the variable sufficiently or perfectly informed vs. partly or badly informed. However, there are no significant gender differences in either of these two groups. Estimation is correct in 78.6% of cases (χ2 = 5021.9; p < 0.001; Nagelkerke R2 = 0.23) in the model for alcohol consumption. The probability that an adolescent will have drunk is 37.3 times higher if most of their friends drink than if they do not (CI = 30.49–45.59; d = 1.995). It is also 8.08 times higher when only some of their friends drink (CI = 6.57–9.92; d = 1.152). An adolescent’s consumption of alcohol also increases when their mother is a regular drinker (OR = 1.21; CI = 1.08–1.37; d = 0.1051) and when they feel better informed (OR = 1.28; CI = 1.19–1.37; d = 0.1361). In the model for getting drunk (Table 4), estimation is correct in 80.9% of cases (χ2 = 6874.5; p < 0.01; Nagelkerke R2 = 0.303). The probability that an adolescent will have got drunk is 44.8 times higher when most of their friends have got drunk than when they have not (CI = 39.44–50.89; d = 2.096). Whether an adolescent gets drunk also depends on whether their mother is a regular drinker (OR = 1.17; CI = 1.03–1.32; d = 0.086), whether only some of their friends have got drunk (OR = 8.97; CI = 7.98–10.15; d = 1.209), and whether they feel well informed (OR = 1.23; CI = 1.14–1.31; d = 0.1141).Regarding binge drinking, the model provides correct estimation in 80.5% of cases (χ2 = 2912.0; p < 0.001; Nagelkerke R2 = 0.136). The probability that an adolescent will have binge drunk is 7.36 times higher if most of their friends have binge drunk than if they have not (CI = 6.77–8.00; d = 1.1005). This form of consumption depends on whether their fathers drink habitually (OR = 1.11; CI = 1.01–1.20; d = 0.0575), whether any of their friends have binge drunk (OR = 2.88; CI = 2.64–3.14; d = 0.5832), and whether they perceive themselves to be well informed (OR = 1.23; CI = 1.15–1.31; d = 0.1141).We observe that adolescents who feel worse informed are slightly more exposed to both alcohol consumption and getting drunk when most of their friends have these behaviors than adolescents who feel better informed (unlike what occurred with the consumption of tobacco and hashish/marijuana) when the consumption of alcohol is controlled for the variable sufficiently or perfectly informed vs. badly or partly informed. The OR for alcohol consumption among adolescents when most of their friends drink is 21.4 (CI = 19.46–23.53) in the group who feel better informed and 22.05 (CI = 19.00–25.58) in the group who feel worse informed. When it comes to drunkenness, the OR are 40.34 (CI = 34.94–45–58) and 62.52 (CI = 47.43–82.42), respectively. There were no significant gender differences in either of the two groups or between them, nor were there any differences in the prevalence ratios between those who feel better or worse informed regarding binge drinking. Our analysis shows that substance use begins at an early age [30], i.e., before the age of 14, which is in line with other studies [17,31]. Several authors have highlighted the possible consequences of early consumption on habitual consumption and even on risk consumption at a later age [32,33]. Our results show that 31.1% of adolescents smoke their first cigarette before the age of 14 (32% of boys and 30.3% of girls), while 15% try cannabis before the age of 14 (13.7% of girls and 16.2% of boys), 33.1% drink their first alcoholic beverage before the age of 14 (33.3% of boys and 32.8% of girls), and 15.6% get drunk for the first time before the age of 14 (15.4% of boys and 15.8% of girls). The percentage of teenage boys and girls who consume these substances increases as they get older. At the age of 14, 11.3% say that they have smoked in the previous 30 days, while at the age of 18 this figure increases to 44.4% (p < 0.001; effect size d = 0.217). Also, 5% of 14-year-olds and 26.6% of 18-year-olds say they have used cannabis in the previous 30 days (p < 0.001; d = 0.189), 40.6% of 14-year-olds and 83.3% of 18-year-olds (p < 0.001; d = 0.318) say they have drunk alcohol, 7.9% of 14-year-olds and 40.4% of 18-year-olds (p < 0.001; d = 0.259) say they have got drunk, while 9.4% of 14-year-olds and 30% of 18-year-olds (p < 0.001; d = 0.178) say they have binge drunk.When consumption (of alcohol, tobacco, or hashish/marijuana) is controlled for the variable sufficiently or perfectly informed vs. badly or partly informed, age and gender no longer have an effect on consumption or forms of consumption. At all ages, adolescents who believe that they are better informed have higher percentages of alcohol, tobacco, and hashish/marijuana consumption than those who believe that they are worse informed. This confirms our hypothesis that adolescents’ self-perception that they are well-informed does not necessarily lead to a lower prevalence of consumption. Teenage boys have the same pattern of behavior as teenage girls. Our results suggest that adolescents who believe that they are better informed tend to minimize the risk of effects and problems that are caused by consumption more than those who believe they are less informed and have a greater prevalence for consuming alcohol, tobacco and cannabis. The percentage of teenage boys who believe that they are better or more informed is higher than the percentage of teenage girls who do. However, boys tend to underestimate their habitual consumption of substances more than girls, whereas girls underestimate their sporadic consumption more. These data reflect a paradoxical situation in which the best-informed teenage boys underestimate more the damage to their health caused by consuming these substances. Our assertion that adolescents underestimate the effects of substance use is based on the responses that we received to the question “We would now like to know your opinion regarding the problems (health-related or otherwise) involved in engaging in the following behaviors”. Our analyses show that a high percentage of adolescents believe that few or no problems are caused by smoking 1–5 cigarettes a day (27.5%), smoking electronic cigarettes (44.6%), drinking five or six beers or other alcoholic beverages at weekends (36.2%), drinking one or two beers or other alcoholic beverages every day (39%), and smoking hashish/marijuana (cannabis) occasionally (37.3%). In all cases, the adolescents who believe they are “sufficiently or perfectly informed” also have the highest percentages of those who believe that the above situations cause few or no problems. For example, 28.5% of those who believe they are sufficiently or perfectly informed believe that few or no problems are associated with smoking 1 to 5 cigarettes a day, whereas 24.7% of those who think they are not so well informed have that opinion. For the other consumption situations, the figures are as follows: smoking electronic cigarettes, 46.2% vs. 40.6%; drinking five or six beers or other alcoholic beverages at weekends, 37.2% vs. 32.5%; drinking one or two beers or other alcoholic beverages every day, 39.9% vs. 37%; and, using cannabis occasionally, 38.9% vs. 33.5%. In this context, the consumption behaviors of adolescents may be linked to their underestimation of the effects of substance use and we believe, therefore, that a percentage of adolescents underestimates the effects of substance use. This suggests that the information adolescents have available might not be of sufficient quality for them to evaluate the negative impact of their consumption. Lack of knowledge or misinformation about the nature of drugs could arouse their curiosity and prevent them from accurately assessing the risks of consumption [34]. One of the limitations of this study derives from the question Do you feel sufficiently informed about the drugs issue? because there is no scale and classical methods of reliability, such as calculating Cronbach’s Alpha or the Intraclass Correlation Coefficient (ICC), that can be applied. We admit that no statistical measure can be applied to calculate the reliability and validity of this question, which might raise doubts regarding the authenticity of the responses. However, we could say that there is indirect inter-observer agreement since the responses to this question were similar across the Spanish autonomous communities (inter-observer reliability), as this survey was carried out throughout Spain. This shows that the question was understood and interpreted in the same way. With regard to content validity, we believe that the self-perception indicator does measure what it is supposed to measure, i.e., the extent to which the adolescents feel that they are informed. However, logically, this does not mean that the level to which they are actually informed corresponds to the level at which they perceive themselves to be. This question has been included in the ESTUDES series of surveys, where its capacity to measure self-perception has been qualitatively assessed by researchers and experts.Additionally, the questionnaire does not inform us of the contents of prevention programs provided to schools by institutions or those of programs implemented by the schools themselves. It would be interesting to know what these programs do and how good the information they provide is in order to understand the statistical association between the adolescents’ high perception of being well-informed and the greater prevalence of consumption among adolescents. An issue that is not included in the survey, but that would be interesting to explore, is to determine which channels of information adolescents routinely use to find out about substance use. It would be interesting to analyze the part that is played by the Internet and social networks as information search tools. This analysis could provide clues to enable programs and protocols to be designed for improving the quality of the information that they find. The effect that possessing sufficient quality information would have on the problems and consequences of substance use would justify implementing preventive actions supported by scientific evidence.A limitation when it comes to comparing these results with those of other studies is that the questionnaire we used does not allow for us to accurately compare our results with those of studies that included the specific item “substance use by my best friend”. Therefore, we have been unable to test the ‘best friend’ hypothesis. Instead, for comparison purposes, we have used data on their friends’ frequency of consumption, which allows for us to roughly determine the association between the adolescents’ prevalence ratios and their friends’ consumption.Regardless of their age, teenage boys and teenage girls both who perceive themselves to be well-informed have the highest prevalence of alcohol, cigarette and cannabis consumption in the previous 30 days. They also have the highest prevalence when it comes to modes of alcohol consumption (i.e., getting drunk and binge drinking) [35]. Our results also show that a not-insignificant percentage of adolescents believe that certain consumption situations cause few or no problems and that it is those who perceive themselves to be better informed who believe to a greater extent that such situations cause few or no problems. Generally, adolescents with models who are consumers (i.e., father, mother, and/or friends) have a greater prevalence to consume and a lower risk perception [36]. However, the habitual patterns and forms of alcohol and tobacco consumption of the adolescent’s father and mother are not always associated with the patterns and forms of the adolescents themselves. The regression models indicate that, among adolescents, the effect of habitual alcohol consumption is greater when the mother is the habitual consumer and that habitual consumption by the father has little effect. However, this association is reversed when it comes to binge drinking, since, here, the effect is greater when it is the father who is the habitual drinker. With regard to the consumption of tobacco and cannabis, mothers and fathers who smoke are equally associated with the risk that their children will consume these substances [37]. There is a clear relationship between the probability that adolescents will consume alcohol, tobacco, and hashish/marijuana, and whether their friends do. When most friends consume these substances—and, in the case of alcohol, do so by getting drunk and binge drinking—the likelihood that an adolescent will also consume them is much greater than when only some friends or no friends do. Some research suggests that strategies should focus on modifying expectancies, limiting access to alcohol at young ages, and targeting students of higher socioeconomic status to decrease consumption among adolescents in Spain [38].Future analyses should relate these results to parents’ educational styles. Research suggests that a lenient rather than a heavy-handed educational style might protect against substance use irrespective of the prevailing level of danger in the family’s urban context [39]. This shows the importance of involving families in educational prevention processes based on parental commitment. Similarly, some authors [40] highlight the importance of parental commitment combined with responsible supervision for protecting adolescents against consumption, rather than authoritarian parental styles, which are less effective in providing this protection and have even been identified as risk factors [41]. Finally, we should bear in mind that new substances begin to appear over time. Therefore, we need to incorporate new analysis criteria that are more sensitive to consumption patterns, especially the more problematic ones [42]. We also need to progressively incorporate measures pertaining to other drugs that begin to be consumed at a later age. Therefore, prevention must now respond to new challenges, such as: new forms of addiction to, for example, gambling, social networks and the Internet; the social acceptance of substances such as alcohol; the few truly well-informed perceptions among adolescents of the effects of alcohol, tobacco, and cannabis consumption; the pressure to legalize cannabis; and, the emergence of new psychoactive substances onto the market.A.B.-E. and I.P.-G. worked on the analysis and final writing; L.R.-A. and F.V.-F. collaborated in the methodology and in the definition of the variables; T.T.-C. and S.F.-A. reviewed the analyzes and the final wording. All authors have read and agreed to the published version of the manuscript.This research received no external funding. The authors would like to thank the Spanish Government Delegation for the National Drug Plan for allowing access to data from the Spanish Survey on Drug Use in Secondary Schools (ESTUDES). We would also like to thank the Prevention Service of Tarragona City Council for awarding funds for a statistical program on substance use in our local area. The authors declare no conflict of interest.Percentage of adolescents who believe that the consumptions shown pose few or no health problems. Note: This Figure shows the percentage (bars) of adolescents who believe that the consumption situations shown involve few or no problems as well as the percentage (circles) who do not know how to answer or have no opinion on the matter. In each case, the total percentage would reach 100% if we added those adolescents who believe that these situations involve a lot or quite a lot of problems. Source: Authors’ own based on data from ESTUDES 2016.Number (percentage) of subjects in the sample by age and gender.Source: Authors’ own based on data from ESTUDES 2016.Independent variables used in logistic regression analysis.Source: Authors’ own based on information from ESTUDES 2016.Results of logistic regression analysis for the consumption of tobacco and hashish/marijuana.Note: B = Regression coefficient; E.T. = standard error; p = probability; Exp (β) = odd ratio; 95% CI = 95% confidence interval. In all cases, the responses Mother smokes, Father smokes, Some friends smoke and Most friends smoke refer only to tobacco consumption. Source: Authors’ own based on data from ESTUDES 2016.Results of logistic regression analysis for alcohol consumption and forms of consumption.Note: B = Regression coefficient; E.T. = standard error; p = probability; Exp (β) = odds ratio; 95% CI = 95% confidence interval. Source: Authors’ own based on data from ESTUDES 2016.

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+Physical activity reduces the risk of several noncommunicable diseases, and a number of studies have found self-reported physical activity to be associated with sickness absence. The aim of this study was to examine if cardiorespiratory fitness, device-measured physical activity, and sedentary behaviour were associated with sickness absence among office workers. Participants were recruited from two Swedish companies. Data on sickness absence (frequency and duration) and covariates were collected via questionnaires. Physical activity pattern was assessed using ActiGraph and activPAL, and fitness was estimated from submaximal cycle ergometry. The sample consisted of 159 office workers (67% women, aged 43 ± 8 years). Higher cardiorespiratory fitness was significantly associated with a lower odds ratio (OR) for both sickness absence duration (OR = 0.92, 95% confidence interval (CI) 0.87–0.96) and frequency (OR = 0.93, 95% CI 0.90–0.97). Sedentary time was positively associated with higher odds of sickness absence frequency (OR = 1.03, 95% CI 0.99–1.08). No associations were found for physical activity at any intensity level and sickness absence. Higher sickness absence was found among office workers with low cardiorespiratory fitness and more daily time spent sedentary. In contrast to reports using self-reported physical activity, device-measured physical activity was not associated with sickness absence. Office workers are a group commonly associated with sedentary behaviour and low physical activity level during working hours [1]. The sedentary lifestyle at work may have contributed to the declining levels of cardiorespiratory fitness which have been seen in Sweden in recent years [2].Having high cardiorespiratory fitness, being physically active, and minimising prolonged time spent in sedentary behaviour have been shown to reduce the risk of mortality and morbidity from several noncommunicable diseases [3,4,5,6] and mental ill-health [7], but the association with sickness absence is less examined. Sickness absence refers to an individual’s reduced capacity to work due to ill health [8]. It is thus not only related to health but also individual characteristics and factors at the workplace [9]. The individual may experience greater personal suffering in terms of lower income and social and psychological consequences, such as feeling isolated and powerless, as consequences of sickness absence [10,11]. It can also lead to financial strain on companies and society [10]. Furthermore, several short sickness absence spells have been shown to predict later long sickness absence [12] and can also predict premature mortality [13], even when controlling for health status.Earlier studies have found low levels of physical activity to be associated with higher sickness absence due to musculoskeletal diseases [14,15,16], depressive disorders, and respiratory diseases [14]. However, physical activity at a vigorous level, but not at a moderate level, has shown an association with a lower risk of sickness absence [17,18]. It has been previously demonstrated that individuals who go from an inactive to a vigorously active lifestyle have a lower risk of subsequent sickness absence spells, and those who remained vigorously active exhibited the lowest risk [19]. However, earlier studies on physical activity in relation to sickness absence have only used subjective self-reported data on physical activity. This has been suggested as a major limitation, and the use of more valid, device-based measures of physical activity, such as accelerometers together with fitness tests, has been recommended for future studies [20]. In regards to cardiorespiratory fitness and sedentary behaviour in relation to sickness absence, very little is known. One study found cardiorespiratory fitness to be moderately associated with sickness absence due to noninjury musculoskeletal absence [21]. Low muscle fitness and aerobic endurance have been found to be associated with higher sickness absence among male military personnel [22]. Other studies have found no association in office workers [23]. Cardiorespiratory fitness has been shown to be related to work ability [24], which is a strong predictor of sickness absence [25].While subjective measures of physical activity often refer to more intense-level activities, sedentary behaviour not just is the opposite, but refers to activities such as sitting or lying down and is often defined as activity that involves an energy expenditure ≤ 1.5 metabolic equivalents [26]. Henriksen et al. [27] found no association between sitting time and sickness absence among office workers. Prolonged sitting has in another study shown an association with less sickness absence among Finnish working-aged individuals [28].The aim of this study was to investigate how cardiorespiratory fitness, device-measured physical activity, and sedentary time are related to sickness absence duration and frequency in a sample of office workers in Sweden.Data were collected in 2016–2017 from the “Physical activity and healthy brain functions project”, which involved office workers at two Swedish private companies. The employees were invited to participate (n = 1971) via email and were asked to fill out a web-based questionnaire during working hours and to wear an accelerometer and an inclinometer. Additionally, they performed cognitive tests and a submaximal cycle ergometer test. After 6 months, participants were invited to answer the questionnaire once again. Exposure variables and covariates were taken from the baseline measurement, whereas the outcome variable, sickness absence, was derived from the follow-up questionnaire at the 6 month follow-up. The analytical sample consisted of 159 participants, 106 women and 53 men, after exclusion of individuals without valid data on variables used in this study (Figure 1). Ethical approval was granted by the Stockholm Regional Ethical Review Board (2016/1840-32). Cardiorespiratory fitness (fitness) was estimated using the Ekblom-Bak submaximal cycle ergometer test [29], which uses heart rate recordings at two standardised work rates, together with the age and sex of the individual, to calculate VO2max. This test has been shown to provide a valid estimation of VO2 max for a wide variety of ages [30]. Relative values (mL per minute per kg body mass) were used in the present study.Physical activity was measured using an ActiGraph GT3X (ActiGraph, Pensacola, FL, USA) at baseline. The participants were instructed to wear the accelerometer on the hip during daytime and on the wrist when they went to bed at night (necessary for sleep analyses which were not used in the present study). The accelerometer sampled 3-axial acceleration with a frequency of 30 Hz [31], and data were subsequently extracted as 60 s epochs [32] with a low-frequency extension filter [33]. Inclusion criteria included minimum wear time of 600 min of valid data on at least 4 days, excluding sleeping time [34]. Nonwear time was defined as a minimum of 60 consecutive minutes with no movement (0 counts per minute) with maximum 2 min of a vector magnitude between 0–200 counts per minute (cpm) [32]. As accelerometers were worn 24 h, sleep time was excluded based on individual sleep diaries. Standard times for in bed, 23:00, and out of bed, 6:00, was added for individuals without diaries or missing data in diaries. Light physical activity was set to 200–2689 cpm, moderate to 2690–6166 cpm, vigorous to 6167–9642 cpm, and very vigorous to >9642 cpm [35,36]. Vigorous and very vigorous physical activities were combined in the analyses. Average percentage of daily time (excluding sleeping time) spent in moderate-to-vigorous physical activity (MVPA), light (LIPA), moderate (MPA), and vigorous physical activity (VPA) were used in the analyses. Sedentary time (SED) was assessed at baseline using activPAL monitors (PAL technologies limited, Glasgow, U.K.) placed on the thigh [1]. Participants were instructed to wear the activPAL 24 h per day over one week, which was the same week the GT3X was worn. The devices were waterproofed and secured to the front of the right midthigh. The activPAL device measures the angle of the thigh and can thereby discriminate between sitting/lying down and standing. We used data for sitting/lying down to measure SED. The devices were initialised and processed using the activPAL software version 7.2.32 (PAL Technologies limited, Glasgow, UK) using references on awake time and bedtime from participants’ diaries. Standard bedtime (23:00–06:00) was added for individuals without diary data. Additional data processing was conducted using the HSC analysis program (developed by Dr. Philippa Dall and Professor Malcolm Granat, School of Health and Life Sciences, Glasgow Caledonian University). SED was expressed in percentage of day, excluding sleeping time. Assessing sedentary behaviour with activPAL and physical activity with actiGraph has been recommended in earlier research [37].Sickness absence was derived from two questions assessed 6 months after baseline, specifically on dimensions of duration and frequency [38]. Duration was ascertained from the question “How many DAYS have you been home from work due to illness in the last 12 months?”. The response options were “Not at all”, “1–7”, “8–30”, “31–90”, and “91 days or more”. The question on frequency was “How many TIMES have you been home due to illness in the last 12 months?”. The response options were: “never”, “one time”, “2–5 times”, “6–10 times”, and “more than 11 times”. Sickness absence duration was dichotomized into 0–7 days and ≥8 days per year, and sickness absence frequency into 0–1 times and ≥2 times per year. The cutoff was set based on the distribution of sickness absence in our sample and was limited to low cutoffs for sickness absence due to the small analytical sample. Age (continuous), education (four categories: compulsory, upper secondary, university, higher academic education), gender (man, woman), smoking (yes, sometimes, no), and general health (very good, good, fair, poor, very poor) were based on self-reported data from the baseline questionnaire. These covariates were included based on earlier research regarding their associations with the exposures and outcomes [9,39,40,41,42,43,44,45]. Descriptive statistics were presented for the overall sample but also according to high and low fitness level (high ≥ 39.9 mL/min/kg), MVPA (high ≥ 6.25% of time awake), and SED (low ≤ 60.49% of time awake) using median split. Mean values and standard deviations were provided for the continuous variables, and percentages were provided for the categorical variables. Multivariate analysis of variance (MANOVA) was used to examine statistical differences between the groups for the continuous variables and chi-square statistics for the categorical variables. Multiple logistic regression analyses were performed to calculate odds ratios with 95% confidence intervals to examine the association between the different independent variables assessed at baseline: fitness (mL/min/kg), percentage of day in SED, MVPA, LIPA, MPA, and VPA, and sickness absence at follow-up. Collinearity between the chosen covariates was examined and the variance inflation factor never exceeded two, indicating that multi-collinearity was not a concern in our models. All statistical analyses were performed in IBM SPSS Statistics Version 25 (IBM, Armonk, NY, USA).The total sample consisted of 159 individuals (66.7% women, mean age 43.0, SD = 8.3). The majority (59.1%) had a university education or higher (Table 1). The MANOVA showed that individuals with a high amount of MVPA had higher fitness (F = 4.29, p < 0.05) and more time in LIPA (F = 4.50, p < 0.05), MPA (F = 124.17, p < 0.001), and VPA (F = 41.29, p < 0.001) compared with individuals with low MVPA. Individuals with high fitness were of younger age (F = 19.34, p < 0.001) and were more likely to be men (p < 0.001), to spend more time in VPA (F = 11.48, p < 0.001), and to have better general health (p < 0.01) and less sickness absence (p < 0.01) compared with individuals with low fitness. Individuals with low SED had higher education (p < 0.001) and higher proportion of time spent in MVPA (F = 6.91, p < 0.01), more LIPA (F = 35.96, p < 0.001) and VPA (F = 4.99, p < 0.05), and smoked less (p < 0.05) compared with individuals with high SED. Missing data analyses were performed comparing the analytical sample (n = 159) (Figure 1) with those who were excluded due to missing values (n = different for each variable). The analytical sample was of higher age, had lower education, and had more days of sickness absence at baseline compared with the excluded individuals.The results for sickness absence duration are presented in Table 2. For every mL increase in estimated VO2max, the odds of having ≥ 8 days of sickness absence per year decreased by 8% (OR = 0.92, 95% CI 0.87–0.96) in the unadjusted model. The relationship remained in all five presented models after sequentially controlling for age, education, gender, smoking, general health at baseline, MVPA, and SED. Neither SED nor PA at any intensity level showed a significant relationship with ≥8 days of sickness absence. Table 3 shows similar trends for sickness absence frequency. The odds of sickness absence ≥2 times per year decreased by 7% (OR = 0.93, 95% CI 0.90–0.97) for each unit increase in estimated VO2max (mL/min/kg) in the unadjusted model (Model 1), and the association remained after full-adjustment (Models 2–5). Percentage of the day in SED increased the odds of sickness absence ≥2 times per year by an odds ratio of 1.03 (95% CI 0.99–1.08) per percentage. This association was statistically significant after additional adjustment for age, education, and gender (in Model 2), smoking (Model 3), and baseline health (Model 4), but not when controlling for MVPA and fitness (Model 5). None of the intensity levels of physical activity were statistically associated with sickness absence ≥2 times per year.This study investigated the association between cardiorespiratory fitness, physical activity at various intensity levels, and sedentary behaviour on the outcome of sickness absence duration and frequency among office workers in Sweden. Higher cardiorespiratory fitness was significantly associated with lower odds of sickness absence assessed as both duration and frequency. Higher sedentary behaviour was associated with frequent sickness absence. No association was found between physical activity at any intensity and sickness absence. The present study supports two earlier studies that found fitness to be associated with sickness absence [21,22] but adds new knowledge regarding the associations for both sickness absence frequency and duration. However, the findings from Bernaards et al. [23] were not consistent with ours, potentially due to differences in assessments of fitness and methodology. Cardiorespiratory fitness has previously been found to be a stronger predictor for ill health compared with objectively assessed physical activity [46,47], which our results support. To the best of our knowledge, this is the first study that has found increased sedentary behaviour to be associated with a higher frequency of sickness absence. In contrast, Lallukka et al. [28] found an inverse association between self-reported sedentary behaviour and sickness absence. This discrepancy in results between studies may be due to the earlier study including other types of occupations in the population and not solely office workers. Moreover, Henriksen et al. [27] reported no association between self-reported sedentary behaviour and sickness absence measured in days (duration) among office workers, which was in line with the present study.Earlier studies found self-reported physical activity to be associated with sickness absence [14,15,48,49,50], which the present study could not confirm with device-based measures of physical activity. Furthermore, our study did not find a statistically significant association between vigorous physical activity and sickness absence, which has been previously demonstrated [17,18,19]. These discrepancies between studies can also be explained by variations in methodology for measuring physical activity and sickness absence. Earlier studies have investigated differences using questionnaires and accelerometer data for assessing physical activity [51]. Another possible explanation is that the accelerometer method has a limited validity in assessing differences between the upper part of moderate-intensity, vigorous, and very vigorous activity, i.e., the types of activities that would affect maximal aerobic capacity. This inability is mainly due to a proprietary frequency filter reducing the signal at high intensities. Work has been published [52] with this filter removed, indicating far better accuracy. More studies are needed based on unfiltered data to assess the potential relation between vigorous activity and sickness absence and any relation to cardiorespiratory fitness. Strengths of this study include the use of device-based measures of physical activity, cardiorespiratory fitness, and sedentary behaviour. This is especially important since it has been suggested as a limitation in earlier research in this area [20]. The inclusion of office employees from two companies may have limited the effect of the social gradient as a source of confounding since the occupational status and the physical work environment of the employees are rather similar. One limitation is the use of self-reported sickness absence, which can be prone to recall-bias, yet self-reported data on sickness absence has shown generally good agreement with sickness absence recorded from employers [38]. Furthermore, there may have been potential bias from the small population size, limiting the power of the study and increasing the risk of a type II error. Thus, conclusions drawn from these results require careful consideration. Reverse causality may have also impacted the results, because individuals who were too sick to work probably also were too sick to exercise. However, we aimed to reduce the effect of reverse causation by controlling for baseline health. Worth noting is that our sample was very physically active: 50% had greater than 6.25% of their wake time in moderate-to-vigorous physical activity, which corresponded to about an hour per day. The sample may be healthier than office workers in general because individuals with ill health at the time of measurements may have been less likely to participate. Additionally, sickness absence was reported 6 months after baseline, but the question refers to sickness absence in the last 12 months. Therefore, this study may be potentially interpreted as a cross-sectional study. Further, SED and LIPA are usually strongly collinear, and having them in the same model should normally be avoided. This study does, however, use data from activPAL to measure sedentary time and data from ActiGraph to measure LIPA, which makes the variables only moderately collinear (Pearson 0.51) and could therefore be used in the same model. Mainly standing time could not be included as sedentary time from activPAL or LIPA from ActiGraph. Higher cardiorespiratory fitness is associated with lower odds of sickness absence, both in frequency and duration. Time spent sedentary is associated with higher odds of frequent sickness absence. No associations were found between physical activity at different intensity levels and sickness absence. This suggests that office workers with low cardiorespiratory fitness and more sedentary behaviour may have a higher risk of sickness absence, and interventions aiming to reduce sickness absence should target these groups. The impact of fitness on sickness absence can potentially be substantial since our results suggest an increase of the odds of sickness absence of 7–8% per unit mL/min/kg. Future longitudinal studies are needed with larger samples, together with intervention studies, to explore more about the associations between fitness, physical activity, and sickness absence. The findings presented here might motivate employers to provide incentives for their employees to become more fit and/or active, and researchers to carefully evaluate/compare such initiatives. Such evaluations should include effects on physical activity patterns, cardiorespiratory fitness, work environment, mental health, productivity, and sickness absence. Conceptualization, E.D. and V.B.; methodology, E.D., Ö.E. and V.B.; formal analysis, E.D., Ö.E. and V.B.; resources, M.M.E., Ö.E., L.V.K. and V.B.; writing—original draft preparation, E.D.; writing—review and editing, E.D., M.M.E., Ö.E., L.V.K. and V.B.; project administration, M.M.E. and V.B.; funding acquisition, M.M.E. All authors have read and agreed to the published version of the manuscript.This study is part of the “Physical activity and healthy brain functions” project which is funded by the Knowledge Foundation (grant 20160040), and by the following companies: ICA-gruppen, Intrum, SATS Elixia, Monark Exercise, and Itrim Sweden. Proofreading was performed by Emerald Heiland.The authors declare no conflict of interest. The companies had no role in analyses or interpretation of data, in the writing of the manuscript, nor in the decision to publish the results.Flowchart illustrating how the analytical sample was reached from the invited individuals.Characteristics of the sample, stratified by fitness, MVPA, and sedentary time status. Statistical differences between the mean variables were examined using MANOVA for continuous variables and chi-square tests for the categorical variables (n = 159).* = p < 0.05; ** = p < 0.01; *** = p < 0.001. a Poor to fair health. None responded “very poor”. MVPA, moderate-to-vigorous physical activity; LIPA, light-intensity physical activity; MPA, moderate physical activity; VPA, vigorous physical activity; SED, sedentary time; SD, standard deviation; m, mean.Odds of sickness absence ≥8 days per year according to baseline fitness, and percentage in LIPA, MPA, VPA, MVPA, and SED (n = 159).LIPA, light-intensity physical activity; MPA, moderate physical activity; VPA, vigorous physical activity; MVPA, moderate-to-vigorous physical activity; SED, sedentary time. Model 1: unadjusted. Model 2: adjusted for age, education, and gender. Model 3: Model 2 + smoking. Model 4: Model 3 + general health at baseline. Model 5: Model 4 + SED, fitness and/or MVPA.Odds of sickness absence ≥2 times per year according to baseline fitness, and percentage in LIPA, MPA, VPA, MVPA, and SED (n = 159).LIPA, light-intensity physical activity; MPA, moderate physical activity; VPA, vigorous physical activity; MVPA, moderate-to-vigorous physical activity; SED, sedentary time. Model 1: unadjusted. Model 2: adjusted for age, education, and gender. Model 3: Model 2 + smoking. Model 4: Model 3 + general health at baseline. Model 5: Model 4 + SED, fitness and/or MVPA.

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+Urbanization processes at both global and regional scales are taking place at an unprecedent pace, leading to more than half of the global population living in urbanized areas. This process could exert grand challenges on the human living environment. With the proliferation of remote sensing and satellite data being used in social and environmental studies, fine spatial- and temporal-resolution measures of urban expansion and environmental quality are increasingly available. This, in turn, offers great opportunities to uncover the potential environmental impacts of fast urban expansion. This paper investigated the relationship between urban expansion and pollutant emissions in the Fujian province of China by building a Bayesian spatio-temporal autoregressive model. It drew upon recently compiled pollutant emission data with fine spatio-temporal resolution, long temporal coverage, and multiple sources of remote sensing data. Our results suggest that there was a significant relationship between urban expansion and pollution emission intensity—urban expansion significantly elevated the PM2.5 and NOx emissions intensity in Fujian province during 1995–2015. This finding was robust to different measures of urban expansion and retained after controlling for potential confounding effects. The temporal evolution of pollutant emissions, net of covariate effects, presented a fluctuation pattern rather than a consistent trend of increasing or decreasing. Spatial variability of the pollutant emissions intensity among counties was, however, decreasing steadily with time.In 2008, more than half of the world’s population lived in urbanized areas, overtaking the rural population for the first time, and the urbanization rate was projected to reach 66% or so by 2050 [1,2]. The unprecedently rapid urbanization processes taking place in developing countries undoubtedly contribute much to the increased global urban population [3]. Particularly, after the Economic Reform and Opening-up policy, China’s urbanization rate jumped from 17.92% in 1978 to 59.58% in 2018. Decades of fast and stable economic growth were an important driving force of the large-scale rural-to-urban migration process [4].Explosive population growth combined with limited living space in urban areas caused a series of issues to be solved urgently, among which tackling air pollution and the associated health problems was a priority [4]. Deterioration of air quality in urban areas was mainly caused by emissions of pollutants such as PM2.5 (particulate matters with an aerodynamic diameter ≤ 2.5 μm), NOx and SO2 [5,6]. A large number of studies had proven the negative effects of exposures to PM2.5, NOx and SO2 on human health, such as premature mortality [7], lung cancer [8], and cerebrovascular diseases [9]. Pollutant emissions in urban areas were largely driven by anthropogenic processes such as biomass burning, industrial, and mobile sources [10,11].A growing number of empirical studies have been conducted to examine the relationships between urbanization, economic development, and environmental pollution. For instance, [12] analyzed the influences of urbanization, economic growth, trade openness, financial development, and renewable energy on pollutant emissions in Europe. [13] explored the spatial spillover effects of industrialization and urbanization on pollutant emissions in China’s Huang-Huai-Hai region. Spatial differences in the impacts of urbanization and economic growth on air pollutants in China were further explored by looking at provincial panel data [14,15]. Nonetheless, most of these studies relied on analysis units with coarse spatial scales (either being provinces or prefecture cities), thus ignoring the potential within-unit heterogeneity effects. In addition, the temporal coverage of environmental pollution indicators was most often short (e.g., five to ten years), which might compromise the reliability and accuracy of estimated relationships between urban expansion and environmental pollution. Furthermore, few studies explicitly took into account spatial correlation and temporal dynamics simultaneously when modeling urbanization and pollution data under study. However, it is a well-known fact that ignoring spatio-temporal correlations could lead to unreliable statistical inferences on relationships between covariates under key research interest [16,17,18]. The distributions of urbanization and environmental pollution were rarely uniform or even over space. Instead, they often exhibited evident spatial characteristics such as clustering patterns, partly because of the spatial sorting and clustering of economic activities and populations [19]. Addressing the aforementioned issue needs an interdisciplinary perspective [20], high-quality and integrated data sets linked from various sources such as remote sensing and satellite images [21], and appropriate methodologies capable of dealing with complex underlying spatial and temporal effects of the data.This paper attempts to offer a reliable estimate of the relationship between urban expansion and pollutant emissions by carefully addressing the above issues. It first uses pollutant emissions data with fine spatial resolution and long temporal coverage (~20 years), which was compiled by using a bottom-up approach and had been rigorously tested in previous studies [22,23]. In addition, we compiled two urban expansion indicators exploiting various remote sensing and satellite data sources such as the nighttime light data (NTL). New instruments of urban expansion using NTL and satellite images, moving beyond the traditional measures of urbanization from administrative statistical data, have been proposed and employed in environmental studies. A comprehensive review on this strand of literature was provided by [21], and the economic and statistical rationales of these indicators were offered in [24]. Finally, this study built a Bayesian spatio-temporal autoregressive model to estimate the relationship between urban expansion and pollutant emission, explicitly and flexibly modeling spatial correlations and temporal dynamics underlying the data under investigation. Although we took a case study of Fujian province of China, the research methodology and design could be readily applied to other data sets. With respect to the key empirical results, we found a significant relationship between urban expansion and pollution emission: urban expansion in Fujian province during the two decades from 1995 to 2015 significantly elevated PM2.5 and NOx emissions intensity. This result was insensitive to two different measures of urban expansion and held after controlling for potential confounding effects.The remainder of this paper is structured as follows. Section 2 describes the study area, data, and research methods. Section 3 and Section 4 present findings and discussions from our descriptive analyses and statistical modeling. Section 5 concludes with a brief summary of the findings.Our study area is the Fujian province, located on the southeast coast of China (28°30′–28°22′ N, 115°50′–120°40′ E). It is adjacent to Zhejiang province in the northeast and borders Jiangxi province in the west and northwest and Guangdong province in the southwest (Figure 1). The land area of Fujian province is 1.24 × 105 km2 with a population of about 37 million in 2010 [25]. There are 85 counties constituting Fujian province, serving as our analysis units. The average land area of the counties is about 1436 km2 with a standard deviation of 1028 km2 whilst the average population is 434,000 with a standard deviation of 319,000 [25].Environmental pollution impacts of urbanization were measured by using pollutant emissions instead of pollution concentrations in this study. First, pollutant emission data were compiled with fine spatial resolution (~0.1° by 0.1°) and relatively long temporal coverage. Emissions of various pollutants such as PM2.5, NOx, SO2, and TSP were compiled by using a rigorous bottom-up approach based on energy consumption and source-specific emission factors. Details on source information and the calculation and calibration procedures were provided in [22,23]. Pollutant emissions data were made publicly available by the School of Environmental Sciences at Peking University (http://inventory.pku.edu.cn). Second, high space–time resolution emissions data can serve as an important input into the GEOS-Chem atmospheric transport model to derive high-resolution and spatio-temporally consistent pollutant concentrations [26,27]. Finally, official air pollution monitoring data did not have the necessary temporal coverage required by the present study. Accuracy of monitoring data could also be compromised by various spatial interpolation operations when deriving areal pollution summaries from monitoring station readings. Monthly gridded pollutant emissions data in 1995, 2000, 2005, 2010, and 2015 covering the study area were downloaded and aggregated to annual cumulative measures of pollutant emissions for counties. As county boundaries and grids were not compatible geographies [28], a standard GIS areal weighting approach was used to transfer gridded emissions data onto county-scale measurement. We finally obtained the annual pollutant emission intensity of each county by dividing the annual cumulative pollutant emissions by the area of each county.Remote sensing-based land use monitoring data were extracted from the Landsat TM/ETM images through the manual visual interpretation method [29]. Land use data in the same years (1995, 2000, 2005, 2010, and 2015) as the pollutant emissions data were downloaded from China’s Resource and Environment Data Cloud Platform (http://www.resdc.cn/), with a spatial resolution of 1 km by 1 km. In this data, land use types were divided into six major categories: cultivated land, forest land, grassland, water area, urban and rural construction land, and unused land. Each major category was further divided into several sub-categories. With this data, we measured urban expansion by forming an urban land development intensity (ULDI) indicator, calculated as the ratio of urban construction land area of a county to its total area during 1995 and 2015. As an assurance on the estimated relationship between urban expansion and pollutant emissions, we derived another indicator of urbanization by using the nighttime light (NTL) data available from NOAA/NGDC (https://www.ngdc.noaa.gov/ngdc.html). The NTL data were compiled from DMSP/OLS and NPP-VIIRS with a spatial resolution of 1 km by 1 km in the matched time periods. NTL data have been increasingly used to calibrate indicators of both urbanization and economic development [24,30,31,32,33] (DMSP/OLS and NPP-VIIRS data themselves are not without problems when approximating levels and variations of regional urbanization and economic development: the relatively poor county ad over-saturation of DMSP/OLS data and existences of negative values, extremely high values, and unstable light sources for NPP-VIIRS data [34]). We therefore extracted the NTL data for the study area from 1995 to 2015. Urbanization was measured by dividing the total luminosity of a county by its total area (LD). We acknowledge that remote-sensing-based measures of urbanization focus on the urban land development or expansion. It is less capable of reflecting urbanization processes in other domains, such as population, culture, and lifestyles. It was useful to note that the LD measures of urban expansion were consistent with the ULDI indicator (the Pearson coefficient about 0.8). The gridded ULDI and LD data were used to extract county-level urban expansion measures with the standard GIS areal weighting approach [28].Geographical and locational factors were also incorporated in our pollutant emission models to capture potential confounding effects. Geographical variables included the greenness of each county (measured by the green space density—Green) and land development potentials (details on the calculation of this indicator were provided in [35]; Available construction land of each county—ACLD). With respect to locational variables, we included a variable representing whether a county is a coastal county and two distance variables measuring the geographical proximity of a county to Xiamen (the state-level special economic zone in Fujian province and the most affluent city in terms of per capita GDP) and to its affiliated prefecture-level city. As economic activities were unevenly distributed across places, those places with locational advantages such as being adjacent to the province’s growth center would attract more development opportunities, i.e., the spatial spillover effects well-recognized in the economic geography literature [19,36,37]. These factors could affect the levels of urban development as well as pollution emissions and would compromise the estimated relationships between urban expansion and pollutant emissions if excluded from the modelling analysis. The statistical summaries of variables were displayed in Table 1.Given the spatio-temporal nature of our data, the study employed a recently developed Bayesian spatio-temporal statistical model to capture the spatial correlations between spatial units and temporal dynamics across time periods. Denoting the non-overlapping counties constituting the study area as Ak (k = 1, 2, …, K) and time periods as t (t = 1, 2, …, 5), the statistical model is specified as
+        (1)ykt|μkt ~ f(ykt|μkt, μkt); k=1,2,…,K;t=1, 2, …, 5
+        μkt=Xktσ+Uktγ+ψktIn Equation (1), ykt is the observed pollutant emission of county k at time t, which follows a normal distribution with mean μkt and variance σ2, N(μkt, σ2); Ukt are the urban development intensity variables measured from two different data sources, while Xkt are other predictor variables; β and Υ are coefficient vectors to be estimated.The ψkt term is a latent component for county k at time t, and they collectively (ψ=ψ1,ψ2,…,ψ5 where ψt=ψ1t,ψ2t,…,ψKt) capture the structured spatiotemporal random effects underlying the data. Spatial correlations are modeled by introducing a K × K spatial weights matrix W specifying the potential spatial connection structure among counties. Following the spatial modeling convention [16], each element of W was formed on the basis of geographical contiguity: wkj = 1 if counties k and j share a common geographical border and 0 otherwise. In order to model the spatially and temporally evolved pollutant emissions surfaces, we formulated a Bayesian spatio-temporal autoregressive model following Rushworth et al. (2014, 2017) [17,38],
+        (2)μkt=Xktβ+Uktγ+ψkt
+        (3)ψt|ψt−1~N(λψt−1, τ2Ω(W, ρ)−1)
+        (4)ψ1~ N(0, τ2Ω(W, ρ)−1)
+        (5)τ2~ Inverse−Gamma(a,b); λ, ρ ~ Uniform(0,1)Equation (3) specifies that the K × 1 vector of random effects for time t evolving over time follow a multivariate first-order autoregressive process with a temporal autoregressive parameter λ. The distribution of random effects at time period 1 (ψ1) is specified in Equation (4) as a Gaussian Markov Random Field (GMRF) model [39]. The spatial autocorrelation among counties is introduced by the precision matrix Ω (W, ρ). Following Rushworth et al. [17], we adopted a special conditional autoregressive (CAR) model developed by Leroux et al. [40] in this study. The conditional distribution of random effect of county k at time period 1, ψk1, given other random effects (ψ−k1), is formulated as [17]
+        (6)ψk1|ψ−k1, W,ρ,τ2 ~ N(ρ∑k~lψl11−ρ+ρwk+,1τ2(1−ρ+ρwk+)) (2)
+        where wk+ is the number of geographical neighbors that a county k has, and ρ measures the strength of spatial correlation. The resulting precision matrix of the LCAR model is: ΩLCAR=τ2(LW−W) where LW= diag (1−ρ+ρw+). To complete the specification of the Bayesian spatiotemporal autoregressive model, conventional prior distributions were specified for unknown model parameters: a multivariate normal distribution for regression coefficients (β and Υ); an inverse-gamma distribution for variance parameters (σ2 and τ2); and a uniform distribution for spatial and temporal autoregressive parameters (ρ and λ). In our empirical study, non-informative priors were used in the model estimation.The model was implemented by using the Bayesian Markov Chain Monte Carlo (MCMC) simulation approach, available in an open-source R software package CARBayeST [18]. For each of the models implemented below, statistical inferences were based on two MCMC chains, each of which consisted of 70,000 iterations with a burn-in period of 20,000 to ensure the convergence of samplers. We further retained every tenth sample to reduce autocorrelation in each MCMC chain. Model convergence was examined by visual inspection. Deviance information criteria (DIC) [41] were used for model comparisons. A simple working flowchart of the present study is presented in Figure 2.The spatial distributions of pollutant emissions and urban expansion and their temporal evolutions are presented in Figure 3. In 1995, the lowest amount of PM2.5 emissions was recorded in Siming District (1.857, on the log scale) of Xiamen, while the highest emissions were recorded in Gulou District (6.083) of Fuzhou. Siming District again emitted the smallest amount of PM2.5 emissions in 2015, while Taijiang District of Fuzhou became the area emitting the largest amount of PM2.5. Overall, there were 19 counties experiencing a decrease in PM2.5 emissions from 1995 to 2015, with the largest decrease being Pingnan County. By contrast, there were more than 77% of counties in Fujian province that experienced increases in PM2.5 emissions with an average increase of 0.104 in PM2.5 emissions during the study period. It was also clearly seen that spatial clusters of relatively high PM2.5 emissions gradually formed, surrounding Siming and Haicang Districts of Xiamen and Gulou and Taijiang Districts of Fuzhou. The spatial patterns of NOx emissions and their temporal evolution were largely similar to those observed for PM2.5 emissions (maps and statistics are available upon request).With respect to urban expansion, the lowest ULDI value was recorded for Jianning County of Sanming City in 1995, while the highest level of urbanization was found in the Taijiang District of Fuzhou. The county with the lowest ULDI value in 2015 became Zherong County of Ningde, whilst Taijiang District was still associated with the largest ULDI value. From 1995 to 2015, urban land development levels were increased by about 60% on average for all counties of Fujian province. The spatial patterns of urbanization in 1995 and 2015 measured by the NTL data were very similar to those revealed by the ULDI indicator (Figure 3). The similarity in the spatial distributions of PM2.5 emission and urban expansion suggested a potentially positive correlation between them, which will be further tested in our statistical models.We implemented a series of models to explore the relationships between pollutant emissions (PM2.5 and NOx) and urban land development. We first note that both the spatial and temporal autoregressive parameters are very high (both > 0.9) with narrow 95% credible intervals, indicating significant spatial correlations and temporal dependences underlying the data and signifying the necessity of a spatio-temporal autoregressive statistical modeling of pollutant emissions. Urban expansion was statistically significantly associated with higher PM2.5 and NOx emission intensity (emission per km2). Based on the estimated regression coefficients (Table 2), an increase of 0.05 in ULDI (roughly the average increase of ULDI from 1995 to 2015) was associated with about 7.9% (with a 95% credible interval of [5.3%, 9.9%]) increases in PM2.5 emissions and about 8.8% (with a 95% credible interval of [6.1%, 10.8%]) increases in NOx emissions, ceteris paribus. Previous national-scale studies found that China’s urbanization process helped to reduce pollutant emissions and concentrations partly because of the higher energy use efficiency in urban areas made available to people migrating from rural areas with lower energy use efficiency and a poor energy mix [26]. Such seemingly contradictory findings would require a further multiple-scale analysis of how pollutant emissions respond to urban expansion and its geographical scale dependency. Nonetheless, unlike the univariate analyses in [26], this study adopted a more suitable spatio-temporal dynamic model and considered potential confounding effects.With respect to other covariate effects, we found that locational factors were statistically significantly related to PM2.5 and NOx emissions: counties further away from the Economic Special Zone (ESZ) Xiamen and the affiliated prefecture city were associated with lower pollutant emission intensity, holding other variables constant. A plausible explanation is that counties far from the economic growth hotspots such as the ESZ Xiamen tend to have fewer development opportunities (e.g., domestic and foreign direct investment). Green land of a county appeared to be negatively correlated with pollutant emission intensity, but this association was not statistically significant at the 95% credible interval. Available construction land of a county and being a coastal county were not statistically significantly associated with pollutant emission.We then turned to test whether the relationships between urban expansion and pollutant emissions depended on geographical locations of counties. A series of interaction terms between urban expansion and locational factors were sequentially added to the above model (Table 3). The statistically significant interaction term was the one between urban expansion and whether a county is coastal. The negative coefficient of the interaction term highlighted that urban expansion had a much smaller effect on pollutant emissions in coastal areas than in inland areas. High economic development levels and tight environmental regulations implemented in coastal areas might contribute to the above findings, but rigorous tests on causes of the differential effects are left for future research. We note that estimates on other model parameters remained similar to those in Table 2.In order to obtain reliable estimates on the relationship between urban expansion and pollutant emissions, we implemented models with urban expansion measured by the NTL data. Model estimation results for PM2.5 and NOx emissions were reported in Table 4. Estimates of the coefficients of LD were both statistically significant, implying that urban expansion was positively related to pollutant emissions. An increase of 0.04 in LD (roughly the average increase of LD from 1995 to 2015) was associated with about 2.5% (with a 95% credible interval of [1.6%, 3.3%]) increases in PM2.5 emissions and about 3.2% (with a 95% credible interval of [2.3%, 4.1%]) increases in NOx emissions, ceteris paribus. We note that the magnitudes of the estimates on how LD and ULDI were related to pollution emissions intensity were different. However, these estimates were consistent in terms of suggesting that urban expansion was associated with increasing pollutant emissions intensity in the study area. Locational factors still presented statistically significant associations with pollutant emissions as found in the above models. We also added meteorological factors such as the average wind speed of each county in the pollution emission models, but found they were not statistically significantly related to pollutant emissions intensity. For instance, the coefficients of the wind speed variable in the PM2.5 and NOx model were 0.543 [−0.206, 1.547] and 1.135 [−0.27, 2.245].Figure 4 presents model-based estimates on the temporal evolutions of PM2.5 and NOx emissions from 1995 to 2015, superimposed by the lower and upper quantiles of these estimates (dashed lines). Two interesting features were revealed. First, the overall pollutant emission intensities (PM2.5 and NOx) were bouncing back and forth with time, rather than presenting a steady trend of increase or decrease. In addition, the gap or variability in pollutant emissions among counties in Fujian Province was shrinking during the two decades. Figure 5 presented the estimates on spatial distributions of PM2.5 and NOx, net of covariate effects, in the study area. Spatial correlations of these estimates were clearly shown with hotspots around the Jimei and Xiangan districts of Xiamen and gradually decreasing to the surrounding areas (Figure 5).How environmental quality responds to urbanization is an important theoretical and empirical enquiry to pursue, given the fast pace of urbanization processes taking place at both global and regional scales. This study proposed a Bayesian dynamic spatio-temporal statistical model to analyze the relationship between urban expansion and pollutant emissions while explicitly capturing the spatial autocorrelation, heterogeneity, and temporal dynamic effects. Quantifications of these effects were interesting in themselves, but more importantly, it allowed for more reliable estimates of the relationship between urban expansion and pollutant emissions [17,18].Our model estimation results suggest a consistent positive relationship between urban expansion and pollution: urban expansion tended to lead to an increase in pollutant emission intensity in Fujian province during the last two decades. This appears to be in contradiction with the finding that urbanization led to decreases of pollution emissions and concentrations in a recent national-scale study [26]. Meanwhile, it highlights an important issue of scale effects when examining relationships between variables, i.e., the well-recognized modifiable areal unit problem (MAUP) in the spatial analysis and modeling literature [42,43]. Briefly, it refers to the fact that relationships between variables could be very different in magnitudes or even reversed when examined at different spatial scales. This could reflect that the underlying process governing the relationship between two variables could be different at different scales. We therefore argued that at a finer spatial scale (counties in this study), urban expansion could exert detrimental impacts on environmental quality, but at a coarser national scale, urbanization could be beneficial to environmental quality through various channels, such as improved energy production and use efficiency [26]. The potential heterogeneous impacts of urban expansion upon environmental pollution at local and national scales would have important urban and regional development policy implications. One-for-all national uniform policies targeted to urbanization may not be as effective and environmentally friendly as anticipated.Some limitations remain. First, the results on the relationship between urban expansion and pollutant emissions should not be interpreted as cause and effect. One reason is that certain confounding variables that affect both pollutant emissions and urban expansion might be not incorporated in our model because of data limitations. Second, the relationship between urban expansion and pollution concentrations was not explored in the present study. Although real-time air quality was an optional data source, it lacks the temporal coverage of our emission data. It also suffers from noises added by various spatial interpolation techniques and issues from selective choices of monitoring sites. The next step of our research is to use the GEOS-Chem atmospheric transport model with emission data as key inputs to derive high-resolution pollutant concentration indicators [23,27]. We then will examine the relationships between urban expansion and pollution concentration with the Bayesian spatio-temporal statistical models. Finally, with new credible data sources on urban expansion for other Chinese provinces, we shall test whether the relationship between urban expansion varies across provinces and discuss the potential mechanisms leading to such spatial heterogeneities.In this study, we analyzed how pollutant emissions were responding to urban expansion in Fujian province. Our exploration mainly drew upon the fine spatial resolution pollution emissions data and the spatio-temporally matched urban expansion indicators extracted from various remote sensing and satellite data sources. A Bayesian spatio-temporal autoregressive statistical model was developed to examine the relationship between urban expansion and pollutant emissions, explicitly modeling potential spatial correlations and temporal dependency underlying the data. Our empirical results showed that urban expansion in Fujian province elevated pollution emission intensity during 1995–2015. This finding was retained for different measures of urban expansion and after controlling for potential confounding effects. Model-based estimates of the spatial distributions of pollutant emission presented clear clustering patterns. The temporal evolutions of pollutant emission, net of covariate effects, showed a fluctuation pattern rather than a consistent trend of increase or decrease. Nonetheless, the spatial variability of pollutant emissions intensity among counties in Fujian province was decreasing with time.Conceptualization, S.Z., G.D., and Y.X.; methodology, S.Z. and G.D.; formal analysis, S.Z., G.D., and Y.X.; investigation, S.Z., G.D., and Y.X.; resources, Y.X.; data curation, S.Z., and Y.X.; writing—original draft preparation, S.Z., G.D., and Y.X.; writing—review and editing, S.Z., G.D., and Y.X.; visualization, S.Z.; supervision, G.D., and Y.X.; funding acquisition, Y.X. All authors have read and agreed to the published version of the manuscript. This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences, Grant No. XDA23020101 and China Scholarship Council, grant number 201804910734.The authors declare no conflict of interest.The study area and the county boundaries in Fujian province.A simple working flowchart of the present study. Note: locational factors in the diagram included a dummy variable representing whether a county is a coastal county and two distance variables measuring the geographical proximity of a county to Xiamen and to its affiliated prefecture-level city.Spatio-temporal dynamics of Log PM2.5, ULDI, and LD from 1995 to 2015 in Fujian Province.Model-based estimates on the temporal trends of PM2.5 (left) and NOx (right) emissions. The 25%, 50%, and 75% lines represented the lower quantile, median, and upper quantile of model-based estimates on count-level pollution emissions after adjusting for covariate effects during 1995 and 2015.Estimated spatial patterns of PM2.5 (left) and NOx (right) emissions.Statistical summaries on data and variables.ULDI: urban land development intensity; LD: Urbanization was measured by dividing the total luminosity of a county by its total area. ACLD: Available construction land of each county.Estimation results from the dynamic spatio-temporal pollutant emissions model.Note: the symbol “*” indicates statistical significance at the 95% credible interval. The columns labeled as “Median”, “2.5%”, and “97.5%” reported the median (i.e., the 50th percentile), the 2.5th percentile, and the 97.5th percentile of the estimated distributions of regression coefficients. A regression coefficient is statistically significant at the 95% credible interval if the 2.5th and 97.5th percentiles of the distribution of this parameter do not contain zero. DIC: Deviance information criteria.Model estimation results on the potential spatial heterogeneity effect in the relationship between urban expansion and pollutant emissions.Note: the symbol “*” indicates statistical significance at the 95% credible interval. A regression coefficient is statistically significant at the 95% credible interval if the 2.5th and 97.5th percentiles of the distribution of this parameter do not contain zero. Other covariates included in the previous models (Table 2) were also incorporated in the current model. Estimates on covariate effects were very similar to those reported in Table 2; hence, they were omitted to save space.Model estimation results of models where urban expansion is measured by nighttime light (NTL) data.Note: the symbol “*” indicates statistical significance at the 95% credible interval.

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+Air pollution is associated with premature mortality and a wide spectrum of diseases. Traffic-related air pollution (TRAP) is one of the most concerning sources of air pollution for human exposure and health. Until TRAP levels can be significantly reduced on a global scale, there is a need for effective shorter-term strategies to prevent the adverse health effects of TRAP. A growing number of studies suggest that increasing antioxidant intake, through diet or supplementation, may reduce this burden of disease. In this paper, we conducted a non-systematic literature review to assess the available evidence on antioxidant-rich diets and antioxidant supplements as a strategy to mitigate adverse health effects of TRAP in human subjects. We identified 11 studies that fit our inclusion criteria; 3 of which investigated antioxidant-rich diets and 8 of which investigated antioxidant supplements. Overall, we found consistent evidence that dietary intake of antioxidants from adherence to the Mediterranean diet and increased fruit and vegetable consumption is effective in mitigating adverse health effects associated with TRAP. In contrast, antioxidant supplements, including fish oil, olive oil, and vitamin C and E supplements, presented conflicting evidence. Further research is needed to determine why antioxidant supplementation has limited efficacy and whether this relates to effective dose, supplement formulation, timing of administration, or population being studied. There is also a need to better ascertain if susceptible populations, such as children, the elderly, asthmatics and occupational workers consistently exposed to TRAP, should be recommended to increase their antioxidant intake to reduce their burden of disease. Policymakers should consider increasing populations’ antioxidant intake, through antioxidant-rich diets, as a relatively cheap and easy preventive measure to lower the burden of disease associated with TRAP.Ambient air pollution is the greatest environmental risk factor for human health, being associated with considerable levels of mortality and morbidity worldwide [1]. Globally, air pollution has been estimated to result in 4.2 million premature deaths annually [1]. Traffic-related air pollution (TRAP) is a prominent source of ambient air pollution, and one of particular concern for human health [2,3]. It is estimated that almost 20% of the United States population lives near a high traffic volume road, the exposure to which disproportionately affects minorities and those with low socioeconomic status [4]. A 2015 study using spatial mapping techniques revealed that 24% of the population in Toronto (Canada), 41% of the population in New Delhi (India), 66% of the population in Beijing (China), 67% of the population in Paris (France), and 96% of the population in Barcelona (Spain) are exposed to higher levels of TRAP when compared to background concentrations [5]. TRAP originates from motorized vehicles that generate exhaust and non-exhaust emissions. Exhaust emissions are produced from the combustion of fuel in motorized vehicles [6]. Non-exhaust emissions result from tire, brake, and road wear particles in addition to resuspended dust. The exhaust and non-exhaust emissions contribute to ambient air pollution both by primary emissions and formation of secondary pollutants [7]. Common traffic-related pollutants include particulate matter with a diameter of 10 micrometers or smaller (PM10), particulate matter with a diameter of 2.5 micrometers or smaller (PM2.5), ultrafine particles (UFPs), nitrogen oxides (NOx), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), black carbon (BC), elemental carbon (EC), hydrocarbons (HCs), and volatile organic compounds (VOCs) [8]. In 2013, traffic was responsible for 38% of NOx emissions, 14% of VOC emissions, and 34% of all CO emissions in the United States [9]. NO2 and particles with smaller size ranges (e.g., UFPs) are hallmarks of traffic pollution, especially emissions from diesel exhaust. While disentangling the source of individual pollutants is challenging, BC and EC in particular, are commonly used as indicators of traffic in urban environments, given the high contribution of vehicles to combustion-derived emissions.The prominence of TRAP exposures is a major public health concern as they have been associated with many adverse health effects. In general, air pollution is associated with cardiovascular diseases, respiratory diseases and premature mortality [10]. Notably, there is substantial evidence supporting an association between exposure to air pollution and premature mortality. The seminal Harvard Six Cities study demonstrated the association between ambient concentration of particulate matter (PM), ozone (O3), SO2, and sulfates (SO4) and loss of life [11]. More specific to TRAP, other studies have documented associations between living near a major road and cardiopulmonary mortality [12], long term exposures to air pollution and cardiovascular mortality [13], lung cancer mortality [14], and mortality from strokes [15]. TRAP has furthermore been linked to pulmonary morbidity, including onset of asthma and exacerbation of asthma symptoms in children [16,17,18,19], increased risk for persistent wheezing in children [20], decreased lung function [21] and the development of chronic obstructive pulmonary disease in adults (COPD) [21,22]. Other adverse health effects associated with common traffic-related air pollutants include diabetes [23], increased blood pressure [24], hospital admissions for circulatory diseases, myocardial infarction, lung cancer, kidney cancer, low respiratory tract infections [25], respiratory hospital admissions [26,27], decreased bone density and osteoporosis-related hospital visits [28]. More recent studies have demonstrated a link between traffic-related air pollutants and neurological effects and disorders [29,30]. For example, exposure to PM10 and NO2 in children was associated with the childhood attention hyper deficit hyperactivity disorder (ADHD) diagnosis [31], and children exposed to elemental carbon attributable to traffic (ECAT) had increased depression and anxiety symptoms [32]. Emerging research reveals an association between TRAP and declines in cognitive function [32,33], lower scores on a cognitive reasoning tests [34], lower verbal learning performances, lower logical memory abilities and lower executive functioning [35]. Dementia incidence has also been associated with increased exposures to PM2.5 [36], NOx [37], NO2, and CO [30]. Furthermore, exposures to PM10 and O3 (which can be formed from the reaction of hydrocarbon emissions with sunlight) were associated with increased risk for Alzheimer’s disease and vascular dementia [38]. The widespread impact of TRAP warrants urgent strategies to mitigate its adverse health effects. There are many biological mechanisms by which different air pollutants can have adverse effects on the body. One prominent mechanism is oxidative stress: The formation of reactive oxygen species (ROS) beyond that which can be removed by cellular defenses, leading to the harm of cells and organs. Among ROS involved in oxidative stress are free radicals: forms of oxygen with unpaired electrons in the outer shell of their molecule, which lead to high levels of reactivity. Low levels of ROS play a natural role in cellular function by fine regulation of signaling and acting as a cellular defense mechanism for inflammatory cells where they are used to mediate inflammatory response and kill invading pathogens [39]. However, external stimuli, such as trauma, alcohol, medications, and exposure to radiation or toxins, can lead to an excessive amount of ROS, thus overcoming cellular defenses [40]. Air pollutants such as NOx, O3, PM2.5, and UFP are potent oxidants that are able to generate ROS and induce oxidative stress which can lead to cell death, inflammation, and injury [39,40]. Consequently, the promotion of oxidative stress has been identified as one of the most important mechanisms responsible for toxic air pollutant effects [41]. Fortunately, the body is equipped to handle a certain amount of oxidative stress. The term “antioxidants” refers to the biological chemicals and molecular systems that provide protection against oxidative stress. For example, the nasal cavity contains high levels of uric acid, a powerful antioxidant, and the lungs are lined with an extracellular antioxidant defense system comprised of reduced glutathione, ascorbic acid (vitamin C), uric acid, and alpha tocopherol (vitamin E) [40]. The excessive oxidative stress caused by pollutants can lead to the development of adverse health effects in the lungs and beyond, including decreased lung function, increased airway hyperactivity, pulmonary inflammation, damaged lungs and cell permeability [40]. Pulmonary effects can also progress to systemic effects through alterations in oxidative mediators and close interaction with inflammatory processes.Several studies have investigated oxidative stress as a mechanism for the adverse health effects of air pollution. Oxidative stress can be quantified through a variety of methods, including measurement of ROS-modified molecules, indirect biomarkers of oxidative stress and alterations in levels of antioxidant activity. These biomarkers have been used to demonstrate that air pollution exposures are associated with oxidative stress and inflammation in humans [42], with support and further mechanistic insight provided by preclinical studies [43]. In this context, antioxidants represent a potential preventive strategy for disease processes due to their ability to blunt the effects of oxidative stress. The Food and Drug Administration (FDA) defines antioxidants as substances that, following absorption from the gastrointestinal tract, participate in physiological, biochemical, or cellular processes that prevent free radical-initiated chemical reactions or inactivate free radicals altogether [44]. Antioxidant provision can occur through diet or supplementation. Diets rich in soy, fruits, vegetables, nuts, seeds, oils, whole grains, some spices, and compounds found in chocolate and wine are great sources of antioxidants [45]. An example of an antioxidant-rich diet is the Mediterranean diet. The Mediterranean diet is rich in antioxidants due to common consumption of fruits, vegetables, whole grains, healthy fats, nuts, and fish [46]. Furthermore, antioxidants may be consumed as a supplement, which typically take the form of an oral pill. Once ingested, the antioxidants are absorbed by the gastrointestinal tract, leading to systemic availability [44]. Many antioxidant supplements are available, including vitamin C, vitamin E, beta-carotene, omega-3 polyunsaturated fatty acids (PUFA) and selenium [47].A 2008 review addressed the potential of antioxidant diet and supplements for ameliorating the adverse effects of air pollution [48], and a more recent 2018 review discussed antioxidant use for the protection against the pulmonary effects of air pollution [49]. However, there is a need for an up-to-date literature review that holistically examines both antioxidant-rich diets and antioxidant supplements and for the various health outcomes associated with TRAP. The current review addressed this topic by compiling and analyzing the existing literature (until July 2019) on antioxidant-rich diets and supplements to mitigate adverse health effects of TRAP, in human subjects.This paper is not meant to be a systematic review of the evidence but rather an overview of studies we identified through a structured and up-to-date literature search and expert knowledge. Time and resource constraints did not allow for the completion of a systematic review. However, this non-systematic review provides a critical assessment of some of the studies on antioxidant-rich diets and antioxidant supplements that may mitigate the burden of disease associated with TRAP exposures. It also paves the way for more informed future reviews and systematic reviews. Our aim is that this summation of the evidence will be of use to researchers, public health practitioners, clinicians, policymakers, and other stakeholders with an interest in the health effects of TRAP and how to mitigate them.We searched the following databases and search engines: PubMed, Web of Science, Science Direct, Google and Google Scholar. We focused on literature published in the past 15 years by limiting the studies to only include those published between 1 January 2004 to 18 July 2019 (time of search). Relevant studies were identified using the following keywords and keyword combinations: “air pollution and health effects”, “health effects of air pollution”, “oxidative stress”, “oxidative stress and air pollution”, “antioxidants and air pollution”, “dietary intake and air pollution”, “Mediterranean diet and air pollution”, “dietary supplements and air pollution”, “dietary interventions and air pollution”, “antioxidant diet and air pollution”, “nutrition and air pollution”, “antioxidant polyunsaturated fatty acids”, “oxidative stress and antioxidant diet and air pollution”, “oxidative stress and antioxidant supplement and air pollution”, and “oxidative stress and antioxidant and air pollution”. Studies were exported to Mendeley reference manager software and any duplicates were removed. We also identified relevant reviews by expert knowledge.It is worth noting that animal studies, which may have provided more evidence on antioxidants and underlying mechanisms, were excluded from this review. We decided to focus on research in human subjects due to time and resources limitations, but also because mechanistic evidence has been reviewed elsewhere [50,51], and is beyond our primary expertise.We selected studies that met all the following criteria:
+      Were published peer-reviewed journal articles offering insight to the relationship between antioxidant-rich diet or antioxidant supplement interventions and the adverse health effects of TRAP, or markers thereof.Any design in human populations including cohort studies and clinical studies with controlled exposures.Were published peer-reviewed journal articles offering insight to the relationship between antioxidant-rich diet or antioxidant supplement interventions and the adverse health effects of TRAP, or markers thereof.Any design in human populations including cohort studies and clinical studies with controlled exposures.We excluded studies that were:
+      Animal studiesCell culture studiesPapers without an English translationPapers where full text was not availablePapers with pollutants or exposures not relevant to trafficAnimal studiesCell culture studiesPapers without an English translationPapers where full text was not availablePapers with pollutants or exposures not relevant to trafficJournal articles were first screened by title and abstract by J.B. Irrelevant articles were excluded while potentially relevant articles were retained. Potentially relevant articles were then screened again by reading their full text. Once again, irrelevant articles were excluded, and the remaining articles were retained for inclusion in this review. The reference lists of all articles were checked for additional relevant articles for inclusion. J.B. extracted data from included articles based on a predetermined template designed by H.K. and J.B. The data elements extracted and documented included: Study name and reference, study design, objective of the study, country of origin, population details, sample size, air pollutant(s) examined, nutrient or supplement intervention, analysis methods, key findings and notes/gaps. Other important and necessary information was extracted from articles’ supplementary materials. Data extraction was done manually by J.B. and independently checked by two other authors (50% by K.S. and 100% by H.K.). A narrative synthesis was conducted in order to summarize and discuss the findings of the included studies.The literature search yielded 11 studies that fit the inclusion criteria (Table 1). Three were cohort studies and 8 were randomized controlled trials (RCTs). Sample sizes in the cohort studies ranged from 208 to 548,845 subjects. Various age groups were studied: 1 of the cohort studies examined adults age 50 to 71 years old, another examined asthmatic children between the ages of 6 and 14 and the third cohort study examined infants who were between 11 and 23 months. Sample sizes in the RCTs ranged from 29 to 267 subjects. One investigated asthmatic children between the ages of 7 and 11 years old, 5 RCTs examined healthy adults over the age of 18, whereas two used a more elderly population (50 to 72 years or over 60 years). Of the 11 studies that fit the inclusion criteria, 3 cohort studies examined participants’ dietary patterns through a self-answered dietary assessment to score their fruit and vegetable intake or their Mediterranean diet adherence and 5 of the 11 studies examined the use of fish oil supplementation. Two of these 5 compared fish oil supplementation to olive oil supplementation. Fish oil is known to contain antioxidants and has beneficial action on several antioxidant/inflammatory pathways. Olive oil was used as a partial-control for fish oil, however, it should be noted that it contains oleic acid, which is a key component of the Mediterranean diet that possesses a degree of antioxidant and anti-inflammatory properties. Two of the 11 studies examined the use of sulforaphane through a broccoli sprout beverage. Finally, 1 study examined the use of a combined supplement of vitamin E and vitamin C. The included studies looked at the following air pollutants: PM2.5, PM10, concentrated ambient PM (CAP), NO2, O3, diesel exhaust particles (DEP) and benzene (Table 1). Of the 11 studies that fit the inclusion criteria, 4 were conducted in the United States, 4 in Mexico, 2 in China and 1 in Spain. Three studies addressed antioxidant-rich diets while 8 studies addressed antioxidant supplementation. In the following sections, we describe the evidence from the 11 included studies under key categories of antioxidant-rich diets and antioxidant supplementations.Fruits and vegetables are well known for being rich in nutrients and antioxidants. In a 2012 birth cohort study, Guxens et al. [52] analyzed the effects of antioxidants on infant mental development and its relationship to prenatal exposure to NO2 and benzene. Prenatal exposure to air pollution was assessed by passive samplers distributed over the study areas and land use regression models were developed based on these measurements to predict average outdoor air pollution levels for the entire pregnancy at each residential address. Mothers used a self-reported food frequency questionnaire (focused on fruit and vegetable intake) during their first trimester and whether the infant was breastfed through the second year of life. A single maternal fasting blood specimen was drawn during pregnancy (mean ± SD, 13.4 ± 1.7 weeks of gestation) and maternal plasma vitamin D levels were determined. Mental development in infants between 11 and 23 months was assessed using the Bayley Scales of Infant Development. The Bayley Scales of Infant Development is composed of 163 items that assess age-appropriate mental development, performance abilities, memory, and early language skills. The results demonstrated an inverse association between both NO2 and benzene exposure with mental development. The inverse association between pollutants and mental development was also found in infants who were not breastfed. Neither of these results were statistically significant. However, the study did result in a statistically significant inverse relationship between pollutants and mental development among infants with low maternal intake of fruits and vegetables. This study suggested that the antioxidants consumed from fruits and vegetables may inhibit the cognitive impairments in infants that might have resulted from maternal exposure to air pollutants, especially in mothers who have a low antioxidant intake.The Mediterranean diet is rich in antioxidants because it is rich in plant-based foods, such as whole grains, fruits and vegetables, and olive oil [62]. It also includes low consumption of meat, moderate alcohol consumption (generally in the form of wine) and fish [63]. This diet is associated with improved cardiovascular health, reduced inflammation and reduced oxidative stress responses [64]. A large cohort study conducted in the United States had 548,845 adults between the ages of 50 and 71 used a self-reported dietary questionnaire to formulate an alternative Mediterranean diet (aMED) score based on their dietary patterns [46]. Participants who reported greater adherence to the Mediterranean diet (i.e., had a high aMED score) had significantly lower rates of cardiovascular disease mortality associated with long-term exposure to NO2 and PM2.5, where long term exposure to air pollutants was determined as annual average concentration levels from 1994 to 2010. This supported the idea that greater adherence to the antioxidant-rich Mediterranean diet may blunt the adverse cardiovascular effects from air pollution exposure. Similarly, a dynamic panel cohort study of 208 children in Mexico City analyzed the relationship between fruit and vegetable intake (FVI) and Mediterranean diet index (MDI) with lung function and airway inflammation. Readings from the closest fixed site monitoring station were assigned to the child’s residential address and used to estimate their exposure to PM2.5, NO2, and O3. Children were followed for 22 weeks, with their pulmonary function measured every 2 weeks, and their nasal lavage was collected and analyzed for inflammatory markers. Asthmatic children with a higher FVI scores had statistically significant lower interleukin-8 (a mediator of inflammation, IL-8) in their lavage after exposure to PM2.5, NO2, and O3. Children who had high FVI scores had 8% lower IL-8 than children with low FVI scores. Furthermore, asthmatic children who had higher MDI scores had significantly higher lung function after exposure to PM2.5, NO2, and O3 [53]. Children with the highest MDI scores had a 15.3% higher forced expiratory volume in one second and 16.5% higher forced vital capacity than children with lower MDI scores, which indicates increased lung functioning in those with higher MDI scores [53]. However, no statistically significant protection from inflammation and reductions in lung function were found in the non-asthmatic children.Fish oil and (to a lesser extent) soy oil have anti-inflammatory effects and have been shown to reduce ROS generation and mitigate the oxidative stress response from stimuli, including air pollution [65]. In a randomized, double-blinded, controlled trial, the effects of fish oil were compared to the effects of soy oil in 50 nursing home residents (all >60 years old) who had been exposed to elevated levels of PM2.5 from the ambient air. The participants spent 93% of their time indoors, and the mean levels of ambient PM2.5 in the room where the study was conducted was 18.6 µg/m3 (24 h average). This study was in Mexico City, where the major source of PM2.5 pollution is vehicular traffic and a large proportion of vehicles use diesel fuel. The mean levels of ambient PM2.5 outdoors during the study period was 19.6 µg/m3 (24 h average). Participants were given either 2 g of soy oil per day (control) or 2 g of fish oil per day with a 6-month monitoring period (1-month pre-supplementation and 5 months supplementation). In the pre-supplementation phase, the group receiving fish oil supplements experienced a 54% reduction in parameters of heart rate variability (HRV); high frequency log10-transformed HRV associated with a 1 standard deviation change in PM2.5 exposure. During the supplementation phase, this reduction was 7%. Participants who were given 2 g of fish oil supplements per day experienced a statistically significant reduction in their heart rate variability (HRV) decline after being exposed to PM2.5. On the other hand, participants who were given soy oil supplements experienced marginal and non-significant changes in HRV after PM2.5 exposure [54]. Decreased HRV has been associated with increased mortality from sudden death and ventricular arrhythmia in both healthy and diseased individuals [57], thus the fish oil supplement suggest a beneficial effect whereas the soy oil did not.In another RCT conducted by the same authors [55], 52 participants from a nursing home were given similar supplements of fish oil or soy oil for 4 months. Participants spent 93% of their time indoors where they were chronically exposed to ambient PM2.5 with a mean daily concentration of 38.7 µg/m3. Both fish oil and soy oil groups increased plasma levels of superoxide dismutase (SOD) activity and increases in levels of reduced glutathione (GSH) demonstrating systemic efficacy of the antioxidant supplements (both SOD and GSH are key antioxidant mediators). Additionally, the fish oil, but not the soy oil, group showed decreases in levels of lipoperoxidation (LPO), a marker of oxidative stress. A similar randomized, double-blinded, placebo-controlled trial in China analyzed the extent to which fish oil supplements (2.5 g per day) would protect against cardiovascular damage as a result of PM2.5 exposures. The participants were 65 healthy, college students (20 to 25 years old) who underwent a 5-month supplementation phase with 4 rounds of follow up visits with an interval of 2 weeks in the last 2 months of the intervention. In this study, the placebo group was given sunflower seed oil. There was greater levels of oxidative stress (higher levels of ox-LDL and lower activities of antioxidant capacity), inflammation and coagulation biomarkers, as well as endothelial dysfunction (higher levels of endothelin-1 and E-selectin, and lower levels of concentration of serum eNOS protein), and neuroendocrine disturbance in the placebo group compared to the fish oil supplement group [56].Another RCT conducted in the United States found that healthy individuals (20 participants aged 50 to 72) given fish oil supplements (3 g per day) for 4 weeks prior to sequential 2 h chamber exposures to CAP and ultrafine particulate matter (mean: 278 ± 19 µg/m3), were protected from autonomic, cardiac electrophysiological, and lipid changes [57]. Cardiac electrophysiological changes were measured through HRV and cardiac repolarization while lipid levels and blood cells were analyzed to indicate lipid changes. Participants who received a similar olive oil supplement were unprotected from cardiac electrophysiological and lipid changes. Fish oil supplementation attenuated CAP-induced reductions in high frequency/low frequency ratio and elevations in normalized low-frequency HRV. Furthermore, participants who consumed olive oil supplements experienced significant increases in their normalized low-frequency HRV immediately after exposure to CAP, which persisted for at least 20 h, while those given the fish oil supplements did not experience any significant alteration in HRV in response to CAP exposures [57]. Furthermore, one RCT investigated the effect of olive oil compared to fish oil in mitigating endothelial dysfunction (a marker and risk factor for cardiovascular disease) and coagulation markers in response to a two-hour controlled exposure to CAP (mean: 253 ± 16 µg/m3, by drawing ambient air from above the roof and passing it through a 2-stage aerosol Harvard concentrator that produces up to a 30-fold increase in particle number and mass) in 42 middle-aged volunteers. Participants who consumed 3 g of olive oil per day for 28 days experienced a statistically significant increase in flow mediated dilation and increases in fibrinolysis blood markers which indicate a protective effect to attenuate vascular effects of exposure to CAP. This effect was not seen in participants consuming 3 g of fish oil per day [58]. These results warrant further investigation because other studies found that fish oil supplements provided protection from air pollutants. Sulforaphane is a molecule often found in cruciferous vegetables, such as broccoli, that has anti-inflammatory and antioxidant properties [66]. Due to its antioxidant nature, sulforaphane has been investigated for its ability to mitigate the adverse health effects of TRAP. Previous research conducted to investigate the effects of sulforaphane on the expression of oxidative stress genes revealed that sulforaphane had detoxification properties that could provide protection from the harm brought on by air pollutants [67].A single blinded, placebo-controlled trial was conducted to analyze the effects of standardized broccoli sprout extract on nasal inflammatory response after exposure to DEP. DEP exposures of 300 µg in an aqueous suspension were administered from a dilution tunnel constant volume sampler. A standardized dose of 100 micromolar sulforaphane broccoli sprout extract in mango juice was given to 29 healthy adult participants for four consecutive days. Participants consuming the juice exhibited a lower inflammatory response (white blood cell counts) to the DEP compared to the control. [59]. Another randomized, placebo-controlled trial in China investigated whether daily consumption of a broccoli sprout beverage for 12 weeks could ameliorate the detrimental effects of benzene exposure. Participants who received the broccoli sprout beverage had a statistically significant higher urinary S-phenyl mercapturic acid (SPMA) and hydroxypropyl mercapturic acid (3-HPMA) excretion [60]. SPMA and 3-HPMA are markers for exposure to benzene air pollution because they are levels of mercapturic acids formed in the metabolism of benzene. These levels increase as a result of benzene exposure. Increased level of excretion of SPMA and 3-HPMA indicates that the broccoli sprout beverage enhanced detoxification of pollutants. While the broccoli sprout beverages prove to be useful in mitigating the adverse effects associated with the exposures to DEP and benzene, participants in the studies often complained of the beverage’s bad taste, and some experienced nausea from the drink.Vitamin C and vitamin E have been the focus of several studies due to being inexpensive antioxidants that are widely taken as supplements across the world. In a randomized, double blinded, placebo-controlled trial conducted in Mexico, asthmatic children (7 and 11 years) were given a supplement comprising of 50 mg vitamin E and 250 mg vitamin C with measurements of nasal lavages were taken 3 times during a 4 month follow up and analyzed for content of interleukin-6, IL-8, uric acid, and glutathione. Children who received the placebo had statistically significant increases in interleukin-6 (IL-6; a marker of inflammation) in nasal lavage that was associated with O3 and PM10 exposure, while children receiving the antioxidant supplement did not [61]. However, the study did not account for information regarding allergens, which limits the results. This literature review provides evidence that antioxidant-rich diets and antioxidant supplements can protect against the adverse health effects associated with exposure to air pollution, and specifically, TRAP. The evidence is largely consistent and originates from RCTs with relatively small numbers of volunteers and a limited number of population-based cohort studies. The data suggests that increased antioxidant intake, whether it be through diet or supplementation, can blunt the adverse health effects of exposure to common traffic-related air pollutants. However, the number of studies investigating this question is rather small (11) and further research is required to replicate and confirm previous findings.Antioxidant-rich diets, such as the Mediterranean diet and increased fruit and vegetable intake, gave the most promising evidence for protection from TRAP. On the other hand, the benefits of olive oil, a feature of the Mediterranean diet, were inconsistent between studies. These results warrant further research in order to determine the effectiveness of olive oil in mitigating adverse health effects from TRAP exposure. In contrast, fish oil supplements provided more consistently effective results in mitigating the effects of TRAP. Fish oil supplements are relatively cheap and can be accessed easily without prescription. In addition to taking fish oil supplements, people could also increase their intake through diet by consuming fish rich in oils (n-3-PUFA). Fish that are rich in n-3-PUFA include sockeye salmon, farmed trout and salmon, Copper River salmon, Coho salmon, bronzini, and toothfish [68]. The effective dose of fish oil (in diet or as supplements) requires further research. Broccoli sprout beverages containing sulforaphane also mitigated the adverse health effects of TRAP exposure, albeit only two studies that were identified. However, people may be unlikely to consume a broccoli sprout beverage regularly if they dislike the taste or experience side effects such as mild gastrointestinal upset [59]. Finally, vitamin C and vitamin E were investigated in one study and were found to reduce inflammation associated with air pollution exposure. While the evidence suggests that vitamin C and E supplements may be useful in providing protection from TRAP, the overall findings of large clinical trials of these antioxidants assessing mortality and clinically-relevant end-points have been disappointing [69]. Concerningly, a meta-analysis of 19 clinical trials using vitamin E supplements found that high doses (≥400 IU/d for at least 1 year) of vitamin E may even increase all-cause mortality [70]. Vitamin C and E should therefore not be taken in high doses and consumed with precaution until there is more research to determine their effective dose to protect from pollutants. For all anti-oxidants identified in the literature, more research is needed to determine their appropriate dosages. Once the effective dose for each of these supplements is determined, they could offer a relatively cheap and accessible method to increase antioxidant intake, thus increasing protection from TRAP. Other factors to be considered when investigating the effectiveness of antioxidant supplementation would be the time the antioxidant is consumed, duration of supplementation, the balance between diet and supplementation, the amount of antioxidants that reach the bloodstream and whether or not antioxidants reach the areas of disease or subcellular locations. Further points of interest include what formulations can be used to increase bioavailability of antioxidants, whether formulations can be used to target specific organs or diseases, whether antioxidants combat only some parts of the disease pathways and not others, if are antioxidants useful for specific patient subgroups and not others, and finally, whether combinations of antioxidants needed to fully target multiple free radicals and disease processes.Based on the results of this review, increasing people’s fruit and vegetable intake as well as encouraging adherence to the Mediterranean diet seem to be the most promising strategy. In addition to offering protection against TRAP effects, dietary interventions are associated with other co-benefits, such as reduced mortality and reduced risk of diseases overall by decreasing the inflammatory response associated with exposure and mitigating oxidant damage to cell structures [69]. Furthermore, dietary changes that increase antioxidant intake should be encouraged for all people, and especially for susceptible populations such as children, the elderly, asthmatics and those who are occupationally exposed to TRAP. Those who suffer from preexisting chronic conditions and chronic inflammation [48] and those who have damaged or weakened antioxidant defense systems may be more susceptible to oxidative stress [71]. Children are also a susceptible population because their organ systems are still developing, and therefore there is a greater cellular susceptibility to oxidative stress. Likewise, elderly persons have an increased susceptibility due to weakened immune and detoxification systems. Transportation workers, taxi drivers, construction workers, and street vendors may experience greater exposures to TRAP due to their occupational location and/or type of work. Indeed, a study revealed that taxi drivers had higher levels of oxidative stress biomarkers, increases in pro-inflammatory mediators and an increased risk for cardiovascular events, compared to non-occupationally exposed persons [72]. Genetic abnormalities can also engender greater susceptibility to more oxidative stress [73]. Polymorphisms in genes involved in oxidative stress such as NAD(P)Quinone oxidoreductase 1 (NQO1) and glutathione-S-transferase (GSTM1 or GSTP1) have been found to alter response to pollutants. For example, genetic variations in these genes led to a greater nasal inflammation, increased airway epithelial damage, and higher levels of oxidative stress in response to O3 exposure [73]. It is worth noting that 5 of the 11 articles included in this review investigated populations of potential susceptibility. Two RCTs enrolled elderly participants, 1 RCT enrolled asthmatic children, 1 cohort study investigated children, and 1 considered prenatal exposures of infants.The findings of this literature review are consistent with findings of previous relevant studies. For instance, a RCT in 80 adults in Brazil investigated the effect of antioxidant supplementation (6 month of 500 mg of vitamin C and 800 mg of vitamin E) on biomarkers of oxidative stress linked to PM exposure originating from coal combustion emissions [74]. While this study is specifically not a TRAP exposure, there are similarities between the health effects of both these combustion-derived emissions and their pathways of action. Level of exposure was determined by whether people were directly exposed (those who handle the mineral coal), indirectly exposed (office workers of the electric power plant 200 m from the burning area), residents (subjects living in the city 2 kilometers from the burning area) or non-exposed subjects (controls who lived 100 km from the emissions). After taking the antioxidant supplement for 6 months, participants in all groups who were exposed to PM emissions (direct exposure, indirect exposure, and residents) had similar levels of biomarkers of oxidative stress as the control group [74]. Older studies before time frame for this literature review’s search criteria also present evidence that antioxidant supplementation can mitigate the adverse health effects of air pollution. A controlled trial in the Netherlands, investigated the use of a supplement (650 mg of vitamin C, 75 mg of vitamin E and 15 mg of beta carotene) in 26 young amateur cyclists exposed to O3. The cyclists who took the supplement experienced no effect from the O3 exposure on lung function (forced expiratory volume in one second, forced vital capacity, peak expiratory flow, and maximal mid expiratory flow) while the control group that received a placebo had adverse responses to O3 [75]. A double-blinded randomized trial in 158 children with asthma in Mexico City investigated the use of daily supplementation (50 mg of vitamin E and 250 mg of vitamin C). This study revealed that daily antioxidant supplementation provided protection against exacerbation of asthma symptoms from O3 and NO2 exposures [76]. Both studies provide more evidence supporting the claim that vitamin E and vitamin C can mitigate pulmonary decrements after exposure to traffic-related air pollutants and secondary pollutants (e.g., O3 which is promoted by traffic-related emissions).We did not intend this literature review to be an all-inclusive review of antioxidant interventions studied in relation to air pollution. Instead, we focused on human studies in the last 15 years, to provide a summation of recent findings that have relevance to TRAP and highlight key research findings and gaps from the most up-to-date evidence base. We acknowledge that the current review was non-systematic, searching specific databases and being limited to the last 15 years. Conducting a systematic review is likely to identify further evidence and potentially different conclusions. Furthermore, there is a substantial body of preclinical data from animals and cellular models that could provide useful mechanistic insight into the human observations. Another potential limitation of this review stems from the limitations of the studies analyzed and the methodologies employed in the included papers. For example, RCTs are not representative of the combination of TRAP exposures people experience in the real-world. Instead, they are usually limited to specific pollutants being tested in each experiment through controlled exposures. On the other hand, there are many benefits of controlled exposure studies over real-world investigations due to their ability to control exposures at specific rates over specific time periods and the minimization of bias, especially selection bias and confounding. Another limitation relates to the exposure assessment in the included studies. Often, exposure assessment was based on a fixed monitoring network rather than a personal monitor, which could lead to exposure misclassification. The increased availability of more accurate lower-cost personal sensors will allow gathering of more accurate individual exposures, or at the very least offer insight into the potential uncertainty arising from use of fixed monitoring data. The literature identified considered studies conducted in different geographic areas, which provides some benefits in terms of ascertaining the generalization of the observed effects in different populations. However, it also introduces other factors that could be confounders (e.g., different air pollution mixtures in different regions, genetic background, socioeconomic variables, differences in diet, and compliance for taking supplements). Finally, in several of the antioxidant supplement studies, some aspects of participants’ diets were not controlled for or only adjusted for at baseline, with no tracking of changes over the follow-up period. This short review raises the need for a systematic review of literature on this topic, however, it also allows us to make recommendations for practical research topics. We recommend that future studies specifically investigate the effects of antioxidants on vulnerable populations, such as children with asthma, the elderly, certain occupational workers and people with genetic susceptibility as these subpopulations may benefit the most from targeted dietary or supplemental interventions. Although several of the studies identified did focus on susceptible populations, it would be beneficial to expand the literature regarding those who experience increased responses to TRAP and specifically investigate genetic susceptibilities possibly in different ethnic populations. In the included studies, many participants were generally healthy adults. While healthy adults are also at risk of the adverse effects of TRAP, young and healthy adults may be more likely to consume better foods and be more active than the general population, which could influence exposure and response to pollutants and antioxidants [46]. Furthermore, this review warrants more detailed research regarding the role that obesity may play in the adverse health effects associated with TRAP. Obesity continues to be a major threat to health and contributes to other TRAP health effects listed in this review, such as asthma [77]. A vulnerable population that has not been discussed in the literature is lower socioeconomic status individuals. These populations exhibit a variety of factors which might heighten their risk of adverse health effects from TRAP exposures, including exposure to violence, stress, reduced access to health care and poor diet [78]. Additionally, there is a need for further investigation on the effective dose of antioxidant supplements, as well as a greater insight into reasons for conflicting results regarding the effectiveness of different antioxidant diets (e.g., fish oil and olive oil). Future research would also benefit from control for confounding effects from daily dietary intakes and changes in diet over follow-up. It should be noted that curcumin, an Asian spice that has antioxidant properties, was not included in this review. A meta-analysis suggests that the antioxidant properties of curcumin could mitigate depressive and anxiety symptoms in patients [79]. Therefore, future research could be aimed at investigating the potential for curcumin to mitigate the burden of disease caused by TRAP. Finally, more research could be undertaken to evaluate the potential of antioxidants in mitigating air pollution effects in other organs or diseases of the body than were discussed in this paper.Policy makers should continue to pursue legislation that would reduce levels of TRAP. In 2016, 91% of the world’s population still lived in areas that exceeded the World Health Organization air quality guideline values [80], which are even too high to fully protect public health. However, until the long-term goal of cleaning the air can be met, policy makers could consider the use of antioxidant-rich diets, and to a lesser extent supplements, as a means of mitigating adverse health effects associated with TRAP. For example, schools in highly polluted areas may be incentivized to serve lunches that are antioxidant rich. Simple changes to a school lunch menu could be serving oil rich and organic fish at least once a week and increasing the organic fruits and vegetables at every meal. Furthermore, nursing homes and other care facilities for older adults should consider employing the use of antioxidant-rich diets. In addition to the Mediterranean diet reducing inflammation and mitigating adverse health effects of TRAP, there is evidence that the Mediterranean diet supplemented with extra virgin olive oil and mixed nuts can reduce age related cognitive decline in the elderly [81]. Such evidence might be applicable to the increasing body of evidence showing that air pollution, and TRAP specifically, is linked to cognitive decline [33,34,35,82]. It is important to address TRAP in particular as vehicles are one of the major sources of ambient air pollution, which specifically act in close proximity to an increasing proportion of people, thus making the adverse impacts of TRAP exposure widespread [78,80].Clinicians and health practitioners should encourage their clients to consume an antioxidant-rich diet and increase their organic fruit and vegetable intake, especially for children, elderly, pregnant women, and asthmatics. A cost-effective population-based intervention would be to bring awareness to the importance of dietary practices. Furthermore, occupations that are chronically exposed to TRAP, such as construction workers, transportation workers, and street vendors, should recommend or incentivize their employees to increase their nutritional or supplemental antioxidant intake. Raising awareness in dietary health benefits can be provided relatively easily, for little cost and in a manner that goes hand-in-hand with improving education for all on the health risks of air pollution.Antioxidants may reduce the effects of oxidative stress because they can remove oxidizing agents and inhibit oxidation. Because of this, an antioxidant-rich diet or antioxidant supplement intake can potentially be used as a preventive strategy for the harmful health effects of TRAP. In this literature review, we identified 11 papers in the last 15 years that considered the potential benefits of increased antioxidant intake through diet or supplementation on mitigating the adverse health effects of exposure to common traffic-related air pollutants. Antioxidant interventions investigated ranged from adherence to the Mediterranean diet, increased fruit and vegetable intake, consumption of fish oil and olive oil, sulforaphane intake via broccoli sprout beverages, and vitamin C and E supplements. Major points to note from the literature include fruit and vegetable rich diets, the Mediterranean diet, fish oils and vitamin C and vitamin E provide protection from the adverse health effects associated with TRAP. Greater adherence to a diet rich in fruits and vegetables or the Mediterranean diet was effective in reducing the adverse health effects associated with TRAP and had no negative effects associated with them. While there are inevitably inconsistencies in the findings, the overall weight of evidence suggest that antioxidant intake can ameliorate the effects of TRAP in different organ systems. There is good evidence to recommend that healthy and susceptible individuals should practice greater adherence to the Mediterranean diet and increase their fruit and vegetable intake. There is conflicting evidence regarding the use of antioxidant supplements and thus a need for more research focusing on antioxidant supplementation. Future research should focus on conducting cohort studies to analyze long-term effectiveness of antioxidants in studies that are representative of real-world exposures and with better control for confounders. Given the near ubiquitous exposure to pollution worldwide, and the huge impact on health, these findings have relevance to the general public, but also to health practitioners, clinicians, employers and policymakers seeking to limit the burden of air pollution on health. Specifically, susceptible populations including asthmatics, elderly and those with genetic variations should increase their antioxidant intake in order to attenuate the adverse health effects associated with air pollution and TRAP exposures. In conclusion, until lower levels of TRAP are achieved, antioxidant-rich diets and supplementation may offer promise for reducing the burden of disease associated with TRAP exposures.H.K. conceived the idea and design of this literature review. J.B. conducted the literature review and drafted the paper. H.K. and J.B. independently conducted all data extraction. K.S. independently checked 50% of all data extraction. M.R.M. provided critical analysis of the summarized evidence and manuscript. All authors have read and agreed to the published version of the manuscript.This study was partly funded from the Texas A & M Transportation Institute’s Center for Advancing Research in Transportation Emissions, Energy, and Health, a U.S. Department of Transportation’s University Transportation Center, College Station, TX. The grant number is 69A3551747128. More information about the Center for Advancing Research in Transportation Emissions, Energy, and Health is available at: https://www.carteeh.org/. M.R.M. is funded by the British Heart Foundation (CH/09/002).None of the authors have a financial relationship with a commercial entity that has an interest in the subject of this manuscript. Characteristics of the included studies.

