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Background: Evidence on the associations of fine particulate matter (PM 2.5 ) constituents and glucose metabolism is limited in resource-limited areas. This study aimed to explore the associations of PM 2.5 constituents with glucose metabolism in rural areas, and to further specify the most responsible constituent., Methods: A total of 38,442 adults were recruited from the Henan Rural Cohort Study during 2015-2017. Three-year averaged concentrations of PM 2.5 mass and its constituents (black carbon (BC), ammonium (NH 4 + ), nitrate (NO 3 - ), organic matter (OM), inorganic sulfate (SO 4 2- ), soil particles (SOIL) and sea salt (SS)) were estimated by a hybrid satellite-based model. Generalized linear model was applied to explore the associations of PM 2.5 mass and its constituents with type 2 diabetes mellitus (T2DM), fasting blood glucose (FBG), insulin, and HOMA-β. Proportion and residual analyses were employed to specify the most responsible constituent., Results: The adjusted odds ratio (OR) for T2DM associated with 1 μg/m 3 increase was 1.02 for PM 2.5 mass, 1.28 for BC, 1.15 for NH 4 + , 1.08 for NO 3 - , 1.10 for OM, 1.11 for SO 4 2- , and 1.12 for SOIL. Significant associations of PM 2.5 mass and its constituents with elevated FBG, decreased insulin and HOMA-β were also observed. Proportion and residual analyses indicated that BC was the most responsible constituent, in which 1 percentage increment in the proportion of BC in PM 2.5 corresponded with 1.51-fold risk for T2DM, 0.17 mmol/L increase in FBG, 2.18 μU/mL decrease in insulin, and 38.26 % decrease in HOMA-β; and 1 μg/m 3 increment in the PM 2.5 -adjusted BC corresponded with 1.59-fold risk for T2DM, 0.53 mmol/L increase in FBG, 4.79 μU/mL decrease in insulin, and 91.32 % decrease in HOMA-β., Conclusions: PM 2.5 mass and its constituents (BC, NH 4 + , NO 3 - , OM, SO 4 2- , SOIL) were associated with T2DM, increased FBG, decreased insulin and HOMA-β, of which BC was most responsible for these associations., Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Associations of combined different cooking fuel types and cooking duration with sleep quality were scarcely reported. This study aimed to explore the associations of exposure to household air pollution (HAP) from different cooking fuel types and cooking duration with sleep quality and examine the effect modification of kitchen ventilation on these associations., Methods: A total of 28,135 eligible participants were obtained from the Henan rural cohort study. Sleep quality was assessed by the Pittsburgh sleep quality index (PSQI), and participants with a PSQI score > 5 were identified as having poor sleep quality. A questionnaire was used to collect the cooking fuel types, cooking frequency, cooking duration, and kitchen ventilation. The average daily cooking duration was calculated as the cooking frequency per week multiplied by the cooking duration for each meal divided by 7., Results: Both domestic fuel use and cooking duration were positively related to poor sleep quality. The solid fuel users with a cooking duration ≥1.5 h/day had a higher prevalence of poor sleep quality (OR: 1.390, 95% CI: 1.233, 1.567), relative to those who never cooked. Notably, the estimated OR and 95% CI for poor sleep quality of clean fuel users with a cooking duration <1.5 h/day plus mechanical or natural ventilation versus those who never cooked was 1.05 (0.933, 1.187) or 1.306 (1.163, 1.466) and these associations were modified by kitchen ventilation., Conclusion: Positive associations of combined different cooking fuel types and cooking duration with the prevalence of poor sleep quality were attenuated by kitchen ventilation, implying that installing mechanical ventilation may be an effective measure to improve sleep quality in low- and middle-income countries. These results need to be confirmed by future studies, which measure HAP more accurately using personal monitoring devices or behavior diaries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Socioeconomic status (SES) was a crucial influencing factor of household air pollution (HAP). However, few studies have explored the potential effect modification of SES on the associations of HAP with type 2 diabetes mellitus (T2DM) and glucose homeostasis., Methods: A total of 20900 participants were obtained from the Henan Rural Cohort. HAP reflected by cooking fuel type and cooking duration was assessed via questionnaire. SES was evaluated by two dimensions: educational level and average monthly income. Associations of cooking fuel type, cooking duration with T2DM and glucose homeostasis indices (insulin, fasting plasma glucose (FPG), and HOMA-β) were assessed by the generalized linear model. Analyses were also conducted in different SES groups to explore the potential effect modification., Results: Significant negative association of cooking fuel type and cooking duration with T2DM, FPG, and HOMA-β was not observed. However, cooking with solid fuel and long-duration cooking were associated with decreased insulin level in women, and the adjusted coefficients were - 0.35 (95% confidence interval (95% CI): - 0.53, - 0.17) and - 0.36 (95% CI: -0.50, -0.21), respectively. Results from stratified analyses showed that these associations were more prominent in women with low average monthly income, with corresponding coefficient of - 0.57 (95% CI: -0.77, -0.37) for cooking with solid fuel and - 0.34 (95% CI: -0.52, -0.16) for long-duration cooking. Among women with low average monthly income, the largest decreased insulin level was observed in those who cooked with solid fuel, long-duration and poor kitchen ventilation, while the negative association of cooking fuel type and cooking duration with insulin level was slightly alleviated in the good kitchen ventilation group., Conclusions: Low average monthly income aggravated the negative association of HAP and insulin level among rural women, while improving kitchen ventilation may be a practical intervention., Trail Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Aims: To evaluate the associations between residential greenness and glucocorticoid levels and whether air pollutants and sex modify the relationship between greenness and glucocorticoid level in Chinese rural adults., Methods: We collected cross-sectional survey data from 6055 participants from the Henan Rural cohort. The three-year average residential greenness for participants was assessed using normalized difference vegetation index (NDVI) values from a satellite platform. Liquid chromatography-tandem mass spectrometry was employed to quantify the concentrations of glucocorticoids, which were measured by morning blood draw after at least 8 hr of fasting. A random forest model was employed to obtain the average concentrations of PM 1 , PM 2.5 , and PM 10 . A general linear regression model was performed to estimate the associations of NDVI 500-m values with cortisol, 11-deoxycortisol, and cortisone. Furthermore, interaction plots were used to present the interaction effects of particulate matter, sex, and green space on glucocorticoid levels., Results: After adjusting for multiple variables, an elevated average NDVI 500-m value in the total population was associated with a decrease in cortisol levels (β = -0.063, 95 % confidence interval (CI): - 0.118, - 0.008), and 11-deoxycortisol levels (β = -0.118, 95 % CI: -0.190, -0.047), as well as an increase in cortisone levels (β = 0.130, 95 % CI: 0.079, 0.181). By adding the interaction terms of air pollutants and residential greenness into the regression model, interaction effects between air pollutants and residential greenness were found (cortisol, PM 2.5 : P interaction=:0.018; PM 10 : P interaction=0.016; 11-deoxycortisol, all pollutants: P interaction< 0.001), suggesting that the protective effect of residential greenness on serum glucocorticoids disappeared accompanying with increased concentrations of particulate matter. Moreover, trends towards modification in the association between green space and glucocorticoid levels were also evident by sex, but these did not reach statistical significance (for all glucocorticoids: P interaction> 0.05)., Conclusion: Long-term exposure to green space was negatively correlated with cortisol and 11-deoxycortisol levels, and positively correlated with cortisone levels. There may be sex differences in these associations. Moreover, the protective effect of residential greenness on serum glucocorticoids was altered by high levels of particulate matter., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Long-term exposure to ambient ozone (O 3 ) and residential greenness independently relate to altered hormones levels in urban settings and developed countries. However, independent and their joint associations with progestogen and androgen were sparsely studied in rural regions., Materials and Methods: A total of 6211 individuals were recruited in this study. Random forest model was applied to predict the daily average concentrations of O 3 using the satellites data. Residential greenness was reflected by the normalized difference vegetation index (NDVI). Liquid chromatography-tandem mass spectrometry was used to measure serum progestogen and androgen concentrations. Gender and menopausal status modified associations of long-term exposure to O 3 and residential greenness with hormones levels were analyzed by generalized linear models., Results: Long-term exposure to O 3 was negatively related to 17-hydroxyprogesterone, testosterone, and androstenedione in both men and women (premenopausal and postmenopausal); the estimated β and 95% CI of ln-progesterone in response to per 10 μg/m 3 increment in O 3 concentration was -0.560 (-0.965, -0.155) in postmenopausal women. Association of long-term exposure to O 3 with serum androgen levels in premenopausal and postmenopausal women were alleviated by residing in places with higher greenness. Additionally, a prominent effect of long-term exposure to O 3 related to decreased serum progestogen and androgen levels was found in participants with middle- or high-level of physical activity or lower education level., Conclusions: The results suggested that long-term exposure to high levels of O 3 related to decreased serum androgen levels was attenuated by living in high greenness places in women regardless of menopause status. Future studies are needed