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+Veterinary students across the United States face the challenge of stress during school every day. When managed improperly, stress can become chronic and manifest in physical and emotional consequences. The purpose of this study was to examine the utility of the multi-theory model (MTM) of health behavior change in predicting the initiation and sustenance of stress management behaviors among veterinary students. A cross-sectional design was used to study the efficacy of the MTM in predicting initiation and sustenance of stress management behaviors among veterinary students at a private College of Veterinary Medicine in the Southeast United States. Researchers collected data using a 54-item valid and reliable survey. Only students who did not already engage in daily stress management behaviors were included in the study. After recruitment and exclusion, a total of 140 students remained and participated in the study. Hierarchical multiple regression revealed that, for initiation of stress management behaviors, 49.5% of the variance was explained by depression, academic classification, and behavioral confidence. Regarding sustenance of stress management behaviors, 50.4% of the variance was explained by perceived stress, depression, academic classification, and emotional transformation. MTM serves as a promising framework for predicting initiation and sustenance of health behavior change. Based on the results of this study, interventions aimed to promote stress management behaviors in veterinary students should focus on the MTM constructs of behavioral confidence and emotional transformation.Stress is defined as a psychosocial and biochemical human reaction to situations that may elicit feelings of anxiety or fear [1]. In moderate amounts, sometimes stress can be beneficial and even promote learning opportunities among students [2]. For example, a moderate amount of stress to perform well on an exam may encourage students to spend more time studying. However, extreme amounts of exposure to stressors or misjudged perception of stressors may become debilitating, causing a wide range of negative consequences on the affected individual [2]. Negative consequences of stress manifest in both emotional and physical changes. Emotional effects include anxiety, anger, irritability, and depression [1,2,3]. Physical consequences of stress include weight loss, changes in sleeping habits, increased heart rate, difficulty breathing, and digestive problems [1,2,3]. Furthermore, stress has been identified as a risk factor for numerous chronic conditions, including heart disease, cancer, respiratory illness, and cirrhosis of the liver [4].The concept of stress is widely prevalent in veterinary education and veterinary medical clinics worldwide [5,6]. Program rigor, competition among peers, emotional fatigue, and high debt load faced by graduates all contribute to a stressful environment throughout veterinary schools [7]. Studies have shown that nearly 38% of veterinary students each year report feeling depressed [5]. This statistic is high when compared to non-veterinary student populations [8]. After veterinary school, in the veterinary medical field, stress levels remain high. Since leaving their educational programs, studies show that 14.4% of male and 19.1% of female veterinarians report having considered suicide due to emotional fatigue and depression caused by workplace stress [9]. Chronic or persistent stress in veterinary school can have severe impacts on student learning by interfering with concentration, decision-making ability, and emotional wellbeing [5]. Veterinary academic institutions must address the problem of stress among students to effectively promote quality learning and prevent negative consequences of stress, such as elevated suicide rates, post-graduation.Perhaps the simplest solution to the problem of stress among veterinary students is stress-management training or teaching anxiety-reducing behaviors to students during school. This could be performed via numerous mechanisms—utilizing school counselors, external specialists, or even outreach programs orchestrated within the student body [10,11,12]. One study found evidence that practicing a mindfulness intervention as an anxiety-reducing behavior may temporarily lower stress levels in veterinary students [11], and another found that encouraging a growth mindset, instead of a fixed mindset, helps students to appropriately handle stressful situations [12]. While these strategies appear promising, studies have also found that veterinary students are often reluctant to seek counseling and medical attention for mental health problems, possibly due to a negative stigma associated with mental health issues [13]. This reluctance to seek help makes anxiety-reducing interventions difficult to implement at veterinary schools. Additionally, researchers have recommended various socio-behavioral models for promoting behavior changes among students. The health belief model, transtheoretical model, and PRECEDE–PROCEED model are three of the most commonly recommended models [14]. However, these models are not adequate for promoting health behavior change among veterinary students specifically for multiple reasons. The health belief model focuses more on short-term behavior change than long-term change. Given the problems with continued stress and elevated suicide rates after school, a long-term focus is essential for interventions with veterinary students. The transtheoretical model is not specific toward health education, making it less suitable for use in anxiety-reducing behaviors. Finally, the PRECEDE–PROCEED model is too broad to be pragmatic for application and testing in veterinary practice [14,15].Recently, Sharma has taken note of the limitations of previous health behavior theoretical models and proposed a fourth-generation theoretical model called the Multi-Theory Model of Health Behavior Change (MTM) [14,16]. The MTM model incorporates multiple different socio-behavioral theories, highlighting the strengths of each and bringing them together into a model of two components—initiation and sustenance of health behavior change. This model has already been tested on college student populations regarding the prediction of initiation and sustenance of health behavior changes such as a reduction in binge-drinking, increase in eating fruits and vegetables, improvement in sleep behaviors, increased physical activity, and portion size control [17,18,19,20,21]. Ideally, the MTM should work well among veterinary students for predicting initiation and sustenance of health behavior change because it is both specific for health education and sustainable for long-term change. Within this backdrop, the objective of this study was to examine the utility of the MTM in predicting the initiation and sustenance of stress management behaviors among veterinary students.As mentioned previously, the MTM model of health behavior change is based on two interlinking components: initiation (i.e., one time) and sustenance (i.e., continuation) of health behavior change. Each of the two components, initiation and sustenance, are composed of three unique constructs. The constructs for initiation of health behavior change are as follows: participatory dialogue, behavioral confidence, and changes in the physical environment. Participatory dialogue involves two-way communication between a health educator and a subject that focuses on the advantages and disadvantages of initiating a health behavior change. Behavioral confidence, named on the basis of its simplicity and cultural specificity, focuses on a subject’s confidence to change health behavior in the future specifically, not in present day. Finally, “changes in the physical environment” construct emphasizes that the subject must modify his/her physical environment to make resources that support health behavior change more readily available. The constructs for sustenance of health behavior change are the following: emotional transformation, practice for change, and changes in the social environment. Emotional transformation involves focusing one’s feelings and emotions on health behavior change and channeling thoughts toward sustaining the change. Practice for change focuses on reflective actions, during which the subject thinks about his or her health behavior change. One mechanism in which subjects may embody practice for change is by using a journal or diary daily to track progress. Lastly, the construct “changes in the social environment” involves surrounding oneself with a firm support system that encourages health behavior change. Using these six constructs, empirical support thus far in support of the MTM leads us to believe that one can successfully initiate and sustain a health behavior change regarding stress-management behaviors [14].Researchers utilized a cross-sectional study design to investigate the efficacy of the MTM model in predicting initiation and sustenance of anxiety-reducing behaviors among veterinary students at a private University in the Southeast United States. Independent study variables were the previously described MTM constructs, while dependent variables were the intention to initiate and the intention to sustain relaxation behaviors. Students were eligible to participate in the study if they were currently enrolled veterinary students at the University and were not already engaging in twenty minutes or more of relaxation behavior per day. Due to the nature of this study focusing on health behavior change, students already participating in relaxation behaviors were excluded from the study. Following initial recruitment, three hundred and forty-two students of veterinary medicine consented to participate in the current study. After exclusion of those currently engaging in intentional relaxation behaviors, 140 students remained and were included as participants of this study.Data collection occurred via a 54-question online survey administered to participants through email, and collection took place over a three-week period with two reminder emails. All participants were over the age of 18 and gave informed consent before completing the survey. This study was granted ethics approval by institutional review board (IRB) at the Lincoln Memorial University (protocol number: 661 V.0).The survey instrument consisted of 54 items. The first 10 items assessed students’ current perceived stress levels using the perceived stress scale [22], with questions such as “In the last month, how often have you felt nervous and ‘stressed’?” The next 4 items assessed Anxiety and depression using the four-item patient health questionnaire (PHQ-4) [23]. Items 15–23 identified demographic characteristics such as age and marital status, and item 24 determined eligibility by asking about current relaxation behavior practice. The remaining 30 items focused on the MTM constructs for both initiation and sustenance of relaxation behavior. Advantages and disadvantages of participatory dialogue were gauged with 5 items each, all of which were scored on a 5-point scale. The disadvantage score was subtracted from the advantage score to give a final score for the construct. Behavioral confidence was gauged with 5 items focused on confidence in practicing relaxation behavior despite various challenges (“being busy”, “not enjoying it”, etc.), and 3 items gauged changes in the physical environment in a similar manner. The emotional transformation was gauged using 3 items, such as “How sure are you that you can motivate yourself to practice relaxation for 20 min daily?” Items 47–49 assessed practice for change by asking about keeping a journal and adjusting plans to make time for relaxation behavior. “Changes in the social environment” construct was gauged using 3 items as well with questions such as “How sure are you that you can get the help of a friend to support you with practicing relaxation for 20 min daily?” Items 53 and 54 assessed the initiation and sustenance, respectfully, by asking “How likely is it that you will practice relaxation for 20 min daily in the upcoming week?” (53) and “How likely is it that you will practice relaxation for 20 min daily from now on?” (54). For all construct questions, answered were scored on a scale of 0–5, with higher scores associated with higher likelihood of initiation/sustenance of behavior change.Face, content, and construct validity were all established for the survey instrument used in the study. Face and content validity were determined by utilizing six experts in the field, while construct validity was determined using confirmatory analysis with the maximum likelihood method. The maximum likelihood method gave 1-factor solutions for each subscale, all of which matched criteria of factor loadings over 0.32 and Eigen values over 1.0. Cronbach’s α was used to establish internal consistency of the survey instrument, with acceptable reliability denoted as a Cronbach’s α value of ≥0.70 [24].Descriptive statistics were performed for all variables. The dependent variables, intention to initiate and to sustain relaxation behaviors, were calculated on a continuous scale. To assess statistically significant relationships between demographic covariates and MTM variables of interest, Pearson Product-Moment correlations were performed for continuous variables and independent samples t-tests were performed for categorical variables. Analyses were performed to determine the utility of MTM in predicting intention to both initiate and to sustain relaxation behaviors in two separate models, model 1 and model 2. In model 1, initiation, independent variables were participatory dialogue, behavioral confidence, and changes in the physical environment. In model 2, sustenance, independent variables were emotional transformation, practice for change, and changes in the social environment. For both models, researchers first determined statistically significant demographic covariates and entered them into block 1. Hierarchical multiple regression was then performed among the significant covariates and the independent variables (MTM constructs, entered into block 2) for each model. All statistical analyses of data were completed using IBM SPSS statistical software version 25.0 with a significance level of 0.05.The vast majority of participants were females (92.9%), with approximately 88% identifying as White/Caucasian, Table 1. Little representation by racial minorities was observed in this study. As this study was conducted in rural Appalachia, this low representation of non-White ethnic groups may not be surprising. The majority of participants were second-year students (30.7%), followed by third-year (26.4%), first-year (25.0%), and fourth-year (17.9%). Participants generally held high grade point averages with more than 70% having a GPA (grade point average) above 3.0, which is not uncommon among medical programs. Furthermore, most participants were not married (80.0%), reported no children (95.7%), were not employed (88.6%), and resided off campus (95.0%). The average stress level of the participants was 21.64 (SD: 6.49, possible range 0–40). Sixty percent of the participants screened positive for anxiety, and 32.9% screened positive for depression.To examine the relationship between MTM constructs and the initiation and sustenance of relaxation behaviors, hierarchical multiple regression models were constructed. Step one of these regressions controlled for the variables perceived stress, depression, and academic classification, as each displayed significant bivariate relationships with both initiation and sustenance of relaxation behavior. Descriptive statistics and reliabilities for specific MTM variables can be seen in Table 2.For initiation of intentional relaxation behavior, 15.9% of the variance in initiation was explained by the lower-order terms forming the base model (R2 = 0.159, p < 0.001), Table 3. Herein, significance was observed for depression (b = −0.413, p = 0.040) and academic classification (b = −0.597, p < 0.001). Variance accounted for increased to 49.5% with the inclusion of MTM constructs in model 2 (R2 = 0.495, p < 0.001). In the final model, only behavioral confidence exhibited a significant association with initiation of relaxation behavior (b = 0.138, p < 0.001).For sustenance, lower- order terms perceived stress, depression, and academic classification explained 16.6% of the variance in sustenance for intentional relaxation behavior (R2 = 0.166, p < 0.001), with perceived stress (b = −0.035, p = 0.009) and academic classification (b = −0.454, p = 0.001) exhibiting significance, Table 4. MTM constructs were entered in model 2 and provided a substantial increase over the base model in variance accounted for (ΔR2 = 0.337). The final model explained 50.4% of the variance in sustenance of intentional relaxation behavior (R2 = 0.504, p < 0.001). Once all variables were accounted for in the model, emotional transformation held the only significant relationship to sustenance (b = 0.178, p < 0.001).The purpose of this study was to explore the use of the multi-theory model (MTM) of health behavior change in predicting intention for veterinary students to begin consciously performing relaxation behaviors for twenty minutes per day. The MTM is a relatively new, robust model based on two interlinking components: initiation and sustenance of health behavior change. Both initiation and sustenance are composed of three constructs that predict the success of the component. By conducting this study, researchers hoped to identify significant constructs of the MTM that can be used as targets for interventions in veterinary schools to improve the likelihood of student participation in conscious relaxation behaviors.From the initiation model, significant lower-order predictors included depression (p = 0.040) and academic classification (p < 0.001), while behavioral confidence was the only significant higher-order construct (p < 0.001). The full model predicted 49.5% of the variance in the initiation of conscious relaxation behavior. The construct of behavioral confidence has been derived from Bandura’s self-efficacy theory [25] and Ajzen’s perceived behavioral control theory [26]. It focuses on one’s confidence to initiate a health behavior change despite opposition, a busy schedule, or not enjoying the behavior. Behavioral confidence has been identified as a significant construct in prior MTM studies on different health behavior changes [17,18,19]. One important concept regarding behavioral confidence is that it includes confidence gathered from both internal and external sources, meaning sources such as counselors and mentors are equally as important as inner dialogue and self-regulation. A 2019 study found that the use of a life coach for first-year medical students showed promise for mental health improvements [27]. Veterinary schools could use this idea to promote an intervention targeting behavioral confidence. Weekly meetings with a counselor, mentor, or even small group sessions of classmates could help students to identify barriers to completing relaxation behaviors and work to formulate a plan to prioritize wellness. Potential barriers to student participation in relaxation behaviors include busy class schedules and distractions such as television and social media. Once students identify these barriers and ways to combat them, their behavioral confidence in initiating relaxation behavior should increase. Studies show that veterinary students are often hesitant to seek counseling and help for mental health issues [28,29]; therefore, any proposed interventions should be presented to all students, even those who do not actively seek help. Furthermore, counselors and external sources should encourage students’ own inner-dialogue, as behavioral confidence must come from within the students themselves in addition to external sources.Regarding the sustenance model, significant lower-order predictors included perceived stress (p = 0.009) and academic classification (p = 0.001), while emotional transformation was the only significant higher-order construct (p < 0.001). The full model predicted 50.4% of the variance in the sustenance of conscious relaxation behavior. The emotional transformation has been identified as a significant construct in past MTM studies on health behaviors such as fruit and vegetable consumption and sleep activity [18,19]. Derived from the self-motivation construct of emotional intelligence theory [30], emotional transformation focuses on overcoming self-doubt and directing one’s emotions and motivation toward the goal of health behavior change, in this case, participating in twenty minutes of conscious relaxation behavior per day. Studies show that veterinary students often experience low self-esteem, especially during the first year [31]. This may explain the significance of the emotional transformation construct, as low self-esteem suggests an inability to overcome self-doubt. As with behavioral confidence, interventions in the form of weekly meetings with counselors, mental health educators, and/or small group sessions could be the best way to target the construct of emotional transformation for the sustenance of conscious relaxation behaviors. During these sessions, educators should discuss self-motivation with students as well as the concept of a growth mindset. While the construct of emotional transformation has not specifically been studied in regards to sustaining relaxation behaviors, the idea of a growth mindset has been extensively studied and is associated with reduced anxiety and higher performance levels among students [13,32,33]. Growth mindset concepts could help students to overcome self-doubt about sustaining relaxation behavior. Furthermore, educators should encourage students to keep track of their participation in relaxation behaviors as a way to focus their emotions on behavior change. Students can then look back on this record of their progress as a way to overcome self-doubt in sustaining daily relaxation behaviors. Finally, interventions in the form of posters on campus or emails detailing the benefits of daily relaxation behaviors may help motivate students through the construct of emotional transformation.In evaluating the results of this study, there are a few limitations to consider. First, the study’s cross-sectional design provides little more than a snapshot in time. Therefore, the results cannot be viewed temporally, and we do not technically know if the constructs predict behavior change. Secondly, as with any survey-based study, the self-reporting nature of the data lends itself to bias. While largely unavoidable, self-report bias must be considered in the analysis. Additionally, information obtained only reported students’ intentions to change behavior, not the end result of behavior change. A follow-up study could evaluate how well students’ actions align with their reported intentions. Furthermore, demographic data was mildly misrepresentative of the veterinary student demographic, preventing researchers from generalizing their findings to the entire veterinary student population. For example, while 92.9% of the students surveyed were female, the American Veterinary Medical Association (AVMA) reported in 2018 that females comprised only about 80% of the veterinary student population nationwide [34]. Finally, test–retest reliability was not performed for the study instrument and should be performed in all future MTM studies.This research study paves way for future interventional studies that will test the efficacy and effectiveness of MTM-based interventions for stress management among veterinary students. For conducting efficacy studies, since internal validity is of paramount importance, utilizing randomized controlled designs (RCTs) in small sample sizes will be appropriate. In designing such efficacy studies, the initiation construct of behavioral confidence will be specifically relevant. Mastery through small steps, role modelling, providing multifarious sources of confidence, and enhancing futuristic ability to perform stress-management behaviors may be fruitful methods of increasing behavioral confidence. For sustenance model, the emotional transformation construct will be especially relevant, in which interventions should incorporate educational methods such as psychodrama, role-play, and simulations that influence the affective aspects and help in directing feeling toward stress management behaviors. Once efficacy studies are able to support evidence derived from this cross-sectional study, effectiveness studies at different veterinary institutions with this target population can be designed.Chronic stress among veterinary students and professionals is a growing issue in the field of veterinary medicine. Counselors and faculty members at veterinary schools have the ability to help students control stress levels by encouraging and providing resources for the use of conscious relaxation behaviors. The multi-theory model of health behavior change provides a starting point for interventions in veterinary schools. Based on the results of this study, interventions regarding conscious relaxation behaviors should target the constructs of behavioral confidence and emotional transformation. By focusing on veterinary student behavior, interventions will not only improve students’ experiences in school but will equip students with tools to use after graduation in combatting pitfalls in the veterinary profession such as compassion fatigue and burnout.V.K.N. and M.S. contributed to study conceptualization and design; M.S. and V.K.N. contributed to instrument development; V.K.N., E.C.J., and J.W.J. contributed to data collection; V.K.N. contributed to data analysis; all authors are responsible for data interpretation; all authors drafted the article or revised it critically for important intellectual content; all authors gave final approval of the version of the article to be published; all authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors have read and agreed to the published version of the manuscript.No funding was obtained for this study.We would like to thank all those who voluntarily participated in this research study. This study was presented at Association of American Veterinary Medical Colleges and Society for Public Health Education conferences in 2019.The authors declare no conflict of interest.The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.Socio-demographic Characteristics of the Participants (N = 140).Descriptive Statistics of Constructs of Multi-Theory Model (MTM) (N = 140).Hierarchical Multiple Regression Predicting Initiation for Intentional Relaxation Behavior (N = 140).a Reference category = no depression; b Reference category = first/second year veterinary students; SE = standard error of the unstandardized coefficient; 95% CI = 95% confidence interval for the unstandardized coefficient.Hierarchical Multiple Regression Predicting Sustenance for Intentional Relaxation Behavior (N = 140).a Reference category = no depression; b Reference category = first/second year veterinary students; SE = standard error of the unstandardized coefficient; 95% CI = 95% confidence interval for the unstandardized coefficient.

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+These authors contributed equally to this work.Chinese medical aid team members (CMATMs) play an important role in the implementation of China’s health assistance strategies in Africa. This paper explored the influencing factors of expatriation willingness for Chinese medical aid team members (CMATMs). We employed a qualitative descriptive study using semi-structured interviews with twenty-five participants. Participants included hospital directors and local Health and Family Planning Commission (HFPC) officers who were in charge of CMATMs dispatching, and CMATMs that had returned from medical aid service. Six influencing factors emerged: career advancement, loneliness, living conditions, personal safety, family–work conflict, and doctor–patient relationship. Career advancement is the most important factor and concern for doctor CMATMs. Social use of Internet is on the core of entertainment. Enhancing technical title promotion policies is the most important motivator. This study obtained baseline information that is useful to relevant stakeholders in their attempts to improve CMATMs’ expatriation willingness.Ever since dispatching medical aid teams to Africa in 1963, China has been showing its strong willingness to participate in global governance as well as to help other developing countries, especially African countries. Offering health assistance is one of China’s priorities in providing assistance to African countries, and one of the main channels is dispatching medical aid teams to these countries. By 2017, China had sent 25,000 medical aid team members to African countries [1], and there are currently still thousands of Chinese medical aid team members (CMATMs) providing services in recipient countries [1,2]. Obviously, CMATMs have a significant impact on the implementation of China’s health assistance strategies in Africa. However, some studies have declared that China is facing a dilemma between the increasing demand for health assistance and the difficulty of dispatching medical aid personnel to African countries, as medical staff have shown low willingness to be dispatched to African countries as CMATMs [3,4]. Expatriation willingness—that is, candidate’s willingness to accept expatriate assignment—is an important predictor for expatriate success [5]. Considering the significant role of CMATMs, needless to say, it is necessary and important to explore the influencing factors for expatriation willingness of CMATMs, because it is the premise to understand and boost the expatriation willingness of this population. However, little has been determined so far regarding this particular population, let alone the expatriation willingness and its influencing factors of this population. Therefore, the present study aimed to identify the influencing factors for expatriation willingness of CMATMs in Africa, and to provide scientific evidence for implementing relevant measures to enhance expatriation willingness of this particular population.The work–family conflict is among the most discussed factors for discouraging expatriation willingness. Family issues are often cited as a main reason for refusing international assignments [6,7,8,9]. Studies focused on long-term expatriation have found that married candidates may resist and refuse overseas expatriation for the spouse’s reluctance to move or/and for the quality of education available to children in the host countries [8,9]. It is understandable that since long-term expatriation lasts more than one year, expatriates probably will take their family along, hence having to consider spouse willingness to move and the education quality for kids. Whereas, studies have found that short-term expatriates are usually not accompanied by their family [10]. However, it should be pointed out that although the expatriation period of CMATMs generally lasts for two years, which is considered as long-term expatriation, CMATMs are hardly accompanied by their family. Hence, while the prior studies focusing on long-term expatriation are informative, some of their contexts are different from that of CMATMs, hence the previous findings may not apply to this study. One significant difference is the children education issue. Since CMATMs do not take their children to the recipient country, the education issue in the recipient country is definitely not an influencing factor for the expatriation willingness of CMATMs. However, since CMATMs must stay in the recipient country for 2 years, which means they could not take care of their family during this period, it is the same case with the spouse affair, children care affair, and eldercare affair for CMATMs. Overall, CMATMs will not be able to fulfill their family roles, which include their role as spouse, parent, and offspring. Living conditions in the host country have also been found related to expatriation willingness. Employees from advanced regions are most reluctant to relocate to developing economies due to the living conditions [11]. Prior studies have suggested that countries with a high level of economic level are favored by expatriate candidates, especially those from developing or transitioning economies [12,13]. Another study showed that quality of place factors contribute positively towards the retention of global talent [14]. Advanced economies are preferred by expatriates and immigrants because they can offer career advancement [5], which is especially true for those from less-developed economies [12,13,14,15]. Barrett and O’Connell suggested that individuals relocate to different countries for career advancement reasons rather than for other reasons [16]. However, the medical technology level of the medical aid sites is worse than that of China. Medical aid sites are often short of common devices, let alone the advanced devices. Access to advanced and newest devices and technology during the expatriation period is difficult, whereas medical technology updates very fast. Hence, it means CMATMs will be kept away from advanced devices and technology for two years, and they could not keep pace with the new development. When CMATMs finish the expatriation assignments and come back to China, they are behind their colleges and have to make great effort to learn new technology, which may put them at a disadvantage.The destinations of CMATMs usually have a high prevalence of infectious diseases, such as HIV, malaria, dengue fever, and Ebola. Liang’s study on Guangxi CMATMs found that the most concerned risk was diseases, and 57% of CMATMs from Guangxi suffered from malaria infections for one to three times [17]. Overall, a high prevalence of infectious diseases and inadequate medical resources lead to high health and life risk for CMATMs. Besides, the destinations of CMATMs are with dangers from public security or even terrorist attack possibilities. The Aid Worker Security Report 2018 reported that 2017 saw a 30% rise in global fatalities compared to 2016. In 2017, 139 aid workers were killed, 102 were wounded, and 72 were kidnapped [18]. This study adopted a qualitative descriptive approach, in which in-depth, semi-structured interviews were the primary data collection strategy [19,20,21]. Conventional content analysis was used to analyze the data. We chose qualitative description because there is a general lack of knowledge regarding influencing factors for the expatriate willingness of CMATMs. In the absence of such knowledge, quantitative methods are difficult to apply. Qualitative description allows us to “stay closer to the data and to the surface of words and events” than other qualitative traditions [20] to elicit in-depth insights from participants on their perspectives towards the themes of the present study. Ethical approval for this study was obtained from the institutional review board of School of Health Science of Wuhan University (Project Identification Code: 2016-S-0011-4/03). Data collection occurred between July 2016 and October 2016.Purposive sampling was used to achieve a heterogeneous selection in terms of area, institution, position, career, and architecture of these factors. In fact, Chinese medical aid team dispatching are undertaken by twenty seven provinces instead of National Health and Family Planning Commission of the People’s Republic of China, and each province has fixed recipient countries. Participants from H, B, and Q were interviewed. H has been one of the best provinces regarding medical aid team dispatching management (measured by National Health and Family Planning Commission of the People’s Republic of China). B is one of the provinces responsible for most medical aid sites, and every year it sends nearly 80 personnel to nine medical aid sites (7.9% of all the overseas medical aid sites) in Africa. Q is one of the undeveloped provinces and depends entirely on funding from central government regarding the medical aid team dispatching issue. In terms of gross domestic product (GDP), in 2014 and 2015, Provinces H was in the top five (about 35 trillion in 2014, 37 trillion in 2015), Province B was in the top ten (about 27 trillion in 2014, 29 trillion in 2015), and Province Q was in the bottom three (about 23,000 billion in 2014, 24,000 billion).This study chose participants who are in actual charge of CMATMs dispatching. These participants were from hospitals that have sent CMATMs, and from the previous local Health and Family Planning Commission (HFPC). Participants included hospital directors and local HFPC officers who were in charge of CMATMs dispatching, and CMATMs that had returned from medical aid service. To ensure the validity of the data, participants should have different professional backgrounds and roles in work related to medical aid, and represent the architecture of personnel in medical aid sites. Hence, doctors, drivers, translators, accountants, and cooks were chosen to participate in the present study, because a medical aid site includes all these personnel.Semi-structured interview guidelines were used to study the participants’ opinions on factors influencing expatriate willingness, and measures related to expatriate willingness. All questions were intentionally left open-ended to allow participants to describe their expatriation experiences and opinions on the topics in their own words. Interviews were conducted in the conference rooms of local HFPC.Questions could be classified into two groups according to their purposes. In the first group of questions, participants were asked to explain their insights of influencing factors for expatriate willingness of CMATMs. Participants’ experiences and feelings were welcomed to be cited as examples. In the second group of questions, participants were asked to describe related policies that could enhance or hamper expatriation willingness to be sent as CMATMs. Then they were asked to put forward suggestions for boosting expatriation willingness of the target population in this study. Interviews lasted for 25–30 min, and were conducted until no new information was yielded. All interviews were audio-recorded and transcribed verbatim.Audio recordings of the interviews were transcribed within 24 h, and then reviewed against original recordings for accuracy. Inconsistency was confirmed by phoning the interviewer. Interview data were analyzed using conventional content analysis and coded. Keywords and key semantics were abstracted via an iterative process of analysis and review.Twenty five people participated in this study. Nine were from H province, eight were from B province, and eight were from Q province. Over a half of the participants were doctors (53.8%), who had returned from medical aid service in Africa. Among these doctors, there were two team leaders from H and B, respectively. Every province sent one officer of the local HFPC and one officer of the hospital to participate in the interview. Participants included one accountant, one translator, one cook, and one driver. Officers of local HFPC and hospitals are in charge of selecting and managing CMATMs. Their duties and working experience may lead to different insights from CMATMs. Thus, they were categorized as the “A” class, including six participants. Owing to the selection criteria and managerial duty, team leaders of CMATMs also may have different insights from common CMATMs. Hence, team leaders were categorized as the “B” class, including two participants, and common CMATMs were categorized as the “C” class, including 17 participants. Characteristics of the 25 participants are presented in Table 1.Six themes emerged during the survey and analysis, including career advancement, living conditions, personal safety, leisure, family–work conflict and doctor–patient relationship (Table 2).Analysis did not show participants from different provinces divided in the influencing factors issue. Analysis also did not reveal that different groups of participants (officers, team leaders of CMATMs, and common CMATMs) had different opinions on this issue. However, officers cited more cases, and these cases were more representative than did the other two kinds of participants. CMATMs spent more time expressing their opinions on the influencing factors issue than the policy and suggestion issue.Topic of career advancement took up the most time among officers and doctor CMATMs. The push and pull sides for career advancement were shed light on, although participants spent much more time talking about the pull sides, indicating that they concerned much more about the pull sides. All doctor CMATMs and officers perceived that a 2 years aid period plays a negative role in doctors’ career advancement. The negative effects have three focuses: strangeness of the original medical skills and technology, loss of chance to master new medical skills and technology, and high possibility of losing the original position. Besides old devices, medical aid sites are often in serious lack of common devices. Without the necessary medical equipment, doctors will gradually become unfamiliar with the medical technology, which they were quite skilled before being dispatched. Besides, medical skills and technology is advancing at a breathless pace. During 2 years’ expatriation, access to these new advancements is impossible, let alone mastery of them. Hence, doctors deemed that medical aid expatriation undoubtedly leads to strangeness of medical skills and technology, and offers little chance to master new skills and technology. They also worried that their original position would be replaced, because 2 years is not a short period and the hospital have to operate. Some of the doctors and officers cited some real cases of returned CMATMs having been replaced. Concern of being replaced is particularly evident among doctors in the surgical department. “I think the impact on the doctors in the surgery department is relatively serious. Surgery departments, such as obstetrics and gynecology, ophthalmology and surgery, have many patients and operations. So, some CMATMs from these departments found that they had already been replaced when the medical aid assignment was over. If your ability is not improved, you will be slowly marginalized and moved to a new department. This happened before.” (A-1).“The level of medical care in medical sites is very low, and the medical equipment is so poor that it is impossible to carry out new projects. After working there for two years, your skills cannot be improved. But in China, technology is advancing by leaps and bounds. When you come back, you will find that you cannot keep up with your colleges.” (B-1).“Going out for 2 years results in decline in business and skills. This loss is irreparable.” (C-1).All of the doctor participants thought that technical title promotion policy could motivate CMATMs candidates. All officers respondents perceived technical title promotion policy as the most important motivation for those who are willing to assume the assignment. “Most of CMATMs who are willing are mainly motivated by the technical title promotion policy.” (A-2).Leisure was mentioned by the largest number of participants, although it did not account for the most time. Due to travel regulations, CMATMs mostly stayed in the dormitory after work. However, the medical sites lacks recreational facilities and sports venue. Thus, CMATMs found the after-work life very monotonous. “They often had no other entertainment but taking a walk inside the building.” (A-4, A-6). Watching TV and surfing the Internet are the main forms of entertainment. “After-work life there is very monotonous. In addition to browsing news on internet and chatting with family, there is no other entertainment.” (C-9). However, there are few Chinese channels on TV, and the network speed is very slow. “It takes more than ten minutes to send a word document” (B-2).Internet is considered as the core among all the entertainment means for CMATMs. Its social use (e.g., browsing social networking sites and instant messaging) and entertainment use (e.g., downloading files) were both shed light on. Participants cared about the social use of Internet more than the entertainment use of it. Chatting with family and friends via instant messenger were highlighted by participants. However, since CMATMs could only surf the Internet during free time, video chatting time with their family and friends was undoubtedly concentrated, leading to great difficulties to contact with family and friends with the network conditions in recipient countries. Lack of entertainment and difficulty of communicating with family and friends resulted in feeling lonely among CMATMs, which even led to psychological disorder and illness. “Some CMATMs even may have depression.” (A-2) and “Some tried to commit suicide.” (A-4). Moreover, consequences included disharmony and even quarrel among CMATMs. “If there was no net that day, everyone quarreled.” (C-3).As of describing feelings or physiological state, respondents used the following words: dull, monotonous, lonely, depression, pressure, and disorder.“The CMATMs could not go around freely, which was quite like being restricted. It easily leads to psychological distortion.” (A-4).“They were prone to quibble during the assignment. They were depressed, and since there were no good way to release their depression. Gradually, they were prone to quarrel. A common issue, which could be solved easily in China, would be handled by them in an abnormal way. This situation is common in each batch.” (A-1).Three themes emerged in terms of living conditions, including shortage of water and electricity, poor diet, and bad housing. Living conditions of medical sites in capital are better than those in remote regions. CMATMs concluded that life there was hard. Poor living conditions discourages expatriation willingness.Shortage of water and electricity are the norm in many medical sites. “CMATMs often drive three kilometers away to get water.” (A-1).“For some teams, going out of electricity and water is very common.” (C-2).Due to the shortage of daily consumer goods production and supply, coupled with inflation, the cost of diet was high, leading to restriction of selection and consumption. “The prices were very high because of the speedy inflation.” (C-10). “Most of the local meat was beef and mutton, and it was very expensive.” (C-7). So, “We bought it once or twice a month.” (C-9). “Vegetables were usually very expensive.” (C-11) and “The variety of vegetables was very different from that in China” (C-6). Hence, many CMATMs took vegetable seeds to recipient countries and planted vegetables there. Some CMATMs also took flavorings along. Moreover, in some medical aid sites, the water was of poor quality, and harmed CMATMs’ health.“The water quality was not good there, and the elements exceeded the standard. The hair turned white after two years. Some CMATMs had been buying mineral water. But it was very expensive if you bought mineral water for daily use……and there was no water purifier.” (C-8).As of housing, CMATMs had to share rooms, which was of poor sound insulation effect. The household appliances were old and damaged. However, the maintenance period was very long, and the cost was very high. The recipient countries lacked spare parts for the corresponding equipment and electronic products, and sometimes they had to order from China. Besides, there was a lack of maintenance technicians. Therefore, it was difficult to repair the household appliances in time, and sometimes CMATMs had to apply for a new one, which brought inconvenience to the normal life.“We had to share rooms. The rooms are separated by a partition, but the sound insulation effect was very poor. You could hear every sound. Household appliances were very old, slow to update, and had a long maintenance cycle.” (B-1).Three kinds of threats to personal safety have been focused: local security, high risk of being infected with local infectious diseases, and life or health threats resulted from local inadequate medical service.As of local security, high criminality rates, loose restriction on guns, and terrorism pose a potential threat to the personal safety of CMATMs. “You must return to the city before three pm. The aid site is surrounded by small hills, and anti-government forces can be seen on the road. Guns can easily be seen on the top of the hills. Although anti-government forces claimed that they would not hurt Chinese, and they had a good impression of CMATMs. But no one could prevent accidents from happening. They were all live-fired, and there were bound to have some psychological impact on CMATMs.” (A-1).“Their guns are open and scary, which is a potential danger.” (C-15).Owing to the prevalence of infectious diseases, CMATMs will face many more infectious patients than they do in China, which leads to higher possibility of being infected. Moreover, some infectious diseases are incurable, bringing great pressure to CMATMs. “CMATMs in our team used to have this psychological disorder when they came back. His gloves were broken during the operation, and he clearly knew that the patient was an AIDS patient. You can imagine his feeling. After he came back, the psychological pressure could not be erased for a long time. You can imagine how much pressure he underwent when he did the surgery.” (A-2).“Generally, eight to ten members of every team will be infected with malaria. Although the disease can be cured there, it would relapse when they come back to China.” (A-1).“I went there…… my hand was punctured during the operation. AIDS is very prevalent there. I was very scared at the time.” (C-17). Local inadequate medical service is also a risk for CMATMs if they are heavily injured or have serious illness. “One of our team members fell off the stairs, and his leg broke. But there was no way to treat it in the recipient site. So, we finally gave him a temporary plaster and sent him back to China. It cost seven days to come back. When the plaster was cut, the legs had turned black. Luckily, we sent him back without any hesitation. If it had cost two more days, the leg would not have been saved.” (A-4).During 2 years’ assignment, CMATMs basically could not assume family responsibilities or take care of their family. According to the regulations, CMATMs can only enjoy one family vacation paid by the government. In addition, lacking of network resources in medical sites results in much less contact with family, “It is easy to conflict with the family” (C-3).The old and the young members in the family are mostly mentioned. “Every time I think of it, I feel I owe a lot to my parents.” (C-9).“There are a lot of cases that the members were late for their parents’ funeral. …… Our team leader’s grandson, a five-year-old child, suddenly developed a brain tumor. The boy was going to die in hospital. Although we agreed the team leader to come back at once, he could do nothing after he came back.” (A-4).“CMATMs suffer from career loss and family loss.” (B-1).In sum, absence of a family role, which includes the role as spouse, parent, and offspring, negatively affects expatriation willingness to be dispatched as CMATMs.Besides technician title promotion policy, doctor–patient relationship in the recipient countries can also motivate doctors to accept the expatriation. Participants who showed willingness to be present as CMATMs expressed that they would accept the assignment because they enjoyed the nice doctor–patient relationship in the recipient countries. Patients are respectful to doctors, and doctors could concentrate on offering medical service without paying extra attentions to dealing with medical disputes. Doctors have and enjoy the sense of accomplishment. “The doctor–patient relationship is very good there. Patients are very respectful to the doctors…. We went there again because of this specific nice relationship, but not money.” (A-6).“Nice doctor–patient relationship is one main motivation factors for most doctors who are willing to be sent again……. You have the sense of accomplishment every time you save a patient.” (A-4).Analysis did not show participants from different provinces divided in the policy and suggestion issue, nor revealed that different groups of participants (officers, team leaders of CMATMs, and common CMATMs) had different opinions on this issue. Topic of policy and suggestion took up much less time than topic of influencing factors. Policies and suggestions discussed were related to career advancement, entertainment, living conditions, and family–work conflict (Table 3). Technical title promotion policy was the core of the policy issue. All doctor respondents and officer respondents agreed that technical title promotion is the most important motivator. In terms of suggestions for career advancement, two main issues were put forward. First, adopting more effective technical title promotion policy. Second, increasing the foreign aid gross income to compensate for the 2 years’ loss.Regarding solving leisure problems, the internet speed was the focus. “Internet is the only form of entertainment, as well as the most important form of communicating with family and friends, which could ease the psychological pressure. Hence, it is very important to solve internet problem, mainly the speed” (C-7). Increasing entertainment budget ranked the second.As of living conditions, participants called for more investment to improve the overall conditions.In terms of family–work conflict, participants had different opinions. Some considered shortening 2 years aid period to 1 year as an effective approach, whereas some deemed it inefficient, because “A year later, CMATMs just get adjusted and familiar with the life and work there, and have the ability do it better. But the assignment ends. This is a waste of resources.” (A-5). Some held the opinion that allowing family companionship could ease family–work conflict, while others thought it unpractical because it would not do good to the spouse’s career, or it would not be a good idea owing to the living conditions and personal safety issue.This study explored the expatriation willingness and its influencing factors for CMATMs. The findings showed that career advancement, leisure, living conditions, personal safety, family–work conflict, and doctor–patient relationship were related to CMATMs’ expatriation willingness. Results revealed that participants did not put forward many suggestions.All doctor participants spent the most time talking about career advancement. This phenomenon indicates that career advancement is the most important factor and concern for doctor CMATMs. The push and pull sides for career advancement have been shed light on, although more participants concerned about the pull sides. It is understandable that these excellent doctors worry about the high possibility of falling behind in career when the expatriation ends. Local HFPC and hospitals are required to select qualified and excellent doctors from grade three hospitals as CMATMs. In another word, these selected doctors have a bright future. We could reasonably assume that these doctors value their occupational role and have high motivation for occupational achievement. Prior studies found that employees’ need for occupational achievement can have considerable influence on their willingness to accept an international assignment [13,21], because they believe the assignment would help advance their career. Previous studies have primarily suggested that employees expect to upgrade their skills, increase their knowledge, and advance their careers by relocating to advanced countries [12,13,15]. Hence, according to prior studies, employees in need of occupational achievement are willing to assume those beneficial overseas assignments. However, the present study revealed that owing to backwardness and lack of medical device, and hardly possible access to learning and mastery of new technology, assignment as CMATMs could not advance doctor CMATMs’ career, but on the contrary, have a negative impact on their career, which not only results in lagging behind in terms of knowledge and skills, but also losing the original position. For these excellent doctors, they surely take these aspects as demerits to their career advancement. It is reasonable that these doctors deem that they are likely to have greater achievement if they spend the 2 years in China instead of being dispatched as CMATMs. How to reduce the demerits to doctors’ career advancement is a core for motivating doctors, which should be the key point of policy. Findings of the present study suggest that enhancing technical title promotion policies is an effective approach to motivate doctors. However, we find that not all provinces benefit CMATMs in technical title promotion. In the provinces that have set a technical title promotion policy to encourage CMATMs, experience of CMATMs could not help direct technical title promotion. In some provinces, such experience could only bring priority under the same conditions. In some other provinces, such experience can exempt a man-machine oral test, which is one of the technical title promotion conditions. We suggest all provinces should benefit CMATMs in technical title promotion. Moreover, further study should explore different promotion measures.Results demonstrate that their after-work life in the recipient country was very monotonous and dull, as well as there were too little entertainment resources. In another word, CMATMs had very poor leisure quality and experienced leisure boredom during the medical aid service period. Plenty of previous studies have proven that participating in leisure activities are beneficial to people in a numerous aspects, such as physical health, psychological, social, and economic well-being, and quality of life [22,23,24]. Furthermore, leisure is considered as an important way to reduce the negative influence of stress on physical and mental situation [22]. However, when people subjectively (lacking the ability to manage their leisure time meaningfully) or objectively (inadequate leisure resources) cannot utilize their leisure time, they probably will not receive benefits from their leisure time, resulting in leisure boredom. Leisure boredom is “a mismatch between desired arousal-producing characteristics of leisure experiences, and perceptual or actual availability of such leisure experiences” [25]. Feelings of emptiness, meaninglessness, and restlessness are considered as the characteristics of leisure boredom [26]. Literature focusing on the consequences of leisure boredom shows that boredom is related to poor mental health (e.g., loneliness, depression, and anxiety), and to problematic behavior (e.g., eating disorders and substance abuse) [27,28,29]. Leisure boredom has also been found to significantly predict low life satisfaction [26,30,31]. Leisure boredom explains depression cases, physiological disorder cases, seemingly unreasonable behavior, and proneness to quarrel among CMATMs. Results of the present study call for more resources and measures to enhance leisure life quality of CMATMs. It does not only affect the CMATMs’ expatriation willingness, but also influences their mental health, life satisfaction, and their cooperation and assignment performance. It is worth noticing that Internet use is the core topic for entertainment in this survey, and participants complained mostly about great difficulty of contacting with their family and friends, which was a result of the slow Internet speed. It depicts two important themes: the use of Internet, and the need to be socially connected. There are several explanations for the fact that Internet use being the core of all entertainment means in the present study. Firstly, respondents probably had been used to entertaining on the Internet, or even had relied on the Internet. As of December 2016, the number of Internet users in China reached 731 million. Data shows that in 2016, Chinese netizens spent 26.4 h a week on the Internet, roughly the same as in 2015. In 2016, the usage rate of Internet users of instant messaging, search engines, online news, online video, and online music was 91.1%, 82.4%, 74.5%, and 68.8%, respectively [32]. Secondly, loneliness, depression, and stress, which were used by participants to describe their feelings and psychological state, and which were the probable outcomes of going abroad without the companionship with family, poor leisure life, and typical characteristic of leisure boredom, would lead to CMATMs’ greater need for Internet use. Perceiving psychological problems as the cause of Internet use, previous studies have shown that psychological problems were directly related to Internet use [33,34,35]. Of all these psychological problems, loneliness attracts the most attention. Morahan’s study found that lonely individuals were more likely to use the Internet to modulate negative moods, and they used the Internet more than others [35]. Meanwhile, the benefits of Internet use should not be ignored in the present study. Shaw’s study found that Internet use could significantly increase perceived social support and self-esteem, while decrease loneliness and depression significantly [36]. Some studies also have suggested that Internet use has an overall positive effect on well-being [37,38]. Regarding the need to be socially connected, studies have shown that being socially connected is influential for psychological, emotional well-being, physical well-being [39], and overall longevity [40,41]. On the contrary, a lack of social connections is detrimental to health. Considering the two following facts: (a) participants complained mostly about great difficulty of contacting with their family and friends via Internet and (b) undoubtedly, Internet is the only and the best social connecting means for CMATMs, which not only enables CMATMs to communicate with domestic important social relationship in time, but also helps CMATMs to connect with domestic society by offering instant channels to get domestic news and comments, we could focus on probing into the social use of Internet. A 15 years’ longitudinal study showed that using Internet to communicate with offline strong ties, such as family and close friends, are beneficial to psychological well-being as measured by declines in depression, loneliness, and stress, and increases in perceived social support, mood, and life satisfaction [42]. Another study found that greater use of the Internet as a communication tool was associated with a lower level of social loneliness [43]. Overall, CMATMs subjectively have expressed their need for social use of Internet. The beneficial influence of Internet use, especially its social use, have been demonstrated by previous studies. Results of the present study and findings of previous studies are calling for the guarantee of the social use of Internet. On the other hand, we must admit that it is not easy to do so, because increasing the Internet speed is related to the network infrastructure. Making use of the Internet resource of local Chinese enterprises or other entities might be a practical approach.Furthermore, it is interesting and noticeable that leisure was the most discussed topic among participants, rather than living conditions. It was in line with our study on CMATMs’ overseas life satisfaction, in which showed that leisure satisfaction was lower than food satisfaction and housing satisfaction [44]. These findings probably contradict to many people’s impression, which deems hard living conditions as the most concerned factor among CMATMs, because previous reports have discussed living conditions much more than entertainment. It is understandable that previous studies and media reports have taken living conditions as a more important issue, since hard living conditions are visible, instant, and more eye-catching for media coverage. However, the fact that leisure got more attention than living conditions in the present study may be due to the reason that the impact of psychological feeling lasts longer than that of living conditions, which deserves our attention. It is understandable that CMATMs were not satisfied with the living conditions, and the tough living conditions negatively affect their expatriation willingness, which was in line with previous studies [3,4]. Although China itself is a developing country, it is undeniable that China’s economy and living conditions have gained great achievement. China has set a high criteria for selecting CMATMs, particularly doctors. Local HFPC and hospitals are required to select qualified and excellent doctors mostly from tertiary hospitals (top level in China) as CMATMs. These hospitals often locate in relatively developed regions in China. For example, there were 67 tertiary comprehensive hospitals in Guangdong Province in 2016, and 62.9% of these hospitals locate in Guangzhou (18), Shenzhen (6), Foshan (7), Dongguan (6), Zhongshan (3), and Zhuhai (2) [45]. These six cities are the richest place in Guangdong. It is understandable that the doctors have good living conditions due to their professions and the location of the regions. However, CMATMs are often dispatched to hardship arrears of African countries, which are with hard living conditions. Africa has 33 least developed countries, 29 of which are recipients of China. Most of these recipient countries locate in Sub-Saharan Africa. 319 million people in Sub-Saharan Africa are without access to improved reliable drinking water sources [46]. Hardships mentioned by participants included shortage of water and electricity, poor diet, and bad housing, which were in line with previous studies [17,47,48]. Tian’s study revealed that some medical team sites had been out of water for three months, making daily washing a big problem [49]. While shortage of water and electricity is hard to solve by China alone, housing and diet are much easier and could be solved by China alone by investing enough funds.Although the present study did not find that participants ranked personal safety the most important factor, personal safety is undoubtedly the most basic need of a person, and guaranteeing its citizen’s personal safety is the basic responsibility for a country and its government. Results showed that participants focused on the following three kinds of threats to personal safety: local security, high risk of being infected with local infectious diseases, and life or health threats resulted from local inadequate medical service. As of local security, participants also mentioned crime (e.g., robbery) and terrorist. These two issues fall into the scope of indicators of Ibrahim index of African governance (IIAG). IIAG measures the overall governance in all African countries and is issued annually by the Mo Ibrahim Fund. The index, which began in 2007, measures four aspects, including Safety and Rule of Law, Participation and Human Rights, Sustainable Economic Opportunity, and Human Development. The index uses a percentile system. According to IIAG, the absolute level in many categories is very low. Perception of personal safety score is 45.9 in 2013, 45.6 in 2014, 44.6 in 2015, and 42.4 in 2016 [50]. Absence of crime score is merely 47.5 in 2013, 48.4 in 2014, 48.1 in 2015, and 48.7 in 2016. In 2011, four gunmen entered the room and robbed three CMATMs. In 2012, twenty-eight Chinese workers were kidnapped in Niger [51]. Absence of domestic armed Conflict or risk of conflict, which is worried by CMATMs, is low, standing merely at 56.3 [50]. At the end of 2012, the situation in Central Africa was so volatile that the Ministry of Health had to withdraw the medical team that was carrying out the medical mission there [51]. Since non-interference in each other’s internal affairs is a principle of international law, China could only communicate with recipient country to take more measures to ensure the CMATMs’ safety. CMATMs have to face high risk of being infected as well. The prevalence of tuberculosis and the spread of HIV in sub-Saharan Africa are among the highest in the world [52]. Malaria, typhoid fever, dengue fever, and other diseases are frequent in Africa. Many media reports and studies have mentioned that some CMATMs died of illnesses after being infected with the disease, and some others suffered recurrent attacks, or could not be cured and suffered for life [53,54]. As of the threats from being infected, and from local inadequate medical service, a possible approach might be equipping medical sites with more necessary and advanced devices and medicines. The findings indicated that absence of taking care of family negatively affect CMATMs’ expatriation willingness, which is consistent with previous studies. Phyllis’s longitude study on 839 Australian employees demonstrated that employees with less family barriers showed stronger expatriation willingness, and the expatriation interest of childless singles were most realized [7]. Besides, a study conducted by Konopaske and his colleges suggested that eldercare also influences managerial willingness to assume global assignments [55]. The fact that participants mentioned children and elders mostly in this part suggest that policy or local government and hospitals could take measures to take care of these two populations to ease CMATMs’ worries and boost their willingness. The importance of family–work conflict is not only that it is one of the factors affecting expatriation willingness, but also that it has a positive correlation with depressive symptoms among employees [56,57,58,59]. Hao’s study found that family–work conflict could increase doctors’ depressive symptoms [60]. The findings of these studies call for attention for caring for mental health of CMATMs, especially offering perceived organizational support, since perceived organizational support, as a positive resource, could fight against doctors’ depressive symptoms [60].Findings show that a nice doctor–patient relationship in recipient countries motivates CMATMs to accept a new assignment. This is in line with previous findings. A study sampling on 600 young medical staff found that doctor–patient conflicts negatively impact the retention of the participants [61]. Another study conducted among 882 medical staff showed that the doctor–patient relationship was negatively correlated to turnover intention, indicating that the better the doctor–patient relationship, the lower the turnover tendency. The study also found and doctor–patient relationship was positively correlated to job satisfaction [62]. Li’s study found that there was a positive correlation between doctor–patient relationship and doctors’ work engagement [63].Another study conducted by us in 2016 depicted the gross aid income. Of 317 respondents, 32.2 got 130,000–190,000 RMB as the gross aid income, 30.6% got 190,000–250,000, 19.2% had less than 130,000, and 18% had more than 250,000 [44]. Economically, it is not attractive for doctors, especially excellent doctors or doctors in developed areas. Measures should be taken to increase the gross aid income.Shortening the expatriation period may be one effective approach to reduce all the negative influences of the six factors. Since 2016, some provinces have begun to shorten the period to one year, for example, Ningxia, Guangxi, and Tianji. Of the six factors, domestic policy can have great effect on career advancement, living conditions, and leisure. In terms of career advancement, NHC can require all provinces to adopt more effective technical title promotion policy, and guarantee that returned CMATMs could have adequate and qualified technical training. Regarding living conditions, housing and diet could be solved by investing enough funds. As of leisure, recreational facilities and sports venue in the medical team site are much easier to improve than the internet resource. Since recreational facilities and a sports venue do not rely on the infrastructure or conditions of recipient countries. A basketball court, table tennis room, and movie studio are good choices. Policy should increase and ensure investment on living conditions and leisure. It is also necessary to establish minimum standards for living conditions, recreational facilities, and sports venue.Last, a number of limitations of this study should be elucidated. First, the present study evaluated the opinions of only 25 individuals; in future studies, it might prove useful to increase the sample number to corroborate the findings of this study. Second, this is a qualitative research, hence findings of this study cannot be generalized to people who were not included in the study sample. For further study, qualitative method should be adopted.This study is among the first to explore the influencing factors of expatriation willingness for CMATMs. Career advancement, leisure, living conditions, personal safety, family–work conflict, and doctor–patient relationship were found related to expatriation willingness of participants. Career advancement is the most important factor and concern for doctor CMATMs. However, all doctor CMATMs and officers perceived that a 2 years aid period plays a negative role in doctors’ career advancement. Leisure was complained by the largest number of participants. Poor leisure quality during the assignment negatively affects expatriation willingness. Slow Internet speed results in great difficulty of communicating with domestic important social relationships as well as connecting with domestic society. The tough living conditions and absence of family roles also negatively affect expatriation willingness. The technical title promotion policy is the most important and effective motivator for doctor CMTAMs. A nice doctor–patient relationship in recipient countries is the other motivator. The present study indicated that adopting more technical title promotion policy, improving living conditions and leisure facilities, shortening expatriation period, and increasing the annual aid income could be an effective way to boost expatriation willingness.Z.M. designed this study and collected the data; X.C., and X.L. conducted the data analysis, and drafted the paper; X.C. and Z.M. revised the manuscript. All authors have read and agreed to the published version of the manuscript.This study was supported by the National Health Commission of the People’s Republic of China (Project Identification Code: 2016-S-0011-4/03).The authors would like to thank Zhen Li, Fuhui Ta, and Yao Wang from Wuhan University, for their assistance in data collection.The authors declare no conflict of interest.Demographics of respondents (n = 25).Six influencing factors for expatriation willingness.Suggestions for motivating CMATMs candidates.

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+This research examines the mediating role of the tendency for Internet addiction, fear of missing out (FOMO), and psychological well-being in the relationship between online exposure to movement-related information and support for radical actions. A questionnaire survey that targets tertiary students was conducted during the Anti-Extradition Law Amendment Bill (Anti-ELAB) Movement (N = 290). The findings reveal the mediating effect of Internet addiction and depression on the main relationship. These findings enrich the literature of political communication by addressing the political impact of Internet use beyond digital architecture. From the perspective of psychology, this research echoes the literature that concerns depression symptoms driven by a protest environment. Radical political attitudes driven by depression during protests should also be concerned based on the findings of this survey.The political impact of the Internet is a major topic in political communication as it may affect voting behavior, political discussion, and political participation, etc. Most research so far has focused on the role of alternative information and the impact of network structures on social media, which is believed to affect actors’ decision-making based on the information and opinion to which they are exposed [1,2,3]. However, besides the impact of exposure to information and opinion, the political impact of the Internet can be studied from a more everyday life perspective.The political implications of the Internet can be more revealing during times of social and political turbulence. In a massive protest which is emotionally provoking and full of unexpected social and political dynamics, some people are prompted to keep being exposed to information related to the protest. This tendency can be addictive among them. The impact of Internet addiction on psychological well-being is a widely studied topic. In the ongoing Anti-Extradition Law Amendment Bill (Anti-ELAB) Movement in Hong Kong, the society is polarized regarding some radical and militant protests, and thousands of protesters were arrested. Perceived social isolation and depression, as attributes of psychological well-being, are worth investigating in this protest situation. Some people might perceive themselves to be isolated minorities during the addictive exposure to the online public opinion. Others might feel depressed from seeing some protesters sacrificed for the movement in terms of being arrested and beaten up by the police, etc. The relationship between depression and support for radical actions is a new area of research that is under-explored. The Anti-ELAB Movement is characterized for being emotionally eventful and radicalized with persistent support from parts of the public [4]. This movement provided an optimal background for data collection and analysis for this exploratory research. Therefore, with the data collected from students at the tertiary level during a relatively mild period in the movement, this research attempts to explore the relationship among the use of Internet for movement-related information, Internet addiction, psychological well-being, and support for radical actions.The political impact of the Internet on social movements is an important theme in political communication, and there has been a vast amount of literature on the relationship between the Internet and social mobilization. The topic is especially important when many massive protests were leaderless, uncertain, and improvising in the age of social media, such as the Arab Spring uprisings and the global Occupy movement. Explanations related to the Internet and social media were provided. The Internet is an open platform for developing a vibrant landscape of alternative media, where alternative views and information on social movements that are commonly ignored by conventional news media can be widely circulated [2,5]. Frequent viewers of alternative news were also found to be more knowledgeable in protest-related information [6]. Therefore, the Internet can bring a positive effect on social mobilization and cultivate a stronger acceptance of radical actions among frequent viewers of alternative opinions.The second stream focuses on the structure of social networking on social media. The architecture of social media is favorable to exposing people to opinions and information of a similar rather than opposing view. It allows minorities with alternative views to overestimate their influence, discourages people with opposing views to be exposed to each other, and encourages an echo-chamber effect [3,7,8]. The online networking platform also helps strengthen their identity and group efficacy for mobilization when they can easily connect with each other [9,10,11]. Moreover, social media facilitates the mobilization of “connective action” that is crowd-enabled, leaderless, and improvised [12,13,14].Following the trend of the “affective turn” [15], affect and emotions are increasingly considered when discussing the role of the Internet in political communication [16]. The nature of networking is still key to the analysis. Papacharissi [17] gave a comprehensive account of how affect is circulated on social media, and how an affective-networked public is built. Studying university students in urban China, Gan, Lee, and Li [18] found that circulation of negative emotions through “public affair communication via social media” strengthens the impact of social media on political participation. Kim and Kim [19] further found that negative emotion is strengthened when users are exposed to dissimilar views together with uncivil comments.The emphasis on the nature of the Internet and social media in political communication is due to the background of technological determinism of communication studies [20]. The supposedly unlimited amount of information on the Internet drives scholars to compare the impact of online news media to the conventional news media’s ability to set the agenda [21]. The “selective exposure” thesis proposed by Bennett and Iyengar [22] also defines the way of studying the impact of the Internet on public opinion and political attitudes. Against this background, this research attempts to examine the relationship between Internet use and political attitudes by filling the following gaps in the literature. First, instead of considering the infrastructural nature of the Internet and social media to be the analytical premise, this research adopted a user-centered approach by focusing on the experience and psychological impact of obtaining news information online. Second, variables about psychological well-being are often considered as the ultimate dependent variables in a psychological study. This is due to the practical purpose of clinical psychology, which inclines to identify individuals that are more vulnerable to problems related to psychological well-being. However, this research attempts to examine the association between psychological well-being and political attitude, and the possible mediating role of the former. Third, although there is a large volume of literature related to the impact of the Internet on political attitudes and political participation, its impact on radicalization is rarely discussed. Fourth, there are only limited studies on the psychological and attitudinal impacts of the Internet conducted during a protest. To address the above, this research includes the tendency of Internet addiction, fear of missing out (FOMO), and psychological well-being to examine the relationship between Internet use and support for radical actions.Internet addiction is highlighted because it is closely relevant to a social movement context, especially prolonged large-scale political incidents. Many remarkable massive social protests were emotionally eventful in the sense that they are composed of sentimental moments. Emotionally driven actions during protests can affect the overall dynamics between protesters and the government. Examples can be found in major massive protests in the Arab Spring [23]. In Hong Kong, the Umbrella Movement in 2014 was also found to be motivated by unusual grievances and it had a continuous psychological impact on the population across the movement [24,25]. During a massive protest, the context itself can motivate people to have stronger tendency to be exposed to movement-related information. In its extreme form, Internet addiction can be expected within the context of a movement.Internet addiction refers to an extreme degree of obsession to the use of the Internet in the sense that users’ offline social life is interrupted because of indulgence in the online arena. It is an important topic in clinical psychology as Internet addiction can bring a range of problems in people’s psychological well-being. Uses of the Internet, including online gaming and social networking addiction, have been widely studied [26]. On the other hand, FOMO can be an amplified practice of Internet addiction. FOMO refers to “pervasive apprehension that other might be having rewarding experiences from which one is absent” [27]. It implies an anxiety of being out-grouped among one’s peers in terms of circulation of information that is considered to be valuable for in-group bonding. Being an emotional symptom, FOMO does not just take place online; however, in the online realm, FOMO can intensify problematic use of social media that affects the well-being of both the users and their peers [28].The impact of Internet addiction and FOMO on psychological well-being has been widely examined. The research of Wu, Cheung, Ku, and Hung [29] illustrated the positive relationship between the use of social networking sites and its addictive tendency, and it addressed the consequent psychological risk. Studying the addictive use of smartphones, Peper and Harvey [30] found that addictive use of smartphones strongly leads to a range of mental health symptoms, including depression, anxiety, loneliness, etc. People with heavier social media use were found to have stronger perceived social isolation and depression, respectively [31,32]. Similar observations were also found in FOMO. The experiment of Hunt, Marx, Lipson, and Young [33] revealed that FOMO and its associated depression can be reduced by limiting the use of social media. Robinson, Bonnette, Howard, Ceballos, Dailey, Lu, and Grimes [34] explained the relationship between Internet addiction and depression in more detail based on a comprehensive survey. They found that Major Depressive Disorder was more likely to be found among people who had a stronger tendency to compare themselves with other people on social media, who were more eager to maintain a positive image on social media, and had a larger perceived discrepancy between their online and offline identity.To explore the relationship between Internet use and the support for radical actions by a user-centered approach, the above psychological variables are considered. Not only have their relationships been supported, but they are also worth discussing in the context of social movements. First, as mentioned, a massive protest usually includes sentimental moments that induce people to keep themselves updated about the protest. Second, a massive protest is an important event in the public agenda as well as a popular topic for public discussion. People can feel the need to keep updated about the event in order to feel involved in the group alongside their peers. Referring to the observation of Robinson et al. [34], Internet addiction in the context of a movement can lead to depression due to comparison between users and their peers who are highly involved in the movement and adjusting one’s persona on social media to fit the movement atmosphere. Third, a movement context itself can be emotionally provoking. A massive protest is an amalgam of various emotions including grievances, anxiety, hope, desperation, etc. [35]. The impact of addictive exposure to movement-related information can be strengthened in this context. Fourth, given that emotions have a significant place in social mobilization [36], the psychological well-being driven by addictive exposure potentially has a similar role in enhancing support for radical actions.Based on the above discussion, the following research questions and hypotheses are proposed to substantiate the analysis of the relationship between Internet use and support for radical actions.The first hypothesis aims at testing the direct relationship between Internet use and support for radical actions. A positive relationship is partly supported by the research of Lee [37], though his findings focused on the exposure to online alternative media that facilitates the spread of radical views. Therefore, focusing on exposure to movement-related information online in a general sense, H1 aims at opening the discussion by testing their direct relationship:Online information exposure and support for radical actions are positively related.H2 and H3 try to echo the relationship between online information exposure, Internet addiction, and psychological well-being that has been discussed in psychology. FOMO is also included as it is associated with Internet addiction [38] and it fits the movement context that is full of uncertainties and unexpected incidents. Psychological well-being includes depression and perceived social isolation as they are commonly observed as possible consequences of Internet addiction [29,31]. In the context of a movement, depression was found to be an emotional symptom during and after a protest [39,40], but its role is rarely discussed in social mobilization. In addition, perceived social isolation is not covered in the discussion about mobilization and yet, addictive Internet use can lead to a perception of whether some people are part of the majority or minority in a highly polarized atmosphere during a massive protest. The operationalization of the measurements was adjusted due to the context of massive protest in Hong Kong. This will be explained in the next section.Online information exposure relates positively to tendencies of Internet addiction.Online information exposure relates positively to FOMO.Internet addiction relates positively to depression.Internet addiction relates positively to perceived social isolation.
+        FOMO relates positively to depression.FOMO relates positively to perceived social isolation.The respective impact of depression and perceived social isolation on support for radical actions can be made sense of in the context of a movement. Feelings of depression are more ambiguous than anger, fear, and hope which are more frequently discussed in social mobilization. Depression is a mix of negative feelings including sadness, self-disappointment, inefficacy, guilt, etc. Regarding the relationship between depression and radicalism, there was research that investigated how depression as a mental illness related to extreme behaviour and terrorist attacks [41]. However, the relationship between depression and support for radical actions as a general political attitude is rarely discussed. The relationship between the two can be both positive and negative conceptually. Depression can be positively related to support for radical actions as people with stronger depression may seek a more radical change to overcome their depression. In contrast, depression can discourage people from supporting radical actions due to the feeling of powerlessness. Similarly, there was no clear evidence about the impact of perceived social isolation on supporting radical actions. In public opinion studies, people who perceived themselves to be the minority were found to be silent rather than vocal and radical [42]. On the other hand, some people with stronger perceived social isolation consider themselves to be the legitimate frontier in the context of a movement and tend to show stronger support for radical actions. Due to the open possibilities regarding the impact of depression and perceived social isolation, the following research questions are proposed:What is the relationship between depression and support for radical actions?What is the relationship between perceived social isolation and support for radical actions?The last hypothesis is established based on the potential findings of the above hypotheses and research questions, and the literature arguing that the relationship between Internet use and political attitude and participation is intervened by other variables rather than a direct relationship [43,44].The relationship between online information exposure and support for radical actions is stronger when it is mediated by Internet addiction, FOMO, and psychological wellbeing.Online information exposure. The respondents were asked about their frequency of obtaining movement-related information from a list of media outlets. They answered for each media outlet from 1 = “never” to 5 = “always”. The frequency of obtaining movement-related information through online news media, Facebook, Instagram, WhatsApp, Snapchat, Telegram, and online forums was averaged to construct the variable (α = 0.80, M = 3.73, SD = 0.87).Internet addiction. The index of Internet addiction was referenced from the Young’s Internet Addiction Test [45]. The measurements were moderated to match the context of a movement. The respondents were asked to what extent they agree with the following statements: “I spend less time with family and friends because I spend time on surfing movement-related information online”, “I expect to see updated information about the movement online”, “I feel pissed when I am interrupted by the other from surfing movement-related information online”, “I cannot sleep at night because I spend time surfing movement-related information online”, and “my study and work are affected because I spend much time on surfing movement-related information online”. The respondents answered from 1 = “never” to 5 = “always”. The index was constructed by averaging the five statements (α = 0.86, M = 2.75, SD = 1.06).FOMO. Measurement of FOMO was referenced from Przybylski et al.’s [27] 10-item FOMO-scale. Four of them, which were more relevant to the context of a movement, were chosen and revised to be covered in this survey. The respondents were asked how frequently they experienced the following: “I feel bad when my friends know more information about the movement than I do”, “sometimes I find that I spend too much time on knowing the latest information about the movement”, “sharing updated information about the movement (both online and offline) with friends is an important thing for me”, and “I am eager to know updated information about the movement when I am on a vacation”. The respondents answered from 1 = “never” to 5 = “always”. The index was constructed by averaging the score from the four statements (α = 0.74, M = 2.47, SD = 0.92).Perceived social isolation. This set of measurement was referenced from Primack et al. [31] with minor moderations in translation. The respondents were asked to what extent the following statements describe the relationship between the respondent and his/her friends in the Anti-ELAB Movement: “I feel that I am ignored by them”, “I feel that they cannot understand me”, “I feel that I am too different from them”, and “I feel that my friends and I belong to different circle”. The respondents answered from 1 = “totally cannot” to 5 = “totally can”. The variable was constructed by averaging the score from the four statements (α = 0.89, M = 1.71, SD = 0.83).Depression. Five sets of measurements from The Beck Depression Inventory [46] that fit the situation of young people and the context of the movement were used in this survey. The respondents were asked “in each set of statements, please choose a statement that can describe your feeling in this movement”. The statements can be found in Table 1. Each statement refers to different degree of depression, from 1, meaning no sign of depression, to 4, meaning serious signs of depression. The variable was constructed by averaging the score of the five sets of statements to be a 1 to 4 index (α = 0.73, M = 2.06, SD = 0.52).Support for radical actions. The respondents were given a list of radical protest actions which took place during the Anti-ELAB Movement, and they were asked to what extent can they accept the actions, respectively. They answered from 1 = “strongly unacceptable” to 5 = “strongly acceptable”. The list of actions includes “blocking roads”, “interrupting the operation of railway and airport”, “vandalizing railway stations and facilities inside the station”, “vandalizing shops owned by Chinese capital or owners who openly expressed pro-government opinion”, “arson”, “doxing police officers”, “militant attack to policemen”, and “physically attacking people with opposite views who attacked or making nuisance to other protesters (private resolution)”. The variable was constructed by averaging the degree of acceptance of all the actions (α = 0.96, M = 3.41, SD = 1.15). Furthermore, the respondents’ support for “ordinary peaceful protests” was also covered in the survey which is addressed in the analysis for reference (M = 4.74, SD = 0.65).Besides demographics, two variables related to attitude and participation in the Anti-ELAB Movement were included in the analysis as control variables.Support for Anti-ELAB Movement. The respondents were asked how much they support the Anti-ELAB Movement in general, and they answered from 1 = “totally not support” to 10 = “totally support” (M = 8.02, SD = 2.35).Participation in the Anti-ELAB Movement. This variable is constructed based on two questions. First, 12 major protests from 9 June to 20 October were listed, and the respondents were asked to indicate the protests they attended, which gave us a continuous variable for participation in major protests from 0 to 12. Besides the major mass protests, there were numerous protests at the community level that took place in different districts since July. The respondents were asked how many of those protests they attended. They answered from 0 = “none” to 4 = “more than 10”. The variable was constructed by summing the number participating in major mass protests and community-level protests (M = 3.76, SD = 4.37).This research was conducted in Hong Kong during the fifth month of the Anti-ELAB Movement, which is still ongoing at the time of writing. The movement has been eventful in the sense that it witnessed a lot of critical moments that changed the state–society relationship and citizens’ political attitudes. It was initially mobilized to urge the government to withdraw the proposed amendment of the Extradition Bill that could seriously harm the rule of law and liberty in Hong Kong. At a later stage, due to the intensification of conflicts between the police force and citizens, the movement was also driven by public dissatisfaction with the police force [4]. Many citizens were emotionally provoked by the brutality of the police in the protest every weekend. Research on data traffic of a major online forum “LIHKG” from June to August shows that the number of visits rocketed every Monday and Tuesday due to people revisiting the events that occurred during the previous weekend (the data from the online forum were collected and analysed by some authors of this manuscript. Relevant details are in another manuscript that is currently under review). According to a longitudinal survey carried out by the School of Public Health, The University of Hong Kong [47], the degree of depression of Hong Kong citizens during this movement reached an all-time high since the survey began in 2009. Both evidently showed that the Anti-ELAB Movement is an emotionally stimulating event that affects one’s psychological well-being and political attitude. This movement can serve as an appropriate background to study the relationship between Internet use, psychological well-being, and support for radical actions.Young protesters are the core members of the Anti-ELAB Movement [4], and therefore this research solely focuses on tertiary students in Hong Kong. The period of data collection was from 4 to 8 November 2019, which was a relatively mild period in the movement. To ensure diversity of samples, data were collected from various tertiary educational institutes in Hong Kong, which included both universities as well as colleges that offer sub-degree programs. Teachers from each participating institute presented a QR code for the online questionnaire during class breaks and students took part on a voluntary basis. Most of the samples were collected in classes of the General Education curriculum for a better sample heterogeneity. Coffee coupons were offered to respondents to encourage participation.A total of 290 samples were collected. As all questions were set to be mandatory at the digital interface, the completion rate is 100%. Over half of the samples (59.3%) were from females and most of the respondents were aged between 18 and 20 (78.6%). Eighty percent were born in Hong Kong. Regarding their socio-economic status (SES), 26.1%, 27.6%, and 37.4% claimed that they were from the lower, lower-middle, and middle classes, respectively. Most of the respondents identified themselves to be moderate democrats (40.1%) and 21.7% were localists under a broad definition.Table 2 shows the zero-ordered correlations of key variable before hypotheses testing. Both attitudinal support for, and participation in, the Anti-ELAB Movement are positively correlated with online information exposure (r = 0.51 and 0.40 respectively, p < 0.001 for both). It supports the observation that people with stronger involvement in the movement tend to be more attentive to the relevant information, albeit not being part of the main analysis. Internet addiction and FOMO are highly correlated (r = 0.75, p < 0.001), which is consistent with the literature. There is no significant correlation between depression and perceived social isolation although they are both considered to be related to psychological well-being. This result is not unexpected as depression can also be intensified by mutual reinforcement among peers. Besides perceived social isolation, all the key variables are positively related to support for radical actions (r = 0.47 to 0.79, p < 0.001 for all).Models 1 to 3 of Table 3 show the relationships between the independent variables and support for radical actions, while Models 4 to 6 of the same table show the regression analysis for support for peaceful protests that is used as reference. As expected, attitudinal support for the movement strongly associates with support for radical actions (β = 0.63, p < 0.001 in Model 1). There is also a statistically significant but weak relationship with support for peaceful protests (β = 0.18, p < 0.01 in Model 4). Online information exposure has no significant relationship with support for radical actions and therefore H1 is rejected. Interestingly, online information exposure relates positively to support for peaceful protests with an impressive strength (β = 0.38, p < 0.001 in Model 4). This means that online information exposure can prompt people to support social protests only in a general sense. Neither Internet addiction nor FOMO has a significant relationship with support for radical protests, and they have no significant relationship with support for peaceful protests either. Model 3 tests RQ1 and RQ2. It shows that people with stronger depression tend to support radical actions more (β = 0.13, p < 0.01). However, those with stronger perceived social isolation tend to show less support for radical actions (β = −0.07, p < 0.05). The latter finding echoes the spiral of silence thesis that perceived minorities tend to stay mild instead of being vocal [42].Table 4 shows the relationship among online information exposure, Internet addiction, FOMO, depression, and perceived social isolation by regression analysis. People with stronger attitudinal support for the movement have a higher degree of depression (β = 0.31, p < 0.001). People with more online information exposure have a stronger Internet addiction and FOMO (β = 0.29 for both, p < 0.001 for both) and hence H2a and H2b, respectively, are supported. While online information exposure has no direct impact on depression, Internet addiction relates to depression positively (β = 0.28, p < 0.001). FOMO has no impact on depression. Neither Internet addiction nor FOMO is related to perceived social isolation. Only H3a is supported among the whole set of H3.Table 3 and Table 4 provide a preliminarily positive sign for testing the mediating effect. The results of Sobel’s test show that Internet addiction is a significant mediator between online information exposure and depression (z = 3.08, p < 0.01), while depression is a significant mediator between Internet addiction and support for radical actions (z = 2.29, p < 0.05). Therefore, H4 is partly supported. Figure 1 illustrates the path of mediating effect by structural equation modelling. To improve the model, FOMO and perceived social isolation were removed while all the other control variables were kept. The goodness of fit is short of being optimal (RMSEA = 0.24, CFI = 0.65, X2 = 344.01, p < 0.05). Nevertheless, the findings in structural equation modelling can support the mediating role of Internet addiction and depression that was found to be significant. A bootstrap test with bias-corrected 95% confidence intervals on 5000 bootstrapped samples was conducted to further substantiate the result. The result shows a significant indirect effect of Internet addiction and depression on the relationship between online information exposure and support for radical action (β = 0.16, p < 0.001).This research explores the relationship between Internet use, addictive behaviour, psychological well-being, and radicalism. The findings open doors for further research on political communication, psychology, and social movement studies. First, this research provides a concrete explanation for the relationship between online information exposure and support for radical actions, which is still an under-explored dimension in both political communication and social movement studies. Besides the influence of content such as alternative news and similar opinions, this research shows that the psychological process of addictive Internet use to depression will lead people to support radical actions. The user-centered approach argues that a protest atmosphere itself can drive people to become addictive in obtaining movement-related information, which indirectly brings stronger acceptance of radicalization. However, it does not mean that contents and opinions circulating on the Internet are minor issues. Instead, Internet addiction can be strengthened by exposure to certain types of contents and opinion. The relationship between Internet addiction and the type of contents circulating online can be a meaningful topic for follow-up research to strengthen the understanding of how radicalization in a protest can be influenced by online communication.Second, the significant relationship between depression and support for radical actions is the key contribution of this research. While the role of some emotions including anger, grievances, desperation, hope, anxiety, etc., in mobilization and radicalization has been widely explored, the coverage of depression is still thin. It is probably because depression is more readily associated with demobilization rather than making a positive impact. Yet, this research shows the potential to further investigate the political implication of depression. Regarding its relation to support for radical actions, a possible qualitative explanation can be drawn from our observation in the Anti-ELAB Movement. That is, the feeling of depression amongst certain people was based on the perception and experience that they could not contribute much, but at the same time witnessing the sacrifice that many people made during the movement. They therefore would support the people who attempted to fight for the goals through alternative and radical means. In this sense, the positive relationship between depression and support for radical actions includes demonstration of solidarity and sense of compensation. This can also explain why attitudinal support for the movement relates to depression positively, yet the latter has no relationship with frequency of participation. In this sense, the study of depression within a social movement is beyond the interests of public health and clinical psychology and deserves further investigation in social movement studies.Third, this research opens a new dimension to study Internet addiction. Given that the online realm represents a “virtual realm” of society that “authentic” social life could be interrupted by Internet addiction, studies related to psychological risk from Internet addiction tend to focus on users’ detachment from social life and its impact on personal and public health. This research reveals that the risk of depression symptoms can also come from online addiction due to an intensive alert to a society in turbulence. This finding represents an alternative paradigm to study Internet addiction. More importantly, in the age of social media and leaderless “connective action”, politically motivated Internet addiction will be more prevailing rather than declining. Figuring out those who are vulnerable to depression and who need professional advice during a protest is a practical concern for clinical psychologists. While the relationship between depression and extremism and terrorist actions is still debatable [41], this research found that depression and support for radical actions as political attitude are associated. Follow-up research is necessary to further examine those who are more likely to conduct deviant and radical activities due to feelings of depression.The limitations of this research must be addressed. First, being a cross-sectional survey conducted during a protest, respondents’ feelings and attitudes can inevitably only be recorded at a particular time. During a prolonged and eventful movement like the Anti-ELAB Movement, people’s emotions fluctuate as unexpected incidents unfold. This research was conducted during a relatively calm period before a major incident broke out the following week. This explains why the respondents’ degree of depression was relatively less serious. In an ideal situation where data can be collected shortly after a significant incident, a comparison between the models in a normal situation during a protest and shortly after an incident would be possible.Second, the overall sample size is somewhat dissatisfactory. This is due to a series of major incidents that took place during the second week of November, which led to the cancellation of all remaining classes of the teaching semester in most tertiary institutes. This clearly has a significant impact on data collection. The weakness is that descriptive findings are not very referential because of the margin of error. However, this does not weaken the value of the multivariate analysis as it still brings a lot of insights for follow-up research. Key variables can be replicated in surveys conducted during the later stage of the movement and even in normal situations. Moreover, although young people with a tertiary level of education made up the main body of the anti-ELAB Movement [4], the psychological well-being and political attitudes of secondary school students should also be investigated, as they face more layers of pressure from both school and family.Third, being a cross-sectional survey, the inter-relationships of some variables are hypothesized to be casually related instead of empirically tested by experiment. Having said that, the path from online information exposure to support for radical actions as indicated in the study forms the foundation of the follow-up experiment. What kind of content can stimulate stronger Internet addiction? To what extent depression is a consequence of Internet addiction rather than a motivation of Internet addiction? These are all interesting questions to be investigated by carrying out experiments. In this case, this paper opens up a new path to study online addiction and depression in the context of a movement.Fourth, the measurements of Internet addiction, FOMO, perceived social isolation, and depression were modified based on the existing scales of which their reliability is promising [27,31,45,46]. The modification enables the analysis to be more focusing on people’s everyday life and mental condition under a context of movement. However, their validity can be uncertain when the context of movement is emphasized in the operationalization. Respondents’ answers can go extreme if there is an unexpected incident taken place during the data collection period. Researchers need to pay attention to this limitation when follow-up research on similar topics is conducted.This research aims to examine the relationship between online exposure to movement-related information and support for radical actions during a social movement. In this research, their relationship was found to be stronger when they are mediated by Internet addiction and depression. People with more online exposure to movement-related information are more likely to have Internet addiction. The latter is positively related to depression. Then, stronger depression prompts stronger support for radical actions. This finding has profound implications for political communication, social movement studies, and political psychology, as it is an exploratory attempt to adopt psychological well-being to be an intervening variable in order to explain the relationship between exposure to online information and radicalism. Besides this key finding, several findings outside the major argument should be noted. First, participation in the Anti-ELAB Movement relates positively to support for radical actions, but it has no relationship with support for peaceful protests. In contrast, online exposure to movement-related information relates positively to support for peaceful protests, but it has no relationship with support for radical actions. Third, a strongly perceived level of social isolation discourages people from supporting radical actions.G.T. performed analysis and wrote initial draft of the manuscript. E.P.W.H., H.-K.C.A.-Y., and S.Y. proofread and edited the manuscript, and supervised the research team. All authors have read and agreed to the published version of the manuscript.The research received no external funding.The authors declare no conflict of interest.Analysis of mediating effect of Internet addition and depression on online information exposure and support for radical actions. The entries are standardized coefficients. Missing values are replaced by means. N = 290. *** p < 0.001. Gender, age, SES, birthplace, attitudinal support for Anti-ELAB, and participation in Anti-ELAB are included in the analysis, but they are not shown in this figure for simpler demonstration.Operationalization of depression.Correlations of key variables.Note. Missing values are replaced by means. N = 290. *** p < 0.001, * p < 0.05.Regression analysis for support for radical protests and peaceful protests.Note. The entries are standardized coefficients. Missing values are replaced by means. N = 290. *** p < 0.001, ** p < 0.01, * p < 0.05.Regression analysis for Internet addiction, FOMO, depression, and perceived social isolation.Note. The entries are standardized coefficients. Missing values are replaced by means. N = 290. *** p < 0.001, ** p < 0.01.

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+These authors have contributed equally to this work and are co-first authors.The study protocol of a prospective and randomized controlled trial for the assessment of the efficacy of nature activity therapy for people with Fibromyalgia (NAT-FM) is described. The primary outcome is the mean change from baseline in the Revised Fibromyalgia Impact Questionnaire (FIQR) score at post-treatment (12 weeks) and at 9 months of follow-up, and secondary outcomes are changes in the positive affect, negative affect, pain, fatigue, self-efficacy, catastrophising, and emotional regulation. A total of 160 patients with fibromyalgia will be divided into two arms: treatment-as-usual (TAU) and NAT-FM+TAU. Pre, during, post, +6, and +9 months assessments will be carried out, as well as an ecological momentary assessment (EMA) of intrasession and intersessions. Results will be subjected to a mixed group (NAT-FM+TAU vs. TAU) × phase (pre, post, +6 months, +9 months) general linear model. EMA intrasession measurements will be subjected to a 2 (pre vs. post) × 5 (type of activity) mixed-effects ANOVA. EMA between-session measurements obtained from both arms of the study will be analysed on both a time-domain and frequency-domain basis. Effect sizes and number needed to treat (NNT) will be computed. A mediation/moderation analysis will be conducted. According to the American College of Rheumatology (ACR), Fibromyalgia (FM) is a chronic disease of unknown etiology, characterised by the presence of generalized musculoskeletal pain and other symptoms, such as fatigue, waking unrefreshed, and cognitive problems [1]. The etiopathogenesis of FM involves several mechanisms, the most notable of these being the sensitization of the central nervous system (CNS). Abnormalities in the ascending and descending pathways associated with pain processing have been observed in FM [2]. The chronic nature of pain, wide range of symptoms, and comorbidity with mental disorders (mainly anxiety and depression) strongly impact on the well-being and quality of life of patients with FM [1,3,4].Currently, the prevalence of FM among the general population is estimated to be around 2% worldwide and 2.6% in Europe [5]. In Spain, a prevalence of 2.4% is reported in the general population over 20 years of age, corresponding to 4.2% for women and 0.2% for men [6]. The direct costs (medical care, prescription of medicines, etc.) and indirect costs (absenteeism from work, loss of work, etc.) of FM are close to 11 billion € per year [7]. Due to the variety of complex factors involved in FM, recent years have seen the development and testing of various pharmacological [8] and non-pharmacological [9,10] treatments for management of the condition. The side effects associated with pharmacological treatments, along with their suboptimal clinical effects, have recently prompted the European League against Rheumatism (EULAR) to recommend that these treatments should only be used to control pain and sleep disturbances caused by FM [11].Multicomponent treatments integrating exercise therapy (ET), cognitive behavioural therapy (CBT), and pharmacological treatment have generally been one of the most beneficial alternatives for improving quality of life, increasing functional capacity, and decreasing chronic pain in FM patients [12]. Randomized controlled trials (RCTs), testing for the simultaneous combination of ET and CBT, have been shown to be the most effective non-pharmacological treatments for FM [13]. Treatments based exclusively on ET have contributed to the reduction of symptoms of pain, fatigue, and depression, as well as to the improvement of mental health, psychological well-being, and physical function [14,15]. CBT-based treatments have favoured the acceptance of FM, strengthening of self-efficacy, development of coping strategies, and the reduction in depressive moods [16]. Pain neuroscience education (PNE) has been shown to be more effective than biomedical education [17] for FM and it is proving to be a key strategic piece in both the physical and cognitive approach of FM patients [18,19,20].The strengths of such treatments, coupled with the identified benefits of exposure to natural contexts for people’s mental health, justify the need to explore new interventions for FM patients conducted in nature. Considering the moderate benefits that have been reported for the four therapeutic components mentioned above, it seems necessary to test empirically, for the first time, the synergistic effects of its combination. There is some evidence that nature can exert a synergistic effect when added to other therapeutic ingredients [21,22,23,24,25,26]. In this context, the Nature, Activity Therapy for people with Fibromyalgia (NAT-FM) project has emerged as a new generation of therapeutic treatments for intervention of health problems, which integrates CBT, PNE [27], ET, and nature exposure. Although activity-based interventions in nature have demonstrated positive effects for treating emotional, cognitive, and behavioural functioning in both the general population [28,29,30] and clinical population [31,32], as far as we know there is only one clinical trial that provides empirical evidence of their efficacy in FM patients [33]. This paper describes the design characteristics of the NAT-FM treatment in comparison with a treatment-as-usual (TAU). The objectives of the RCT are the following: (a) to analyse the efficacy of the NAT-FM program as an add-on to TAU in improving the functional status (primary outcome) of FM patients; (b) to compare the efficacy of NAT-FM treatment with respect to TAU in improving affectivity, emotional regulation, perceived competence, self-esteem, self-efficacy, anxiety, depression, and other secondary outcomes; and (c) to identify factors that may act as mediators or moderators of the efficacy of NAT-FM treatment (age, years of evolution, psychological inflexibility, etc.). The RCT protocol was developed following the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) [34] and has been registered with ClinicalTrials.gov (Trial registration: NCT04190771). This study will employ a 9-month, randomized controlled trial (RCT) design, with two treatment arms. For the reporting of the RCT, we will follow the guidelines of the Consolidated Standards of Reporting Trials (CONSORT) [35]. The two arms of the treatment will be: (a) TAU (control group) and (b) TAU+NAT-FM (intervention group). Patients in both arms received TAU, since NAT-FM will, in principle, be a complementary treatment to that which is usually provided by the Spanish National Health System [36].A total of 160 patients with FM will be recruited from the Central Sensitivity Syndromes Unit (CSSU) at the Vall d’Hebron University Hospital (Barcelona, Spain). The sample size was established using IBM SPSS SamplePower 3.0 (IBM, Chicago, IL, USA), considering the results of a meta-analysis of therapies in nature [21], which reported an average effect size of g = 0.50, regarding clinical variables. With the anticipation of a 20% dropout and setting alpha = 0.05 and power 1-b = 0.80, the estimated sample size is n = 80 participants per condition. The sample size in each of the arms and the treatment follow-up period were estimated in such a way that they will be sufficiently representative to capture important results.Patients visited consecutively by the physical therapist of the CSSU from November to December 2020 who met the selection criteria will be recruited. The inclusion criteria will be: (a) adults ≥18 years old, (b) to meet the 2010–2011 ACR diagnostic criteria for FM [1,37,38], and (c) to be able to understand and agree to participate in the study. The exclusion criteria will be: (a) participating in concurrent or past RCTs (previous year) and (b) exhibiting comorbidity with severe mental disorders (e.g., psychosis) or neurodegenerative diseases (e.g., Alzheimer’s) that would limit the ability of the patient to participate in the RCT.The main researcher (M.S.) will, through an initial interview, provide an overview of the study to FM patients interested in participating who met inclusion and exclusion criteria. Prior to being randomly allocated to treatments (TAU or TAU+NAT-FM), informed consent forms will be collected, which will include a detailed description of the characteristics of the interventions. Patients will also be informed that their participation will be voluntary and that they will be able to withdraw at any time, with the guarantee that they will continue to receive their usual treatment. This research will be conducted in accordance with the ethical standards set forth in the 1964 Declaration of Helsinki and was approved by the hospital’s Ethics Committee (PR(AG)120/2018). Patient data will be treated confidentially, ensuring that only the research team can access this information after recoding the name and personal identity number. Only the principal investigator will have access to the patient code key, which, according to current data protection legislation in Spain, will be stored separately in a safe place. The participants will be assigned to the intervention group (TAU+NAT-FM) or control group (TAU), employing a SPSS v25 randomization list.The pharmacological treatment will not be modified during the RCT. Only rescue paracetamol (maximum 1 gram every 8 hours) will be allowed if there is worsening of pain. Patients will be evaluated before (pre), after the 6th session of treatment (during), and after (post) treatment, as well as 6 and 9 months after baseline assessment (follow-up). Measurements shall be made according to the time established for their administration: (a) Classical structural assessment (CSA): pre, during, post, and follow-up; and (b) ecological momentary assessment (EMA): intrasession (session log) and intersessions (day log between sessions). The flow chart of the RCT is presented in Figure 1. Recruitment of patients: November 2019Finalisation of patient monitoring period: July 2020Publication of results: June 2021NAT treatments are a new generation of therapeutic programs for health intervention, in which CBT, PNE [27], ET, and nature exposure are integrated. NAT-FM is conceived as an add-on therapy and, in particular, has the primary therapeutic objective of helping patients to improve their functional status. The secondary objectives are to contribute to improving their affectivity, emotional regulation, and self-efficacy, as well as to reduce their perception of pain, fatigue, and catastrophising. Other variables that are usually improved by these treatments are perceived competence, self-esteem, stress, sleep quality, anxiety, depression, psychological inflexibility, kinesiophobia, physical function, and functionality. Table 1 and Table 2 show an outline of the NAT-FM.The NAT-FM design process was guided by the procedures established in the protocol and the proof of concept study. The therapeutic objectives were selected by taking into account the results of a systematic review of the psychological characteristics of people with FM (affective, cognitive, metacognitive, and personality profiles) [39] and the validation of a panel of experts made up of researchers and psychologists (M.S., J.P.S.-M., A.F.-S., J.L.M.-U., J.V.L, and A.S.), who evaluated the existing scientific evidence and the clinical and investigative relevance of each objective. The panel concluded that the processes to be included in the treatment are self-efficacy, negative affect, positive affect, emotional regulation, and catastrophising. The activities indicated in Table 1 were selected considering the results of an empirical study on the therapeutic potential of 10 activities in nature [40]. The number of activities practiced in each session was adapted according to the established targets, taking into account the progression of the patients and the evolution of the treatment. The activities addressing each target were selected considering the therapeutic potential identified by the expert panel.The sectors (natural spaces) in which the outdoor sessions will be conducted have been validated by experts to guarantee their suitability for the treatment activities [40]. The geographical areas are Sant Genís Forest (coordinates N 41° 25.930 E 2° 8.237) and Les Escletxes del Papiol (coordinates N 41° 26.319 E 2° 1.101). The researchers conducted a proof of concept study (J.P.S.-M., E.G.-T., C.M.-C., and A.S) in these sectors to test the manualisation of procedures and to evaluate the suitability of the NAT-FM structure based on the testing of a series of representative sessions [41]. The protocol of the NAT-FM is the result of the consensus of the proposed instruments, of the moments of assessments corresponding to each phase of the treatment, and of the administration platforms used. The decision to combine different assessments (CSA+EMA) is motivated by the need for a strategy that could obtain more precise information about the dynamics of the variables to be evaluated and, in particular, could record the affective and cognitive impact of each activity, as well as its transfer to everyday life. The frequency of administration of the EMA has been established from analysing the results of a systematic review on the characteristics of its use in studies with patients with chronic pain [42]. The NAT-FM treatment will be carried out in a group-based format in groups made up of a maximum of 20 patients per session with a total of 12 weekly 2 h sessions (1 session per week). The sessions will be directed by the M.S., who is a physiotherapist of the CSSU of Vall d’Hebron University Hospital and also a psychologist and sports technician with the required legal qualifications for conducting this activity.The TAU provided to patients in the control group of this study is based primarily on the prescription of drugs adjusted to the symptomatic profile of each patient, with complementary advice on aerobic exercise and pain neuroscience education adapted to the physical capacities of the patients. Patients of the control group will be placed on a waiting list so that at the end of the RCT they can benefit from the NAT-FM treatment. The participants of the intervention group (TAU+NAT-FM) and the control group (TAU) will complete the instruments described below. Assessment will be organized considering the timings (CSA+EMA) that were established from the results of the proof of concept study [41]. Table 3 shows the measurement scheme and timings for the NAT-FM treatment protocol.The CSA will measure general information, clinical characteristics and screening, primary outcomes, secondary outcomes, and additional secondary outcomes. These instruments will be applied to patients in both the control group (TAU) and intervention group (TAU+NAT-FM).The Socio-demographic and clinical questionnaire will be used to obtain general and clinical patient data (age, educational level, socioeconomic status, marital status, ethnic group, personal medical history, years of FM diagnosis, comorbid medical conditions, etc.).The Structured Clinical Interview for DSM Axis I Disorders (SCID-I) [43] will be used for the diagnosis of mood disorders. It is based on the research version of SCID-I and the DSM-IV criteria. The Revised Fibromyalgia Impact Questionnaire (FIQR) comprises three dimensions: physical dysfunction (scores from 0 to 30), overall impact (scores from 0 to 20), and intensity of the symptoms (scores from 0 to 50), which are used to measure the impact generated by FM during the last week. It consists of 21 items, which are answered on a numerical rating scale of 11 points (from 0 to 10). Total scores can range from 0 to 100, with higher scores reflecting greater deterioration. The Spanish version has an adequate internal consistency (α = 0.93) and acceptable test-retest reliability (r = 0.84) [44].The Positive and Negative Affect Schedule (PANAS) is used to evaluate positive and negative affects. It consists of two dimensions (positive affect and negative affect) of 10 items, each answered on a 5-point Likert scale. Total scores of each scale range from 10 to 50, where higher scores indicate a greater presence of the specific affectivity. The Spanish version has an adequate internal consistency for the positive affect (α = 0.92) and for the negative affect (α = 0.88) [45].The Cognitive Emotion Regulation Questionnaire (CERQ) is used to assess individual differences in the cognitive regulation of emotions. The instrument measures nine 2-item dimensions (self-blame, blaming others, acceptance, refocusing on planning, positive refocusing, rumination, positive reappraisal, putting into perspective, and catastrophising). This study will use the short 18-item version. Responses are given on a 5-point Likert scale ranging from 1 (almost never) to 5 (almost always). Total scores for each dimension range from 2 to 10, with the highest scores indicating the specific cognitive strategy most used. The Spanish version has an adequate internal consistency (α = 0.77 to 0.93) and acceptable test-retest reliability (r = 0.60 to 0.85) for the subscales [46].The Personal Perceived Competence Scale (PPCS) is used to measure perceived competence. It consists of eight items that are answered on a 6-point Likert scale. Total scores of each scale rangefrom 8 to 48, with higher scores indicating greater perceived competence. The Spanish version has an adequate internal consistency (α = 0.83) [47].The Rosenberg Self-Esteem Scale (RSES) is used to measure self-esteem. It consists of 10 items that are answered on a 4-point Likert scale. Total scores of each scale range from 10 to 40, where higher scores indicate higher self-esteem. The Spanish version has an adequate internal consistency (α = 0.87) and acceptable test-retest reliability (r = 0.72 to 0.74) [48].The Pain Catastrophizing Scale (PCS) is used to evaluate catastrophic thoughts associated with pain. It consists of three dimensions (rumination, magnification, and helplessness) of 13 items in total, which are answered on a 5-point Likert scale. Total scores on each scale range from 0 to 52, with higher scores indicating more catastrophising. The Spanish version has an adequate internal consistency (α = 0.79) and acceptable test-retest reliability (r = 0.84) [49].The Perceived Stress Scale (PSS) is used to evaluate the stress perceived by people during the previous month. This study will use a 4-item version with a 5-point Likert type response format. Total scores range from 0 to 16, with higher scores indicating greater perceived stress. The Spanish version has an acceptable internal consistency (α = 0.77) [50].The Hospital Anxiety and Depression Scale (HADS) is used to quantify the severity of anxiety and depression symptoms. It consists of two dimensions (anxiety and depression) of seven items, each responding on a 4-point Likert scale. Total scores of each scale (HADS-A and HADS-D) range from 0 to 21, where higher scores indicate greater severity of symptoms. The Spanish version has an adequate internal consistency for anxiety (α = 0.83) and for depression (α = 0.87) [51,52].The Psychological Inflexibility in Pain Scale (PIPS) is used to assess psychological inflexibility in patients with pain. It consists of two dimensions (avoidance and cognitive fusion with pain) of 12 items, which are answered on a 7-point Likert scale. Total scores of each scale range from 12 to 84, with higher scores indicating greater psychological inflexibility. The Spanish version has an adequate internal consistency (α = 0.90) and test-retest reliability (r = 0.97) [53].The Tampa Scale for Kinesiophobia (TSK-11) is used to assess fear of pain and movement. It consists of 11 items, which are answered on a 4-point Likert scale. Total scores of each scale range from 11 to 44, where higher scores indicate a greater fear of pain and movement. The Spanish version has an adequate internal consistency (α = 0.79) [54].The physical function of the 36-Item Short Form Survey (SF-36) will be used to assess the physical function typically affected in patients with chronic pain. This dimension comprises a total of 10 items, which are answered on a Likert scale of 3 points. Total scores on each scale range from 0 to 100, with higher scores indicating better physical function. The dimensions have shown optimal internal consistency (α = 0.94) [55].The UKK Walk Test (UKK) [56] is used to assess people’s physical fitness, endurance, and cardio-respiratory capacity (maximum VO2). The test is performed in a straight line with no difference in height between the two extremes. In this study, the distance from the beginning to the end of the route will be adapted from 2 km (original version) to 1 km, given the specific characteristics of the population of this study. In addition, we will use Polar Advantage heart rate monitors with their respective software to mark the times and obtain the average heart rate of the patients during the route. The Adverse effects Assessment Checklist [57] is an ad hoc measure to check for potential adverse events (e.g., headaches, dizziness, physical injuries) across the interventions and follow-up.The Patient Global Impression of Change (PGIC) [58] and Pain Specific Impression of Change (PSIC) [57] are self-reported measures frequently used as indicators of meaningful change in treatments for chronic pain. Responses are given on a 7-point Likert scale ranging from 1 (much better) to 5 (much worse). The PGIC is one item that refers to the perception of global improvement, whereas the PSIC asks about the impression of change in more specific domains (physical and social functioning, work-related activities, mood, and pain). These scales will be completed by the participants assigned to the treatment (NAT-FM+TAU) group.EMA is used to assess: (a) the specific short-term impact of each activity and (b) the transfer of the treatment effects to everyday life. Measurements during the sessions (intrasession assessment) will be taken before and after each activity in nature using an online form. Measurements of the daily records between sessions (intersession assessment) will be carried out through an app, in which patients will have to respond six times a day (twice in the morning, twice in the afternoon, and twice at night). Intersession instruments will be applied to patients in both the control group (TAU) and intervention group (TAU+NAT-FM). However, intrasession instruments will only be applied to patients in the intervention group (TAU+NAT-FM).The Self-Assessment Manikin (SAM) [59] is used to assess the affective state of people. It consists of three blocks of diagrammed pictograms in a continuous line, representing the following three dimensions of the affective response: valence, arousal, and dominance. Each scale has a 9-point Likert response format. The total scores on each scale range from 1 to 9. Higher scores on valence indicate greater positive mood; higher scores on arousal indicate greater activation and alertness; whilst for dominance a higher score indicates greater perception of control and personal confidence. These three dimensions of the affective response were evaluated both in intrasession assessment and in intersession assessment.Single-item questionnaires: For the assessments of the variables fatigue, pain, and sleep quality, the three items of the Visual Analog Scale (VAS) of the FIQR were selected. For stress and self-efficacy, ad hoc questions were designed with a single item, rated on a scale from 0 to 10, in a VAS format. Higher scores indicate greater perceived fatigue, pain, sleep quality, stress, and self-efficacy. The variables fatigue, pain, and sleep quality were evaluated by intersession assessment, whereas the variables energy, pain, stress, and self-efficacy were evaluated by intrasession assessment.Data analyses will be conducted by means of the statistical program SPSS v25 and MPlus 7.0. Initially, descriptive statistics will be calculated for all measures of the study (general, clinical characteristics/screening, and primary/secondary/additional secondary outcomes). Subsequently, multivariate analyses will be conducted to define the effect size of the intervention at the different assessment periods: CSA (pre, during, post, and follow-up) and EMA (during). Continuous variables will be analysed using the Kolmogorov–Smirnov test to assess normal distribution and the Levene test for equal variances. First, we will use the Student’s t-test to examine the baseline between-group differences in sociodemographic and clinical characteristics. The primary between-group analysis to assess the effect of treatment will be conducted on an intention-to-treat (ITT) basis with the FIQR total score as a continuous variable and assuming data missing at random. This involves using 2 × 4 mixed-effects ANOVA with the group (TAU+NAT-FM vs. TAU) as the between-groups factor and phase (pre, post, follow-up+6, follow-up+9) as the within-subjects factor. Corrected ηp2 (partial eta-square) will be estimated for the full model (group and phase main effects and group x phase interaction). We will also report the effect size (Cohen’s d) for each pairwise comparison, using the pooled baseline SD to weight the differences in the pre-post means and to correct for the population estimate. Separate models will be estimated for each of the secondary outcomes using the same analytical strategy. In addition, to assess the clinical significance of the improvement in the primary outcome (FIQR), we will classify participants into two categories (responders vs. non-responders to treatment), using the following criterion: ≥20% reduction in the pre–post FIQR total scores [60]. This classification will be used to compute the number needed to treat (NNT) in NAT-FM compared with TAU. Finally, we will examine whether the effect of NAT-FM on the primary outcome at post and at the 6 and 9-month follow-ups is mediated/moderated through pre–post changes in secondary measures and personal factor variables (age, years from diagnosis, severity), using a structural equation model. According to the proposal of Luciano et al. [60], change scores before and after NAT-FM treatment will be calculated for these variables, as well as change scores before follow-up for the outcome variables. The analysis of temporality will increase the possibility of drawing conclusions about causality relationships. In this process, the data of the patients of the treatment with the greatest participation in the intervention will be analysed, defining participation as a minimum of 75% attendance of the sessions (per protocol analysis). The Benjamini–Hochberg correction for multiple comparisons will be applied; a procedure to detect false findings designed to overcome the limitations of other common procedures [61].Complementary analyses will be conducted. Firstly, EMA intrasession measurements obtained from the NAT-FM treatment group will be subjected to a 2 (pre vs. post) × 6 (type of activity) mixed-effects ANOVA for pain, fatigue, self-efficacy, stress, and affect in order to assess the short-term impact of the planned activities. Secondly, EMA between-session measurements obtained from both arms of the study will be analysed both on a time-domain (single regression linear model for each dependent variable) and a frequency-domain basis (spectral analysis for each dependent variable) in order to assess transfer of the treatment effects to daily life.The main objective of this article is to report the design characteristics of the NAT-FM treatment in comparison with TAU. The protocol for this RCT was designed using SPIRIT recommendations and recorded in a clinical studies database (ClinicalTrials.gov) in accordance with CONSORT guidelines. If the findings of the RCT are sufficiently robust, NAT-FM treatment could be offered as an add-on intervention to the usual treatment (TAU), with a coherent strategic approach that is adjustable to the health resources allocated to FM patients. In this RCT, in addition to evaluating the clinical effects of NAT-FM treatment in the mid- and long-term, we will seek to recognize relevant moderators and mediators of clinical change.The possible withdrawal of patients from the trial will be one of the risk components that will be considered. In this regard, two strategies will be developed: (a) conduct a sensitivity analysis to determine the impact of adherence to the NAT-FM protocol on the observed effects and (b) combine this RCT to the MOTI-NAT programme (Motivational intervention for Nature Activity Therapy) [62], which will have as its main objective the development of specific therapeutic adherence strategies for patients linked to the different protocols of the NAT Project based on the increased motivation to participate in these therapies. NAT-FM treatment is presented as the first intervention that integrates CBT, PNE [27], ET, and nature exposure. The integrative commitment of this RCT is based on the recognition of the scientific evidence identified in different studies in the components of treatment. The results obtained in the proof of concept study [41], designed as a preparation for this protocol, suggest moderate to strong size effects of the therapy, which constitutes an empirical basis for the rationale underlying the intervention.The results derived from the planned full trial are expected to constitute a preliminary step towards the development of this new generation of therapeutic treatments for intervention in various health problems based on CBT combined with PNE and ET in natural contexts. A deeper understanding of the specific therapeutic effects of NAT-FM could be very informative when considering the relevance of this approach as a complementary model of health intervention, specifically in the domain of chronic pain. With regards to FM, it is worth remembering that there are currently no curative treatments and that developing new approaches that improve the functionality of patients would be of great benefit both at a social and personal level (due to the high impact and prevalence of this condition), particularly given the healthcare (high use of public resources) and economic (high consumption of health resources/job losses) consequences of this illness.This study represents the first attempt for combining pain neuroscience education, exercise therapy, psychological therapy, and exposure to nature in the treatment of fibromyalgia.
+      A randomized controlled two-arm trial is planned to address safety and potential efficacy of NAT-FM (Nature Activity Therapy for Fibromyalgia) in comparison with traditional care (TAU).NAF-FM combines the classical structural assessment (CSA) and ecological momentary assessment (EMA) to obtain more precise information about the dynamics of the variables to be evaluated, to record the affective and cognitive impact of each activity, and to identify its transfer to everyday life.As indicated in previous studies, there is scientific evidence that the improvement in functional status of the people diagnosed with fibromyalgia can be attained by the direct intervention in processes such as the positive and negative affect, self-efficacy, pain, fatigue, emotional regulation, and catastrophising.Some issues arise from the complexity of combining the components of the intervention, particularly those related to logistics and the diversity of activities to be completed by the participants, and the determining the ‘effective’ treatment components.A randomized controlled two-arm trial is planned to address safety and potential efficacy of NAT-FM (Nature Activity Therapy for Fibromyalgia) in comparison with traditional care (TAU).NAF-FM combines the classical structural assessment (CSA) and ecological momentary assessment (EMA) to obtain more precise information about the dynamics of the variables to be evaluated, to record the affective and cognitive impact of each activity, and to identify its transfer to everyday life.As indicated in previous studies, there is scientific evidence that the improvement in functional status of the people diagnosed with fibromyalgia can be attained by the direct intervention in processes such as the positive and negative affect, self-efficacy, pain, fatigue, emotional regulation, and catastrophising.Some issues arise from the complexity of combining the components of the intervention, particularly those related to logistics and the diversity of activities to be completed by the participants, and the determining the ‘effective’ treatment components.Systematic revision of the literature and conceptualization, M.S., J.P.S.-M., J.L.M.-U. and A.S.; panel of experts for the analysis of the therapeutic potential, M.S., J.L.M.-U. and A.S.; MOTI-NAT-FM study for the analysis of the determinants for initiation and adherence to the programme, M.S., J.P.S.-M., C.M.-C., J.L.M.-U. and A.S.; treatment design, M.S., J.P.S.-M., M.A., A.F.-S., J.L.M.-U., J.V.L. and A.S.; protocol design, M.S., J.P.S.-M., E.G.-T., A.F., M.A., A.F.-S., J.V.L. and A.S.; instruments selection, M.S., J.P.S.-M., M.A., A.F.-S., J.V.L. and A.S.; proof-of-concept, J.P.S.-M., E.G,-T., C.M.-C. and A.S.; paper writing, reviewing, and editing, M.S., J.P.S.-M. and A.S.; paper revision, M.S., J.P.S.-M., C.M.-C., M.A., A.F.-S., J.L.M.-U., J.V.L. and A.S.; original draft preparation, J.P.S.-M.; ethical approval and trial registration, M.S., M.A. and J.V.L. All authors have read and agree to the published version of the manuscript.This research was funded by the Vall d’Hebron Institute of Research Funding, Autonomous University of Barcelona (Ideas Generation Program, Price 2018), and Parc Sanitari Sant Joan de Déu. A.F.-S. has a Sara Borrell contract and J.V.L has a Miguel Servet contract, awarded both by the Institute of Health Carlos III (ISCIII; CD16/00147 and CPII19/00003, respectively). The funding bodies did not have any role in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.The authors declare no conflict of interest. Flow chart of the randomized controlled trial (RCT).Structure of the Nature Activity Therapy for people with Fibromyalgia (NAT-FM), indicating the activities to be performed and the psychological targets to be addressed in each of the sessions.Note. The “X” expresses the sessions in which each activity is planned. The numbers of the targets’ columns are referred to the steps described on Table 2. Cognitive behavioural intervention on primary and secondary outcomes is distributed along the sessions. * Hiking is a homework assignment to do as a therapeutic exercise with cognitive targets. ** Shinrin Yoku is understood as mindfulness in a natural context. Nordic walking (NW); yoga (YO); hiking (HK); photography (PH); Shinrin Yoku (SY).Steps in pain neuroscience education and in the cognitive-behavioural treatment for each outcome.Note. To present in a most understandable way this information to patients, a power point has been used with pictures, examples, and metaphors, according to the recommendations [18]. All these aspects have been reinforced point by point in each session with the book Explain Pain in Spanish [27].Measurement scheme and timings for the NAT-FM treatment protocol.Note: “X” expresses the moment when each assessment instrument is planned to be administered. Structured Clinical Interview for DSM Axis I Disorders (SCID-I); Revised Fibromyalgia Impact Questionnaire (FIQR); Positive and Negative Affect Schedule (PANAS); Cognitive Emotion Regulation Questionnaire (CERQ); Personal Perceived Competence Scale (PPCS); Rosenberg Self-Esteem Scale (RSES); Pain Catastrophizing Scale (PCS); Perceived Stress Scale (PSS); Hospital Anxiety and Depression Scale (HADS); Psychological Inflexibility in Pain Scale (PIPS); Tampa Scale for Kinesiophobia (TSK-11); 36-Item Short Form Survey (SF-36); UKK Walk Test (UKK); Adverse Effects Assessment Checklist (AEAC); Patient Global Impression of Change (PGIC); Pain Specific Impression of Change (PSIC); Self-Assessment Manikin (SAM); Visual Analog Scale (VAS). * Only for NAT-FM arm.

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+Urbanization is playing a key role in big cities of developing countries, which, in effect, is increasing the population. This study takes care of the mega infrastructure project (Orange Line Metro Train (OLMT)) to explore and identify the H&S (Health and Safety) factors that affect the local residents and the main key stakeholders working on the project. A Sequential Mixed-Method approach of the OLMT-project includes qualitative and quantitative methods were adopted. The data have been collected from the targeted population working on the OLMT-project through a questionnaire. The main key finding of the study indicates that poor planning and a lack of communication between the public and government led to frustration. The most significant factors that identified in the study were unsafe to work practice, project scope constraints, lack in technical and material support, unsafe/bad condition, health/environment degradation, declination and loss of resources and time, no proper emergency system, and negligence in adopting safety rules and laws. The study also revealed that the consensus should also be noticed between the key stakeholders (e.g., contractors, clients, safety officials, academia) in the second round of the Delphi survey of the project. The study findings will help the key stakeholders to prioritize their energies towards attaining zero levels of inadequate health and safety practices in infrastructure projects. The study outcomes can also be generalized for the other developing countries having a similar work scenario.The migration of people from villages to cities is the concept of urbanization [1,2]. Urbanization is triggered due to change in local market conditions, poverty, unemployment, lack of basic facilities, and resources for growth as the push factors to move from villages, while all of the factors include technological advancement, better policies, better opportunities, employment, industry, and education [3,4,5]. The urban environment includes advancements in the shapes of the streets, its structure, nature, and the potential to foster the business economy of any country [5]. In any developed country, overall 80% of streets used to build and esteem the business activity for maintaining the urban environment [1,5]. This trend of the urban environment is observed throughout the world and it is at its peak in Japan, India, Bangladesh, Mexico, the USA, Brazil, Nigeria, Indonesia, and Pakistan [2,6,7,8]. The countries start to urbanize with the development of technology, advanced civic amenities, opportunities for education, facilities for transport, business, and social interaction [2,9]. In the process of the urbanization, the infrastructure of a country has great importance for its development and economy boosting [10]. Infrastructure-projects involves the complexities and safety issue that leads to an unsafe environment and their environmental impacts for different project key stakeholders and the residents [1,5]. Infrastructure-projects have continued to cultivate and commercialize the world economy and globalization has driven us to scientific advancement, convenient communication, rapid transportation, and facilitate the development of the construction process [4,11,12]. The Governments in developing countries, where approximately 85.4% of the world’s population lives, develop infrastructure projects to achieve their social and economic sustainable development objectives [13,14]. Infrastructure projects are prevailing in developing countries, and during the recent decades, many infrastructure projects are in their execution, development, and planning phases [6,7,15]. In South Asia, Pakistan is among the most rapidly urbanizing countries [9], and the part of the population in urban areas has increased from 17% to 37% from 1951 until 2010 and up to 43% to 2018 survey [12,16,17,18]. In addition, it is calculated that half of the population will live in urban areas in the next 10 to 15 years [18,19]. It is estimated in recent studies that the planet will be populated up to 2030 of 8.5 billion people [20]. The constant trends for the urbanization will have an enormous impact on the climate change and the environmental destruction. Furthermore, this will produce a unfavorable environment for the urban habitants while maintaining the developing cities [1]. According to the statement of the Saldaña-Márquez, 2019 half of the places to be urbanized up to the 2023 has not been built yet, Hence, there is an esteemed need to establish the environmental codes and practices in developing countries to counter the environmental destruction for the human beings [1,5]. Population growth and migration are the major forces behind urban growth [7,19]. Migration in developing cities is major due to the search for employment, education, and better opportunities [15]. An increase in population demands more public transportation [21]. The environment might get impacted by the infrastructure-projects and affect the surroundings of residents; thus, it is not rare to attract criticism from several stakeholder groups. The aim of any public infrastructure and construction (PIC) projects is to improve the comfort of society [22,23]. The development of any public infrastructure construction (PIC) project from the initialization phase to the handover phase can have controversies, and it might affect the interests positively as well as negatively. Representatives of these interests are referred to as the project stakeholder [2,24]. OLMT (Orange Line Metro Train) is one of its kind projects, and yet no study has taken place regarding the health and safety of residents, or issues arising due to such a project. Therefore, the literature on similar projects from the rest of the world is used to support the research. This study has a case scenario, which presents to identify and explore the contributory factors that cause an unsafe environment in the construction industry.Society contribution and consensus are important in the planning of mega construction projects [25]. A systematic participatory framework for PIC projects was proposed in the “express rail link project” from the findings and lessons learned of the China–Hong Kong express rail service linkage project. The researchers focused on the methodology of consensus building and keeping because of previous practices, suggested for improvements in it. In consensus building, they suggested that more effort was to be made in the growth of saturation point reaching of all the stakeholders. From the study, it was proven that, for the success of the project, all of the stakeholders are important. They also concluded that stakeholders were also affected by the project. Thus, their consensus is very important and should be considered while the planning phase, so that risks and people issues could be mitigated [25].Previous research studies also prove that infrastructure-projects can often be planning disasters and they can generate heavy impacts on society as well as cost over runs [26,27]. It is due to the result of a lack of public participation [28]. The benefits from such projects occur on a certain level. Municipal area level gets benefited, residents may get adversely affected, and may incur a lot of issues [29]. It may include mobilization and displacement due to space formation for new facilities, increased traffic, noise, and air pollution. In the world, Korea became the fifth country to operate and own a high-speed railway in 2004, called ‘Korea Train Express (KTX)’. Mega construction projects involve a lot of planning and management for their success. If planning is insufficient, the project leads to delay or may fail, as the same case with the KTX project. Five major delays were found in the KTX project, which is “Lack of owner’s abilities and strategies to manage hi-tech oriented mega-project, frequent route changing triggered due to conflicts between public agencies and growing public resistance from environmental concerns, inappropriate project delivery system, lack of proper scheduling tool tailored for a linear mega project, and redesign and change orders of main structures and tunnels for high-speed railway” [30]. There are a variety of procedures and programs that can be planned that support the performance of safety and to avoid environmental hazards for project phases for employees as well as for the public [1,2,5].Safety practices in construction companies in developing countries are not so developed and have proved to be risky due to the involvement of different types of project complexities [2,31,32]. According to one’s findings, in the construction industry of developing countries (i.e., India, Bahrain, Bangladesh, Nepal, Pakistan, Iran, Malaysia), safety performance is not satisfactory, which are creating the environmental risk, in addition, stakeholders only emphasize reducing time and cost [21,31,33]. The client does not allocate any safety budget and according to results, 61.8% of construction companies do not have any policy related to safety or workers as well as locals stakeholders [8,15,34]. Construction safety is considered as a second responsibility in the construction projects [18,35,36], which causes an unsafe environment and makes project risky [12,32,37,38].The safety policies are almost invisible in the construction industries of developing countries; furthermore, the occurrence of the work-site accidents is increasing day by day [31,38,39] due to the low level of the inspection and regulating bodies besides [40,41], in addition work-site accidents are threatening the work environment and construction safety [41]. The main cause of the work-site accidents is low level of workers trainings [35,37], and this is considered to be the most ignored safety practices in the construction industry [34,42,43]. Safety training programs are also not conducted [36,37], due to which workers do not know about their job-specific safety before start of their project work [15,32], though from the review, it shows a direction towards the results that more importance was given to measuring the factors of projects delays factors, project planning and scheduling, and causes of accidents [40,44], a little attention was given to identifying the major factors that produce an unsafe environment and environmental codes for the residents and the key stakeholders of the infrastructure projects in developing countries.The main objectives of the Study is: (i) to study, identify, and explore the H&S (health and safety) factors, (ii) to prioritize the H&S factors in term of their significance, (iii) to apply the practical knowledge of construction health and safety in infrastructure projects, and (iv) to establish the guidelines for the construction enterprisers regarding H&S and environmental impacts for the future. According to author knowledge, no study has yet been investigated to prioritize the fundamental roots of unsafe construction environment and environmental impacts in infrastructure projects of Pakistan. The study findings will also provide the path to the key stakeholders (i.e., contractors/subcontractors, clients, consultants, academia) to prioritize their efforts towards achieving an effective and safe environment for the construction projects.This section presents the research design involving both Narrative (A type of Qualitative methods) and Quantitative methods (i.e., Delphi survey) to overcome the limitation of the single design [4,15,45]. The data (i.e., Semi-structured interviews) were collected from the targeted population (local residents of the OLMT-project) by adopting the Narrative technique. A total of 32 nodes were extracted after the screening of the raw data while using the qualitative analysis. Later on, these collected nodes were trailed by the qualitative methods (two-round Delphi Survey) from the key project stakeholders (targeted population) to measure and prioritize the identified factors (themes) as their significance level. The methodology is illustrated in detail in the below segment (as shown in Fig.1).There are two types (i.e., Qualitative & Quantitative) of data that have been collected in this study and, furthermore, it can be described in two ways. (i) semi-structured interviews (narrative technique), which were taken from the local residents (targeted population for qualitative methods) living around the “OLMT-project”. In this method, data have been recorded in audio-tapes and later on it was screened out and manuscript to generate the nodes (semi H&S factors) by the help of statistical tools (NVIVO vs 10, Statisticians). In addition, expert opinion was also a major part of this step. A total of 10 major themes (H&S factors) were selected from the selected semi factors (nodes). (ii) The identified themes were used again for quantitative analysis (two-round Delphi survey); however, for the Delphi-Survey, a questionnaire has been developed based on the (five-point Likert scale) to collect the data from the target population (project key stakeholders i.e., contractors, safety officials, client, academia). The instrument (questionnaire) that was adopted for the semi-structured interviews consisted of 15 major open-ended questions. The construction industry experts validated these open-ended questions using the pilot survey. The questionnaire (instrument) used for the narrative technique (a type of qualitative study) was designed in such a way that it can be used to collect the data from the targeted population easily [8,15]. Interviews were conducted to include views of the people who lacked education and were unable to answer the questionnaire in writing. More questions were to be asked at the spot and a complete interview was to be audio recorded for complete narration and transcription in original form. There was a total of 26 stations, and thirteen areas were spotted (each area comprises two stations) for the interviews to complete the process of a qualitative study. The 26 stations and the thirteen areas of the “OLMT-project” are depicted below in Table 1. A Delphi survey was conducted based on narrative study (semi-structured interviews), which consist of (i) demographics (i.e., stakeholder group, experience, a position at project sector) and (ii) H&S factors (identified themes). The targeted population (key stakeholders i.e., contractors, clients, academia, safety officials) were asked to prioritize the H&S factors according to their significance based on Likert scale (five-point) by using the Delphi technique, with 1 showing “not important” 2 “somewhat important” 3 “important, 4 “very important”, and 5 “extremely important” [4,15,46,47,48]. The success of the Delphi method based on the experience of the panel members [2,4,47]. According to Ameyaw and Chan (2015), the guarantee of the reliability of the collected data depends upon the respondent’s organization and its versatile experience regarding its particular working domain (sector) [49]. Hereafter, the panel would be a mixed-group enriched with diverse experience [50]. The panel size is suggested by Hon et al. (2010) to be seven members that can be amplified up to 50 [50,51]. An effort has been made for this study to collect the minimum 10 responses from each respondent (e.g., contractors/subcontractors/client, safety officials, academia), with each member having a diverse experience. By adopting this selection method, it was felt that the results achieved would be impartial and more reliable.The objective of the Delphi survey is to gain a specific opinion of the different groups having versatile experience in a particular area [27]. A criterion has been set for the population (project key stakeholders), who must have a registration from the Engineering Council (PEC) as a professional member i.e., professional engineer, client, and contractor. A Delphi-survey is commonly used in the construction management field [4,52]. A two-round Delphi survey was adopted to verify as an accurate and precise technique for element prioritization [22,43,48]. The complete research methodology adopted for (OLMT) study is illustrated in detail (as shown in Figure 1).In the first phase, 61 responses were collected. Table 2 shows the distribution of the respondents along with their versatile experience. The data were collected in the first round through field links, postal mails (printed instruments), and the face to face meetings. The identities of the respondents were concealed to each other to get the more reliable results [53], and it continues to the repetition of the round until the consensus was established and sharing the desired statistical results to the responders after the completion of the first round. The data that were collected from the first round were used for the statistical analysis to test whether the consensus had been made between the respondent groups or not. The mean score was calculated for the second round and presented to the respondents using the online questionnaire. It was an open choice that was given to the respondents to either sustain or change their original grading. Nevertheless, for this round, the respondents lessened up to 49, as shown in (Table 2) with their distribution as clients (11), academia (11), safety officials (13), and contractors (14). The Delphi survey was stopped when the consensus was made between the respondent’s group. The results of the data analysis are presented in the next section.This section signifies two types of analysis. (i) qualitative analysis (i.e., creation of nodes, themes/factors development, intercorrelation of the H&S factors, (ii) quantitative analysis (i.e., normality & reliability of the data, ranking, and prioritization of H&S factors based on mean scoring.Table 3 shows the 32 nodes and their occurrence on the different stations of the OLMT-project. There is an increase of population told by the interviewee of area 1,3,8,11 and no public transport facility was provided (2,4,6–10) from the last six years, which take us to the situation that there was also poor condition of the roads (1,3,4,6,8,9,10,11) and unsafe traffic route (4,5,7,9–12) and declination in public daily routine (2,4,6,8,10,11,13) through the execution of the project. The condition becomes worst when rain (1–4,6,8–12) happens due to God’s will situation [17,32]. The interviewee of all areas elaborated that there is an increase in population due to which current services did not fulfill the transport requirements of people, which means there was a lack of public transport [54] and lack of public transport results in an increase of private transport [22,55].According to the study of Qureshi (2010), there was a poor condition and lack of public transport, as well as handy car loans via banks, causes a lot of increase of private transport in Lahore [55]. This drove us to a major issue of traffic congestion [7,56] due to which people suffer a lot. The interviewee of AREA 1,4,8, and 11 said that there was no need for the OLMT-project route in their areas, but the interview of AREA 2,3,5,6,7,9,10,12, and 13 said that they were optimistic regarding the future benefit that this will facilitate in travelling and there was a need of public transport in this area. Zaman (2012) clarifies, in his study, that there was an increase in transport on roads in urban areas of Malaysia which was causing severe traffic congestion, air pollution, and deteriorating the environment of cities [57]; the same situation has accrued within Lahore [54]. Most of these nodes were common in all areas of the OLMT-project. However, few areas gave differently results as according to the interviewee of AREA 1,2,4,7,8, and 10, there was a proper use of sign-boards, but, according to the interviewee of AREA 3,5,6,9,11–13, there was no proper use of sign-boards. This shows that proper usage of sign-boards is missing in seven out of thirteen areas. According to the interviewee of AREA 1,3,4,6–8,10,11, and 13, they were not informed regarding the start of OLMT-project in those areas, but according to the interviewee of AREA 2,7,5,9 and 12, they were told regarding the start of the OLMT-project in those areas. This clearly shows that residents of many areas were not informed about the project before its start, which drives us to the lack of project planning [7,31,32,56,58]. Wang & Zuo (2016) describe in his study that the low level of information leads to limited knowledge, limited knowledge, then consequence leads to irrational behavior by the public [44], which justifies the results of our study.The Interviewee of AREA 2,4,5,7,9,10–13 said that there were no piles of material or mud in those areas, but the interviewee of AREA 1,3,6, and 8 said that piles of mud and material were spread [9] due to the construction of OLMT-project, which clearly shows that there were ten areas in which piles of material and mud were on pavements due to which unsafe conditions occurred in these areas [59]. According to Wang & Zuo (2016), during the project development, the social and environmental effects of projects have been misjudged and have not usually been taken into account [44]. The same case was with the high-speed rail mega-project in Germany, which was condemned for not taking environmental disorders into account [28]. These issues disrupt communities and habitants [4,9,55,60].The interviewees also noticed the use of the heavy machinery (1,2,3,6,7,9,11) causing so much noise pollution [2,19] and no advancement in tools [6,61] on site (1,2,4,5,6,9,10,11). It was also revealed by the interviewee that there was debris (1,3,4,6–8,11) everywhere and environmental hazards (2,4,6,9–11) were also noticed on the sites. In addition, people also have a health problem [2,62] i.e., drug addiction (3,5,6–9,11–13).According to interviewee of AREA 1,2,4,6, and 13, workers of these areas properly use personal protective equipment, but, according to the interviewee of AREA 3,5,7–12, the workers of these areas use partially or no personal protective equipment, which shows that safety practices were not so good in all areas, which justified the findings of the Khan (2012) [15]. According to his study, the most ignored safety practices in construction industry are related to health and safety training [12,15,22], which is not provided to employees/ workers of subcontractor, due to which they are not aware of safety practices and it results in causing a hazardous situation for themselves and others around, which cause incidents [17]. Safety training programs [2,31] are also not conducted, due to which technical workers do not know about their job-specific safety before the start of their project work. This leads to unsafe work practices and conditions. [4,43,63]. According to interviewee of AREA 1,2,4,6–8,10–12, their businesses were in loss with the start of the OLMT-project, which shows that there was a loss of resources [15] due to the construction of OLMT-project in nine areas out of thirteen. There was traffic congestion [64] in the area of 2,4, and 6, and the traffic condition was normal in other areas told by the interviewees.The interviewee of AREA 2,4,6,8–11 revealed that there were a lot of work accidents [15] and the death of locals and workers (2,4,6,8,10) in these areas. The interviewee of AREA 8 has revealed a death case, that there was the death of 18–20 workers of the OLMT-project due to falling of the wall. Similarly, according to the interviewee of AREA 6, there was the death of seven people due to the accident of crane, which is on work of OLMT-project, with a rickshaw having seven passengers, one of them was a boy of eight years. The Interviewee of AREA 5 mentioned a car accident in which the back screen of the car shattered into pieces due to the fall of tools during cleaning pillars from the worker of the OLMT-project team. Similarly, no emergency system was installed [15] for accidents (1,3,4,7,9,10,12,13) and no insurance policy for health of workers (1,2,3,7,9,10,12,13). Unskilled workers (1,4,6,8,11,12) and no awareness for the project execution (3,5,8,10,11,13) were also identified from the interviewees [9,56]. The outsourcing of materials (3,4,6,8,9,10,12) was at its peak and there was not a proper reporting system between teams and workers (2,5,6,7,11,12), which shows a complete lack of planning and work quality [7,32,65].From these all major nodes (semi factors), which were the most common in all thirteen interviews, ten themes (H&S factors) were generated. They were developed after finding nodes. These 10 major themes/factors are as follows:(1)Poor Project Planning [15,66](2)Limited Information [7,18,31](3)Unsafe work Practices [9,17,67](4)Project Scope Constraints (Schedule, Budget) [7,65](5)Lack of Technical & Material Support [68,69](6)Unsafe/Bad Condition [40,70](7)Health/Environment Degradation [12,15](8)Declination and loss of Resources & Time [19,31,67](9)No Proper Emergency System [7,19](10)Negligence in Adopting Safety Rules and Law [17,31,56,58,67]Poor Project Planning [15,66]Limited Information [7,18,31]Unsafe work Practices [9,17,67]Project Scope Constraints (Schedule, Budget) [7,65]Lack of Technical & Material Support [68,69]Unsafe/Bad Condition [40,70]Health/Environment Degradation [12,15]Declination and loss of Resources & Time [19,31,67]No Proper Emergency System [7,19]Negligence in Adopting Safety Rules and Law [17,31,56,58,67]Developing the framework is the final step in the interpretation of data in the qualitative approach [7,31,43], which is shown as below in Figure 2, that all of the themes correlate with each other [8,15], which will be explained in the next section i.e., data analysis.According to the developed framework, with the increase in population [2], available transport facilities did not fulfill the transport requirements of people i.e., lack of public transport [31]. The local government started the OLMT-project in order to compensate for this issue [71]. However, at the start of the project, due to poor planning [43] and keeping them uninformed and not considering issues of stakeholder resulted in limited information, lack of awareness, and scope creep [56]. Support contractors and sub-contractors did not follow the safety rules and practices due to poor planning and lack of technical knowledge and material [64], which triggers unsafe work practices [54]. Limited information and unsafe work practices lead to the poor condition of roads, hazardous situations, piles of material, and combinedly prompt unsafe/poor conditions [15,65]. Air pollution, dust, noise, and many other associated risks, including health risks, like breathing problems, allergies, and cough, etc. increased a great deal and affected the people adversely due to the construction of OLMT-project [9,15,31]. This triggered two major themes i.e., health/environment degradation and decline and loss of resources [17]. A lot of people have been affected due to the unsatisfactory conditions of environment and health. Resources, like buildings, have also been affected and human resource [34] has been affected a great deal. The passerby’s also face similar problems, as those people are also locals of that area for a certain period of time. A lot of accidents included injuries and deaths of common people, which involved both the passersby and the residents, which triggered two other two major themes/factors i.e., no proper emergency system and negligence in adopting the safety rules and laws [6,7,31,56].A statistical tool that was developed by the IMB called Statistical Package for Social Science (SPSS vs. 25) and Microsoft Excel was used to collect and analyze the data. Shapiro–Wilk-normality test was performed to check either data was normally distributed or not. The results show that the identified significance value was less than 0.05 (p < 0.05) for both rounds of the Delphi survey of all the factors. In this case, it requires the non-parametric test for further analysis [4,15]. Cronbach’s coefficient α was conducted for both rounds of the Delphi survey, besides, the statistical test was led for each respondent group to access the reliability of the collected data. The results show that all of the values were more than the 0.7, as shown in (Table 4 and Table 5), and the data are reliable and can be conceived for the more analysis [15,32,72].In this table, factors represents as e.g., A = Poor project planning; B = Limited information; C = Unsafe work practices; D = Project scope constraints (schedule, budget); E = Lack in technical & material support; F = Unsafe/bad condition; G = Health/environment degradation; H = Declination and loss of resources & time; I = No proper emergency system; and, J = Negligence in adopting safety rules and law.The health and safety factors were calculated and organized from not important to extremely important based on their mean, in addition, the respondent’s groups were asked to identify and prioritize the H&S factors on the scale of 1 to 5, where 1 represented the not important and 5 represented extremely important. Overall, 10 factors were ranked based on their mean score not only for all respondents, but also for each respondent group (Table 4 and Table 5). Table 4 shows the ranking of the H&S factors of the first round. The factor “Limited information” (mean 4.244) was selected as the very important used by the respondents and ranked 1st based on their mean. Likewise, the factor “Poor project planning” was selected as the important (mean 3.246), as per their significance, and then ranked 10th in the group. The “factor” Unsafe work practice (mean 4.372) was ranked first (Table 5) by the respondents of the second round of Delphi survey and conceived as very important, as per their significance from the group. Similarly, the “factor” Negligence in adopting safety rules and the law was ranked 10th (mean 3.372) by the respondents and considered as the very important as per their unified significance level. The deep analysis of both rounds of the Delphi survey revealed that some of the respondents have refined the ranking of the factors in the second round and some have switched their ranking in second rounds. The factor A (mean 3.246), C (mean 3.836), D (mean 4.000), E (mean 4.033), F (mean 3.787), and H (mean 3.475) enhanced their ranking in second round; A (mean 3.629), C (mean 4.372), D (4.030), E (mean 4.327), F (mean 3.794), and H (4.088) from ranked (10th,6th,5th,4th,7th,8th) to (8th,1st,4th,2nd,6th, 3rd). In the same way, the factors; B (mean 4.244), G (mean 4.230), I (mean 4.049), and J (mean 3.262) has substituted their ranking in second round; B (3.749), G (mean 3.571), I (mean 3.992), and J (mean 3.372) from (1st,2nd,3rd,9th) to (7th,3rd,5th, 10th). The consensus between the respondent’s groups (e.g., contractors, clients, safety officials, academia) was also developed after the second round of the Delphi survey. In the first-round, contractors and academia had a consensus for factor (A and B), while in the second round the consensus exists between clients and academia (ranked fifth) for factor A (Table 4 and Table 5). Similarly, in the first round, the factor D (ranked 3rd) has consensus between clients and safety officials and, in the second-round, consensus exists between clients, contractors, and safety officials for factor D (ranked 4th).In this table, factors are represented as e.g., A = Poor project planning; B = Limited information; C = Unsafe work practices; D = Project scope constraints (schedule, budget); E = Lack in technical & material support; F = Unsafe/bad condition; G = Health/environment degradation; H = Declination and loss of resources & time; I = No proper emergency system; and, J = Negligence in adopting safety rules and law.The Factors E and F (ranked 4th,6th) have consensus between clients and academia in the first-round, while in the second-round factor G (ranked 3rd) has consensus on clients and contractors. The factors H and I (ranked 10th,9th) had consensus between (contractors, safety official) and (safety official and academia) in the first round. Though the three respondent groups (e.g., contractors, safety officials, academia) have consensus for factor H (ranked 3rd) in the second round of the Delphi survey. The factor J (ranked 9th) has consensus between the contractors, safety officials, academia in the first round. However, the consensus has also been noticed between (clients, safety officials) and (contractor and academia) for factor (ranked 6th and 9th) in the second round. All of the H&S (health and safety) factors were ranked based on their mean score gained after the second round of the Delphi survey. The scale has been drawn to measure the significance of each factor as: not important (mean <1.5); somewhat important (mean 1.51 ≤ mean ≤ 2.5); important (mean 2.51 ≤ mean ≤ 3.5); very important (mean 3.51 ≤ mean4.5); and, extremely important (mean ≥ 4.5) [15,63,73].The results in (Table 6) indicated that the mean score of all the factors in both rounds were less than the mean score 4.5 (extremely important), which shows that their significance level was very important (3.51 ≤ mean score ≤ 4.5) in both rounds which is quite a higher level of significance [73].The results also direct that the two factors “poor project planning” and “declination and loss of resources & time” has increased their significance level based on their mean score from “important” to “very important” (highlighted by upward arrow) [74,75,76], other factors have a significance level based on mean score as “limited information (significance as V. imp) in both rounds [15,20,77,78,79], unsafe work practices (significance as V.imp) in both rounds [61,76,80], project scope constraints e.g., schedule, budget (significance as V.imp) in both rounds [81,82], lack in technical and material support (significance V.imp) in both rounds, unsafe/bad condition (significance V.imp) in both rounds, no proper emergency system (significance V.imp), negligence in adopting safety rules and laws (significance Imp) in both rounds of the Delphi survey [15,20,49,77]. Likewise, the significance level of the factor “health/environmental degradation varies from the first-round (V.imp) to second round (Imp) and the factor “declination and loss of resources & time) from important(first round) to very important(second round) [15,19,79,82]. This study witness to mark that not a single factor was graded below 2.5 and each factor has a significant level as important or very important. Hence, it is concluded that all of the identified factors have a significant role in the infrastructure project e.g., OLMT-project with a perspective of health and safety [4,15,83].The study has presented the H&S factors that cause the construction process of infrastructure projects to slow down and produce a risky environment [4,34] for the workers. The study based on the mixed-method strategy of OLMT-project encompassed semi-structured interviews and the Delphi survey. The qualitative data were collected from the targeted population (local residents of the OLMT-project) while using the semi-structured interviews (occupying Narrative technique). A total of 32 nodes were generated from the qualitative analysis, which was lagged by a two-round Delphi survey (quantitative method) from the targeted population (key stakeholders i.e., contractors, academia, client and safety officials) to prioritize the identified factors as per their significance. The qualitative data were screened out and went for analysis by the help of statistical tools (NVIVO and Statisticians), which results in the extraction of the total (10) Health and Safety factors. The Delphi survey (quantitative analysis) was conducted to check the consensus between the respondent groups of clients, contractors, academia, and safety officials, which resulted in a rational consensus that was noticed between the key stakeholders of the project, as shown in Table 4 and Table 5. For further analysis of the data, Cronbach’s α was applied to check the reliability [17,32] of the data, which gives higher values in both rounds of the Delphi-survey.The Health and Safety Factors (H&S) were signified and prioritized through mean score ranking analysis. All of the H&S factors are concise in the table (6) in order of their significance, which is from “extremely important” to “important”, indicating that there is an extreme need to emphasize on the all prioritized health and safety factors of the construction projects [4,15].
+      The analysis shows that the most significant factors e.g., poor project planning; Declination and loss of resources and time; limited information; No proper emergency system; unsafe/bad condition; project scope constraints (schedule, budget) and lack in technical and material support were graded as very important [8,9,15] and the factor (negligence in adopting safety rules and law) graded as “important” in the second round of the Delphi-survey, as indicated in Table 6.The respondent groups highlighted that these major factors have a strong consensus, which was also noticed, besides the academia and the clients group having strong consensus on the factors “poor project planning” after the second round of the Delphi survey [15].A strong consensus has been developed between the client, contractors, and safety officials for the factor “project scope constraints (schedule, budget)” after the second round of Delphi survey which shows that it is the most significant factors as per their occurrence and significance level [4,17,43]. The factor (declination and loss of resources and time) was graded as “most important” and all of the respondent groups were agreed on their common consensus [4,56]. The factor “unsafe work practices” emerged to be the first most significant factor [34] and the factor “health/environment degradation” was graded as the 10th most significant factor in this study [4,15,84].Although the significance level of the next eight factors ranked from second to ninth in (Table 6) were measured as very important (poor project planning, limited information, unsafe work practices, lack in technical & material support, project scope constraints (schedule, budget), unsafe/bad condition, declination and loss of resources and time, no proper emergency system) to important (health/environment degradation, negligence in adopting safety rules and law) [4,35].The analysis shows that the most significant factors e.g., poor project planning; Declination and loss of resources and time; limited information; No proper emergency system; unsafe/bad condition; project scope constraints (schedule, budget) and lack in technical and material support were graded as very important [8,9,15] and the factor (negligence in adopting safety rules and law) graded as “important” in the second round of the Delphi-survey, as indicated in Table 6.The respondent groups highlighted that these major factors have a strong consensus, which was also noticed, besides the academia and the clients group having strong consensus on the factors “poor project planning” after the second round of the Delphi survey [15].A strong consensus has been developed between the client, contractors, and safety officials for the factor “project scope constraints (schedule, budget)” after the second round of Delphi survey which shows that it is the most significant factors as per their occurrence and significance level [4,17,43]. The factor (declination and loss of resources and time) was graded as “most important” and all of the respondent groups were agreed on their common consensus [4,56]. The factor “unsafe work practices” emerged to be the first most significant factor [34] and the factor “health/environment degradation” was graded as the 10th most significant factor in this study [4,15,84].Although the significance level of the next eight factors ranked from second to ninth in (Table 6) were measured as very important (poor project planning, limited information, unsafe work practices, lack in technical & material support, project scope constraints (schedule, budget), unsafe/bad condition, declination and loss of resources and time, no proper emergency system) to important (health/environment degradation, negligence in adopting safety rules and law) [4,35].This study presents the health and safety (H&S) factors involved in the process of construction in infrastructure projects, which permits the identification process of the health and safety issues in construction projects among all sectors. Though the non-availability of reliable data for these types of complex infrastructure projects narrowed this research study to evaluate and identify the primary factors that cause health and safety issues in infrastructure projects in developing countries. Overall, 32 nodes (semi factors) were generated by using the narrative technique (semi-structured interviews) from the targeted population (local residents); furthermore, these identified nodes were rectified and then screened out to extract the themes (major factors). A Delphi-technique (quantitative analysis) was applied to test the consensus between the key stakeholders (e.g., contractors, clients, academia, safety officials). The major outcomes taken from the study after applying the research methods are as follows:There was a positive consensus achieved between the respondent groups after the second round of the Delphi-survey and this consensus was prioritized for significance level. The consensus that was perceived between the client of having mean (3.930) and contractor (mean 4.177) for the factor (poor project planning), which was ranked fifth after the second round of the Delphi survey, which authenticates the findings of the [4,9,17]. A mutual consensus was also noticed between all of the respondent groups for the factor “declination and loss of resources and time” after the second round.The factors “unsafe work practice” having an accumulative mean value of (4.372), lack in technical and material support (mean 4.327) was ranked as (1st and 2nd) with a significance level of (very important). Besides, the factor “Negligence in adopting safety rules and law” with the mean value of (3.372) and the factor (Health/environment degradation) with the mean value of (3.571) was graded as “important” and ranked as (10th and 9th).All of the respondent groups were agreed except the academia for the factor “Project scope constraints (schedule, budget)” with the mean value of (4.260, 4.211, 4.225) and having a priority of (ranked 4th).There was a positive consensus achieved between the respondent groups after the second round of the Delphi-survey and this consensus was prioritized for significance level. The consensus that was perceived between the client of having mean (3.930) and contractor (mean 4.177) for the factor (poor project planning), which was ranked fifth after the second round of the Delphi survey, which authenticates the findings of the [4,9,17]. A mutual consensus was also noticed between all of the respondent groups for the factor “declination and loss of resources and time” after the second round.The factors “unsafe work practice” having an accumulative mean value of (4.372), lack in technical and material support (mean 4.327) was ranked as (1st and 2nd) with a significance level of (very important). Besides, the factor “Negligence in adopting safety rules and law” with the mean value of (3.372) and the factor (Health/environment degradation) with the mean value of (3.571) was graded as “important” and ranked as (10th and 9th).All of the respondent groups were agreed except the academia for the factor “Project scope constraints (schedule, budget)” with the mean value of (4.260, 4.211, 4.225) and having a priority of (ranked 4th).There are many stakeholders involved in their own responsibilities in construction projects. The contractors and the subcontractors are considered to be the major’s stakeholders in the construction sector, because they are answerable for the project budget, execution and project timeline limit [31,63,85]. In addition, all of the budget and the project scope is based on the clients and contractors [31] and the project safety depends upon the safety officials [9]. Hence, these stakeholders need to play a vital role to achieve better safety performance in the construction industry, besides, they have also been suggested to regulate the adequate safety practices, training, and safety awareness campaigns to enhance the safety compliances.This study is limited to only infrastructure projects e.g., OLMT-project that helps to boost the economy of the country [31,41]. The stakeholders that are involved in the survey were limited to the enlisted firms under Engineering Council (PEC), Pakistan; furthermore, future research can be conducted in developed and non-developed countries to investigate the health and safety factors involved in the infrastructure projects. There is a major need to adopt and implicate the systematic approach of the health and safety practices in the local construction environment. Finally, the health and safety standards (codes) need to be developed for mega infrastructure projects in developing countries i.e., Pakistan.A.N. and X.S. conceived & designed the concept; A.N. and S.A.R.S. performed the literature review; A.N. and Q.M.U.D. contributed in the data collection; M.B. helped to provide technical support to collect the data from the (OLMT-project) and the respondents including (public/private departments), M.I.K. contributed in analysis tools; A.N. wrote the paper. X.S. has supervised the work, and X.S. and S.A.R.S. reviewed the work to improve the outcomes. All authors have read and agreed to the published version of the manuscript.This research is fully funded by the China Scholarship Council and National Natural Science Foundation of China (71971196).The authors declare no conflict of interest.Research Methodology adopted for (OLMT) study.The Developed framework of health & safety factors of (OLMT-project).Orange Line Metro Train (OLMT) areas and stations.Group Wise distribution of the respondents for two rounds of Delphi survey.Note: Digits in brackets “()” shows the respondents of the second round in Delphi survey.Health and safety nodes (semi factors).First Round of Delphi Survey.Note: M = Mean; R = Rank.  Present consensus between contractors and safety officials.  Presents consensus between clients and safety officials.  Presents consensus between clients and academia.  Presents consensus between safety officials and academia.  Presents consensus between contractors, safety officials, and academia.Second Round of Delphi Survey.Note: M = Mean; R = Rank.  Present consensus between client and academia.  Presents consensus between clients, contractors and safety officials.  Presents consensus between clients and contractor.  Presents consensus between clients, contractor, safety officials and academia.  Presents consensus between clients and safety officials.  Presents consensus between contractors, safety officials, and academia.The significance level of health and safety factors.Note: M = Mean; R = Rank; S = Significance and V. imp, very important; ↑ shows an increase in the significance of the factors from first round to second round.

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+It is well acknowledged that human immunodeficiency virus stigma (HIV stigma) challenges people living with HIV globally. There is a scarcity of information about determinants of HIV stigma and discrimination among married men in the Indonesian context. This study aimed to explore factors that contribute to stigma and discrimination against HIV-positive men married to women in Yogyakarta, Indonesia. Face-to-face in-depth interviews were conducted to collect data from participants using a snowball sampling technique. A framework analysis was used to guide the analysis of the data. HIV stigma framework was also applied in the conceptualisation and the discussion of the findings. The findings indicate that participants experienced external stigma within healthcare facilities, communities and families. This external stigma was expressed in various discriminatory attitudes and behaviours by healthcare professionals and community and family members. Similarly, participants experienced anticipated stigma as a result of HIV stigma and discrimination experienced by other people living with HIV. Individual moral judgement associating HIV status with amoral behaviours and participants’ negative self-judgement were determinants of perceived stigma. The current findings indicate the need for training programs about HIV stigma issues for healthcare professionals. There is also a need to disseminate HIV information and to improve HIV stigma knowledge among families and communities.Globally, human immunodeficiency virus stigma (HIV stigma) and discrimination affect physical and mental health of people living with HIV (PLHIV) [1,2]. HIV stigma and discrimination against PLHIV have been demonstrated in various forms, such as negative labelling, discriminatory behaviours and negative treatment by healthcare professionals, families and communities [3,4]. It is also known that HIV stigma and discrimination have negative impacts on PLHIV, such as self-isolation, social exclusion, loss of jobs, economic difficulty and poor access to healthcare services [2,5,6].Studies in different settings have identified the determinants of HIV stigma and discrimination against PLHIV, including the lack of basic knowledge of the route of HIV transmission and there is also a belief that being infected with HIV is an individual responsibility [2,3]. In addition, poor understanding of effective HIV current management has led to the perception that HIV is still a life-threatening infection. Studies by Liu and Tsui [7] and Liu and colleagues [8] suggested that people who have poor HIV/AIDS knowledge are more likely to hold negative attitudes and behaviours toward PLHIV. Further studies [2,9,10] have also reported community fears and discomfort while interacting with PLHIV as being determinants of HIV stigma and discrimination. Fear, shame, and blame in many cultures build irrational beliefs (e.g., physical contact with PLHIV can transmit the virus) about HIV transmission and cause stigma and discrimination against PLHIV [6,11]. The perceptions that AIDS is a disease of men who have sex with men (homosexuality) and that HIV infection is associated with amoral sexual behaviours (e.g., having sex with multiple sex partners or sex work) increase and maintain stigma and discrimination against PLHIV [12,13,14,15].Several studies in Indonesia have focused on HIV-related stigma and discriminatory attitudes by healthcare professionals and identified factors including poor knowledge on HIV transmission and prevention modalities [16,17,18,19], religious perceptions that HIV is a punishment from God and a belief that HIV positive status is a rejection of homosexuality [20]. Studies in other settings have focused on HIV-positive women and men who have sex with men and identified gender, sexual orientation [21,22,23,24,25,26,27] and other factors as supportive of HIV stigma and discrimination [28,29,30,31].In Indonesia, men married to women make up the majority of adult men in communities and make up a significant proportion of PLHIV [32]. However, no studies have attempted to specifically and qualitatively explore the views of ‘married men’ living with HIV on factors associated with HIV stigma and discrimination in Indonesia. This paper fills the gap in knowledge on the evidence of determinants of HIV stigma and discrimination among ‘married men’ in the Indonesian context. The understanding of these factors is important to inform the development of policies and programs that address the problem among men married to women and other PLHIV in Indonesia. This qualitative exploratory study aimed to understand determinants of HIV stigma and discrimination against HIV-positive men married to women in Yogyakarta, Indonesia.The city of Yogyakarta, the current study’s focal setting, is a municipality in the Special Region of Yogyakarta province. The city is divided into 14 sub-districts and 45 villages and has a total population of 422,732 people (13,007.13 people per km2) [33]. The majority of people in Yogyakarta are cultural groups, including Javanese (the main group comprising about 87% of total population), Sundanese, Malay, Chinese, and Batak [32]. It is the capital city of the Special Region of Yogyakarta province, which is one of the 34 provinces in Indonesia. This province is situated in the south of Java Island, covers an area of 3158.80 km2, and has the total population of 3,452,390 people [33]. The number of HIV cases in Yogyakarta has been reported to be increasing annually, from 4060 in 2016 to 4783 in 2017, 5616 in 2018 and 5891 in June 2019, and the prevalence rate of HIV infection up to July 2019 was 0.0017%, which was higher than that of the national rate of 0.0013% [32]. The municipality of Yogyakarta, where the current study was conducted, provides HIV-related health services in four hospitals and 10 community health centres. The services provided include dissemination of health information on HIV/AIDS and the related services, HIV counselling and testing, CD4 tests, viral load tests, and ART provision [34,35,36]. In addition, several non-governmental organisations in collaboration with the health sector in the study setting provide HIV-related support, such as regular HIV information sessions and mobile voluntary counselling and testing for target groups and general communities, peer support groups for PLHIV, monthly meetings with PLHIV and sustained support to ensure access and adherence to treatment among PLHIV [35]. Yogyakarta is one of the few cities in Indonesia where HIV-related information and health services have been reported to be relatively well disseminated and provided [37,38]. Understanding HIV stigma and discrimination in the context of the current study setting is necessary to inform practices and policies for improvements in HIV management. Evidence from the current setting can also be used to inform further investigation of this problem in other parts of the country, where these services are not readily available.The conceptualisation and discussion of the current study findings were guided by the HIV stigma framework by Earnshaw and Chaudoir [39]. The framework suggests that HIV stigma is a devalued attribute which has negative impacts on both uninfected and infected people within a given society through its concomitant stigma mechanisms. Stigma mechanisms reflect how people respond to the knowledge or the fact that they either have (HIV infected) or do not have (HIV uninfected) the devalued attribute. For uninfected people, stigma mechanisms reflect the psychological responses to the knowledge of the existence of HIV-infected people who may transmit the virus to them or threaten their life and health and who possess moral blemishes [40]. Such responses are often reflected in efforts to avoid people who are infected with HIV [41]. There are three predominant ways through which stigma mechanisms are manifested, which show how uninfected people react towards infected people: prejudice, stereotyping, and discrimination towards PLHIV. Prejudice represents negative emotions of uninfected people towards and how they feel (such as disgusted, angry, and afraid) about PLHIV [42]. Stereotypes (e.g., that PLHIV are sexually promiscuous or of low moral standing) refer to the beliefs held by a certain group of people or community about PLHIV that are often applied to specific individuals living with HIV [43]. Discrimination reflects the behaviours of uninfected people towards PLHIV as the expression of prejudice [42]. For PLHIV, stigma mechanisms reflect the psychological responses to the knowledge or fact that they may have violated social mores and religious norms and values, and thus may be treated negatively by other people. This framework suggests that stigma mechanisms experienced by PLHIV (enacted stigma, anticipated stigma and internalised or perceived stigma) can cause negative impacts on their behaviours, psychological state, social life and health outcomes. Enacted stigma is about the belief that PLHIV have that they have actually experienced prejudice and discrimination from other people [44]. Anticipated stigma reflects the degree to which PLHIV expect that they will experience prejudice and discrimination from other people [45]. Perceived stigma reflects the individual’s attitudes and behaviours of others and internalised stigma reflects the degree to which PLHIV endorse the negative beliefs and feelings associated with HIV about themselves [46].A qualitative inquiry employing one-on-one face-to-face in-depth interviews was conducted from May to August 2018 to explore married men’s experience of HIV stigma and discrimination in Yogyakarta. The use of qualitative design has been found appropriate to explore participants’ understanding, interpretations, values and meanings regarding HIV stigma and discrimination facing them in their daily lives [47,48,49], and is effective when exploring participants’ perspectives and deep insight of their real life experiences [48,50].The study participants (n = 20) were HIV-positive men married to women in the city of Yogyakarta, Indonesia. They were recruited using the snowball sampling technique [48]. The study information sheets with the contact details of two male field researchers (NKF and DBM) were initially posted on the information board of a non-governmental organisation providing support and services for PLHIV. Participants who contacted the researchers and agreed to take part in the study were recruited. At the end of each interview, the participants were asked to disseminate the study information sheets to other potential participants, including their friends and colleagues who might be willing to take part in the study. This recruitment process was continued until the researchers felt that the data were rich enough and data saturation had been reached [51]. A total of 20 participants were recruited based on the inclusion criteria that one had to be 18 years old or above, married, and HIV-positive. No one other than the researcher and participant was present in the interview room. None of the potential participants who agreed to be interviewed withdrew their participation. The interviews were conducted in Bahasa.Face-to-face in-depth interviews were conducted at a time and place agreed upon by the researcher and participant. Each potential participant who called and stated his willingness to be interviewed was offered a possible date and place for interview. The interviews with each participant were conducted in a private research room at Duta Wacana Christian University. The interview focused on exploring the HIV-related stigma and discrimination experience of the participants within families, communities, and healthcare settings, and their own perceptions about their HIV status. The main areas of questioning in the interview included: the attitudes and treatments of healthcare providers or doctors and nurses they had received in any healthcare facilities; the attitudes and reactions of other community members who knew about their HIV status; participants’ daily experience of the attitude and treatment of other family members after HIV diagnosis; participants’ perceptions on how other people would treat or react to their HIV status, if known; and the feelings and perceptions the participants had about themselves in relation to their HIV status. The duration of each interview ranged from 45 to 60 min. At the end of the interview, each participant was offered the opportunity to read and correct the transcript once it has been transcribed; however, no participants chose to do so.Ethics approval for this study was obtained from the Duta Wacana Christian University health research ethics committee (No. 640/C.16/FK/2018). Prior to the interviews, each participant was informed about the purpose of the study and that the study had obtained ethical approval. They were also advised about the voluntary nature of their participation and that they had the right to withdraw their participation without any consequences if they felt uncomfortable with the questions being asked. They were also advised that the interview would take approximately 45 to 60 min and would be recorded using a digital tape recorder. They were assured that the data or information that they provided during the interview was confidential and anonymous, as each participant was assigned with a specific study identification letter and number. This was to prevent the possibility of linking back the data or information to any individual in the future. Each participant received reimbursement of IDR 100,000 (±USD 7) for the transport and time spent. Before commencing the interviews, each participant signed the informed consent form and returned it to the researcher.The recorded interviews were transcribed into coding sheets and translated into English by the authors (NKF and DBM) who are fluent in Bahasa and English. To maintain the quality and validity of the data, data cross checking was performed by the authors during the transcription and translation processes. The translations were also checked for accuracy by other authors. The transcripts were imported into the qualitative data analysis software package ATLAS.ti version 8.4.3 (Scientific Software Development GmbH, Berlin, Germany). The data analysis was guided by Ritchie and Spencer’s framework analysis [52]. This framework suggests six steps in qualitative data analysis. First, familiarisation with the data through the repeated reading of the transcripts, taking notes, and giving comments and labels to the transcripts; second, identification of a thematic framework where recurrent issues, concepts and themes were written down; third, indexing the entire data by creating a list of codes (open coding) to search for similar and redundant codes to reduce long list of codes into a manageable number. This was followed by closed coding where similar codes or codes that referred to the same theme were grouped together; fourth, charting the data by arranging appropriate thematic references in a summary chart which enabled the researchers to compare the data across the interviews and within each interview; fifth, mapping and interpretation of the data through which the ideas that made each theme were examined to see the relationship and association between them [52].The participants’ age ranged from 27 to 51 years, with the mean age of 40.9 years. All the participants resided in the city of Yogyakarta, 19 were Javanese and one was Chinese. They had different levels of educational background (see Table 1). More than a half (n = 12) acquired HIV infection through injecting drug use, while the others got infected through unprotected sexual intercourse with multiple female sex partners (n = 3) and multiple female and male sex partners (n = 5). Five people had been HIV positive for 2–5 years, 11 people for 6–10 years and four people for more than 10 years.Participants described having experienced HIV-related discrimination attitudes from healthcare professionals within healthcare settings. For example, they commented that they were left untreated for many days in healthcare facilities (hospitals) while doctors and nurses seemed unwilling to help them during their stay in the hospitals:“…. The first time I was admitted to hospital X [pseudo name], I was left untreated at all, I hardly breathed at the time, the doctor knew that, but he did not do anything to help me. I did not receive any medical treatment for 10 days in the hospital” (R10, 48 years old).“The problem with B20 patients like me is that the nurses, once our status is known to them [doctors and nurses], they seemed reluctant or unwilling to help us get better. They seemed lazy to treat me when I was in the hospital” (R13, 44 years old).“…. I once experienced discriminatory treatment in the hospital, the doctor did not want to be close to me. He seemed very afraid to replace the infusion” (R18, 38 years old).Discriminatory treatment from healthcare professionals created negative impressions and perceptions among PLHIV towards healthcare professionals. The participants had the perception and impression that healthcare professionals seemed to feel disgusted by their health conditions and treated them in unfriendly ways:“…. The nurse who helped me at that time was so unfriendly. I was not comfortable at all. I felt that the nurse felt disgusted by my condition and did not want to touch me, the infusion hose was also thrown in front of me, so rude. There were a few nurses who I knew that they felt disgusted with HIV patients (R9, 27 years old).“…. I once underwent blood check at a private laboratory clinic, the nurse wore disposable gloves, but after that she went back and forth, back and forth a few times to wash her hands. Oh my God…. should it be like that? It felt like I was disgusting” (R10, 48 years old).Discriminatory behaviours led to perceptions among the participants that some healthcare professionals were not well informed about HIV and how to treat patients with HIV:“…. The doctor did not want to treat me and was scared to change the infusion bottle. I was mad at the doctor, how come a medical doctor does not know information about HIV? They should know how to treat patients with HIV like me and do not leave patients with HIV untreated” (R8, 38 years old).“I think healthcare professionals who are not specifically trained about HIV lack information and knowledge about HIV. The treatments from those who work in HIV clinic and the ones who do not are different” (R1, 29 years old).There was also a mistrust by patients that healthcare professionals were unable to keep confidentiality about patients’ HIV status:“There are healthcare professionals who spread HIV status of patients: ‘This patient is infected with HIV, be careful …. I think they are the ones who are not well informed about HIV” (R4, 42 years old).Discriminatory behaviours against the participants within healthcare settings were reported to influence their access to healthcare services. Several participants commented that they were reluctant to access healthcare services in healthcare facilities where they had previously experienced discriminatory treatments from nurses or doctors. As a consequence, some decided to access healthcare services in other healthcare facilities:“…. I felt uncomfortable with the treatment of the doctor that handled me, so I was reluctant to go to the same hospital, I may meet her again” (R7, 34 years old).“I was ashamed and asked myself why did they treat me so rude? …. After that I do not go the place [healthcare facility] anymore. …. I go to another community health center” (R16, 30 years old).“…. I do not want to be served by the same person [nurse] who has treated me unfriendly, so I do not go there anymore” (R20, 39 years old).HIV stigma and discrimination against the participants were reported to occur within communities where they lived and interacted. Refusing to sit close to PLHIV or moving away from the chairs next to PLHIV, keeping distance and fear of having direct physical contact with PLHIV were the instances of discriminatory behaviours by other community members:“…. There are community members who keep their distance from me, this is very obvious. They moved away from me to other chairs and refused to sit next to me” (R4, 42 years old).“There are some [community members] who said ‘he has this disease [HIV/AIDS], we may get infected’. They did not want to sit next to me at all ….” (R2, 42 years old).Lack of information and knowledge about the means of HIV transmission was expressed by the participants as a factor which maintains discriminatory behaviour against PLHIV within communities. Participants commented that many community members were not informed about the basic knowledge of HIV, especially modes of HIV transmission. This perception was supported by the fact, as acknowledged by the participants, that dissemination of HIV-related information had not reached many communities in Yogyakarta:“Discrimination against people living with HIV depends how well-informed community members are about HIV. In some villages it seems like the ratio of people who are not informed and the ones who are informed about HIV is 10:1. HIV-related stigma and discrimination are worse in such villages. They [community members] deem HIV/AIDS as a horrible disease” (P1, 29 years old).“I am also involved in HIV programs and activities, including HIV information sessions for community members but we have not reached many communities or groups, and many people are not informed about this infection. This is reason why they stigmatise and discriminate people with HIV” (R5, 33 years old).HIV-related stigma and discrimination were also reported to occur within families of the participants. Isolation and separation of personal belongings and eating utensils were the examples of discriminatory behaviour or treatment experienced by the participants within their families, performed by other family members, such as their parents and the family of their wives. Several comments of the participants illustrated such experiences:“When I was physically weak [sick] and admitted to the hospital, I felt like I was left and isolated by my family members: parents and siblings …. I felt isolated because all my personal belongings, eating utensils, and toiletries were separated from those of other family members” (R20, 39 years old).“… Once I was tested positive with HIV, all the family members of my wife started to keep distance from me. It is so obvious: foods and plates are separated. They also avoid touching my clothes because they think it can be transmitted through sweat” (R3, 31 years old).However, stigma and discrimination against the participants seemed to be diminished once the family members were informed about the modes of HIV transmission:“… My parents and siblings were taught about HIV by the doctor who handled me and finally they accept me, I am welcomed in the family…. It is because I was accompanied by my mom once I consulted the doctor about the situation, I told the doctor everything I experienced in the family. The doctor said to my mom: “you do not need to separate eating utensils, they do not transmit the virus ….” I was so happy because after that they [family members] do not separate my eating utensils anymore” (R20, 39 years old).Anticipated stigma was prevalent among the study participants. Fear of being discriminated against by other community members, the intention to maintain the reputation of the extended family and to avoid negative impacts on children, and the perception of HIV as a disgrace were the factors maintaining anticipated stigma among the participants. Such anticipated stigma seemed to support the decision of some of the participants to hide their HIV status from community members:“…. If other people know about my status, would I be accepted? That is what I am scared of. HIV is like a taboo thing for many people, especially people who know nothing about it. So, I keep it secret to secure the reputation of my family and avoid negative impacts on my children. I am afraid if my children are discriminated due to my HIV status” (R11, 43 years old).“…. I think that getting infected with HIV is my fault, and this is my life. So, I am not sure that other people who I tell them about my HIV status understand and care about me. This infection is disgrace for me, and I think I do not need to let other people know about it” (R16, 48 years old).Negative experiences of other PLHIV they had seen or heard of, such as being neglected, avoided, rejected and having their personal belongings burned were additional factors linked to anticipated stigma, often leading to non-disclosure of their HIV status. Several participants commented that they did not want to experience the same negative treatments as their friends:“…. I heard that a friend died of HIV/AIDS and nobody wanted to bathe his body. His family members did not want to …. At the end, other friends who were companions of people with HIV [they are also HIV-positive] took the initiative to bathe the body. I also heard that nobody wanted to carry him to the cemetery because people were scared of being infected. …. So, I am afraid that if I am open about my status, I might experience the same thing” (R9, 27 years old).“Another friend of mine died from AIDS in Bali, all his personal belongings and sleeping equipment were burned off. The same thing can happen to me as well, so I do not tell everybody about my status” (R1, 29 years old).“My close friend died, and he was HIV-positive. Everybody in the village avoided and did not want to bathe his body, and even his own family did not want to do that and seemed to reject him. Two other friends of mine and I were the ones who bathed the body ….” (R15, 48 years old).Perceived HIV stigma was also experienced by the participants, which served to maintain their individual moral judgement on their HIV status. Several participants commented that they felt ashamed of their HIV status due to the perceptions that getting infected with HIV was associated with amoral behaviours and engagement in sex with sex workers:P (Participant): “Before I met other friends who are also HIV-positive I was ashamed of having HIV infection. But now if someone asks and he or she really wants to know then I will explain. But so far, nobody asks”R (Researcher): How will you explain about it?P: “I will explain that I get this infection not through sex but injecting drug use”R: Do you think there is a difference between getting HIV through sex and injecting drug use?P: “I will be so sad if I get it through sex because people will judge me as a bad person. If I am infected by sex workers, then that means I am a bad guy. But if I am infected through injecting drug use [sharing needle], then it is associated with male delinquency, so I will not think or be ashamed of it” (R10, 48 years old).“I feel ashamed of having this infection because people must think that I have had sex with sex workers” (R6: 42 years old).The above perception of HIV/AIDS, which is associated with amoral behaviours and which seems to lead to negative self-judgement as a ‘bad person’, increased guilty feelings and perceived stigma among the study participants. Several of them commented that they felt guilty about having the infection and judged themselves as “dirty people” or sinners:“…. I feel guilty, why I had done that [having sex with other men], it is forbidden by the religion. So, I do feel guilty because of that, I am a sinner” (R9, 27 years old).“I feel guilty because of the stigma from the society that HIV/AIDS is the disease of people with dirty [amoral] behaviours. So, I am a dirty person, have a lot of sins” (R6, 42 years old).“People perceive that HIV/AIDS is the disease of specific groups of people: transgender women, sex workers, and men who have sex with men. People may think that I belong to one of these groups” (R4, 42 years old).Participants’ moral judgement also seemed to endorse negative stereotypes about themselves or self-stigma. Self or internal stigma can be deduced from the following sentiments expressed by participants:“I am a sinner” (R9, 27 years old).“I am a dirty person, have a lot of sins” (R6, 42 years old).“I am a bad person because I did what I was not supposed to do” (R17, 51 years old).Two other participants expressed negative stereotypes of themselves or self-stigma which seemed to be influenced by their religious thoughts:“What I did [sex with multiple sex partners before marriage] was opposite to what I heard from the church, I am a very bad person” (R12, 41 years old).“At the first time I was diagnosed with HIV, some family members questioned me “how do you get the infection?” And once they knew that I might have got it from any sex workers I had sex with, some said “you should not have done that, it is wrong, it is sin. You have done a wrong thing which is not allowed in our religion. I feel like I am a very guilty person, a sinner. I was long time ago but what they said still stays with me up to now” (R14, 42 years old).Stigma and discrimination are often experienced by PLHIV due to their HIV-positive status. This study aimed to explore HIV stigma and the discriminatory experiences of HIV-positive men married to women in Yogyakarta, Indonesia. Consistent with previous findings [9,10,53,54,55], this study identified that stigma and discrimination against HIV-positive men married to women came from healthcare profession, family members, their local community and their own self-evaluations.Healthcare professionals’ discriminatory attitudes and behaviours in the current study manifested in various forms, such as an unwillingness and reluctance to treat/touch patients with HIV, and being unfriendly towards them. As per previous studies [9,10,53,54,55,56], these findings are an indication of health professionals’ poor knowledge of HIV, as they think that they could be infected with HIV through interaction with the patients. The discriminatory treatment experienced by the current study participants was probably conducted by healthcare professionals who were not formally trained in HIV, because in Indonesia, HIV patients who are admitted to general hospitals are taken care of by healthcare professionals from units such as the intensive care unit, who might not be well-equipped with information or knowledge about HIV [57,58]. Consistent with previous studies [59,60,61,62], the participants in this study were reluctant to access healthcare services in healthcare facilities where they had previously experienced discriminatory attitudes or treatment, which is indicative of the need for training programs among health care professionals across facilities. Training of health professional has been identified as effective in addressing HIV stigma, as indicated previously in a study with transgender women in the same study setting, where the availability of positive support by healthcare professionals led to effective access to HIV services by transgender participants [35].Consistent with other studies [63,64,65], the current findings indicate that HIV stigma and discrimination against the participants occurred within families and communities due to a lack of knowledge about HIV transmission. These findings support the HIV stigma framework and previous findings [39,41,42,66,67], where poor understanding about HIV in general has been stated as one of the main reasons for prejudice, stereotypes and discrimination from family and community members against PLHIV. Similarly, according to the findings elsewhere [68,69,70,71], anticipated stigma was common among the current study participants due to the fear of discrimination, shame to the family and negative impacts on children. In Indonesia, family is deemed as an entity where the behaviours and HIV status of a family member can have serious negative impacts on the extended family [6,72]. This has been underlined in Ho and Mark’s concept [73] asserting that societies that emphasise collectivism, such as in Indonesia, can blame or stigmatise the entire extended family if one among family members is infected with HIV. This seemed to be one of the cultural factors that contributed to anticipated stigma among the study participants, leading to participants concealing their HIV status [74,75,76]. Concealment of HIV status from other community members may also lead to the lack of social support for PLHIV, which has been reported to lead to HIV stigma and discrimination against PLHIV [77,78] and poor access to HIV healthcare services [79], a vicious cycle.Experiences of perceived stigma were also identified from participants’ own moral judgement on their HIV status. Being infected with HIV was associated with amoral behaviours (e.g., engagement in sex with sex workers), which led to the participants’ self-judgement as ‘dirty people’ or sinners. The HIV stigma framework [39,40] suggests that self-judgement or ‘moral blemishes’ contribute to the internal stigma experienced by PLHIV. This finding also supports the idea that stigma is associated with social and cultural process and a moral issue in which the conditions that are stigmatised (in this case HIV) threaten what is considered valuable to a social group and community [80,81]. Participants’ moral judgement on their behaviours through which they contracted the infection (sex with multiple sexual partners) and self-judgement as “dirty people” or sinners, which supports perceived stigma among them, align with the previous reports on stigma and moral experiences [80,82], suggesting that the moral standing of an individual is influenced by the moral discourse of the community or a society and the requisite morally appropriate behaviour is the behaviour that can meet socially constructed discourse.The study has several limitations that should be considered in the interpretation of its findings. Firstly, the study included a small number of respondents in a single setting, which could have led to a biased overview of HIV stigma and discrimination against married men living with HIV. The snowball technique used to recruit the participants may also be a limitation as it might have led to under-sampling of married men with HIV outside of the social networks of the current participants. Therefore, the findings of this study may be less likely to be transferable to other married men with HIV with different characteristics and in different settings in the country. However, these findings are useful to informing governments and organisations or institutions concerned with HIV, health service providers and program planners to develop evidence-based interventions that address the stigma and discrimination facing PLHIV within families, communities, and healthcare facilities. Future studies that cover heterogeneous participants with different backgrounds and from different settings, and that further explore religious thoughts and moral stances of participants in relation HIV infection, are recommended.This study found that HIV-positive men married to women experienced external, anticipated and perceived HIV stigma and discrimination due to their HIV status. External stigma was experienced within healthcare facilities, communities and families where they lived and interacted, which was reflected in various discriminatory behaviours and treatments by healthcare professionals, community and family members. Anticipated stigma was based on the HIV-related stigma and discrimination experienced by other PLHIV, such as neglect, rejection, avoidance and burning of personal belongings, and on the perception that being infected with HIV is a disgrace, which can ruin the reputation of the extended family. Participants’ individual moral judgement that associated their HIV status with amoral behaviours and engagement in sex with female sex workers, and participants’ self-judgement as ‘dirty people’ or sinners which increased guilty feelings, were additional factors leading to HIV’s perceived stigma. The participants’ moral judgement also led them to endorse negative stereotypes regarding themselves or self-stigma. The current findings indicate the need for HIV stigma-related training for healthcare professionals, which has been reported to be effective for stigma reduction [35,83,84], and broader coverage of HIV information dissemination for people within families and communities to improve their knowledge on HIV, and mitigate stigmatising and discriminatory attitudes, behaviours or treatments and services for PLHIV within families, communities and healthcare facilities.D.B.M. was involved in conceptualisation, project administration, investigation, and in developing the methodology, conducting formal analysis and writing the original draft of the paper. N.K.F. was involved in conceptualisation, project administration, investigation, and in developing the methodology, conducting formal analysis, writing the original draft of the paper and reviewing and editing the paper critically for important intellectual content. M.S.M. was in project administration and investigation. T.A.S. was involved in conceptualisation and developing methodology. L.M. and P.R.W. were involved in conceptualising, reviewing and editing the paper critically for important intellectual content. All authors have read and agreed to the published version of the manuscript.This research received no external funding.We would like to thank the participants who had spent their time to voluntarily take part in the interview and provided us with valuable information.Authors declared no conflict of interest.Socio-demographic characteristic of the participants.