to confirm the positive health effects of residential greenness on the potential detrimental effects due to exposure to O 3 ., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Famine exposure or air pollution is linked to type 2 diabetes mellitus (T2DM). However, their combined effects on T2DM remain largely unknown. A total of 11,640 individuals were obtained from the Henan Rural Cohort Study. According to their birthdate, participants were divided into three famine exposure subgroups: fetal exposed, childhood exposed, and unexposed groups. The air pollutants (particles with aerodynamics diameters ≤ 1.0 µm (PM 1 ), ≤ 2.5 µm, and ≤ 10 µm, and nitrogen dioxide) concentrations of each individual were estimated by a spatiotemporal model. Participants were divided into low or high air pollution exposure groups taking the 1st quartile value of air pollutants as the cut-off point. Logistic regression model was used to analyze independent and joint associations between air pollution exposure, famine exposure, and T2DM. Positive associations of air pollution and famine exposure with T2DM were found. Participants who experienced fetal or childhood famine and also were exposed to high concentrations of any kind of the air pollutants had a much higher risk for T2DM than those with no famine and low air pollutants exposure (taking PM 1.0 for example, the odds ratio [OR]: 1.76, 95% confidence interval [CI]: 1.25, 2.47 for fetal famine, and OR: 1.64, 95%CI: 1.13, 2.40 for childhood famine). After stratified analysis, similar results were observed in women. The results indicated that both famine exposure in early life and air pollution exposure in adulthood are related to increased risk for prevalent T2DM, and they have combined effects on T2DM., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Obesity and ambient air pollution are independent risk factors of type 2 diabetes mellitus (T2DM), however, the evidence regarding their joint associations on T2DM was sparsely studied in low-middle income countries., Methods: A total of 38,841 participants were selected from Henan Rural Cohort study which was carried out during 2015-2017. Obesity was identified by body mass index (BMI), WC (waist circumstance), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BFP (body fat percent), and VFI (visceral fat index). Three-year averaged-concentrations of NO 2 , PM 1 , PM 2.5 , and PM 10 were assessed by using the method of spatiotemporal model incorporated into the satellites data. The independent associations of obesity indicators and exposure to air pollutants on fasting blood glucose (FBG) and T2DM were assessed by generalized linear and logistic regression model, respectively, and their interaction associations on T2DM were quantified by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S)., Results: Positive associations of six obesity measures and four air pollutants with FBG levels and prevalent T2DM were observed. Obese participants measured by BMI plus high exposure to NO 2 , PM 1 , PM 2.5 and PM 10 were related to a 2.96-fold (2.66-3.29), 2.87-fold (2.58-3.20), 2.98-fold (2.67-3.32) and 3.01-fold (2.70-3.35) increased risk for prevalent T2DM, respectively; similarity of joint associations of the other obesity measures and air pollutants on T2DM were observed. The additive associations of different obesity measures and air pollutants with prevalent T2DM were further found., Conclusions: The synergistic associations of obesity and air pollutants on FBG levels and prevalent T2DM were observed, indicating that obese participants were at high risk for prevalent T2DM in highly polluted rural regions., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Long-term exposure to air pollutants and residential greenness related to advanced fibrosis have been sparsely studied in low- and middle-income countries. A total of 29883 participants were selected from a cross-sectional survey of the Henan Rural Cohort. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 μm (PM 1 ), ≤ 2.5 μm (PM 2.5 ), ≤ 10 μm (PM 10 ) and nitrogen dioxide (NO 2 )) for participants were predicted by using a spatiotemporal model. Residential greenness of each participant was indicated by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI). Independent and joint associations of air pollutants and residential greenness indices with prevalent advanced fibrosis reflected by fibrosis-4 score (FIB4), aspartate-to-platelet-ratio index (APRI) and ALT/AST ratio were analyzed by generalized linear mixed models and their interactive effect on prevalent advanced fibrosis were visualized by using the interplot method. Long-term exposure to PM 1 , PM 2.5 , PM 10 and NO 2 were positively related to FIB4 or APRI as well as prevalent intermediate-high advanced fibrosis; EVI was negatively related to FIB4 or APRI as well as prevalent intermediate-high advanced fibrosis. Negative associations of residential greenness indices (EVI or NDVI) with prevalent advanced fibrosis were decreased as increased air pollutants (PM 1 , PM 2.5 , PM 10 or NO 2 ) (P < 0.05 for all). This study indicated that residential greenness may partially attenuate negative effect of long-term exposure to air pollutants related to