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+Climate change and natural resource exploitation can affect Indigenous people’s well-being by reducing access to ecosystem services, in turn impeding transmission of traditional knowledge and causing mental health problems. We used a questionnaire based on the Environmental Distress Scale (EDS) and the Connor–Davidson Resilience Scale (CD-RISC-10) to examine the impacts of environmental changes on 251 members of four Indigenous communities in the eastern Canadian boreal forest. We also considered the potential mitigating effects of sociodemographic characteristics (i.e., age, gender, parenthood, and time spent on the land) and protective factors (i.e., health, quality of life, resilience, life on the land, life in the community, and support from family and friends). Using linear regression, model selection, and multi-model inference, we show that the felt impacts of environmental changes increased with age but were lower for participants with higher quality of life. The effect of resilience was opposite to expectations: more resilient participants felt more impacts. This could be because less resilient individuals ceased to go on the land when environmental changes exceeded a given threshold; thus, only the most resilient participants could testify to the impacts of acute changes. Further research will be needed to test this hypothesis.Climate change, added to an ever-increasing pressure to exploit natural resources, causes environmental changes that impact public health [1,2,3,4]. Indigenous peoples live in close connection with the land and are thus more directly affected by environmental changes [5,6,7]. Hence, environmental distress is experienced in Indigenous communities as a result of reduced well-being due to the lower access to ecosystem services, hindered transmission of traditional knowledge, and altered lifestyles [6,8,9,10,11].Reading [12] used the metaphor of a tree to explore the social determinants of Indigenous health. The tree crown represents the proximal determinants such as age, gender, the physical environment, income, and social status. The tree roots represent distal (or structural) determinants, i.e., the historical, political, ideological, economical, and social foundations from which all other determinants evolve. The tree trunk represents intermediate determinants that facilitate or hinder health through connexions between proximal and distal determinants; they include social support, access to services, and relationship with the land.Among the proximal determinants of health, different sociodemographic characteristics might influence how environmental changes affect Indigenous well-being. The more time someone spends on the land, the more likely he/she is to be affected by environmental changes. In addition, women and men use the land differently and this could be reflected in how they are affected by environmental changes [13,14,15,16,17]. Similarly, youth, adults, and elders do not use the land in the same way and could be affected differently by environmental changes [18,19,20,21,22]. Having children or not also results in different land use patterns and possible impacts of environmental changes.The impacts of environmental changes on Indigenous well-being can also be mitigated by proximal and intermediate determinants of health acting as protective factors. More resilient individuals have a higher capacity to bounce back after a disturbance and could thus be expected to be less affected by environmental changes [10,23]. Higher quality of life and better health conditions are also expected to reduce the impacts of environmental changes [19,24]. Support from family and friends and good relations with others within communities or on the land could also mitigate the impacts of environmental changes [25,26].Our main objective was to examine how environmental changes affect Indigenous well-being in the boreal forest of eastern Canada, taking into account sociodemographic characteristics and protective factors. We considered the following hypotheses: 
+      Hypothesis 1 (H1).Environmental distress increases when environmental changes increase.
+      Hypothesis 2 (H2).The relationship between environmental distress and environmental changes varies according to sociodemographic characteristics (i.e., age, gender, time spent on the land and parenthood).
+      Hypothesis 3 (H3).Environmental distress resulting from environmental changes is reduced by protective factors (i.e., resilience, health, quality of life, support from family and friends, life on the land, and life in the community).Environmental distress increases when environmental changes increase.The relationship between environmental distress and environmental changes varies according to sociodemographic characteristics (i.e., age, gender, time spent on the land and parenthood).Environmental distress resulting from environmental changes is reduced by protective factors (i.e., resilience, health, quality of life, support from family and friends, life on the land, and life in the community).We found that the more environmental changes were perceived, the more impacts were felt. Older participants felt more impacts from environmental changes, but no other sociodemographic characteristic had a significant effect. Participants with higher quality of life felt less impacts, whereas more resilient participants unexpectedly felt more, maybe because less resilient persons do not go on the land if environmental changes exceed a given threshold.The study area was in the eastern Canadian boreal forest, on the traditional territories of four communities belonging to three different Indigenous peoples: the Cree community of Ouje-Bougoumou (820 members), the Atikamekw community of Opitciwan (2697 members), and the Anishnaabeg communities of Pikogan (996 members) and Wahgoshig (303 members). These communities experience various degrees of environmental changes, both in number and intensity of stressors (e.g., climate change, forestry, mining, hydropower development).The three Indigenous peoples to which the participating communities belong are part of the Algonquian language family, share several cultural traits, and all used to follow a nomadic lifestyle based on hunting, trapping, fishing, and gathering before forced settlement in the 20th century [27,28]. Education levels are generally low, and the unemployment rate is high. The main sources of employment are public services, administration, education, health, and development of community infrastructure.We designed a questionnaire based on the Environmental Distress Scale (EDS) and on the 10–item Connor–Davidson Resilience Scale (CD-RISC 10) (see Supplementary Materials). The EDS was developed to evaluate the impacts of environmental changes on human distress in rural and Indigenous communities in Australia [29]. It was also used in a study with the Rigolet Inuit community in Labrador, eastern Canada [30]. We used two sections of the EDS to measure people’s observations of environmental changes (15 items) and felt effects of environmental changes (22 items). Items were measured on a 5 point Likert scale.We also measured participants’ sociodemographic characteristics (4 items) to determine if they influenced the link between perceived environmental changes and felt impacts: gender (man or woman); age group (18–35 or >35 years old); parenthood (having children or not); and time spent on the land (never, a few times a year, a few times a month, a few times a week, always). We also measured protective factors with slightly modified items of the EDS (all measured on a 5 point Likert scale): life in the community (14 items); life on the land (7 items); support from family and friends (5 items); quality of life (1 item), and health (1 item). We measured resilience with the 10–item (each measured on a 4 point Likert scale) Connor–Davidson Resilience Scale [31] which was validated for use with different ethnic groups around the world including Indigenous peoples [31,32,33].We respected the principles of ethical research with Indigenous peoples [34]. Each community provided approval and each individual participant completed a consent form [35]. We obtained an ethics certificate from the Ethics Review Board of Université du Québec en Abitibi-Témiscamingue in April 2016 (#2016-04-Asselin). The names of the participants were not collected to ensure confidentiality. We conducted the survey between June and November 2016. All participants were 18 years of age or older. The time to complete the survey averaged approximately 30–45 min per person. Liaisons within each community helped recruiting participants who were contacted in the streets, in their homes or offices, and at public gatherings.We used three series of linear regressions and model selection based on the Akaike information criterion (AICc) to assess the relationship between perceived frequency of environmental changes and felt impacts of changes (H1) as well as the effects of sociodemographic characteristics (H2) and protective factors (H3) on this relationship. We conducted statistical analyses with version 3.4.4 of the R software using the base package and the AICc modavg package [36]. We considered parameters with a confidence interval excluding zero to have significant effects. We verified the application conditions for all regression series with a visual examination of the validation plots for the general models (with all variables). We checked outliers for possible errors during data entry. We performed the analyses with and without outliers and, as the results were similar, we kept the outliers. We considered models with a delta AICc ≤ 2.We verified the reliability and internal consistency of the EDS sections (0.48–0.84) and CD-RISC 10 (0.85) with Cronbach’s alpha. Except for life in the community (0.48), all other variables had Cronbach’s alpha values higher than 0.70 which was deemed acceptable. We tested the effect of the perceived frequency of environmental changes on felt impacts (H1) using a linear regression. We subsequently analyzed the effects of sociodemographic characteristics (i.e., gender, age, time spent on the land, and parenthood) on the relationship between perceived frequency of environmental changes and felt impacts (H2). We used model selection to compare the contributions of sociodemographic characteristics and to identify the most parsimonious combination explaining environmental distress [37]. We ranked sociodemographic characteristics using model averaging. We calculated the weight of a variable by summing the weights of all models including it [37]. The most parsimonious model was then selected to test if protective factors (i.e., resilience, support from family and friends, life in the community, life on the land, health, and quality of life) reduced the impacts of perceived environmental changes (H3). We thus performed a second model selection with felt impacts as a response variable and perceived frequency of change, retained sociodemographic characteristics, and all possible combinations of protective factors as explanatory variables. We weighted the contributing factors using model averaging (as for H2).A total of 251 persons completed the survey (126 women, 125 men) (Table 1). Highly correlated variables were deleted (health and life on the land). Participants were initially assigned to one of three age groups: 18–35, 35–65, and ≥66 years old. However, only a few (13) seniors accepted to participate. Most mentioned they prefer interviews, as they can detail and contextualize their answers rather than answer closed-ended questions. Hence, age was reclassified into only two groups for analyses: 18–35 and ≥36 years old. The majority of participants were older than 35 years old (68.5%). Between 5% and 40% of the adults living in the communities took part in the survey. Most participants had children (77%). Time spent on the land was a few times a year/month/week for most participants (47%, 26%, and 11%, respectively) with some living full time on the land (14%) and only 2% never going.We tested the link between perceived frequency of environmental changes and felt impacts using linear regression (H1). The confidence interval of the coefficient for felt impacts excluded zero (Table 2), confirming the collinearity of this variable with perceived frequency of environmental changes. Thus, H1 was verified: the more someone perceived environmental changes, the more impacts he/she felt.We used model selection based on AICc to assess the effects of sociodemographic characteristics on the relationship between perceived frequency of environmental changes and felt impacts (H2). A total of 16 models were tested, of which four had a delta AICc ≤ 2 and were thus considered (Table 3). All retained models included age. Model 12 was the most parsimonious and only included age (confidence interval excluding zero; Table 4); it was thus selected for further analyses (see below). We summed cumulative AICc weights and age had the highest weight (age = 0.75; time spent on the land = 0.42; parenthood = 0.37; gender = 0.35).Felt impacts of environmental changes varied according to age, and, thus, H2 was partly verified. Older participants (≥36 years old) felt more impacts than younger participants (18–35 years old) for the same frequency of environmental changes. However, all participants regardless of age group felt the same (highest) impacts for the highest frequency of environmental changes. None of the other sociodemographic characteristics affected felt impacts of environmental changes.We used model selection based on AICc to assess the effects of protective factors on the relationship between perceived frequency of environmental changes and felt impacts (H3). Of the 16 tested models, three had a delta AICc ≤ 2 and were thus considered (Table 5). All retained models included resilience and quality of life. Model 5 was the most parsimonious combination of variables and included resilience and quality of life (confidence interval excluded zero; Table 6). Resilience increased the felt impacts of environmental changes, whereas quality of life had the opposite effect. Resilience had the highest cumulative AICc weight (resilience = 1.00; quality of life = 0.83; life in the community = 0.76; support from family and friends = 0.38).Hypothesis 1 was confirmed: the more participants perceived environmental changes, the more impacts they felt. Previous research in Australia and Canada has shown that Indigenous people consider environmental changes as a hazard not only affecting the land but also their mental health [38,39]. With increasing environmental changes as a result of natural resource exploitation and climate change in Canada, environmental distress will likely increase in Indigenous populations [3,11,39,40,41].Hypothesis 2 was partly confirmed, as older participants (≥36 years old) felt more impacts than younger participants for a given level of environmental change, hence supporting the assertion that attachment to the land increases with age [42]. As older persons spent more time on the land than younger persons [8,43], they felt more impacts, although the effect of time spent on the land was not significant (see below). Some of the oldest participants might have felt more impacts because they had responsibilities on the land as suggested by previous work with Cree tallymen [27].Because of the low participation of elderly people (≥66 years old), it was not possible to compare the answers of participants 36‒65 years old and older than 65 years old. Older participants had difficulty understanding the abstract concepts that the questions conveyed, and that were hard to translate into their native languages. Furthermore, they mentioned they felt more comfortable with open questions rather than multiple-choice questions, as they prefer to explain and contextualize their answers. Closed-ended questions therefore do not appear appropriate to work with older Indigenous people, and qualitative methods are better suited [44,45].Gender did not significantly affect the impacts felt from perceived environmental changes. This could be explained by the fact that men and women share common values and cultural systems that influence their perception of environmental changes in a similar way [46,47].Parenthood did not significantly affect the impacts felt from perceived environmental changes. Parenthood was expected to play a role, because the land is a privileged setting for cultural transmission as revealed, for example, by previous work with the Atikamekw people [8]. Maybe the lack of an effect of parenthood is due to the fact that Indigenous peoples in Canada tend to live in an extended family setting where everyone (parent or not) contributes to children’s education [48,49].Time spent on the land did not significantly affect the impacts felt from perceived environmental changes. While it is possible that participants spending more time on the land were more exposed to environmental changes, the perceived frequency of environmental changes was controlled in the model. Moreover, attachment to the land might not be directly associated with the amount of time spent on the land. There is cultural transmission between persons spending more time on the land and those spending more time in the community [50,51], and social cohesion could mean that all community members share attachment to the land as well as distress associated with changes regardless of time spent on the land [52,53].Other sociodemographic characteristics not tested here might affect the impacts felt from perceived environmental changes such as family composition, employment or education [1,54]. In addition, someone can feel distressed not only in face of environmental changes but also because of other situations with which he/she must cope [54].Hypothesis 3 was partially confirmed, as resilience and quality of life significantly influenced the felt impacts of environmental changes. As expected, persons with a higher quality of life felt fewer impacts of environmental changes [39,54,55]. However, while resilience was also expected to reduce the felt impacts of environmental changes [56], the relationship was in the other direction: more resilient participants felt more impacts of environmental changes. As resilience was positively associated with felt impacts, but also with perceived frequency of environmental changes (data not shown), it could be that only the most resilient persons continue to go on the land when environmental changes are frequent, and thus they perceive more changes and feel more impacts. However, as they are resilient, they have the adaptive capacity to cope with changes [57]. Conversely, persons with low resilience might cease to go on the land when it is highly disturbed, as they are not able to handle so much change. More research is needed to test this assertion.Support from family and friends did not have a protective effect on felt impacts of perceived environmental changes. In three of the four participating communities, the territory is divided into family hunting grounds, and thus family members are all exposed to the same level of environmental changes and likely experience similar distress. Previous studies have shown that support from family and friends is less efficient when distress is spread throughout the family [58].Life in the community also did not have a protective effect on felt impacts of perceived environmental changes. The low internal consistency of this variable (Cronbach’s alpha = 0.48) could explain why its predictive power was low. Furthermore, while life in the community might turn people away from the traditional way of life [59], having a job can also provide the money needed to pursue traditional activities on the land [60]. Mobility among places increases adaptability to different environments and situations [10,61].When Indigenous people perceive more environmental changes in the eastern Canadian boreal forest, they feel more impacts on their well-being. This is especially true for older individuals, for those who have a low quality of life, and likely for those that are less resilient. Environmental distress will continue to increase in the study area, as climate change will continue in the next decades and as the pressure to extract natural resources will continue to rise.Limitations to this study could have influenced the results. First, some factors that could possibly affect people’s distress were not included such as education, employment, access to services, or family composition. Nevertheless, we likely took at least part of their effects into account by considering overarching variables such as quality of life, support from family and friends, and resilience. Second, due to the low participation from the oldest age group (>66 years old), we had to use a combined age class (≥36 years old) which could have masked some of the variability. Indeed, older Indigenous people are more often responsible for family hunting grounds and have a deeper connection with the land. Yet, the significant difference between the level of impacts felt by the younger and older age groups was consistent with expectations.Two possible solutions to reduce environmental distress are (1) to refuse resource development projects beyond a certain threshold of environmental change where felt impacts exceed the resilience capacity of the more vulnerable community members; and (2) to develop measures to increase protective factors, especially resilience and quality of life.The following are available online at https://www.mdpi.com/1660-4601/17/2/637/s1, Questionnaire.Conceptualization, H.A. and O.L.; methodology, L.F., H.A., A.C.B. and O.L.; formal analysis, L.F., A.C.B.; investigation, L.F. and H.A.; data curation, L.F.; writing—original draft preparation, L.F.; writing—review and editing, L.F., H.A., A.C.B. and O.L.; supervision, H.A. and O.L. All authors have read and agreed to the published version of the manuscript.This research was funded by the Social Sciences and Humanities Research Council of Canada, grant number 435-2014-1705.The authors would like to thank the members of the Opitciwan, Ouje-Bougoumou, Pikogan, and Wahgoshig communities for their trust, co-operation, and commitment. Sincere thanks are also extended to the following people for their help during field work: Joël Bear Babin, James Cananasso, Maël Casu, Benoît Croteau, Louis-Joseph Drapeau, Brian Gélinas, Roxane Germain, Maurice J. Kistabish, Kevin Lacroix, Roger Lacroix, Wayne Lefebvre, Chris Sackaney, Alice Wapachee, and Marie-Soleil Wezineau.The authors declare no conflict of interest.Number of participants from each community according to gender and age group.Specifications of the linear regression of felt impacts as a function of perceived frequency of environmental changes (H1).Linear models determining the effects of sociodemographic characteristics on felt impacts of perceived environmental changes. Retained models are shown in bold.Specifications for the regression of felt impacts as a function of frequency of environmental changes and age (H2, Model 12).Linear models determining the effects of protective factors on felt impacts of perceived environmental changes. Retained models are shown in bold.Specifications for the regression of felt impacts as a function of frequency of environmental changes, age, resilience, and quality of life (H3, Model 5).

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+Folate requirement among women who plan to become pregnant should be raised to 600 μg/day during the periconceptional period. To meet this need, several countries began to promote the use of folic acid supplements before and during pregnancy. Here, we investigated prevalence and determinants of dietary folate intake and folic acid supplement use among 397 pregnant women (aged 15–50 years old, median = 37 years old). We also investigated their effects on neonatal outcomes in a subgroup of women who completed pregnancy. For doing that, we used data from the “Mamma & Bambino” project, an ongoing mother-child cohort settled in Catania (Italy). Inadequate folate intake was evaluated using a Food Frequency Questionnaire and defined as an intake < 600 μg/day. Women were also classified as non-users (i.e., women who did not use folic acid supplements), insufficient users (i.e., women who did not take folic acid supplements as recommended), and recommended users of folic acid supplements. Neonatal outcomes of interest were preterm birth (PTB) and small for gestational age (SGA). Nearly 65% of women (n = 257) reported inadequate folate intake, while 74.8% and 22.4% were respectively classified as insufficient or recommended users of supplements. We demonstrated higher odds of inadequate folate intake among smoking women (OR = 1.457; 95%CI = 1.046–2.030; p = 0.026), those who followed dietary restrictions (OR = 2.180; 95%CI = 1.085–4.378; p = 0.029), and those with low adherence to the Mediterranean Diet (OR = 3.194; 95%CI = 1.958–5.210; p < 0.001). In a subsample of 282 women who completed pregnancy, we also noted a higher percentage of SGA among those with inadequate folate intake (p < 0.001). Among 257 women with inadequate folate intake, those with low educational level were more likely to not take folic acid supplements than their more educated counterpart (OR = 5.574; 95%CI = 1.487–21.435; p = 0.012). In a subsample of 184 women with inadequate folate intake and complete pregnancy, we observed a higher proportion of SGA newborns among women who did not take supplement before pregnancy and those who did not take at all (p = 0.009). We also noted that the proportion of PTB was higher among non-users and insufficient users of folic acid supplements, but difference was not statistically significant. Our study underlined the need for improving the adherence of pregnant women with recommendations for dietary folate intake and supplement use. Although we proposed a protective effect of folic acid supplement use on risk of SGA, further research is encouraged to corroborate our findings and to investigate other factors involved.During pregnancy, maternal nutrition plays a key role in fetal development and neonatal growth [1]. Specifically, during the preconception and gestational periods, inadequate intake of micronutrients might affect the risk of adverse pregnancy outcomes [2]. In line, mounting evidence suggests a strictly interplay between newborn and mother metabolisms, which in turn involve nutrient stores and intakes [3,4,5]. For this reason, the World Health Organization (WHO) and the Food and Agricultural Organization (FAO) developed several dietary recommendations and strategies for the prevention of adverse pregnancy outcomes [6]. Among these, pre-term birth (PTB; birth before 37 weeks of gestation) and small for gestational age (SGA; birth weight below the 10th percentile for gestational age) represent the major causes of death among newborns [7,8,9].Folate—a water-soluble vitamin B found in fruits, legumes, cereals, and green leafy vegetables—is required for placental tissue growth [10] and neural tube formation [11]. More recently, its role as a methyl donor in several molecular pathways and epigenetic mechanisms has been demonstrated [12,13]. Folate requirement among women of childbearing age is usually of 400 μg/day, but it should be raised to 600 μg/day during the periconceptional period [14]. To meet this need, in 1998, the United States began the compulsory fortification of cereal flour enriched with folic acid [15]. Subsequently, several countries promoted policies for folate fortification [16]. Nowadays, developed countries proposed folic acid supplementation as a strategy to ensure the correct fetal growth [17]. However, several lines of evidence showed that folic acid supplementation was often insufficient in the preconception period, with several negative effects on pregnancy and neonatal outcomes [18].Thus, further studies should investigate social and behavioral determinants that might affect the adherence to these recommendations and increase the awareness about benefits of folic acid supplement use [19,20,21,22]. Although inadequate folate concentrations were often associated with anencephaly and spina bifida [23], its impact on other adverse pregnancy outcomes is not fully understood. Interestingly, there was also evidence that folate status and supplement use were associated with a slightly increased risk for wheeze and lower respiratory tract infections in newborns [24,25,26].Our hypothesis is that folate deficiency leads to PTB [27] and SGA [28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46], but further studies are necessary to better investigate the potential protective role of adequate folate intake and/or folic acid supplementation. To fill this gap, the primary aim of the current study was to describe the prevalence of dietary folate intake and its determinants among pregnant women from Catania (Italy). We also evaluated folic acid supplement use according to national recommendations. Finally, we investigated the effect of folate intake and folic acid supplement use on neonatal outcomes in a subgroup of women who completed pregnancy.In the current analysis, we used data from the Mamma & Bambino project, an ongoing mother-child cohort settled in Catania, Italy, which aims to understand the effects of social, environmental, behavioral, and molecular factors on maternal and infant health. Study design and protocols have been fully described elsewhere [47,48] and at the website http://www.birthcohorts.net. From 2015, this cohort prospectively recruits pregnant women during their prenatal genetic counselling (median gestational age = 16 weeks; range = 4–20 weeks) at the Azienda Ospedaliera Universitaria “Policlinico-Vittorio Emanuele” (Catania, Italy). Pregnancy is the unit of observation with planned follow-up of children at birth, one and two years. Women with plurality, pre-existing medical conditions or pregnancy complications (i.e., autoimmune and/or chronic diseases, preeclampsia, gestational hypertension, and diabetes), intrauterine fetal death, and congenital malformations were excluded from this study. The study protocol has been approved by the ethics committee of the involved Institution (CE Catania 2; Prot. N. 227/BE and 275/BE). Participants were informed and gave written their informed consent of the purpose and procedures of the study, which was conducted according to the Declaration of Helsinki.At the recruitment, socio-demographic and behavioral information was collected by trained epidemiologist through structured questionnaires. Educational level was classified as low (primary school), medium (high school), or high (degree or higher), while employment status was categorized as unemployment (including students and housewives) and employment (both part-time and full-time). Women were also classified in those who lived alone or in couple, and in those who had children or not. With respect to smoking status, women were classified as non-smokers, former smokers, or current smokers. Women were asked to report their weight and height before pregnancy and pregestational BMI was calculated as weight in kg divided by height in m2 and classified according to the WHO criteria [49]. Women were also asked to report if they followed dietary restrictions or suffered from food intolerances.Dietary folate intake was evaluated using a 95-item semi-quantitative Food Frequency Questionnaire (FFQ) referred to 30 days before recruitment [12,13,50,51,52] and hence to the early phase of pregnancy (i.e., from the beginning to the 16 week of gestation). The extended form of this tool was adapted from a 46-item FFQ, which has been validated for the assessment of folate intake in Italian women of child-bearing age [13]. For each food item, information on frequency of consumption (twelve categories from “almost never” to “two or more times a day”) and portion size (small, medium, and large) were collected using an indicative photograph atlas, and then converted into daily food intakes. Dietary folate intake was calculated using the table of food composition of the US Department of Agriculture (http://ndb.nal.usda.gov/), adapted to typical Italian food consumption. Inadequate folate intake was defined as an intake < 600 μg/day of dietary folate equivalents (DFEs) [53]. Adherence to the Mediterranean Diet (MD) was evaluated using the 9-item Mediterranean Diet Score (MDS), as previously described [54,55]. For this reason, ranged from 0 (non-adherence) to 9 (perfect adherence) and adherence to MD was classified as low (MDS ≤ 3), medium (MDS = 4–6), or high (MDS > 6) [56].Women were also asked to report the use of folic acid supplements, alone or in combination with other multivitamin supplements, before pregnancy and during the first trimester of pregnancy. The current Italian recommendation suggests that women who plan to become pregnant should use folic acid supplements for 4 weeks before and until 12 weeks after conception [57]. Accordingly, women were classified as non-users (i.e., women who did not use folic acid supplements), insufficient users (i.e., women who did not take folic acid supplements as recommended), and recommended users.Gestational age and neonatal anthropometric measures were assessed at birth, among women with who completed singleton pregnancy. At recruitment, gestational age was assessed by ultrasound evaluation and used to define preterm birth as spontaneous delivery before 37 weeks. According to sex-specific national reference charts, birth weight and length were used to assess birthweight for gestational as follows: small for gestational age (birth weight < 10th percentile for gestational age), adequate for gestational age, or large for gestational age (birth weight > 90th percentile for gestational age) [58].Statistical analyses were performed using SPSS software version 26.0 (SPSS, Chicago, IL, USA). Characteristics of pregnant women according to dietary folate intake and folic acid supplement use were described using frequency (%) or median and interquartile range (IQR). Categorical variables were compared using Chi-squared test. Continuous variables were checked for normality using the Kolmogorov-Smirnov test and compared using the Mann-Whitney U test. Logistic regression analysis was used to identify main determinants of inadequate folate intake and folic acid supplement use. The models included variables that were significantly associated with inadequate folate intake or folic acid supplement use in the univariate analysis. Results were reported as Odds ratio (OR) and 95% confidence interval (CI). All statistical tests were two-sided, and p-values < 0.05 were considered statistically significant.The current study included 397 pregnant women from the “Mamma & Bambino” cohort (aged 15–50 years old, median = 37 years old) recruited from 2015 to 2019, 282 out of which completed pregnancy at the time of this study. In general, the average dietary folate intake was 533.4 μg/day (median = 516.3 μg/day; range = 68.9–2633.5 μg/day), and 64.7% of women (n = 257) did not meet the current recommendation of 600 μg/day during pregnancy. Figure 1 displays the distribution of women according to dietary folate intake and the use of supplements. Table 1 shows the characteristics of women according to their dietary folate intake. We observed that women who did not meet dietary recommendation were more likely to be smokers (p = 0.028) and exhibited higher pregestational BMI (p = 0.029) than their counterpart. With respect to dietary habits, women who did not meet dietary recommendation were more likely to follow dietary restrictions (p = 0.003) and less likely to adhere to MD (p < 0.001). Interestingly, logistic regression analysis demonstrated that following dietary restrictions (OR = 2.180; 95%CI = 1.085–4.378; p = 0.029), being a smoker (OR = 1.457; 95%CI = 1.046–2.030; p = 0.026), and low adherence to MD (OR = 3.194; 95%CI = 1.958–5.210; p < 0.001) were the main determinants of inadequate folate intake. In the subsample of 282 women who completed pregnancy, we also noted a higher percentage of SGA and LGA among those with inadequate folate intake (p < 0.001).We next examined the use of folic acid supplements among women of the Mamma & Bambino cohort. Figure 2A shows that only 2.8% of women did not take supplements, 74.8% were classified as insufficient users before pregnancy, while 22.4% met the recommendation before and during pregnancy. We also compared supplement use between women with inadequate folate intake and those with adequate folate intake (Figure 2B). Compared with the latter, we observed higher proportions of non-users and recommended users among women with inadequate folate intake. By contrast, a higher proportion of insufficient users has been observed among women with adequate dietary folate intake. However, these differences were not statistically significant. With respect to neonatal outcomes, we did not observe differences in the proportion of preterm birth and inadequate birthweight for gestational age (p = 0.430 and p = 0.770, respectively).We next aimed to identify the main determinants of folic acid supplement use among 257 women who did not meet the recommendation of dietary folate intake. Univariate analysis showed that women who did not take supplements were less educated (p < 0001) and reported lower MDS (p = 0.047) than supplement users (Table 2). Notably, logistic regression analysis further confirmed that women with low educational level were more likely to not take folic acid supplements than their more educated counterpart (OR = 5.574; 95%CI = 1.487–21.435; p = 0.012).Finally, we examined the effect of folic acid supplement use on neonatal outcomes among women with inadequate folate intake. With this in mind, we investigated 184 women with inadequate folate intake, who completed singleton pregnancy. In this subsample, median gestational duration was 39 weeks, with 9.8% of preterm deliveries. With respect to neonatal anthropometric measures, median values of birth weight and length were 3.25 Kg (range = 1.0–4.75 Kg) and 50.0 cm (range = 41–56 cm), respectively. According to sex-specific national reference charts [51], approximately 84.1% of newborns were adequate for gestational age (AGA), while 5.5% and 10.4% have been classified as SGA or LGA, respectively. Compared with women who met supplement recommendation, we observed a higher proportion of SGA newborns among those who did not take supplements before pregnancy and those who did not take any at all (p = 0.009) (Figure 3A). By contrast, the proportion of AGA newborns was the highest among women who took supplements before and during pregnancy. Instead, no difference in the distribution of LGA newborns was evident. We also noted that the proportion of preterm newborns was higher among non-users and insufficient users of folic acid supplements (Figure 3B). However, these differences were not statistically significant.The recommended intake of folate for pregnant women is 600 μg/day DFE, an estimation that was introduced to account for difference in the bioavailability between synthetic folic acid and naturally occurring folate [53]. Magnitude of folate deficiency varies between and within countries, with higher prevalence in those without folic acid fortification of cereal-grain products [59,60]. In our study, two out of three women did not meet current recommendation. The high prevalence of deficient women was in line with figures obtained by previous studies from the same Italian region [12,13,50,61,62].The primary aim of our study was to uncover the main determinants of dietary folate intake, an approach that could help the development of public health strategies against folate deficiency in states of increased demand (e.g., pregnancy and lactation). With this in mind, we observed that women who followed dietary restrictions and those with low adherence to MD were more likely to report inadequate folate intake. In fact, naturally-occurring folates are present in high concentrations in green leafy vegetables, dark green vegetables, legumes, and some fruits [63], so that higher intakes can be expected among people who follow a varied and balanced diet such as the MD. Moreover, we noted that inadequate folate intake was higher among current smokers than in former or non-smoking women. This is in line with previous findings reporting unhealthy diet among smokers [64,65,66], with greater intake of saturated fat and cholesterol, and lower intake of vitamins and fiber [67].Beyond folate intake, supplementation of folic acid during the periconceptional period represents one of the best strategies to tackle pregnancy adverse outcomes, as suggested by the WHO in 2006 [17]. However, the prevalence of folic acid supplementation remains often inadequate in several countries [20,68]. Although we showed that only ~3% of pregnant women did not take folic acid supplements, ~75% of them did not take supplements as recommended (i.e., 4 weeks before conception until 8 weeks after). Our data were consistent with a previous study reporting that only 3% of Italian pregnant women used folic acid supplements as recommended [69]. By contrast, in other European countries, prevalence of recommended users reached 50% [70]. In our study, the proportions of insufficient or non-users were not significantly different according to dietary folate status. However, among women with inadequate folate intake, those with low educational level were more likely to not use folic acid supplements than their more educated counterpart. Several studies aimed to identify the main determinants of inadequate supplement use during pregnancy. Among social factors, for instance, it has been demonstrated that younger age [20], low income [71], educational level [68], and employment status [21] might affect the use of folic acid supplements. In our opinion, social inequalities in the use of supplements could be partially explained by the reduced level of knowledge, attitude, and awareness among the more disadvantaged groups [22]. Our findings, together with those from previous studies, underline the need for increasing the prevalence of folic acid supplementation through the identification of people at the highest risk for folate deficiency.It has been clearly demonstrated that low maternal folate intake during the periconceptional period increases the risk for neural tube defect (e.g., spina bifida, anencephaly) and perhaps for other congenital anomalies (e.g., congenital heart defects, oral cleft lip and plate) and adverse outcomes [17]. In our study, for instance, we reported higher proportions of SGA and LGA births among women with inadequate folate intake compared with those who met dietary recommendation. However, these data did not take into account the use of folic acid supplements. For this reason, we also evaluated the effects of folic acid supplements among women with inadequate folate intake. In this subgroup, we consistently reported a higher proportion of SGA births among women who did not take supplement before pregnancy and those who did not take at all. It is worth mentioning that SGA is one of the main risk factors for adverse outcomes and mortality at birth [72,73], as well as for chronic diseases in later life [74,75,76,77,78]. In line, the implementation of policies based on folic acid supplementation should be one of the main goals to tackle the burden of low birthweight, especially in developing countries. However, there are still controversies about the effect of folic acid supplementation on low birth weight and SGA risks. The majority of studies demonstrated that supplement use before and during pregnancy reduced the risk of SGA [31,36,38,40,42,44,79]. However, others demonstrated an opposite [39,41] or null effect [30,45]. Thus, further research should be encouraged to understand the effect of folic acid supplement use on the risk of SGA and associated outcomes.Our findings should be interpreted with cautions due to some limitations. Firstly, the Mamma & Bambino study is an ongoing mother-child cohort that recruits pregnant women during their prenatal genetic counselling. For this reason, there is a discrepancy in the number of pregnant women with those who completed pregnancy. We described prevalence and determinants of dietary folate intake and supplement use among 397 pregnant women. Instead, findings on the neonatal effects of folate deficiency were obtained in a subsample of women who completed pregnancy, and thus should be confirmed by future analysis. In general, low sample size in some subgroups (e.g., women with inadequate folate intake and those who completed pregnancy) did not allow us to adjust for potential confounders. Moreover, we cannot rule out the possibility of bias from residual unknown or unmeasured factors. For instance, it has been demonstrated that several genetic polymorphisms involved in folate metabolism affected folate status in healthy subjects before and after folic acid supplement use [80,81]. Secondly, data on dietary folate intake and folic acid supplement use relied on self-reported interviews, which cannot completely exclude reporting errors. For instance, we previously reported that folate intake was higher when assessed with the FFQ than with a 4 days weighed dietary record [13]. To overcome this limitation, in the future, studies should evaluate folate status by measuring folate blood concentration and reviewing the size and morphology of blood cells.In spite of these limitations, our study underlined the need for improving the adherence of pregnant women with recommendations for dietary folate intake and supplement use. On one hand, this could be achieved with the promotion of a healthy diet rich in vegetables and fruits. On the other hand, the identification of social determinants that might affect the use of folic acid supplements could help the development of public health strategies and policies to reduce the burden of adverse pregnancy outcomes. Although we demonstrated a protective effect of folic acid supplement use on risk of SGA, further research is encouraged to corroborate our findings.Conceptualization, M.B. and A.A.; software, A.M. and R.M.S.L.; formal analysis, A.M., R.M.S.L., G.F., M.C.L.R., C.L.M.; resources, A.A.; data curation, M.B., A.M., and R.M.S.L.; writing—original draft preparation, A.M. and R.M.S.L.; writing—review and editing, all the Authors; visualization, A.M. and R.M.S.L.; supervision, A.A.; funding acquisition, A.A. All authors have read and agreed to the published version of the manuscript.This work was supported by the Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia”, University of Catania, Italy (Piano Triennale di Sviluppo delle Attività di Ricerca Scientifica del Dipartimento 2016-18).The authors declare no conflict of interest.The distribution of women according to dietary folate intake and use of supplements.Use of folic acid supplements among pregnant women. (A) Panel A shows proportions of non-users, insufficient users and recommended users among the overall cohort. (B) Panel B shows the categories of folic acid supplement according to folate intake.Neonatal adverse outcomes and folic acid supplement use among women with folate deficiency. (A) Panel A shows the distribution of small for gestational age (SGA), adequate for gestational age (AGA) and large for gestational age (LGA) infants. (B) Panel B shows the distribution of preterm and at term birth. ** p-value < 0.01.Characteristics of pregnant women according to folate intake.a Results are reported as median (Interquartile range), or percentage. Statistical analysis was performed using Chi-square test for bivariate or categorical variable, and Mann-Whitney test for continuous variables. b Significant results are indicated in bold font. c Data are reported for 282 women who completed pregnancy. Abbreviations: BMI, Body Mass Index; MDS, Mediterranean Diet Score.Characteristics of folate deficient women according to supplement use.a Results are reported as median (Interquartile range), or percentage. Statistical analysis was performed using Chi-square test for bivariate or categorical variable, and Kruskal-Wallis test for continuous variables. b Significant results are indicated in bold font. Abbreviations: BMI, Body Mass Index; MDS, Mediterranean Diet Score.

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+The aim of this article was to explore the experiences and attitudes of people with HIV/AIDS. A systematic review of qualitative studies was carried out. Twenty-seven articles were included, with sample sizes ranging from 3 to 78. Articles from North America, South America, Central America, Europe, and Africa were included. Five topics emerged from the synthesis: feelings about the diagnosis of HIV/AIDS; stigma and HIV/AIDS; changes in sexual behavior after becoming infected; living with the virus; and pregnancy and motherhood in seropositive women. The moment of diagnosis is of vital importance for these people due to feelings such as disappointment, sadness, fear, despair, lack of awareness, and pain. Social support is highly valued among these people and is linked to an improvement in these peoples’ quality of life. Different kinds of stigma accompany people with HIV/AIDS throughout their life, like social stigma, self-stigma, and health professionals’ stigma. Seropositive women who decide to become mothers can feel frustration because they cannot breastfeed. Spirituality helps some people to deal with the fact of being a virus or disease carrier.HIV is one of the main problems with regard to public health, with greater representation in developing countries [1]. The most affected region is Africa, where almost two thirds of new HIV infections can be found [2]. Worldwide, amongst the population with HIV, 54% of adults and 43% of children are currently being treated with antiretroviral therapy, with the global coverage of these medications for pregnant women or for women who are breastfeeding being approximately 75%.Being seropositive or having the disease tends to occur in several stages, among which are: the stage of diagnosis, where the person is normally in shock; and the stage of acceptance (positive adaptation) or denial (negative adaptation) [3]. From the beginning of the disease, when it was labelled the so-called “gay-syndrome”, it was characterized by a huge burden of discrimination [4]. This stigma is a negative element that limits the individual’s adaptation to the disease/seropositivity, as well as complicating the management and treatment of the disease; it also creates difficulties in the relationship with the population in general, and with health care professionals [5].Currently, there are global proposals, such as the well-known 90–90–90, the Joint United Nations Program on HIV/AIDS [6], whose aims include raising awareness of the HIV/AIDS epidemic. This proposal, through an ambitious project, suggests that, by 2020, 90% of seropositive people must be diagnosed in the world, 90% of them must be treated, and 90% of them must be free of viral load. It also suggests that different governments and policies join forces to control the disease. In this sense, this research aims to explore the disease from the individual’s own perspective and, therefore, to contribute to making the daily life of people who suffer from it visible.The purpose of this review was to explore the experiences and attitudes of people with HIV/AIDS. We consider that knowledge-based outcomes from this study can help improve decision-making on health strategies to cope with HIV, and also guide future research on the topic.A systematic review of qualitative studies was developed. Our research included studies published in Spanish, Portuguese and English. We selected original articles oriented to qualitative methodologies, whose interest of study was to explore the perspective of people with HIV/AIDS. Studies regarding a pediatric population or focused on adolescence were excluded. We intended to show a broad view regarding the phenomenon under study, which incorporated works from a wide geographical context. That is why different search sources and databases were used, such as CINAHL, PubMed, Lilacs, Cuiden and Google Scholar. In the same way, descriptors from MESH, CINAHL/MeSH, Subject Headings and DeCS (for the Spanish Language) were employed, in addition to non-standardized terms. The English terms that we used were: Human Immunodeficiency Virus, HIV, AIDS, qualitative research or studies; whereas the Spanish terms were: VIH, SIDA, cualitativo. The search was conducted from January to March 2019, including publications until 2018. The oldest article included in the review was published in 2004.Search. Different search strings were designed with thematic, main, and free descriptors for the different databases. For instance, we used the following search string for the PubMed database: <(HIV[mj] OR Human Immunodeficiency Virus*[tiab] OR Human T Cell Lymphotropic Virus Type III[tiab] OR Human T Cell Leukemia Virus Type III[tiab] OR Lymphadenopathy Associated Virus*[tiab] OR Lymphadenopathy-Associated Viruses[tiab] OR Human T Lymphotropic Virus Type III[tiab] OR AIDS Virus*[tiab] OR Acquired Immunodeficiency Syndrome Virus[tiab]) AND (qualitative research[mh])>. Supplementary File 1 shows the different search strings employed in each data source.Initially, duplicate studies were excluded and after that, a screening process took place based on: (1) title; (2) abstract; and (3) the full text. The discrepancies regarding article selection were solved by consensus. Finally, the articles’ methodological quality was evaluated. Hence, 27 articles remained in this review. Figure 1 shows the flowchart.Critical Evaluation. The articles which we considered to be relevant after reading the full text  were evaluated via peer review. An evaluation of these articles’ methodological quality was conducted through the CASPe program for qualitative research [7]. The items included in this guide are “present”, “doubtful” and “not on record”. Therefore, some eligibility criteria were proposed; first, that one of the elimination items does not have “not on record” (1, 2, 3), and also that the rest of the items do not have four or more “doubtful” or “not on record” (4, 5, 6, 7, 8, 9). Item number 10 was not evaluated because it does not focus on the applicability of this research in concrete situations, which exceeds the discoveries’ methodological evaluation and evaluation of relevance. The results of this phase are shown in Supplementary File 2.Despite the fact that 26 articles passed the quality evaluation according to the proposed criteria, we decided to include an article that did not pass it because of the relevance of its results in relation to the aim of the research. On this matter, regarding the syntheses procedures of qualitative studies was followed, which suggests giving priority to the discoveries’ quality in the article selection [8]. Hence, the final number of articles included in the systematic review was 27.Data Extraction. Relevant data (author/s; participants’ country, number and other features: man or woman -mothers or pregnant-; type of research; qualitative approach chosen in the research and field where it was developed, understanding “Hospital” as any hospital field and “Community” as any association, advice or monitoring clinic or health center) were extracted by the main author of this review and verified by the rest of the authors.Data Analysis. After repeated reading of the articles, we carried out the narrative synthesis. It consisted of joining the information by means of common topics, creating in this way different categories and subcategories when necessary. The results are presented here, taking the identified topics as the core idea, describing the main discoveries of the different studies in an integrated manner and incorporating, in some discoveries, direct quote of the studies’ informant participants to show evidence of their narratives.This research is consistent with the guide “Enhancing Transparency in Reporting the Synthesis of Qualitative Research” [9] with the purpose of giving uniformity to the publications of qualitative synthesis studies.Of the 27 studies that met inclusion criteria, sample sizes ranged from 3 to 78, with participants coming from Canada, Ireland, Spain, Kenya, Malawi, Ghana, Ethiopia, South Africa, Brazil, Chile, Peru and Mexico. Moreover, 63% of the participants came from the community field, whereas 27% belonged to the hospital one. All of the articles used the interview in different forms, and, furthermore, only two of them used focus groups among their methods of data collection (Table 1).Five topics emerged after the narrative synthesis: feelings about the diagnosis of HIV/AIDS; stigma and HIV/AIDS; changes in sexual behavior after becoming infected; living with the virus; pregnancy and motherhood in seropositive women (Table 2).This category was identified in 33.33% of the articles, which includes the feelings that the study participants experienced after the diagnosis of HIV/AIDS, as well as the different attitudes that they took to face the situation. The feelings we can highlight are disappointment, sadness, fear, despair, lack of awareness, and pain. In some cases, these emotions lead to depression, or they might intensify it. Hence, feelings of frustration might appear as well due to not achieving the targets that the subjects have set in their life [16].After the diagnosis of HIV/AIDS, it was highlighted that people were afraid of being alone, because the lack of awareness about it causes social exclusion toward the people infected. The acceptance of the diagnosis is difficult; however, it depends on the cultural and social traits of the person. In some cases, people opt for submission to the diagnosis and its consequences or to conformism.In some cases, they accept that the risky practices they have made in their life have resulted in the fact that they are carriers of the virus and they accept their mistake. One participant of the research by Carrasco et al. [15] expresses it in this way: “...when I was informed that I suffered from HIV, I felt an extremely huge sorrow, an extremely huge helplessness, but, at the same time, I was very calm because I admitted and accepted the mistake that I had made when I did not take care of myself...”. However, it should be noted that there are many ways in which a person could become infected (transmitted from a HIV+ mother during birth, blood transfusion), so it does not follow that each person infected did something wrong, made a mistake. Furthermore, even people felt that they were a mistake, it seems unlikely that every one of them would get to a stage where they all “accept their mistake”.Many women discover their HIV status (seropositive) in prenatal care or when the children they have had get sick. This leads to an intensification of all of the feelings previously described and, above them, the fear of transmission to their children, in cases where they are pregnant.After the diagnosis, we can notice in the articles’ results that the advice on and treatment of HIV/AIDS helped participants to accept their situation, avoiding in this way feelings of hopelessness or exclusion. Moreover, they helped to increase their responsibility in regard to self-care, which guarantees longevity and the fact of trying to lead a normal life.This category was identified in 44.44% of the articles, which was, in turn, divided in three subcategories: social stigma, self-stigma and health professionals’ stigma.Social stigma is linked to family stigma; that is, the feeling of prejudice against people with HIV/AIDS which, in many cases, results in the social exclusion of the people who suffer from it. Social stigma is a common issue that people infected with the virus suffer, although it is more highlighted in developing countries. For instance, in these countries, women do not undergo a diagnostic test for fear of being judged by people. Therefore, they have to go to other villages to undergo the test because they are afraid of being isolated from the community. Another characteristic of these countries is that women are the ones who undergo these tests, so that men can blame them (even if they are the main carriers) when they are HIV-positive. Seropositive people are still labelled and judged every day, being treated as promiscuous, homosexual or less honorable, which is linked in many cases to the virus being transmitted through sexual contact.HIV-positive people or people with AIDS make new circles with infected people because they feel free of any judgement. This results in the fact that these people close old social or family circles and they do not divulge the diagnosis. Stigma causes a serologic silence as a means of protection, as well as to avoid discrimination and prejudice. When the serological status is revealed to close people or to relatives, people infected with HIV feel liberated and, generally, accepted. Nevertheless, there are some families that prefer this news to be kept in the privacy of their home to avoid being judged by close people, such as their neighbors. This family acceptance has an influence on the increase in the quality of life, acceptance of the virus/disease and better adherence to antiretroviral therapy in HIV-positive people. In the case of homosexual people with the virus, they frequently suffer the so-called “double stigma”: one because of their sexual orientation, and another because of being seropositive.Most HIV-positive people or people with AIDS, besides suffering discrimination and prejudice by others, also suffer these feelings toward themselves. The fear of transmitting the disease to their relatives or to people in their environment is a common feeling in these people. They even go so far as to take exaggerated hygiene measures or to use different pieces of cutlery to the rest of the family.They also experience feelings of guilt and embarrassment, as well as the belief that the disease is a divine punishment because of their risky behavior some time ago. In the research by Peñarrieta de Córdova et al. [31], one participant stated that: “...every bad act leads to a bad consequence... It is the price that I am paying because of everything that I have done...”. The feeling of being useless, not respectable to society, and undesirable to other people causes social isolation and the retirement of social circles.Some seropositive people take the views of the health professionals who treat them as a reference point because of all the knowledge which they have concerning health. That is why some of these professionals’ practices or attitudes can make people with the virus internalize the discriminatory behaviors that some professionals carry out.In some cases, the fact that health professionals take additional measures as extra-safety precautions during procedures, when they provide clinical care and treatment, is mentioned. This is obvious from the clinical safety point of view; however, participants might misunderstand it in terms of stigma.Although the patients reveal that they felt more singled out and judged by these professionals in the past, they still sometimes perceive it in their clinical care. Other results make reference to the opposite. Health professionals support and reinforce people with HIV/AIDS, which leads to a better adherence to the therapy and to the fact that these professionals become people with whom they can relieve their feelings. This support is more emphasized and necessary when people know they are carriers, because of the psychological impact that this entails.This issue is addressed in 37% of the articles included in this review, so that the main changes, measures and attitudes regarding the sexual behaviors of people with HIV/AIDS are presented. Feelings of anxiety when talking about this matter, insecurity, fears caused by the possible refusal of the others when becoming intimate, decrease in desire and sexual appetite, and apathy and lack of interest are common among seropositive people regarding their sexual lives.It was highlighted that sexual pleasure and intimacy became affected after diagnosis of HIV/AIDS due to fear of transmitting the virus, guiltiness, and lack of freedom. In the majority of them, a change of behavior after the diagnosis prevails concerning the use of a condom. The goal of its use is to prevent the transmission to their sexual partners or to avoid repeated exposure to the virus. The use of a condom is a limitation for many seropositive people, maybe because of the loss of feeling or freedom of choice as they are “forced” to use them (as a preventive measure). This fact makes the adaptation of the individual to live with HIV difficult.In some cases, practices like sexual abstinence for fear of infection are reported. Other people deny accepting their seropositivity and they prefer to give up on sex, which even leads to the person’s isolation on several occasions. In the research by Freitas et al. [20], one of the participants expressed: “I cannot be cured, so I stopped going out, I stopped dating, I isolated myself”.Among these individuals, there is an inability to look for sexual partners with whom they can enjoy life. This is due to the fear of rejection after revealing their serological status, which causes anxiety and constant concern on this matter. On the other hand, the ideal of romantic love and confidence that exists among steady partners (those who are serodiscordant, that is, one of the individuals is carrier of the virus and the other is not) makes them feel less vulnerable to infection themselves, and they forget about the prevention measures.In developing countries, as can be seen in the study carried out by Sikweyiya et al. [32], men feel a loss of masculinity when they find out about the diagnosis, because they have to use a condom (which is one of the reasons why it is hardly used in these countries) and because they have to reduce the number of their sexual partners (polygamy). Another feeling expressed by men is sadness, which is linked to the impossibility to perpetuate their family name and, therefore, this results in a sense of castration.Another relevant issue consists of who is in charge of taking care of the prevention means or of accepting unsafe sexual behaviors. As the reviewed studies present, this responsibility can be understood in three different ways. On the one hand, the responsibility lies with the seropositive person, who has the “duty” to protect the others and to take care of themselves. This is the ethical and correct option. On the other hand, the responsibility is shared, that is, both people must decide whether to take precautions or not to avoid risks. Finally, many people defend the idea that the responsibility of looking after and protecting oneself is individual, as is indicated in one of the participants’ statement that appears in the research by Fernández-Dávila et al. [17]: “The boy took it off from me (the condom). I didn’t say anything. Because this depends on him. I do not think it was necessary that he said any word to me...”.Finally, in spite of understanding concepts like safe sex and preventive measures, condoms are still not used as they should to avoid new infections. As Juárez and Pozo [25] specified in their research, people who are in antiretroviral therapy, despite the fact that the possibilities of infecting the rest have only diminished, feel invulnerable. This makes them relax and employ risky behaviors in their sexual practices.This category was identified in 44.44% of the articles, where the confrontation strategies that people with HIV/AIDS apply in their lives are principally addressed. According to many of the participants of the studies, being seropositive, or a carrier of the disease, means that they increase their self-care, fight for their lives and love other people more in order to receive the necessary support.To overcome the diagnosis with the desire to continue living requires that people with HIV/AIDS make changes in their lifestyles voluntarily and with the full conviction that they are necessary actions to lead a “normal” life. Understanding how the disease functions and what it involves is fundamental for the participants of the different studies reviewed. What helps to put bad practices aside is to focus on healthy habits such as maintaining a positive attitude, moderate physical exercise, a healthy diet and trying to have an active social life. This helps to avoid depression, loneliness, isolation and hopelessness.Among the responsibilities that being seropositive entails, we can include taking medication (antiretrovirals), which help these people to retain their wellbeing as the age. Like Juárez and Pozo [25] mentioned in their research, participants who took medication noticed some improvement in their quality of life. That is why adherence to the therapy and good monitoring is important for them. In Oliveira’s article [30], one of the participants states: “It is a responsibility, because you must take that medication, you must have medical monitoring and you must be careful because you can develop some other diseases”.In developing countries, men who are infected by the virus believe that the search for social support to cope with HIV disease or with being HIV-seropositive is a sign of weakness. Nevertheless, some others express that, after being diagnosed, they had to change their life a lot and to adapt themselves to this new situation. Having to take medication made them feel prisoners and it made the acceptance and adaptation to life with HIV/AIDS difficult.Social support is valued highly among these people. The desire to have more social relationships in their lives is expressed, because this helps them to overcome the negative situation linked with the virus. Their close family and friends are an essential source of support, helping them to make their everyday life more bearable and to make their adaptation positive. Most seropositive people learn to give more value to life, family and friends, as they already know that they are fundamental pillars of support, just like one participant states in the research by Braga et al. [13]: “In this case, it happens that you give more value to life”. Some others, however, avoid speaking about the disease/seropositivity and the feelings that it entails with people close to them, omitting in this way the problem and showing some maladjustment.Finally, another way in which participants attempt to confront the diagnosis and to live with the virus is to get close to religion, which emerges as an emotional support. Faith in some superior being fills these people with motivation, relief, self-improvement and strength. They ask for courage through prayer to not to fall into depression. In Neves and Gir researched [29], one participant declares: “I devoted myself to God’s hands, he is going to give me the answer”. However, other people in De la Cruz et al. [16] described that God punished them for something wrong that they had done in spite of being faithful believers, which creates some uncertainty in them. This category was identified in 37.03% of the articles. It includes comments of seropositive women, some of them being mothers, some others pregnant, and some others with the intention of having offspring. Several issues, such as the causes of becoming pregnant, breastfeeding, and the feelings they experience regarding pregnancy with their condition of seropositivity, are addressed.Among the different reasons that women have for continuing with their pregnancy, as most of them are not planned, we found a need to satisfy their spouses or count on their support. On occasion, family is another kind of support that helps them to continue. Nevertheless, some other times they advise them not to continue with the pregnancy to focus on their own health, because of their condition. Some ecclesiastic communities support these women and encourage them during the motherhood process. Lastly, the most important cause in this category is their own feelings and the availability of antiretrovirals. Some women who are diagnosed before pregnancy tend to be more negative about pregnancy due to the concern about vertical transmission.Many seropositive women should be conscious of the right to motherhood, because they have the same rights as any other women. Many participants of the studies included in the review are aware of this. However, some others, in spite of knowing this, prefer to refrain from motherhood for fear of transmitting the virus, even if it is desired. Regarding breastfeeding, we found distinguishable comments among women who are treated with antiretrovirals and who decide to breastfeed, either by choice or because of the social pressure, and women who, with regret, avoid breastfeeding for the baby’s benefit.With respect to the first group, in many countries, especially in developing ones, it should be noted that breastfeeding is a cultural norm which continues through generations. Women who are virus carriers live with the difficulty of motherhood in these communities, as Acheampong et al. [10] described, and they normally suffer and feel pressured when they breastfeed the baby. Among the feelings that they experience, we can highlight the fear and dread of transmitting the virus to their children through their milk, anxiety because of the uncertainty of knowing if their children are contaminated or not by drinking their milk, and the feeling of guilt when they contract HIV because the responsibility is theirs alone. Hope for the use of antiretrovirals and the effect that these have when they reduce the burden to almost imperceptible levels have also been shown.In the second group, we find mothers who present feelings of failure, sorrow, helplessness or suffering. One participant of the study by Sousa and Gimeniz [33] points out: “It was my dream to have a child and to see him nurse... When he was crying, I could breastfeed him and see how he stopped crying”. For the majority, breastfeeding was a symbol of motherhood.Because of the fact that these women are recommended not to breastfeed, to reduce the virus transmission to their children, the people around them have many prejudices when they see them feeding their children with infant formula. This means that these women do not reveal their diagnosis for fear of rejection, either of themselves or of their children in the future, having to lie on several occasions, as one participant explains in the article by Linder et al. [26]: “When people ask me if I don’t breastfeed, I say that I have an inverted nipple and, although it is true, it is an excuse as well...”. Many of them stated that the information they received from health care providers about why they must not breastfeed was very superficial. Finally, motherhood is perceived as a support in their lives, giving seropositive women a reason to continue living eagerly. They have hope of seeing their children grow up and this is a positive factor in the face of the disease/seropositivity. These mothers usually overprotect their children in order to avoid suffering and rejection from people, as was described by Spindola et al. [34] in their research. Motherhood is a positive factor with respect to the adherence to antiretroviral therapy as well, because the possibility of their children growing up healthily encourages mothers to follow health recommendations.Systematic reviews of qualitative studies provide a broad view of the experiences of people facing health problems. This research focused on analyzing the experiences and attitudes of people who live with HIV/AIDS, based on a wide review that includes works from several countries, with representation in North America, South America, Central America, Europe and Africa. The analysis allowed us to identify the common elements regarding the feelings when facing the seropositivity/disease diagnosis, the stigma, sexual behaviors, and motherhood, which consolidates the work’s international relevance. This review updates the discoveries which were already generated in previous works of similar characteristics, although they were published more than 10 years ago [37,38]. On the other hand, the publication of systematic reviews in this field has progressed in recent years [39,40,41,42,43]; however, the ones that include qualitative research as a source of results or that focus on very specific aspects are scarce. This strengthens the review that is presented in this work, as it is based on qualitative studies, helping topics which were not treated before to emerge.Based on our results, we can highlight the stigma that people who are carriers of HIV suffer. Three types of stigma (social stigma, self-stigma and health professionals’ stigma) were relevant in the results. In accordance with the research by Sandelowski et al. [38], in their metasynthesis, although they focus on the female population, one of the problems of revealing the diagnosis to other people is the prejudices that exist toward seropositive people. On the one hand, when they reveal it, they feel relief and their relationships now provide authenticity. On the other hand, it can also be a reason for social isolation because of the non-acceptance of the others. Barroso et al. [37], in their metasynthesis, supported the results obtained in the research about social relationships, as these are a foothold to better adapt to the virus or to the disease. On the other hand, Villa et al. [40] confirmed in their literature review that the psychological aspects of seropositive people are reinforced by the social support they receive, which helps their adherence to the therapy and improves their quality of life. This last idea was also shown by Tavera [41] in her systematic review.Regarding adherence to the therapy, in one review, Puigventós et al. [39] stated that, in general, people with HIV/AIDS adapted well to the therapy. In the cases in which they do not adhere, the reasons might be that they are social outcasts (stigma), that they are minors, or the lack of motivation, among others. In the results obtained, we observed that, for instance, motherhood is a positive factor (apart from social support) in better adherence to the therapy, reducing in this way the possibility of vertical transmission to the baby. Concerning this last matter, guides for HIV/AIDS management have been published [42,44] which are particularly interesting regarding the approach to motherhood, including recommendations which result in a reduction of vertical transmission.Among the ways to adapt to the disease/seropositivity, we found in the results of this research that religion or the practice of healthy habits favored its normalization in their lives. This is in line with the proposals suggested by other studies [37,41], which claim that spirituality helps some people to confront HIV/AIDS. In addition, it is stated that understanding the disease makes the adaptation favorable as well, as it helps them to carry out positive strategies, such as physical exercise, changes in their diet or safe sexual behaviors. Benito [43], in his systematic review, explained that physical exercise in people with HIV/AIDS makes them gain weight and is favorable to their psychological wellbeing.Based on the results obtained, we suggest the further exploration of themes like the experiences of pregnant women or of mothers and their sexual behaviors in future research, as the fact that some HIV carriers adapt to their situation and some others deny it, despite knowing the risks, can be underlined. Likewise, new research on the moment of diagnosis would be enriching, as it is a crucial moment because of the great psychological impact that it entails.This review is not exempt from limitations. First, even though the sources used for the studies’ search are pertinent, they might not give an account of all of the relevant studies for the objective of this research. To compensate for this limitation, it should be pointed out that the database and the base of resources used are specific to the Health Sciences area (the area in which this research is circumscribed), so that they are widely known and relevant sources in this area. Although no exclusion criteria was applied on a geographical basis, there are regions such as Asia that are not represented in this review, which may be of interest in future research. In this regard, it would also be interesting in future research to locate studies published in languages other than those included in this review.On the other hand, an excessive number of duplicate documents were avoided, which could have happened with the use of other databases that might have a high degree of overlap with the ones used in this review. Another limitation of this review involves the synthesis procedure. We opted for a classic procedure of narrative synthesis, which limits the descriptive and explanatory ability of the studied phenomenon. It would be relevant to progress toward metasynthesis procedures in future research and, in this regard, the discoveries of this review might be the base on which this future research can be oriented.Finally, it would be interesting to specifically include in future research an analysis that could differentiate the findings of the studies analyzed based on various factors. For example, how people feel about being diagnosed is likely to be qualitatively different when there are few options compared to when people can live long lives with effective treatment. It is important to note how the country of origin is related to such feelings, as those in under-developed countries may have less access to treatment, which could impact their feelings about the diagnosis.Most of the people who are carriers of the virus have common feelings when they are informed about their seropositivity. Among them, we found disappointment, sadness, fear, despair, lack of awareness and pain. Sometimes, the diagnosis might lead to depression and social isolation. Social culture and environment are determining factors regarding the acceptance of the diagnosis. Intimacy and sexual pleasure are affected after the disclosure of the diagnosis; some seropositive people feel a decrease of their sexual appetite and, in general, there are changes in their sexual behaviors (e.g. use of condoms). In other cases, they opt for abstinence or, on the contrary, for risky practices, despite knowing their consequences.In the case of pregnant women, many of them find out about the diagnosis when they get pregnant. Some others decide to have children in spite of being carriers and the causes that drive them to do this might be the satisfaction of being mothers or the need to satisfy their partners. Being mothers is a positive factor to fight HIV/AIDS, because it gives them the strength to continue and see how their children grow up. Furthermore, breastfeeding generates distinguishable comments between the ones who desire it and find themselves forced to breastfeed because of the social pressure, for whom the use of antiretrovirals relieves their fears in the face of transmission danger, and the ones who opt for not breastfeeding, showing an evident helplessness.The fact of being seropositive implies a high degree of stigma, as the prejudices against people with HIV/AIDS are evident. Some people lean on their intimate social circle to confront the disease or seropositivity. Religious practices are a positive factor in which they take refuge as well.In the moment of diagnosis, the approach of healthcare providers is of vital importance, because of the impact that the news about being carriers causes on people. Thus, enough support and advice must be offered to these people to avoid future isolation and for appropriate therapeutic adherence. In the same way, correct health education is key to avoiding risk behaviors. It is relevant, from the social environment, to ensure the inclusion of these people in society, avoiding social exclusion.Regarding pregnant women, an early diagnosis of HIV status makes it possible to adopt measures that drastically reduce the risk of mother-to-child transmission. The information provided about the risk of breastfeeding babies must be complete. The fact that these mothers fully assimilate the information before they make a decision must be checked, avoiding uncertainty, sadness or feelings of helplessness.Finally, the COCHRANE collaboration recognizes that “evidence from qualitative studies that explore the experience of those involved in providing and receiving interventions, and studies evaluating factors that shape the implementation of interventions, have an important role in ensuring that systematic reviews are of maximum value to policy, practice and consumer decision-making” [45]. Therefore, this review offers an understanding of the perceptions and feelings of people with HIV/AIDS, and thus it can help to improve the implementation of interventions focused on people and guide public health policies or the development of protocols and clinical practice guidelines, which are in tune with the UNAIDS proposal worldwide [6].The following are available online at https://www.mdpi.com/1660-4601/17/2/639/s1, Table S1: Search strategy in the databases; Table S2: Results after the methodological evaluation CASPe.Conceptualization, T.A.-C., M.Á.P.-M., and C.H.-M.; methodology, T.A.-C., M.Á.P.-M., A.J.R.-M., C.C.-D., M.R.-M., and C.H.-M.; Supervision, M.Á.P.-M., and C.H.-M.; writing—original draft, T.A.-C., M.Á.P.-M., and C.H.-M., writing—review and editing, T.A.-C., M.Á.P.-M., A.J.R.-M., C.C.-D., M.R.-M., and C.H.-M. All authors have read and agreed to the published version of the manuscript.This review received no external funding.The authors declare no conflict of interest.Flow chart of study inclusion and exclusion.Summary of studies included in the review and narrative synthesis.Source: own elaboration.Categories identified in each study.Note: We opted to unify the references by mentioning the first and the second author, if there were two authors. From three authors or more, the first is mentioned and we add “et al.” for the rest. Note 1: “✓” = Article included in the category. Source: own elaboration.

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+Electronic cigarette (e-cigarette) use has had an exponential increase in popularity since the product was released to the public. Currently, there is a lack of human studies that assess different biomarker levels. This pilot study attempts to link e-cigarette and other tobacco product usage with clinical respiratory symptoms and immunoglobulin response. Subjects completed surveys in order to collect self-reported data on tobacco product flavor preferences. Along with this, plasma samples were collected to test for immunoglobulin G (IgG) and E (IgE) levels. Our pilot study’s cohort had a 47.9% flavor preference towards fruit flavors and a 63.1% preference to more sweet flavors. E-cigarette and traditional cigarette smokers were the two subject groups to report the most clinical symptoms. E-cigarette users also had a significant increase in plasma IgE levels compared to non-tobacco users 1, and dual users had a significant increase in plasma IgG compared to non-tobacco users 2, cigarette smokers, and waterpipe smokers. Our pilot study showed that users have a preference toward fruit and more sweet flavors and that e-cigarette and dual use resulted in an augmented systemic immune response.Currently, toxicity from e-cigarette exposure has been observed in acellular, cellular, and human models. E-cigarette vapors have been shown to generate acellular reactive oxygen species (ROS), and exposure to e-cigarette vapors results in an increased generation of ROS by small airway epithelial cells, which poses a potential for lung injury [1]. E-liquid exposure to mucosal tissue has resulted in cytotoxicity and an increase in DNA fragmentation, and exposure to e-cigarette vapors have resulted in cytotoxicity and DNA strand breaks in epithelial cells [2,3]. E-cigarettes use is perceived to be safer than traditional cigarette smoking as there are fewer carcinogens, but concerns regarding pulmonary and cardiovascular diseases remain [4]. Short-term e-cigarette use was found to have immediate adverse effects on pulmonary function, with an increase in lung impedance and peripheral airway flow resistance and a decrease in fractional exhaled nitric oxide [5]. Cardiovascular risks of e-cigarette use are found to be lower than the risks associated with traditional cigarette smoking, but they may pose a great risk to individuals with a predisposition to cardiovascular disease [6]. Given the diversity of e-cigarette products, there has been research exploring the mechanisms in which e-cigarettes affect the body, specifically the immune system. Innate defense proteins, such as elastase and matrix metalloproteinase-9, secreted in the airways are altered in the sputum of e-cigarette users when compared to nonsmokers and have resulted in both similar and unique alterations compared to traditional cigarette smoking [7]. In a rat model, exposure to tobacco smoke resulted in an increase in serum immunoglobulin E (IgE) levels, but did not alter immunoglobulin G (IgG) and immunoglobulin M serum levels [8]. Similar increases in IgE levels were seen in a general population of adult cigarette smokers [9]. It was also observed that ex-smokers had a decrease in levels of IgE once smoking ceased, and the spike of IgE seen in humans due to seasonal allergic rhinitis in non-smokers, but was not seen in smokersthough smokers had high levels of serum IgE [9]. However, to the best of our knowledge, there have been no studies with a diverse group of human subjects that associate e-cigarette use with immunoglobulin level. Currently, only research with mouse models are available; for example, BALB/c mice sensitized to ovalbumin and exposed to e-cigarette vapors experienced increased IgE and cytokine levels compared to unexposed mice [10]. Recently, a survey-based study showed that e-cigarette users reported allergic rhinitis responses; however, immune responses by flavors were not studied [11].It is widely accepted that chronic obstructive pulmonary disease (COPD) can be linked with cigarette smoking and that the most effective management for COPD is smoking cessation [12,13]. Chronic smoking is associated with a higher percentage of symptoms like cough, shortness of breath, and other respiratory problems [14]. Given the similar toxic effects from cigarette smoke and e-cigarette vaping in cellular models, it should then be tested whether or not similar results in immune-inflammatory responses occur. Because e-cigarettes have only been on the market for a short time, long-term effects have not yet been studied. However, clinical symptoms from e-cigarette use, like coughing and dry or irritated mouth or throat, are prominent [15].This pilot study aimed to determine the flavor preference of tobacco product users within our cohorts. We also attempted to determine the clinical symptoms that tobacco product users have, as well as to determine whether tobacco product usage can potentially induce an immune-inflammatory response by measuring immunoglobulin levels, such as IgE [16]. All experiments performed in this pilot study were approved and in accordance with the University of Rochester Institutional Biosafety Committee. These protocols were approved by the Institutional Review Board (IRB) at the University of Rochester Medical Center, Rochester, N.Y. Written informed consent was obtained from all study participants.We used a rigorous and unbiased approach throughout the experimental plans and when analyzing the data to ensure that our data would be reproducible, with full and detailed reporting of both methods and analyzed data. All of the key chemical resources used in this pilot study were validated, authenticated, and of a scientific standard from commercial sources. Our results adhere to the National Institutes of Health (NIH) standards of reproducibility and scientific rigor.This was a cross-sectional pilot study with data collected from 2016–2019, using self-reporting measures on a variety of information in regards to product usage and symptoms. Subjects were recruited via local newspaper and magazine advertisements in the Greater Rochester Area. The pilot study was conducted at the University of Rochester Medical Center (URMC), New York (IRB approval #RSRB00064337 and IRB approval #RSRB00063526), via the Clinical Research Center (CRC). The participants were selected based on a self-reported questionnaire containing information about demographic variables, clinical symptoms, electronic cigarette use, and vaping history and behavior. The participants were categorized into six groups between two separate cohorts. Cohort 1: Non-tobacco users 1, individuals who do not use any tobacco products (n = 26) and e-cigarette users (n = 22); and cohort 2: Non-tobacco users 2 (n = 25), cigarette smokers (n = 26), waterpipe smokers (n = 12), and dual smokers, comprising both waterpipe and cigarette smokers (n = 10). Details on inclusion and exclusion criteria have been reported previously [17,18]. Briefly, inclusion for cohort 1 was based on age, and exclusion was based on other tobacco product usage, individuals with chronic illnesses, or individuals currently infected with pulmonary/respiratory pathogens. Exclusion for cohort 2 was based on age and usage and individuals with chronic illnesses or currently infected with pulmonary/respiratory pathogens. Female participants currently breast feeding or pregnant were also excluded [17,18]. Subjects’ self-reported use was biochemically confirmed via plasma cotinine assay. All subjects were asked to fill out a survey based on the type of tobacco product used. The surveys had all the same questions, and wording only varied on the type of product used in the questions. Data generated for each group were based on responses about the subject’s usage, motivation, and quitting methods. Collection was done following previous methods. Briefly, whole venous blood was collected from participants, and plasma was processed and separated by centrifugation for 10–15 min at 2000× g within 60 min of collection [17,18].Plasma levels of IgE were quantified in samples collected from e-cigarette users, non-tobacco users 1, non-tobacco users 2, smokers, waterpipe smokers, and dual users using an ELISA kit (Invitrogen, Carlsbad, CA, USA, BMS2097) following manufacturer instructions with the minor modification of using a five-fold dilution for non-tobacco users 1 plasma samples and a ten-fold dilution for e-cigarette-user, non-tobacco users 2, smoker, waterpipe, and dual-user plasma samples. Plasma levels of IgG were quantified in samples collected from e-cigarette users, non-tobacco users 1, non-tobacco users 2, smokers, waterpipe smokers, and dual users using an ELISA kit (Sigma, St. Louis, MO, USA, RAB0001) following manufacturer instructions.We used the outcome (IgE and IgG) levels for subjects enrolled in n = 25 with baseline (i.e., non-tobacco users) and analyzed for power calculations using the calculated mean and standard deviations from the data. Using the proc power procedure in SAS v9.4 (SAS Institute Inc., Cary, NC, USA), we computed the power of our statistical analysis through an exact method with a significance level alpha of 0.05. We found that the power ranged from 0.05 to 0.152 for our IgE data analysis and from 0.05 to 0.313 for our IgG data analysis. Analyses used to explore statistically significant differences included using either an unpaired t-test or one-way ANOVA with Tukey’s post hoc test for multiple comparisons by GraphPad Prism Software version 8.1.1. The results are shown as mean ± SD. Outliers were tested using RUOT (robust regression and outlier removal) with Q = 1% by GraphPad Prism Software version 8.1.1. Data were considered to be statistically significant for p values < 0.05.Cohort I: In our cohort 1, consisting of non-tobacco users 1 and e-cigarette users, the average age of non-tobacco users 1 was 33.88 ± 14.07 years old and consisted of 42.30% males and 57.69% females. The average age of e-cigarette users was 35.54 ± 12.21 years old and consisted of 45.45% males and 54.54% females. In non-tobacco users 1, the demographic breakdown was 69.23% Caucasian, 11.53% African American, 15.39% Asian, and 3.84% Hispanic. The e-cigarette users’ demographic breakdown was 50.00% Caucasian, 27.27% African American, 13.63% Asian, and 9.09% Hispanic. Non-tobacco users 1 had no history of e-cigarette vaping or smoking, while e-cigarette users had a vaping duration of 2.00 ± 1.64 years and no history of smoking [18]. Cohort II: In our cohort 2, consisting of non-tobacco users 2, cigarette smokers, waterpipe smokers, and dual users, the average age of non-tobacco users 2 was 36.16 ± 12.52 years old and consisted of 52.00% males and 48.00% females. The average age of cigarette smokers was 46.73 ± 9.96 years old and consisted of 50.00% males and 50.00% females. The average age of waterpipe smokers was 33.16 ± 14.61 years old and consisted of 66.66% males and 33.33% females, and the average age of dual users was 39.50 ± 12.49 years old and consisted of 60.00% males and 40.00% females. In non-tobacco users 2, the demographic breakdown was 84.00% Caucasian, 4.00% African American, and 12.00% Asian. The cigarette smokers’ demographic breakdown was 61.54% Caucasian, 30.76% African American, 3.84% Asian, and 3.84% Hispanic. The waterpipe smokers’ demographic breakdown was 41.66% Caucasian, 25.00% African American, and 33.33% Asian. The dual users’ demographic breakdown was 70.00% Caucasian, 10.00% African American, and 20.00% Asian. Non-tobacco users 2 had no history of cigarette smoking or waterpipe smoking. Cigarette smokers had a duration of 20.03 ± 8.55 years of cigarette smoking and no history of waterpipe smoking. Waterpipe smokers had a duration of 2.72 ± 1.84 years of waterpipe smoking and no history of cigarette smoking. Finally, dual smokers (both cigarette and waterpipe) had a duration of 14.00 ± 12.89 years of cigarette smoking and a duration of 4.69 ± 3.72 years of waterpipe smoking. Smoking patterns in e-cigarette users were measured by self-reporting in three ways: Duration, frequency, and session length. Of the three categories, the most common responses were a duration less than half a year, frequency of greater than ten sessions per day, and a session length of less than five minutes. However, responses varied from half a year to greater than five years’ duration, a frequency of fewer than three sessions per day to greater than ten, and a session length of less than five minutes to a maximum of twenty-minute sessions (data not shown).Nearly half (47.9%) of all subjects preferred fruit flavors, with tobacco being the next most popular flavor (25%), followed by menthol (16.67%), spices (6.25%), and candy (4.16%) (Figure 1A). From this list, it was determined that 63.16% of subjects preferred sweeter flavors over flavors that were less sweet (Figure 1B). For e-cigarette users specifically, 70% of males preferred more sweet flavors, while 63.63% of female users preferred less sweet flavors, more sweet flavors being defined as those that have a sweeter taste, such as those in the fruit and candy categories. For both genders, at least 50% reported that their most preferred flavor was fruit (data not shown).The most common clinical symptom reported by e-cigarette users had eleven subjects reporting a cough 1–2 times per week and only two e-cigarette users reporting having any chest pain/tightness. The most common clinical symptom reported by traditional cigarette smokers had nine subjects reporting a cough several times per week. Cigarette smokers also had the most subjects reporting chest pain/tightness, with four subjects reporting chest pain/tightness 1–2 times per week. Most waterpipe smokers reported having no clinical symptoms with only two subjects reporting chest pain/tightness and another two subjects reporting a cough. Similar to both smokers and waterpipe smokers, thee dual-user subjects reported either a cough several times per week, a cough 1–2 times per week, or chest pain/tightness 1–2 times per week (Table 1).E-cigarette users had a significant increase in plasma IgE levels when compared to non-tobacco users 1. (Figure 2A). However, there was no significant change in plasma levels of IgG in e-cigarette users compared to non-tobacco users 1 (Figure 2B). There was also no significant difference between non-tobacco users 2, smokers, waterpipe smokers, or dual users in plasma IgE levels (Figure 2C). However, in dual users, there was a significant increase in plasma IgG levels compared to non-tobacco users 2, smokers, and waterpipe smokers (Figure 2D).This pilot study attempted to relate e-cigarette and other tobacco product use and plasma immunoglobulin levels with users’ self-reported clinical symptoms in order to bring more attention to the need for longitudinal research. Our pilot study showed a significant elevation in IgE levels (a product of allergic reaction) in e-cigarette users compared to non-tobacco users 1, and e-cigarette users reported the second-highest clinical symptoms of all groups, behind only traditional cigarette smokers. A majority of e-cigarette users reported coughing one to two times per week compared to coughing several times a week among traditional cigarette smokers. This, however, could be due to the shorter duration of vaping e-cigarettes compared to traditional cigarette smokers. Similar to our results, another study conducted on wheezing risk of adult e-cigarette users found that vaping had an increased risk in both wheezing and other related respiratory symptoms [11]. Although there was no significant increase in plasma IgE levels between smokers and non-tobacco users 2, previous papers have found significant increases in IgE levels in adult smoking populations [9]. Smoker plasma IgG levels were found to be decreased in our cohort, although not significant, which is in line with other research that has shown that an increase in the number of cigarettes smoked would result in a decrease in serum IgG levels [19]. Even though there was a significant increase in plasma levels of IgG in dual-users, there were three values that were higher than the majority, while not being outliers. These values may have driven the average to become significantly higher than the other subject groups. Due to this being a pilot project, our current sample size is small, and with a larger subject group from current subject recruitment, we may be able to determine if the select values are driving the average higher than it should be. E-cigarettes have been marketed to adults as a smoking cessation aid or as a safe alternative nicotine delivery system. However, data are mixed on whether or not they are truly helpful [20]. A prospective cohort study in 2015–2016 that looked at whether or not electronic nicotine delivery systems (ENDS) aided in smoking cessation in adult smokers found that ENDS use did not result in higher quitting rates in adult smokers compared to smokers who did not use ENDS [21]. Our e-cigarette subjects reported experiencing clinical symptoms due to their use, although there were no significant effects in lung function of e-cigarette users. The reason there was no alteration in lung function is unknown, but previous studies have shown that the immediate effects of e-cigarette use result in adverse effects on pulmonary function [5]. Regardless of the presence of clinical symptoms, a majority of e-cigarette users reported believing that e-cigarettes are very safe to use. A study looking at college students’ perception of safety for e-cigarette use found that individuals that used e-cigarettes perceived e-cigarette use as safe and posing no risk of second- or third-hand effects [22]. Even though e-cigarette users perceived e-cigarettes as safe, it was shown that e-cigarette users had an elevation in other pro-inflammatory mediators [18]. Perception of e-cigarette health effects are inconsistent with the fact that, even in the short term, users are experiencing adverse effects. A greater focus should be placed on not only conducting research on the health consequences of e-cigarette use, but also on making these findings readily available for the general public for risk assessment and regulation.Our cohort of subjects showed a near majority preference for fruit-flavored products and a majority preference for sweeter flavors. This is in line with another study that looked at JUUL flavor usage in middle-schoolers and high-schoolers, which showed that fruit-flavored pods like mango and fruit were preferred by this young cohort [23]. Despite the fact that e-cigarettes were first introduced to the market in 2007, there has been a rapid market expansion with the amount of unique flavors more than doubling from 2013–2014 to 2016–2017, with 15,568 distinct flavors being sold [24]. With this continuously changing product, future studies should be conducted in a longitudinal model with a larger cohort, looking at immunoglobulin, pro-inflammatory, and oxidative stress biomarkers in e-cigarette users and non-users, with a specific interest in the flavoring effects on these biomarkers. Furthermore, due to recent episodes of e-cig (or vaping) product use-associated injuries, it may be worthwhile to include these cohorts for determining systemic immune-inflammatory responses associated with clinical symptoms.Despite the ability of this pilot study to correlate biological samples with clinical symptoms reported by a group of subjects that use a diverse variety of tobacco products, there are certain limitations to the pilot study. One example is the small sample size due to the limited amount of time collecting samples in the Monroe County. Further work is in progress to increase the sample size in various demographics, using the nationwide Population Assessment of Tobacco and Health (PATH) study samples to correlate the immune-inflammatory response with tobacco flavorings. Our pilot study shows a potential link between clinical symptoms and usage of e-cigarettes and other tobacco products. Our pilot study also showed elevated plasma IgE levels in e-cigarette users compared to non-tobacco users 1, potentially indicating a significant immune response in e-cigarette users. Clinical symptoms for e-cigarette users were the second-most prevalent for subjects, except for subjects that used traditional cigarette smoking. Future studies are required to study subjects over a period of time in a longitudinal study to assess long-term immune response based on flavors and their clinical symptoms.M.J. wrote and edited the manuscript. K.P.S. compiled and edited the manuscript. T.L. conducted IgG and IgE assay/data analysis and edited the manuscript. S.M. edited the manuscript. I.R. participated in writing, editing, and study design. All authors have read and agreed to the published version of the manuscript.This work was supported in part by the National Institutes of Health (NIH) Grants, NIH 1R01HL135613, and the National Cancer Institute of the National Institutes of Health (NIH) and the Food and Drug Administration (FDA) Center for Tobacco Products under Award Number U54CA228110. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the FDA.We thank our participants and our research assistants and nurses, including J.G. at the University of Rochester, N.Y., for initial recruitment of subjects. Thanks to Z.Q.T. at the University of Rochester, N.Y. for discussing the results. We would also like to thank D.L. from the CTSI, URMC, Rochester, N.Y. for providing help in power calculations and biostatistics support.The authors have declared that no competing interests exist.Flavor preferences of subjects. (A) Self-reported survey data based on favorite flavor. Total number of subjects = 48. (B) Self-reported survey data based on sweetness of flavor. Total number of subjects = 38.Plasma immunoglobulin levels in tobacco product users. (A) Plasma samples collected from either e-cigarette users or non-tobacco users 1 were measured for IgE levels following a 1:5 dilution or 1:10 dilution, respectively. *** p < 0.001 vs. non-tobacco users 1. N = 21–23. Outliers removed following robust regression and outlier removal test (RUOT). (B) Plasma samples collected from either e-cigarette users or non-tobacco users 1 were measured for IgG levels following a 1:10,000,000 dilution. N = 21–23. Outliers removed following RUOT test. (C) Plasma samples collected from either non-tobacco users 2, smokers, waterpipe smokers, or dual users were measured for IgE levels following 1:10 dilution. N = 11–21. Outliers removed following RUOT test. (D) Plasma samples collected from either non-tobacco users 2, smokers, waterpipe smokers, or dual users were measured for IgG levels following a 1:10,000,000 dilution. ** p < 0.01, *** p < 0.001 vs. indicated subjects. N = 8–20. Outliers removed following RUOT test, and certain samples were out of range of the plate reader.Clinical symptoms experienced by e-cigarette and tobacco users.Classification of chest pain and cough are based on frequency of symptom experience. Values are reported based on survey data as a total number experiencing that criteria. Varying sample sizes between variables is due to omission of some self-reported items by some subjects.

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+The prevalence of burnout in midwives has been briefly studied. Given the negative effects of burnout syndrome in the physical and mental health, and also related to the quality of care provided, rates of absenteeism and sick leave; identifying related factors for the syndrome are needed. The aim was to determine the prevalence, levels, and factors related to the burnout syndrome, measured with the Copenhagen Burnout Inventory in midwives. A systematic review and meta-analysis were selected from CINAHL, LILACS, ProQuest, PsycINFO, PubMed, SciELO, and Scopus databases, with the search equation “burnout AND (midwife OR midwives OR nurses midwives)”. Fourteen articles were found with a total of 8959 midwives. Most of the studies showed moderate levels of personal burnout. The prevalence obtained was 50% (95% CI = 38–63) for personal burnout; 40% (95% CI = 32–49) for work-related burnout; and 10% (95% CI = 7–13) for client-related burnout. Midwives’ age, less experience, and living alone constitute the main related factors, as well as, the scarcity of resources, work environment, and the care model used. Most midwives present personal and work-related burnout, which indicates a high risk of developing burnout. Personal factors and working conditions should be taken into account when assessing burnout risk profiles of midwives.The well-being of the healthcare workforce is related to levels of job satisfaction and motivation [1]. Its deterioration can provoke many disorders with the burnout syndrome being one of the most frequent. Burnout is a psychological syndrome characterized by physical, emotional, and mental fatigue, which appears as a result of exposure to a series of stressors in a chronic manner [2].There are several validated tools for the measurement of burnout syndrome such as the Maslach Burnout Inventory (MBI) [3], the Professional Quality of Life (ProQOL) [4], or the Copenhagen Burnout Inventory (CBI) [5].The MBI is one of the main measurement scales used in the literature, characterized by a three-dimensional concept (emotional exhaustion, depersonalization, and personal accomplishment), but there are some controversies between its dimensions [5]. That is why given the growing concerns about the methodological quality of the MBI, some authors developed the CBI to reflect more accurately the physical and mental exhaustion [6]. This instrument provides information according to source and causality, without introducing ambiguous concepts such as depersonalization and personal accomplishment.The CBI consists of three subscales: Personal-burnout (degree of physical and mental exhaustion experienced by the individual), with six items; work-related burnout (degree of physical and psychological exhaustion related to the person’s work), with seven items; and client-related burnout (degree of physical and psychological exhaustion related to the person’s work with clients) with six items [6]. All items use a five-point scale score with a range between 0 (low burnout) to 100 (severe burnout). A score between 50–74 represents a moderate level of burnout, a score between 75–99 represents a high level of burnout, while a score of 100 represents severe burnout [5].Midwives are continually exposed to stress-inducing factors associated with absenteeism and work leave profession due to the low degree of personal and professional satisfaction perceived [7,8]. Moreover, the closure of health units and the reorganization of services has reduced their autonomy and medicalized the assistance [9,10]. It supposes a negative impact related to the ability of concentration and communication skills and endangers the quality care [11].To improve the relationship between mother–midwife, new models of care have appeared, such as the caseload midwifery [12]. This model is focused on the continuity of care, with a 24 h availability upon the mother’s needs, and a strong emotional link between mother and midwife [13]. Caseload model offers autonomy and independence in care, and is considered to be a related factor against burnout [14,15].Many authors have studied the prevalence and levels of burnout in health professionals [16,17,18,19,20], and even some systematic reviews and meta-analyses have explored their relationship with possible related factors [21,22,23,24,25]. However, these papers have been performed in different hospital units, excluding maternity ward or did not distinguish between the nurses and midwives [26].Although the multiple factors related to burnout syndrome in other groups may apply to midwives, only a few studies analyze its impact. Moreover, few studies have been developed through the use of a measurement tool of burnout syndrome. Therefore, the importance of this work is focused on the CBI scale, being an instrument validated in midwives with greater reliability [27].Furthermore, it is important to clarify which are the burnout related variables to contribute to the service reorientation and care models and identify the prevalence among midwives. However, no known meta-analyses have been conducted regarding this context. Therefore, the objectives of this paper are: (1) To calculate a meta-analytical estimation of the prevalence of burnout syndrome in midwives, (2) to describe the levels of the three CBI subscales (personal, work-related, and client-related burnout), (3) to analyze the factors related to burnout syndrome.A systematic review and meta-analysis were performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines [28] (Table S1).The following sources were consulted: CINAHL (Cumulative Index of Nursing and Allied Health Literature), LILACS (Latin American and Caribbean Health Sciences Literature), ProQuest (Proquest Health and Medical Complete), PsycINFO, PubMed, SciELO (Scientific Electronic Library Online), and Scopus. The search was conducted in December 2019, using the MeSH terms “burnout AND (midwife OR midwives OR nurses midwives)” as a search strategy.First, two authors, after removing duplicate studies, independently reviewed the title and abstract of the articles found. A third author was consulted in case of disagreement. Subsequently, the full-text articles were reviewed, according to the inclusion criteria and a critical reading was done (see Figure 1).The inclusion criteria were: (1) Primary quantitative studies, (2) sample of midwives, (3) the use of the CBI scale as a measurement instrument, (4) the measurements of burnout levels expressed in mean or percentage values, (5) written in English, Spanish, or French languages. Any date of publication was acceptable. We excluded articles that did not meet the following criteria: (1) Mixed samples lacking independent data on midwives, (2) not providing sufficient statistical information to calculate the effect size, (3) not using the CBI as a tool to measure burnout, (4) midwifery students sample.Two authors extracted data from all included studies using a data coding form. A third author verified the data in case of disagreement. The following variables were obtained for each of the articles: (1) Information about the study (authors, year of publication, country), (2) study design, (3) sample selection, (4) instrument reliability coefficient, (5) sample size, (6) burnout levels (mean, standard deviation), (7) percentages for each subscale of the CBI (personal, work, and client-related burnout), (8) factors related to burnout syndrome.To access the reliability of the data coding by the researchers, the intraclass correlation coefficient was calculated and it was 0.97 (minimum = 0.96; maximum = 1). The Cohen Kappa coefficient was used for categorical variables and it was 0.96 (maximum = 0.97; maximum = 1).The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guide was used, proposed by Sanderson et al. [29]. The domains evaluated were: Selection bias, measurement bias, design specific bias, confounding bias, statistical method bias, and conflict of interest or funding source.A quality assessment tool, Oxford Center for Evidence-Based Medicine Levels of Evidence Working Group (OCEBM) [30], was used for the level of evidence and grade of recommendation.Three meta-analyses of randomized effects were performed, to calculate the prevalence of burnout and the corresponding confidence interval, one for each CBI subscale.The program used was StatsDirect (StatsDirect Ltd., Cambridge, UK) for the analysis, presenting the results grouped on forest plots.Data heterogeneity was assessed using the I2 index. This test measures the percentage of the variability in effect estimates that is due to heterogeneity. There was significant heterogeneity if the I2 values were greater than 50% [31]. Publication bias was assessed using the Egger lineal regression test.The initial search provided 1756 articles. After reading the title and abstract, 873 articles were not selected. After reading the full text of the remaining articles, a total of 14 articles were finally selected. The study selection process is shown in Figure 1.All of the included studies (n = 14) were cross-sectional. Half of the studies were conducted in Australia [32,33,34,35,36,37,38], two in Denmark [5,39], and the rest in Canada [40], New Zealand [34], Norway [41], Sweden [42], and the United Kingdom [43]. The total number of midwives was 8958. All of the studies, except one [5], were done after 2013. Most of the articles used convenience sampling, except two articles, being randomized [39,41]. The reliability of the CBI questionnaire estimated in nine articles was acceptable, with a Cronbach α minimum of 0.76 and maximum of 0.93 (Table 1). Regarding the methodological quality, all studies presented an adequate level of quality. The evaluation is represented in Table 1 and Table 2.Moderate levels in personal-burnout are shown with average scores from 50 points to 65.4 [32,34,35,36,38,40,43,44]; although other authors found low levels of personal-burnout [5,33,37,39,42].Regarding the work-related burnout dimension, two authors found moderate levels of burnout [36,43], while the rest of the authors established lower scores between 33.85 and 48.44 [38,42].Finally, all the authors found low average scores in client-related burnout, from a minimum of 8.3, to a maximum of 38.4 [5,44]. This information is listed in Table 1.Among the personal variables, a lower age range and being single is related to a higher burnout score [35,36,40,41,42,43]. The family plays a protective role [41], although having children generates controversy; for certain authors, this fact contributes to reducing personal and work-related burnout [35], others only found a relationship with client-related burnout [42,43], and for some, having children increases the levels [40], or even no relation was found [36].Regarding the geographical area, studies carried out in northern Europe, show lower levels of burnout [5,39,41]. The postnatal area and performing education and management functions increase burnout [35,36], as well as, working in rural areas reduces the scores [35].Regarding work-related variables, the autonomy and a major experience are positive related factors [35,36,37,41,42,43]. The lack of staff and resources [34,42], low salary [36], a poor professional recognition and organization [34,41], and a negative work environment [34,40,42], are considered factors related to burnout. This is related to high rates of dropout from the profession of up to 58.9% [42].Moreover, other associated psychological variables were found, such as medium-high levels of anxiety (20%–38%), depression (17.3%–33%), and stress (22.1%–36.7%) [32,42,43].The caseload midwifery model presents lower levels of burnout than the traditional models [33,34,35,37,39,44]. Some factors such as autonomy, care continuity, work schedule flexibility, and work for task organization, are the main aspects identified in the caseload midwifery model [34,37].Despite showing a 24 h availability, the satisfaction levels are elevated, thus working a high number of hours, which is not related to a higher risk of burnout [41,42].A total of 5946 midwives were included in this meta-analysis (Table 3). Egger linear regression shows an absence of publication bias, being for personal-burnout p = 0.30; for work-related burnout p = 0.44; and for client-related burnout p = 0.88.Regarding the analysis of the heterogeneity of the studies, the I2 index was 98.5% for personal burnout, 97.3% for work-related burnout, and 90% for client-related burnout, with a high level of heterogeneity in the three subscales of burnout.With a random effects meta-analysis, the prevalence for personal burnout was 50% (95% CI = 38–63), for work-related burnout was 40% (95% CI = 32–49), for client-related burnout was 10% (95% CI = 7–13). The meta-analytical estimate is shown in Figure 2, Figure 3 and Figure 4.The purpose of this systematic review and meta-analysis was to analyze burnout levels and prevalence in midwives who carry their work in any healthcare setting, as well as, the related factors that could influence the development of the syndrome.There are high levels of personal and work-related burnout, and low levels of client-related burnout; however, other authors found high levels in work and client-related burnout dimensions [27]. The results show a prevalence for personal-burnout of 50%; for work-related burnout of 40%; and for client-related burnout of 10%, similar to other studies [45].In relation to personal-burnout, the high prevalence is related to a low salary and a lack of professional recognition which could reduce the commitment at work [8,46,47,48,49].The high prevalence found in work-related burnout is due to occupational variables, such as media shortages, labour disputes, and lack of organization [50]. Similarly to the results found in this review, many authors associate these factors to leave the profession up to 50% [8,42]. Although deep dissatisfaction with their role in the organisation is also related to the exposure to chronic stress and anxiety situations [51]. Even the fast and inadequate care information after discharge, putting in risk the mother and the newborn’s health, could be related to higher levels of burnout in the postnatal area [52]. A lower score is found in rural areas, although several studies report that in these areas there is a lack of resources and a high level of stress, that predispose to burnout appearance [53,54]. Moreover, other authors found that management and administration functions are associated with higher levels of burnout [55].Although we found low levels of client-related burnout, other authors report high levels related to constant demands and family claims [27].On the three subscales, the young, less experienced, and single midwives, presented higher levels of burnout [56,57], probably related to poor practical skills and lack of emotional support [58]. Family and having children are considered positive related factors; although the relationship of the latter case is not clear [23,50].In caseload midwives, the number of working hours does not appear to increase the level of burnout; although in other health groups this relationship is found [59].The benefits of the caseload model are clear. The fact that this model reduces burnout levels is due to a continuity of care and autonomy [1,15,60]. Therefore, it may be that in northern European countries where currently trialing caseload care mode and Australia that has already adopted this model, leading to score lower levels of burnout [14]. In addition, greater job satisfaction is found, since, despite being available at any time of the day, they can organize work and family life balance thanks to working schedule flexibility [61]. However, other authors found difficulties related to the high responsibility in care [62].The burnout syndrome is a complex, subjective, and multifactorial term, so it is difficult to attribute its development to a specific cause. However, the measurement by the CBI is very useful. This is because the CBI addresses more realistically the levels of physical and mental exhaustion of health personnel, and in our case in midwives [27,63]. Moreover, this model distinguishes between occupational and personal related factors, and it is also interesting because it contemplates the relationship between healthcare professionals and patients [64].The key to early prevention is the identification of risk factors and the reorganization of care [65]. Essential strategies are increasing work motivation and developing techniques to cope with the great physical and mental burden, to take account by healthcare administrators and managers [66].This study presented some limitations. The first one, since they are cross-sectional studies, it is difficult to establish a causal relationship over time. Second, in the majority of the articles, a convenient sampling was used and this increases the risk of selection bias [31]. Moreover, the heterogeneity of the obtained data is due to the different geographical locations, where healthcare systems, structures, and resources vary depending on the economic status [67].Midwives are vulnerable to the burnout syndrome because moderate levels in personal-burnout and high prevalence in personal and work-related burnout have been reported. The factors that appear to exert more influence are age, less experience, and living alone. Furthermore, some work-related positive variables are autonomy and continuity of care.The use of the Copenhagen Burnout Inventory allows identifying the different contexts related to burnout, both at a personal and work-related level, establishing with more precision the origin of the cause. However, longitudinal studies are needed to determine the possible risk factors that could influence burnout levels in midwives.Adopting new care models and reorganizing the system providing continuity in care, are aspects to be developed on sanitary organizations against burnout. Future research should develop strategies programs in midwives, aimed at reducing personal and work-related burnout.The following are available online at https://www.mdpi.com/1660-4601/17/2/641/s1. Table S1: PRISMA checklist.Conceptualization, N.S.-M., L.A.-G., E.O.-C., and E.I.D.L.F.-S.; Data curation, L.R.-B. and J.L.G.-U.; Formal analysis, N.S.-M., L.A.-G., L.R.-B., J.L.G.-U., and E.I.D.L.F.-S.; Funding acquisition, N.S.-M. and E.O.-C.; Investigation, N.S.-M., L.A.-G., L.R.-B., J.L.G.-U., K.V.-R., and E.I.D.L.F.-S.; Methodology, N.S.-M., L.R.-B., and J.L.G.-U.; Project administration, N.S.-M., L.A.-G., and E.I.D.L.F.-S.; Resources, K.V.-R. and E.O.-C.; Software, L.A.-G. and J.L.G.-U.; Supervision, L.A.-G. and E.I.D.L.F.-S.; Validation, E.I.D.L.F.-S.; Visualization, L.R.-B., K.V.-R. and E.O.-C.; Writing—Original draft, N.S.-M., K.V.-R., E.O.-C., and J.L.G.-U.; Writing—Review and Editing L.A.-G., L.R.-B., and E.I.D.L.F.-S. All authors have read and agreed to the published version of the manuscript.This research received no external funding. This study forms part of the Doctoral Thesis of the first-named author within the Psychology Doctoral Programme from the reference University. The authors declare no conflict of interest.Flow diagram of the selection process.Forest plot of personal-related burnout prevalence.Forest plot of work-related burnout prevalence.Forest plot of client-related burnout prevalence.Sample characteristics.a,b Two samples were present; * p < 0.001; ** p < 0.01; *** p < 0.05. Note: CB: Client-related burnout; CBI: Copenhagen Burnout Inventory; CS: Compassion satisfaction; DASS: Depression, Anxiety and Stress Scale; EL: Evidence level; QOLS: Quality of Life; MPQ: Midwifery Process Questionnaire; PB: Personal burnout; PEMS:  Perceptions of empowerment in Midwifery Scale; PES: Practice Environment Scale; RG: Recommendation grade; WB: Work-related burnout.Criteria for assessing risk of bias for observational studies by Sanderson et al. [29].Note: H: High; L: Low; UC: Unclear.Prevalence of personal, work, and client related burnout (CBI scores > 50 points).

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+Background: Health literacy (HL) is perceived as one of the most important concepts for modern health promotion activities to be successful. The research undertaken in the context of HL usually focuses on its antecedents and consequences, either for specific groups of patients or society or for the whole population. Objectives: The main aim of this study was to assess the antecedents and consequences of limited health literacy (HL) in a nationally representative sample of the Polish population. Methods: The analysis was carried out on the data obtained from a sample of 1000 Polish citizens through a telephone-based survey undertaken using a short, 16-item questionnaire developed within the European Health Literacy Project (HLS-EU). The total HLS score was calculated according to the guidelines published by the HLS-EU project. Chi2 test and logistic regression models were used for the analysis of the relationships between the variables. Results: The mean HL score (standard deviation) in the study sample was 12.99 (3.11). HL was related to age, marital and vocational status. Limited HL was associated with a lower self-assessment of health (OR, 95% CI: 2.52, 1.54–4.13), the prevalence of obesity and disability (1.71, 1.13–2.57, and 1.92, 1.25–2.94, respectively), less frequent physical activity (0.70, 0.49–0.99), a lower consumption of fruits and vegetables (0.47, 0.34–0.65), and with more frequent hospitalisations (2.02, 1.38–2.95). Conclusions: The assessment of HL using the16-item HLS-EU questionnaire may be a useful tool to enable health behaviours and utilisation of health care resources by society to be predicted.Health literacy (HL) is perceived as one of the most important concepts for modern health promotion activities to be successful. In the Declaration arising from the 9th Global Conference of Health Promotion held in 2016 in Shanghai, health literacy was indicated as a critical determinant of health [1]. The Declaration reinforced the message about HL being a pivotal tool to empower citizens and enable them to engage with collective health promotion actions [1]. In the available literature, there are many definitions of health literacy. The one which is often cited originates from the “Health Promotion Glossary” published in 1998 under the auspices of the World Health Organisation (WHO), which defines HL as “the cognitive and social skills which determine the motivation and ability of individuals to gain access, understand and use information in ways which promote and maintain good health” [2]. A comprehensive review of the existing HL definitions and models was carried as part of the European Health Literacy Project (HLS-EU) [3]. Apart from a detailed literature search, the researchers from the project developed an integrated model of health literacy encompassing access, understanding, appraisal, and application of health-related information in three domains; health promotion, disease prevention, and health care [3]. The research undertaken in the context of HL usually focuses on its antecedents and consequences, either for specific groups of patients or citizens or for the whole population. The available evidence from population studies shows that health literacy may depend on sex, age, level of education, economic and/or social status, and the type of vocational activities. In the research carried out to date, it has been demonstrated that lower HL is displayed by men rather than by women [4,5,6,7], by people having lower levels of educational attainment than by those with higher levels [4,5,6,7,8,9,10,11,12], by single people than by married people [7,13], by people with lower social status than by those with a higher status [8,11,14], by people of lower rather than those of higher economic status or income [4,7,8,9,13,15,16] and, finally, by people living in more challenging conditions [6,8]. In most studies, there was also a general trend for HL decreasing with age [4,6,8,9,15]. The efforts undertaken in the last decade resulted in a comprehensive assessment of the consequences of limited health literacy. In 2011, the updated version of the systematic review authored by Berkman et al. [16] was published. This stated that low HL might be associated with more frequent hospital admissions and the use of emergency care; lower participation in screening programmes, e.g., mammography; lower receipt of influenza vaccine; as well as a lower appreciation and understanding of health information, e.g., that provided on labels attached to health products. It was also found that in older groups, low HL may be associated with lower overall health status and with higher mortality rates [16]. More recent reviews have confirmed, or have revealed new findings about, the consequences of low HL in various groups of patients and citizens. For example, according to Humphry et al. [17], low HL may be associated with poor uptake of cancer screening, difficulty in making treatment choices and reduced quality of life following a diagnosis of cancer. In turn, the review of Zaben and Khalil [18] showed that low HL in patients with acute coronary syndrome is associated with their reduced quality of life. During the HLS-EU project, the consequences of low HL were thoroughly assessed [4]. The European survey was carried out using a 47-item questionnaire developed by the project (HLS-EU-Q47) [19] in eight European countries. It revealed that limited health literacy was associated with poor health status, having more than one long-term illness and the higher use of health care services involving six or more consultations with doctors in the last 12 months [4]. Other studies, in which national versions of the HL questionnaire developed within the HLS-EU project were used, confirmed that low HL may be associated with people’s poor self-assessment of health status [12,20], the prevalence of long-term illnesses [12], the higher utilisation of health care resources [14,21], and a lower level of physical activity [22,23,24].Although the scope of information which arises from the HLS-EU-Q47 is extensive, it appears that the size of the tool may result in reduced compliance of respondents, especially if the questionnaire is used as a part of a survey which is also focused on other issues. Therefore, a shortened but also validated, the 16-item version has been used in many surveys (HLS-EU-Q16) [5,12,25,26,27,28,29]. The HLS-EU-Q16 questionnaire has been used not only in direct interviews with respondents [27,29] but also for telephone-based studies [12,26,30] or online surveys [31]. In some studies, the paper-based questionnaire was self-administered by respondents [32]. The only previous study of HL on a nationally representative sample of the Polish population was undertaken as part of the HLS-EU project [4] using the HLS-EU-Q47 questionnaire. This survey was carried employing a computer-assisted personal interview (CAPI) technique in July and August 2011 on a sample of 921 respondents. The mean general HL score in Poland was 34.45, which was lower than that in the Netherlands and Ireland and broadly the same as in Germany. Of the Polish respondents, 10.2% possessed inadequate general HL and 34.4% problematic HL. The general HL score showed a low correlation with age, education level, the main employment status, and the self-assessed social status but a moderate correlation with the self-assessment of financial deprivation. It would appear that no follow-up surveys are available. The main aim of this study is to report on the assessment of health literacy using the HLS EU-Q16 tool as well as undertaking an analysis of the possible antecedents and consequences of limited HL in the Polish population. The analysis reported in this paper was based on the data originating from the survey carried out on a nationally representative sample of respondents at least 18 years old (n = 1000) in December 2016. The participants of the survey were recruited by a third party, Biostat Company (Biostat Sp. z o.o., Rybnik, Poland) [33], a company which has considerable experience in the conduct of opinion polls. This minimum size of the sample was established after taking into consideration the size of the population (31,535,606, according to Statistics Poland, the central statistical office in Poland [34]), the fraction of 0.5, and a confidence level of 0.95. For the sample of 1000 respondents, the level of the sampling error was 3.1%. A technique of computer-assisted telephone interviewing (CATI) was used in the survey. It was carried out by the CATI System’s research panel of interviewers employed in the Biostat Company [33]. The selection of the respondents relied on stratified proportional sampling from a database of mobile and stationary phone numbers developed by the Company. The structure of the sample corresponded to the Polish population relating to age, education, place of residence and NUTS1 regions. The strata were based on data given in the 2015 Local Data Bank of Statistics Poland [34].The study received the consent from the Bioethical Committee of Jagiellonian University (No. 122.6120.313.2016 issued 24 November 2016).The questionnaire used in the survey consisted of 58 items and included the HLS-EU-Q16 (Polish version of items applied in the survey performed initially within the HLS-EU project), an 8-item Polish version of eHEALS scale (Pl-eHEALS) [35,36], and a set of items asking about the use of Internet-based health information, health behaviours, self-assessment of health status, chronic diseases, disability status, and attitudes toward the possibility of public health interventions. Items exploring a series of key socio-demographic factors were also included in the integrated questionnaire. The respondents could assign one of four responses to items in the HLS-EU-Q16 (very difficult, fairly difficult, fairly easy, very easy). In the event of them not being able to select, or they did not wish to select, any of these options, the interviewer was supposed to mark the particular item “difficult to say/not applicable”. The score based on the responses to the 16 items was calculated according to the recommendations of the HLS-EU project team [37]. The response options, “very difficult” and “fairly difficult”, were assigned with the score 0 and response options “fairly easy” and “very easy”—with the score 1. The response “difficult to say/not applicable” was regarded as a missing value. The total score was calculated as a sum of the subscores obtained for the individual items, but only if the number of missing values was not greater than 2. The evaluation of the16-item version of the HLS-EU questionnaire confirmed its adequate reliability; the Cronbach’s alpha coefficient was 0.902, and the Guttman half-split coefficient was 0.820. As recommended by Pelikan et al. [37], based on the total score, three categories of HL were established: “inadequate” for a score below 9, “problematic” for a score in the range from 9 to 12, and “sufficient” for a score above 12. In this reported study, the first two categories have been combined into a “limited HL” category as in the study reported by Levin-Zamir et al. [27].Following a review of literature, it was decided to include the sociodemographic variables including sex, age, education level, place of residence, marital status, professional activity as well as the use of the Internet, the use of mobile telephony and the time spent watching TV in the analysis as antecedents of HL. It was also assumed that HL might be associated with the self-perception of health status, the presence of chronic disease or disability, the prevalence of obesity, health behaviours and the utilisation of health care, this being based on the use of health care services and hospital admissions in the preceding 12 months.Statistical analysis was performed with the IBM SPSS v.24 software (IBM Corp. Armonk, NY, USA). Descriptive statistics were calculated for variables used in the analysis; absolute and relative frequencies for categorical variables and the mean and standard deviation (SD) for continuous variables. In the analysis, the chi2 independence test and univariate and multivariate logistic regression models were used. The level of p < 0.05 was treated as being significant. In the first step, the association of the variables reflecting the potential antecedents or consequences with HL was evaluated with the chi2 test. As a second step, the association of the potential determinants of HL was assessed with univariate logistic regression models. The effect of limited HL on potential outcome variables was assessed further by employing multivariate logistic regression models after making an adjustment for sex, age, and the level of education of respondents. Before the multivariate logistic regression models were developed, the multicollinearity was assessed. The variance inflation factor and the tolerance were in the expected ranges for all three models. For each multivariate regression model, the Hosmer and Lemeshow chi2 test and the Nagelkerke R square were calculated. For the independent variables included in logistic regression models, the p value, the odds ratio (OR) and 95% confidence interval (95% CI) are reported.The mean age (SD) of the respondents participating in the survey was 45.9 (16.2) years of age. In the study group (n = 1000), 52.3% were women. Of the respondents, 28.3% lived in rural areas, 32.7% resided in urban areas with a population at least 100,000. 56.4% of the survey group declared an education level below upper secondary and 38.5% possessed a university bachelor’s or master’s degree. Of the respondents, 58.0% were married, singles comprised 29.0% and widowed, divorced or persons in separation 13%. Of the surveyed persons, 54.6% were employed in the public or private sector or were self-employed (entrepreneurs or farmers), 28.0% were retired, or on a disability pension, 8.4% were University or high school students, and the remaining 9.0% were vocationally inactive. In the study group, 84.9% were users of the Internet, and a total of 92.6% were mobile telephone users, including 64.2% who owned a smartphone. The percentage of missing values due to the responses “difficult to say/not applicable” ranged from 1.3% for item 4 to 11.6% for item 12 on the questionnaire, as shown in Table 1. The response “fairly easy” was selected by more than 50% of respondents for all items, but “very difficult” was selected least frequently with the highest percentage being 3.9% for item 12. An HLS-EU-Q16 score could be determined for 84.2% (n = 842) of the respondents. The mean score (SD) was 12.99 (3.11), with a median of 14.00. After dichotomisation of the score, of the 842 for whom a score could be determined, 34.8% (n = 293) respondents were categorised with a limited HL, and 65.2% (n = 549) with sufficient HL. The analysis of the potential antecedents of HL carried out with the chi2 test showed a statistically significant association with the marital and vocational status (Table 2). Further analysis based on the univariate logistic regression revealed that there was a significant association between HL and age, marital and vocational status (Table 2). Specifically, respondents 50–59 years old were less prone to have limited HL than those aged 18–20 years (OR, 95% CI: 0.61, 0.38–0.98). Furthermore, married persons less frequently had limited HL than singles (OR, 95% CI: 0.65, 0.47–0.89). Finally, students and pupils were 1.8 times more likely to have limited HL than respondents who were employees or self-employed (OR, 95% CI: 1.80, 1.08–3.00). The chi2 test revealed that HL was associated with the self-assessment of health status (p = 0.001), disability status (p = 0.006), the prevalence of obesity (p = 0.019), the intensity of physical activity (p = 0.048), the consumption of fruits and vegetables (p < 0.001), the consumption of fast food (p = 0.022) and hospital admission in preceding years (p < 0.001) (Table 3). The multivariate logistic regression models, in which the effects of dichotomised HL variable were adjusted for sex, age, and education level, confirmed most of these associations. The persons with limited HL, 2.5 times more frequently (OR, 95% Cl: 2.52, 1.54–4.13), those with disability nearly twice as often (OR, 95% CI: 1.92, 1.25–2.94) and obese persons 1.7 times more frequently (OR, 95% CI: 1.71, 1.13–2.57), assessed their health status as unsatisfactory than those with sufficient HL. Furthermore, such respondents less frequently undertook any form of physical activity in the preceding month (OR, 95% CI: 0.70, 0.49–0.99) or consumed fruits and vegetables (OR, 95% CI: 0.47, 0.34–0.65). Finally, these respondents were 2 times more often admitted to hospital in last the 12 months (OR, 95% CI: 2.02, 1.38–2.95). In this paper, the results of the analysis of the possible determinants of HL, as well as the association of limited HL with the self-assessment of health status, the prevalence of a chronic disease or/and disability, health behaviours and the utilisation of health care resources, are reported. The paper reports the first assessment of the HL of Polish society carried out five years after the HLS-EU survey. For this assessment, a short, 16-item version of the HLS-EU questionnaire was used. On the basis of the responses to this questionnaire, an HLS-EU-Q16 score was calculated according to the HLS-EU project team’s recommendations. It was possible to calculate the score for 84.2% of the respondents to the questionnaire. The score was dichotomised into categories of “limited” and “sufficient” HL. Further analysis was carried out from the perspective of the antecedents and consequences of the possession of limited HL. For those for whom a score could be calculated, it was found that 34.8% had limited HL. A very similar level of inadequate and problematic HL was found by Levin-Zamir et al. [27] in a national sample of respondents in Israel. These researches also undertook their survey using the HLS-EU-Q16 tool but adapted to Hebrew, Russian, and Arabic. In 2013–2014 the “German Health Update” study was carried out using the HLS-EU-Q16 questionnaire and showed that inadequate and problematic HL was as high as 44.2% [26]. Tiler et al. [25] reported the results of the assessment of HL in 1,107 urban elderly adults from Eastern Germany recruited for the 2013 wave of the CARLA study. Although these authors used the HLS-EU-Q16, they calculated HL scores using the method applied earlier for the HLS-EU-Q47 giving results in four categories of HL. Therefore, their results are not fully comparable with the results of the Polish survey. Nonetheless, it is relevant to report that in their study, the frequency of inadequate HL was 4%, and that of problematic HL was 23%.The frequency of limited HL in Polish society was much higher than among respondents from Catalonia as reported in a recent study by Garcia-Codina et al. [29]. They performed a survey of HL on a group of 2433 inhabitants [27]. The total frequency of respondents with inadequate and problematic HL was only 15.4%. However, the validation study of the HLS-EU-Q16 carried out on 223 Italian respondents from Florence and its surroundings published by Lorini et al. [12] stated as many as 67% of the respondents displayed inadequate or problematic HL. In two studies undertaken in African countries, the frequency of limited HL (inadequate or problematic) was much higher than has usually been reported in the studies carried out on European populations. Almaleh et al. [7] used the adapted HLS-EU-Q16 tool to assess the HL of patients attending an outpatient clinic of one of the University hospitals. In this sample, only 18.9% of respondents demonstrated sufficient HL. The frequency of inadequate HL was 34.3% and of problematic HL 46.7%. In turn, the study performed by Amoah [28] among inhabitants of the Ashanti Region in Ghana revealed that the frequency of inadequate HL was 24.0% and of problematic HL 38.8%.The HLS-EU-Q16 instrument was applied by Wangdahl et al. [38] in the survey performed in 2015 on a group of 455 adult refugees in Sweden. In this group, only 38.2% of the respondents had sufficient HL. A high frequency of inadequate and problematic HL measured with the HLS-EU Q16 tool on a group of Somali refugee women in Oslo was reported by Gele et al. [39]. It should be noted that these authors calculated the total score and established categories of HL analogically, as did Tiler et al. [25].The analysis of possible antecedents of HL in the Polish population showed statistically significant association only with age, marital and vocational status. Limited HL occurred less frequently among the respondents aged 50–59 years than among those aged 18–29, similarly less frequently among married persons than singles and finally, among employed or self-employed than among students and pupils. Jordan and Hoebel [26] reported in 2015 that HL measured with the HLS-EU-Q16 tool was associated with educational level but not with the sex and age of respondents. In the study of Tiler et al. [25], there was a positive association between HL and age, educational level, net household income, and self-perceived social position. Interestingly, in this study, women displayed a lower HL than men. The study of Levin-Zamir et al. [27] found, that after controlling for other determinants only the number of years of education and the level of income were significantly associated with HL. Garcia-Codina et al. [29] reported that low health literacy was associated with lower levels of education and low socioeconomic status. These researchers regarded a physical limitation that restricted the ability to perform everyday activities as an antecedent of HL and confirmed that it was strongly associated with low HL (OR, 95% CI: 2.50, 1.34–4.66). In turn, Lorini et al. [12] showed that the HLS-EU-Q16 score (as assessed with the chi2 independence test) was associated with the level of education and being trained or employed in healthcare. In this study, the prevalence of long-term illness, treated as an antecedent, was also associated with low HL. In the Egyptian population, inadequate HL was more frequently found in males and in persons with a low level of education [7]. The study of Amoah [28] in Ghana showed that HL was associated with age, place of residence, marital status, education level and income. Recently, Eronen et al. [40] carried out face-to-face interviews with a group of 292 Finns aged 75 years old in order to assess their HL. The authors used the HLS-EU-Q16 tool but calculated the HL score using the method recommended for the HLS-EU-Q47 by the HLS-EU project team [40]. These authors found that the HL, from all analysed sociodemographic and economic variables, was associated only with the perceived financial situation. Those who assessed their situation as very good demonstrated the highest HL.The reported pattern of relationships between sociodemographic factors and the level of HL is different in the various studies. However, the most persistent finding in other studies is a significant association between a person’s HL and their level of education. Interestingly, such a relationship was not found in our study. However, the HLS-EU project team reported a low but statistically significant correlation for the Polish population [4]. However, their analysis was based on the survey using the CAPI technique and the use of the standard 47-item HLS-EU questionnaire. It should be recognised that in Polish schools, the curriculum does not focus on the development of health-related knowledge or skills. The lack of any association between the level of education and HL should strengthen the current efforts to include health education in Polish school curricula.As for the consequences, applied multivariate logistic regression models revealed that limited HL, after adjustment for sex, age, and education level, was associated with a lower self-assessment of health status, the prevalence of obesity and disability, less frequently undertaking of physical activity and the lower consumption of fruits and vegetables. Respondents with limited HL had also more frequently been admitted to hospital in the preceding year.The findings of the Polish survey are in line with the results reported by Jordan and Hoebel [27]. They found that higher HL was associated with beneficial health behaviours and that low HL was related to poorer physical and mental health. Tiler et al. [25] reported that there was an inverse association between HL and the prevalence of myocardial infarction among women, diabetes in both sexes and strokes in men. Levin-Zamir et al. [27] also used logistic regression to analyse the relation between HL and self-assessment of health status and with health behaviours, including sun protection, smoking and physical activity. However, the association of HL was statistically significant only with the self-assessment of health. In a study involving 9617 members of a Belgian health insurance fund it was confirmed that low HL was associated with more admissions to one-day clinics, general practitioner home consultations, psychiatric consultations, ambulance transportation and with longer stays in general hospitals [31]. The study undertaken by Garcia-Codina et al. [29] showed that low HL was modestly associated with low levels of physical activity, having self-perceived chronic disorders and not undertaking preventive activities. According to Lorini et al. [12], the HL score calculated from HLS-EU-Q16, was related only with self-perceived health status, and not with the BMI category, doctor’s visits, emergency department admissions, admissions to hospital or access to outpatient specialist care. The study of Amoah [28] on the inhabitants of one region in Ghana confirmed that the level of HL enabled the prediction of health status and wellbeing. Finally, Eronen et al. [40] using the Spearman correlation coefficient, demonstrated that lower HL was associated with lower cognitive status and self-assessment of health, more frequent depressive symptoms and chronic conditions, lower life-space mobility, and physical performance. The association between low HL determined by the HLS-EU-Q16 score and unfavourable health behaviours was also reported for inhabitants of rural areas in Indonesia by Mubarokah [41]. There are many other papers reporting the results of the evaluation of the potential determinants and consequences of limited HL, measured with other versions of the HLS-EU questionnaire, and with other types of instruments. Nonetheless, the discussion presented here has been focused on the results reported by recent studies using the HLS-EU-Q16 tool. The importance of HL is not fully appreciated in Poland. Apart from the activities of the HLS-EU project completed in 2012 [4], there have been no significant attempts to assess the HL of the general population or specific groups of respondents. There are only a few review papers focused on HL available in Polish literature. Furthermore, HL has never been included as a target or an indicator in the initiatives undertaken within the public health domain even in the current National Health Programme for 2016–2020 [42]. It was also not addressed in the Law on Public Health issued in 2015 [43].The results of the current study can have important implications for the provision of health services and public health activities in Poland. Firstly, it appears that about 35% of the general population has limited HL and the high percentage may be an indicator of an inadequate level of health education being provided by the educational system. It may also reflect on the relative weakness of health communications addressed to society. The analysis of potential antecedents showed that young adults, especially pupils or students, and singles, may be at risk of limited HL. These observations justify the recent initiative to introduce a health education programme to the school curriculum in 2021 and justify the reorientation of information strategies employed in health care facilities. To date, older patients have been perceived as the group that requires special attention when providing medical advice and explanation. It seems that health professionals should be advised to provide clearer communications when interacting with young adults. Our research revealed that limited HL is associated with obesity. Such a link supports the inclusion of broader initiatives and interventions to enhance HL to counteract the growing trend towards an overweight and obese society. Furthermore, in health programmes targeting unfavourable health behaviours, e.g. concerning nutritional habits or physical activity, one of the critical objectives should be the development of adequate HL.Interestingly, our study showed also that there is a statistically significant relationship between limited health literacy and hospital admissions. One might expect that hospital admission should be associated with higher HL. However, it is also probable that persons with low HL may be prone to readmissions because they are unable to self-manage their long-term illnesses, and therefore, they are at risk of disease exacerbations. The promotion of the concept of HL-friendly health institutions, including the screening for patients with limited HL, and implementing strategies to enhance the HL of such patients, could be an appropriate initiative to avoid unnecessary hospitalisations.There are several aspects of this study that need to be considered. Firstly, the use of the HLS-EU-Q16 tool is in itself related to certain limitations in the evaluation of potential antecedents and consequences of limited HL. It should be noted that the arbitrary classification of the resulting HLS score to limited and sufficient HL groups may be related to the lower sensitivity in detecting interrelations with the variables characterising the respondents. In this reported study, the CATI technique was applied. Although more and more researchers go beyond the initial technique of direct interviews, it is not clear how the use of CATI or online survey influences the sensitivity of the HLS-EU tools. With appropriate instruction being given to interviewers who connect with the respondents, a lack of response resulting in a missing value could be only assigned if the respondent had a real problem with giving a response. Even with such an approach, the HLS-EU-Q16 score could not be calculated for nearly 16% of the respondents. Finally, the use of the HLS-EU-Q16 tool and the CATI technique does not allow for a full comparison of the obtained results with the first survey assessing HL in Polish society which was undertaken as part of the HLS-EU project. The HL categories established on the basis of the score originating from the response to the 16-item version of the HLS-EU questionnaire are relatively insensitive to options assumed by sociodemographic variables. Among the variables treated in the study as the antecedents of HL, significant associations were confirmed only for age, marital status, and vocational status. However, it was possible to confirm that there were statistically significant relationships between HL and several variables modelled as consequences, including the self-assessment of health, the prevalence of obesity and disability, the intensity of physical activity, the consumption of fruits and vegetables and the number of admissions to hospital in the preceding year. The undertaken analysis reported in this paper showed that limited HL is associated with a less favourable self-assessment of health status, the prevalence of obesity and disability, less favourable health behaviours and making use of health care resources such as hospital admissions more frequently.Conceptualization, M.D.; methodology, M.D.; formal analysis, M.D.; investigation, M.D.; resources, M.D.; data curation, M.D.; writing—original draft preparation, M.D.; writing—review and editing, M.D.; project administration, M.D.; funding acquisition, M.D. The author has read and agreed to the published version of the manuscript.This research was supported by the statutory project No N43/DBS/000050 performed in the Department of Health Promotion and e-Health, Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, Poland.The author thanks John R. Blizzard, a retired UK University Senior Lecturer, Chartered Engineer and Churchill Fellow, for proofreading of the manuscript.The authors declare no conflict of interest.The distribution of responses to individual items included in the European Health Literacy Project (HLS-EU)-Q16 *.* Only relative frequencies (%) were provided in the table due to the fact that total sample n = 1000.The assessment of potential antecedents of limited health literacy (HL) with chi2 test and univariate logistic regression.ap for chi2 independence test, b p for univariate logistic regression with HL as a dependent variable (limited HL vs sufficient HL), * referential categories in the logistic regression models for limited HL.The analysis of potential consequences of limited HL (chi2 independence test and multivariate logistic regression models adjusted for sex, age, and education level).a p for chi2 independence test, b p for multivariate logistic regression with HL as an independent variable (sufficient HL used as a reference category for limited HL), * referential categories in the logistic regression models for limited HL.

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+Background: Previous studies have analyzed the impact of economic crises on adult’s health and lifestyles, but evidence among children and adolescents is limited. The objective of this study was to analyze the impact of the economic crisis on self-perceived health and some risk behaviors in the Spanish adolescent population. Methods: We used data from four waves (2002, 2006, 2010, 2014) of the Health Behavior in School-Aged Children (HBSC) survey in Spain. Separate multilevel logistic and linear regression models were applied for health complaints, self-rated health, life satisfaction, smoking, alcohol consumption, and breakfast skipping. Annual change in Spanish regional unemployment rates was used as a proxy of the economic crisis. An increasing set of control variables were included, consisting of individual, socioeconomic, and family and peer relationships indicators. Median odds ratios were estimated to quantify the cross-region and cross-school variation. Results: Increases in unemployment rates were linked to a higher risk of poorer health and bad habits in the simplest models. The effect was no longer statistically significant when indicators of family and peer relationships were included, suggesting a protective effect against the impact of the economic crisis. Our findings also show that schools had a larger effect on health and lifestyles than regions. Conclusion: The child’s social context—family, peers, school, and region—play an important role on the effects of the economic crisis on health and risk behaviors.The global economic recession initiated at the end of the first decade of the 21st century had important macroeconomic effects in most developed countries. Spain was no exception, with a gross domestic product (GDP) fall of almost 9% between 2008 and 2013, leaving high levels of debt and public deficit. The effects of the crisis quickly shifted to the level of employment. The unemployment rate of the general population rose from 7.9% in 2007 to 26.9% in 2013, with marked differences between regions, and the number of unemployed individuals increased by 4.5 million [1].There is an extensive body of literature focused on analyzing the impact of the economic crisis on the health and lifestyles of the population, with mixed findings [1,2,3]. Evidence suggests that the crisis had a greater effect on the mental health than on the physical health of the population [1,2]. Most studies are based on analyzing the impact on the health of adults, but there is less work focused on children or adolescents.There is a virtuous circle between good childhood health and present and future well-being. Health in childhood and youth can mark future personal, social, and academic development, and difficulties in adolescence can have important consequences in adult life [4,5]. For its part, health risk behaviors include unhealthy lifestyle habits related to nutrition, lack of physical exercise, and consumption of harmful substances (alcohol, tobacco, drugs), which can negatively affect pupils’ school performance and health [6,7].The family is one of the most important determinants of children’s development [8]. In particular, family socio-demographic conditions have a relevant impact on the health and risk behaviors of children and adolescents. The educational level of the parents is related to adolescent lifestyles [9]. Children of parents with lower educational levels have a higher risk of poor school performance and of reporting lower life satisfaction and self-perceived health than children of parents with a university degree [10]. Family wealth also plays a crucial role in the well-being of adolescents and is a potential source of health inequalities. Adolescents from more affluent families show greater satisfaction with their lives than those from less affluent families and feel healthier than those who report that their home has few resources [1,11].The impact of the crisis on health may differ between adults and children. Adolescents spend much of their day in school. Their environment can play an important role in their well-being. Relationships with peers and their families may affect their mental health [12]. Parental communication is one of the key ways in which the family can act as a protective health asset, helping young people to deal with stressful situations or adverse influences. Ease of parental communication and parental support are associated with positive body image, higher self-rated health, higher life satisfaction, and fewer physical and psychological complaints [13,14,15,16]. They are also less likely to participate in aggressive behaviors and substance use [17]. Schools may also have a significant effect on risk behaviors and mental health, both directly through school rules, peer influences, social activities, teacher support, and school connectedness, and indirectly by influencing student-level skills and knowledge [18,19,20].The effects of unemployment on health and lifestyles can occur at both the individual and contextual levels [21]. For children, adult unemployment may have a dual effect. On the negative side, the fact that one or both parents lose their jobs or suffer the impact of the recession may psychologically affect the child (more stress, fear, worry) and significantly reduce family wealth [16,22,23]. On the other hand, children could also benefit, at least in the short term, from their parents’ unemployment situation by being able to spend more time with them, therefore being more available to communicate, help, cook, or control bad habits and influences [3,24]. Previous research on parental employment and youths’ well-being also suggests that parents’ unemployment is associated with young people’s lower well-being [8,16,25,26].Parental unemployment has been found to have unintended consequences on the probability of having bad habits, such as drugs consumption, binge drinking, or smoking. Having an unemployed father has been associated with a positive effect on the probability of binge drinking [27]. The ‘economic stress’ mechanism links substance consumption to psychological reasons [28]. On the contrary, other studies indicate a positive relationship between unhealthy lifestyles and household budget, suggesting a procyclical relationship between macro-economic conditions and risk behaviors [29,30,31].In this context, it is worth exploring the effect of the economic crisis experienced in Spain on children and adolescents. We focus on analyzing the impact on health indicators as well as on lifestyles factors, as the latter might be a mechanism that explains changes in health that have accrued and/or will develop in the long run. The aim of this work was thus to analyze the possible impact of the recession on self-perceived health and some risk behaviors of the adolescent population in Spain, taking into account family socioeconomic variables and contextual factors, and controlling for the school and regional environments.Data were obtained from the Health Behavior in School-Aged Children (HBSC), an international cross-sectional survey supported by the World Health Organization (WHO) aimed at understanding young people’s health-related behaviors, well-being, and developmental contexts [32]. The responses were collected by means of standardized self-completed questionnaires, administered in school classrooms according to standard instructions [33]. We used data from four consecutive HBSC waves (2002, 2006, 2010, and 2014) performed for Spain. Microdata were provided by the Spanish Ministry of Health, Consumption, and Social Welfare [34].The sample comprised 77,651 students aged between 9 and 21 years. 0.47% of the sample (n = 364) were adolescents older than 18 years old, who were still enrolled in secondary education because they repeated one or more school years during their life. The mean age of the sample was 14.35 years (standard deviation (SD): ±2.22) with a balanced representation of boys and girls (49.18% boys and 50.82% girls). The students were enrolled at a total of 1181 educational centers from the 17 Spanish Autonomous Communities (plus two Autonomous Cities). Due to missing values of some of the included variables, the final sample sizes of the conducted models ranged from 53,543 to 56,507.There are two sets of dependent variables, regarding health and lifestyles. Adolescents’ health was measured in three alternative ways, by asking him/her about health complaints, self-rated health status, and life satisfaction (Table 1).
+        Physical and psychological health complaints were measured using the HBSC symptom checklist. Pupils were asked how often in the past 6 months they had experienced somatic (headache, abdominal pain, backache, feeling dizzy) or psychological (feeling low, feeling irritable or bad-tempered, feeling nervous, and having difficulties in getting to sleep) symptoms. The response options for each item ranged from ‘about every day’ to ‘rarely or never’ (5 response options). A composite dichotomous index was created including these eight symptoms, coded as 1 when the child had rarely or never experienced any of the symptoms, and 0 otherwise. Additionally, two separate composite indexes were created for the four physical and psychological complains, following an analogue structure.The HBSC survey includes a question about the child’s self-perceived health, with four possible answers: excellent, good, fair, or poor. We recoded the variable into a dichotomous one, 1 being excellent or good health, and 0 fair or poor health.The survey also includes a 10-point visual analogue life satisfaction scale, where the child was asked to indicate the step of the ladder at which he/she would place his/her life at present (from 0 to 10). The top of the ladder indicates the best possible life and the bottom, the worst.Physical and psychological health complaints were measured using the HBSC symptom checklist. Pupils were asked how often in the past 6 months they had experienced somatic (headache, abdominal pain, backache, feeling dizzy) or psychological (feeling low, feeling irritable or bad-tempered, feeling nervous, and having difficulties in getting to sleep) symptoms. The response options for each item ranged from ‘about every day’ to ‘rarely or never’ (5 response options). A composite dichotomous index was created including these eight symptoms, coded as 1 when the child had rarely or never experienced any of the symptoms, and 0 otherwise. Additionally, two separate composite indexes were created for the four physical and psychological complains, following an analogue structure.The HBSC survey includes a question about the child’s self-perceived health, with four possible answers: excellent, good, fair, or poor. We recoded the variable into a dichotomous one, 1 being excellent or good health, and 0 fair or poor health.The survey also includes a 10-point visual analogue life satisfaction scale, where the child was asked to indicate the step of the ladder at which he/she would place his/her life at present (from 0 to 10). The top of the ladder indicates the best possible life and the bottom, the worst.Three risk behaviors were also analyzed: smoking, frequent alcohol consumption, and absence of breakfast on weekdays. The variables were included individually in a dichotomous form, 1 being the bad habit and 0 the absence of it.Of all the possible macroeconomic measures, we used unemployment as proxy of the economic crisis, as it is the most widely available indicator of economic difficulty, and previous research has shown that fluctuations in employment are more closely associated with short-term changes in health than are other economic indicators [35,36]. Poor and vulnerable members of the population are most sensitive to unemployment, and could be missed by GDP measures. We used as proxy the annual relative changes in the regional unemployment rates for the four years included in the analysis. We also checked the robustness of our findings using the change in unemployment regional rates measured in absolute percentage points. The data were extracted from the Spanish National Institute of Statistics [37].We included several control variables in the models. Besides individual measures such as age and gender, specific socioeconomic variables were employed, as well as variables about parental relationships and conflicts with peers. Socioeconomic measures include parents’ working status (both parents are working), family structure (single versus two-parent households), and family material wealth. The family material wealth was assessed using the Family Affluence Scale (FAS) [33]. A global score was calculated as the sum of the following individual item scores [38,39]: car ownership (No: 0 points; Yes, one: 1 point; Yes, two or more: 2), having one’s own bedroom (No: 0 points; Yes: 1 point), number of computers/laptops at home (None: 0 points; One: 1 point; Two: 2 points; More than two: 3 points), and number of family holidays during the last year (None: 0 points; One: 1 point; Two: 2 points; More than two: 3 points). Using an additive score, the responses were recoded into three groups: low (0–2 points), medium (3–5 points), and high (6–9 points) family-wealth. Several indicators were also included in order to approximate family and peer relationships. Four variables aimed to measure if the child felt understood, supported, beloved, and/or known by his/her parents. Regarding peers, three variables aimed to detect bullying (give or receive) or physical fights.Multilevel regression models were applied, as data were organized at more than one level: individual, school, and region. These models were used to separately estimate the variance between pupils within the same school and region, and the variance between schools and regions. Separated models were performed for the three health outcome variables (symptoms, self-rated health status, and life satisfaction scale) and the three risk behavior variables (tobacco, alcohol consumption, and absence of breakfast), in order to assess the impact of the economic crisis on each of them.Due to the nature of the dependent variables, logistic multilevel regression models were fitted, except for the life satisfaction scale, where linear models were used. The fixed parts of the models are a linear function of individual- and contextual-level determinants. The random parts included three variance components between regions (level 3), schools (level 2), and students (level 1).For each dependent variable, three models were fitted by stepwise regression. Model 1 assessed the association between the outcome variable and individual-level variables (gender, age group) as well as the crisis proxy, to analyze the region- and school-level variance. Model 2 added socioeconomic variables (family wealth, parental work, and family structure) and Model 3 added family and peer relationship indicators (parental relationship and peer conflicts).For the multilevel linear regressions on the vital satisfaction scale, residual intraclass correlation coefficients (ICC) were estimated. To quantify the cross-region and cross-school variation on health outcomes and risk behaviors of the multilevel logistic regressions, we calculated the median odds ratios (MOR) [40]. The MOR quantifies the variation between clusters by comparing two persons from two randomly chosen, different clusters. It allows us to compare between two identical individuals (level 1) that belong to different groups (region and school). In our models, it shows the extent to which the individual probability of declaring good health or a risk behavior is determined by the region where the child lives or the school of attendance.In all models, whether the differences were significant was assessed by using the Wald chi-squared test for each predictor. The analyses were performed using the Stata 14.2 program (StataCorp., College Station, TX, USA).Table 1 and Table 2 provide a summary of the descriptive statistics. Almost half of the sample were boys (49.18%) and reported a high family affluence according to the FAS composite index (49.76%). The prevalence of several socioeconomic and relationship/conflict indicators worsened in 2010: both parents working (68.9% in 2006 versus 66.8% in 2010), biparental familiar structure (82.8% versus 79.14%), physical fights with other children (31.5% versus 33.2%), and parental knowledge (47.4% versus 46.1%) and love (87.6% versus 86.1%).The relative change in the annual regional unemployment rates showed a different pattern over the analyzed years. The regional unemployment rates fell in relative terms by an average of 7.48% between 2005 and 2006 and 7.43% between 2013 and 2014. However, they increased by 12.07% in 2010, with substantial differences among regions. During this year of economic crisis, the unemployment rate increased in all but one region, in a range of between 23.2% and −5.7%.Raw data on life satisfaction shows that it remained at mean levels of 6.87 by 2006 and 2010, improving up to 7.7 points by 2014. Regarding health status, 91.93% of the students reported an excellent or good health status in 2010 (3.56 percentage points more than in 2002). The proportion of students reporting good or very good health (no or few physical or psychological symptoms) dropped from 62.31% in 2006 to 61.41% in 2010 (Table 3).Regarding lifestyles, the prevalence of regular smoking increased slightly between 2006 and 2010, with a deep decrease in 2014. Breakfast during weekdays also showed a deterioration during 2010. By contrast, the prevalence of frequent alcohol consumption decreased two percentage points between 2006 and 2010, and more than halved by 2014.In accordance with the multilevel logistic regression models, girls presented a higher risk of reporting health complaints or a poorer health status compared with boys. Students aged 17 and older showed a higher risk of poor health than younger peers. Individuals living in more affluent households had a significantly higher probability of reporting better health (less health complaints) than those living in more deprived households. Belonging to a two-parent family structure is also related with better health outcomes. However, the fact that both parents have a job seems to have a slight positive effect on vital satisfaction and psychological health, but not on physical health or self-reported global health. The same results were observed when the symptoms were analyzed separately by dividing them into physical and psychological (Supplementary Table S1).The four variables regarding parental support showed a positive correlation with better health and vital satisfaction (especially parental knowledge, with odds ratios between 0.36 and 1.59). By contrast, being involved in fights and bullying other peers were linked to a lower probability of enjoying good health. Being a victim of bullying by peers was a strong and significant risk factor for worse health and vital satisfaction (Table 4 and Table 5).The changes in regional unemployment were linked to a worse health status at Models 1 and 2. However, the economic crisis proxy was not statistically significant when incorporated in the most complex models that included family and peers relationships indicators (Model 3). The effect only remained significant at a 10% significance level for vital satisfaction. Conclusions of the analyses were robust when the change in unemployment regional rates was measured in absolute percentage points.In the multilevel models on lifestyles, the effect of gender indicates that girls are more likely to smoke and skip breakfast, but are less likely to consume alcohol than boys. Being 17 and older is associated with a higher probability for each of the risk behaviors considered. Family affluence decreases the risk of smoking and missing breakfast but does not have an effect on alcohol consumption (Model 2). The variables related with a better communication with parents (Model 3) were significantly associated with good lifestyles. By contrast, the variables regarding fights or bullying peers presented a higher risk of following these three unhealthy habits. The effect of the economic crisis remained statistically significant in all models for smoking and absence of breakfast, suggesting a positive association between increases in unemployment rate and higher risk of that bad habit. However, the size of the effect was considerably reduced when controlling for family and peer relationship indicators. The effect on alcohol consumption was no longer significant when such covariates were added.Findings of random intercepts suggest that schools had a higher effect on health and lifestyles than regions. After adjusting for family and peer relationship indicators (Model 3), all intraclass school and region correlation coefficients (ICC and MOR) were slightly reduced in the regressions on health outcomes and smoking. MORs indicate that the school level explained between 25% and 38% of the total variance for health symptoms. School-level variance was larger for frequent alcohol consumption (MOR of 2.24–2.35) than for the other dependent variables, suggesting that the school environment has the largest effect on alcohol consumption.According to our results, it seems that the economic crisis is inversely related to good health and life satisfaction when controlling for individual and socioeconomic variables. However, the link between higher regional unemployment and poorer health disappears when family and peer relationships indicators are considered, suggesting a protective effect against the negative impact of the economic crisis. A similar result was found for frequent alcohol consumption. The observed detrimental effect of the economic crisis on life satisfaction, smoking, and absence of breakfast remained, but was substantially reduced when controlling for these indicators. A possible explanation for this pattern could be that tobacco and food consumption are more linked to the family income than alcohol, which is an unhealthy lifestyle that could depend to a larger extent on friends and the school context. However, this result should be considered with caution, since we were only able to analyze this alcohol variable, but not others like binge drinking.The second relevant finding is that the school environment has an influence on health outcomes and lifestyles, especially on alcohol consumption. We found that intraclass correlation decreased for health outcomes and smoking after controlling for family and peer relationship indicators, suggesting that at least some of the identified region and school-level variance is due to parental and peer influences.The present study contributes to the existing literature by expanding the research on the protective effect of the family and good relationships with other children against the economic crisis than hindered self-reported health and healthy lifestyles among children and adolescents. The HBSC survey has been widely used to analyze the effect of socioeconomic determinants on self-perceived health and well-being among young people [22,29,33,41,42,43]. However, to our knowledge, this is the first time that it was used to measure the potential impact of the economic crisis on health and lifestyles, jointly considering the different environment influence levels: individuals, families, schools, and regions.Previous studies on the detrimental health effects of an economic recession on teenagers highlighted a complex causal chain between economic, social, and individual relationships [44]. Young people’s health and well-being decline was found to be anchored to parents’ unemployment [8,22,23]. The effects of both paternal and maternal job losses on child health have been associated with declines in child health in the short-run. Paternal job loss was associated with increases in depression and anxiety, while maternal job loss reduced the incidence of infectious illnesses [24]. At a macroeconomic level, higher rates of precarious employment in a region have a negative effect on people’s mental health, and likewise, lower health spending per capita [45]. However, according to other studies, the negative shift of the recent recession on the employment market has not affected adolescents’ psychological health complaints [44].Social protection and cultural importance of families might protect adolescents from economic downturns [44]. Previous studies have demonstrated the existence of environmental influences (family, school, and friends) on the subjective health and mental health of adolescents [42,46,47,48]. Parents, teachers, and family were sources of support most consistently found to be protective against depression in children and adolescents, whereas findings were less consistent for support from friends [12]. They have been presented as a protective factor of adolescents’ well-being against adversity caused by parental unemployment [49]. Other protective factors are family autonomy and control, family and school sense of belonging, and social support at home and school [50]. School is an ideal place to improve the health and well-being of today’s children and tomorrow’s adults, but it can also be a source of anxiety and bad behaviors. In line with other studies, we have shown that health risk behaviors have relatively higher school-level variance compared to other health outcomes, although the causal mechanisms are difficult to be established [18,19]. Multilevel analyses performed in Wales using the HBSC survey have revealed that family relationships also protect from harmful substance use [42,51].Our findings should be interpreted with caution because of several methodological limitations. The use of self-reported data on health status and socioeconomic welfare may be affected by the adolescents’ subjective perception. The cross-sectional design of the study limits causal inference. Although we used four consecutive waves of the same survey, with disaggregated microdata, no temporal follow-up of the same children could be done. Other limitation is related to the lack of homogeneous questions among the four waves, hindering us from using other relevant variables such as the urban/rural habitat, the parents’ educational level, or the consumption of drugs. Also, available data prevented us from using a detailed measure of binge drinking. Lastly, other proxies of the economic crisis could have been used, and some effects of the economic crisis on health may not be observable in the short term but in a longer period of time.Despite these limitations, this study presents a new effort to better capture the effect of the economic crisis on adolescents’ health, life satisfaction, and risk behaviors, pointing out the importance of the family socioeconomic position and parental/peer relationships. Childhood is of particular interest for public policies, because of its special vulnerability and because the consequences of childhood deprivation may be perdurable throughout life [52]. The effects of the crises depend to a large extent on social protection policies, on the safety net of the Welfare State, and on the structuring of social and family networks [1].Therefore, some policy implications derived from this work are related to the importance of maintaining strong active employment policies, as well as social policies focused on single-parent families and less affluent homes. Also, attention should be paid to reducing inequalities between schools, which can be a focus of poor health and unhealthy habits for life. Lastly, given the importance of the child’s social environment, efforts should be made to enhance family communication and support and to avoid bullying.Economic crises may have devastated aggregate and individual effects on the population health and wellbeing. Our results confirm that the increase in unemployment experienced in Spain during the recession may have worsened adolescents’ health status and lifestyles. However, the child’s social network seems to play an important protective role against the effects of the economic crisis. The conclusions derived from the work may be relevant to provide more evidence on the importance of designing and implementing public policies that try to alleviate the negative consequences on the well-being of present and future populations, preventing social inequalities and social exclusion. In the future, it would be desirable to make further progress in understanding the short-, medium-, and long-term health consequences of this recent economic crisis on the young population. Also, it may be desirable to examine the relationship between the school context and wider community processes.The following are available online at https://www.mdpi.com/1660-4601/17/2/643/s1, Table S1: Results from the multilevel logistic regressions on health complaints (odds ratios). Conceptualization, N.Z. and L.V.; formal analysis, N.Z.; writing—original draft preparation, N.Z.; writing—review and editing, L.V. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors would like to thank the Ministry of Health, Consumer Affairs, and Social Welfare as well as the University of Seville for providing microdata from the HBSC surveys. We also want to thank Patricia Barber Pérez and Concepción Moreno-Maldonado for their help with the initial database and Juan Oliva Moreno for his useful comments to this article.The authors declare no conflict of interest.Variables included in the analyses.Descriptive analysis of the independent variables.Descriptive analysis of the dependent variables.Results from the multilevel logistic regressions on health complaints, self-rated health, and life satisfaction (odds ratios/coefficients).Standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. The models include dummies for the missing values of relationship/conflict indicators. Number of groups: 18 regions; 1,181 schools. Odds ratios and median odds ratios (MOR) for the logistic regression models and coefficients and intraclass correlation coefficients (ICC) for the linear models.Results from the multilevel logistic regressions on lifestyle habits (odds ratios).Standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. The models include dummies for missing values of the categorical contextual variables. Number of groups: 18 regions; 1181 schools.

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+The hydrophobicity and anti-fouling properties of materials have important application value in industrial and agricultural production and people’s daily life. To study the relationship between the unit width L0 of the parabolic hydrophobic material and the hydrophobicity and anti-fouling properties, the rough surface structure of the parabolic with different widths was prepared by grinding with different SiC sandpapers, and further, to obtain hydrophobic materials through chemical oxidation and chemical etching, and modification with stearic acid (SA). The morphology, surface wetting and anti-fouling properties of the modified materials were characterized by SEM and contact angle measurement. The oil–water separation performance and self-cleaning performance of the materials were explored. The surface of the modified copper sheet forms a rough structure similar to a paraboloid. When ground with 1500 grit SiC sandpaper, it is more conducive to increase the hydrophobicity of the copper sheet surface and increase the contact angle of water droplets on the copper surface. Additionally, the self-cleaning and anti-fouling experiments showed that as L0 decreases, copper sheets were less able to stick to foreign things such as soil, and the better the self-cleaning and anti-fouling performance was. Based on the oil–water separation experiment of copper mesh, the lower L0 has a higher oil–water separation efficiency. The results showed that material with parabolic morphology has great self-cleaning, anti-fouling, and oil–water separation performance. The smaller the L0 was, the larger the contact angle and the better hydrophobic performance and self-cleaning performance were.Infiltration in life can be seen everywhere, for example, the excess energy consumed by a ship sailing due to hydraulic friction [1]. Interest in super-hydrophobic surfaces has increased in recent years [2,3,4,5,6]. Hydrophobicity and stain resistance are widely used in many areas such as anti-biofouling surfaces in a marine environment [7,8,9,10], fluid drag reduction [11,12], anti-contamination surfaces of windows for buildings and automobiles [13,14,15], microfluid [16,17], and many others. Therefore, studying hydrophobicity and stain resistance is particularly important in industry, agriculture, and people’s daily life.To obtain excellent hydrophobic and anti-fouling materials, scholars constantly explore the prediction theory of the superhydrophobic model and the preparation technology. Nishino et al. [18] found that after a low surface energy modification on a smooth solid surface, the maximum contact angle (CA) did not exceed 120°. Therefore, the construction of the surface microtopography has a great influence on the hydrophobic surfaces. In terms of model theory prediction, by analyzing the microstructure of natural super-hydrophobic surface examples, based on Young’s theory [19], both the classical Wenzel model [20] and the Cassie–Baxter model [21] consider that the roughness of the solid surface can enhance the hydrophobicity of the surface. However, both the Wenzel model and the Cassie–Baxter model are only suitable for the case where the droplets are sufficiently large relative to the surface convex structure. In addition, Young’s equation, the Wenzel model and the Cassie–Baxter model provided a basis for the subsequent proposed hydrophobicity model. Shi et al. [22] established an energy model based on the minimum Gibbs free energy. Salvadori et al. [23] designed a periodic micropore array model. Eyal Bittoun and Abraham Marmur [24] constructed different morphologies of rough surfaces: a cylinder, a truncated cone, and a hemisphere.After the investigation of the microstructure deeply, scholars found the key factors affecting the contact angle are the aspect ratio h/R of the microstructure, a/b ratio of the column width, and the multiscale microstructure. Nosonovsky [25] studied the relationship between the surface roughness and the wetting property of the hemispherically topped cylindrical structure, conical structure, and pyramidal structure, finally, it was found that as the aspect ratio h/r increased, both hemispherically topped cylindrical structure and pyramidal structure can reach the maximum contact angle. For the column width ratio a/b, Yamamoto and Ogata [26] thought that the microscopic rough surfaces were pillar surfaces and did not consider the case where the protrusive surfaces were curved. Zhang [27] constructed the top of the mastoid, which was a curved structure, and found that the microstructure parameters and the unit width of the mastoid were the key factors to affect the contact angle. These microstructures are used to improve the hydrophobicity of materials. However, previous studies have lacked an in-depth exploration of the prediction of hydrophobicity and stain resistance in the establishment of proprietary spherical or parabolic models.In terms of material preparation, in recent years, inspired by surface structures like the lotus leaf self-cleaning surface and mosquito compound eyes [28], a series of superhydrophobic materials were prepared and used for oil–water separation. Some of the most used methods consist of the surface modification of metallic meshes and fabrics, with diverse techniques such as hydrothermal methods [29], leaching [30], electrochemical anodization [31], solution immersion [32,33], and thermal polymerization [34]. Li has done a series of studies on oil–water separation materials in harsh conditions [35], such as fabricating superhydrophobic CS and silica overlap coated meshes for efficient oil–water separation. Xue et al. [36] reported superhydrophobic polyester fabrics obtained through alkali etching, chemical vapor deposition, and ultraviolet light initiated click chemistry. Unfortunately, the component toxic fluorinated materials may cause great harm to the environment. Li et al. [37] suggest an innovative biomimetic way for the recycling of valuable inks or reactants, especially in environmental protection, chemical analyses, and printing processes. These materials have a great oil–water separation effect, however, the material’s anti-fouling performance was not considered.Anti-fouling is a significant feature of hydrophobic materials. For example, Liu et al. [38] have developed a superhydrophobic and antifouling performance PET fabric, which still maintains great performance after being recycled. Li et al. [39] have demonstrated a novel electrostatic manipulation method to control the jumping of water drop in varied directions. This research would provide new opportunities to improve self-cleaning and reduce icing. Wang et al. proposed a dynamic, time-varying cleaning method based on superhydrophobic surfaces [40]. However, some shortcomings cannot be ignored, including long preparation process and expensive cost. Copper meshes have attracted widespread attention for their mechanical strength, low density, high specific surfaces, and environmentally friendliness [41,42]. Therefore, the technique used to etch a specific shape on the copper surface and then apply it as a hydrophobic and self-cleaning material was the most interesting issue.In this paper, parabolic structure materials with different unit widths of the parabolic (L0) can be obtained by grinding, chemical etching, oxidation, and modifying. Then, the surface of the materials was characterized by scanning electron microscopy (SEM) and contact angle measurements. Finally, the copper mesh and copper sheets were applied to oil–water separation, anti-fouling, and self-cleaning experiments, which showed that the parabolic morphology has great hydrophobic and anti-fouling properties. It was shown that the parabolic morphology materials had certain application value in environmental protection.FEI Quanta 200 SEM (FEI company, Hillsboro, OR, USA), SL200KS contact angle meter (American Kono Industrial Co. Ltd., Seattle, WA, USA).Copper meshes (200 meshes) were purchased from Shenyang Copper Network Co., Ltd. (Shenyang, China). Copper sheets were purchased from Tianjin Shengao Chemical Reagent Co., Ltd. (Tianjin, China). Acetone (purity > 99%), benzene (purity > 99%), ethanol (purity = 99.5%), stearic acid (SA), FeCl3 (35 wt %) (purity > 98%), H2O2 (30 wt %), and kaolin (purity > 99%) were purchased from Tianjin Kemiou Chemical Reagent Co., Ltd. (Tianjin, China). SiC sandpapers (320, 400, 600, 800, 1000, 1200, and 1500 grit) were purchased from Shanghai Ruihan Vision Co., Ltd. (Shanghai, China). The experimental water was deionized water. All other chemicals were analytical-grade reagents.Copper meshes (200 meshes) (4 cm × 4 cm) and copper sheets (2 cm × 4 cm) were placed in a beaker and ultrasonically cleaned in acetone, ethanol and deionized water for 10 min to remove oil and inorganic impurities on the surface. To achieve different unit width of copper meshes and copper sheets surface by mechanical abrasion, 320, 400, 600, 800, 1000, 1200, and 1500 grit SiC sandpaper were used to grind 20 times horizontally so that the scratches were aligned parallel to each other. The copper meshes and copper sheet samples were washed successively with absolute ethanol and deionized water and air-dried at room temperature. The cleaned copper meshes were placed in a well-prepared 35% FeCl3 solution and ultrasonically etched for 20 min with an ultrasonic cleaner; the etched copper meshes were placed in 30% H2O2 and oxidized by an ultrasonic cleaner for 3 min. The copper meshes were immersed in a 10 mol/L ethanolic solution of SA (1:3 refers to the volume ratio of ethanol to water) at 60 °C for 24 h. The cleaned copper sheets were immersed in a 10 mol/L ethanolic solution of SA (1:3 refers to the volume ratio of ethanol to water) at 60 °C for 30 min. The modified copper meshes and copper sheets samples were washed successively with absolute ethanol and deionized water and air-dried at room temperature.The water contact angles at ambient temperatures using an SL200KS contact angle meter. The test steps are as follows: Firstly, click the moving image button in the upper right corner of the interface. Then, place the sample to be tested on the stage, 3 μL liquid is extracted from the microsyringe and fixed above the sample, then turn the knob on behind the base of the camera, adjust the distance from the camera to the stage to make the image clearest. Subsequently, the volume of the test water droplets approximately 3 µL squeezed out from the microsyringe, in this time, a clear small droplet dropping from the syringe. Finally, keep the droplet on the sample, click the freeze image button in the upper right corner of the interface to save the picture, press the angle of the measurement button, and calculate the contact angle. At least three parallel positions on the surface were measured to obtain average contact angle values.An oil–water mixture of benzene–water was used for the separation experiments. For convenience, deionized water was stained with methylene blue. Oils were stained with Sudan I. Oils and deionized water was mixed at a volume ratio of 1:1, respectively. The oil–water separation performance of the copper meshes was determined by the gravity-driven oil–water separation test.A red suspension of kaolin-Rhodamine B was formed by a mixture between 15 g kaolin and rhodamine B solution for 30 min. Each sample was weighed by high precision balance and recorded as initial value M0. The copper sheets were immersed in the red suspension of the uniformly mixed kaolin-Rhodamine B. After soaking for 3 s, the copper sheets were placed obliquely to ensure that the angle with the horizontal plane was 45°. Finally, the copper samples were successively dried in air at room temperature and samples with soil were weighed again as Mx. The difference ΔM was the mass of the contaminant to which the sample surface adhered.To better observe the microscopic morphology of the surface of the copper sheets, it was necessary to carry out gold pretreatment on the surface of the sample before the test to enhance the conductivity of the sample and then fix the sample on the sample stage to observe the test. The operation needs to be done in a vacuum environment. The microscopic morphologies of the surface of the copper sheets after grinding were observed by SEM.Figure 1a–c showed that the copper sheets were ground with 320, 800, and 1500 grit SiC sandpapers, respectively. It can be seen via a microscope that the surface of copper sheets becomes rough. As can be seen from Figure 1, with the grit of the sandpaper increased, the unit width of the parabolic had a significant change. Figure 1a–c showed the different L0 were 3.3 μm, 2.4 μm, and 1.6 μm, respectively.The contact angle refers to the wetting property of water droplets on a solid surface. For hydrophilic surfaces, the droplets wet the surface easily and spread out. The contact angle of the water droplets is less than 90°. However, for hydrophobic surfaces, the droplets were not easily spread and appeared spherical on the surface, the contact angle of the water droplets is greater than 90° [43]. It is generally believed that as the contact angle increases, the hydrophobic property improves. Therefore, the contact angle is an important index to reveal hydrophobic and super-hydrophobic properties [44,45,46,47].The wetting behaviors of water on the as-prepared copper sheets were evaluated by the contact angle measurement. The water contact angles of the copper sheets with the different unit width were shown in Figure 2. Figure 2a–c and Figure 2d–f were the CAs of copper sheets with unit width L0 3.3 μm, 2.4 μm, and 1.6 μm, respectively. It can be seen from Figure 2a–c, the unmodified with SA copper sheets were hydrophilic and the CAs of the copper sheets surface were 68.7°, 72.5°, and 82.4°, respectively, which indicated that as the L0 of the copper sheets decreased, the CAs increased. The results of Figure 2 agree with the results from Shi et al. [22], who used different PMMA samples with convex width analytical methods.In Figure 2d–f, the CAs of the as-prepared copper sheets that were modified with SA were measured to be 94.5°, 100.2°, and 110.5°, respectively, which showed that the copper sheets became a hydrophobic surface after modification with SA [48] and it was consistent with the research of Gui-Hua et al. [49]. It can be seen that as the L0 of copper sheets modified with SA decreased, the CAs increased.To better illustrate the contact properties of water droplets on the copper sheets, all the contact angles were listed in Table 1.From Table 1, the CA of the copper sheet modified with SA was always bigger than that of unmodified with SA. That was due to the low surface energy being a key factor in achieving superhydrophobicity [43]. The surface free energy can affect the value of the contact angle; the smaller the surface free energy is, the larger the contact angle is.Copper meshes can be obtained by grinding 320, 800, and 1500 grit SiC sandpaper, etching with 35% FeCl3, oxidation with 30% H2O2 solution, and modification with SA. Previous studies have shown that using SA as a modifier can form a super-hydrophobic membrane surface on the surface of the materials [50,51,52].To understand the separation efficiency of the different unit width of the parabolic L0 of copper meshes surface for oil–water mixtures more intuitively, the oil–water separation experiment was carried out. The process is as follows: To completely cover the beaker mouth, the as-prepared copper meshes that were trimmed into dimensions of 4 cm × 4 cm were fixed over the beaker, and then the small beaker was placed in the center of the large petri dish. The volume of deionized water and benzene used for the experiments were both 6 mL. After shaking the mixture of oil and water in the syringe, then gradually squeezed the syringe and slowly dripped the mixture from the needle to the membranes.A device diagram of the oil–water separation test is shown in Figure 3a. The as-prepared copper meshes completely covered the beaker mouth to prevent deionized water from entering the beaker from other places. The separation experimental processes of benzene–water are shown in Figure 3b. The density of benzene was less than water and water passed first through the syringe and then flowed into the membranes. With the accumulation of deionized water on the copper mesh surface, it can be found that water droplets gradually flowed out from the edge of the copper mesh and did not penetrate the copper mesh into the small beaker. However, benzene passed through the deionized water, reached the surface of the membranes, and flowed into the beaker quickly, as shown in Figure 3c. The process of oil–water separation in the whole process was approximately 3 min. Figure 3d showed that after completion of the experiment, there was almost no blue residue on the membranes by pouring the water above the membranes into a large petri dish.According to the above methods, the mixtures of benzene and deionized water were separated by the oil–water separation experiment. When the separation process was completed, the oils in the beaker were poured into a measuring cylinder and the volumes of oils were measured after separation. It was found that the volumes of benzene after separation were approximately 5.1 mL, 5.3 mL, and 5.6 mL, respectively. After separation of oil and water, according to the amount of oil passing through the membranes and the separation efficiency, η (%), was calculated by Equation (1).
+        (1)η=VtV0×100%,
+        where V0 is the benzene mass of the original and Vt is the benzene mass after separation. The results obtained are shown in Figure 4.The oil–water separation efficiency of the three different L0 copper mesh surfaces were measured. From Figure 4, the separation efficiency of benzene was 85%, 89%, and 94%. It can be seen that due to the different etching methods of copper meshes, the separation efficiency was different [53,54]. It was shown that with a decrease in L0, the separation efficiency became higher.To understand the self-cleaning properties of the untreated and as-prepared copper sheets more intuitively. The copper sheets were immersed in the red suspension of the uniformly mixed kaolin-Rhodamine B. The kaolin adhesion to the surface of copper sheets were observed by SEM. Figure 5 and Figure 6 showed the self-cleaning performance of soil on copper sheets with or without modification with SA. Figure 5a–c and Figure 5d–f were the copper sheets that were ground with 320, 800, and 1500 grit SiC sandpapers, respectively. As the L0 of the copper sheet surfaces decreased, the amount of kaolin gradually decreased, which indicates that copper sheets had better self-cleaning properties.Compared to Figure 6a,b, it can be seen that there was a significant change in the copper sheet surface. It was obvious that the contaminant on the modified copper sheets was significantly reduced, indicating that the copper sheets modified with SA had the stronger self-cleaning ability.To express quantitatively the anti-fouling properties of copper sheets surface of the different L0. The copper sheets ground with different grit sandpapers were immersed in the red suspension of the uniformly mixed kaolin-Rhodamine B.The amount of kaolin adhered to the surface of unmodified and modified with SA copper sheets with different L0 was shown in Figure 7. It can be seen that as the sandpaper grit of ground copper sheets increased, the unit width L0 of the parabolic gradually decreased, and the amount of adsorbed kaolin on the copper sheets tended to decrease. In Figure 7, the adhered kaolin of the copper sheets modified with SA decreased. It was possible that as the surface energy of the copper sheets modified with SA decreased, the contact angle increased, the adhesion ability of the kaolin was lowered, and the stronger self-cleaning performance was.In Figure 7, it can be seen that as the L0 on the copper sheets surface gradually decreased, the adhesion of kaolin to the copper sheets decreased. It can be seen that with a decrease of L0, the contact angle became higher and so was the self-cleaning. However, the surface adsorption capacity of the modified copper sheet was significantly less than that of the unmodified.The unit width L0 of the parabolic on the copper sheet decreased gradually, the contact angle increased gradually, the amount of adsorption of the kaolin reduced gradually. The self-cleaning performance was gradually enhanced. In summary, there was a negative correlation between the reduction of L0 and self-cleaning performance.In summary, by controlling grinding, chemical etching, oxidation, and modifying conditions, the parabolic structure can be obtained on the surface of the copper sheets and copper mesh. Copper mesh and copper sheets were used in oil–water separation, anti-fouling, and self-cleaning experiments, which showed that the parabolic morphology has great hydrophobic and anti-fouling properties.The unit width L0 of the parabolic ground with 320, 800, and 1500 grit SiC sandpapers was 3.3 μm, 2.4 μm, and 1.6 μm, respectively, and the static contact angles modified with SA were 94.5°, 100.2°, and 110.5°. The oil–water separation efficiency of the copper meshes were 85%, 89%, and 94%, respectively.Experimental results showed that the smaller the L0, the larger the contact angle, the better the hydrophobic performance, the higher the oil–water separation efficiency, and the better the self-cleaning performance. The unit width of the parabolic L0 was reduced and the hydrophobicity and the anti-fouling property were more easily realized.The change of L0 can reflect the change in contact angle. It can be used as a significant indicator of hydrophobicity, self-cleaning, and oil–water separation efficiency in predicting the hydrophobicity and antifouling of materials.Conceptualization, Y.L.; data curation, Y.C.; funding acquisition, S.Y.; investigation, Y.L.; methodology, Y.L.; project administration, S.Y.; software, D.Z.; validation, Y.C.; visualization, D.Z.; writing—original draft, Y.L.; writing—review and editing, S.Y. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Key Research and Development Program of China (No. 2016YFC0400701); the National Natural Science Foundation of China (No. 41672224, No. 41977163 and No. 41807457); the Provincial Natural Science Foundation of Shaanxi Province, China (No. 2019JM-428 and No. 2019JQ-664).The authors declare no conflict of interest.Copper sheets morphology under SEM. (a) Ground with 320 grit SiC sandpaper; (b) ground with 800 grit SiC sandpaper; (c) ground with 1500 grit SiC sandpaper.Wettability of water droplets on the surface of the copper sheets. (a,d) The contact angle (CA) of L0 = 3.3μm; (b,e) the CA of L0 = 2.4 μm; (c,f) the CA of L0 = 1.6 μm.Separation effect diagram of oil–water mixture using modified copper meshes: (a) separation of preparation; (b) separation begins; (c) in separation; (d) end of separation.Results of the separation efficiency of copper meshes. (a) Ground with 320 grit SiC sandpaper; (b) ground with 800 grit SiC sandpaper; (c) ground with 1500 grit SiC sandpaper.The self-cleaning effect diagram of the copper sheets surface. (a,d) Copper sheet of L0 = 3.3 μm; (b,e) copper sheet of L0 = 2.4 μm; (c,f) copper sheet of L0 = 1.6 μm.SEM image of self-cleaning on copper sheet surfaces: (a) unmodified with stearic acid (SA); (b) modified with SA.The self-cleaning performance of copper sheets ground with different grit SiC sandpapers.Water contact angles of different copper sheets.

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+The contradiction between industrial development and ecological environment pressure has been becoming progressively severe. Under this circumstance, more attention has been paid to the balance between industrial economic development and environmental deterioration and resource consumption. Thus, this study takes the development of industry and ecological environment change as an interactive system consideration, and comprehensively evaluates the changes of the industrial–environment system on resilience perspective with innovation. Accordingly, this paper establishes a comprehensive evaluation model. The Environmental Performance Index (EPI) and Industrial Structure Entropy (ISE) were applied to analyze the current environment pressure and industrial conditions. Then, the catastrophe theory was used to evaluate the reasonably established index system for the impact of various factors in the industrial–environment system on the resilience change. Next, the adaptive cycle model was used to analyze the evaluation results and reveals the dynamic change law of the system in the resilience range. Finally, Chengdu was selected as the research area to verify the validity of the whole study. It was found that the resilient change process of Chengdu industry–environmental system accord with the four-stage theory of adaptive cycle model. The resilient level of the city was also improved during the cycle. The result of the study can be useful to future plans and decisions. What is more, understanding the characteristics of each stage will be helpful to determine the reasonable implementation time of each key factor and improve its feedback ability.The indispensable industrial activities in the process of economic development are directly reshaping the Earth’s environmental system [1,2]. Unhealthy industrial development modes will cause serious damage to the ecological environment, such as climate, soil, and water quality. In the past few decades, the trade-off between industrial development and environmental protection has attracted much more attention than before. The research of sustainable development management has also increased [3,4]. Reckless resource development and pollution discharge behavior has already sounded the alarm for the safety of environmental systems for human survival [5,6]. However, in order to achieve stable and rapid economic development, this unreasonable, fast-growing industrial economy pattern still exists in China. Since the reform and opening-up policy in the late 1970s, China’s rapidly-developing industries are over-reliant on energy and resource inputs and production capacity expansion [7]. Thus, China’s industry is developing into a huge source of pollutant emissions [8], which is a contradiction that urgently needs to be solved in development.Till now, there have been many cross-over studies on industrial development and ecological environment protection. Scholars have also paid more attention to the sustainable development of the industry and environment systems from pilot studies of the environmental impact in the process of resource development. In the process of studying the relationship between industry and environment, many theories have been introduced, including resource curse theory [9], inverted U-shaped environmental Kuznets curve [10], and resilience theory [11].The concept of resilience has been increasingly introduced into current industry–environmental system research, and has been a hot topic in many studies. For instance, Industrial Symbiosis (IS) [12,13,14], Eco-Industrial Park (EIP) [15,16], Social–Ecological System [17,18,19], and resource consumption [19,20]. These studies have gradually referred to the application of resilience trajectories to explore the interaction between regional industries and ecosystems. Resilience theory can provide a more efficient way to assess the dynamic change process with system balance and adaptability [20]. It can be used to solve the coordinated development problem between industry and environment through studying the resilient change mode of industry–environmental system under continuous mutual interference. But it has not yet received enough attention to consider the resilient relationship between industry development and environmental protection as an interactive whole system at present. Therefore, under these new challenges, this study focuses on exploring the dynamic resilience changes of the industry–environmental coupling system, and contributing to policy changes, industrial adjustment, and strategy formulation.To analyze the dynamic resilient changes of the coupling systems under a series of external disturbances, such as environmental resource consumption, policy changes, and industrial structure adjustment, a new comprehensive evaluation method is proposed. Specifically, this paper established an evaluation index system of the industrial activities and ecological environment. Then, Environmental Performance Index (EPI) and Industrial Structure Entropy (ISE) were applied to analyze the current environment pressure and industrial conditions. The data obtained by the two calculation methods helped to initially analyze the changing trend of industry and environment, and will also serve as the data source for further operation of the evaluation model to ensure the accuracy of the evaluation results. Next, the catastrophe theory was used to evaluate the reasonably established index system of the impact of various factors in the industrial–environment system on the resilience change. The Catastrophe Progression method controlled the subjectivity of the evaluation by uncertain weight, making the evaluation results more scientific and objective. Finally, the adaptive cycle model was used to analyze the evaluation results. The characteristics of resilience dynamics conveyed by the four-phase adaptive cycle, namely exploitation, conservation, release, and reorganization [21,22], reveal the dynamic change law of the system in the resilience range. The research goals were as below:(1)Evaluate environmental pollution, resource consuming, and industrial adjustment in a quantitative way, and give the pressure levels of different indexes in industrial–environment system. Identify resilience changing curve of industrial activities sub-system and environment subsystem by using resilience quantitative and analyze the coupled system adaptive ability.(2)The validity of the evaluation model is verified by an empirical case. The results of the study provide guidance for the sustainable development of Chengdu and provide decision-making basis for promoting industrial development and maintaining economic and ecological balance.(3)Master the resilient change law of the industry–environmental system, discuss and understand the characteristics of different stages, and explore the appropriate implementation cycle and feedback effects of various key indicators. In the period of industrial transformation and development of various cities, it contributes to policy changes, industrial adjustment, and strategy formulation.Evaluate environmental pollution, resource consuming, and industrial adjustment in a quantitative way, and give the pressure levels of different indexes in industrial–environment system. Identify resilience changing curve of industrial activities sub-system and environment subsystem by using resilience quantitative and analyze the coupled system adaptive ability.The validity of the evaluation model is verified by an empirical case. The results of the study provide guidance for the sustainable development of Chengdu and provide decision-making basis for promoting industrial development and maintaining economic and ecological balance.Master the resilient change law of the industry–environmental system, discuss and understand the characteristics of different stages, and explore the appropriate implementation cycle and feedback effects of various key indicators. In the period of industrial transformation and development of various cities, it contributes to policy changes, industrial adjustment, and strategy formulation.The novelty of this study is outlined as follows: (1) Innovatively integrate the two seemingly independent development systems of industrial activities and environmental changes as a coupled system, and integrate the idea of resilience to research the resilient change process of the coupling system under the interaction; (2) a comprehensive evaluation model was established, which combined a variety of methods to reveal the dynamic change law of ecological environment caused by continuous industrial activities disturbances.In general, the purpose of this study is to seek a new way for the sustainable development of the industry–environmental system, which can play an essential role in ensuring coordinated development between industrial economic development and ecological environmental protection.The remainder of this paper is as follows: Section 2 describes the main problems in industry–environmental system. Section 3 describes approaches of the comprehensive evaluation framework, including the comprehensive evaluation indicators, catastrophe theory, and the adaptive cycle model. Following that, Section 4 provides a case study to validate the availability and applicability of the methods. The final Section 5 gives the conclusions and future research directions.As one of the important means to promote the rapid development of national economy, industry is often the first choice. Therefore, resource depletion and potential environmental damage have become inevitable. Because of this, many scholars began to pay attention to the study of industry pollution. Terao put forward the concept of “development and environment” and discussed the relationship between industrial policy and industrial pollution control in order to reduce the harm of heavy industrial pollution [23]. In China, the study of carbon emissions from pollution industries has sprung up like bamboo shoots [24]. With the acceleration of industrial development in major countries, the concepts of “green industry” [25] and “ecological industry” [26] emerge as the eras require in order to alleviate the severe situation of dual superposition of world economic crisis and environmental crisis. Due to various uncertain factors and dynamic changes in industrial activities, the environmental problems caused by them have not been completely solved, so there are more and more cross-studies on industrial activities and environmental protection. Recently, some scholars have tried to embed industrial activities in and confined by the environmental system and the resources it provides in order to analyze the interaction between them [27]. Thus, how to combine the dynamic system of industrial activities with ecological environment change has become the focus of current research.In order to reduce the limitation of resources and environment, many explorations have been made on the sustainable development path of industrial activities and ecological environment. These extensive research topics cover low-carbon technology and circular economy [28,29], green utilization of natural resources [30], environmental health appeals [31], identification of major pollution sources in industrial development [32], sustainable resource transformation [33,34], industry–environmental policies identification [35], resilience transitions [10,36], and so on. The methods applied in these research topics involved index evaluation, economic network analysis, life cycle analysis, and model simulation. Among these studies, the concept of resilience evaluation was gradually borrowed to account for the adaptive capacity of the coupled systems. Initially, scholars tried to use the concept of resilience to evaluate urban ability to resist disasters, and gradually started to use resilience theory to study the adaptive capacity of coupled systems [37], such as human–environmental systems [38] and social–environmental systems [39]. Unfortunately, contemporary studies have not devoted sufficient attention to the resilience evolution of the industry–environmental system.The industry–environmental system is an integrated system to recognize industrial development and environmental protection. Nevertheless, much research is not comprehensive: Some researches preferred to focus on only one or two aspects of the problems. For example, research on industrial wastewater pollution evaluation [40], efficiency evaluation of industrial system cleaner production and waste disposal [41], and industrial eco-efficiency indicators have been established [42,43]. Meanwhile, from the perspective of environmental protection, scholars studied ecological environment evaluation on all kinds of perspective [44], and analysis of the interactions among China’s economic growth and its energy consumption, air emissions, and air environmental protection investment [45]. However, industrial activities are dynamically changed, and environmental changes are an effective response to industrial adjustment. It is even more necessary to study the changes of industrial activities and the ecological environment as a coupling system. Only clarifying environmental system change laws under the continuous interference of industrial activities and the restrictive effect of environment on industrial development, it can provide a scientific basis for the sustainable development of the industry–environmental system. Therefore, this article attempts to study the interaction law between industrial and environmental systems from the perspective of resilience.This paper mainly focuses on the coupling law of industry–environmental system and look forward to finding a new way for the sustainable development of the industrial economy. Since there are respective interests of the two major themes of industrial development and environmental protection, this paper chooses to conduct a resilient evaluation of the entire industry–environmental system from the resilient perspective. The catastrophe theory and the adaptive cycle model were used to analyze how to find a balance between the industry and the environment. Therefore, establishment of comprehensive evaluation model considers the contribution of various factors in the industrial activity sub-system and the environmental sub-system to the resilience. The framework of the comprehensive evaluation model is summarized in Figure 1 with the following three research phases.This section describes the integrated resilience evaluation for industry–environmental system. Combined with the research of this paper, indicators selected from two aspects of environmental response and industrial activities in some related literatures. Table 1 briefly reviews the literature and selects the most common influencing factors for resilience evaluation of industry–environmental system.Industry–environment integration is a highly complex system that involves the impact of industrial activities on the environment and the restrictions of environment and resources on industrial development. Based on previous studies, selecting appropriate indicators should meet the following criteria: (1) The selected indicators can be widely used in this situation; (2) the selection process should combine regional yearbooks with field research. As shown in Table 1, the most common cited indicators are economy, pollution, land use, and resource consumption. However, some indicators are often ignored, such as production and treatment. These factors still play a significant role in industry–environmental system resilience evaluation. Based on the brief literature review in Table 1 and indicators selection criteria, six main secondary indicators are selected from the industrial activities and environmental sub-systems, which are derived from seventeen primary indicators. These indicators reflect the overall situation as comprehensively as possible. At the same time, this paper will use the EPI to analyze environmental press and the ISE to analyze the orderliness of industrial structure. Therefore, the selection of indicators also considers the applicability of two index calculations. Accordingly, a comprehensive evaluation index framework is established to determine the resilient level of system with the semi-quantitative and semi-deterministic analysis. They represent the interaction between the disturbance of industrial activities and the environmental systems, including economic development, industrial structure, resource consumption, environmental pollution, and waste discharge. The detailed index system is shown in Table 2.Since indicators have different units, they need to be standardized to eliminate the impact of different dimensions. This also meets the requirements of the catastrophe modeling approach [38,39]. All values are normalized to values between 0 and 1 by Equations (1) and (2). The choice of equation needs to consider the positive and negative effects of the indicator. The benefit index, that is, the larger the value, the better the positive index formula is used, (Formula (1)); otherwise, the cost index uses the negative exponential formula (Equation (2)).
+          (1)Positive indicator:xij′ =(xij−min{xj})/(max{xj}−min{xj})
+          (2)Negative indicator:xij′=(max{xj}−xij)/(max{xj}−{xj})xij is the value of indicator j in year i, max{xj} is maximum value of indicator j, min{xj} is the minimum value.The Composite Index of Environmental Performance (CIEP) was developed by the World Health Organization (WHO), based on the driving–force–pressure–state–exposure–effect–action (DPSEEA) methodology proposed [51]. The EPI is jointly developed by the Yale Center for Environmental Law & Policy (YCELP) and the Center for International Earth Science Information Network (CIESIN) at Columbia University, in collaboration with the Samuel Family Foundation and the World Economic Forum [52]. The CIEP and the EPI are two composite indexes commonly that are used to quantitatively measure ecological quality or impact and used in many studies that often accept innovation and improvement [53]. Those indicators can be used to guide the operation of all subsequent steps. This paper needs to select the most suitable one to represent the pressure level of environmental indicators and reflect the resilience level of the environmental system. According to Neves Almeida’s [54] analysis of the possible differences between the CIEP and EPI indices, the model compares the pros and cons of the two. Using the two EPI objectives of environmental health and ecosystem vitality, CIEP is explained by two models and ten policy categories of EPI are adopted. The third model uses EPI as the dependent variable and the independent variables are the following five CIEP dimensions: driving force, pressure, state, effects, and actions.
+        CIEP it = α + β1ehit + β2evit + φi + φt + εit (Model 1)
+        CIEP it = α + β1ehehit + β2ehairit + β3ehwaterit + β4evairit + β5evwaterit + β6evbhit + β7evagit + β8evforestit + β9evfishit + β10evclimateit + φi + φt + εit (Model 2)
+        where, α is the constant; i is the individuals (countries); t in the time (year); eh is environmental health and ev is ecosystem vitality; φi and φt, are the dummies to measure the individuals and time effects, respectively. The εit is the random effect.
+        EPI it = α + β1dfit + β2pit + β2sit + β2efit + β2ait + φi + φt + εit (Model 3)
+        where, α is the constant; i is the individual countries; t in the time (year); df is the driving force, p is the pressure, s is the state, ef is the effects and α is the actions, φi and φt are the dummies to measure the individual countries and time effects, respectively. The εit is the random effect.According to the difference in comparison results, the CIEP model uses multiple imputations to complete the missing values, but the EPI does not use any imputation methods. The EPI also includes environmental policy factors. Moreover, the EPI can be calculated only with ecological index data and GDP value, and conforms to the rules of ecological tools used by the decision-maker to formulate environmental policies [54]. Therefore, combined with the effectiveness and practical convenience of this study, EPI is more suitable to reflect the pressure level of resource consumption and pollutant emission in industrial activities [33]. It is easier for policy makers to refer to environmental policies. Therefore, this paper chooses EPI to reflect environmental pressure. The calculation process can be expressed as the following formula:(3)EPI=(xi/g)(Xi/G)
+        where xi is the total consumption of environmental factor i in the study area; Xi is the total consumption of environmental factors i in the country; g is the GDP of the study area; G is the GDP of the entire country. The smaller the EPI, the higher the utilization level of environmental factors or the lower the environmental pressure of the study area [33].Frequent economic activities have brought increasing pressure on the ecological environment. The rationality of industrial structure has important impact on the ecological environment [46]. Therefore, it is necessary to consider the influence of industrial structure in the industry–environmental system. Industrial Structure Entropy (ISE) is selected to describe the state and degree of industrial structure system evolution [55].Entropy is a physical quantity that indicates the degree of disorder of molecular states. It was later that Shannon firstly introduced the definition of information entropy in the information theory, which can be used to demonstrate the probability and statistics methods to prove the chaotic state of any system [56]. Thus, the industrial structure entropy is used in the industrial structure to describe the state of industrial structure system evolution. The industrial structure is stable, the uncertainty is small, and the entropy is small. Conversely, if the industrial structure is chaotic, the uncertainty is large, and the entropy is large [57]. Therefore, by using the Shannon–Weaver formula [58], it is expressed as:(4)H=−∑i = 1nPi × lnPi
+        where: H represents the ISE; n represents the number of industry; Pi represents the proportion of the output value of i industry in the output value of all n industries in the region. A larger H indicates that the industrial structure is more disorderly, discrete, and diverse [33].Any movement in nature or human society has always been in a stable and unstable state. Under the influence of tiny accidental interference factors, the steady state can still recover. But when the system is too strong to change, absorb, and adapt, the system will enter another new stable state or another state. The range of effective adjustment is the purpose of elastic evaluation. A range of approaches have been applied to resilience assessment such as quantification based on indicators (quantitative) [59] and framework (qualitative) [60]. Theoretical resilience frameworks are built on collections of concepts or ideas. The framework-based approach mainly guides people to think about how to quantify resilience [61]. In recent years, more and more scholars have made achievements in the quantitative research of resilient change. The following Table 3 has some typical quantitative models in related fields.Catastrophe theory can directly deal with discontinuity without linking any specific internal mechanisms; therefore, it is particularly applicable for the study of systems with unknown internal functions. The study of industry and environment as a whole system is a new exploration, so the resilience change of industry–environment system is unknown. Based on the above resilient quantification methods, it is the most suitable theory to analyze.The catastrophe theory studies the phenomena and laws from a stable configuration to another stable configuration. It describes the evolution of form, especially for the analysis of sudden dynamic changes caused by gradual changes in force [65,66]. The solution process combines the fuzzy theory to generate the mutated fuzzy membership function by evaluating the multi-level contradiction decomposition of the target. It then normalizes the quantitative operation through the normalization formula. Finally, the normalization function is a parameter that obtains the total membership function and analyzes the evaluation objectives.The method is characterized by not weighting the indicators, but taking into account the relative importance of each indicator. Thereby, it can reduce subjectivity without losing scientific and rationality through simple and accurate calculation in a wide application range. At the same time, the theory can detect changes in the resilient variation between industrial and environmental randomness with different equilibriums, and can solves the adaptability of the resilient system. Furthermore, the results of catastrophe theory represent the time-dependent transformation of the coupled systems rather than simply increasing values of all indicators [20]. Considering these two key features of catastrophe theory, this study chose it as a method of industry–environmental system resilient calculation.There are seven basic mutation models, namely, folding mutation, cusp mutation model, swallow tail mutation model, butterfly mutation model, hyperbolic umbilical cord, elliptical umbilical cord, and parabolic umbilical cord. However, the commonly-used mutation progression methods are fold catastrophe, cusp mutation model, swallowtail mutation model, and butterfly mutation model.The fold catastrophe is:f(x) = x3 + ax(5)The cusp mutation model is:f(x) = x4 + ax2 + bx(6)The swallowtail mutation model is:(7)fx=15x5+13ax3+12bx2+cxThe butterfly mutation model is:(8)fx=16x6+14ax4+13bx3+12cx2+dx
+        where f(x) represents the potential function of the state variable x of a model, and the coefficients a, b, d, c of the state variable x represent the control variables of the state variable. If an indicator can only be decomposed into two sub-indicators, it is a cusp catastrophe model; if there are three sub-indicators, it is a swallowtail mutation model; if there are four sub-indicators, a butterfly mutation model.The normalization formula is solved by the potential function f(x) = x4 + ax2 + bx of the cusp mutation. Let ∂f(x)/∂x = 0, the equation of the critical point of the f(x) can be got:f′(x) = 4x3 + 2ax + b = 0(9)Let ∂f′(x)/∂x = 0, the equations of all singular point sets the f(x) can be got:f″(x) = 12x2 + 2ax = 0(10)Combine (9) and (10), eliminate x, and get a divergence equation: a = −6x2, b = 8x3, and then get:xa=−ab ,xb= b8 3 Using this as a normalization formula will result in inconsistent values of x, a, and b, and will also make the value range of (0,1) of the utility function and fuzzy membership function inconsistent, so control the value of the variable x and the variables a, b in the interval [0,1]:Since xa = −a6, when xa is in the interval [0,1], the corresponding value range of a is also in the interval [0,1]. Then the value of a needs to be 6 times smaller, therefore xa = a. The same reason, let b also shrink 8 times, then b will also be in the interval [0,1], xb = b3.So, the four catastrophe model normalization formulas are is derived by the bifurcation equation:The fold catastrophe is:(11) Xa = aThe cusp mutation model is:(12)Xa = a, Xb = b3The swallowtail mutation model is:(13)Xa = a, Xb = b3, Xc = c4The butterfly mutation model is:(14)Xa = a, Xb = b3, Xc = c4, Xd = d5Two important principles must be considered in the fuzzy comprehensive evaluation, when using the catastrophe progression method. If there is no obvious correlation between the control variables of the same project variables (such as u, v, and w), then the control variables are called non-complementary variables (such as u, v, and w), otherwise the control variables are called complementary variables (such as u, v, and w). When the catastrophe membership function value is calculated, as for non-complementary variables, the x is the minimum value of the corresponding control variable. As for complementary variables, the x is the average value of the corresponding control variable, such as x = (xu + xv + xw)/3.According to the calculation process of the catastrophe progression method, a normalized formula is adopted to calculate the catastrophe membership function value gradually until the comprehensive catastrophe membership function value is obtained.The final step is to instantiate the resilience values that calculated by using the catastrophe progression method. Adaptive cycle model is an important model, and has a wide range of applications in resilient analysis [33,38,67]. Adaptive loop provides a systematic approach that uses four phases to illustrate the resilience changes at different stages and reveals the adaptive ability of adaptive loops [21]. They include “exploitation (r)” (with a significant increase of resilience), “conservation (K)” (accumulation, monopolization, conservation of structure and resilience tends to decline), “release (Ω)” (rapid collapse or release phase of creative destruction) and “reorganization (α)” (renewal and reconstruction phase during the resilience tends to increase), which is shown in Figure 2. It must be emphasized that the adaptive cycle is neither constant nor absolute, but the most diverse. Understanding the phases of these cycles, their temporal and spatial extent and succession, it is important to identify the points at which the system can accept positive changes and the points at which the system is susceptible or likely to be affected by regime changes [68]. These four phases can be divided into two cycles: The “fore-cycle” (from the exploitation phase to the conservation phase) and the “back-loop” (from the release phase to the reorganization phase) [49]. The conversion of adaptive loops in two cycles can be used for the adaptation and conversion capabilities of the surveillance and navigation systems. When the industry–environmental system fails to resolve the “back-loop” phase, the system’s adaptability will be lost, which may lead to the system’s resilience collapse. The “fore-cycle” phase is the time to implement the new policy, which represents the state of the industry–environmental development required [22,69].In order to verify the effectiveness of the proposed evaluation model, this paper used the data of Chengdu to calculation, the city located in central Sichuan Province. The test aimed to illustrate how the proposed comprehensive evaluation model can be applied to the analysis of industry–environmental system resilience and future plan.As a national regional central city, Chengdu is the center of the economy, technological innovation and financial trade in Southwest China. At the same time, in recent years, Chengdu put forward a development goal: To build inland open economic highlands and a Park City (PC) with ecological value. PC is the sublimation of the traditional urban planning concept under the new era, and it is a new mode of sustainable development of urban construction. At this point, Chengdu has become the first city to mention the concept of PC. The location of the study area is shown in Figure 3.For a long time, the industrial economy has been the main source of economic growth in Chengdu. However, due to the special watershed environment, Chengdu has always faced tremendous ecological pressure. Therefore, coordinating industrial development and environment issue is an inevitable problem for the future development of Chengdu. In order to promote the construction of the “Made in China 2025” pilot demonstration city, Chengdu has proposed to focus on the development of five pillar industries about electronic information, automobile manufacturing, food and beverage, equipment manufacturing, and biomedicine. Meanwhile, it also forms an industrial functional cooperation zone with neighboring cities in the economic zone, and neighboring cities such as Ya’an promote the integration of industry and environment in the form of vigorously developing tourism. While developing emerging industries, the impact of the rapid development of traditional industries on ecosystems cannot be ignored. The problem of industrial pollution problems and the effective utilization of resources are still urgent problems to be solved. Therefore, it is an inevitable choice to choose Chengdu as the research area to analyze the elastic relationship between Chengdu’s industry and environmental variables. The results of Chengdu case study will contribute to the sustainable development of other ecological cities in China.The data of industrial activities, environmental pollution, and resource consumption used in this paper are from 2000–2018 Chengdu Statistical Yearbook, Sichuan Statistical Yearbook, China Statistical Yearbook, China Energy Statistical Yearbook, and Statistical Communique of Chengdu’s National Economic and Social Development. The raw data for these indicators are all from the annual statistical yearbooks. In the evaluation application process, the first-hand data obtained from the statistical yearbook is usually directly used for analysis, but many data are not blindly pursued the maximum or minimum value is the optimal value. In a complex system, the choice of the optimal value needs to weigh the multi-interest and take the optimal value under comparison. At the same time, some indicators are not easy to quantify directly, so the data of some indicators are processed with EPI and ISE in this study. The final data after calculation and analysis are selected as the data of resilient assessment analysis.Four resource consumption indicators and four pollution discharges indicators from 2000 to 2017 are calculated by EPI index based on the Equation (3). These indicators are selected to reveal the environmental pressure since 2000. Because of the “treatment” indicators are mainly used to reflect the improvement of technical level and environmental awareness, they are abandoned here. The calculation results roughly reflect the changes in the environmental system of Chengdu since 2000. The pressure on most environmental factors is decreasing. The following Table 4 is the calculation result for the eight indicators represented by EPI in the environment sub-system.The performance indicators of eight environmental factors of Chengdu from 2000 to 2017 are based on the calculation results of Equation (3) as shown in Figure 4.Since 2000, the environmental pressure of the three indicators of industrial pollution emissions has decreased significantly, indicating that environmental protection policies and industrial transformation are gradually releasing the pressure of environmental pollution. The performance of industrial smoke dust and industrial waste gas is the most obvious. However, the EPI of the three environmental factors, that is, electricity consumption, sewage discharge, and construction land fluctuated greatly. In the meantime, there was a slight upward trend, which indicates it is necessary to improve the economic utilization of electricity and land resources, and strengthen the governance of wastewater discharge problems. This situation may be the result in rapid urban expansion and the vigorous development of high-tech industries. Simultaneously, during the research period, the EPI of energy consumption was relatively stable and slightly decreased, indicating that the adjustment of industrial structure is gradually reducing the dependence of economic growth on resource-dependent industrial development, such as heavy industry. What is more, it also reflects the higher level of energy resource utilization. Due to the superior environmental location of the Chengdu Plain, water resources have remained stable and low for a long term. Also, abundant water resources greatly promoted Chengdu’s industrial development.The ISE is calculated by the four types of indicators, that is Chengdu’s primary industry output value, secondary industry output value, tertiary industry output value, and industrial gross output value from 2000 to 2017. The calculation results reflect the changes in the industrial structure adjustment of Chengdu. In the past 20 years, the industrial structure of Chengdu has become more and more stable. According to the calculation results of ISE based on the Equation (4), the change index of industrial structure from 2000 to 2017 is shown in Figure 5.The ISE of Chengdu in the past 20 years is generally concentrated between 1.18 and 1.3 showing a certain stage characteristics. The ISE value fluctuated and declined in the period from 2000–2007. It continued to decline rapidly from 2008 to 2015 and has rebounded slightly since 2015. Overall, the ISE value has decreased significantly, and the industrial structure has been continuously improved. In recent years, after the adjustment of Chengdu’s industrial structure, it has changed the situation of the industrial upgrading lagging behind economic development. The industrial structure has undergone major changes, which have gone from “two, three, one” to “three, two, one”. The industrial structure of Chengdu has been transformed into a new industrial structure dominated by industry and modern service industries. It is further alleviating the pressure on the environmental system and providing a breathing space for the rebound of the industry–environmental system.According to the index system established in the previous section, the resilience value of the factors represented by each index in the layer, and the comprehensive resilience value of the environmental and industrial sub-systems are all calculated by the catastrophe progression method. The indicator data used in the evaluation are derived from statistical yearbooks and data calculated by EPI and ISE. According to the number of control variables, each layer index is selected corresponding to the appropriate catastrophe model, and the formula corresponding to the model is selected in Equations (12)–(14) for calculation.Next, the detailed calculation procedure for the catastrophe progression method is provided with some simple example using data from Chengdu.(1) Calculating the membership degree for criteria layer (B) and use its corresponding indicators (C) as control variables, and in accordance with complementary principle.Cusp model for B3 and B6:xB3 = (xC371/2 + xC381/3)/2 = (0.787 + 1.00)/2 = 0.893xB6 = (xC6161/2 + xC6171/3)/2 = (0.571 + 0.00)/2 = 0.285Swallowtail model for B1, B2 and B4:xB1 = (xC111/2 + xC121/3 + xC131/4)/3 = (0.453 + 0.357 + 0.097)/3 = 0.302xB2 = (xC241/2 + xC251/3 + xC261/4)/3 = (0.468 + 0.822 + 0.00)/3 = 0.784xB4 = (xC491/2 + xC4101/3 + xC4111/4)/3 = (0.366 + 0.905 + 0.880)/3 = 0.717Butterfly model for B5,
+        xB5 = (xC5121/2 + xC5131/3 + xC5141/4 + xC5151/5)/4 = (0.630 + 0.721 + 0.00 + 0.717)/4 = 0.517(2) Calculating the membership degree for sub-system (A) and use its corresponding criteria layer indicators (B) as control variables. The industrial activity sub-system is calculated according to the principle of complementarity, and the environment sub-system is based on the principle of non-complementarity.Cusp model for A1:xA1 = (xB11/2 + xB21/3)/2 = (0.550 + 0.755)/2 = 0.652Butterfly model for A2:xA2 = min{xB31/2, xB41/3, xB51/4, xB61/5} = min{0.845, 0.895, 0.848, 0.778} = 0.778(3) Calculating the catastrophe membership degree for industrial–environment system resilience, and in accordance with non-complementary principle.Butterfly model for A:xA = min{xA11/2, xA21/3} = min{0.743, 0.920} = 0.743The all calculation results are drawn into the following three line graphs.The line chart of Figure 6a shows vividly that from 2000 to 2017, the resilience of all environmental factors experienced a typical transition period. Two distinct points of change are 2008–2009 and 2015–2016. Overall, there has been a positive change in environmental resilience resulting in a constant change in adaptive capacity. In addition to land resource, the other environmental factors are shown more resilient than the beginning of the research period. Especially in pollution and treatment, the rising trend of adaptive curve is more significant. The stronger the resilience of various factors in the environmental sub-system, the lower the resource pressure and the stronger the adaptability.It can be seen from Figure 6a that the adaptive curves of the four indicators of the environmental sub-system have three distinct fluctuation periods. The adaptive curve of environmental resources demonstrates its vulnerability. Their release phase can be observed: The adaptation curve of land resources declined rapidly in 2004–2008 and 2013–2015, and the adaptability curves of other resources also showed in almost the same period in 2004–2009, and 2015–2016 is a clear downward trend. This is a positive environmental response to the dynamic changes of industrial activities. Chengdu began to promote the policy of Urban and Rural Industrial Development Integration in 2003, which promoted the conversion of a large amount of rural land into construction land. According to the Statistical Yearbook data, it can be found that the growth rate of Chengdu’s resource consumption level was significantly faster than the national level during the period of the adaptability curve declined. At the same time, the bottom of land resource resilience in 2008 was also due to the 2008 Wenchuan earthquake, which caused the massive destruction of urban land resources. The orderly construction after 2008 has restored land resource resilience. What is more, high-tech industries such as the IT industry have gradually become Chengdu’s iconic industries from 2009, which has also eased the dependence of Chengdu’s economic development on resource consumption. As a result, the adaptive curve shows an upward trend. The policy of Green Development and Economic Transformation in 2012 has brought a new round of resilient changes. Environmental pollution and treatment are experiencing increasing resilience. The adaptive curve of environmental treatment has emerged for the first time in 2015–2016. The downward trend of pollution pressure and governance pressure helps maintain a healthy environment which could support the industry–environmental system functional and long-lasting system development.The comprehensive resilience of the environmental sub-system is affected by four indicators and the resilience is constantly changing. As can be seen from Figure 6c, the resilience of resources such as land, water, electricity, and energy rapidly decline in 2004–2008, and 2013–2016 has also led to the adaptability of the environmental sub-system decline. However, in general, the resilience value of the environmental sub-system has improved compared with 2000 indicating that the local industry–environmental system has recovered and improved its adaptability for resource consumption and environmental pollution. In addition, the vulnerabilities and fluctuations of observed variables should be addressed to answer the challenges of limited resources and environmental risks during industrial transformation. Therefore, it is necessary to formulate positive and effective policies to solve future industry–environmental system’s development problems in order to improve adaptive capacity.The industrial activity sub-system is different from the fluctuation of the environmental sub-system. The resilience value of the industrial sub-system is shown in Figure 6b as an increasing trend. Only the indicators show that the industrial structure suddenly dropped in 2002–2003. During the period, Chengdu industrial restructure was carried out for the first time, and the major strategic decision of structural adjustment of the eastern suburb industrial zone was implemented. The trend then quickly turn a reorganization phase in which the resilience value continued to increase steadily. The resilience of the industrial activity sub-system is also affected by the industrial structure indicators, and there was a small drop between 2002 and 2003, which was also due to the changes in agricultural restructuring. The industrial structure adjustment gradually reduced the proportion of the primary industry. Among these influencing factors, the industrial structure is the key dominant factor of the industrial activity sub-system when the system is in the lowest or highest resilient state. Overall, the industrial activity sub-system has experienced a relatively stable upgrade and transformation, and the adaptability has been significantly improved.Policy makers and environmental managers of regional industrial development are very interested in understanding the economic effects of industrial restructuring and the positive impact on the environmental system. Understanding the structure, direction and innovation of the industry and the interaction of the environment can help to develop viable new development plans to develop emerging alternative industries and minimize environmental burdens. At the same time, the exploration of other aspects of industrial sustainable development will also provide us with valuable experience [70,71].When catastrophe theory is applied to the quantitative calculation, the calculation equation is the normalization formula. Therefore, the calculated resilience value is usually very high, and the obtained resilience values are very close to each other [72]. The numerical value of the resilience value is not suitable as a basis for evaluating the resilience change. Thus, through the K-means clustering analysis in the SPSS software, the calculated composite resilience values of the industry–environmental system are clustered and analyzed with five different levels: Non-resilience, low-resilience, resilience, mid-resilience, and high-resilience. This makes it easier to judge the four adaptive cycles of resilience. The results of cluster analysis of SPSS are shown in Table 5 below. Table 5 shows the range of values for different resilience levels from low (level 1) to high (level 5).According to the K-means clustering analysis, the line chart of the industry–environmental system resilience from 2000 to 2017 is drawn as Figure 7 below. The variation of the line chart uses the four stages of the adaptive cycle model to analyze the changes in resilience.It can be seen from Figure 7 that the comprehensive resilience grades curve of the industry–environmental system presents a wave-like upgrade, which shows the process of adaptive cyclic transformation of the coupled system. The resilience grades are in the “exploitation” stage from 2000 to 2002. The resilience grades show a rapid growth and peaked in 2002. Then it enters the “release” stage, and the resilience grades dropped sharply to level 2 in 2003. After that, it entered the “exploitation” stage that resilience grades rapidly increased to level 5. The subsequent period of 2005–2010 is a long-term “conservation” stage with resilience accumulation, showing a downward trend. After the “conservation” stage, the resilience grades of the industry–environmental system go through the “release” and “reorganization” stages, complete the “back-loop” phase and the adaptability improved. The end of the “back-loop” phase also marks the beginning of a new round of policy development, and indicates the regional development goals are in line with the future development requirements of industrial activities and environmental system. Finally, the industry–environmental integration system enters the next cycle in 2013, and the resilience grades experience a sharp increase and decline again. It is currently in the “conservation” stage, and the industrial–environment system returns to the highest level of resilience.The curve shows that since 2000, Chengdu’s development goals and direction adjustment behavior have carried out within its own flexibility, and the city resilient level is also improved in the cycle, it ensures the adaptability of the industrial environment system itself. Starting with the adaptive cycle model, the “exploitation” and “reorganization” phase is the best time point to adopt the new management strategy to enhance resilience, and the “release” stage is the most vulnerable stage. Analyze the characteristics of the four stages will help to grasp the key points of policy promotion and protection. The most recent major industrial adjustments and environmental policies announcements in Chengdu was in 2004–2010. For example, The Guidance Catalogue of Industrial Structure Adjustment (2005), the 11th five-year Plan of Chengdu Environmental Protection in 2007, and the 11th five-year Plan of Chengdu Industrial Economic Development in 2008. During this period, Chengdu carried out three time industrial restructure. These all confirm the analysis of adaptive cycle model.This study modeled and described the resilience of the industry–environmental system based on catastrophe theory and adaptive cycle model. By considering industrial activities and environmental systems as a self-organizing system, this integrated approach helps to explore how the negative consequences of new initiatives in different periods can transform the system into a relatively sustainable and resilient state.Results and analysis show that the research results are consistent with the laws of adaptive cycle model. As this study found in the above comprehensive resilience grades curve, the current overall resilience has been significantly improved. Meanwhile, the curve shows that Chengdu’s development goals and directions since 2000 have completed the “back-loop” phase, which is the guarantee of the industry–environmental system’s own adaptation and resilience. However, rapid economic development and urbanization are inevitably main sources of environmental pollution and degradation. In addition, the resilience grade of the industrial sub-system is significantly enhanced, while the resilience value of the environmental sub-system shows obvious fluctuations. It indicates that the rapid development of the economy and the continuous improvement of the industrial structure still threaten the environmental sub-system. Reasonable adjustments and updates to the development goals of the industrial–environment system are needed based on the rule of system resilience.Adaptive cycle model believes that resilience systems must undergo cycles of exploitation, conservation, release, and reorganization. Starting from the adaptive cycle model, the exploitation phase is the best time point to adopt the new management strategy to enhance resilience. But the release phase is the most vulnerable phase. It may lead to irreversible resilience loss. Only the completion of the “back-loop” phase represents a recovery of resilience, which formed by the release and reorganization phase. Through the quantitative analysis of the catastrophe method and qualitative analysis of the adaptive cycle model, the key drivers in the resilience development of the industry–environmental system are determined. It includes industrial structure, urban development and construction, and the utilization degree of environmental resources. The study found that the industrial structure and industrial proportion of industrial activity sub-systems are the key factors for the development of industrial resilience. The control of resource consumption in environmental sub-systems is the key to future environmental governance. Environmental pollution and resource consumption caused by industrial production structure changes are the key factors for balancing the environmental resilience of coupled systems. These different dimensional changes affect the transition between different phases in the adaptive loop to varying degrees. These indicators determine the resilient state of the sub-system, the resilience trend of the industrial activity sub-system, and the environment sub-system under mutual influence. Mastering the laws of the system’s resilience cycle will really help to rationally adjust and update the sustainable development goals of the industry–environmental system. It helps to determine the reasonable implementation time of new policies and countermeasures.The cycle model provides a reference for the next policy development, and also explains the reasonable implementation time of the relevant actions. Understand the structure, direction, and innovation of the industry and the interaction of the environment to minimize the environmental burden. The research on this system has helped to analyze the most vulnerable issues in sustainability management. Sensitive indicators have become the key control indicators for future sustainable development, and time-based strategic adjustments to ensure industry–environmental resilience.In this study, EPI and ISE were used to measure the pressure level of eight environmental factors and the stability of industrial structure. Then the catastrophe theory was used to calculate the resilience value of the system and analyze the absorption and adaptability of the industry–environmental system. In addition, the adaption cycle model was used to study the resilient dynamics of the system in order to reveal the resilience change of the system. The four-stage cycle process demonstrates the process of industry–environmental system destruction and recovery, as well as the response of industrial activity sub-systems, environmental sub-systems, and integrated systems to various resilient interference factors. The comprehensive evaluation model explores the key factors, the process and the change law that affect resilient change in industry–environmental system.According to the exploration of this paper, we can better grasp the focus of the policy adjustment and the reasonable implementation time of various measures to promote the sustainable development of the industry–environmental system. On the basis of different characteristics of four stages, the adaptive cycle model is used to discuss the suitable implementation cycle and feedback effect of each key index. In the period of industrial transformation and development in various cities, it contributes to policy adjustment, industrial adjustment and strategy formulation. Through the resilient grade change curve, we can grasp the reasonable action point of the new policy implementation and avoid the fragile period of the industry–environmental system. It provides a reference for the next policy and implementation nodes. The research of the system is helpful to understand the most vulnerable problems in sustainable management and to explore a new model for the sustainable development and construction of ecological cities such as Chengdu. The sensitive index has become the key index for the future sustainable development, and they will be the breakthrough point of the future research.The catastrophe theory used in this paper is the most direct and convenient method to measure the resilient level in the index evaluation. Then analyze the resilient law by adaptive cycle model. The transition between stages in the adaption cycle model is a key decision point to ensure system resilience. This is a continuous but disconnected process. Further exploration of more effective tools is needed to directly assess elastic changes and obtain accurate data for each key point threshold. Exploring the laws of resilient change is only the first step need to be taken in the research of the resilience of the industry–environmental system. Further research on system threshold determination and variable range can also help to confirm the effectiveness of policy implementation and extract optimal solution.X.W. conceived the research framework, designed the evaluate model, implemented the entire experiments and wrote the majority of the manuscript; X.Y. carried out the field research, collected the data and wrote the rest of the manuscript; Q.W. refined the manuscript and improved the use of language; J.G. applied statistical and mathematical techniques to analyze or synthesize study data and provided constructive suggestions on mathematical theory; L.G. proposed novel ideas and technical solutions to achieve the goals. All authors have read and agreed to the published version of the manuscript.This research was funded by the Key Funds of Sichuan Social Science Research Institution “System Science and Enterprise Development Research” (Grant No. Xq18B06), the Foundation of Chengdu Science and Technology (Grant No. 2017-RK00-00274-ZF & Grant No. 2019-RK00-00311-ZF), and Chengdu Philosophy and Social Science Research Funds (Grant No. 2019L12).The authors declare no conflict of interest.The flow chart of the research. Phase I: Establish a resilient evaluation index system, and use the Environmental Performance Index (EPI) and Industrial Structure Entropy (ISE) to show the pressure level of the environment system and the orderly trend of industrial activities in the indicator. Phase II: Calculate the resilience value of each index by using the catastrophe theory, and provides a basis for subsequent analysis. Phase III: Analyze the law of resilient change of the system through the adaptive cycle model, and apply it to the choice of future development.Adaptive cycle in resilience interpretation.Location of study area.EPI of eight environmental factors in Chengdu from 2000 to 2017.ISE in Chengdu from 2000 to 2017 and the two-period moving average curve reflects the trend of ISE.(a) Changes in the resilience values of the four main indicators of the environmental sub-system; (b) changes in the resilience values of the two main indicators of the industrial activity sub-system; and (c) changes in the composite resilience values of the environmental sub-system, the industrial activity sub-system and the industry–environmental system. The resilience value from 0 to 1 indicates ascending adaptive capacity.Resilience grades changes of the industry–environmental system.Impact factors of industry–environmental system evaluation.Indicators for industry–environmental system resilience evaluation.++ denotes the highly cited indicators. + denotes the moderately cited indicators. * denotes the novel indicators.Different techniques for quantifying and modelling resilience.Result of indicator data processing.Cluster range and resilience level of resilience values.

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+Aspects of human evolutionary biology and prehistory are discussed in relation to vitamin D. The evolution of hairlessness, combined with the need for efficient eccrine sweat production for cooling, provided evolutionary pressure to protect the skin from ultraviolet damage by developing cutaneous pigmentation. There was a subsequent loss of pigmentation as humans journeyed to northern latitudes. Their increasing mastery of technology outstripped evolution’s finite pace as further dispersal occurred around the globe. A timeline for the development of clothing to provide warmth, and the consequent shielding from ultraviolet light, which diminished vitamin D synthesis, can be inferred by an examination of mutations in the human louse. In the modern world, it is easy to take for granted the speed and ease of travel and accept the accelerating pace of change in contemporary society whilst forgetting the role of evolutionary biology on our prehistorical ancestors and its persisting effects in relation to vitamin D. Evolutionary changes in biological systems have finite speed, but the rapid mastery of technology by humans far outstrips the evolutionary process. For example, consider Moore’s law of the exponential growth in the complexity of computer integrated circuits proposed just 50 years ago and the potential for quantum computing. In contrast to such technological advances, the evolutionary story starts millions of years ago. This review considers some of the evolutionary changes in the structure and function of skin during prehistory in relation to vitamin D.The generally accepted view is that modern humans (Homo sapiens) originated from Africa [1,2]. The earliest members of our lineage were members of the genus Ardipithecus and lived mostly in woodland environments [3]. Later protohumans, also referred to as hominids, in the genus Australopithecus, lived in a wider range of environments but have also only been recovered from Africa [4]. Data from fossil records to study climate change indicate that approximately 2.6 million years ago, as the Pleistocene Epoch began, the habitat of protohumans changed as the earth entered the period of climatic oscillations known as the ice ages. Perhaps in response to the increased variance in the environment, approximately 2.6 million years ago the archaeological evidence indicates that our ancestors started to use stone tools to butcher animal bones [5]. Meat is a richer source of nutrients than vegetable matter but it is scarce and mobile. In addition to the stone tools, these early members of the genus Homo also evolved modern human-like skeletal proportions that reflect a more efficient long-distance walking ability [6]. With the greater energy expenditure of daytime long-distance walking came the need for greater thermal regulation, particularly cooling. Bipedalism carries significant competitive advantages of speed, height, and the use of tools. Homo erectus, 1.6 million years ago, was the first hominid to have elongated limbs capable of sustained walking and running. Therefore, the switch from less hair to an efficient cooling system was underway 1.6 million years ago [7].There is an evolutionary advantage to hairlessness. The modern-day chimpanzee is our closest living relative. Chimpanzees have pink skin covered with black fur. The hominids are believed to have shared this phenotype. Hair provides effective sun protection and thermoregulation for a sedentary lifestyle. The most efficient evaporative cooling of sweat occurs at the skin’s surface and then water vapour is transferred through the fur. Dry fur also protects the body from external environmental heat gain. If fur becomes wet, evaporation occurs at the surface of the fur and not at the skin, and therefore heat from the cutaneous vessels has a barrier to its site of loss. Consequently, there is an advantage to hairlessness when there is a need for significant heat loss, which will occur with exercise [8]. In modern humans, there are three types of sweat glands in the skin: eccrine, apocrine, and apoeccrine. They secrete fluid directly into the duct. These glands vary in type, density, and anatomical location. The eccrine glands are the most important for temperature control. Approximately 1.6 to 4 million are distributed over most of the body’s surface. Eccrine sweat is a sterile dilute electrolyte solution. The apocrine glands are limited in their distribution to axillae, anogenital, and periumbilical skin, nipples, and vermillion border and they connect by a stretched duct into the follicular canal. Apocrine sweat is a sterile viscous oily fluid.  The apoeccrine glands are confined to the adult axilla. The chimpanzee, gorilla, and baboon have fur coats. These animals have thermal apocrine glands and eccrine glands. Therefore, it is inferred that the ancestral great apes were able to “supply” eccrine glands to the protohumans. These coats provide physical protection and are efficient cooling systems, using apocrine sweat when dry, but are not effective cooling systems when wet from sweat production. Thus, hair is disadvantageous for heat loss after prolonged physical exercise. There are no thermal apocrine glands that are not associated with hair follicles. Natural selection, therefore, drove the loss of hair and apocrine glands to favour the development of eccrine sweating for effective temperature control in concert with bipedalism [8].The central equatorial African savannah is a high ultraviolet (UV) environment, and a lack of hair results in UV-induced damage through a lack of sun protection. The effect of climate change producing a drier environment also placed stress on the epidermal barrier. Therefore, evolutionary pressures worked to provide the needed protection, and there are several theories concerning this, including the need to protect against UV induced skin cancer and UV induced barrier dysfunction as well as the requirement for folic acid protection. Normal functioning of the skin barrier with an intact epidermis is essential for health, and atopic dermatitis is an example of a disease with disrupted function. Pigmented skin has enhanced barrier function, with greater cohesion of the stratum corneum and reduced susceptibility to infection, as well as providing protection from UV induced dysplasia and skin cancers [9]. Folic acid is an essential vitamin needed for numerous biological functions, including DNA synthesis and repair, red blood cell production and spermatogenesis. In humans, disorders associated with lack of folic acid include megaloblastic anaemia, peripheral neuropathy, and, in pregnancy, foetal neural tube defects. Folic acid deficiency is also associated with multiple defects in non-human mammals. In the human body, folate (the naturally occurring form) is sensitive to UV-induced degradation in the skin. UV-induced folate degradation has been demonstrated in light-skinned patients exposed to natural sunlight. Therefore, there was a strong evolutionary pressure to protect the skin and this was achieved by the production of melanin [10]. Melanin is produced in the melanocyte. The melanocyte is a cell derived from the neural crest that, in the skin, resides in the basal layer of the epidermis. The production of melanin is complex and occurs in the intracytoplasmic organelle called the melanosome. This moves along the dendritic process of the melanocyte and is then transferred to the keratinocyte. It is the activity, and not the number of melanocytes that determines skin colour. Darkly pigmented skin has melanosomes with a heavy deposition of melanin compared with fair skin, which has minimal melanin deposition. There are two major forms of melanin produced by melanocytes: brown-black eumelanin and yellow-red phaeomelanin. Melanin attenuates UV radiation by absorption, dissipating it as heat. The melanocortin 1 receptor (MC1R) is a membrane-bound receptor on melanocytes and is one of the most important regulators of melanin production [11].The MC1R gene is mapped to chromosome 16q24. There is almost no variation in this coding region in African populations, supporting the strong selective pressure to maintain a dark skin colour in the African environment [12,13]. Therefore, at some point in the transition from the hairy to the hairless state, evolutionary pressure would have acted to support the selection of the MC1R alleles producing skin pigmentation. Genetic modelling suggests that this gene variant found in Africans may have emerged 1.2 million years ago, which roughly corresponds to an innovation in stone tool technology that likely reflects an increase in the sophistication of hunting ability [14,15].The vitamin D binding protein (VDBP) has also been subject to evolutionary pressure that can be considered a continuous process of structural modification from primates [16]. The gene was the target of locally exerted selective pressure driving different haplotypes in distinct human populations [17]. There are different polymorphisms of the VDBP, with group-specific component (GC) 1F being most abundant in persons of African ancestry and GC1S being most abundant in European populations [18]. The affinity of the two VDBPs is different for vitamin D, with GC1F being greater than GC1S, and it is possible that during evolution the most abundant form of the VDBP in dark skin was able to transport vitamin D3 more efficiently from the skin to the liver for its metabolism to 25-hydroxyvitamin D [19]. There are lower levels of 25-hydroxyvitamin D in the African-American population, but there are higher bone densities in the African-American population compared with that of the white population. Lower levels of VDBP in African-Americans will result in bioavailable levels of 25-hydroxyvitamin D equivalent to those in caucasians [20]. However, the methodology and therefore the conclusions of this study have been challenged for a number of reasons, including not considering the role of the renal proximal tubule, the methodology of calculating the bioavailable 25-hydroxyvitamin D, and the monoclonal antibodies used [21,22].The exact method, mode, and timing of human dispersion out of central Africa are uncertain, but the older archaeological evidence of this migration is supported by a modern genomic analysis of ancient bones [2,23]. Human dispersal from Africa is unlikely to have occurred in one wave and is more likely to have occurred in multiple waves with the following two major episodes: the first through the Arab peninsula into southern Asia and Oceania and a later wave through a northern route [24]. These uncertainties aside, humans walked north probably through modern-day Egypt and the eastern Mediterranean into Europe and east into Asia, perhaps following the coastline [25]. There have been numerous changes in coast lines [26] and the ancient coastline was different from today. Sea levels were lower because of large quantities of water locked in polar ice caps. The migration of protohumans in eastern Asia was occurring during the Pleistocene era (2.6 million to 11,700 years ago) [27]. Movement further east into the Pacific may have occurred from Taiwan (the “out of Taiwan model”) or possibly from Wallacea, which is a geographical group of islands between the Asian and Australian continental shelves. However, recent genome-wide data from 56 Austronesian groups suggest that their ancestry is closely related to aboriginal Taiwanese favouring the “out of Taiwan model” [28]. The last major migration of humans was into the remote eastern Pacific during the Holocene era (10,000 years ago to current) [29]. The Pacific rat (Rattus exulans) travelled with ancient humans and can be used as a proxy to estimate the time of arrival at a given location. Radiocarbon dating of distinctive rat-gnawed seeds and rat bones from different locations around New Zealand show that the rat was established in New Zealand by approximately 1280 in the common era, and there is no evidence to suggest the presence of rats during the preceding millennium [30]. This time frame is supported by mitochondrial DNA studies of Māori, whose founder population of women arrived in the sea-going waka (canoes) numbering 170–230 [31].As humans migrated away from the central equatorial African climate to different latitudes, the exposure to ultraviolet B (UVB) diminished and therefore the ability to produce sufficient vitamin D also diminished. Highly melanised skin requires longer exposure to UVB when the intensity is reduced in order to produce sufficient vitamin D. Rickets is a serious complication of vitamin D deficiency which would have resulted in deformed pelvises that were inadequate for successful childbirth in prehistory if the evidence of recent history is reviewed. In 1956, approximately 15% of African-American women had significantly deformed pelvises due to childhood vitamin D deficiency, which reflected the cohort of women born prior to the widespread adoption of dietary vitamin D supplements in the 1930s [32]. The obstetric complications included abnormal presentation, umbilical cord prolapse, and impossible vaginal delivery in 10% of cases, with foetal mortality at 10–15% in the absence of caesarean section [32]. Therefore, evolutionary selective pressure favoured the loss of melanin over tens of thousands of years. Depigmentation was evolved through different complex genetic mechanisms in northern Europeans, modern East Asians and Neanderthal humans [33,34,35,36,37].There is a strong correlation of skin reflectance with latitude and UV radiation. Interestingly, in all the studied populations, females are found to have lighter skin than males. The lighter skin of females may be due to the evolutionary pressure to produce greater quantities of vitamin D during pregnancy and lactation [10]. New Zealand lies approximately between latitude 35° and 46° south. Wellington sits at 41°19′ south. The potential for the synthesis of previtamin D3 in the skin has been estimated from average annual UV minimal erythemal doses. The minimal erythemal dose is the quantity of UV radiation required to produce a barely perceptible reddening of the skin. New Zealand and southern Australia, including Tasmania, fall into a zone where there is insufficient UV radiation to catalyse the formation of previtamin D3 in moderately and highly melanised skin. In lightly pigmented skin, these areas fall into the category for which there is insufficient UV radiation during at least one month of the year to produce vitamin D3 [10]. Therefore, approximately 700 years ago, the earliest Polynesian colonisers of New Zealand, arriving by boat, entered a UV environment, setting the stage for relative vitamin D deficiency. This is an example of how the technology of the day, the sea-going waka, outstripped evolution. In New Zealand, Māori women have significantly lower levels of vitamin D than non-Māori women, and Pacific men and women have significantly lower levels of vitamin D than non-Pacific men and women [38]. Modern migrants travelling to New Zealand arrive by plane from all over the world and those with low levels of vitamin D, including those of Indian and African descent but those of Asian ethnicity have the lowest mean level (37.0 nmol/L) [39,40].Although diet is important, 90% of vitamin D synthesis is derived from cutaneous sun exposure [41,42]. Therefore, the development of clothing, which blocks UV exposure, is important. Protection from cold is a leading theory for the development of clothing [43] particularly relevant in the higher and lower northern and southern latitudes of the globe where the temperatures are cooler, the need for warmth greater and the incident UV is less than that in central equatorial latitudes. The development of clothing by ancient humans is another example of adoption of the use of technologies that include scraping, cutting pelts, and the ability to pierce and sew, which has the unintended consequence of compounding potential vitamin D deficiency. In the archaeological record, needles and hide scrapers can be found but it is likely that the use of clothing predated the development of this technology as ancient clothing would degrade quickly. However, the study of human lice Pediculosus humanus capitis (head lice) and Pediculosis humanus humanus (body lice) has shed light on the first use of clothing. These two lice are morphologically similar but inhabit different body sites. Head lice live on the scalp and feed more frequently than the body lice that live in clothing and move to the body to feed once or twice a day [44]. Sucking lice parasitising mammals are generally host specific [45], and body lice are derived from head lice [46]. With human evolution and the loss of body hair, the louse needed to evolve and diverged in to the two types [47]. All modern body lice associated with modern humans are confined to a single mitochondrial descendant (clade) [47]. Examining when that divergence took place provides a proxy estimate as to when humans may have started to wear clothing and it is estimated that this divergence may have occurred between 83,000 and 170,000 years ago during the middle to late Pleistocene era [47]. If this is correct, then vitamin D deficiency may be a relatively modern phenomenon in the evolutionary timeline. It is notable that the Neolithic (12,000–3500 years before the common era) skeleton of a 25–30 year-old female found on the Scottish island of Tiree (latitude 56.5° north) had deformation of the sternum and ribs consistent with rickets [48].Human imagination, combined with the ability to develop technology, such as tools, clothing, and sea-going waka, far outpace biological processes, however, our evolutionary roots still have a direct consequence onvitamin D in modern society.Conceptualization, P.J. and R.S. writing—original draft preparation, P.J.; writing—review and editing, P.J. and R.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding.The authors wish in particular to thank reviewer 3 for helpful comment and guidance.The authors declare no conflict of interest.

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+With increasing girls’ enrolment in schools, school preparedness to ensure a menstrual friendly environment is crucial. The study aimed to conduct a systematic review regarding the existing evidence on menstrual hygiene management (MHM) across schools in India. It further aimed to highlight the actions that have been taken by the government to improve the MHM situation in India. We conducted the systematic literature search using PubMed, EMBASE, and Web of Science for searching the peer-reviewed articles and Google Scholar for anecdotal reports published from inception until 30 October 2019. Of 1125 publications retrieved through the search, 183 papers were included in this review, using a priori created data-extraction form. Meta-analysis was used to estimate the pooled prevalence (PP) of MHM practices in schools. Less than half of the girls were aware of menstruation before menarche (PP 0.45, 0.39 to 0.51, I2 = 100.0%, n = 122). Teachers were a less common source of information about menstruation to girls (PP 0.07, 0.05 to 0.08, I2 = 100.0%, n = 86). Separate toilets for girls were present in around half of the schools (PP 0.56, 0.42 to 0.75, I2 100.0%, n = 11). MHM in schools should be strengthened with convergence between various departments for explicit implementation of guidelines.Inadequate menstrual hygiene management (MHM) among adolescent girls (15–19 years) is a public health problem, mainly in low and middle-income countries [1]. With over 0.6 billion adolescent girls (8% of the world’s population), the issue of menstrual hygiene by virtue of its magnitude is an issue of global concern. More than 80 percent of these adolescents reside in the Asian and African continents [2]. India is home to 243 million adolescents, which accounts for a quarter of the country’s total population [3]. India has over 355 million menstruating women and girls, but millions of women across the country face uncomfortable and undignified experience with MHM [4].Menstrual hygiene is often regarded as a multi-sectoral issue that requires an integrated action from the Department of Education, Health, Women, and Child Development and Water Sanitation Hygiene (WASH) [5]. In recent years, we have witnessed a strengthened move by the government towards addressing this public health issue. With the launch of the National Rural Health Mission in 2005, menstrual hygiene promotion was formally included as a key responsibility of the community health workers (Accredited Social Health Activist; ASHA) followed by the implementation of menstrual hygiene promotion scheme for girls in rural areas in 2011 [6]. In 2015, another milestone was achieved when the Ministry of Drinking Water and Sanitation published guidelines on MHM [7]. There has been a lot of national and international level push to address this issue through various social media platforms including the making of a film called Padman [8], roll out of menstrual hygiene campaigns, performing trials on eco-friendly or biodegradable menstrual products, implementing comprehensive sexuality education in schools, etc. [4].Menstruation among school-age girls is a neglected issue on the implementation front despite the formal inclusion of a menstrual hygiene scheme under the reproductive and child health program by the government of India (in 2011) [9]. This issue still lacks educational support from health workers, pragmatic guidelines to operationalize MHM in schools, and adequate monetary resources to implement the needed actions. Fear, shame, ongoing social taboos, ignorant unsupportive teachers, lack of water, sanitation, disposal facilities, and privacy, are some of the barriers in building an enabling environment for safe and hygienic menstrual practices within the school premises [10,11,12]. These system-level challenges, in conjunction, not only negatively impact sexual and reproductive health outcomes of adolescent girls but also affects their self-confidence and agency (ability to make a decision and take actions for self) [11]. The increasing enrolment of girls in secondary and senior secondary schools demands a more comprehensive approach to make schools menstrual hygiene friendly and prevent school dropouts or absenteeism [13].Given that a comprehensive approach to study MHM among schools in India was not made in previous reviews, we chose to conduct a systematic review. The review aimed to objectively summarize the evidence on the actions taken at the school (system)- and policy-level to make schools a menstrual hygiene friendly place for adolescent girls in India.The research question was defined as “Are schools in India menstrual hygiene friendly, and what are the policy-level actions taken by the government of India to make our schools menstrual hygiene friendly?”We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework for systematic reviews to identify the published and grey literature on school (system-) and policy-level actions [14]. A systematic literature search was undertaken to identify the evidence using the online databases of MEDLINE (PubMed), EMBASE, and Web of Science, from inception until 30 October 2019. In addition, for the policy-level actions, we did a manual search for the relevant documents through the government of India’s website and Google Scholar. We searched the websites of the four concerned ministries related to MHM, including the Ministry of Health and Family Welfare, Ministry of Women and Child Development, Ministry of Drinking Water and Sanitation, and Ministry of Human Resource Development. Since many papers, project reports, documents, or guidelines are not published in peer-reviewed journals, the Google Scholar search was extended to include the grey literature.Keywords used for the search across three databases were: (‘Menstruation OR Menstrual OR Menses OR Periods OR Hygien* OR Sanitation OR Sanitary OR Hygiene’) AND (‘School OR Adolescent OR Adolescen* OR Pubescence’ AND ‘Girl OR Women OR female’) AND India. Cross-referencing (screening reference list of included studies) was also used to add other studies of relevance to our review. We did not consider abstracts from conference books, manuscripts, or reports published in any language other than English. Endnote X.8.0.1 (Clarivate Analytics, Philadelphia, US) was used to manage all references identified in the search. All the search results were imported in endnote and duplicates if any were removed.For the purpose of this review, a ‘menstrual hygiene friendly school’ was defined as schools where (1) teachers had adequate knowledge about MHM or teacher was a source of information for MHM (before or after menarche) to girls, (2) school management committees took menstrual health-promoting actions, and (3) there were facilities of clean, separate girls’ toilets, changing rooms, water, soap, safe disposal of used pads, and emergency sanitary pads (sanitation facilities). Furthermore, (4) male sensitization on MHM, (5) girls’ awareness on menstruation before menarche, (6) availability of education material on menstrual hygiene promotion, (7) waste management facilities in school premises, and (8) regular monitoring of the schools for rolling out MHM, were added dimensions of menstrual hygiene friendly schools [12]. We established inclusion criteria as any publication that described any of the above-said components of menstrual hygiene friendly schools in India for school-level actions (Figure 1). Any study not reporting on any of these eight dimensions was excluded during the screening process. Studies that included girls’ awareness of MHM in their findings but did not mention that they were school-going girls were also excluded from the analysis. For policy-level actions, guidelines, or reports that have specified about the government of India’s actions on MHM promotion in schools were included. Quality assessment of included studies was performed based on seven criteria as specified in another review [15]. Each criterion had a value of one or zero. For each study, the results of all the seven criteria were summed to obtain a quality score ranging from 0 to 7. However, studies were not excluded on the basis of a quality score. The quality assessment sheet of the includes studies is provided as Supplementary Table S1. We did not contact the authors of the studies or reports for further information. Two authors (Shantanu Sharma and Devika Mehra) independently reviewed all the titles and abstracts to select the relevant studies. The data on the above-said dimensions, as specified previously, were extracted from the included studies according to a standard form created a priori. Discordance between the two authors was resolved by consensus. The results are presented based on the eight components of menstrual hygiene friendly schools. Meta-analysis was performed on four out of the eight components of school-level actions as quantitative data were available for only four of them. These four components included teacher as a source of information about MHM (before or after menarche) to girls, separate toilet facilities for girls in schools, awareness of girls on menstruation before menarche, and good disposal facility for sanitary pads in schools. Pooled prevalence (PP) was estimated in a random-effects model using the RevMan version.5.3 software (Cochrane Collaboration, London, UK). Forest plots were generated to display the overall random-effects pooled estimates with 95% confidence intervals. The heterogeneity was quantified using the I2 measure and its confidence interval. We used generic inverse variance method and computation of the standard error was done using the formula: Square Root [(proportion*(1-proportion))/sample size]. Of 1125 papers and reports (of which 152 retrieved through cross-referencing and grey literature), 183 were considered eligible (Figure 2). Furthermore, 153 out of 183 were used for the quantitative synthesis of meta-analysis. Most of the studies were of low-to-moderate quality with the combined average score of 2.6. The characteristics of the included papers have been shown in Table 1. The PRISMA framework checklist is provided as Supplementary Table S2. The findings from included papers were presented under two broad themes, namely, school-level (system) actions, and policy-level actions. Under the system-level (school) actions, eight components were included, as defined previously.According to our literature review, there was no peer-reviewed publication or anecdotal reports on the knowledge of school teachers regarding menstruation issues in India. The programs that included reproductive health education as a means to disseminate MHM information in schools did not measure or mention this. Moreover, school teachers were reported as the less common source of MHM information among adolescent girls in 74 studies [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89], yet in 12 studies, a large proportion of girls (more than one-fourth) reported that teachers were a common source of information about MHM (Table 2) [90,91,92,93,94,95,96,97,98,99,100,101]. The teachers in those schools were reported to have been supportive [95]. In addition to these challenges, non-availability or limited availability of female teachers in schools was a serious issue. Despite schools running health programs, teachers found discussing menstruation embarrassing and instruct the students to read that chapter in the textbook at home. As English was not taught in some schools, the use of vernacular terms for human reproductive organs in the local language became very embarrassing for teachers as well as students [102]. It has been reported that many teachers were insensitive to the physical and mental state of girls during their periods [16]. Moreover, a study from Tamil Nadu reported that 1.3% of the schoolgirls were scolded by teachers for menstrual problems [103]. Teachers felt the need to do games and activities to share information about various menstruation-related issues with girls. However, they could not conduct such activities in school because they were pre-occupied with routine duties and curriculum targets [77]. Teachers were a source of information among 7% girls (PP 7.0%, 95% Confidence Interval (CI) 5.0% to 8.0%, I2 = 100%, n = 86) (Figure 3).The World Health Organization proposed the concept of Health Promoting Schools (HPS) in 1995, which advocated for the total life approach to school-based health promotion while focusing on the curriculum, the school’s ethos, and the environment. The HPS framework emphasized creating a management committee as a support structure for schools to help in planning, designing policies, strategies, and procedures towards health promotion [104]. Menstrual hygiene promotion could be one of the outcomes of the actions of this committee. However, evidence on the existence of such committees and their commitment to health promotion was limited [105]. In two intervention studies from Bihar and Chandigarh, the school management committee under the HPS framework was established as an effective means towards promoting health [105,106]. School management committees were non-functional and completely unaware of their roles and responsibilities [107,108].Unavailability of disposal mechanisms for pads, poor water supply for washing or flushing, poor hygienic conditions of the toilets, lack of soap, washbasins, mugs for washing in the toilets, and no separate toilets for girls were major WASH challenges girls faced during menstruation. Broken lock/doors of the toilets were a matter of concern for the security of the girls in schools. These findings have been reported in 30 studies [26,33,72,77,78,95,102,105,106,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129]. There were gaps with respect to the non-availability of emergency supplies of sanitary materials in schools [26,69,72,78,95]. The girls in schools threw away sanitary pads or other menstrual articles in toilets or left the soiled wrapped pads at toilet corners due to lack of dustbins or separate place for disposal. As a result, the sewage system was blocked, or toilets became dirty, a breeding place for flies and mosquitoes, and unhygienic for other toilet users and cleaners [26,77,109]. Less than two-thirds of schools in India had dustbins with a lid for disposing of pads. The proportion of schools with bins having lids for the disposal of sanitary materials was 62%. [110]. Moreover, only 21% of girls could get pain relievers for menstrual cramps, and 37% told that absorbents were available in schools when needed [78]. Only 56% (PP 56%) schools in India had separate toilets for girls (95% CI 42% to 75%, I2 = 100%, n = 11) (Figure 4). Table 3 shows the characteristics of some of the studies that reported on the presence of separate toilets for girls in schools. In 2014, UNESCO, in its technical note, emphasized that male teachers in the schools might not be sensitized to the needs of girls, and hence, did not allow them to visit the toilet during their lecture. Male teachers perceived that girls were not interested in studies [130]. In other studies, it was reported that teasing by male teachers was common. This insensitive behavior might be fueled by ignorance, prevailing local myths, and cultural taboos related to menstrual blood among men [130,131]. As a result, topics such as puberty and menstruation were not included in the curriculum due to the predominance of male teachers in most of the schools [16,77]. There was a higher predominance of male teachers or administrators in schools, and they were hesitant to talk about MHM due to the gendered rooting of menstruation and cultural taboos related to it. It was reported that girls were often teased and subjected to embarrassment by boys and male teachers in schools due to the staining of their clothes during periods [130]. Moreover, because of the lack of knowledge about menstruation, boys displayed a negative attitude towards menstruation [132].Another barrier to a comfortable and dignified experience of MHM among girls was the lack of or limited awareness as reported in 92 studies (Table 2) [16,18,23,24,25,26,31,33,34,35,36,37,39,40,41,42,43,44,48,49,51,52,53,54,55,57,58,62,63,64,65,67,68,69,70,71,77,78,80,81,82,83,84,85,87,89,90,92,93,95,97,99,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172]. The lack of awareness led girls to think menstruation as a representation of sin, and menstrual blood as an impure entity. Schools were not reported often as a source of menstrual hygiene education [78]. On the contrary, 34 studies documented that a large proportion of girls (more than two-third) had high knowledge about menstruation [19,22,28,29,30,45,47,60,76,79,88,94,96,98,100,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191]. Among 122 studies with available information, the pooled prevalence of awareness about menstruation before menarche was 45% (95% CI 39% to 51%, I2 = 100%) (Figure 5). There was not much difference in the proportion of girls who were aware about menstruation before menarche between rural and urban areas (around 2%, not shown in the data).Limited data were available related to this component of MHM in schools. The study among schools across three states of India (Chhattisgarh, Maharashtra, and Tamil Nadu) reported that written materials about menstruation were infrequently available (19%) in schools [78]. In the global baseline report 2018, it was reported that around 64% of schools in India were providing menstrual hygiene education to female students [110].Safe waste management of used sanitary pads in schools was another major issue. Most of the schools lacked any such facility. The lack of facilities discouraged girls from using sanitary pads in schools or attending schools during menstruation [72,75,78,102,109,123]. School sanitation and hygiene education under the total sanitation campaign in Uttar Pradesh, the largest state in India, had the provision of installing incinerators in toilets of secondary schools, but none of the schools implemented the same [114]. It was reported in a study that only 27% of schools had good disposal facilities for menstrual waste on their premises (Table 3). The most frequently mentioned option for disposal was taking the soiled item home (21%) followed by burn pits (20%), rubbish pits (17%), bins (16%), and incinerator (7%). Incinerators were common in selected states and certain grades of schools [78]. It has been reported that some schools used incinerators or “feminine hygiene bins” for disposing menstrual waste material, but due to shyness or fear of being seen by others, they were not used. Sanitary napkin vending machines have been installed in toilets of some schools in Kerala, which are semiautomatic and operated by inserting a coin in it. It contained 30–50 sanitary napkins to meet the emergency needs of the girls/women in schools [109]. In the joint WHO-UNICEF baseline report 2018, it was reported that only 36% of schools in India had functional incinerators for disposal of sanitary wastes. Mizoram is the only state where more than 50% of schools have a functional incinerator for the disposal of sanitary waste. [110]. Thirty percent of the schools had good disposal facilities for sanitary products (PP 30%, 95% CI 13% to 69%, I2 = 100%, n = 2) (Figure 6). The concept of periodic monitoring of the data related to MHM practices in schools was in its nascence, and a key focus on measuring outcome indicators needs to be levied. To our knowledge, there was no school-based data on such measures.The first in the series of national-level directions on MHM for schools was the operational guidelines for the promotion of menstrual hygiene (2012) in rural areas [9]. The guidelines outlined the strategy to reach school girls through the adolescent education program. The key components of the school-based program were the provision of sanitary napkin distribution, health education, and incinerator for safe disposal. In 2014, the Ministry of health and family program launched the National Adolescent Health Programme known as Rashtriya Kishore Swasthya Karyakaram (RKSK), which levied clear guidelines for providing education, awareness, and support for better MHM using the peer education model. This national program worked at building protective factors that could help adolescents developing ‘resilience’ through both community and school-based interventions [192]. In the recent five years, sanitation and hygiene received a much-needed impetus from stakeholders of all spheres. With the launch of menstrual hygiene management guidelines in 2015 [7], the issue was streamlined into a formal agenda. The action guide laid down the suggestive measures to ensure menstrual hygiene friendly schools. The guidelines addressed the performance measurement with six indicators dedicated to assessing school performance based on MHM. However, there was a lack of detailing on the process and activity-oriented charting of the MHM framework, which schools would follow.Another milestone in this realm towards filling MHM gaps in schools was a comprehensive WASH assessment tool. It was operationalized in a three-year project led by the Urban Management center and supported by the government of Gujarat [193]. The tool underscored the need for MHM facilities and IEC across schools besides key components of WASH infrastructure assessment. The initiative (2014–2017) envisaged innovative approaches such as mobile application-based data collection for school sanitation surveys, competition-based approach to WASH improvement named as school swachh survekshan (cleaniness assessment), the concept of creating ‘model school’ based on Indian standard codes and Sarva Shiksha Abhiyan (a program for universal elementary education) standards with a positive environment for integrated learning, sports, recreation, and good access to WASH facilities. This joint action research program involved behavior change approaches such as IEC campaigns, school sanitation clubs, self-assessment tools for monitoring sanitation index, etc. [193].The push for MHM at an international level contributed towards sailing the agenda across nations, including India. Understanding the importance and growing interest in transforming the school environment for menstruating girls and female teachers, the “MHM in ten” members put forward a 10-year agenda (2014–2024). The five key action priorities of the plan revolved around building a strong cross-sector evidence base for MHM in schools, around developing and disseminate guidelines, do evidence-based advocacy, delegate responsibility, and integration with the education system [194]. The recently released Clean India: Clean Schools handbook underpinned the theme of securing a healthy school environment [195]. Installation of the napkin-vending machines and environmentally safe disposal mechanisms such as low-cost incinerators attached to the girls’ toilets in schools for disposal of used MHM products were major efforts in this direction. The government launched 100 percent oxy-biodegradable sanitary napkins under the name “Suvidha (facility)”. These sanitary pads were available under the scheme, entitled “Pradhan Mantri Bhartiya Janaushadhi Pariyojana” (Prime Minister Indian People Drug Scheme). The sanitary pads were made available at INR 1 in the drug dispensing stores created under the scheme. These napkins biodegrade automatically when it comes in contact with oxygen after being discarded [196].Menstrual health promotion in schools remains an issue of concern in India. Limited evidence was available on the different components of menstrual hygiene friendly school. Most of the evidence was available on two components, primarily girls’ awareness about MHM, and sanitation facilities in schools, leaving other components unaddressed. MHM in schools, although it was conceptualized comprehensively with different components as documented in guidelines, the data on its implementation was limited. There was a dearth of literature on education programs focusing on MHM in schools and knowledge, attitude, practices of mentors (teachers) who acted as an immediate source of information to girls. Although the data were available for the source of information about MHM (teachers), the studies on whether teachers as a source of information to girls had adequate knowledge about MHM were not available. We estimated that more than half of the girls did not have information about menstruation prior to menarche. Only 7% of girls reported teachers as a source of information for MHM. Menstruation hygiene education in school has most often being outsourced to non-governmental agencies [197,198]. Discrimination against female teachers to continue teaching in schools during periods was another example of a social barrier against menstruation. Not only did this practice disrupt the learning process, but it also perpetuated negative images among young minds and society [199].Research evidence revealed that lack of sanitation facilities in schools hindered the ability of girls to manage menstruation healthily, safely, and with dignity. Evidence showed how this aspect affected coping strategies of girls during menstruation [5]. Only 56% of schools had the facility of a separate toilet for girls. Appropriate menstrual waste disposal facilities were still lacking in the majority of the schools in the country. Studies reported that because of a lack of awareness and sanitation facilities, most of the girls did not change pads in schools [23,78,111]. Despite being emphasized in the education policies, display of MHM messages through information, education, and communication (IEC) materials were not routinely practiced in schools [200]. IEC materials such as posters, leaflets helped to reinforce the health promotion messages and supporting behavior change at large [201]. Although online monitoring of some of the WASH indicators in schools was done, MHM components were not included [202]. A lack of evidence on MHM management information system (MIS) data takes away the system of their efficacy in dealing with this social health problem at a large scale [203]. Other reviews have reported similar findings on one or more of the eight components of MHM friendly schools in India [15,204,205]. Our review highlighted minimal rural-urban differences in menstrual hygiene practices in schools. However, in the national-level survey, it was reported that more than 50% of the rural girls did not use hygienic methods of menstrual protection (girls who use locally prepared napkins, sanitary napkins, or tampons during their menstrual period) compared to 23% in urban areas [206]. The plausible explanation for this could be the heterogeneity in the included studies in our review. Furthermore, most of the studies had low quality scores. It is imperative to emphasize the four primary considerations to build effective evidence on MHM friendly school aspect. These are discussed further, below.Firstly, pre-service training of teachers on MHM with knowledge assessment at regular intervals is a crucial step in this regard since teachers are viewed as health promoters [195,207]. Teachers’ knowledge assessment can be a part of the regular school education surveys [13]. Furthermore, the sensitization of male teachers and boys on MHM is equally important. The provision of MHM-related education materials in schools such as booklets, flipcharts, and modules can be the cornerstone in enhancing the knowledge of teachers and girls [208].The second major issue is the urgent need for improvement in the sanitary facilities at schools. MHM was missing in the majority of the schools [194]. We found data that highlighted the poor sanitation facilities across the school, and effective implementation and monitoring on this aspect were awaited. Previously published meta-synthesis highlighted that the poorly supportive physical infrastructure, such as a lack of water and sanitation facilities, made it difficult for girls to practice MHM safely [208]. Waste disposal is of equal concern to make the school environment clean and healthy. The widespread reality of poor sanitary facilities and ignorance about menstruating girls’ needs in schools can make its experience a negative one resulting in increased dropout rates among girls [209]. The third major area is the efficient working of the school management committee with an emphasis on MHM services in schools. Regular monitoring and timely actions are crucial to transform poor MHM practices in schools. Lastly, an efficient MIS is paramount in constructing evidence-based planning for the policymakers and the education leaders. Improved management of supplies and data generation demands an MIS software to update school authorities and concerned departments in the government at regular intervals. The MIS software may generate monthly data regarding the menstrual supplies stock, availability of sanitation facilities across schools, count of the menstruating adolescent girls, and school preparedness towards maintaining sanitation friendly status [210]. The Education MIS under UNICEF’s WASH programs (Wins) in schools across 194 countries provides a classic example of robustness and usefulness of data monitoring [211].The multi-sectoral approach to MHM gaps in schools calls for convergence among various Departments such as Health and Family Welfare, Human Resource Development, Tribal Affairs, Woman and Child Development beyond the Department of Drinking Water and Sanitation. We need to leverage the use of resources and concentrated efforts to support school-based interventions for MHM. The different components to make schools menstrual hygiene friendly have been prioritized in other resources [212].The ad-hoc grant-based projects or pilot initiatives by external agencies on MHM in schools are essential for evidence generation, which can be scaled-up as cost-effectiveness solutions at the national or state level. WaterAid India and Vatsalya (Breaking the Silence program) in Uttar Pradesh were working with the schools and service providers to change the perception around MHM [213]. The program proactively engaged with boys, school teachers, and management committees. Another intervention called ‘the MHM curriculum’, implemented by WASH United India, adopted game-based approaches across schools to empower girls in overcoming the stigma around menstruation [214]. Under the broad school health-promoting framework, knowledge and perceptions around menstruation were addressed with the support of lay counsellors in the SEHER (Strengthening Evidence base on scHool-based intErventions for pRomoting adolescent health) project from Bihar. This randomized control trial advocated for the involvement of lay counsellors in transforming the school climate and improving adolescent health outcomes [105].Multiple non-peer reviewed anecdotal evaluation reports and articles documented that the implementation of such school-based MHM interventions was imperative to construct evidence. One such evidence was from a large-scale study covering 15 districts in India, called project JAGRITI, with menstrual hygiene promotion among adolescent girls as one of the components [215]. The program, run by the MAMTA-health Institute for Mother and Child, made a 10-step pragmatic guideline towards transforming schools into menstrual hygiene friendly with essential and desirable components (adapted from the National guidelines). Other national and state-level menstrual health players active in India are contributing to the availability of low-cost disposable sanitary material, MHM education to girls through comic books, training of facilitators, and researching on MHM behavior and practices [4].Poor menstrual hygiene practices can lead to potential long-term consequences such as dropping out of school, early marriage, restriction of mobility, agency development (capacity to act independently), menstrual irregularities, and other reproductive and mental health problems. Moreover, menstrual irregularities during reproductive age group are common in many gynecological diseases, such as endometriosis, which may affect mental and psychological well-being in long-term [216]. There are multiple challenges girls face in managing menstruation due to poor awareness about safe practices, limited access to sanitary products, sanitation, and lack of support from teachers or family members. Schools have emerged as an important delivery platform for health promotion interventions, which needs more consistent efforts to improve the health outcomes of young girls.The results of the review should be interpreted in view of some limitations. This review aimed to provide an overview of menstrual hygiene practices in schools. We could not produce a critically appraised and synthesized results for all the components of menstrual hygiene friendly schools. Heterogeneity between the included studies was very high, which might affect the validity of the pooled results. Most of the included studies were of low quality. The reports and peer-reviewed journal articles, which were publicly available, were included in our study. This limits our access to published literature in the public domain only. The study results might be considered in lieu of publication bias for positive findings because negative findings might not have been placed in the included reports and papers or papers and reports with negative findings may not have been published or made publicly available. MHM practices in schools are poor in India. Furthermore, we lack sufficient data to conclude the MHM situation in schools. The government has developed national level guidelines on all the aspects of MHM friendly school. However, its effective implementation on the ground is lacking. Still, MHM in schools is largely supported by outside agencies. Research on MHM in schools is mainly focused on observational studies to assess the knowledge and practices of girls regarding MHM. Moreover, research on the other aspects, such as waste management, teacher’s knowledge assessment, and management information, is limited.There is a wide scope of integrating various curriculum or non-curriculum-based actions on menstrual health education and establish schools as an ideal forum to disseminate MHM information. There is a need for transforming the existing infrastructure into menstrual hygiene friendly, which needs to be the priority area for all the schools (government or private). Simplifying the elaborated guidelines into pragmatic action points would help authorities and management committees to implement the program easily in all the schools. The increased momentum from international donors, small and medium-sized enterprises, and non-governmental organizations could be synergized and channeled into constructive outcomes for attaining improved menstrual health outcomes. The emerging scientific and innovative solutions from MHM projects could help policymakers in strategizing concentrated efforts in this direction. Moreover, expanding MHM accountability from sanitation and health ministries to other departments will help to improve menstrual hygiene conditions in the country multilaterally. To better understand the problems surrounding MHM for adolescent girls in school, the impact of MHM interventions, we need new research studies with expanded range of methodologies.The following are available online at https://www.mdpi.com/1660-4601/17/2/647/s1, Table S1: Description of the qualitative assessment of the studies included in the review, Table S2: PRISMA checklist. S.S. conceived and designed the study. S.S. and D.M. performed the literature search, and extraction and analysis of the data. N.B. supported in designing the search strategy. S.S. wrote the first draft of the paper, which was critically revised by N.B., D.M., and S.M. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors declare no conflict of interest.The figure depicts the photo of a well-designed toilet infrastructure in one of the States in India. Moreover, the figure depicts the eight components of menstrual hygiene friendly schools, which were used as the inclusion criteria for studies in this review. (MHM: Menstrual Hygiene Management).Search and exclusion criteria for literature review.Pooled prevalence of teachers as a source of information about menstruation to girls in India, from the included studies published until October 2019 (n = 86 studies). CI: Confidence Interval; SE = Standard error. I2: Heterogeneity; Squares represent proportions or prevalence. Lines represent 95% CI. Diamonds represent pooled prevalence.Pooled prevalence of schools with separate toilets for girls in India, from studies published until Oct 2019 (n = 11). CI: Confidence Interval; SE = Standard error; ASER: Annual Status of Education Report Centre. I2: Heterogeneity. Squares represent proportions or prevalence. Lines represent 95% CI. Diamonds represent pooled prevalence.Pooled prevalence of girls’ awareness about menstruation prior to menarche in India, from studies published until Oct 2019 (n = 122). CI: Confidence Interval; SE = Standard error; I2: Heterogeneity. Squares represent proportions or prevalence. Lines represent 95% CI. Diamonds represent pooled prevalencePooled prevalence of proportion of girls/student populations reported that schools had good disposal facilities for sanitary products, from studies published until Oct 2019 (n = 2). CI: Confidence Interval; SE = Standard error; I2: Heterogeneity. Squares represent proportions or prevalence. Lines represent 95% CI. Diamonds represent pooled prevalence.Characteristics of included studies related to menstrual hygiene friendly schools published until October 2019.¶North: New Delhi, Haryana, Jammu and Kashmir, Chandigarh, Himachal Pradesh, Punjab. Central: Chhattisgarh, Madhya Pradesh, Uttar Pradesh and Uttarakhand. East: Bihar, Jharkhand, Odisha, West Bengal, Meghalaya. West: Gujarat, Maharashtra, Rajasthan, Goa. South: Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, Puducherry, Telangana, Hyderabad.Characteristics of the included studies for teachers as a source of information about menstruation and girls’ pre-menarche awareness.* Percent girls aware about menstruation prior to menarche. ** Percent girls reported teachers as a source of information on menstruation. † Sample size for MHM awareness and ‡ Sample size for teachers as a source of information; C*= Chhattisgarh; M*= Maharashtra; T*= Tamil Nadu.Characteristics of the included studies for separate toilet for girls and good disposal facilities for sanitary products.C*: Chhattisgarh; M*: Maharashtra; T*: Tamil Nadu. β In Sivakami et al. study, it is the proportion of girls reporting on the presence of disposal facilities in schools. Abbreviations: ASER: Annual Status of Education Report Centre; NA: Not Available.

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+In this study, the characteristics and distribution of the organic phosphorus (Po) fractions in the surface sediments of seven inflow rivers around Hongze Lake in China were analyzed with a soil Po fraction method, as used by Ivanoff. The relationships between the Po fractions and physiochemical features of sediments were also discussed. The results showed that, the sediments of the rivers had been moderately pollution with certain ecological risk effects except the Waste Yellow River. The relative contribution order of the Po fractions in the sediments was residual Po > HCl-Po > fulvic acid-Po > humic acid-Po > labile organic phosphorus (LOP). Moderately labile organic phosphorus (MLOP) was the main part of the Po forms in the whole sediments. The risk of phosphorus released from river sediments was the highest in the western region, followed by the southwestern region, and finally the northwestern region. There were significant correlations between Po forms and total phosphorus (TP), inorganic phosphorus (Pi), and Po. Non labile organic phosphorus (NLOP) had the strongest correlation with TP. The distribution of Po forms in each region was different due to the impact of human activities, industrial and agricultural production and the land types; the heaver polluted sediments with higher Po fractions. It is suggested that most of the sediments of the inflow rivers in the regions have certain ecological risk effects and P of them have an important contributions on the eutrophication of Hongze Lake. Po forms can provide a reliable theoretical basis for dealing with the change of water quality and should be paid more attention in the lake eutrophication investigation. There was reciprocal transformation between different Po forms, especially non-bioavailable fraction can change into bio-available ones. The results can provide a basis for the earth cycle of phosphorus and a new perspective of eutrophication control of shallow lakes.Phosphorus (P) is an essential nutrient for aquatic organisms and is a limiting nutrient for primary production in lake ecosystems [1,2,3], so excessive phosphorus (P) is a key factor for eutrophication [4]. Over the last few decades, the external inputs of P have been gradually reduced; however, the release of internal P from the sediments of lakes to the overlying water has become a significant source of P [5,6]. These may cause continuous eutrophication in lakes, even after control of external inputs [7]. Therefore, the various chemical interconversions of phosphorus, biological effectiveness, the exchange between the sediments and overlying water have been widely studied [8,9]. However, not all the fractions of phosphorus can be released from sediments, and cause lake eutrophication [10,11,12]. Accordingly there are many extraction methods for phosphorus fractions in sediments [13]. Most of them divide the fractions into two parts: inorganic phosphorus (Pi) and organic phosphorus (Po) [14]. The Pi fraction is composed of exchangeable phosphorus, Fe, Al, Mn oxides-bound phosphorus and Ca-bound phosphorus. Po refers to various Po compounds which include nucleic acids, phospholipids, inositol phosphates, sugar phosphates, condensed P, etc. [15]. However, most former studies have mainly focused on the compounds of Pi. In fact, the internal source of Po is the important part for constituents of P [16]. Microbial degradation and mineralization of Po compounds play a vital role in the migration and transformation of P, and may result in Po becoming Pi in the overlying water to participate in the geochemical cycle [17]. A large number of studies show that the relative contribution of Po in the sediments can reach 80.0% of total P [18]. However, until now, investigations of the species, quantification, concentrations, dynamics, biogeochemical cycling and ecological significance of these organic P compounds have been limited due to its complexity and the limitations of analytical methods [19].For these reasons, in recent years, sequential extraction schemes have been developed based on the assumption that chemical extractants selectively dissolve discrete groups of Po [20]. These methods were first used in soils then in sediments. Bowman and Cole [21,22] developed the first integrated scheme for separating soil Po into four distinct fractions: labile Po, moderately labile Po, moderately resistant Po, and highly resistant Po. Hedley et al. [23,24] used a simple method that rapidly separated and analyzed Pi and Po from environmental samples into several fractions, and then quantized the microbial biomass-P. Then Ivanoff et al. [25] divided Po into three fractions: labile Po; moderately labile Po, containing HCl-Po and fulvic acid-P; and non-labile Po containing residual Po and humic acid-P. The method greatly increased the Po recovery by using additional steps and prolonging the extraction time for each Po fraction. The pH value of fulvic acid-Po and humic acid-Po was reduced to 0.2, which made the separation more strict and had no effect on the recovery of organic phosphorus. This also increased the analysis of residual Po. Fan et al. modified some aspects of the Bowman Cole system. They changed the division of highly resistant Po and moderately resistant Po according to pH 1.0–1.8. This method can significantly increase the content of labile Po and resistant Po, but decrease the content of moderate Po, which may be related to the order of extraction. Up to now there has been no standard fractionation system for Po in sediments [26].In the last twenty years, the booming economy of China, with fast development of agricultural and industrial activities, has led to serious eutrophication of the hydroecological sytem [27,28]. The second national investigation surveyed 138 lakes with an area of more than 10 km2, and the results showed that 85.4% of the lakes have eutrophication issues, and almost half of them (>40%) are hyper-eutrophic lakes [29]. Wu et al. investigated 22 typical lakes of China, and found that 59.1% of the lakes presented a certain degree of eutrophication [30]. Hongze Lake is the fourth largest freshwater lake in China [31]. Experts at home and abroad have done a lot of work in the aspects of pollution source control, total amount of nutrients in sediment, distribution of the nutrient elements forms, sediment transport and dredging etc., but the lake eutrophication is still serious. In recent years, agriculture and aquaculture around Hongze Lake have developed rapidly; traditional agriculture and aquaculture promote the accumulation of phosphorus in sediments. As a lake, Hongze Lake has become the intersection of the main and tributaries of the upper reaches of the river basin [32]. In view of this, it is not comprehensive to only pay attention to the nutrient elements in the water body and sediments of the lake itself. The characteristics and distribution of nutrient elements especially the limiting nutrient P fractions in the sediments of the rivers flowing into the lake should be studied. The characteristics and distributions P forms in the sediments of the rivers flowing into the lake directly affects characteristics and distribution P fractions the in the sediments of the lake, thus affecting the eutrophication level of the lake. Based on our investigation, there are few researches on the fractions of P in the sediments of the rivers flowing into the lake, let alone the systematic research and analysis on the relationship between Po forms in the sediments of the rivers flowing into the lake through the land use types [33,34,35]. Therefore, it is of great significance to study the characteristics and distribution of Po components in the sediment of the inflow rivers around Hongze to basis for eutrophication control in lakes and geochemical cycle of phosphorus.The objectives of the present study were to: (1) investigate physiochemical features in the surface sediments of inflow rivers around Lake Hongze; (2) investigate the characteristics and distribution of Po fractions and the bioavailability in the surface sediments of the study areas according to the land use type sediments, and (3) analyze the relationships between Po and physicochemical nature of the sediments.We take the northwest to southwest of the Hongze Lake Basin as the research area. Seven tributaries or main stream sediments were selected in the basin as the research objects. The distribution of sampling points is shown in Figure 1.Hongze Lake, located in the northwest of Jiangsu Province (33°06′–33°40′ N, 118°10′–118°52′ E), is a shallow water lake with a water area of 1597 km2, a maximum water depth of 4.37m, an average water depth of 1.77 m, a water storage capacity of 27.9 × 108 m3 and a shoreline of 354 km. The lake area has monsoon climate characteristics, which is regulated by the Hongze Lake water body, with four distinct seasons. The annual average precipitation is 925.5 mm, and the rainy season is mainly from June to September [36,37]. There are six counties along the lake, namely Xuyi, Hongze, Sihong, Siyang, Huaiyin, and Jinhu. The rivers entering the lake, which include the Huaihe River, Sui River, Huaihongxin River, Xinbian River, and Xuhong River, are mainly concentrated in the west. The rivers leaving the lake mainly include Huaishuxin River, Subei irrigation channel, Huaihe River water channel, and Huaihe River water channel, of which the water volume entering the river accounts for 60–70% of the total water volume leaving the lake. The annual average flow into the lake is 33 billion m3, and the water exchange rate reaches 11 times per year. As a hub connecting the middle and lower reaches of the Huaihe River, Hongze Lake and Huaishuxin River connect the Huaihe River system with the Yi, Shu, and Sishui systems. It is necessary to not only regulate and control the flood in the upper and middle reaches, but also to store part of the incoming water, which irrigates a large area of farmland in Northern Jiangsu, and protects the safety of more than 20 million people and 2 million square hectares farmland in the Lixia River area in Northern Jiangsu. The east line of the South to North Water Transfer Project in China will also transfer 400 m3/s of water northward through Hongze Lake. However, with the aggregation of human activities, Hongze Lake has become the main receiving water body of industrial wastewater and domestic sewage in the upper and middle reaches of the Huaihe River, and water pollution has reduced the ecological service function of Hongze Lake [38,39].In this study, 65 sampling points were set up using a grasp sampler in June 2015 and 2016, with a sampling depth of 0–10 cm. the sampling points numbered C1 toF11 are located on the Waste Yellow River, X1to X11 are on the Xuhong River, A1 to A10 are on the An River, S1 to S8 are on the Sui River, B1 to B9 are on the Bian River, XH1 toXH9 are on the Huihongxin River, and H1 to H7 are on the Huaihe River. Each sediment sample (a composite of samples from five nearby sampling sites) was immediately put into air-sealed plastic bags and storage in a heat preservation box with ice (about 4 °C). Then, the collected sediments were freeze-dried, crushed, passed through standard 100-mesh sieves and stored at 4 °C in the dark until further analysis. Sediment pH was determined on sediments suspended in deionized water at a ratio of 1:2.5 [40]. Total Fe, Al, Mg, Mn, and Ca were detected by a PW2440 type ray fluorescence analyzer from Panaco (Panaco, Almelo, Netherlands). The organic matter (OM) was measured after treatment with K2Cr2O7/H2SO4 according to Walkey–Black method [41]. Total nitrogen (TN) used the concentrated H2SO4 digestion method [42]. After addition of 5 mL 1M H2SO4 and 0.5 g of K2S2O8 and autoclave digestion during 30 min at 121 °C, total phosphorus (TP) in the extract was determined [43]. Inorganic phosphorus (Pi) was checked by direct extraction with 1 M HCl (16 h), and then analyzed through colorimetry using the molybdate blue method and organic P (Po) in the extract was calculated as the difference between total P and inorganic P [44].A sequential extraction method used to obtain different forms of Po based on the Ivanoff et al. scheme [45], presented in Figure 2. Po is divided into labile Po, moderately labile Po, and non-labile Po fractions. Firstly, labile Po was extracted with 0.5M NaHCO3 at pH 0.5. The extracted Po was mainly called the loosely adsorbed Po on the sediment colloids. The moderately labile Po was extracted with 1.0M HCl followed by 0.5 M NaOH. The NaOH extract was acidified to pH 0.2 with 37% HCl, and the non-labile component (humic acid-Po) was isolated from the appropriate fraction (fumic acid-Po). Finally, by buffering the residue extracted by NaOH, the non-labile segmentation is determined by high resistance H2SO4 dissolved to 1 M at 550 °C for 1 h. Each extraction step is performed at room temperature in an orbital shaker running at 4500 r/min. TP in all extracts was calculated with an aliquot that was digested with K2S2O8 and H2SO4. Po in the samples was calculated by the difference between TP and Pi.The whole samples were analyzed in triplicate and the results are expressed as the average values. The distribution of sampling points was drawn by ArcGIS (ESRI, Redlands, CA, USA). The descriptive statistical analyses were conducted using the SPSS ver. 23.0 statistical software package (IBM, Armonk, NY, USA). Charts were plotted using the Origin 9.0 software (OriginLab, Northampton, MA, USA).The general characteristics and physiochemical features of lake sediments are shown in Table 1.The average value of the four metal elements in the study area was Al > Ca > Fe > Mn. The average value of Ca ranged from 3.38% to 6.03%, with the order Bian River > Sui River > Huaihongxin River > Huaihe River > An river > Xuhong River > Waste Yellow River. The concentrations of Ca in Hongze Lake basin were higher than other basins in the middle of China, such as the Tiaoxi basin [46,47]. This may be related to the large amount of calcium carbonate deposition in the soil of the study area [48]. The spatial variation of trace elements in the sediments of Mn was the largest, followed by Fe. The spatial variations of trace elements in the sediments were related to the different soil patterns, hydrodynamic forces, geographical environments and the different land use patterns, such as land for farming, also influenced the concentrations of them [49,50]. As a whole, the sediments of the seven rivers were weakly alkaline. The mean values of pH varied from 7.47 to 8.59. The order is the same as Ca. pH was significantly correlated with Ca (R = 0.914, p < 0.01, n = 65). Carbonate calcium is greatly affected by environmental pH, which easily forms precipitation in alkaline environments and is easy to dissolve and release in acid environments.OM is one of the most important colloids in sediments, mainly derived from many kinds of residual of authigenic alga and bacteria. It can absorb, distribute, and complex with heavy metals and organic pollutants, which is an important indicator to reflect the organic nutrition level of sediment [51,52]. The order of OM is Bian River > Sui River > An river > Huaihong River > Huaihe River > Waste Yellow River > Xuhong River, with the range from 0.89% to 2.11%.TN ranged from 840.96 mg·kg−1 to 1130.62 mg·kg−1; TP ranged from 488.90 mg·kg−1 to 960.22 mg·kg−1. OM, TN, and TP showed a great spatial difference. However, the sequence of OM, TN, and TP was the same.TN and TP also had a positive correlation with OM (R = 0.827, R = 0.697, p < 0.01, n = 65). Concentrations of OM, TN, and TP in the sediments were consistent with the trophic status of those studied lakes. In sediments of the seven rivers, the pollution was more and more serious from northwest to west and from southwest to west. Bian River was the most polluted, then the Sui River. This was because the rivers of the west were far away from the cities. Along the rivers, aquaculture and agriculture are relatively developed. Domestic sewage and industrial waste water are not centrally disposed.Exogenous input is the main factor affecting TP and TN, and the concentrations were higher in the heavily polluted areas. According to the Sediment Quality Guidelines issued by the Ministry of Environment and Energy of Ontario (Canada), when the concentration levels of TP exceeds 600 mg·kg−1 and TN exceeds 600 mg·kg−1 in the sediment, it can cause the lowest level of ecotoxicity effect [53]. With the conclusion of Liu [54], when TP < 500 mg·kg−1 in the sediment, there had been no pollution; when 500 mg kg−1 < TP < 1000 mg·kg−1 in the sediment, there had been moderate pollution, so in addition to the Waste Yellow River, the sediments of rivers from the northwest to the southwest of Hongze Lake Basin had a certain ecological risk effect and had been moderate pollution with certain ecological risk effects. For the whole region, the nitrogen/ phosphorus (N/P) of the sediments ranged from 1.17 to 1.72, far less than the Redfield ratio (C: N: P = 106:16:1). On the one hand, this reflects that the phosphorus in the sediments is mainly imported from land. Due to the different geological structure, landform, land use type, vegetation damage, and surface runoff erosion, a large number of phosphorus-containing substances are brought in by land-based sources of rivers entering the lake. On the other hand, this reflects that the biochemical action of the sediment the sediment–water interface in shallow lakes is intense, and the dissolved oxygen with low concentration causes nitrogen (N) to be lost due to mineralization and degradation, while P is enriched in the sediments [55,56].From Figure 3 and Figure 4, Pi was the main content of TP, ranging from 321.74 mg·kg−1 to 731.34 mg·kg−1, accounting for 65.81–76.15% of TP. Po ranged from 167.16mg·kg-1 to 228.88 mg·kg−1. Relative contributions were 34.19%, 33.30%, and 32.61% for Waste Yellow River, Xuhong River, and An River, respectively. The population mean was 33.84% for the northwestern region. It was the highest among the southwestern region, named Huaihongxin River (27.85%) and Huaihe River (32.17%) with the population mean at 30.18% and the western region, including Sui River (24.82%) and Bian River (23.83%) with the lowest population mean at 24.58%. Except for point B1, the concentration of TP at the entrance of each river to the lake was the highest value of the river. One reason was that the dynamic condition of the lake inlet was poor, and the sediments were easy to accumulate, which lead to the increase of the concentration of TP. The higher concentrations of TP in the sediments of the lake inlet will affect the concentrations of TP in the water of Hongze Lake, which will finally increase the risk of eutrophication of Hongze Lake. The concentration of TP in the sediment of B1 was lower, it may because that there was a large amount of land used for growing grass. Grassland can reduce the concentration of nutrients in sediment [47]. The increase of TP concentration in each river was accompanied by the increase of Pi and Po concentration, but the percentage of Po in TP decreased with the increase of TP concentration. This was consistent with the results of Jin’s study [57], and the proportion of Po in relatively clean sediments is relatively high. This fully explained why a part of Po had transformed into Pi, and on the other hand, there were some external source inputs in the rivers. The different distributions of TP, Pi, and Po were related to pollution sources and land patterns. The western region was the most seriously polluted of all, as along these two rivers there were mainly rural areas or the suburbs of towns where agriculture was the main activity and there was no sewage collection system for domestic sewage and scattered industrial wastewater; they discharged into the river in a non-point-source way. The land use type was mainly cultivated land and grassland, long-term unreasonable fertilization and improper disposal of livestock manure, resulting in serious agricultural non-point source pollution. In addition, due to a large number of cage cultures in the rivers, with the increase of organic food, animal and plant residues and other nutrients and organic matters, the river sludge increased, the nutrient load of sediment was heavy, and most of the water body was eutrophicated. The northwestern region was polluted the least. Although the three rivers were near the city Suqian or town Siyang, some of the sample points were inside the city or town, such as F10, F11, etc. The density of the urban population and the development of industry might bring a mounting of exogenous P input, but the point-source pollutions in the city and town were collected and controlled better for disposal. Along the Waste Yellow River and Xuhong River there were some protective wetlands and primary protection areas of water sources. In addition, the upper reaches of Waste Yellow River collected the river called Chenzi River; it had abroad riparian zone and wide river surface. A large hydrodynamic force, strong self-purification capacity and light nutrient load of sediment in the river area might be the cause of the observed lower concentration of P [58]. Not long before our sampling, sediment dredging had been carried out on the Xuhong River. This might another reason for the lower of concentration of P. The southwestern region was the second. The water quality of Huaihe River has been improved through years of treatment. However, the Huaihongxin River is near the western region, and the industrial structure, lifestyle, and sewage discharge around it were similar to those in the western region.Po is mainly deposited in the processes of river input, human emission, metabolism of aquatic animals, and plants. Its content will directly affect the availability level of soluble P required by primary productivity [59]. Po can be used to roughly estimate the formation and degradation of organic matter. It is a better indicator of eutrophication than TP [60]. The organic phosphorus in sediment can be divided into labile organic phosphorus (LOP), moderately labile organic phosphorus (MLOP), and non-labile organic phosphorus (NLOP) composed residual Po and fumic acid–Po. Distributions of organic phosphorus in the sediments of seven rivers are shown in Table 2: There recovery of Po ranged from to 95.45% to 106.57%, with an average of 101.6%. This indicated Po in sediments was sufficiently extracted with this method.LOP is the most active component of Po, which has high biological efficiency. However, this part of phosphorus was also the least in the form of Po. Its percentage content was the key factors for the degradation of Po mineralization to Pi [61]. The LOP of sediments ranged from 10.47 mg·kg−1 to13.55 mg·kg−1, and the average was 11.81 mg·kg−1, the only relative contribution was 5.66% to6.52%, and the average only 5.94% of Po, less than 7% in the soil [62]. The sequence of percentage content of LOP in river sediments was Waste Yellow River > Xu River > An River > Huaihe River > Huaihongxin River > Sui River > Bian River. The region order was northwestern > southwestern > western.Obviously, the higher the pollution degree, the lower the contributions of LOP. The difference of contribution of LOP indicated that the contribution of polluted sediment released to overlying water through mineralization is higher than that of less polluted sediment, which has a greater impact on eutrophication of rivers [63].MLOP included HCl–Po and fulvic acid-Po. It is the most active component in the Po, which has a certain biological effectiveness. On the whole, the concentration of MLOP ranged from 87.51 mg·kg−1 to 105.20 mg·kg−1, with the relative contribution of Po at 43.93% to 54.47%. MLOP was the same as LOP, where the concentration was higher in heavily polluted sediments, and the percentage decreased. HCl–Po was the main part of the MLOP, the chemical components are mainly phosphate ester, phospholipid, nucleic acid, phosphoprotein, and phosphosaccharide, which are easily, decomposed bio-macromolecules with poor stability. Under certain conditions, they can be hydrolyzed or mineralized, decomposed into soluble small molecule organic phosphorus or soluble phosphate, and have potential biological effectiveness through migration and diffusion of pore water [64,65]. In the study area, a higher polluted degree with higher concentration, ranged from 36.07 mg·kg−1 to 79.78 mg·kg−1, accounting for 22.45–33.32% of Po. Huang Qinghui et al. found that the release of acid extractable organic phosphorus from sediments may be one of the important processes leading to lake eutrophication in the study of Lake Taihu, Chaohu, and Longgan in the east of China. Hua Liping et al. also put forward the same view in the study of Lake Baiyangdian in the north [66]. In addition, some studies have shown HCl–Po/Po can reflect the difference of lake eutrophication levels [67]. HCl–Po/Po for Sui River and Bian River both exceeded 0.3, the highest of the other regions. This can further indicates that HCl–Po may be an important source of phosphorus for rivers, which can well reflect the eutrophication level of rivers, and provide a new theoretical basis for the establishment of aquatic environment quality standards and the assessment and prediction of lake eutrophication in the future [68]. Fulvic acid-P has relatively weak potential bioavailability due to its solubility. The release of it under anaerobic conditions is a process of Po mineralization under the mechanism of microbial enzymology. It accounted for 10.62–32.02% of Po.NLOP was the least active component of Po, with low bioavailability. It consisted of humic acid–Po and residual Po with relative contributions of 7.71–13.41% and 25.61–42.70% of Po. The concentration and the percentage of NLOP increased with the increase of pollution degree, it was different from LOP and MLOP. The NLOP relative contribution of Bian River was over 50% to Po.In this study, the relative contribution of bio-available organic phosphorus (LOP + MLOP) [69] in rivers with light pollution is higher than that in rivers with heavy pollution, and the increase of the bio-available phosphorus concentration in water becomes potential endogenous phosphorus pollution in lakes, which is consistent with other research results. In general, the risk of phosphorus released from river sediments was the highest in the western region, followed by the southwestern region and finally the northwestern region. The MLOP is the main form of Po of the sediments in the northwestern and southwestern region. However in the western region the NLOP was the capital form of Po. This may be because the western region had the highest OM. In the high organic matter, the organic phosphorus components that can be degraded and deposited by organic matter are far-reaching and mineralized. In the case of weak water exchange capacity, they are absorbed by particulate matter and enter the sedimentary facies in the form of organic matter, resulting in changes in the composition of the sediment, so most of the refractory organic phosphorus components are easy to deposit [70]. Zhang et al. [71] found that the inactive organic phosphorus is only a relative chemical solubility, the main components such as phytate phosphorus can be absorbed and utilized by microorganisms and plants, and still have potential biological activity under certain conditions. The concentration of NLOP in the seriously polluted river is higher than that in the lightly polluted river, which shows that the non-active organic phosphorus also has an important impact on lake eutrophication. The order of the relative contribution order of organic phosphorus in each river was residual Po > HCl-Po > fulvic acid–Po > humic acid–Po > LOP with the ratio of 5.77:5.14:3.04:1.86:1.The relationships between Po fractions and physiochemical features are shown in Table 3:There was a significant correlation between Ca and MLOP (R = 0.911, p < 0.01, n = 65). It might be that MLOP mostly existed in the form of calcium. NLOP had a significant correlation with Fe (R = 0.933, p < 0.01, n = 65). This showed that NLOP was easily an effective carrier of Fe [72]. There were significant correlations between Po fractions and TP, Pi, and Po. This showed that the source of phosphorus in sediment was consistent. Among them, the correlation between NLOP and TP was higher (R = 0.934, p < 0.01, n = 65), than with the Pi (R = 0.930, p < 0.01, n = 65). This proved the viewpoint of Zhang [71]: NLOP was an important component of total phosphorus, which can be converted into Pi under certain conditions. It was a potential phosphorus source of sediment. We can further analyze whether NLOP is the carrier of Fe from Corum, K.W.’s atomistic modeling of mineral–water interfaces theory [73], which is one of the important reasons for NLOP to become a potential phosphorus source. The main mechanism is a problem to be further studied.Po fractions were also strongly positively correlated with OM and TN. This was consistent with previous results [74]. Generally speaking, the organic phosphorus in the lake ecosystem mainly comes from the mixed input of the terrestrial, marine, and authigenic Po, and the Po in the sediment is mainly controlled by the OM. The study on Wuli Lake in Taihu Lake [74] showed that in the early diagenesis process of the sediment, the organic phosphorus was released preferentially when the internal OM in the lake degraded, and the degradation was as follows: The OM can be released or even released to the organic matter during the early diagenesis. It is similar to the application of organic fertilizer in the soil, which can increase the soil Po and redistribute the soil OM pool. The cation exchange capacity and the Po with lower activity form may be released. The high correlation of mass fraction is due to the fact that the organic exchange group in the surface colloid of sediment is mainly composed of humic acid, while LOP provides more organic exchange groups and forms more exchangeable organic–inorganic complexes on the surface of sediment. Humic acid binding P does not belong to bio-available phosphorus, which is not necessarily related to the occurrence of lake eutrophication.(1) The sediments of the whole rivers had been moderately pollution with certain ecological risk effects, except the Waste Yellow River. Except for point B1, the concentration of TP at the entrance of each river to the lake was the highest value of the river. It is suggested the higher concentrations of TP in the sediments of the lake inlet will finally affect the concentration of TP of Hongze Lake, which will lead to a risk of eutrophication of Hongze Lake. (2) The characteristics and distribution of Po fractions were different in rivers with different pollution levels, suggesting that Po fractions were indicators of eutrophication and should be paid more attention in an- lake eutrophication investigation. (3) Non labile organic phosphorus (NLOP) had the strongest correlation with TP. It may also suggest that NLOP can transfer into a potential source of available P for aquatic phytoplankton and bacteria, although it was considered as the non-bioavailable fraction.In the process of eutrophication treatments of shallow lakes that rivers flow into, more solicitude should be shown for non-point source pollution and internal phosphorus of the lake. However, the contractions of Po fractions and the transformation of different forms of Po in the sediments of the upstream rivers can’t be neglected, which should be paid more attention. What’s more the transformations between the Po fractions are complex. We can use 31P-NMR to research the mechanism of the transformation of internal Po in the sediments in the further investigation to help controlling the eutrophication. Additionally, the concentrations of phosphorus forms in the sediment of the inflow rivers have a certain contribution to the eutrophication of the shallow water lake, but the specific contribution degree needs to be further fitted with the water quality model.Conceptualization, J.W. and X.Y.; Funding acquisition, X.Y., H.Y. and X.Y.; Investigation, J.W. and H.Y.; Project administration, X.Y.; Software, L.H.; Writing—review & editing, X.Y. All authors have read and agreed to the published version of the manuscript.This research was support by NSFC project (41372354, 41601540), class a science and technology project of Education Department of Fujian Province (JAT170591), The key science and technology plan project of Nan Ping City (N2017T02) the Natural Science Key Foundation of Education Committee of Anhui Province (KJ2019A0153). The author also wishes to thank you the assistance from the Key Laboratory of Surficial Geochemistry, Ministry of Education of Nanjing University.The authors declare no conflict of interest.The map of sampling points. North western rivers: Waste Yellow River (F and C); Xuhong River (X); and an River (A); western rivers: Sui River (S); and Bian River (B); south western rivers: Huaihongxin River (HX); and Huaihe River (H).Fractionation procedure of organic phosphorus (Po) fractions in the sediments.Concentrations of P fractions in the sediments of the seven rivers. Organic phosphorus (Po), inorganic phosphorus; (Pi), phosphorus (P).Relative contribution of P fractions in the sediments of the seven rivers. Total phosphorus (TP).Characteristics and physiochemical features of sediments. The organic matter (OM), total nitrogen (TN), total phosphorus (TP), inorganicphosphorus (Pi), organic phosphorus (Po), nitrogen/phosphorus (N/P). Coefficient of Variation (C/V).Distributions and the recovery of different Po fractions in the sediments. Labile organic phosphorus (LOP) moderately labile organic phosphorus (MLOP) and non labile organic phosphorus (NLOP), total extracted phosphorus (OPEX).The relationships between Po fractions and physiochemical features.** p < 0.01; n = 65.

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+Although nurses work in stressful environments, stressors in such environments have yet to be clearly assessed. This study aimed to develop a Nurses’ Occupational Stressor Scale (NOSS) with high reliability and validity. Candidate questions for the NOSS were generated by expert consensus following focus group feedback, and were used to survey in 2013. A shorter version was then developed after examination for validity and reproducibility in 2014. The accuracy of the short version of the NOSS for predicting nurses’ stress levels was evaluated based on receiver operating characteristic curves to compare existing instruments for measuring stress outcomes, namely personal burnout, client-related burnout, job dissatisfaction, and intention to leave. Examination for validity and reproducibility yielded a shorter version of NOSS with only 21 items was considered sufficient for measuring stressors in nurses’ work environments. Nine subscales were included: (1) work demands, (2) work–family conflict, (3) insufficient support from coworkers or caregivers, (4) workplace violence and bullying, (5) organizational issues, (6) occupational hazards, (7) difficulty taking leave, (8) powerlessness, and (9) unmet basic physiological needs. The 21-item NOSS proved to have high concurrent and construct validity. The correlation coefficients of the subscales for test-retest reliability ranged from 0.71 to 0.83. The internal consistency (Cronbach’s α) coefficients ranged from 0.35 to 0.77. The NOSS exhibited accurate prediction of personal burnout, client-related burnout, job dissatisfaction, and intention to leave.As highlighted by the International Labour Organization [1], occupational stress is an increasingly global phenomenon which affects workers in all workplaces and countries. Nurses are known to have high work demands, high occupational stress, high rates of burnout [2,3,4], low job satisfaction [5], to experience workplace bulling [6], and may have mental health problems [7]. Job stress and burnout result from the cumulative effects of stressors in nursing work, and may consequently influence patient outcomes [8,9,10] and nurses’ intention to leave their jobs [11,12]. In accordance with the statistics of Taiwanese National Union of Nurses Associations (TUNA), presently only about 60% of licensed nurses in Taiwan practice [13]. However, Singapore and Australia have around 86.1% and 98.5% in active practice, respectively [14,15]. TUNA found 57.28% nurses had intention to leave nursing profession, and the three major reasons were about “salary and bonus”, “heavy workload” and “work–life imbalance”. Ref. [16] In the study of 10 European countries [17] showed 27.1% nurses considered to leave the workplace, and their perceptions of nursing practice environment was an important factor of retention.In addition to applying stress management interventions to reduce stress [18], as recommended by Happell et al. [19], an initial step toward reducing occupational stress is to understand the stressors present in nurses’ work environments as well as the methods through which these stressors may be eliminated. Not only qualitative researches have been performed to look for nursing stressors [19,20], but several self-report scales have been developed to measure nursing stress indicators in hospital environment, such as Expanded Nursing Stress Scale (ENSS) [21], and Practice Environment Scale of the Nursing Work Index [22]. However, stressors vary widely in different cultures and are highly influenced by health care systems. Examples of variations include those in frequencies of on-call duty, patient-to-nurse ratios, reliance on patients’ families for daily partial care, regulated break times, and monetary compensation for overtime work. Additionally, although scales for measuring nursing stressors have been developed, measurements of psychological stress among nurses, including burnout, job dissatisfaction, and intention to leave, are rarely reported. The study developed a Nurses’ Occupational Stressor Scale (NOSS) to identify comprehensive nursing stressors. The scale was evaluated for validity and reliability and to examine relationships among stress indicators.Two cross-sectional studies were conducted to develop an instrument to measure nurses’ occupational stressors. This study was divided into three phases: (1) generation and pilot testing of candidate questions, (2) condensation of the scale according to validity and reproducibility, and (3) examination of accuracy of the condensed NOSS for predicting stress outcomes.In 2013, candidate questions for the NOSS were pilot tested on nurses who worked in hospitals with “excellent” ratings under the New Hospital Accreditation of 2012 in Taiwan. The condensed NOSS was tested in 2014. Participants were recruited from the population based on conformity and excellence under the New Hospital Accreditation between 2010 and 2013. The research protocols were approved by Research Ethics Committee of National Taiwan University Hospital with the approval numbers of 20130807RINC and 201407075RINA. Exemption of written consent was approved, and returned questionnaires were regarded as nurses’ willingness to participate in the study. No ethical issues occurred during the study period.Stratified random sampling for the questionnaire surveys in 2013 and 2014 was conducted. Electable hospitals were sampled in proportion by hierarchy. The hospital managers were invited to approve the study via phone call. Nurses were recruited from multiple wards, namely the internal medicine ward, surgical ward, maternity and pediatric ward, intensive care unit, operating room, emergency department, psychiatric department, and outpatient department. The questionnaires were mailed to the participating hospitals and delivered to nurses. All returned questionnaires were previewed by the researchers and then recorded through optical mark reading.The questionnaires were self-administered. The participants’ demographic characteristics, work environment traits, levels of personal burnout, client-related burnout, job satisfaction, and intentions to leave were inquired.A Chinese version of the Copenhagen Burnout Inventory (C-CBI) was developed with high internal consistency, constructive validity, and criterion-related validity [23]. Personal burnout and client-related burnout are two subscales in the C-CBI, containing five and six items, respectively, to assess the frequencies of specific scenarios within the preceding week on a 5-point Likert scale (0 to 4 representing “never” to “always”). Following Chin et al. [24], the cut-off point for nurses in the high burnout group was set as the 90th percentile.Job dissatisfaction was assessed by the answer “somewhat unsatisfied” or “very unsatisfied” to the question, “Generally speaking, are you satisfied with your job?” Intention to leave a nursing job was assessed by the following three items: (1) Answering “unlikely” or “uncertain” to the question, “Do you intend to remain in your job for at least 2 more years?” (2) Obtaining a score of 7 or higher on the item, “Please rate your intention to leave on a scale of 0 to 10, with 0 being no intention to leave and 10 being highly considering leaving.” (3) Answering “once a month” or “more frequently” to the question, “How often do you think about leaving your job?”Data analysis was performed using JMP statistical software version 10.0 (SAS Institute, Cary, NC, USA). Descriptive statistics were calculated to summarize demographic characteristics. Test-retest reliability and internal consistency were examined by analyzing test-retest correlations and Cronbach’s α scores. Content validity was assessed by experts. Construct validity was calculated through common factor analysis. The suitability of factor analysis was inspected using the Kaiser–Meyer–Olkin (KMO) test [25] and Bartlett’s test of sphericity [26]. For all analyses, p < 0.05 was considered statistically significant.The procedure for developing the NOSS is described sequentially as follows: information collection, content confirmation, format design, pretesting, panel discussion, expert validation, pilot study, and content determination.After the literature review, the content of the NOSS was constructed according to research goals, and by referring to the questionnaire titled “survey of perceptions of safety and health in the work environment in 2013 Taiwan” [27] and the work–family conflict scale [28]. The researchers had the pretest to find unsuitable wordings and expert panel discussions for suggestions and clarification. The expert panel was composed of three professionals in the fields of nursing, psychiatry, and occupational medicine and six nurses from primary, secondary, and tertiary hospitals.Expert validity was assessed after revision of the panel discussion. The experts were the aforementioned three professionals on the panel. NOSS items were scored on a Likert-type scale (1 and 2: modification required; 3: related; 4: strongly related). After alteration or deletion of inadequate items (scores lower than or equal to 2), the content validity index of the NOSS was 0.81.A total of 72 hospitals rated “excellent” under the 2012 Hospital Accreditation were our target hospitals. Of these 72 hospitals, 13 were tertiary hospitals, 41 were secondary hospitals, and 18 were primary hospitals. In 2013, Stratified random sampling and questionnaire survey of 7 tertiary, 10 secondary, and 2 primary hospitals was conducted. A total of 2956 questionnaires were issued and 2796 were returned. After exclusion of men, nurse managers, nurse practitioners, and incomplete questionnaires, 1781 questionnaires were deemed eligible for analysis. The effective response rate was 60.3%.The participants’ demographic characteristics are summarized in Table 1; their mean age was 30.3 years, most were single (64.3%), and most had an educational level of college or above (63.1%). The average total working tenure was 8.6 years.The internal consistency scores assessed by Cronbach’s α were 0.92 for personal burnout and 0.90 for client-related burnout. The mean scores for personal burnout and client-related burnout were 63.9 and 47.9, respectively. Of the participants, 15.5% harbored intentions to leave their jobs.The KMO score (0.93) and Bartlett scores (chi-square statistic = 51,378.93; degrees of freedom = 990; p < 0.001) indicated that factor analysis may be practical. Common factor analysis was performed to assess the construct validity of the NOSS, resulting in 10 factors with eigenvalues greater than 1.0 (Table 2). Relying on the assumption that the dimensions of the scale were correlated or uncorrelated, we implemented Varimax (orthogonal rotation) and Promax (oblique rotation) both. The outcomes showed that Varimax and Promax grouped the same items into 10 factors. The cumulative variability of these extracted 10 factors explained by varimax was 51.8%.A convenience sample of 50 hospital nurses from northern, central, and southern Taiwan was invited to assess test-retest reliability; 36 pairs of test-retest questionnaires were completed. Test-retest reliability scores were calculated through Pearson’s correlation with a 2-week interval. The Pearson’s correlation coefficients of the 10 subscales were 0.75, 0.72, 0.74, 0.75, 0.72, 0.75, 0.71, 0.76, 0.72, and 0.61. The test-retest reliability of the whole NOSS was 0.84.Most NOSS items were scored on a 4-point Likert scale (1 to 4 representing “strongly disagree” to “strongly agree”), whereas 5 items were reverse scored. The average total score of the NOSS was 107.1 (SD = 14.2), ranging from 65 to 158. A higher score indicated a higher frequency of work stressors experienced by the participant in question. Cronbach’s α was used to measure the internal consistency. The internal consistency scores of the 10 NOSS subscales were 0.88, 0.92, 0.87, 0.86, 0.35, 0.63, 0.86, 0.78, 0.06, and 0.63. The internal consistency of the whole NOSS was 0.89.The initial NOSS underwent a condensation process to reduce item numbers. All items on the condensed NOSS were selected from the original NOSS. Items were examined as independent variables, and personal burnout, client-related burnout, job dissatisfaction, and intention to leave were set as dependent variables. The selection algorithms were based on predictions of dependent variables and reliability. Items with favorable prediction were prioritized for inclusion in the condensed scale and those without favorable prediction or low reliability were re-examined through panel discussions.First, common factor analysis of the 43 items selected for the condensed scale yielded 10 factors (Table 2): “work demands”, “work–family conflict”, “insufficient support from coworkers or caregivers”, “workplace violence and bullying”, “organizational issues”, “occupational hazards”, “difficulty taking leave”, “powerlessness”, “interpersonal relationships”, and “unmet basic physiological needs”. Since the item numbers differed among factors, the total score of each factor was adjusted to between 0 and 100. Table 3 presents the areas under the receiver operating characteristic curves (AUCs) used to examine sensitivity and specificity. Forward stepwise with a p value of 0.1 was implemented to examine predictions of indicators under each of the 10 factors. Factors 1, 2, 4, 6, and 7 were significantly related to personal burnout (AUC = 0.79). Factors 1, 2, 3, 4, 7, and 8 were significantly related to client-related burnout (AUC = 0.80). Factors 1, 2, 6, 7, and 10 were significantly related to job dissatisfaction (AUC = 0.75). Factors 1, 2, 4, 5, 7, and 10 were significantly related to intention to leave (AUC = 0.75). Factor 9—interpersonal relationships—was not significantly related to any indicators.The stability of the NOSS was assessed through evaluation of test-retest reliability. The values of the 10 factors ranged from 0.61 to 0.76. After setting the minimum stability value of 0.70 [29], factor 10—with a stability value of 0.61—was revised.A range of 0.3–0.7 was set for internal consistency reliability by recommendation [30]. The internal consistency reliability of the NOSS factors ranged from 0.35 to 0.92, except for factor 9 (0.06). Prominent items were preserved to represent the concept of each factor. Because of the conceptual similarity between factor 9 (interpersonal relationships) and factor 3 (insufficient support from coworkers or caregivers), two items of factor 9 (“I am worried that the incompetence of my colleagues will affect patient safety” and “The primary caregivers do not execute their tasks appropriately”) were reclassified under factor 3 and all other items under factor 9 were omitted.After revision, the participants for the confirmation survey were sampled from 417 hospitals in 2014. A total of 71 candidate hospitals (1 tertiary, 7 secondary, and 63 primary hospitals) were sampled. A total of 3974 nurses were recruited, and 3786 returned the questionnaires. Under the same exclusion criteria as those of the 2013 survey, 2655 questionnaires were deemed eligible for analysis, yielding an effective response rate of 66.8%. The participants’ demographic characteristics are shown in Table 1.Of 50 nurses who worked in primary, secondary, and tertiary hospitals in Taiwan, 48 completed the test-retest study within one week. According to Pearson’s correlation, the p values of the nine factors ranged from 0.71 to 0.83. The test-retest reliability of the overall 21-item NOSS was 0.76.Table 4 presents the item-to-subscale correlations. The Cronbach’s α scores of the subscales ranged from 0.35 to 0.77 except for “workplace violence and bullying”, which contained only one item, and thus lacked internal consistency reliability. The internal consistency of the 21-item NOSS as a whole was 0.91.To examine predictions of intermediate markers by the original and condensed NOSSs, the two scales were compared with respect to personal burnout, client-related burnout, job dissatisfaction, and intention to leave (Table 5). The AUCs for the indicators ranged from 0.73 to 0.82 on the condensed NOSS. Among the participants of the first year survey, the AUCs for the original 43-question version ranged from 0.75 to 0.80 and those for the condensed version ranged from 0.75 to 0.81. These results suggested that the condensed NOSS might be equally sensitive and specific to the original NOSS for predicting nurses’ stress outcomes.The process of the NOSS development is illustrated in Figure 1.This study constituted the effort to develop a stressor scale for nurses in Asia.Despite measurements for stress reactions being used extensively, workplace factors, namely stressors among hospital nurses, are rarely characterized or quantified. The ENSS contains 57 items and was tested on 2280 randomly selected nurses; the scale was found to be correlated with overall life stress items and health problem indices [21]. The NOSS has three major advantages: (1) comprehensive assessment of nursing work traits that could interfere with life, including occupational hazards, workplace violence and bullying, difficulty taking leave, and unmet basic physiological needs; (2) 21 items only, so relatively little time required for completion; and (3) comparisons with four important stress indicators in both surveys and reasonable prediction of these outcomes.This section discusses the results of using factors of the NOSS and indicators for confirmation. Burnout is regarded as a response to job stressors correlated with excessive direct contact with patients [3,31]. Hence, “work demands”, “insufficient support from coworkers or caregivers”, and “workplace violence and bullying” [6,12] may be reasonable factors for predicting personal burnout and client-related burnout. Work–life conflict was regarded as a strong predictor of burnout [32,33]. Consequently, the relationship between “work–family conflict” and burnout is predictable. According to the World Health Organization [34], ergonomic hazards is one of potential health hazards among health care workers. Studies conducted in Hong Kong and Japan have revealed that manually lifting patients or heavy objects is a risk factor associated with musculoskeletal disorders such as lower back pain [35,36]. Other researchers observed that lower back pain was related to personal burnout [37]. Thus, it seems plausible that “occupational hazards” factor is associated with personal burnout. Taking a sick leave or a leave for family-related reasons is not easy for Japanese nurses; without substitutes, other nurses need to work harder or more hours to compensate. Thus, nurses may feel guilty about taking leaves, and inability to take leaves could lead to burnout or even overwork death [38]. The “difficulty taking leave” factor may reliably predict burnout. Items under the “powerlessness” factor have been verified as being associated with client-related burnout. Due to higher frequency of suffering patients contact, nurses might experience greater compassion fatigue than other professionals [3]. Burnout can easily occur among those caring for dying people [39], and the associated feeling of powerless and the inability to deliver effective care to such people could cause moral dilemmas and burnout [40].Researchers observed a negative relationship between job satisfaction and nursing tasks left undone [41]. Furthermore, nursing care may be forced out of a work schedule by non-nursing tasks, and neglected nursing care was found to be a strong predictor of intention to leave [42]. These findings may match the relationships of the “work demands” factor with job dissatisfaction and intention to leave in the study.Confrontations with patients and their families may be another nursing stressor [43]; however, the relationships of this item with job dissatisfaction and intention to leave were nonsignificant. A study among physicians revealed that job satisfaction decreased and intention to leave increased when “work–family conflict” increased [44]. Besides, nurses were dissatisfied with inadequate protective equipment when caring for highly infectious patients [45]. This may support our finding of a relationship between “occupational hazards” and job dissatisfaction. In a meta-analysis [46], availability and use of work–family support policies positively related to job satisfaction and intention to stay. In short, the “difficulty taking leave” factor may reliably predict burnout, job dissatisfaction, and intention to leave. For decades, nurses’ meal breaks and rest breaks have been regarded as a factor possibly related to job satisfaction and intention to stay [47]. Instances of nurses holding their urine or decreasing their water consumption were recorded [48]. Accordingly, the items categorized under the “unmet basic physiological needs” factor may be common in Taiwan and China.One item on the NOSS is rather culturally unique; despite patients’ family members not being intuitively recognized as having such collegial relationships as those that nurses have with patients, family members have long made commitments to care for hospitalized patients because of the Chinese value of filial piety [49]. Because hospitals reduce nursing manpower to minimize costs, a portion of care depends on family members or private attendants. Therefore, unsurprisingly, “feeling stressed because primary caregivers do not execute their tasks appropriately” predicts client-related burnout.“I have to maintain professional units other than my own” was found to be related to personal burnout, client-related burnout, job dissatisfaction, and intention to leave. These outcomes were observed when nursing units had temporary shortages of personnel. However, one would imagine the nurses who worked in another unit could face unfamiliar medical equipment, coworkers and an unfamiliar environment. These likely induce additional stress.This study had some limitations. First, males were excluded. The distribution of male nurse in our study was 2.4% (n = 46) and that in Taiwan was approximately 1.6% at the time of the study [13]. Because the exclusion of male nurses had no impact on the results (data not shown), only female nurses were analyzed. Second, questionnaires with any missing item were excluded to ensure the accuracy of developing NOSS, which was the major reason of effective response rates less than 70%. There was not significant different of participants’ demographics between valid and invalid questionnaires (data not shown). Third, the NOSS was developed for hospital nurses; thus, the scale might not be applicable to clinics or nursing homes. Fourth, nurses unable to adapt to given work environments, had left the profession, or had transferred to less stressful environments were not included. Therefore, a healthy worker effect or healthy worker survival effect [50] may be present, and this could have led to underestimation of stress in the study. Fifth, although a single factor is suggested to include at least three items [51], we decided not to ignore less items to detect nursing stressors due to uniqueness of nursing clinical environment. Accordingly, factor 4 had only one item and factor 6, factor 7, factor 8, and factor 9 had only two items. The AUCs of the first- and second-year observations revealed that the 21-item NOSS may be adequate for predicting indicators of common stress among nurses. Finally, our questionnaire did not contain items about participant’s income, economic burden or job insecurity. As described in previous studies, global economic crisis could have caused hospital budgets reduction, and consequently led to medical supply shortage, increased workload and job insecurity [52,53]. Thus, economic crisis was regarded as an important stressor related to workers’ mental health status [52]. Further studies may consider financial factors while assess nursing practice environment and related outcomes.The strengths of the study are described as follows. First, this study analyzed a nationally representative sample based on stratified sampling. Second, in both surveys, rather large numbers of nurses completed the questionnaire, enabling examination of factors and their relationships with stress indicators. Third, the identified stressors in this study were individually related to the subscales of burnout, job dissatisfaction, and intention to leave. The identified stressors can be applied in other countries if pretesting for comparisons with stress indicators is conducted.This current study developed NOSS, which identified nine groups of occupational stressors in nursing practice environments, as well as predicting personal burnout, client-related burnout, job dissatisfaction, and intention to leave. Using this scale, stressors in nurses’ work environment can be measured, and while intervention is applied, the effectiveness of such intervention can be evaluated.Conceptualization, J.-J.H. and J.S.-C.S.; data curation, Y.-C.C. and J.S.-C.S.; formal analysis, Y.-C.C., Y.-L.L.G., Y.-J.L. and J.S.-C.S.; funding acquisition, J.-J.H.; investigation, Y.-C.C. and Y.-J.L.; methodology, L.-C.L., Y.-L.L.G. and J.S.-C.S.; project administration, P.-Y.H. and J.S.-C.S.; resources, P.-Y.H.; supervision, J.-J.H. and J.S.-C.S.; validation, L.-C.L. and Y.-L.L.G.; visualization, Y.-C.C.; writing—original draft, Y.-C.C., Y.-L.L.G. and J.S.-C.S.; writing—review and editing, Y.-C.C., Y.-L.L.G., L.-C.L., Y.-J.L., P.-Y.H., J.-J.H. and J.S.-C.S. All authors have read and agreed to the published version of the manuscript.This research was supported by the Institute of Labor, Occupational Safety and Health, Ministry of Labor, Taiwan. Grant number: ILOSH 103-R328 and ILOSH 104-A315.We thank Wei-Shan Chin for statistical recommendations. We are grateful to the volunteer participants, and appreciate the financial support from the Institute of Labor, Occupational Safety and Health, Ministry of Labor, Taiwan.The authors declare no conflicts of interest.The process of the NOSS development.Participant characteristics.Factor loadings for items loaded on 10 factors of the 43-item Nurses’ Occupational Stressor Scale (NOSS) through varimax rotation.Note: Factor loadings of >0.32 are recognized on the subscale. a SARS: severe acute respiratory syndrome; AIDS: acquired immune deficiency syndrome. b Transfer of percentages to scores are explained as follows: 0%–25% = 4, 26%–50% = 3, 51%–75% = 2, 76%–100% = 1. Items not classified under any factors in the table: “I cannot complete my duties or required tasks during working hours” and “In the preceding month, I have used _______ hour(s) of my free time to handle documents from the hospital for accreditation or unit-related affairs”.Personal burnout, client-related burnout, job dissatisfaction, and intention to leave as indicators for item retention on the NOSS (N = 1781).Note: OR: odds ratio; AUC: areas under the receiver operating characteristic curves. * p < 0.05, *** p < 0.001. a The standardized total score for personal burnout was ≥ 65. b The standardized total score for client-related burnout was ≥ 95. c “Somewhat unsatisfied” and “Quite unsatisfied” were classified as job dissatisfaction. d Intention to leave was defined as “unlikely to or uncertain about staying in the job for another two years”, “score on the scale of leaving the job ≥ 7”, and “thinking about leaving once in a month or more frequently”.Statistics of the 21-item NOSS (N = 2655).Revision and confirmation of the NOSS.a What was originally factor 9 was deleted and factor 10 became the new factor 9 in the 21-item NOSS.

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+Approximately 50% of preschoolers do not meet physical activity recommendations and children who reside in low-income rural communities may be further at risk for higher levels of sedentary behavior. Outdoor play is essential for preschool children; however, literature is unclear as to which types of interventions elicit moderate-to-vigorous physical activity (MVPA) for all preschoolers. The aim of this study was to determine which type of intervention, physical activity or fundamental motor skill focus, elicits MVPA during outdoor play. Ninety-eight preschool children (M age = 4.48 years) from one Head Start center participated in an outdoor play intervention two days per week for 7 weeks. Classes were randomly assigned to one of four groups: fundamental motor skill focus (FMS), physical activity focus (PA), FMS and PA (FMS + PA), and control. An accelerometer worn on the hip measured MVPA. Results showed that age, sex and group assignment contributed to MVPA at the beginning of the intervention and age, sex, group assignment and MVPA during the beginning of the intervention contributed to MVPA at the end of the intervention. Overall, the FMS + PA group elicited MVPA from males and females of all ages. Interventions that combine both FMS and PA may reduce physical activity disparities in preschool children.Physical activity is essential for growth and development in young children and is associated with improved physical, behavioral, cognitive, and social outcomes [1,2]. In addition, physical activity is a contributing factor to decreasing the likelihood and rates of several chronic diseases among children [3]. Whereas, sedentary behavior is associated with cardiovascular disease and all-cause mortality in adults [3], and cardio-metabolic risk factors in children [4]. Current physical activity guidelines recommend preschool-aged children engage in three hours of light, moderate and vigorous physical activity throughout the day [3,5]. Although the benefits of physical activity are well documented, approximately 50% of preschool-aged children do not meet physical activity recommendations [5,6] and preschool children spend most of their time in sedentary activities [7].Fundamental motor skills (FMS) and motor competence are related to physical activity participation in young children [8]. Previous research indicates that physical activity intensity increases during FMS practice, particularly in locomotor skills [9], suggesting that involvement in FMS may lead to increased physical activity levels and greater health benefits. In fact, a review by Figueroa and Anor [10] examined the relationship between motor skill competence and physical activity participation in preschoolers and found that a positive association between motor skill competence and physical activity participation has been consistently documented. Many of the studies included in this review utilized a cross sectional design, and thus, the strength of the relationship between motor skill competence and physical activity participation may be influenced by individual factors such as biological sex [11], age, and current level of physical activity [12]. However, a recent study examining motor competence across a large sample of children aged 3–6 years residing in the United States shows that approximately 77% of the sample examined were classified as delayed in FMS [13]. Thus, these children may be at an increased risk for lower levels of physical activity and potentially poorer health.The low levels of physical activity coupled with delays in FMS calls for the development of intervention strategies aimed at children who demonstrate low levels of physical activity and FMS. Children from low-income families generally demonstrate a greater risk for lower physical activity, as well as long-term health disparities [14,15,16] and low and moderate socio-economic status schools provide fewer physical activity practices [17]. In addition, children who reside in rural, minority, and impoverished communities often demonstrate even lower levels of physical activity and higher levels of sedentary behavior than children who reside elsewhere because rural environments often lack the resources, infrastructure and supports to provide quality physical activity experiences [18]. Moreover, physical activity is influenced by demographic factors such as race and sex. African American and Hispanic children engage in less physical activity than non-Hispanic Caucasian children in the US [19]. Young females engage in less physical activity [20,21] and show further delays in FMS compared to males [13].According to the National Center for Education Statistics, 40% of three-year-olds, 68% of four-year-olds, and 86% of five-year-olds were enrolled in preschool programs in 2017 [22], making preschool centers an ideal location to implement physical activity programs for young children. In order for preschool facilities to meet physical activity recommendations, they must provide opportunities for children to increase physical activity, as well as, engage in a variety of gross and fine movement activities [23]. Ward [24], Gordon [25], and their colleagues evaluated the evidence regarding the effectiveness of intervening in childcare centers and reported that environmental modifications (e.g., portable play equipment, floor markings) improve young children’s physical activity levels. The meta-analysis conducted by Gordon et al., [25] showed a small to moderate effect on preschoolers’ overall physical activity and a moderate effect on their level of moderate-to-vigorous physical activity (MVPA). These results support the notion that the early learning environment is an ideal setting to facilitate MVPA in preschoolers. A more recent review also reported a small but positive effect of childcare center interventions in increasing physical activity in young children [26]. Furthermore, these authors highlight the importance of outdoor play in increasing children’s physical activity levels.Although evidence suggests that FMS and physical activity are interconnected, preschool interventions that examine outdoor play either focus on improving physical activity or FMS outcomes [10]. For example, a review by Gray et al., [27] investigated factors related to physical activity during outdoor play and found only one study out of 28 that examined motor skills. However, studies that have examined outcomes of play interventions in preschoolers have shown that interventions with a FMS focus can support physical activity [28]. For example, Wadsworth et al., [28] examined the effect of a year-long FMS focused intervention on physical activity levels in preschoolers and found that the intervention significantly increased physical activity compared to unstructured free play. What is not clear throughout the literature is if interventions aimed at improving FMS would confer a greater advantage over interventions that are specifically aimed at increasing physical activity levels directly. Furthermore, although both FMS [13] and physical activity [26] interventions have shown different effects for biological sex, no effort has been made to determine which type of intervention would be most beneficial for girls who consistently demonstrate lower physical activity and ball skills compared to their male counterparts. Finally, it is not clear how interventions should be tailored to benefit all children regardless of age, sex, and current level of physical activity, all of which have been postulated to influence physical activity outcomes [26]. This information is vital, as the relationship between motor skill competence and physical activity may be influenced by individual factors such as biological sex [11], age, and current level of physical activity [12] as well as environmental factors (e.g., setting, climate, intervention focus). Therefore, the aim of this study was to determine which type of intervention, physical activity or FMS focus, promoted greater levels of participation in physical activity for all preschool-aged children during outdoor play.Ninety-eight (52 males, 46 females) preschool children aged 3 to 5 attending a local federally subsidized Head Start center participated in this study. Table 1 shows demographic characteristics of the sample. This particular center serves children and families who reside in low-income housing from surrounding rural communities. Preschool hours were from 8:00 am–12:30 pm and included breakfast (8:00–8:30), curriculum instruction including small/large group, centers and outdoor play time (8:30–11:30), lunch (11:30–12:00) and dismissal (12:30). A purposeful sampling was implemented as previous literature suggests that children from lower socio-economic status in rural communities are: (a) at risk for poor health, (b) more susceptible to developmental delays, and (c) do not meet recommended guidelines for physical activity [14,15,16,18].Prior to data collection, this study was evaluated and approved by the Institutional Review Board and meets the latest Declaration of Helsinki (The protocol number for the approved IRB is: 06–262 EP 0701). Before gaining institutional approval, members of the research team met with the parental advisory council for the center to gain approval and input for the study. An informational letter and consent form were sent to the parents via weekly take-home folders. Out of a possible 106 children, 98 (92%) returned signed parental consent forms and assented to participate in the study. In terms of racial demographics, 92.9% of the sample was black, 5.1% Hispanic and 2% were white. Eight classrooms were randomly assigned to one of four high-autonomy groups: fundamental motor skill focus (FMS), physical activity focus (PA), fundamental motor skill and physical activity focus (FMS + PA) and a control group. As the relationship between motor skill competence and physical activity may be influenced by individual factors such as biological sex [11], age, and current level of physical activity [12] as well as environmental factors (e.g., setting, climate, intervention focus) [28,29], we hypothesized that preschool children randomly assigned to the PA and FMS + PS would exhibit higher levels of physical activity at the end of the intervention compared to preschool children in the FMS focused and control group. We also hypothesized that sex and MVPA in the beginning of the intervention would influence levels of physical activity at the end of the intervention.The physical activity program began in January and concluded in April, and was located on two outdoor playgrounds at the Head Start center. Physical activity data were gathered during outdoor play two times per week over nine weeks via accelerometry (Actigraph GT3X). Data were collected for a total of 14 sessions (7 weeks) with interruptions in data collection due to spring break (2 sessions) and a week of inclement weather (2 sessions). Each session lasted for 30 min and consisted of six to eight activity stations. Accelerometers were worn on the right hip and attached with an elastic belt by a researcher prior to the outdoor play and removed after outdoor play.The control group consisted of free play on the outdoor playground (no instruction). The physical play environment for the three experimental groups were high autonomy such that children were allowed to have complete autonomy over which stations they participated in, how long they stayed at these particular stations, as well as, who they played with (if anyone) while visiting these stations. A high autonomy climate was chosen because interventions for preschoolers utilizing high autonomy outdoor play is associated with higher levels of physical activity compared to free play, with children in high autonomy climates spending significantly more time in MVPA compared to free play (36% of time compared to 7%) [29]. High autonomy climates are also associated with improvements in fundamental motor skills for preschoolers [30] and considered developmentally appropriate for preschool children.Each intervention play period consisted of six to eight stations that focused on FMS (hopping, running, galloping, jumping, throwing, catching, striking and dribbling) and physical activity. The stations for each experimental group were the same; however, the instructors manipulated the focus of the experimental condition. All equipment in all four conditions were the same and included a variety of balls, hoops, mats, goals, ground markings and ample space for movement.For the FMS group, the instructors encouraged the children to learn motor skills by providing constant instruction and feedback regarding the technique and form of the skills at each station. At the beginning of each FMS session, a teacher would help the children warm-up by demonstrating FMS that corresponded to each station and the effective techniques for success from an FMS perspective. During the session, the teachers would provide feedback on FMS technique and proper FMS practice. For example, if a child in this group visited an overhand throwing station, the instructor would provide them with cues such as “reach your arm back” and “step with the opposite foot” to emphasize the importance of correct form in sport performance. If a child visited a station with running, the feedback was focused on proper form, including cues for “bent elbows, light on feet or toes and run tall”.For the PA group, the instructors primarily encouraged the children to participate in as much physical activity as possible, regardless of whether or not they correctly performed the motor skill. At the beginning of the session, teachers helped the children warm-up by demonstrated possible physical activities at each station (running, hopping, dancing, etc.) and emphasized how much physical activity they could participate in. During the session, instructors constantly emphasized the importance of physical activity in health and sport performance. For example, at that same throwing station, the children were encouraged to throw the ball but the emphasis was on chasing the ball as fast as they could and retrieving it in order to exercise their heart and get physical activity. At a station that included galloping or running the emphasis was on doing as much as possible for as long as possible, versus proper execution of the skill. During this condition, the instructors never gave instruction on skill development.For the FMS + PA group, the instructors equally encouraged the children to perform their skills correctly and encouraged children to get as much physical activity as possible. The warm-up consisted of both FMS instruction and physical activity and demonstrated both at each station. Instructors not only emphasized the importance of physical activity and exercise, but also addressed the importance of motor skill development. For example, a child at the throwing station was given cues such as “turn to the side before you throw” and also encouraged to retrieve the ball they threw. At a jumping station the child was encouraged to pull “both arms back and explode”, as well as, “to run through the station and try again.” The control group participated in unstructured free play on the opposite playground on the same days of the intervention. The equipment that was accessible to the control group was the same as the experimental conditions; however, no formal instructions were given.Behavioral Fidelity. In order to confirm that each experimental condition conformed to the parameters defined, two reviewers viewed videotapes of eight 10-min lesson segments that were selected at random from each of the four conditions. These segments were evaluated on criteria from a modified climate fidelity checklist [31]. The checklist was modified to reflect how reinforcement and feedback were given in the climates in context to the four experimental conditions. For example, during the PA condition, was feedback and reinforcement given on physical activity or motor skill instruction? Fidelity assessments showed that overall the experimental groups met the criteria 99.3% of the video segments assessed. Specifically, the FMS group met the criteria 99.4%, the PA group met the criteria 97.8% and the FMS + PA and the control group met the criteria 100%. Agreement between the two reviewers was 96.4% across all four conditions.Participants’ date of birth, sex, and race were provided by parents on the parental consent form. Height and weight were measured in a private setting with children dressed in light clothing and shoes removed. Height was measured to the nearest 0.25 cm using a portable stadiometer. Weight was measured to the nearest 0.1 kg using a precision electronic scale.Physical activity data were collected during the program on Tuesdays and Thursdays for a total of 7 weeks using Actigraph GT3X triaxial accelerometers (Mini-Mitter Co., Inc. Bend, OR, USA). Accelerometers were worn on the right hip and attached with an elastic belt by a researcher prior to the outdoor play and removed after outdoor play. ActiLife software was used to extract data, validate wear time, and compute physical activity levels. Each accelerometer was calibrated for each child based on height, weight, sex, and age according to manual guidelines. The accelerometers were programmed with 15-s epoch, which is recommended for preschool children [11] and MVPA was quantified by Butte [32] cut points. The cut-points correctly classified MVPA compared to direct calorimetry and double labeled water approximately 80% of the time. Previous studies report the reliability of the Actigraph accelerometer for preschoolers as 0.90–0.94 [33]. MVPA data were averaged across Tuesday and Thursday for each week.MATLAB (Version R2017a, Natick, MA, USA) was used for all statistical analyses with a level of significance p < 0.05. A stepwise linear regression (stepwiselm) was conducted to determine if there were differences in the percentage of time spent in MVPA during the first two weeks of the intervention. The stepwiselm function in MATLAB uses a sequential process in which the criterion for model terms to be added is based on the p-value of the F-statistic less than 0.05. At each step, the stepwiselm function checks for linear dependencies (i.e., if a term is redundant with another term). If a term is linearly dependent, the function removes the redundant term. The full model included the following terms: group (categorical-control, FMS, PA and FMS + PA), age (continuous), and sex (categorical-male, female). Interactions amongst these factors were also included in the statistical model. To determine differences in the percentage of time spent in MVPA during the last two weeks of the program and the factors that influenced these changes, a similar stepwise linear regression was run. The full model included the following terms: percentage of time spent in MVPA for the first two weeks of the program (weeks 1 and 2 averaged) as a covariate, group (control, FMS, FMS + PA, PA), age (continuous), and sex (male, female). Interactions amongst these factors were also included in the statistical model. Comparison of significant effects and interactions were decomposed using two sample or paired t-tests.Table 1 shows the participants demographics. There was no difference in age between the four groups (F(3,94) = 0.26, p > 0.05) at the onset of the intervention.Table 2 presents the means and standard deviations for each group by sex for weeks 1 and 2 and weeks 6 and 7, as well as the results from the paired t-tests (with Cohen’s d, and p-values) conducted comparing weeks 1 and 2 and weeks 6 and 7 for each group by sex. The only participants that showed a significant increase in MVPA from weeks 1 and 2 to weeks 6 to 7 were the females in the control group (t(10) = −5.15, d = −1.56, p < 0.001). It is important to note that the interventions are underway during week 1 and 2, therefore, null results regarding changes from week 1 and 2 to weeks 6 and 7 for the intervention groups (FMS, FMS + PA, and PA) do not signify that the interventions were not successful.Figure 1 shows the percent of MVPA by group across the intervention. Indeed, although overall, there was a small increase in MVPA across the weeks of the intervention for the control group, the other groups maintained the same relative position across the weeks of the intervention (with the exception of the FMS group for week 2).The stepwise linear regression examining the factors that influence the percentage of time spent in MVPA for weeks 1 and 2 revealed main effect for Age (F(1,86) = 4.98, p < 0.05), where there was age-related increase in the percentage of time spent in MVPA for weeks 1 and 2. There were also main effects of Sex (F(1,86) = 6.52, p < 0.05), Group (F(3,86) = 18.85, p < 0.001), as well as a significant Sex x Group interaction (F(3,86) = 4.82, p < 0.01; Figure 2 Top). The full model accounted for 49.1% of variance (F(1,86) = 10.4, p < 0.001). Follow-up analysis of the Sex x Group interaction via two-sample t-tests revealed that the males in the Control group had significantly less time spent in MVPA for weeks 1 and 2 compared to the males in the FMS group (t(22) = −7.87, p < 0.001, d = −3.30) and males in the PA group (t(24) = −5.16, p < 0.001, d = −2.11). In addition, males in the FMS group spent significantly more time in MVPA for weeks 1 and 2 compared to the males in the FMS + PA group (t(22) = 3.57 p < 0.001, d = 1.44) and males in the PA group (t(26) = 3.64, p < 0.001, d = 1.37). For the females, those in the Control group had significantly less time spent in MVPA for weeks 1 and 2 compared to the females in the FMS group (t(22) = −3.53, p < 0.001, d = −1.44), FMS + PA group (t(21) = −3.01, p < 0.01, d = −1.24) and PA group (t(20) = −2.40, p < 0.05, d = −0.99). All other comparisons were not statistically significant (p > 0.05).The stepwise linear regression examining the factors that influence the percentage of time spent in MVPA for weeks 6 and 7 revealed main effect Age (F(1,76) = 6.61, p < 0.05), Group (F(3,76) = 3.07, p < 0.05), a Sex × Group interaction (F(3,76) = 2.77, p < 0.05; Figure 2 bottom), and an interaction between Age × percentage of time spent in MVPA for weeks 1 and 2. (F(1,76) = 6.27, p < 0.05; Figure 2). The full model accounted for 30.6% of variance (F(1,76) = 3.36, p < 0.01). Follow-up analysis of the Sex x Group interaction via two-sample t-tests revealed that after accounting for all other covariates, the males in the Control group spent significantly less time in MVPA for weeks 6 and 7 compared to the males in the FMS group (t(19) = −2.61, p < 0.05, d = −1.15), males in the FMS + PA group (t(19) = −3.08, p < 0.01, d = −1.38), and males in the PA group (t(21) = −2.51 p < 0.05, d = −1.05). In contrast, for the females, the difference in MVPA for weeks 6 and 7 between the controls and the other groups were not statistically significant (p > 0.05). For the follow-up analysis of the Age × percentage of time spent in MVPA for weeks 1 and 2 (Figure 3), the participants were split based on the median percentage of time spent in MVPA for weeks 1 and 2 (Low < 35%; High > = 35%). After accounting for all other covariates, a significant age-related increase in the percentage of time spent in MVPA for weeks 6 and 7 was observed for the Low group (F(1,40) = 8.20, p < 0.01, R-squared = 0.17), but not for the High group (p > 0.05).This study examined which type of intervention, physical activity or FMS focus, promoted greater levels of MVPA for all preschool-aged children during outdoor play. Our hypotheses were partially supported in that individual factors (i.e., sex and MVPA at the beginnig of the intervention) as well as environmental factors (i.e., group) influenced levels of MVPA at the end of the intervention.The first major finding of this study was that intervention focus (i.e., environment) affected MVPA from the beginning to the end of the intervention. For example, although the girls in the control group showed an increase in MVPA from weeks one and two of the intervention to weeks six and seven, all other groups maintained the same (greater) level of MVPA across all weeks of the intervention. These results suggest that the intervention focus does indeed influence MVPA at the outset of the program (see below for additional influential factors for MVPA during weeks six and seven).The second major finding was an age-related increase in MVPA at weeks one and two of the intervention, where older children demonstrated higher levels of MVPA than younger children, which is aligned with recent findings in which sedentary time decreased and MVPA increased as children aged [34]. This is in contrast to previous findings reported, which demonstrated that younger children (three-year-olds) were more active than older children (four- to five-year-olds) [35]. Pate et al., [35] hypothesized that older children may have more time in structured activities that require more sedentary time; however, this was not the case for children in our study. MVPA differences across groups were observed during the first two weeks of the study for males and females in the different groups. Overall, males showed higher levels of MVPA than girls, which is consistent with previous research [21,34,35]. However, males in the control group had lower levels of MVPA compared to males in the FMS + PA group. Furthermore, males in the FMS group showed higher levels of MVPA compared to males in the FMS + PA intervention, as well as, males in the PA intervention. These results suggest that the FMS intervention, in particular, is more effective in benefitting males MVPA levels, which is consistent with recent findings showing males having higher levels of MVPA in structured activities than females [36]. Females in the control group showed lower levels of MVPA compared to all of the other intervention groups. This effect may be due to females preferring social and structured forms of play versus free play [37] and impacted by level of fundamental motor skill.The third major finding was that in addition to age, sex, and intervention type, children’s MVPA level during the early part of the intervention also had an influenced MVPA in weeks six and seven. Inconsistent improvements in MVPA were observed for weeks six and seven across the groups. Males and females in the control group increased MVPA from weeks one and two (as stated above); however, the males in the control group still exhibited significantly lower MVPA compared to the intervention groups. This finding has been observed in other intervention studies, where children in control groups demonstrate gains over time, but still show less improvement in MVPA compared to the intervention groups [38,39]. The group that showed the largest difference (compared to the controls) were the males in the FMS + PA group. With that being said, there was no significant differences between the intervention groups for either the males or females. These results suggest that the FMS + PA group influenced MVPA in both males and females, regardless of their age or MVPA at the onset of the intervention. There was no significant difference in MVPA in weeks six and seven across females in the control group and intervention groups, suggesting that the control group caught up to the intervention groups. Finally, an age-related increase in MVPA was seen in children that began the intervention with low levels of MVPA. Although this extends the findings from weeks one and two, this finding suggests that over six weeks, the older children may increase MVPA to a greater extent than young children regardless of which intervention group they were in.The present study focused on the types of interventions that would elicit changes in MVPA during outdoor play. Although young children may achieve bouts of MVPA throughout the day, young children may be able to sustain higher levels physical activity for an extended period of time during outdoor play. The time window examined was only 30 min, which was the time allotted for outdoor play at the Head Start center. Although children in the control group increased MPVA over the seven-week intervention, on average males in this group achieved about 10 min of MVPA and females achieved about 12 min of MVPA. In contrast, the males in the FMS + PA were able to achieve over 17 min of MVPA and the females in this group achieved over 13 min of MVPA. These results suggest that young children engaging in non-structured outdoor play may have fallen short of meeting the 15 min per hour recommendation, whereas the males in the FMS + PA group met the recommendation for that hour. This has several implications and practical applications for incorporating outdoor play in early childhood settings. First, when designing outdoor play activities for preschoolers’ activities, which reinforce both FMS and PA are equally beneficial for males and females across age. Second, males exhibit higher levels of physical activity in outdoor play climates that focus on FMS.This study is not without limitations. First, the duration of the study was only seven weeks long. However, we did collect data across the entire seven weeks of the study. Future studies should determine if factors such as initial physical activity impact longer interventions. Second, we were unable to determine the impact of different environments (e.g., different types of preschool programs), as this only examined one preschool center. Finally, we purposely sampled low-income minority children from rural environments, as these children are the most at risk for low levels of physical activity; however, this selective recruitment strategy decreases the generalization of the study.This seven-week intervention was effective at determining which type of interventions elicit changes in MVPA in preschool-aged children during outdoor play. We found that age, sex, intervention approach, and MVPA during the beginning of the intervention all influence preschoolers’ MVPA. However, physical play environments that emphasize motor skill development and physical activity participation (i.e., FMS + PA) may elicit higher levels of MVPA and decrease physical activity disparities for all preschoolers. These findings provide new insights to address the knowledge gap regarding how to elicit MVPA in outdoor play programs to benefit all preschoolers. Future studies should determine if FMS + PA interventions are effective at increasing physical activity levels throughout the day for preschool children.Conceptualization, D.D.W., J.L.J., M.M.P. and M.E.R.; methodology, D.D.W., J.L.J., A.V.C., M.M.P., M.E.R., J.S.; software, D.D.W., M.M.P.; validation, D.D.W., J.L.J., A.V.C.; formal analysis, D.D.W., A.V.C., M.M.P.; investigation, D.D.W., J.L.J., A.V.C., M.M.P., M.E.R., J.S.; resources, D.D.W., M.M.P., M.E.R.; data curation, D.D.W., A.V.C., M.M.P.; writing—original draft preparation, D.D.W., A.V.C., M.M.P.; writing—review and editing, D.D.W., J.L.J., A.V.C., M.M.P., M.E.R., J.S.; visualization, D.D.W., M.M.P.; supervision, D.D.W.; project administration, D.D.W. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors would like to acknowledge and sincerely thank the teachers, school administration, children and parents who made this study possible.The authors declare no conflicts of interest.Percentage of time spent in MVPA by group across the intervention.Top: Percentage of time spent in MVPA for weeks 1 and 2 by group (Control, FMS, FMS + PA, and PA) for males (Left) and females (Right). Bottom: percentage of time spent in MVPA for weeks 6 and 7 by group (Control, FMS, FMS + PA, and PA) by for males (Left) and females (Right). Means and standard errors are presented. Lines represent significant t-tests at p < 0.05.Left: Percentage of time spent in MVPA for weeks 6 and 7 by age for the participants with less than 35% time spent in MVPA for weeks 1 and 2. Each circle represents a participant. The line depicts the fitted regression. Right: Percentage of time spent in MVPA for weeks 6 and 7 by age for the participants with 35% or more time spent in MVPA for weeks 1 and 2. Each circle represents a participant. The line depicts the fitted regression.Demographics [means and standard deviations (SD)].Percentage of time spent in moderate to vigorous physical activity (MVPA) (means and standard deviations) for each group by sex for weeks 1 and 2 and weeks 6 and 7. t-statistics, Cohen’s d, and p-values are presented for the paired t-tests comparing weeks 1 and 2 with weeks 6 and 7 by group and sex.

Med-MDPI/ijerph_4/ijerph-17-02-00651.txt

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+Organic UV filters are a kind of emerging pollutants, which have been widely used in personal care products (PCPs). This study evaluated the effects of benzophenone-4 (BP-4), 4-aminobenzoic acid (PABA), and 2-phenylbenzimidazole-5-sulfonic acid (PBSA) on the selected indices of antioxidative responses in zebrafish (Danio rerio) liver. Zebrafish were exposed to two different doses (i.e., 0.5 and 5 mg L−1) of semi-static water with three individual compounds. Liver samples were collected on 7 and 14 days to analyze biochemical indicators, including superoxide dismutase (SOD), glutathione S-transferase (GST), reduced glutathione (GSH), and malondialdehyde (MDA). Oxidative stress occurred in zebrafish liver with significantly changed indicators during the whole exposure period. Different experimental groups could induce or inhibit the activity of antioxidant enzymes with varying degrees. With a prolonged exposure time and increased exposure dose, the hepatic lipid peroxidation was also obviously observed. Moreover, the toxicity order of three organic UV filters was analyzed using the integrated biomarker response (IBR) index and the results indicate that exposure to PABA for 7 days at 0.5 mg L−1 and PBSA for 7 days at 5 mg L−1 induced the most severe oxidative stress in the liver of zebrafish.In recent years, the amount of ultraviolet radiation has been increasing with the destruction of the ozone layer and its impact on human beings is well known. UV filters in both inorganic and organic forms can separately scatter or absorb UV-A (320–400 nm) and UV-B (280–320 nm) to protect hair and skin [1,2]. However, organic UV filters can be further metabolized in the body when they are absorbed via the skin and finally accumulated in the organism [3]. Organic UV filters are a kind of aromatic compounds widely used among personal care products (PCPs), such as benzophenone-3 (BP-3), benzophenone-4 (BP-4), 4-aminobenzoic acid (PABA), 4-methylbenzylidene camphor (4-MBC), 2-ethylhexyl 4-methoxycinnamate (EHMC), 2-phenylbenzimidazole-5-sulfonic acid (PBSA), octocrylene (OC) [4,5]. The levels of UV filters in cosmetics are generally from 0.1% to 10% [6]. At present, only 14 types of organic UV filters are allowed in cosmetics in the United States, and 26 of them are allowed in the European Union [5]. It has been reported that UV filters entered the aquatic system via either direct input of recreational activities (e.g., washing and swimming) or indirect input from the wastewater treatment plants (WWTPs) [7]. Kaiser et al. [6] observed that B-MDM, EHMC, and OCR were three main pollutants in sediments from the Rhine main area near Frankfurt (Hesse, Germany), with their highest levels of 62.2, 6.8, and 642 μg kg−1, respectively. Jurado et al. [8] reported the detection of a variety of benzophenones in groundwater of Barcelona and the maximum concentrations were measured as 36.6 ng L−1 (BP-4), 19.4 ng L−1 (BP-3), and 19.2 ng L−1 (BP-1). Balmer et al. [9] reported that the concentration of 4-MBC in fish from Swiss midland lakes can reach 166 ng g−1 on a lipid basis. Fent et al. [10] reported the chronic toxicity of organic UV filters, including 4-MBC, EHMC, BP-3, and BP-4, to Daphnia magna, but found the reduced reproduction and body length only at the highest concentration of 4-MBC (50 μg L−1).Environmental contaminants can trigger the toxicity associated with oxidative stress. Oxygen toxicity is a harmful effect caused by cytotoxic reactive oxygen species (ROS), produced during metabolic transformation in organisms [11]. Under normal conditions, antioxidant defense system of organisms can remove ROS and protect complex biological macromolecules from ROS attack. However, when ROS levels induced by pollutants exceed the scavenging capability of antioxidant defense system, the balance will be destroyed, therefore weakening the activity of antioxidant enzymes. Organisms will suffer oxidative stress, resulting in lipid peroxidation (indicated by the significantly enhanced level of malondialdehyde (MDA)), chain breakage, enzyme-protein gluing, and even cell damage [12], death or canceration [13]. Antioxidant defense systems consist of a variety of enzymatic (e.g., catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione reductase (GR), and glutathione S-transferase (GST)) and non-enzymatic antioxidants such as reduced glutathione (GSH) [14,15].Organic UV filters have been reported to be associated with the induction of oxidative stress in aquatic organisms. Gao et al. [2] reported that BP-3 at 1.0 μg L−1 could cause a significant increase of CAT activities and a significant reduction of GSH content of Tetrahymena thermophile. Campos et al. [16] confirmed that exposure to OC at 0.23 and 18.23 mg Kg−1 could lead to an increase in GST levels of Chironomus riparius while 4-MBC at 14.13 mg Kg−1 could cause reductions of CAT activity and an increase of GST activity in Chironomus riparius. Quintaneiro et al. [17] found that GST activity in zebrafish embryos (0–96 hpf) was elevated after exposure to 4-MBC at above 0.15 mg L−1. Owing to the complexity of organic UV filters in aquatic environment, the induction of oxidative stress with the significantly affected antioxidant defenses can be used to reflect the comprehensive pollution of PCPs in aquatic environment and to evaluate the environmental risks of polluted water.Zebrafish (Danio rerio) have been widely used as indicator organism in toxicological studies of environmental pollutants [18,19]. The aim of this work was to (1) measure the levels of four oxidative stress indicators (i.e., SOD, GST, GSH, and MDA) in zebrafish liver exposed to these three pollutants, and (2) evaluate their toxicity order using the integrated biomarker response (IBR) index.The purity of three organic UV filters (i.e., BP-4, PABA, and PBSA, see their physico-chemical properties in Table 1) was 99%. Sodium chloride, acetic acid, and ethanol (95%) are of analytical grade and were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. (Aladdin, Shanghai, China). Enzymatic activity assay kits for SOD, GST, GSH and MDA and protein assay kits were purchased from Nanjing Jiancheng Institute of Bioengineering (Nanjing, China). Fish feed was purchased from a local aquarium store in Wuhan, China. Ultrapure water used throughout the whole experiment was produced via a Millipore Purification System (Millipore Elix 20, Millipore Corporation, Billerica, MA, USA).The instruments used in the experiment included a high-speed refrigeration centrifuge (5810/5810R, Eppendorf, Hamburg, Germany), an electric homogenizer (F6/10, Jingxin Technology, Shanghai, China) and an ultraviolet-visible spectrophotometer (UV-1100, Shanghai Mespectra, Shanghai, China).Experimentation was performed in accordance with the laboratory animal welfare of China and was approved by the animal ethics committee of Anhui University (No. 201916; effective date, 15 March 2019). The experiment was carried out according to the animal protection policy of Anhui University and an approved animal use agreement. The zebrafish (2.0 ± 1.0 cm and 0.2 ± 0.1 g) used in this study were purchased from the Institute of Hydrobiology of the Chinese Academy of Sciences (Wuhan, Hubei). Zebrafish were domesticated in freshwater over 72 h of aeration for a week. Fish were fed once a day according to 1% of the body weight. Only when the mortality rate is less than 1% during domestication can zebrafish be cultured in laboratory. Then, under natural light, zebrafish were cultured in the circulation system at 25 °C with pH 7.5 before further experiments. Semi-static mode was used for water change (every 24 h). Prior to normal experiments, the acute toxicity of three compounds was assessed via water exposure and the results suggest that the lethality of these compounds did not exceed 50%, even at the dose of 100 mg L−1. The doses of BP-4, PABA, and PBSA were selected at 0.5 mg L−1 and 5 mg L−1, which are higher than their environmental levels and the higher dose did not exceed 1/20 of LD50. At different exposure times, each ten zebrafish after domestication as an experimental group were exposed to 10 L experimental solutions containing 0, 0.5, or 5 mg L−1 of BP-4, PABA, and PBSA, respectively. Three replicates were performed for each experimental group. Fish were starved for 24 h prior to sampling to avoid prandial effects and to prevent the deposition of feces in the course of the assay. Livers of three zebrafish were individually taken out from 7 days and 14 days of exposure for determination of oxidative stress biomarkers (i.e., SOD, GST, GSH, and MDA). The water conditions were maintained constant during the whole exposure period (Temperature: 25 ± 1 °C; pH: 7.5 ± 0.1; Dissolved oxygen: 7.05 ± 0.43 mg CaCO3 L−1; Conductivity: 521 ± 9.56 μS cm−1; Hardness: 123 ± 3.42 mg L−1). During the whole exposure, the behaviors (i.e., lethargy, anorexia, erratic swimming, exophthalmia, corneal opacity, visible deformity, and hemorrhage at the operculum, pectoral, and ventral areas) of zebrafish were observed for judging the pathogenicity of fish. In short, the testing procedures for oxidative stress are illustrated in Figure 1.The dissected liver was washed with 0.9% normal saline after zebrafish were frozen to death, then dried with filter paper and weighed. The homogenate produced by Ultra Turrax homogenizer in 0.9% normal saline was centrifuged at 8000 r/min for 10 min at 4 °C. The clear supernatant extract was analyzed for enzymatic activity.All indicators were determined according to the manufacturer’s instructions. SOD activity was determined based on the principle that SOD could inhibit the reactivity of O2−• [20]. GST activity was calculated by spectrophotometric determination of 1-chloro-2,4-dinitrobenzene (CDNB) and GSH at 412 nm [21]. MDA content was tested by method of thiobarbituric acid (TBA) [22]. Under acidic conditions (e.g., glacial acetic acid) and a high temperature (95 °C) for 40 min, the determination of MDA contents in zebrafish liver involved in the reaction between MDA and TBA to form the red complex that can be detected by a UV-VIS spectrophotometer at 523 nm. GSH levels were assayed using the method described by Jollow et al. [23]. The protein concentration measured by the Bradford method [24] was used to correct the activity of antioxidant enzymes.The actual concentrations of BP-4, PABA, and PBSA in exposure water were determined using a HPLC system (Waters e2695). The mobile phases included methanol (80%) and 0.25% ethanoic acid in water (20%) with a flow rate of 1.0 mL/min. The detection wavelength was set as 310 nm for all three compounds. The column (Agilent ZORBAX SB-C18, 150 × 4.6 mm, 5 μm) temperature was 25 °C, and the injection volume was 10 μL. In addition, for preparation of the calibration curve, these compounds were dissolved in methanol at 100 mg L−1 as stock solutions. The stock solution was diluted to different concentrations (0.25, 1, 5, 10, and 50 mg L−1) in a 10 mL volumetric flask. The R2 values of the calibration curves for BP-4, PABA, and PBSA were 0.998, 0.996, and 0.995, respectively.Multiple biomarkers were combined into a general-purpose IBR index, by which the toxicity of three compounds can be directly reflected and proposed by Beliaeff et al. [25]. A brief calculation of IBR is given here. The formula for standardized data (Y) is as follows:Y = (X − m)/S(1)
+        where X = the value of each biomarker responses, m = the mean value of the biomarker, and S = the standard deviation of the biomarker.Z was computed through Z = Y in the case of activation or Z = −Y in the case of inhibition. The minimum (min) is provided by Y. Then, the score of a given biomarker (S) was obtained from S = Z + |min|, where S ≥ 0 and |min| is the absolute value.Star plots can visually show the outcomes of biomarkers. The area of star plots (Ai) was obtained from the following equation:(2)β = Arctan(Si+1sinαSi−Si+1cosα),(3)Ai=Si2sinβ(Sicosβ+Sisinβ),
+        where α = 2π/n radians; Si = the obtained value of each biomarker, and Sn+1 = S1.When only four biomarkers are selected, the area formula was simplified to
+        (4)Ai = SiSi+1/2,The value of IBR was calculated as
+        (5)IBR=∑n−1iAi,
+        where n = the number of biomarkers, which plays a key role [26].The SPSS statistical package program (ver. 22.0, IBM, Chicago, IL, USA) for Win 7.0 was used for a statistical analysis. Prior to a One-way ANOVA analysis, the standardization and homogeneity of data were checked by Kolmogorov–Smirnov test and Levene test, respectively. One-way ANOVA and Dunnett test were used to show difference between the control and the experimental treatments. Duncan’s multiple range test was conducted to identify significant difference among groups. Significant differences between groups could be illustrated by Duncan’s test. Significant difference was divided into two levels, i.e., significant (p < 0.05) and extremely significant (p < 0.01). All the results are represented as means ± S.D., and Origin 2017 (Origin Lab, OriginLab Corporation, Northampton, MA, USA) was used for figure plotting.In the present study, no pathogenic or dead fish were observed during the whole domestication and exposure (14 days). Indicators of oxidative stress included antioxidant enzymes (i.e., SOD and GST) and non-enzyme antioxidant (i.e., GSH and MDA). Changes of these indicators among different treatments are discussed in the next section. The actual levels of BP-4, PABA, and PBSA were monitored throughout the exposure duration (Table 2). The results indicate no significant difference (within 10%) between the nominal (i.e., 0.5 and 5 mg L−1) and measured concentrations. Hence, the nominal concentrations were used in the following discussions.The effect of BP-4, PABA, and PBSA with two different concentrations on the activity of SOD and GST in zebrafish liver is shown in Figure 2. Compared with the control group after 7 days, SOD activity in all experimental groups decreased significantly (p < 0.01) (Figure 2A) and the decreases for the treatments by BP-4, PABA, and PBSA were 12.4%, 29.1%, 34.8% for 0.5 mg L−1 and 31.3%, 52.2%, and 44.4% for 5.0 mg L−1, respectively. After 14 days of exposure, no significant change (p > 0.05) in SOD activity was detected.Contrarily to the trend of SOD activity, GST activity increased significantly in all experimental groups after 7 days of exposure (p < 0.01) (Figure 2B). With the extending exposure time, GST activity in all experimental groups, except the group of BP-4 (5 mg L−1), returned to the level of the control group. After 14 days of exposure, the group of BP-4 (5 mg L−1) showed a significant downward trend and the change of GST activity became the greatest.During the whole exposure, the change of GSH levels in zebrafish liver is illustrated in Figure 2C. After 7 days of exposure, GSH levels in low-dose groups (0.5 mg L−1) of BP-4 and PABA altered significantly (p < 0.01), but no significant variation (p > 0.05) was observed in other groups. GSH levels were significantly induced in the group of BP-4 (0.5 mg L−1), but significantly inhibited in the group of PABA (0.5 mg L−1) (p < 0.01). After 14 days of exposure, no significant change in GSH levels was observed among the experimental groups.Figure 2D exhibits the change of MDA contents. After 7 days of exposure, MDA contents were significantly decreased (p < 0.01) in the treatments, including BP-4 (5 mg L−1) and PABA (5 mg L−1), but all the treatments of PBSA (0.5 and 5 mg L−1) were significantly increased (p < 0.01). After 14 days of exposure, MDA contents were highly induced (p < 0.05 or p < 0.01) in all the treatments, particularly for PABA (5 mg L−1) and PBSA (0.5 mg L−1) (p < 0.01), except for the groups of BP-4 (0.5 and 5 mg L−1).In this study, the standardized values of four biomarkers determined on the 7th and 14th day of exposure are presented in Figure 3A, and the calculated IBR values are shown in Figure 3B. The IBR values for three chemicals-treated groups ranged from 1.24 for PBSA after 7 days (0.47 for 0.5 mg L−1 and 0.77 for 5 mg L−1) to 9.99 for PABA after 14 days (6.89 for 0.5 mg L−1 and 3.09 for 5 mg L−1). This indicates that at the test concentration of 0.5 mg L−1, zebrafish liver was most severely affected by oxidative damage in the following order: PABA-7 d > PBSA-7 d > PABA-14 d >BP-4-7 d > PBSA-14 d > BP-4-14 d > Control group. Comparatively, at the exposure level of 5 mg L−1, zebrafish liver was influenced by oxidative damage in the following order: PBSA-7 d > BP-4-7 d ≈ PABA-7 d > BP-4-14 d > PBSA-14 d ≈ PABA-14 d > Control group.It has been documented that organic UV filters could be released into the aquatic environment, accumulated by organisms in the food chain, therefore posing potential risks on fertility and reproduction of fish species [27,28]. According to the data obtained from this study, BP-4, PABA, and PBSA could cause oxidative damage to fish liver under different exposure doses and durations.Measuring the effects of pollutants on organisms by the changes of key enzymes in specific reactions is a widely used method to study the status of oxidative stress [29]. SOD, as the first line of defense against oxidative stress, can catalyze the mutation of O2−• and convert it into H2O and H2O2. GST, a phase II detoxification metabolic enzyme, can catalyze the binding of electrophilic groups of xenobiotics with sulfydryl groups of GSH to increase its hydrophobicity. GST also has GPx activity, which can inhibit lipid peroxidation [30]. In this experiment, compared with the control group, SOD activity decreased significantly in all the groups after 7 days of exposure to three chemicals. Excessive ROS production in fish after exposure, which exceeds the ability of SOD to remove ROS, was a cause of the results [31]. Similar results were also reported by Li et al. [32], in which SOD activity in the liver of Carassius auratus was inhibited after 14 days of exposure to highly fluorinated PFDDs (100 µmol kg−1). Falfushynska et al. [33] found that the gibel carp Carassius auratus gibelio inhabiting both upstream and downstream of the dam of Kasperivtci HPP in the West Ukraine showed a similar response in the decrease of SOD activity. Aytekin et al. [34] reported an inhibited SOD activity in the liver of Oreochromis niloticusin exposed to 0.6, 3.0, and 6.0 mg L−1 of Cu for 15 days. On the seventh day of exposure, GST activity increased more remarkably (p < 0.01) in all the experimental groups than those in controls, indicating that GST participated in the detoxification of these UV filters. Assessment of the effect of endosulfan in different concentration ranges on clams also showed a similar detoxification mechanism [30]. After 14 days of exposure, hepatic GST activity induced by BP-4 (5 mg L−1) increased significantly, which might be due to the accumulation of pollutants. These results indicate that GST was involved in the biotransformation of BP-4, and the complex of GST and BP-4 was produced to detoxify the toxicants in zebrafish liver.GSH can detoxify not only by acting as a substrate of GPx and GST, but also by directly binding to ROS and electrophilic compounds [35,36]. Previous studies have clearly demonstrated that exposure to organic pollutants resulted in the increase or decrease of GSH levels in organisms depending on the exposure species, exposure duration and dose [37,38]. In this study, significant changes in GSH levels were found in the low-dose group after 7 days of exposure. The significantly increased GSH levels in the group of BP-4 (0.5 mg L−1) probably resulted from the enhanced hepatic uptake of amino acid substrates and the activities of biosynthetic enzymes in order to protect the organisms against oxidative damage [39]. The consumption of GSH due to the direct scavenging of ROS or as a co-factor for GST/GPx activities may significantly decrease GSH levels in the group of PABA (0.5 mg L−1) [40]. Moreover, the reaction of GSH during xenobiotic exposure might have been affected by the dose saturation phenomenon. In other words, GSH levels may not change significantly when the concentrations of test chemicals reach a certain dosage. This suggests that other detoxification systems may be involved in the reaction, or GSH is not very sensitive to those chemicals [41], or GSH contained in fish feed may have an enduring impact on the experiment during domestication [42]. In this study, the antioxidant responses were saturated with PABA group at 5 mg L−1 rather than 0.5 mg L−1. This suggests that GSH may be more sensitive to low doses and suitable for evaluating the antioxidant status of three organic UV filters at low levels.Xenobiotics induce zebrafish to produce a large number of oxygen free radicals and will combine with unsaturated fatty acids in biofilm and cause lipid peroxidation [43]. MDA is a major degradation product of lipid hydroxides (LPO) and is often used as an effective biomarker for evaluating LPO when aquatic species are exposed to pollutants [44]. The level of MDA indirectly reflects the severity of free radical attack on body cells [45]. In the current study, MDA contents of PABA and PBSA at different concentrations increased significantly after 14 days of exposure. With the extension of the exposure time, the increased MDA content in zebrafish liver may indicate a significant time-dependent effect [46,47]. It can therefore be inferred that exposure of xenobiotics at high concentrations resulted in excessive generation of ROS in a short time. However, the ability of the antioxidant system to eliminate ROS was limited, while the remaining oxygen free radicals attacked the polyunsaturated fatty acids in biofilm, leading to the formation of lipid peroxides, i.e., lipid peroxidation, and also an increased MDA content [45,48]. Previous studies have also confirmed the lipid peroxidation in zebrafish liver exposed to triazophos, which was based on the significantly enhanced MDA content in the high-dose groups and a longer exposure time [47]. In contrast, the growth trend of MDA content in PBSA-treated groups was more obvious, indicating that PBSA was more likely to induce ROS production in fish liver, resulting in damage on the cell membrane.Moreover, after 14 days of exposure to PABA and PBSA, the increase was only recorded in hepatic MDA contents. Similar results were also reported by Li et al. [49], in which they found that MDA contents in the liver of Carassius auratus were increased significantly after 2 days of exposure of 10 μg kg−1 2,2′,4-Tris-CDPS, while no significant change in antioxidant enzymes was detected. It was thus speculated that no obvious relationship existed between MDA contents and other oxidative indicators (SOD, GST and GSH) after exposure of PABA and PBSA. Yonar et al. [50] reported that SOD activity, GST activity and MDA contents significantly increased after exposure of Common carp to chlorpyrifos (0.080 mg L−1) for 14 days, while CAT activity and GPx activity significantly decreased. An increase in MDA contents may indicate tissue damage caused by oxidative radicals, which might be reflected by other indicators (e.g., CAT and GPx activity). The findings of this study reinforce that MDA contents might be more suitable as the short-term toxicity index of PABA and PBSA. Moreover, no significant difference could occur in oxidative indicators (SOD, GST and GSH) after 14 days of exposure compared with the control group, depending on time and dose of application as well as the susceptibility of exposed species. However, as a final product of lipid peroxidation, MDA can increase continually by accumulating in fish tissues. MDA contents provide more direct evidence of the toxic process caused by free radicals than other indicators, which can be further confirmed by the determination of ROS levels.In summary, exposure to organic UV filters can not only induce the increase of oxidative stress level in zebrafish liver, but also lead to lipid peroxidation. Antioxidants work together to remove ROS and protect the body from damage of free radicals [38].The toxicity difference of BP-4, PABA, and PBSA was analyzed and compared by the IBR index, which combines different biomarker signals to describe the “health status” of organisms. It is of great environmental significance to estimate the toxic effects of pollutants with specific enzymes and to use them as the biomarkers for early warning of water contamination [51]. Generally, the higher the IBR value is, the greater the environmental pressure will be. The IBR data in this study showed that PABA-7 d at 0.5 mg L−1 and PBSA-7d at 5 mg L−1 can cause the more severe damages in zebrafish liver. The IBR values decreased gradually with the prolonged exposure time, indicating that zebrafish liver could weaken the oxidative damage caused by these chemicals via its self-regulation mechanism. In the later stage of pollutant exposure, zebrafish liver could effectively eliminate the harmful free radicals produced during interactions of UV filters and zebrafish liver. In addition, it is worth noting that the stress of PABA on zebrafish liver in low-dose group is more serious than that of the other two compounds, which needs to be given great health concern.This study explored the effect of exposure to organic UV filters on hepatic antioxidant response in zebrafish. However, some limitations should also be considered. First, the doses of the three test compounds were higher than their environmental levels, and the dose-dependent effect was not observed due to the narrow concentration ranges. Secondly, though the present study demonstrates that organic UV filters (BP-4, PABA and PBSA) may affect the antioxidant system of zebrafish, the molecular mechanisms of oxidative stress need to be further clarified. Finally, determination of the concentrations of organic UV filters in zebrafish liver will facilitate understanding on the correlation of their bioaccumulation and hepatic antioxidant response.In conclusion, the present study demonstrates that BP-4, PABA, and PBSA (0.5–5 mg L−1) could cause significant changes in SOD, GST, GSH, and MDA in zebrafish liver after exposure from 7 to 14 days. These phenomena indicate that exposure to these organic UV filters could increase ROS production and cause oxidative damage in fish liver. With the increase of exposure time and dose, MDA contents increased significantly, suggesting the presence of lipid peroxidation. The calculated IBR values suggested that exposure to PABA for 7 days at 0.5 mg L−1 and PBSA for 7 days at 5 mg L−1 had the most severe toxicity on the hepatic antioxidative defenses in zebrafish liver. In short, the data obtained in this study provide a scientific basis for the ecological risk assessment of different organic UV filters and their toxicological mechanisms are the future research direction needing more attention.X.H., X.Z. and H.L. designed the research. X.H. and Y.L. conducted the experiments. X.H. and X.Z. analyzed the data and drafted the manuscript. T.W. contributed to the improvement of the writing. J.S. contributed to the errors checking. All authors have read and agreed to the published version of the manuscript.This research was funded by the National Natural Science Foundation of China, grant number 21607001 and 21607058.The authors have declared that no conflict of interest exist.The testing procedures for oxidative stress evaluation of BP-4, PABA, and PBSA in zebrafish liver.Effect of exposure to BP-4, PABA, or PBSA (0.5 and 5 mg L−1) for 7 and 14 days on the activity of biochemical indicators (A, SOD; B, GST; C, CSH; D, MDA) in zebrafish liver. Data are expressed as means ± SD, n = 3 for each data point. Superscript letters a–e indicate differences among the experimental treatments at the same exposure time. * Significantly different from controls (p < 0.05), ** Highly significantly different from controls (p < 0.01).Biomarker star plots (A) and the calculated IBR values (B) of all biochemical parameters measured in zebrafish liver after exposure to BP-4, PABA, or PBSA (0.5 and 5 mg L−1) for 7 and 14 days.Physico-chemical properties of three tested chemicals.a Octanol/water partition coefficient, data from reference [2]. b Data calculated in ECOSAR (Ecosar Application 2.0, US Environmental Protection Agency, Washington, DC, USA).Nominal and corresponding measured concentrations of the three compounds.a Data are presented as mean ± S.D. and determined using HPLC.

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+Based on the panel data of 106 cities in the Yangtze River Economic Belt of China from 2007 to 2016, this paper explores the impact of city centrality on the green innovation efficiency and proves the mediation effect of migrants by using spatial econometric model. The results show that there are more and more innovation contacts between cities, and the innovation network is becoming more and more dense. The core cities of the downstream innovation network are mainly Yangzhou, Zhenjiang, Wuxi, Changzhou, Suzhou and Hangzhou; the core cities in the midstream are mainly Wuhan, Changsha and Yichun; the core cities in the upstream are Chengdu and Bazhong. There is an inverted U-shaped relationship between city centrality and green innovation efficiency. In addition, the influence curve of city centrality on the green innovation efficiency of surrounding cities is also inverted U-shaped. Cities with high city centrality attract a large number of migrants that come from cities with lower centrality to improve the green innovation efficiency, but the green innovation efficiency of cities with low city centrality will decline due to lack of talents.Since the reform and opening up, the Yangtze River Economic Belt has became one of the regions with the strongest comprehensive strength in China. However, the development of the Yangtze River Economic Belt faces many difficulties and problems that need to be solved urgently, which are mainly the severe situation of the ecological environment, the arduous task of industrial transformation and upgrading, and the imperfect mechanism of regional innovation cooperation. Therefore, effectively improving the green innovation efficiency in the Yangtze River Economic Belt and giving full play to its role as a green economic support belt will help to improve these problems.China is in a stage of high-quality development, innovation and green development play important role in the national economic strategy. From the perspective of traditional innovation concept, the scholars who first introduced environmental factors into the field of innovation proposed four kinds of innovations in turn: ecological innovation, environmental innovation, sustainable innovation and green innovation. The discussion of ecological innovation originated with Fussler and James [1], who defined ecological innovation as “new products and processes that provide business value to customers but significantly reduce environmental impact.” In the early 1920s, environmental innovation research was still at a nascent stage, and few researchers worldwide who studied innovation addressed environmental problems until Oltra and Jean defined environmental innovation as “New or improved processes, practices, systems and products that benefit the environment [2].” Sustainable innovation increasingly implies long-term and far-reaching changes in technology, infrastructure, lifestyles and institutions. With the rapid growth of the world’s population, living space has been dramatically reduced, and traditional production, manufacturing and business models largely cannot keep up with the pace of economic development. Natural resources are increasingly scarce, and environmental damage is becoming increasingly serious [3]. To reduce environmental pollution and energy consumption, countries are paying growing attention to green technology innovation to achieve the maximum economic and ecological benefits with the lowest levels of consumption and pollution [4]. Chen et al. define green innovation as “hardware or software innovation related to green products or processes, which include technological innovation related to energy conservation, pollution prevention, waste recycling and green product design [5].” Innovation is the fundamental driving force for promoting economic and social development, and green technology innovation is the key driving force for achieving low-carbon economic development and improving the efficiency of natural resources [6]. China has always placed innovation in an important position in the overall development of the country. Relevant data show that the number of R&D personnel in China increased from 304,000 in 2008 to 462,000 in 2017. Internal R&D expenditures over the same period increased from 68.79 billion yuan to 243.57 billion yuan, with an average annual growth rate of 15.08%. Bai [7], however, notes that increasing R&D is a necessary condition for building an innovative country; the focus should be not only on the amount of R&D investment but also on the efficiency of innovation, it is equally salient for developing countries with low levels of science and technology. Green innovation efficiency is a comprehensive efficiency index that considers innovation performance, resource and environmental constraints [8]. Previous studies on green innovation mainly focus on measuring the level of green innovation [9], dividing the types of green innovation [10], analyzing the influencing factors of green innovation [11]. These scholars only explore the influence of regional internal factors on green innovation efficiency without considering the spillover effect of innovation [12,13]. Innovation contacts between regions have complex and network-like structure, and the mobility of R&D elements and the strong connection between researchers make the connectivity of the technological innovation network come true, network research is also applicable to innovation systems [14].Therefore, this article explores green innovation efficiency from the perspective of social network theory. With the increasing complexity of innovation activities, the increasing number of R&D processes is often a collective act, as it reduces the risks and complexities involved in developing new products and processes by spreading innovation to dispersed partners [15]. The evolution of innovation spatial patterns to network has led to the transformation of urban innovation function and innovation mode. Previous scholars have discussed the urban innovation network from the perspective of network structure characteristics and spatial attributes [16,17,18]. However, these studies only describe the characteristics of innovation networks and the mechanism of dynamic evolution, and the research on how network structure elements promote city innovation is still lacking. This paper quotes the research of enterprise innovation networks, which mainly shows that the innovation of individuals or higher-level collectives (teams, organizations, or countries) is influenced by their social network. These social relationships and networks can promote or constrain them to acquire, transfer, absorb, evaluate, and apply knowledge and information [19]. For example, Chen et al. [20] analyzed how an innovation network structure enhances or constrains innovation activities by affecting the frequency of interactions between members and knowledge within the network. Olanrewaju et al. use centrality to represent the number of other enterprises that enterprises associate with through informal social relationships—the higher the enterprise’s centrality, the stronger its ability to obtain network resources, which can allow the enterprise to obtain and utilize the knowledge spillover related to innovation as much as possible [21]. Rydehell et al. also claimed that the position of the company in the innovation network is a key factor affecting the innovation performance of the company [22]. The above studies have shown that the member in the center of the network can make better use of information resources to extract more valuable technology and knowledge, so as to realize the progress and innovation of their own technology. However, this conclusion seems to be more commonly applied to corporate cases, and few scholars have used data of cities to explore this issue. City centrality is used to represent the status of a city in the city innovation network, so we attempt to explore whether there is a similar relationship between city’s green innovation efficiency and city centrality, and what is the mechanism of this correlation. This is the research question of this article. Therefore, this paper proposes the first hypothesis:
+          City centrality affects green innovation efficiency.
+        Some researchers believe that heterogeneity in innovation performance comes from the abilities to access and create the resources [23], when using external knowledge resources to innovate, it’s easy for enterprises to produce innovation without the guidance of partners if innovative resources can be fully absorbed and utilized [24]. Dong found that the acquisition of innovative resources depends on knowledge network centrality [25]. Therefore, the centrality increases the chances of acquiring innovative resources [26], the innovation network plays an important role for network members to acquire innovation resources through inter-organizational relationships, and the positions of members in the network structure directly affect their ability to acquire resource. The same is true for city innovation. With the deepening of social aging and the continuous decline of the number of labor resources, the problem of structural shortages in the labor market is becoming increasingly serious [27]. In this context, how to attract talents and how to “rob” high-quality labor become the key to the future development of the city, various cities are also competing to introduce preferential policies to attract talents, while policies issued by some developed cities are more attractive to talents, and these cities tend to have higher innovation level and higher city centrality, so cities that are at the center of the innovation network seem to be more likely to acquire higher skilled labors or more capital investment, so this paper proposes the second hypothesis:Cities with high city centrality attract a large number of migrants that come from cities with low city centrality to improve the green innovation efficiency.Based on two hypotheses, this paper first uses the spatial econometric model to explore the impact of city centrality on the green innovation efficiency from the perspective of city network, heterogeneity test is used to analyze the different effects of city centrality. Second, the mediation effect model is used to prove the number of migrants is a mediator variable in the effect of the city centrality promoting the green innovation efficiency. Last, the above conclusions still hold after considering the robustness test. The paper proceeds in the following way: the second section introduces materials and methods, the third section describes the results, the fourth section discusses the results, and the last section provides the conclusions and policy recommendations.This paper calculates the green innovation efficiency by using MAX-DEA software. In 1978, Charnes et al. first proposed a nonparametric technical efficiency analysis method based on a relative comparison between the evaluated decision-making units (DMUs)—DEA [28]. The SBM model proposed by Tone solves the problem posed by the fact that radial models do not contain slack variables in their measurement of inefficiency [29]. SBM model cannot distinguish DMUs with an efficiency of 1, but a super-efficiency model can rank DMUs with efficiency at the frontier. Therefore, the super-SBM model is further defined by the fact that it combines the advantages of the super-efficiency model and the SBM model. The model is as follows:(1)minρSE=1m∑i=1mxi¯xik1s∑r=1syr¯yrks.t. xi¯≥∑j=1,j≠knxijλj; yr¯≤∑j=1,j≠knyrjλj; xi¯≥xik; yr¯≤yrk; λ,s−,s+,y¯≥0;  i=1,2,⋯,m; r=1,2,⋯,q; j=1,2,⋯,n(j≠k)Here, n is the number of DMUs, where each DMU has m inputs and q outputs, which are denoted as xi(i=1,2,…,m) and yr(r=1,2,…,q), respectively. λ represents the linear combination coefficient of the DMUs, and the specific indicators are selected as follows.Input indicators: Independent innovation or the purchase of extraterritorial technology requires R&D personnel and financial resources as inputs, which need the support of local governments, funding and staffing must be guided by the number of topics [30]. Based on available data, this paper uses the fixed asset investment (X1), the number of employees in the second and third industries (X2), science and technology expenditure (X3) and electricity consumption (X4) as input indicators.Output indicators: The output of green innovation can be measured in two ways: technological output and green output. Technological output can be further divided into two processes: achievements of technological creation and achievements of technological transformation, The number of patent authorizations (Y1) has been shown to better represent the quality of innovation output [31]. Achievements of technological transformation are premised on harvesting economic benefits; the ultimate goal of technological innovation is to pursue the application of academic achievements and to obtain economic benefits by selling new products [32]. Therefore, this paper chooses gross domestic product (Y2) to represent achievements of technological transformation. In addition, the environmental pollution in the process of innovation activities is mainly caused by the discharge of industrial wastes [33]. Therefore, the emission of three pollutants (y1 represents Industrial smoke and dust emissions, y2 represents Industrial wastewater discharge, y3 represents Industrial sulfur dioxide emissions) in industrial production is regarded as undesirable output. The core explanatory variable of this paper is the city centrality, the greater the centrality, the stronger the ability of the city to control other cities and the more innovation contacts between the city and other cities. This paper uses degree centrality to represent city centrality, degree centrality characterizes the ability of a node to contact other nodes in the network, the larger the value, the more prominent the centrality of the node in the network and the stronger the communication ability, the calculation formula is as follows:(2)DCi=∑j=1NSij
+          where DC is the city centrality, which represents the sum of the number of innovation contacts between city i and all other cities, N is the number of cities in the network, Sij represents the number of innovation contacts between city i and city j, it’s measured by a modified gravity model. The calculation formula of the traditional gravity model is as follows:(3)Fij=G·Mi·MjDij2Here, Fij is the attraction of the region i to the region j, for example, G is the coefficient of attraction between regions, which is generally 1; Mi and Mj are some factors; Dij is the spatial straight-line distance between region i and region j. We modified the traditional gravity model, the innovation contacts are directly proportional to the innovation level of city i and city j, that is, if the two cities have higher levels of innovation, there will be more innovation interaction and knowledge exchange between them. The innovation contacts and the distance between the two cities will be inversely, because higher transportation costs and time costs limit the innovation interaction between the two cities. If the difference in economic development between the two cities is relatively large, the frequency of innovation interaction between the two cities is relatively low. The innovation contacts between cities are set as the function of the spatial distance and the number of patent authorizations, and the innovation contacts between cities decrease with distance and increase with the number of patent authorizations, and developed cities tend to have more innovation links with other cities, so the model is as follows:(4)Sij=K⋅PAi⋅PAjDij2,K=GDPiGDPi+GDPjHere, PAi and PAj denote the number of patent authorizations of city i and city j, respectively; GDPi denotes the gross domestic product; Dij denotes the spatial straight-line distance between city i and city j, which is measured by ArcGIS software.Based on reviewing the relevant literature [34,35], the following four factors are selected as control variables. Companies have the incentive to change production methods and use green technologies because of the increase of production cost caused by environmental regulation, which often motivate enterprises innovation to improve the innovation of cities, this paper chooses the comprehensive utilization rate of industrial solid waste (ER) to indicate the intensity of environmental regulation. Due to the differences in the knowledge base and innovation process of different industries, regions with higher industrial structure have higher innovation ability [36], so the proportion of the added value of the tertiary industry in the regional GDP is used to reflect the industrial structural characteristics of a region (IS); in China, the local economic development level and the local financial input directly affects the government’s support for science and technology activities, which are inseparable from the operation of regional innovation systems [37], thus, per capita gdp (PCGDP) and local fiscal expenditureare (GOV) are used to represent the economic development level and government support. We transform each variable logarithmically to eliminate the effects of heteroskedasticity.Wage and geographical distance significantly affect labors’ migration. If city j has higher wages than city i, then the labor of city i will flow into city j under the drive of “utility maximization”. If the distance between city i and city j is relatively long, then the labor does not necessarily choose to flow due to transportation cost and time cost. Therefore, this paper uses the modified gravity model to define the number of migrants:(5)PFLij=lnLj·lnWAGEi·Dij−2In the above formula, PFLij reprensents the number of migrants flowing from city j to city i, Lj represents the number of employees in the secondary and tertiary industriesand, and WAGEi represents the average wage of employees in city i. Therefore, the total amount of migrants of city i is as follows:(6)PFLi=∑j=1nPFLijBefore applying the spatial econometric model, it is necessary to do a spatial correlation test to ensure the validity of the model. Geary’s C proposed by Geary is a more suitable test method, which is used to determine whether economic activities have global spatial correlation. The calculation formula is put in the Appendix A. Compared with the traditional econometric model, the spatial econometric model takes into account the spatial correlation commonly found in economics, that is, the sample observations in one area depend on the observations in other areas, and spatial correlation is reflected in the lag term of dependent variable and error term in spatial econometric model. Considering that there may be a spatial correlation of innovation activities among regions, one region may be affected by the innovation activities in other adjacent or non-adjacent regions. Thus, traditional econometric models may ignore the spatial correlation of the green innovation efficiency. Accordingly, this paper chooses relevant data from 106 cities in the Yangtze River Economic Belt and uses spatial econometric analysis technology to explore the relationship between city centrality and green innovation efficiency. According to the judgment rules proposed by Anselin et al. [38], the model is set up and fitted by maximum likelihood (ML) estimation and the likelihood-ratio (LR) test. In theory, any factors related to innovation activities may have an impact on innovation efficiency. The spatial lag model (SLM) is generally used to explore the spatial spillover effect in one region, in general, a spatial lag model is applicable if the dependent variable of a spatial unit depends on the dependent variable of the previous period of its surrounding spatial units [39]. In other words, the city’s GIEt is affected by the surrounding cities’ GIEt−1. In general, unobservable variables are ubiquitous, such as regional accessibility, reputation, and status. If the regression model includes unobservable spatial autocorrelation effect, then the spatial error model is applicable, which assumes that spatial spillover are caused by random impact and their spatial effects are mainly transmitted by error terms. If the dependent variable of city i also depends on the independent variables of other cities, the spatial durbin model (SDM) is applicable, which takes into account the transmission mechanism of the above two models, it incorporates the spatial correlation of independent variables and dependent variables, and the spatial spillover effect is characterized by spatial interaction terms. If there is no spatial autocorrelation in the green innovation efficiency among cities, then a traditional ordinary least squares (OLS) model is used to analyze it. If there is spatial autocorrelation, then the optimal spatial econometric model must be further screened through testing. According to the test results, SDM is more suitable for analyzing the problems in this article. The specific reasons will be explained in the Section 4. The SDM is as follows:(7)GIEit=β0+δWGIEit+β1DCit+β2DCit2+β3Xit+θ1WDCit+θ2WDCit2+θ3WXit+εitHere, δ is the spatial autoregressive coefficient, which is used to measure the impact of other cities’ GIEt−1 on the local GIEt. GIEit is the green innovation efficiency of city i in year t, DC is the city centrality, X represents the control variable, which is as follows: ER, IS, PCGDP and GOV. W is the spatial distance weight matrix (Each element in the matrix is equal to the linear distance between the city i and the city j). ε represents perturbation terms subject to independent and identical distribution.In order to further explore the mechanism of city centrality affecting the green innovation efficiency, this paper refers to the mediation effect test method proposed by Baron and Kenny [40], and the model is set as shown in Equations (7)–(9).
+          (8)PFLit=δ1+δ2DCit+μit+εitThe next is as follow:(9)GIEit=α0+ϕWGIEit+α1DCit+α2DCit2+α3Xit+α4PFLit+φ1WDCit+φ2WDCit2+φ3WXit+φ4WPFLit+εitHere, PFLit represents total migrants of city i, the coefficient (β1) of Equation (7) is the total effect of city centrality on green innovation efficiency; the coefficient (δ2) of Equation (8) is the effect of city centrality on mediator variable (PFL); the coefficient (α4) of Equation (9) is the effect of mediator variable (PFL) on green innovation efficiency after controlling the influence of city centrality; the coefficient (α1) is the direct effect of city centality on the green innovation efficiency after controlling the effect of the mediator variable (PFL). Equation (9) can be tested under the condition that the regression coefficient estimates of DC in Equations (7) and (8) are significant. In Equation (9), if the regression coefficient estimate of DC is not significant, but the regression coefficient estimate of PFL is significant, indicating that PFL has a complete mediation effect; if both are significant, but the regression coefficient estimate of DC is smaller than the regression coefficient estimate of PFL, then PFL has a partially mediation effect.The Yangtze River Economic Belt covers 11 provinces and cities including Shanghai, Jiangsu, Zhejiang, Anhui, Jiangxi, Hubei, Hunan, Chongqing, Sichuan, Yunnan, Guizhou, etc., with an area of about 2.0523 million square kilometers, which accounts for 21.4% of the country’s population. The Yangtze River Economic Belt spans three major regions of China’s eastern, central, and western regions, and has unique advantages and great development potential. Based on the availability of data, the relevant data of 106 cities in the Yangtze River Economic Belt from 2007 to 2016 were selected for the analysis. All data are drawn from the EPS database (http://olap.epsnet.com.cn/) and Chinese Research Data Services Platform (CNRDS, https://www.cnrds.com/Home/Login). Descriptive statistics for the data are shown in Table 1.MaxDEA software is used to build a super-SBM model with undesirable output to measure the green innovation efficiency of 106 cities. Additionally, this paper use different colors to show differing efficiency values across cities by ArcGIS, as shown in Figure 1 and Figure 2.Figure 1 and Figure 2 show that, the green innovation efficiency of 106 cities in the Yangtze River Economic Belt was generally low in 2007. The green innovation efficiency of downstream cities was relatively high, such as Shanghai, Jiangsu and Wuxi, the differences between other cities were not obvious. However, in 2016, the overall green innovation efficiency of the Yangtze River Economic Belt has increased significantly, especially in the downstream cities. At th same time, the green innovation efficiency in the midstream and upstream cities has increased, but the gap between the upper, middle and lower reaches has also increased, this may be due to the agglomeration effect, the cities with high green innovation efficiency drive innovation in surrounding cities.Figure 3 and Figure 4 (They are made by “ArcGIS-xy to line”) show that the innovation contacts between the 106 cities in the Yangtze River Economic Belt, and the thick line represents more contacts, this article hides the line between the cities with lower innovation contacts.In 2007, in the downstream area, only three cities have more innovation contacts with other cities, but they have more contacts with neighboring cities and less contact with distant cities, while there are very few innovation contacts between the midstream and upstream cities. In 2016, The innovation contact network of downstream cities continues to expand, and the number of innovation contacts continues to increase. The network with Yangzhou, Zhenjiang, Wuxi, Changzhou, Suzhou and Hangzhou as the core cities is very dense, the radiation effect and driving ability of the core cities are continuously improving, this causes the number of core cities to increase. The core cities in the midstream regional network are mainly Wuhan, Changsha and Yichun, these cities have higher centrality in the innovation network. There are few core cities in the upstream city network, but compared to 2007, the number of innovation contacts in the upstream cities has increased significantly. In addition, downstream cities not only create innovation contacts with surrounding cities, but also have more innovation contacts with cities in other river basins, such as Chengdu and Bazhong. From Figure 1 to Figure 4, maybe the more innovation contacts with other cities, the higher green innovation efficiency of cities. Next, we try to use spatial econometric model to prove this conclusion.Based on the above model setting and testing ideas, Stata software is used to construct the optimal econometric model to explore the correlation between the city centrality and green innovation efficiency, the regression results are presented in Table 2. The results of the spatial autocorrelation test indicate that the spatial econometric model is suitable for this study.The OLS regression constitutes only a “flat domain” estimation of the parameters, which fails to reflect the spatial instability of the parameters in different spaces. Thus, the three spatial econometric models incorporating spatial correlation are selected for analysis. The Hausman test shows that all three models use fixed effects, in terms of the model-fitting effect, the SDM (Spatial Dubin Model) has higher R-sq than the SLM (Spatial Lag Model) and SEM (Spatial Error Model), while AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) are significantly lower. To further judge the fitting effect of the SDM model, this paper performs the LR test on the SDM model, the p values of the corresponding LR space lag test and the LR spatial error test are significant at the 1% level, thus the SDM model cannot be converted into the SLM model or the SEM model. Based on this finding, this paper selects the spatial SDM model for analysis. Table 2 reports the regression results of SDM model (the regression results of the SLM model and the SEM model are shown in Appendix A). Control variables are not added to Model 1, and Model 2 is the fixed effect model with control variables.In model (1), the regression coefficient estimate of DC is significantly positive, city centrality has a positive role in promoting green innovation efficiency, but the regression coefficient estimate of DC2 is negative, which indicates that there is an inverted U-shaped relationship between city centrality and green innovation efficiencyIn other words, when the city centrality is too large, it will lead to a decline in green innovation efficiency. In addition, we define the impact of city centrality on the green innovation efficiencies of other cities as the neighboring effect of city centrality—the regression coefficient estimate of W·DC is significantly positive, and the regression coefficient estimate of W·DC2 is significantly negative, after adding other control variables that affect the green innovation efficiency, the inverted U-shaped effect is more obvious. To sum up, moderate city centrality helps improve the green innovation efficiency in cities and surrounding cities, but when city centrality is too large, this effect is “harmful to others without benefiting oneself”, that is, it will inhibit their own and surrounding cities’ green innovation efficiency. The reason for this conclusion may be that the cities with lower centrality are less connected with other cities, the spillover of innovation is limited, which is not conducive to knowledge spillover or resource acquisition and hinders the development of technological innovation activities. Cities with higher centrality are more active in innovation activities with other cities, which reduces the cost of knowledge search, and it is more conducive to the acquisition of heterogeneous resources and the development of technological innovation activities. More importantly, the core cities in the innovation network can use their “prestige” and “status” to be learned and followed by neighboring cities, which is more conducive to the accumulation of knowledge and the improvement of overall innovation efficiency. However, the heterogeneity of innovation performance comes from the ability to acquire and absorb the elements of innovation input, when the centrality of the city is too high, it is difficult for cities with high centrality to fully absorb and utilize too much innovation elements, in addition, there would be siphon effects on the surrounding cities, which limits the green innovation efficiency of the surrounding cities.For example, many years ago, after the strategy for the rise of the central region was proposed, the overall innovation network of central cities was initially formed. Wuhan, Chengdu, Nanchang, and their surrounding cities developed rapidly, an urban circle with large cities driving small cities have been formed. But now, Wuhan is in an absolutely central position in the central region innovation network, howeve, its radiative effect on the surrounding areas is limited. The development of areas such as Huangshi, Xiaogan, and Xianning lags far behind Wuhan. These cities have not been affected by Wuhan’s knowledge spillover, instead, more talents returned to Wuhan to find work. In addition, Wuhan has the largest number of college students in China, but students from top universities are often reluctant to stay in this city after graduation or go to nearby cities. Therefore, Wuhan cannot absorb these innovation elements, which directly inhibits Wuhan’s innovation level.This article examines the different effects of city centrality on heterogeneous regions (upstream cities, midstream cities and upstream cities). Table 3 reports the regression results. Model (1), model (3) and model (5) respectively represent the regression without control variables, while the remaining three models contain control variables, in which the regression coefficient estimate of DC in each model are positive. Both are significant at the 1% level, but their influence on the upstream, midstream and downstream regions decreases gradually. This shows that the green innovation efficiency in the upstream region is more sensitive to the city centrality. In addition, in the upstream cities, the regression coefficient estimate of DC2 is approximately equal to 0, which indicates that the centrality of the upstream city is positively correlated with the green innovation efficiency. The industries in the upstream cities are mostly labor-intensive industries, these industries mainly require low-skilled labor, and there are fewer jobs for high-tech talents, so there is less innovation interaction and knowledge exchange in upstream areas, there is much room for improvement in centrality and green innovation efficiency. The regression coefficient estimate of W·DC is the largest in the midstream cities, this may be due to the midstream cities, as an important base to undertake industrial transfer in the downstream cities, has a strong ability to learn and absorb innovation, it is faster to improve their green innovation efficiency with the help of the spillover effect of the downstream cities.According to the three steps of the mediation effect test, Table 4 reports this result. Both the regression coefficient estimate of the core explanatory variable (DC) in the model (1) and model (2) are significantly positive, so city centrality positively influence the number of migrants; in model (3), the regression coefficient estimates of the core explanatory variables (DC) and mediator variable (PFL) are positively significant, and the former is smaller than the latter, which fully affirms the partially mediation effect of PFL, this result is similar to China’s actual national conditions. Due to the disappearance of China’s “demographic dividend” and the sharp decline in the number of labor forces, major cities, especially first-tier and second-tier cities, have lowered their settlement threshold, which directly affects the concentration of labor. High-level talents have flowed into more innovative cities based on the principle of “voting with their feet,” and these cities are often more central in the innovation network. The concentration of talents has further improved the city’s innovation efficiency. In addition, the regression coefficient estimate of W·PFL is significantly negative, which indicates that a large number of talents have flowed into the central city, the surrounding cities may be difficult to innovate because of the lack of necessary talents, so the flow of migrants has limited the green innovation efficiency of the surrounding cities.The cities with higher centrality enhance the green innovation efficiency by attracting the migrants that come from cities with lower centrality, but the negative effect is that the inflow of migrants into the central city limits the green innovation efficiency of surrounding cities. We think that the possible reason is that talents are the first element of innovation, cities with more high-level talents having the first mover advantage of innovation and development. In China, cities attract high-level talents through various policies, such as providing free housing for excellent talents, providing research funding for young scholars with excellent research ability, and rewarding enterprises and innovation teams that introduce high-level talents, these policies provide core guarantee for talents. In the cities with high city centrality, the supporting policies for talents are more attractive, so more talents choose to enter these cities, which directly promotes the green innovation efficiency.In summary, both hypothesis 1 and hypothesis 2 are true. This paper uses social network analysis and spatial econometric models to explore the impact of city centrality on the green innovation efficiency, and gravity model is used to prove that the number of migrants is a mediator variable in the effect of city centrality promoting green innovation efficiency. The conclusions of this article will contribute to expanding existing research in two aspects. On the one hand, although previous scholars have carried out in-depth research on city innovation networks, these studies mainly explored the evolution trend of city innovation networks and the influencing factors of city innovation networks [41,42,43]. No scholars have analyzed whether the structure of city innovation networks will affect innovation. In addition, existing research generally believes that higher degree centrality reduces the cost of acquiring knowledge and talent for network members, so the degree centrality positively affects innovation performance [25]. However, this article concludes that there is an inverted U-shaped relationship between city centrality and green innovation efficiency, which makes up for the lack of analysis of the positive and negative effects of centrality in the existing literature. On the other hand, this paper uses the modified gravity model to calculate the number of migrants, cities with high city centrality will attract a large number of migrants that come from cities with low city centrality to improve the green innovation efficiency. Previous research believes that communication and cooperation between enterprises can be used to create dynamic capabilities [44], which bring higher level of innovation and competitive advantage. Enterprises in the center of knowledge network have more ways to obtain innovation resources [45]. When an enterprise uses external resources for innovation, the ability to absorb and use these resources will affect its innovation performance [46]. And the closer an enterprise is to the center of the knowledge network, the more resources it can absorb and use [47]. This article uses data from 106 cities to prove that this conclusion also apply to city innovation networks. People are important elements of innovation, when city centrality is low, there is less innovation interaction between cities, so there is no innovation spillover, the green innovation efficiency of cities is low. When city centrality is high, cities with high city centrality absorb migrants to improve the green innovation efficiency. Although the number of migrants of cities with low city centrality reduced, there is innovation spillover effect between cities, this spillover effect will bring external economy to the cities with low centrality, which is not generated inside the cities, but comes from the cities with high centrality, the innovation interaction between cities is beneficial to the increase of overall green innovation efficiency. However, when city centrality is too high, the cities with high city centrality absorb too many migrants from the cities with low centrality, but it is difficult to absorb and make good use of these innovative elements, which limits the green innovation efficiency, although there is still innovation spillover effect between cities, the cities with low centrality are difficult to innovate due to the lack of innovative elements, so their green innovation efficiency dropped. It should be noted that the endogeneity between innovation network structure and innovation is one of the limitations of this article. We hope to consider the impact of innovation network structure on innovation with the method of causal inference that weakens the endogenous problem. This represents the direction of our future work, which includes not only networks between cities, but also network interactions between and within city groups.To check the robustness of the empirical results, the spatial adjacency weight matrix is used to replace the spatial distance weight matrix to test the benchmark model and mediation effect test [48], this helps to more carefully observe the degree of influence of the independent variable on the dependent variable and its spatial spillover effect. WL is the spatial adjacency weight matrix (If city i and city j are adjacent, each element in the matrix is equal to 1, otherwise it is 0).The results are shown in Table 5. Model (1) and model (2) report the robustness test results of benchmark regression, models (3)–(5) report the robustness test results of mediation effect test. The direction and significance of the regression coefficient estimates of each explanatory variable are substantially consistent with the results of the benchmark regression and mediation effect test. Thus, the results of the model are robust.There are many cases in China to prove these conclusion, for example, in the Wuhan city circle of China, the innovation level, GDP and employment of Wuhan are at the forefront. However, the development of the surrounding areas such as Xiaogan, Xianning and Xiantao is limited, and the gap with Wuhan is very obvious. The reason is that most of the high-tech migrants or low-skilled migrants in the cities around Wuhan have entered Wuhan to find jobs, which has greatly limited the innovation of surrounding cities. In addition, in the Beijing-Tianjin-Hebei city circle, Beijing’s population inflow is very high, but this has not increased the population inflow of surrounding provinces and cities (Tianjin and Hebei), and it is difficult for Beijing’s basic public facilities to provide supporting public services for such a large immigrant population, that is, it is difficult for Beijing to absorb these innovation factors, so the Xiongan New District with a non-capital evacuation function was established to undertake the population transfer in Beijing.This paper draws the following conclusions. First, from 2007 to 2016, there are more and more innovation contacts among 106 cities in the Yangtze River Economic Belt, and the innovation network is becoming more and more dense. The core cities of the downstream innovation network are mainly Yangzhou, Zhenjiang, Wuxi, Changzhou, Suzhou and Hangzhou; the core cities in the midstream are mainly Wuhan, Changsha and Yichun; the core cities in the upstream are Chengdu and Bazhong.Second, there is an inverted U-shaped relationship between city centrality and green innovation efficiency. In addition, the influence curve of centrality on the green innovation efficiency of surrounding cities also presents inverted U-shaped. Cities with high city centrality will attract a large number of migrants that come from cities with low city centrality to improve the green innovation efficiency, but the green innovation efficiency of cities with low city centrality will decline due to lack of talents. Therefore, proper city centrality can promote the green innovation efficiency to the greatest extent.Based on the above conclusions, this paper proposes the following policy recommendations. First, we should pay attention to urban planning and construction from the perspective of network. Regional development depends more on the division of labor and cooperation between cities, the status of cities in the whole system depends not only on their own attribute characteristics, but also on their relations with other cities. Therefore, when planning regional urban development, The government should examine the status and function of the city in the whole urban system from the perspective of urban network, pay attention to the external connection of the city, reasonably determine the orientation of urban development, avoid resource waste and repeated construction in the region; vigorously develop the urban economic zone, constantly support, cultivate and improve the network of urban economic zone based on the central city, and form a certain urban network structure through the aggregation and diffusion of the central city.Second, innovation connections have become the key of local or urban development. To achieve this kind of connection, the government not only needs to establish the local network within the region, but also needs to integrate the local economy into the global market and connect the external non local network. By using new information and network technology to improve its connection with other cities and enhance its accessibility, city centrality and technological innovation in the city innovation network can be greatly improved.Finally, we should strengthen the existing urban center position, cultivate new innovation growth poles and promote the diffusion of knowledge and human capital, but we must avoid the waste of human capital caused by the extremely centrality of the city. Each city must not lower the threshold to settle down without a limit, because this will cause “crowding of talents” and is not conducive to the improvement of urban green innovation efficiency.G.Y. put forward the idea, designed the study and reviewed the paper; H.W. performed the experiments, analyzed the data, wrote and reviewed the draft and put forward ideas and reviews; J.Q. collected data and edited the paper; and all of the authors contributed to the paper. All authors have read and agreed to the published version of the manuscript.This work was supported by the National Social Science Foundation of China (grant number 18ZDA040).We would like to thank the editor and the anonymous referees for their valuable comments on this paper.The authors declare no conflict of interest. The sponsors had no role in the design, execution, interpretation or writing of the study.Geary’ C:C=(n−1)∑i=1n∑j=1nW(xi−xj)22∑i=1n∑j=1nW∑i=1n(xi−xj)2n represents the number of cities, W represents spatial weight matrix, x represents variable what we want to test, C represents Geary’s C. When the regression coefficient estimate of Geary’s C is significant, indicating that there is spatial autocorrelation, we can use a spatial econometric model.Spatial autocorrelation test.Note: *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively, and Z values are in parentheses.Benchmark regression.Note: *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively, and Z values are in parentheses.To help reviewers better understand the mediation effect test, we have detailed the testing process of the mediation effect.
+		  
+		  
+          (A1)Y=cX+e1
+          (A2)M=aX+e2
+          (A3)Y=c′X+bM+e3
+          where the coefficient (c) of Equation (A1) is the total effect of independent variable (X) on dependent variable (Y); the coefficient (a) of Equation (A2) is the effect of independent variable (X) on mediator variable (M); coefficient (b) of Equation (A3) is the effect of mediator variable (M) on dependent variable (Y) after controlling the influence of independent variable (X); the coefficient (c′) is the direct effect of the independent variable on the dependent variable (Y) after controlling the effect of the mediator variable (M); e1~e3 are the regression residual. For such a simple mediation model, the mediation effect is equal to the indirect effect, that is, equal to the coefficient product (ab), and it has the following relationship with the total effect and the direct effect (MacKinnon, Warsi, & Dwyer, 1995):(A4)c=c′+abThe judgment conditions of mediation effect are shown in Figure A1.Judgment conditions for mediation effect test.The most commonly used method to test the mediation effect is to test the regression coefficients step by step (Baron & Kenny, 1986; Judd & Kenny, 1981). First, test the coefficient (c) of Equation (A1). Second, test the coefficient (a) of Equation (A2) and the coefficient (b) of Equation (A3) in turn. If both a and b are significant, than we test c′, if the regression coefficient estimate of c′ is significantly, M has a partial mediation effect. If the regression coefficient estimate of c′ is not significantly, then M has a complete mediation effect. If at least one of a and b is not significant, then we should do Sobel test.In our article, the result is the same as the second case in the Figure A1, Y is equivalent to GIE, X is equivalent to DC, M is equivalent to PFL. Furthermore, in Table 4 in our article, the regression coefficient estimate of the core explanatory variables (DC) is smaller than the regression coefficient estimate of mediator variable (PFL), which fully affirms the partially mediation effect of PFL.Green innovation efficiency in 2007.Green innovation efficiency in 2016.Number of urban innovation contacts in 2007.Number of urban innovation contacts in 2016.Descriptive statistics for the data.Benchmark regression.Note: *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively, and Z values are in parentheses.Heterogeneity test.Note: *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively, and Z values are in parentheses.Mediation effect test.Note: *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively, and Z values are in parentheses.Results of the robustness test.Note: *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively, and Z values are in parentheses.

Med-MDPI/ijerph_4/ijerph-17-02-00653.txt

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+Background: The Standardised Nordic Questionnaire (SNQ) is an instrument to analyse the musculoskeletal symptoms in an ergonomic or occupational health context. We aimed to cross-culturally adapt and evaluate the psychometric properties of the SNQ among Spanish musicians. Methods: Cross-cultural adaptation and psychometric validation (reliability, validity, and feasibility) was performed. Reliability was analysed by test-retest reliability (Cohen’s Kappa) and internal consistency (Kuder–Richardson). Content and face validity were measured by the Expert Committee and the opinion of participants. Construct validity (Mann–Whitney U test) was measured by comparing with questionnaires used to assess pain and disability in neck, shoulders, upper back, and low back regions. Feasibility was calculated with the average response time. Results: A total of 312 Spanish musicians were included. The Spanish version of SNQ achieved good semantic, conceptual, idiomatic, and content equivalence. For most of the variables, test-retest reliability was good to very good (k = 0.60–0.81). The internal consistency showed good to acceptable (Kuder–Richardson 20 (KR20) = 0.737–0.873). Participants with versus without musculoskeletal problems in a related region showed significantly higher disability/pain, indicating a good construct validity. About the feasibility, the average response time of the questionnaire was 6 min (±2). Conclusions: The results show that the Spanish SNQ is reliable, valid, and feasible screening tool to assess musculoskeletal problems among musicians.Musicians require a long training, dedication, study, and practice, performing often into repetitive movements and maintaining postures for long time. These factors can cause pain and musculoskeletal disorders, in fact, playing-related musculoskeletal disorders are one of the main medical problems among musicians [1]. Pain is the primary symptom, but it may be variably described as aching, burning, electrical, or pulsating [2]. Reported point prevalence rates of musculoskeletal complaints varied from 57% to 68% for all musculoskeletal complaints, and from 9% to 68% for playing-related complaints. Playing-related 12-month prevalence ranged between 62% and 93% [3]. The neck, shoulders, and low back were the most frequently affected regions [3,4].Thus, the evaluation of playing-related musculoskeletal disorder in the musician´s occupational context is an important outcome, in order to quantify, classify, and design an adequate treatment. The most commonly used instrument to detect the musician with symptoms is the Standardised Nordic Questionnaire (SNQ) [5,6,7,8,9].The SNQ was developed in 1987 by Kuorinka et al. from a project funded by the Nordic Council of Ministers. It is an internationally self-administered questionnaire designed to evaluate musculoskeletal problems in an ergonomic or occupational health context. It consists in two parts: The general part and the specific lumbar, neck, and shoulders questionnaires. The SNQ has proved to be a valid, reliable, and feasible tool that allows for comparison of musculoskeletal problems among different anatomical areas in epidemiological studies [10]. With these studies, specific health promotion and prevention measures can be designed for each work environment. In general, it shows a good concordance with the functional clinical evaluation, but it should not be used as a tool to confirm the diagnosis of a disorder or a pathology, because it presents an important amount of false positives [11].The SNQ has been adapted and validated to other languages [11,12,13,14,15,16,17], but the Spanish version has not been found. In order to analyse the situation of the musician in Spain, a cultural adaptation and validation of SNQ to the Spanish population is necessary. It will allow to compare results in Spain with those of other countries or between different labour population, and to draw conclusions about the relationship of these symptoms with other factors.The aim of the present study has been adapting the original English SNQ into Spanish, and evaluating its psychometric properties of validity, reliability, and feasibility among Spanish musicians.A cross-sectional observational study was conducted from November 2016 to May 2018. The study reporting followed the “Strengthening the Reporting of Observational studies in Epidemiology” (STROBE) guidelines [18].Participants were musicians recruited from public and private music schools, conservatories, and orchestras in the Community of Madrid (Spain), who fulfilled the inclusion criteria: They had played at least one musical instrument, for a minimum of 5 h per week, for over 16 years; and were native Spanish speakers, thus being able to read and to understand the Spanish language. An exponential discriminative snowball sampling technique was used. It was distributed a package of online open questionnaire by email, WhatsApp, and via Facebook, that included information about the study and the informed consent. Before starting the questionnaire, the participant had to express their consent by clicking on “NEXT”. Then, he had access to the sociodemographic and instrumental practice data, and to the Spanish versions of the Standardised Nordic Questionnaire, the Oswestry Disability Index, the Neck Disability Index, and the Shoulder Pain and Disability Index.The package of questionnaires was administrated by means of the Google Forms platform, which allows to access and to reply the instrument from any type of electronic device with an Internet connection. Validations of questionnaires have already been done using online applications, proving them to be a useful tool [19,20].The response rate could not be controlled.The study was developed in three phases according to the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) [21].Firstly, the original version of SNQ was translated into Spanish by two English–Spanish translators, who (native Spanish speakers) worked independently. The translators and the research team agreed the Spanish translation synthesis. Then, this first Spanish version was back-translated into English by two bilingual Spanis–English translators (native English speakers) worked independently from one another, to verify that the translation reflected the same content as the original. With the first version of the questionnaire and with the back-translated versions, an Expert Committee agreed the preliminary SNQ Spanish version was equivalent to the original instrument.The preliminary SNQ Spanish version was administered to 25 participants who fulfilled the inclusion criteria to reach the final SNQ version. They self-completed the questionnaire, and afterwards, they were interviewed in order to identify and correct potential understanding difficulties of the items and the quality of cultural adjustment. Finally, SNQ Spanish version was obtained.The SNQ Spanish version was administered until it reached a sample of at least 136 symptomatic participants and 80 asymptomatic participants. The sample size has been based on the general recommendations of Altman [22] and Terwee et al. [23], that recommend at least 50 subjects for the evaluation of the measures; and on Bryant & Yarnold [24], who recommend that the relationship between participants and variables be not less than five [25]. The sociodemographic data of the entire sample were collected. To perform the analysis of convergent construct validity, participants were asked to fill in, in addition to the SNQ Spanish version, the Oswestry Disability Index [26], the Neck Disability Index [27], and Shoulder Pain and Disability Index [28].The SNQ is divided in two parts, the general and the specific part. The general part of the SNQ consists of 27 questions with dichotomous response (Yes/No) about musculoskeletal symptoms during the last 12 months or the last 7 days and about the impact on activities during the last 12 months [10]. All these questions refer to 9 areas: Neck, shoulders, elbows, wrists/hands, upper back, low back, hips/thighs, knees and ankles/feet. For facilitating the identification of the anatomical areas, it also includes a corporal diagram seen from behind. The specific parts of the questionnaire delve into the analysis of symptoms of the lumbar, neck and shoulder regions with dichotomous response (Yes/No) or with the timing of the problem [10].The Oswestry Disability Index is a self-applied questionnaire specific for low back pain that measures limitations in daily activities that can be affected by pain and is validated in Spanish [29]. Higher scores show a higher level of disability [26].The Neck Disability Index is a self-completed questionnaire specific for cervical pain that measures limitations in daily activities. It is validated in Spanish [30]. A higher score shows a higher level of disability [27].The Shoulder Pain and Disability Index is a self-reporting questionnaire that measures shoulder pain and disability. It is validated in Spanish [31]. Higher scores in each subscale imply greater pain intensity and greater disability [28].The SNQ Spanish version was tested for reliability, validity, and feasibility.Reliability was assessed by internal consistency and test-retest reliability. The internal consistency, which is determined by the degree to which all elements measure the same, has been studied by comparing the answers to the questions about the troubles and/or disability in neck, shoulder, or low back regions contained in the general questionnaire and the dichotomous questions contained in the corresponding specific questionnaires. It was measured using Kuder–Richardson formula (KR20), which ranges from 0 to 1. Values above 0.9 are considered, excellent; between 0.8 and 0.89, good; between 0.7 and 0.79, acceptable; between 0.6 and 0.69, questionable; and below 0.6, poor or unacceptable [32]. Test-retest reliability is the degree to which a measuring instrument provides stable results on repeated administration when the domains to be measured have not changed [33]. It was assessed in 25 participants who completed the questionnaire a second time, 3–4 days after the first test, and it was evaluated by the Cohen´s Kappa coefficient (k), for which the values range from 0 (without agreement) to 1 (perfect agreement). Values above 0.81 show very good agreement; between 0.61 and 0.8, good; between 0.41 and 0.6, moderate; between 0.21 and 0.4, weak, and below 0.20, poor [22].Validity identifies the degree to which an instrument measures what it is designed for. This was assessed through content, face, and construct validity. The content validity was evaluated by the Expert Committee created for the translation and cultural adaptation of the questionnaire to the Spanish version. Face validity was evaluated by the opinion of the participants in the pilot study, who analysed the scale and decided whether it really seemed to measure what it was proposed for. Construct validity was measured by comparison with questionnaires that are used to assess pain and disability in neck, shoulder, upper back, and low back regions. Answers of SNQ were dichotomous, since we could not measure the construct validity by using correlation analysis. Therefore, we hypothesised that participants with musculoskeletal problems in a related region would have significantly higher disability/pain levels as assessed by the relevant questionnaires. Because these instruments are relevant to short-term situations, it was analysed using items regarding musculoskeletal symptoms during the last 7 days of the general questionnaire of the SNQ. This construct validity was evaluated using the Mann–Whitney U test [16]. For that, the result correlations of the SNQ Spanish version with the Oswestry Disability Index, the Neck Disability Index and the Shoulder Pain and Disability Index Spanish versions were calculated.To evaluate feasibility, the average administration time was calculated by the mean.A p value < 0.05 was considered statistically significant.The data were performed using the IBM ® Statistical Package SPSS, version 24.0 (IBM, Armonk, NY, USA).Translation and cultural adaptation of the questionnaire revealed no difficulties. Only the question regarding work experience time was modified, asking the subject only for the years of experience instead of for the months and years, facilitating the fill in of the questionnaire. After analysing the records for participants’ doubts and suggestions, consensus about translation of the SNQ was obtained and a definitive questionnaire was conducted. The cross-cultural adaptation of the SNQ Spanish version achieved a good semantic, conceptual and content equivalence (Supplementary Material Table S1).A total of 361 responses were received. Forty-nine responses have been excluded for not meeting the inclusion criteria and 312 responses have been included. Of the total sample, 160 (51.3%) musicians were men. The median age was 25 with an interquartile range (IQR) of 16. The average body mass index was 23.43 with a standard deviation of 3.89. The median number of years playing was 15 (IQR 13.75) and the median hours of weekly practice was 10 (IQR 14). Regarding the instrumental group, 97 musicians (33.1%) played string, 35 (11.9%) keyboard, 99 (33.8%) woodwind, 34 (11.6%) brass, and 28 (9.6%) percussion.In the analysis of the test-retest reliability of the general questionnaire, only the question regarding the dorsal area and the prevention from doing normal work at home or away from home showed a weak agreement (k = 0.359 (95% CI: -)); for the lumbar area, a moderate agreement was obtained (k = 0.595 (95% CI: 0.183–1.000)). For the other variables in the general questionnaire, good and very good agreements were obtained. For some variables, it was not possible to compute the test, because all individuals gave the same answer for the two applications of the questionnaire. The Kappa agreement correlation coefficient of the general questionnaire can be seen in Table 1.In the specific questionnaires, the variable related to the reduction of leisure activities during the last 12 months due to neck problems obtained a weak agreement (k = 0.254 (95% CI: -)) and the variables related to having neck problems at some point in life and if lumbar problems had caused to change jobs or duties obtained a moderate agreement (k = 0.503 (95% CI: 0.019–0.988)). The rest of the variables obtained good and very good results. The results are shown in Table 2.The internal consistency of all the variables of each region was good (neck, KR20 = 0.817 (95% CI: 0.786–0.846); shoulders, KR20 = 0.873 (95% CI: 0.851–0.893); lumbar, KR20 = 0.839 (95% CI: 0.811–0.865)). For the severity of the problem in the shoulders, a good internal consistency was also obtained (KR20 = 0.856 (95% CI: 0.830-0.879)). For the rest, acceptable values were obtained, as available in Table 3. The internal consistency of the general questionnaire was 0.835 (95% CI: 0.807–0.860).In the evaluation of construct validity, there was a significant difference in the neck and shoulder disability/pain level assessed respectively by the Neck Disability Index and the Shoulder Pain and Disability Index, among participants with musculoskeletal problems in the neck or shoulder region versus participants without them. The participants who reported upper and low back problems had significantly more disability assessed by Oswestry Disability Index. The construct validity results are showed in Table 4.The average response time of the questionnaire was 6 min (±2).The SNQ is a questionnaire that allows for examining the extent of a problem and recognizing its importance in the workplace. It is a first step to see if there are musculoskeletal health problems and to evaluate the evolution of the situation, although it does not allow for attributing the causes of the problems [34]. It is a widely used questionnaire because it is easy and quick to answer. It is validated in Turkish [16], European Portuguese [12], Brazilian Portuguese [13], Greek [15], Chinese [17], Italian [14], and Chilean [11].The translation/back translation process used to obtain SNQ’s Spanish version has been similar to other SNQ validations [12,13,14,15,16]. The linguistic adaptation process showed that musicians easily understand SNQ’s Spanish version. At the end of the questionnaire, a section for comments was added in, and several musicians suggested asking about musculoskeletal problems in the face area, due to the orofacial problems presented by musicians.In the present study, the sample size was 312 musicians. The sample calculation indicated that at least 136 responses were necessary. The Turkish validation calculates the sample size using the internal consistency data of the European Portuguese and estimating an interval confidence of 95%. In total, they estimated a sample size of 193 participants [16]. The Chilean validation calculated the sample size based on the method used in the original validation [10]. They deemed it necessary to include 20 participants by employment title, so to assess six different work-types, they calculated the sample size in 120 participants [11]. The other validations do not estimate the sample size calculation. They used samples of 40 [13,14] or 60 participants [12]. The response rate could not be controlled.The results of the test-retest reliability of the general questionnaire are good and very good for the specific questionnaires, good and very good values were also obtained. Four questions obtained a moderate agreement and one question obtained a weak agreement (two questions in general questionnaire and three questions in specific questionnaires). These questions refer to problems over the last 12 months or at some point in life, so memory bias may influence the responses of the participants. Moreover, except for the question referring to the presence of problems in the neck, which refers to the severity of the problem, the other questions with lower agreements refer to the impact on the activities. Between questions with good and very good agreements, this fact is also repeated, and better results are obtained for questions about the severity of the problem. A possible explanation is that for the participant it is easier to assess if he has had a problem and the intensity of it, than to assess the impact that this problem has actually caused on the activities. The other SNQ versions also obtained good and very good results for most of the questions [12,13,14,15,16]. In the Brazilian Portuguese version, they obtained a moderate agreement value for pain in the last seven days at the elbow. They think that, regardless of the stability of the instrument, the medical condition of the participant may change at the time of retesting. In addition, by answering a second time, they can respond in a careless manner, resulting in lower stability [13]. The lowest Kappa values were in a range between 0.21–0.40, that reflects weak agreement rates in these questions, but in any case, indicated no agreement or slight agreement. Therefore, no questions were excluded from the validated version and it has been decided to keep the same questions as in the original version.The agreement values have been analysed for questions that are repeated identically or similarly between the general questionnaire and the specific questionnaires. The questions about problems in the last seven days in the lumbar region and the neck, and about problems in the shoulder during the last 12 months, have obtained equal or similar values, while for the variable shoulder problems in the last seven days, a moderate agreement in the general questionnaire was obtained (k = 0.615 (95% CI = 0.296–0.934)), whereas in the specific questionnaire, a perfect agreement value was obtained (k = 1 (95% CI = -)). One explanation for this could be that better agreements are obtained in the specific questionnaires, but they are slightly higher in the other variables of the general questionnaire.In the present study, the internal consistency has been calculated with the KR20 formula. This is a specific case of Cronbach’s alpha for dichotomous questions. The internal consistency of the general questionnaire is good (KR20 = 0.835), similar to the Turkish validations (Cronbach’s alpha = 0.896) [16] and the European Portuguese (KR20 = 0.855) [12]. However, we believe that these values can be the result of chance, since we would have to assume a correlation between variables, such as having problems in the ankle and having problems in the neck, body areas that are not necessarily related. For this reason, similar to the work done in the Italian validation, we compared the questions of the body areas lumbar, neck, and shoulder of the general questionnaire with their respective specific questionnaires, obtaining good values [14]. The internal consistency of the questions referred to the severity of the problem and the questions related to the impact on the activities have also been analysed separately, in a similar way to the online, extended version of the SNQ [19], finding good and acceptable values, being these values for the shoulder region, and for the items on the severity of the problem slightly higher.A correlation analysis could not be used to analyse the construct validity. It was analysed in the same way as in the Turkish version. They hypothesised that participants with a musculoskeletal problem at related regions would have significantly more disability/pain measured with other relevant questionnaires [16]. Construct validity has been shown to be statistically significant for the assessed regions (lumbar, dorsal, neck and shoulders). One limitation of this study is not having analysed the rest of the body areas (lower limbs, elbows, and wrists/hands).The average response time of the questionnaire was assessed in the test time and it was 6 min (±2). Other SNQ validations have not assessed this aspect of the questionnaire, so our result cannot be compared.The results of the present study showed that the SNQ Spanish version has a semantic, conceptual, idiomatic, and content equivalence with the original version. It is an easy to apply questionnaire, as well as being a reliable, valid, and feasible screening tool to assess possible musculoskeletal problems within the workplace.The following are available online at https://www.mdpi.com/1660-4601/17/2/653/s1, Table S1: The SNQ Spanish Version.Conceptualization, R.G.-R., B.D.-P. and M.T.-L.; Methodology, R.G.-R., B.S.-S. and M.T.-L.; validation, R.G.-R. and B.S.-S.; Formal analysis, C.G.-O.; Investigation, R.G.-R.; Writing—Review and editing, R.G.-R., B.S.-S., M.T.-L., C.G.-O. and B.D.-P.; supervision, M.T.-L. and B.D.-P. All authors have read and agreed to the published version of the manuscript.This research received no external funding.The authors want to thank all the volunteers for their participation in this study.The authors declare no conflict of interest.The Kappa agreement correlation coefficient for each answer in the general questionnaire (n = 25).* Could not be computed because all variables were constant. CI: Confidence interval.The Kappa agreement correlation coefficient for each answer in the specific questionnaires (n = 25).NSQ: Neck specific questionnaire; SSQ: Shoulder specific questionnaire; LBSQ: Low back specific questionnaire. CI: confidence interval.Internal consistency verified by the Kuder–Richarson coefficient of reliability (n = 312).KR20 of the general questionnaire = 0.835 (95% CI: 0.807-0.860).KR: Kuder–Richarson; NSQ: Neck specific questionnaire; GQN: General questionnaire, neck; SSQ: Shoulder specific questionnaire; GQS: General questionnaire, shoulders; LBSQ: Low back specific questionnaire; GQLB: General questionnaire, low back. CI: confidence interval.Comparison of the disability levels assessed by the relevant questionnaires between the participants with versus without a musculoskeletal problem during the last 7 days (n = 312).Md: Median; IQR: Interquartile range; (a) Neck disability index; (b) Shoulder pain and disability index; (c) Oswestry low back disability index.

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+A few decades ago, robotics started to be implemented in the medical field, especially in the rehabilitation of patients with different neurological diseases that have led to neuromuscular disorders. The main concern regarding medical robots is their safety assurance in the medical environment. The goal of this paper is to assess the risk of a medical robotic system for elbow and wrist rehabilitation in terms of robot and patient safety. The approached risk assessment follows the ISO12100:2010 risk management chart in order to determine, identify, estimate, and evaluate the possible risk that can occur during the use of the robotic system. The result of the risk assessment process is further analyzed using a fuzzy logic system in order to determine the safety degree conferred during the use of the robotic system. The innovative process concerning the risk assessment allows the achievement of a reliable medical robotic system both for the patient and the clinicians as well. The clinical trials performed on a group of 18 patients validated the functionality and the safe behavior of the robotic system.Stroke is usually defined as a sudden interruption of blood and nutrients flow to the brain. The longer time for which the flow is interrupted, the more severe are the consequences of the stroke [1]. Usual symptoms of an ongoing stroke are speaking difficulties, trouble in understanding, paralysis or in some cases numbness of arm or leg, difficulties in seeing with one or both eyes, headaches, or walking difficulties [2]. The survival rate after a stroke decreases with age and it is reported to be about 81.9% among men and 77.4% among women aged between 25 and 69 years old [3]. About 70% of stroke survivors suffer a certain level of upper limb disability [4] and every survivor needs a qualified person to deliver a specialized training in order to reduce or eliminate the disability. Post-stroke rehabilitation of upper limb is usually carried on through repetitive motions of the impaired limb in order to regain the capability to perform daily tasks using the disabled limb.Given the growing lifespan of the population [5], the number of people suffering a stroke is expected to heavily increase in the near future, yielding a large number of qualified personal to work in post-stroke rehabilitation of survivors. In order to overcome this difficult situation, robotic structures for post-stroke rehabilitation of upper or lower limb started to be developed, being a suitable aid for the kinetotherapist performing the repetitive rehabilitation motions. In the last decades, a series of robotic structures for medical rehabilitation of the upper limb have been developed and analyzed by Huang [6], Al-Fahaan [7], Vaida [8,9], Carbone [10], Görgülü [11], Husty [12], Berceanu [13], Tarnita [14], Gherman [15], Tucan [16] and furthermore systematically reviewed by Ona [17,18], Baur [19], Onase [20], and Rehmat [21]. Some significant research prototypes are presented below.Li et al. [22,23] propose a 5-degrees of freedom (DOFs) robotic structure (Co-Exoskeleton) composed of serial PPRRRP and RRP (where P stands for Prismatic joint and R stands for Revolute joint) mechanisms having five active revolute joints and four passive sliding joints distributed along the upper-body. The robotic structure is able to perform the adduction/abduction, flexion/extension and internal/external rotation of the shoulder, internal/external rotation of the forearm and flexion and extension of the elbow. The entire robotic structure is composed from an adjustable turntable, a cantilever, and the exoskeleton. The exoskeleton is mounted on a liftable column adjustable to different patients’ heights. The cantilever can rotate the exoskeleton to fit different shoulder types. The exoskeleton is suitable both for right arm and left arm rehabilitation. The advantage of this device is that it uses a binding vest to fix the patient to the chair and the modular design of the structure allows the use of the robotic device either as a shoulder rehabilitation device with 3DOf or as an elbow rehabilitation device with one DOF. The authors stated that improvements must be made to the kinematic model of the rehabilitation device in order for this to be implemented in the control system of the exoskeleton.NESM [24] is an exoskeleton for shoulder and elbow rehabilitation mounted on a mobile platform. The robot contains four active revolute joints (three for the shoulder and one for the elbow). The motions performed with the exoskeleton are adduction/abduction/flexion/extension/internal rotation/external rotation of the shoulder and flexion/extension of the elbow. The robot has a modular structure divided into three sections: shoulder section, arm section and elbow section and it uses two main training control strategies: robot-in-charge (the robot performs preplanned motions with joint in position control)  and patient-in-charge (the robot operates using torque mode control enabling the robot to adapt to spontaneous motions of the patient’s arm).  The advantage of this rehabilitation system is that it benefits of a complex control system, able to adapt to various rehabilitation motions and to different anthropometric characteristics of the human arm. Future work regarding this device implies development of algorithms for inertia compensation. Also, the mass distribution in the mechanism is important when designing an exoskeleton (the mas of the moving structure is 12 kg) due to the fact that in the case of a power failure it is possible that the entire weight of the device to be projected onto the patient’s arm.ETS-MARSE [25] is a redundant robot for the rehabilitation of the upper limb with 7-DOF. The design of the robotic structure is inspired from the human anatomy in order to offer a comfortable rehabilitation procedure for the patient. The shoulder joint is mimicked using three active revolute joints, the first one for adduction/abduction, the second one for flexion/extension and the third one for internal/external rotation of the shoulder. The elbow joint motion is performed using one active revolute joint. The other three DOFs are for pronation/supination of the forearm, radial /ulnar deviation and flexion/extension of the wrist. The control of the robotic system has the ability to adapt to different forces from the system through integration of an external force observer to identify the force of the patient. The advantage of this robotic system is the capability to perform every motion of the human arm due to its redundant configuration. At the time of research, the system was only tested as a passive rehabilitation device making it suitable only for the rehabilitation of the patients that recover some motricity after the stroke.A medical rehabilitation system should be of a low degree of complexity both in design (low number of active mechanisms and actuated joints) and control (the number of possible failure modes increases with the degree of complexity of the control system). This paper presents a 4 DOF robotic system for elbow and wrist rehabilitation that uses an industrially tested and accepted control system able to overcome most of the risks associated with the rehabilitation task.A considerable effort in ongoing research activities is spent on providing improved characteristics in terms of efficiency of manipulation and motion trajectories of the robotic structures used in upper limb rehabilitation. Along these technical characteristics of the robotic structures used as medical devices, some aspects regarding the social acceptance and the assured safety during the medical procedure need to be carefully analyzed and optimized (if necessary). Even though for a high safety degree, a complex sensor system should be used (use of internal sensor system to initialize the robotic system and monitor the behavior of the system; use of external observers to monitor the interactions between the robotic system and the patient; use of biosensors mounted on the patient to monitor the forces and displacements during the rehabilitation process) attention should be concentrated into creating a comfortable environment for the patient whom may be overstressed by prolonged preparation times before the rehabilitation procedure (time spent in mounting biosensors or electrodes on the impaired limb or use of brain computer interface that uses multiple electrodes) or the uncomfortable position during the procedure altering in the end the effects of the procedure.Safety is one of the most important aspects of a medical device due to device’s working environment and conditions. Being a device that shares its workspace with the user (patient) a robotic system for upper limb rehabilitation should comply with every safety-related regulation (ISO13482 [26], ISO10218 [27], IEC 6061-4-44:2015 [28], ISO 12100:2010 [29], IEC 80601-2-78:2019 [30]), but sometimes this may not be sufficient to provide a safe robotic rehabilitation system both for patients and clinical personal operating it, for this, means of identifying, estimating and evaluating the risk should be used. One way to identify and overcome most of the risks implied by working with a medical device is to follow a risk assessment process. The output of a risk assessment is given by the severity of the hazards and the probability of the identified hazards (risks) and it should provide the means to achieve a safer device. Achieving safety through risk assessment is a method preferred by some researchers [31,32,33,34] because it provides statistical data without the need of a complex mathematical model to compute the results, based on the opinion of different persons from different research domains.This paper presents a risk assessment process of a parallel robot for lower limb rehabilitation in order to identify different possible unsafe situations that can occur during the progress of the rehabilitation process. The risk assessment follows the risk management chart provided by ISO12100:20100 referring to safety in machinery. A fuzzy logic inference algorithm is used in order to avoid the uncertainties in human thinking in terms of providing objective information regarding the functionality of the robotic system. The ParReEx robotic system for wrist and elbow rehabilitation of stroke survivors is presented in terms of kinematic scheme and the experimental model. In the end, the safety provided during the rehabilitation procedure is validated by clinical trials using the robotic system.The second section of the paper refers to Materials and Methods and it provides data regarding the robotic elbow and wrist rehabilitation system. Also a risk assessment process is described in order to identify the hazards that may occur during the rehabilitation process followed by the determination of the risk level for each hazard using fuzzy logic. The third section of the paper refers to the Results obtained during the research process and it provides data regarding the experimental model of the elbow and wrist rehabilitation robotic system and the functional validation of this robotic system by means of experimental tests performed in hospital environment on real patients. The fourth and fifth part of the paper contains the discussions and the conclusions regarding the research work presented within the paper. ParReEx [35,36] robotic system is composed from two independent parallel modules: ParReEx-elbow (Figure 1a) for rehabilitation of the elbow and ParReEx wrist (Figure 1b) for rehabilitation of the wrist.The module for elbow rehabilitation has 2 DOFs and is composed of two kinematic chains. First kinematic chain is of type RU (where R stands for Revolute joint and U stands for Universal joint) and has its origin in the fixed coordinates system XYZ (Figure 1a). The active joint of this kinematic chain is q1, a revolute joint collinear with OX axis. Using link a the motion of q1 is transmitted to the passive cardan joint Rc which is connected with the mobile coordinates system X’Y’Z’ through link b. The second kinematic chain is of RR type and is actuated by q2 revolute joint connected to link b through link c and passive revolute joint R2. The module for elbow rehabilitation performs the pronation and supination rehabilitation motion of the forearm using q1 joint and flexion and extension motion of the forearm using q2 joint. The module for wrist rehabilitation is a 2 DOFs mechanism too. The fixed coordinate system is placed at the intersection of the rotation axes of active revolute joint q3 and passive revolute joint R’1 and the mobile coordinate system is placed at distance r (Figure 1b). The center of rotation for the wrist is placed in the fixed coordinates system. The mechanism is also composed of two kinematic chains, first one is of RR type actuated by revolute joint q3 connected to the mobile coordinates system through passive revolute joint R’1 and link d. The second kinematic chain is actuated by q4 revolute joint that rotates the circular guide e around the O*Y* axis. The intersection of d link with the circular guide e is made through two revolute joints, R’2 (which slides on the circular guide e) and R’3 (passive revolute joint around O*’X*’ axis). The flexion and extension of the wrist is obtained through the kinematic chain actuated by q3 and the abduction and adduction through the kinematic chain actuated by q4.Risk assessment is an important step in risk management and it has the scope of determining risk context and acceptability, usually by comparison with a similar risk [38]. ISO12100:2010 [29] referring to “Safety of Machineries, General principles for design, Risk assessment and risk reduction” delivers a series of terms, useful in analyzing the degree of safety during the design of the machinery. The flow chart of a risk management analysis is given in Figure 2.First step in the risk assessment process is to define the limits of the machinery for this level of interaction between the patient and the robot should be defined.Ogorodnikova [39] defines in Table 1 the interaction levels between the robot and the human operator.Depending on the position in Table 1, a robotic device should fulfil different safety requirements. During the rehabilitation procedure, the patient shares the same workspace with the robot, resulting in a collaboration between the rehabilitation system and the patient. When the robotic system runs in normal conditions, the patient is seated near the rehabilitation system using either a liftable chair or a wheelchair, depending on the state of the patient, with the right arm attached either to the wrist rehabilitation system or to the elbow rehabilitation system. At the debut of the rehabilitation procedure, the patient has none or little control of the impaired limb, so the degree of help coming from the robotic rehabilitation system should be accordingly dosed. As the patient regains some capability to perform the motions by itself the degree of help coming from the robot would be gradually reduced.The limits of the robotic structure are given by the maximum range (degrees—[°]) of each rehabilitation motion, the range of motion performed using ParReEx are given in Table 2 and illustrated in Figure 3.The design of the robotic structure is based on the anthropomorphic data collected from systematical reviews and clinical studies regarding the stroke survivors that received medical care regarding the rehabilitation of the elbow and wrist [40].After the limits of the machinery have been defined, according to the flow chart from Figure 3, an analysis regarding the hazards must be carried on. Every hazard that can occur must be identified or else will be missed in the risk reduction stage. In the following lines are given the types of hazards that have been analyzed.Mechanical hazards
+          M1: The arm of the patient may be crushed by the moving mechanism. This hazard can occur due to incorrect posture of the patient, wrong parameters introduced in the control system (not suitable for patient movement capabilities), it can even be a consequence of power failure.M2: The patent may bruise or cut its hand in the sharp edges of the components of the robotic structure. This may occur due to improper design of mechanical components of the robotic system.M3: Motion limit exceeded. The robot either exceeds the moving capabilities of the patient or the moving mechanism goes over the end stroke limiters.M4: The patient may crush into the robotic structure. Usually, the patient is either carried using a wheelchair or if he can walk may suffer sudden loss of equilibrium.M5: The patient may have sudden spasms resulting in incontrollable motion of the body (e.g., Parkinson disease). The robot should be able to overcome and resist to this situation, allowing in the same time easy removal of the patient’s arm from the rehabilitation device.M1: The arm of the patient may be crushed by the moving mechanism. This hazard can occur due to incorrect posture of the patient, wrong parameters introduced in the control system (not suitable for patient movement capabilities), it can even be a consequence of power failure.M2: The patent may bruise or cut its hand in the sharp edges of the components of the robotic structure. This may occur due to improper design of mechanical components of the robotic system.M3: Motion limit exceeded. The robot either exceeds the moving capabilities of the patient or the moving mechanism goes over the end stroke limiters.M4: The patient may crush into the robotic structure. Usually, the patient is either carried using a wheelchair or if he can walk may suffer sudden loss of equilibrium.M5: The patient may have sudden spasms resulting in incontrollable motion of the body (e.g., Parkinson disease). The robot should be able to overcome and resist to this situation, allowing in the same time easy removal of the patient’s arm from the rehabilitation device.Electrical hazards
+          E1: Risk of electrocution of the patient.E2: Harming the patient due to sensor malfunction.E3: Crush the arm of the patient caused by the malfunction of stroke limiters.E4: Risk of short circuit.E5: Overloading the rehabilitation device.E1: Risk of electrocution of the patient.E2: Harming the patient due to sensor malfunction.E3: Crush the arm of the patient caused by the malfunction of stroke limiters.E4: Risk of short circuit.E5: Overloading the rehabilitation device.Thermal hazards
+          T1: The patient may suffer burns by coming into contact with overheating parts of the robot.T1: The patient may suffer burns by coming into contact with overheating parts of the robot.Noise hazards
+          N1: Due to the fact that the robot works quite close to the patient, the sound created by moving mechanisms may create some discomfort for the patient.N1: Due to the fact that the robot works quite close to the patient, the sound created by moving mechanisms may create some discomfort for the patient.Vibration hazards
+          V1: Patient may be harmed by loose parts from the robotic system.V2: Patient may be harmed by uncontrolled vibrations of the mechanism.V1: Patient may be harmed by loose parts from the robotic system.V2: Patient may be harmed by uncontrolled vibrations of the mechanism.Ergonomic hazards
+          ER1: The patient may fall due to the fact that he is in a wheelchair.ER1: The patient may fall due to the fact that he is in a wheelchair.After the hazards have been identified, it is time to estimate the probability and the severity of each risk, in order to do this, severity and probability categories need to be defined. In Table 3 the probability categories are defined and Table 4 contains the categories of severity.In order to determine the risk level of each identified hazard, input membership functions have been designed for Probability and Severity using Mamdani FIS (Fuzzy Inference System) provided by MATLAB [41] (Figure 4). The membership function for Probability is given in Figure 5a and for Severity in Figure 5b.The membership functions for Probability were modeled using triangular functions. For the membership function of probability rate Equation (1) was used, where the numerical values are taken from Table 3.
+          (1)μ(x)={0,x≤ax−am−a,a<x≤mb−xb−m,m<x<b0,x≥b}
+          where, a represents the lower limit of the interval, m represents the core of the membership (the core of the membership is the point where the degree of the membership function is maximum while all the others membership functions are 0, best example can be seen in the membership function of “Likely” that differs from the other membership functions, due to the fact that the core has to be positioned when the other membership functions are 0, the asymmetry is caused by the fact that the other functions are defined on the same interval length while the interval of membership function of “Likely” has a smaller length), b represents the superior limit of the interval within which the membership functions degree is different from 0.The membership functions for Severity and Risk Level were modeled using trapezoidal functions. For the membership function of probability rate Equation (2) was used, where the numerical values are taken from Table 4. 
+          (2)μ(x)={0,(x<a)or (x>d)x−ab−a,a≤x≤b1,b≤x≤cd−xd−c, c≤x≤d}
+          where, a represents the lower limit of the interval, b represents the inferior core value of the membership, c represents the superior core value of the membership and d represents the superior limit of the interval within which the membership functions degree is different from 0.The output membership function of “Risk Level” is defined in Figure 5c using the same scale as the previous membership functions. In order to obtain the risk level value, every degree of “Probability “is connected using logical operator “AND” with every degree of “Severity” as described in Table 5.Using the above-mentioned membership functions for inputs and outputs, correlated with the FIS rules form Table 5, the surface distribution of Risk Level is represented graphically in Figure 6.To evaluate the risk of every event, each hazard identified above needs to be the subject of a FIS. For this, using expertise of 15 different researchers from mechanical (7 researchers), electrical (3 researchers) and medical domain (5 clinicians) [16] some mean values in terms of severity and probability have been obtained for each hazard. The values were obtained using the questionnaire provided in Appendix A. Table A1 was used to record the probability and Table A2 was used to record the severity of each hazard. The final values obtained averaging the questionnaire data are given in Table 6.The Risk Level degree is computed by using mean value for each hazard as input in the FIS and following the defined rules. The result for each hazard is represented in Figure 7.After the risk assessment process has been concluded, a series of hazards that present medium or high risk resulted. In order to build a safe robotic system, the development team decided to find means to reduce every identified hazard. To reduce risk of M1, some proximity sensors should be mounted in the areas where collisions may occur, each axis should be equipped with torque sensors, the range of each motion should be limited by controller and an external measuring system should be used to directly measure the motion of the patient’s limb. To reduce the risk of M2, soft materials should be used to cover the parts that may be coming in the vicinity of the patient and again proximity sensors should be mounted in the areas where collisions may occur. To reduce M3 torque sensors should be mounted on each axis, the motion of each axis should be constrained mechanically and from the control unit. To reduce M4 end-stroke sensors should be mounted on each axis, and proximity sensors should be mounted in collisions susceptible areas. To reduce M5 the robotic system should be equipped with a passive mode switch, which allows the clinician to easily remove the patient’s arm from the robotic structure. To reduce E1, E4 and E5 proper regulated protection for the electric components of the system should be used. To reduce E2 and E3 a secondary sensor system should be used to check the position between the robot and the patient. T1 may be reduced by avoiding the use of parts that can generate or store heat when in use or avoiding using this kind of parts in areas where the patient in is direct contact with the robotic structure. V1 and V2 may be reduced by instructing the users to carefully check the robotic system for improperly fixed components before every procedure, and ERH1 may be reduced by using of harnesses to keep the patient in position during the rehabilitation process.In order to assure the safety of the ParReEx robotic structure the above-described method was used. After some means of reducing the risk have been provided the development of the experimental model of the robotic structure started. The safety features defined above are implemented in the developed experimental model of the ParReEx structure presented in the following paragraphs along with the experimental functional validation of the robotic structure.The ParReEx rehabilitation system is composed of two modules (Figure 8), one for elbow rehabilitation and the other one for wrist rehabilitation. Both modules share the same control box and the same control interface. The components of the robotic structure are mostly composed of 3D printed parts, providing in the same time, low fabrication times, high shape complexity which ensures a minimum number of moving components, low resilience material designed to break in case of emergency and the superior material softness to the parts manufactured from metal. Plastic was used mostly in the areas where the patient is in intimate contact with the robot (see anchor points), but for transmitting motion from the motors to the rehabilitation mechanism also some metal parts were used (brass bars, screws, gears). The mechanisms of the rehabilitation structure are actuated using 4 motors, controlled using a PLC and 2 drivers provided by Berneker & Reiner [42]. The control unit is integrated into a control box that acts in the same time as a support base for the entire robotic structure. In the case of unpredicted situations or emergencies the box is equipped with an emergency button placed on top of the box (see Figure 8).The module for elbow rehabilitation uses 3 anchor points to secure the patient’s arm during the rehabilitation procedure. One of these points is placed on the upper arm, one on the forearm and the third one on the hand of the patient (Figure 9a). The patient is carefully positioned in a sitting position in the vicinity of the robotic system (using liftable seat or wheelchair depending on the degree of severity of the impairment), and the right arm of the patient is attached to the rehabilitation device, using the previously described anchor points. The arm of the patient is kept secure in the correct position using Velcro elastic bands. The patient must grip the joystick of the elbow rehabilitation module in order to ensure the correct position of the arm during the elbow rehabilitation procedure. The motions for the elbow rehabilitation module are flexion/extension/pronation and supination. The flexion and extension is performed using the flexion/extension mechanism actuated through a conical reduction box by a servomotor. The pronation and supination motion is performed using also a servomotor but this time the motion is transmitted to the mechanism using a U joint and a spur gearbox.The module for wrist rehabilitation has two anchor points, one placed on the forearm and the other one on the hand (Figure 9b). To keep the forearm in the correct position a Velcro elastic band is also used, and the patient must grasp the joystick of the wrist rehabilitation module using the right hand. The motions for the wrist rehabilitation module are flexion/extension/adduction and abduction. The flexion and extension is performed using the flexion/extension mechanism actuated by a servomotor. The abduction and adduction motion is performed using a second servomotor but this time the link in motion is a circular guide that makes a sliding joint with the flexion/extension mechanism.The robotic system is controlled using a Graphical User Interface (GUI) designed to help the clinicians during the use of the rehabilitation system (Figure 10). The GUI is divided into two sections one for controlling the ParReEx-Elbow module and the other one for controlling the ParReEx-Wrist module. The state of the robot can be visualized using the 4 LED’s on the interface (Orange—the motors are not initialized, Red—the motors are in error state, Green—the motors are initialized and ready to receive commands, Blue—the motors are in motion). To activate each of the rehabilitation modules, the “Activate” button must be pressed, enabling the command that activates the motors and releases the brake. In order to initialize the robotic structure “Homing” button must be pressed and each axis will perform a motion towards the sensor position until the signal from the axis initialization sensor is received. After the axes are initialized the robotic system is ready to perform the rehabilitation task, for this, the range of motion for the patient’s upper limb should be provided in the GUI in terms of amplitudes, speed and number of repetition. After the parameters have been provided a dry run is suggested to check the behavior of the rehabilitation module. After the rehabilitation motion is correctly executed the patient may be seated with the arm placed in the rehabilitation module. In case of emergency, the GUI provides the possibility to cut the power of the controller by pressing the “Emergency Button”. In this case, the patient should be removed from the rehabilitation robot and the system must be re-initialized. If during the functioning of the robotic system, an error occurs, this can be acknowledged by pressing the “Error Reset” button. At the end of the procedure, if no other procedures are performed the system may be turned off by pressing the “Deactivate” button and turning off the main switch placed inside the control box.For validating the functionality of ParReEx robotic system, tests involving human patients have been performed. The approval for performing these tests was given by Institutional Regulatory Board (IRB) of Municipal Cluj-Napoca Hospital, Romania in 1 August 2019. Before performing clinical tests in the hospital environment, the robotic system was previously analyzed and approved for hospital use by the clinicians and for functional validation purposes, the clinicians selected a number of 18 patients with different pathologies and experiencing various degrees of disability of the right upper limb. Data regarding the patients involved in the clinical trials are given in Table 7.The experimental setup consisted of the rehabilitation system and a wheelchair to move the patients between the wrist and elbow rehabilitation modules, a human operator for the robotic structure, a kinetotherapist to evaluate the patient and define the rehabilitation plan and (when necessary) a stretcher-bearer to help in moving the patient from one rehabilitation module to another. The experimental tests were conducted for each patient on a 7 days period of time during which time the patient was admitted in the hospital. Table 8 provides data regarding the mean, minimum and maximum values recorded during the clinical trials, the following notions were used:No. of series—the number series of repetitions for each rehabilitation module;Rep/series—the number of repetitions for each series;Wrist F—flexion amplitude of the wrist [°];Wrist E—extension amplitude of the wrist [°];Wrist Add.—adduction amplitude for the wrist [°];Wrist Abd.—abduction amplitude for the wrist [°];Elbow F—flexion amplitude for the elbow [°];Elbow E—extension amplitude for the elbow [°];Elbow P—pronation amplitude for the forearm [°];Elbow S—supination amplitude for the forearm [°].No. of series—the number series of repetitions for each rehabilitation module;Rep/series—the number of repetitions for each series;Wrist F—flexion amplitude of the wrist [°];Wrist E—extension amplitude of the wrist [°];Wrist Add.—adduction amplitude for the wrist [°];Wrist Abd.—abduction amplitude for the wrist [°];Elbow F—flexion amplitude for the elbow [°];Elbow E—extension amplitude for the elbow [°];Elbow P—pronation amplitude for the forearm [°];Elbow S—supination amplitude for the forearm [°].The angular amplitudes given in the following table were actually the input data for the robotic system, introduced in the specially designed sections in the GUI.The tests performed using the PArReEx robotic system in the hospital environment, proved the functionality of the robotic system and the capability of performing rehabilitation motions of the elbow and wrist following a rehabilitation chart provided by a kinetotherapist. The plan imposed by the kinetotherapist implied a gradual increase in the amplitude of the performed motions. Snapshots taken from the videos recorded during the testing phase can be seen in Figure 11.The safe behavior of the robotic system was proved through “zero events” during the experimental tests (no scratches on the patient, no concussions caused by crashing into the robotic structure, no bruises, no burns, no noise discomfort for the patient and the personal, no electrical shocks or discharges and most important no discomfort for the patient). The robotic system was largely accepted both by the patients and by the clinicians.In the existing regulatory documentation are not clearly specified ways of assuring safe behavior of robotic systems used as rehabilitation devices. Thus, some of the regulation provide a series of paths to follow in order to be able to provide a solution reliable enough to successfully perform the given rehabilitation task, but for this, expertise from different research domains, such as mechanical, electrical, and medical, is required. This paper presents a method of achieving a safer behavior of the robotic structure used in rehabilitation of the wrist and elbow by means of risk assessment and fuzzy logic inference system. First, a risk assessment process is carried on in order to identify the possible hazards that can occur when using a wrist and elbow rehabilitation robotic system. After the hazards were identified, a FIS is used in order to estimate the risk of each hazard. For this, membership functions regarding the inputs (Severity and Probability of the hazard) and output (Risk level) of the FIS are defined using triangle and trapezoidal variance. After the inputs and outputs of the system have been defined, the inference rules of the FIS are defined with respect to a risk assessment matrix, and the output of the FIS is obtained and graphically represented as a surface graph. In order to estimate the risk level of every identified hazard, expertise of 15 mechanical, electrical, and medical experts is used to determine the mean score regarding the Severity and Probability of each hazard. The obtained mean score is used afterwards as numerical inputs for the FIS in order to determine the risk level for each hazard. The obtained risk level for each identified hazard was graphically represented and ways in reducing the overall risk of every hazard were provided.With respect to the safety requirements given in the risk reduction process, the experimental model of the robotic system ParReEx was presented in terms of mechanical structure, control system and GUI.In the development of the experimental model the following measures were taken to overcome the above-identified risks:Risk M1, M3, and M4: inductive proximity sensors have been mounted in order to constrain the mechanism within the allowable limits, no torque sensors were used but instead the drivers of the motors provided information regarding the forces in the mechanism.Risk M2: the anchor points were manufactured from plastic (3D printed) and covered with soft materials (sponges and cotton), inductive sensors have been mounted in order to constrain the mechanism within the allowable limits.Risk M5: when the Emergency button is pressed the robotic system allows easily removal of the patient from the device (the mechanism remains in the position).Risks E1, E4 and E5: properly 220 V encapsulated power supply was used, the power supply for the motors is 80 V and properly encapsulated cables have been used to supply the motors. The large case box containing the control system was used as grounding.Risk E2 and E3: the room where the robotic system was installed did not permit the use of external sensor systems during the patient experimental runs, but the research team achieved two external sensor systems one of them using cameras and the other one using goniometers.Risk T1: was reduced by use of plastic materials in the patient-robot contact areas.Risk V1 and V2: proper instruction manual was provided.Risk ERH1—no harnesses were necessary, instead some pillows were used to adjust the patient position during the procedure.Risk M1, M3, and M4: inductive proximity sensors have been mounted in order to constrain the mechanism within the allowable limits, no torque sensors were used but instead the drivers of the motors provided information regarding the forces in the mechanism.Risk M2: the anchor points were manufactured from plastic (3D printed) and covered with soft materials (sponges and cotton), inductive sensors have been mounted in order to constrain the mechanism within the allowable limits.Risk M5: when the Emergency button is pressed the robotic system allows easily removal of the patient from the device (the mechanism remains in the position).Risks E1, E4 and E5: properly 220 V encapsulated power supply was used, the power supply for the motors is 80 V and properly encapsulated cables have been used to supply the motors. The large case box containing the control system was used as grounding.Risk E2 and E3: the room where the robotic system was installed did not permit the use of external sensor systems during the patient experimental runs, but the research team achieved two external sensor systems one of them using cameras and the other one using goniometers.Risk T1: was reduced by use of plastic materials in the patient-robot contact areas.Risk V1 and V2: proper instruction manual was provided.Risk ERH1—no harnesses were necessary, instead some pillows were used to adjust the patient position during the procedure.Finally, in order to validate the functionality of the robotic structure the ethical approval for performing test using humans was requested and obtained. Experimental data was collected from 18 patients each of them hospitalized for a time period of 7 days. The clinical profile of each patient was provided as a table.The main objective of the in hospital tests was to validate the functionality of the robotic system for elbow and wrist rehabilitation, system previously tested on healthy human subjects in the laboratory environment. Most important aspect of using the robotic system in the hospital environment was the feedback obtained from the patients and the clinicians.The patients were given a consent form prior to the robotic-assisted therapy, so all had to accept voluntarily this type of treatment, but the feedback was better than initially expected. Everyone showed a large interest and excitement in using a device never used before in the hospital. On the medical side, the overall time of each session was around 25 min which seemed to have greater benefits to the patient (as the exercises were performed with lower speeds) as compared to classical sessions which are spread on a period of only 5–8 min. On the motivational side, we noticed that patients exchanged opinions encouraging each other which seemed to help the entire group. The market of rehabilitation devices for upper limb rehabilitation is in continuous development and expansion, but there are not many devices undergoing clinical trials. Basteris [43] provides a list of 38 upper limb rehabilitation devices that were used in clinical trials using real patients, the number of the patients included in the clinical trials varying between 5 and 526. Colombo [44] provides data regarding clinical trials performed on a number of 12 patients accumulating 20 h of training with the robot, the clinical trials were performed on chronic patients. Abdullah [45] reports clinical trials performed on a number of eight patients accumulating 21.4 h of training with the robot but this time the patients were in acute phase. Stein [46] reports clinical trials involving 12 chronic phase patients achieving 18 h of training with the robot. Chang [47] report clinical trials on 20 chronic patients reveling also 18 h of training with the robot. The experimental tests performed with ParReEx robotic system included 18 acute and chronic patients and accumulated 1890 min (31.5 h) of training with the elbow rehabilitation module and 1260 min (21 h) of training with the wrist rehabilitation module. Prior to the clinical trials, the accuracy of the robotic system was tested using runs with healthy human subjects. The experimental setup necessary for determining the accuracy of the system was composed of the robotic system and an external monitoring system provided by Biometrics [48] a sensor system composed from a series of goniometers able to read the angular amplitudes during the rehabilitation process. A series of dry runs (without the human subject) were performed in order to obtain the mechanism accuracy without external forces. The obtained accuracy was obtained between 0.5° and 1° for elbow rehabilitation module and 0.5° and 1.5° for the wrist rehabilitation module. The positioning error increased when attaching the human subject in the rehabilitation device until 3°, due to the elasticity of some of the components parts of the device but this error was considered as a characteristic to improve in the future and has been taken into consideration during the clinical trials. During the clinical trials, the functionality of the robotic system was proven due to no major issues encountered, even though there were cases when the patient suffered muscular spasm due to Parkinson altering normal running conditions, but in most of the cases, the drivers of the motors interrupted the motion due to excessive torque detected. The advantage of performing rehabilitation using a modular robotic device that does not uses the patient’s arm as support is that in cases of malfunction or power failure, the mechanism stops and is kept in place by the gearboxes and the patient’s arm can be easily removed from the device. The robotic system was previously tested using healthy human subjects to intentionally apply excessive forces in the mechanism in order to block it and to test the possibility of removing the arm from the structure. Some irregularities were detected when the elbow joint was at 90° and to overcome this situation, easy removal of the arm anchor point (anchor point 1 in Figure 9a) was provided.The overall behavior of the robotic system during the clinical trials was generally accepted by the clinicians, patients, and operator. The improvement in the patient neurological disorder is yet to be analyzed by the clinicians in order to validate the robotic system from medical point of view as a viable rehabilitation solution for post-stroke patients (or other neurological diseases that cause limb impairment), but the authors consider that the experimental model of ParReEx passed the functionality test. During the clinical trials, some aspects that may be improved were recorded. Future work will be focused on improving the control system, the GUI, and improving the quality of some components of the experimental model of ParReEx, such as material used in anchor points, the Velcro bands should be covered with a softer material, the wheelchair works fine for the chronic phase patients, but in the case of acute patients some extra fixtures should be considered. As stated before, a big preconized problem was the acceptance of the robotic system by the patients, but this proved to be a minor inconvenience and only in the first phase of trials, the research team considers that the general acceptance of the robotic system is due to the fact that the number of sensors has been reduced to minimum and no sensor was mounted on the patient during the procedure in order to reduce the preparation times (actually, patients didn’t need any preparation times) and to create a comfortable environment for the patient.Conceptualization, P.T., D.P., B.G., and G.C.; Methodology, P.T., B.G., and C.V.; Mathematical Validation, P.T. and N.P.; Resources, P.T. K.M., Z.M. and C.V.; Data Curation, C.V. and Z.M.; Writing—Original Draft Preparation, T.P.; Writing—Review and Editing, P.T., C.V., D.P., B.G., and G.C.; Supervision, D.P., B.G., and G.C.; Project Administration, D.P. and G.C. All authors read and approved the final manuscript.The paper presents results from the research activities of project ID 37_215, MySMIS code 103415 “Innovative approaches regarding the rehabilitation and assistive robotics for healthy ageing” cofinanced by the European Regional Development Fund through the Competitiveness Operational Program 014-2020, Priority Axis 1, Action 1.1.4, through the financing contract 20/01.09.2016, between the Technical University of Cluj-Napoca and ANCSI as Intermediary Organism in the name and for the Ministry of European Funds.The authors declare no conflict of interest.How often would you consider the occurrence probability of the following hazards? (Please provide a numeric value in the interval provided).How severe would you consider the consequences of the following hazards? (Please provide a numeric value in the interval provided.).Kinematic scheme of the ParReEx robotic structure ((a) kinematic scheme of the elbow rehabilitation module, (b) kinematic scheme of the wrist rehabilitation module) [37].Risk management flow chart regarding the risk assessment process according to ISO12100:2010.Motion ranges for the elbow rehabilitation module ((a) flexion/extension, (b) pronation/supination) and for wrist rehabilitation device ((c) flexion/extension/adduction/abduction).The structure of Mamdani FIS (Fuzzy Inference System) provided by MATLAB.The membership function of the Fuzzy Inference System (FIS) ((a) Input membership function for Probability of the hazard, (b) Input membership function for the severity of the hazard, (c) Output membership function for the Risk Level of the hazard).Risk level surface with respect to Probability and Severity membership functions.Risk level for each hazard computed using data from Table 7.The experimental model of ParReEx robotic system.The experimental model of ParReEx robotic system ((a) elbow rehabilitation module, (b) wrist rehabilitation module).The Graphical User Interface (GUI) of ParReEx designed using Automation Studio [36].Snapshots from the experimental tests using ParReEx ((a) ParReEx-elbow flexion/extension, (b) ParReEx-elbow pronation/supination, (c) ParReEx-wrist adduction/abduction, (d) ParReEx-wrist flexion /extension).Robot-Human interaction levels [39].Motion ranges for the elbow and wrist rehabilitation.°—degrees.The probability categories for the hazard occurrence.The severity categories for the hazard occurrence.FIS rules defined according to the risk assessment matrix.Mean values for Severity and Probability [16].Data regarding the patients involved in the functional validation of the robotic system.Mean, minimum, and maximum angular amplitudes recorded during the clinical trials.

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+The South African mining industry is one of the largest producers of platinum (Pt) in the world. Workers in this industry are exposed to significant amounts of dust, and this dust consists of particles sizes that can penetrate deep inside the respiratory region. A cross-sectional study was conducted to evaluate dust exposure risk at two Pt mine waste rock crusher plants (Facility A and B) in Limpopo, South Africa. Workers’ demographic and occupational information was collected through a structured questionnaire, a walk-through observation on facilities’ processes, and static dust sampling for the collection of inhalable and respirable dust particles using the National Institute for Occupational Safety and Health (NIOH) 7602 and the Methods for Determination of Hazardous Substance (MDHS) 14/4 as guidelines. Only 79% of Pt mine workers, used their respiratory protective equipment (RPE), sixty-five percent were exposed to work shifts exceeding the recommended eight hours and 8.8% had been employed for more than ten years. The mean time-weighted average (TWA) dust concentrations between Facility A and B showed a significant difference (p < 0.026). The Pt mine’s inhalable concentrations (range 0.03–2.2 mg/m3) were higher than the respirable concentrations (range 0.02–0.7 mg/m3), however were all below the respective international and local occupational exposure limits (OELs). The Pt mine’s respirable crystalline silica (SiO2) quartz levels were all found below the detectable limit (<0.01 mg/m3). The Pt miners had increased health risks due to accumulated low levels of dust exposure and lack of usage of RPE. It is recommended that an improved dust control program be put in place which includes, but is not limited to, stockpile enclosures, tire stops with water sprays, and education on the importance of RPE usage.In response to the demand the mining industry has expanded by 3.7% in 2017, with platinum (Pt) comprising 26% of mineral exports [1]. The Pt industry became the major contributor to the South African (SA) mining sector after the decline of gold production [2]. According to the Chamber of Mines of SA (2018), the Pt industry generated 8 billion rand in sales in 2017 [3]. Furthermore, the SA Chamber of Mines indicated that more than 175,000 people were employed in the sector in 2018 [3].Haque et al. (2014) defined Pt mining as the process of extracting the mineral from the Earth’s crust and the removal of the economic ore [4]. Pt mining categories include underground and opencast operations, with the latter presenting exposure of mine workers to dust particles [4]. Pt mining activities generate residues such as waste rock, which are materials that are not valuable economically. The mine waste generated during the course of Pt mining activities is regulated by the SA Mining Residues Regulations [5] published under National Environment Management Amendment Waste Act (NEMWA, Act 26) of 2014 [6]. The innovative methods currently used in managing Pt mine waste include crusher plants that turn underground mine waste rock into various construction products. The crusher plants perform opencast mining activities which are part of the growing small-scale mining sector [7]. However, these facilities’ mining processes involve crushing and screening of the mine waste rock, which inevitably produces dust particles. These dust particles are classified into coarse and fine particles and exposure occurs when these particles are inhaled during mining operations and pose various respiratory risks depending on the size of the particle [8].There are major health challenges in the mining industry such as pulmonary tuberculosis (PTB). The other challenge is silicosis as most mineral rocks have crystalline free silica (also known as quartz). Surface Pt mining is a leading cause of exposure to excessive dust particles that are harmful to health and are associated with various causes of silicosis and pneumoconiosis [9], with the respirable crystalline silica (SiO2) quartz generated during stone crushing linked to increased occurrences of pulmonary tuberculosis and chronic lung disease. Ndaba’s (2017) study also found the existence of silicosis in Pt miners in 544 out of 6662 certified cases in 2004 [10]. This is attributed to exposure to dust particles, specifically silica dust, which is considered a risk factor for the development of PTB [3]. The Department of Mineral Resources reported 2838 TB cases in 2012, with the Pt mining sector contributing the second-highest number (895) [3]. Phillips et al. (2014) mentioned that workers with the disease or the potential to develop disease from silica dust exposure might be working in the Pt mining sector due to cross-recruitment, which often occurs from gold to Pt mines [11]. To explore the potential Pt risk in mine workers who had never had worked in another mining sector aside from Pt mining, Nelson and Murray (2013) conducted a descriptive case-series study in SA from 1975 to 2009, which showed an autopsy crude prevalence of 0.06% and 0.30% potential silicosis in the case of Pt miners [12].Occupational health and safety (OHS) should remain the number one priority in mining. A research study showed that mining operations were still the leading cause of exposures harmful to health and associated with various causes of occupational accidents and diseases [7]. For example, in SA, Pt mining contributed 25 fatalities and injuries between January and October 2017, with similar statistics for 2016 within the same period [13]. Pt mineworkers’ exposure variations are due to the different mining activities, particle amounts, and the particle size’s ability to penetrate a specified respiratory region.Pt mining in SA is under-researched, which hinders the publication of information in line with dust particles exposure and associated health effects. A study by Nelson and Murray (2013) indicated that most Pt miners’ medical records were not complete; thus, not enough evidence was available to make conclusive findings with regard to dust production and exposure to dust particles during Pt mining [12]. Another challenge was that the migration of miners from one mine to another makes it difficult to find conclusive evidence of dust particle exposure in Pt mining. To minimize the chance of including miners that had been exposed to dust particles outside of the Pt mining sector, Nelson and Murray (2013) conducted a descriptive case series study in SA from 1975 to 2009 [12]. This study included miners who had never worked in any mining sector other than the Pt industry. The results showed evidence of health effects as a result of exposure to dust particles, for example, silicosis in some of the miners. The probable health effects that may occur due to exposure to any amount of dust are determined by the chemical properties of such dust particles.There are several standards to manage production of dust particles and exposure during Pt mining, but there is little evidence that these standards are sufficiently addressing the problem of dust production and the exposure of mine workers to this dust. Therefore, when protective occupational exposure limits (OELs) are set for mining, a large number of workers will be protected.This study was conducted at two pre-selected mine waste rock crusher plants (named Facility A and B) situated in the Limpopo Province of SA, which is known as the Bushveld Igneous Complex. The methodologies used in this study were selected to confirm the dust particle exposure of Pt mine workers in the crusher plants by characterizing dust into size, mass concentration, and hazardous pollutants through exposure monitoring conducted over the standard eight-hour day using a time-weighted average (TWA), with a comparison made with what is acceptable in terms of local and international occupational health standards. The first stage was to identify and evaluate the workplaces (i.e., mine waste rock crusher plants) through a walk-through survey and followed by a self-administered questionnaire. The third stage was conducted using area (static or fixed) dust sampling in the chosen mine waste rock crusher plants.This is a descriptive cross-sectional study using quantitative measures to gather information on occupational dust particle exposure. A stratified sampling method was used with an inclusion criterion predefined by homogeneous exposure group or based on work-task, and the Pt mine workers’ were divided into occupations to establish the difference in exposure. Office workers and security guards were excluded as they were not involved in the production or handling of the waste rock. The target sample size to complete the questionnaire included the existing 100 permanent Pt mine workers. However, out of the 100 total Pt mine workers in the inclusion criteria of both facilities, only 34 respondents (34%) were reached for this study due to low production and facilities process schedules.This methodological approach involved identifying of the characteristics of a population at one point in time and presenting the situation in the facilities as it is, in order to confirm or investigate the Pt mine workers’ dust exposure phenomenon through dust sampling.In this study, data collection was divided into three stages, which included a walkthrough observation, a close ended self-administered questionnaire, and static dust sampling.The first stage was to identify and evaluate the workplaces’ (waste rock crusher plants) handling processes by means of a walk-through survey along with the site manager of each facility. This process was necessary to provide the basis for the quantitative dust assessment.The second stage was conducted using a previously validated questionnaire (Table S1) from the British Medical Research Council. It was then developed with specificity to this study by the authors and the University of Johannesburg’s statistician using close-ended questions to acquire the Pt mine workers’ biographic and occupational details. The questionnaires were distributed to the 34 respondents on site during lunch breaks, and all participants accepted the English version and did not request copies translated to any other languages which, prior to the study, were planned to be made available upon request.The third stage entailed using area static dust sampling in the crusher plants conducted in October 2018, following the guidelines of the international standards of National Institute for Occupational Safety and Health (NIOH) 7602 [14] and the Methods for Determination of Hazardous Substance 14/4 (MDHS) [15] over eight working hours.The nine work stations, (five in Facility A and four in Facility B) were based on the facilities’ scheduled process flow on the date of sampling, and contributed to the collected 18 dust samples (nine inhalable and nine respirable). The workstations were identified during the walk-through survey in the two waste rock crusher plants (Facility A and Facility B). In Facility A, five workstations were identified, namely: the feeder, screener, twister crusher, excavator, and front end loader (FEL). Facility B had four workstations, namely: the feeder station, screening station, multi-stages crusher station, and excavator.The dust collection instruments used were multi-fraction Institute of Occupational Medicine (IOM) samplers, which concurrently collected inhalable and respirable dust particles and meets the international standards. The larger inhalable (<100 μm) dust particles were drawn through a filter paper, which was placed between a cassette and a support grid to trap dust particles. The smaller respirable (<10 μm) dust particles were sampled by a cyclone using the polyvinyl chloride filter enclosed in a cassette to separate smaller particles from larger ones.The flow of the calibration method using a rota-meter was 2.2 Liters per minute for the multi-fraction IOM samplers [14,15], and was checked before and after every sampling to avoid errors in reporting. The sample filter cassettes were covered and stored in cases when transported to the sampling location. To ensure that the outcome of samples were traceable, information such as facility identity, sampling area, the sample identification, and pump start time and end time were recorded on an exposure assessment field sheet adopted from the Department of Minerals and Energy of SA [16]. The collected dust sample for this study is communicated as mass of dust per cubic meter (mg/m3) of air.A quantitative analysis method was followed for this research for analysis of the numerical data. Statistical analysis was conducted using Statistical Package for the Social Sciences (SPSS) version 25 [17] for all questionnaire data. Descriptive analyses such as frequencies, percentages, and means were used to summarize data as appropriate. Gravimetric analysis according to MDHS 14/4 was used for the dust samples collected. The analysis of this study further used Fourier Transform Infrared Spectroscopy with potassium bromide for analysis of silica particles [15]. The gravimetric method used the TWA dust concentration over an eight-hour work shift, which was calculated using the following formula [18]:
+		Sample volume (m3): Flow rate (1/min) × time (min)Correction filter mass (mg): Post filter mass − Pre filter massSample mass (mg): Post weight sample mass − Pre weight sample massCorrected sample (mg): Corrected sample mass − Correction factor.Concentration (mg/m3): Mass ÷ Volume (mg/m3).TWA dust concentration: Concentration × Total sample time (min)The independent sample t-test was conducted with SPSS to determine if the TWA dust concentrations from the two facilities were significantly different, with a significance level considered at α = 0.05.The highest number of Pt mine workers was found at the cleaning activity group, at 20.6%, followed by the crushing activity group, at 17.6% (Table 1). Literature has proven that that all workers are at risk of developing health effects due to dust exposure; however, the risk level could differ per worker due to demographic characteristics such as age and gender [13,19]. The Safety in Mines Research Advisory Committee (2001) handbook explains the relationship between gender, age, personal protective equipment (PPE) usage, length of service, and the cumulative dust exposure as being closely related [19]. The results showed 85.3% males as compared to 14.7% females (Table 1).Referring to this study’s demographic information, which could affect the significance of exposure, the Pt mine workers’ average age, was found to be 37 years (range 23 to 68 years). The largest age group was 30–39 years (41.2%) with similar numbers of workers in each facility. The smallest age group was found to be the 50–59 year olds (2.9%) which existed only in Facility B. The oldest individuals (above 60 years of age) were from Facility A alone (Table 1). Out of the 34 Pt mine workers, most of the workers (38.2%) had working experience of one to four years, while few Pt mine workers (5.9%) had worked ten years or more (Table 1).There was inconsistency or inadequacy in PPE usage, with 3% of participants revealing that they were not being provided with PPE  and, for those provided, 21% admitted to not using their PPE at all times (Table 2). It was found that the 66.7% of the Pt mine workers who admitted to not wearing PPE at all times were working for longer than the recommended eight-hour work shift (Table 2). Analysis of occupational characteristics such as duration of exposure by work shift (Table 2) and length of service (Table 1) showed that 65% of the participants from both facilities were working for longer than the recommended eight-hour shifts, and 8.8% of participants had performed ten or more years of service.In SA, the OELs are published by the Department of Mineral Resources, under the Mining, Health, and Safety (MHS) Act of 1996 (Table 3) [20]. The Pt mine dust respirable particulates were compared to the SA’s MHS Act OELs, which are the only relevant OELs that exist for this particular hazard (Pt mine dust respirable particulates). Table 3 reflects high respirable TWA dust concentrations in Facility B when compared to Facility A. The highest levels of TWA respirable dusts for both facilities were found at the feeder stations (Facility A at 0.6 mg/m3 and Facility B at 0.7 mg/m3). The lowest levels of respirable TWA concentrations for each respective facility were found at FEL A (0.022 mg/m3) and excavator B (at 0.03 mg/m3).Pt mine dust respirable particulates from the facilities were further characterized into Sio2 quartz. This characterization was important as probable health effects may occur due to exposure as determined by the chemical properties of such dust particles. The international OELs used for comparison purposes were from United States Department of Labor under the Occupational Safety and Health Administration (OSHA) as shown in Table 4 and Table 5 [21]. Other countries such as Australia, Belgium, Denmark, France, Greece, Sweden, and the United Kingdom have OELs for respirable SiO2 quartz set at the same amount as SA (0.1 mg/m3), and Italy and Finland have OELs similar to that of the OSHA OEL, which is set at 0.05 mg/m3. The respirable SiO2 quartz concentrations were found to be below the respective local and international OELs of 0.1 mg/m3 and 0.05 mg/m3 at all work stations (Table 4).There are no set OELs for Pt mine dust’s inhalable particulates in both local and international organizations; hence, the OELs for inhalable particles not otherwise classified (PNOCs were used for this study. The highest inhalable TWA concentration in both Facilities were found at the Feeder stations (Facility A at 0.7 mg/m3 and Facility B at 2.2 mg/m3) and the lowest concentrations for each facility were found to be at the excavators (Facility A at 0.1 mg/m3 and Facility B at 0.03 mg/m3).Feeder B showed the total highest inhalable TWA concentration (2.2 mg/m3) as demonstrated in Table 5. Table 5 further shows that the lowest TWA concentrations of inhalable dust were at excavator B (0.03 mg/m3).Combining the results of Table 3 and Table 5, the mean time-weighted average (TWA) dust concentration for both inhalable and respirable dust particles was found to be 0.4 mg/m3 (range from a minimum of 0.2 mg/m3 to a maximum of 2.2 mg/mg3), with a standard deviation of 0.5 mg/mg3. The mean inhalable particle TWA concentration was found at 0.6 mg/m3 and respirable particle TWA concentration at 0.2 mg/m3 over an eight-hour work shift. There was a significant difference between the facilities (p < 0.026), showing Facility B to have levels 0.2 times higher than Facility A.Although exposure assessment is an integral component of environmental epidemiology and OHS, risk profiling according to concentrations is vital in dust exposure assessments. Based on the TWA concentration values obtained during the exposure assessment phase, the SA-OELs, and the health effects of respirable and inhalable dust; the workstations were then risk-profiled (Table 6) according to the guidelines in Table S2. Pt mine respirable dust (<5% SiO2) is associated with pneumoconiosis, Pt mine respirable dust (>5% SiO2) is linked with silicosis, and inhalable mine dust is related to physical irritation. The Pt mine respirable SiO2 quartz concentrations were not subjected to a risk rating as all samples were found below the detectable limits. Out of 18 dust concentration results, the risk-analysis matrix obtained showed a very high risk level at two stations, namely, feeder A and crusher B for respirable dust, with the workstations of lowest risk being the screen, excavator, and FEL. However, the inhalable dust particulates values in all stations were found to be below 30 as per the classifications, showing that the risk of exposure to inhalable dust particles is acceptable or tolerable when compared to respirable dust particles.The risk of dust exposure from the mining industry depends on the specific activity, duration of exposure, characteristics of dust, and workers demographic characteristics. There was exposure to dust particles at all mine waste rock crusher facilities. These solid particles are classified as chemical hazards which Pt mine workers come into to contact with, through inhalation over an eight-hour work shift.The majority of the Pt mine workers were found to be cleaners (20.6%), with four females and three males, which is not surprising as traditionally cleaning services have been dominated by women [22]. The crushing activity group was the second largest group, representing 17.6%.Particle size and mass concentration are crucial factors for the characterization of dust. Most mining activities have greater numbers of coarse particles as compared to fine particles. The inhalable dust fraction TWA mean concentration (0.6 mg/m3) was higher than that of the respirable fractions (0.2 mg/m3). This study’s comparison of inhalable and respirable dust results is supported by a scientific research conducted on  three open cast mines in India which also showed that inhalable particulate matter (PM) of 10 micrometers or more in diameter (>PM10) concentrations were between 22% and 36% higher than respirable fractions (<PM10) [23].The OELs that apply to Pt mining have been set locally and internationally as a mitigating method with respect to dust particles in the workplace. However, there are still struggles with compliance. The findings from this study present TWA concentration levels that are much lower than the local and international inhalable and respirable dust exposure limits set between 15 mg/m3 and 3 mg/m3, which have been deemed unsafe by various studies. A relevant exposure response study conducted among gold workers in SA showed that the OEL set at 0.1 mg/m3 was not sufficient to protect the workers [22]. A scientific report on respirable dust concentration showed results of 0.018 mg/m3 to 0.035 mg/m3, with values lower than SA’s OEL of 0.1 mg/m3; however, the same results were higher than the American Conference of Governmental Industrial Hygienists’ limit of 0.025 mg/m3 [13,23]. Furthermore, the MHS report stated that 95% of exposure measurement should be below the Pt dust respirable particulate level of 1.5 mg/m3 [24].OHS studies have also proven increased risk of exposure due to demographic and occupational characteristics such as age, gender, PPE usage, and duration of exposure by work shift and job service length [8,10,18]. The British Medical Association (2016) stated that there is “an accelerated decline in forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) with age and that the respiratory system reaches maximal function between the ages of 20 to 27 years, thereafter lung function decreases progressively” [19]. Furthermore, the SA mining industry reported a mean age of 54 years for 19,531 pneumoconiosis cases between 2004 and 2012 [10]. Ndaba (2017) further reported specific Pt mining results that showed certified silicosis cases, with most of the affected miners being in the age group of 40 to 59 years and the age group with the lowest rate aged 30 to 39 years, with no cases found in individuals aged less than 30 years [10].Comparing the findings of the present study to those of the British Medical Association (2016) and Ndaba (2017) [10,19], the Pt mine workers aged between 20 and 39 years (65%; n = 17 males and n = 5 females) wee a non-vulnerable group, whereas those aged between 40 and 68 years (35%; n = 12 males and no females) were a vulnerable group, with a more than 20 milliliter FEV1 annual decrease. The lower incidence amongst younger workers as compared to older workers is mostly due to the scientific statistics of cumulative exposures or latency periods, which indicates increased health risks among elderly workers [13]. The 36.8-year average indicates non-vulnerable Pt mine workers in terms of health risks, which is supported by a SA mining industry occupational disease study [10]. However, the presence of different age-groups in the facilities selected for this study indicates variety of the risk to health. The occupational characteristics such as duration of exposure by work shift and job service length showed that 65% of the participants from both facilities worked for more than the recommended eight hours, and that 8.8% of participants had performed 10 or more years of service which is an indication of an increased health risk.The SA mining industry has recorded occupational lung diseases such as silicosis, occupational TB and workers pneumoconiosis as the key challenges of health. In terms of Pt mine health effects, a recent SA mining industry study pertaining to lung diseases amongst male and female miners found that 93% of the diagnoses of pneumoconiosis were in men and only 5% in females [10], which could pose potential threat to males more than females.The results showed further lack of legislation compliance with regard to simple dust mitigation measures such as usage of PPE for an entire shift, even where management made such equipment available to workers. The lack of RPE usage and longer duration of exposure has been associated with the risk of pneumoconiosis; a scientific study found the risk of pneumoconiosis to be higher in people that had been exposed to mineral dusts for long periods of time and in cases of the inconsistent use of RPE [25]. The relationship between PPE usage and duration of work further shows that employees wearing PPE continuously for longer than a normal shift tend to find it uncomfortable. The respirator, based on laboratory-measured performance data, shows that the filtering face piece 2 (FFP) used in both facilities deals with moderate levels of fine dust and can be used during sanding, cement, drilling, and cutting. However, it must be noted that the use of FFP 3 is recommended in the mining sector, where silica could be present.The risk-profiling matrix (Table S2) showed two high-risk profiled workstations with respirable dust (Table 4); this risk-rating evaluation indicated that measures should be implemented to reduce the potential harm at the highest-risk stations.In terms of long-term exposure, the facilities’ waste rock particles may also go through chemical reactions during overtime storage, which may generate additional products that could be toxic human health [26].It has been clearly shown in the literature for the past 40 years that static samplers (also called area samplers) are not adequate when used without personal sampling for characterizing worker exposure. However, they are excellent for determining the continuing adequacy of the process and process controls. That means that in order to protect the Pt mine workers there should be methods used for monitoring their health status.The general conclusion that can be drawn from the present study is that Pt mine workers had increased health risks with accumulated low levels of dust exposure due to lack of RPE usage. No conclusions could be drawn on personal health due to the study not focusing on personal dust exposure or medical examinations but rather on determining risks related to processes or workstation exposure at each crusher plant.Personal samples are generally higher in concentration when taken in the same area. The potential limitation in the study is that personal sampling results are universally considered more appropriate for the protection of workers. Therefore, further studies could extend the exposure monitoring by including medical surveillance and personal dust sampling in order to further establish the impacts on health of the concentrations found at Facility A and Facility B.Pt mine workers in these crusher plants need to be protected from exposure through the use of advanced technologies that are more efficient. Some measures could include the use of bag-houses or collector dumps which can be placed at the machines stone deposition end, which discharge the products close to the ground and reduce discarding of dust. Other measures include the use of wet methods for stockpiles or road-dust haulage; tire stops with water sprays which reduce rollback underneath vehicles and suppress dust at the stockpile deposit areas; use of enclosed hopper dumps; limiting vehicle movements (such as clients’ collection trucks, or delivery trucks) during processing hours and installing speed limits that can reduce dust production; limiting the magnitude and duration of exposure through task rotations or rest periods for workers; provision of appropriate RPE approved by national and/or international standards [8]; and encouraging usage of RPE amongst all persons working in this sector. The most important measure is the training of employees to support a health and safety culture that promotes zero tolerance to dust exposure.The following are available online at https://www.mdpi.com/1660-4601/17/2/655/s1, Table S1: Questionnaire. Table S2: Risk rating determination band table [18].Conceptualization, M.M.S., M.C., and V.N.; methodology, M.M.S., and V.N.; software, M.M.S.; validation, M.M.S., M.C., and V.N.; formal analysis, M.M.S.; investigation, M.M.S.; resources, M.M.S.; data curation, M.M.S. and V.N.; writing—original draft preparation, M.M.S.; writing—review and editing, M.M.S., M.C., and V.N.; supervision, M.M.S. and V.N.; project administration, M.M.S. All authors have read and agreed to the published version of the manuscript.This research received no external funding.Appreciation is given to the scholarship (Global Excellence Stature) afforded to the first author (M.M.S.) for completion of her Masters of Public Health degree at the University of Johannesburg.The authors declare no conflict of interest.Distribution of platinum mine workers’ demographic and occupational characteristics by facility.%: percentages; n = number of samples; N/A = not applicable.Cross tabulation of personal protective equipment (PPE usage (with % within usage) and work shift (with % within each work shift) for each facility.Workstations’ Pt mine dust respirable particulate in comparison with the TWA OELs.BL: Below limit. MHS: Mining, Health, and Safety; TWA: time-weighted average; OEL: occupational exposure limit.Respirable crystalline silica (SiO2) quartz OELs of workstations in comparison to other established OELs.<0.01: Below detectable limit; PEL: Permissible exposure limit.TWA concentration OEL comparisons of Workstations’ inhalable particles not otherwise classified.BL: Below Limit; PEL: Permissible exposure limit.Workstation’s risk rating and classification (Table S2).Red code: Very high risk level; Mustard code: High risk level; Yellow code: Moderate risk level; Green code: Low risk level; Lime code: tolerable risk level.