increased prevalent intermediate-high advanced fibrosis, implying that residential greenness may be an effective strategy to reduce the burden of prevalent hepatic fibrosis and its related disease in association with exposure high levels of air pollutants. The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375 )., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Although exposure to ambient air pollution (AAP) increases the risk for arteriosclerotic cardiovascular disease (ASCVD), evidence on the association of solid fuel use with ASCVD and its association modified by ambient air pollution remains limited., Methods: A total of 16,779 adults were derived from the Henan Rural Cohort Study. Concentrations of ambient air pollutants (PM 1 , PM 2.5 , PM 10 , and NO 2 ) were estimated by a spatiotemporal model based on satellites data. Solid fuel use was assessed by a self-reported questionnaire. The associations of solid fuel use with high 10-year ASCVD risk and the modified association by exposure to air pollutants were explored using logistic regression models., Results: There were positive associations of AAP exposure with high 10-year ASCVD risk among individuals with self-cooking. The joint associations between high AAP exposures and solid fuel use with high 10-year ASCVD risk were found. Compared to clean fuel user with low PM 2.5 exposure, the odds ratios (ORs) and 95% confidence intervals (CIs) of high 10-year ASCVD risk was 1.25 (1.09, 1.42) for solid fuel user with low PM 2.5 exposure, 1.93 (1.75, 2.12) for clean fuel user with high PM 2.5 exposure, and 3.08 (2.67, 3.54) for solid fuel user with high PM 2.5 exposure, respectively. Their additive effect on high 10-year ASCVD risk was observed (relative excess risk due to interaction (RERI): 0.90 (95 %CI: 0.50, 1.30), attributable proportion due to interaction (AP): 0.29 (95 %CI: 0.19, 0.40), and synergy index (SI): 1.77 (95 %CI: 1.38, 2.26))., Conclusion: This study showed a synergistic effect of AAP and household air pollution reflected by solid fuel use on high 10-year ASCVD risk, suggesting that reducing solid cooking fuels and controlling air pollution may have a joint effect on public health improvement., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Low socio-economic status (SES) and exposure to single-air pollutant relate to increased prevalent atherosclerotic cardiovascular diseases (ASCVD), however, interactive effect between SES and exposure to single- or multiple-air pollutants on high 10-year ASCVD risk remains unclear., Methods: A total of 31,162 individuals were derived from the Henan Rural Cohort Study. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ) or ≤10 μm (PM 10 ), nitrogen dioxide (NO 2 )) were assessed using a spatiotemporal model based on satellites data. Independent and joint associations of SES, single- and multiple- air pollutants with high 10-year ASCVD risk were evaluated using logistic regression models, quantile g-computation and structural equation models. The interactive effects of SES and exposure to single- or multiple air pollutants on high 10-year ASCVD risk were visualized by using Interaction plots., Results: Exposure to single air pollutant (PM 1 , PM 2.5 , PM 10 or NO 2 ) related to increased high 10-year ASCVD risk among individuals with low education level or personal average monthly income, compared to the ones with high education level or personal average monthly income. Furthermore, similar results of exposure to mixture of air pollutants with high 10-year ASCVD risk were observed. Positive interactive effects between low SES and exposure to high single air pollutant or the mixture of air pollutants on high 10-year ASCVD risk were observed., Conclusion: Positive association of low SES with high 10-year ASCVD risk was amplified by exposure to high levels of single air pollutant or a mixture of air pollutants, implying that individuals with low SES may more susceptible to air pollution-related adverse health effect., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Population-based studies on the associations of long-term exposure to particulate matter (PM) with androgen and progesterone are still scant. Residential greenness is benefits health by promoting physical activity, reducing air pollution, and improving mental health, but it remains unclear whether it is related to androgen and progesterone levels among humans., Aims: This study aimed to explore the individual and interactive effects of PM and residential greenness on serum testosterone and progesterone levels among rural Chinese adults., Methods: A total of 6017 subjects were recruited from the baseline of the Henan Rural Cohort Study in 2016. Serum testosterone and progesterone were measured with liquid chromatography-tandem mass spectrometry. Particulate matters (PM) (PM 1 , PM 2.5 , and PM 10 ) were assessed by machine learning algorithms. Residential greenness was assessed using the normalized difference vegetation index (NDVI) within 500-m, 1000-m, and 3000-m buffers around participants' residences. The effects of air pollutants and residential greenness and their interaction on serum testosterone and progesterone levels were assessed using linear mixed-effects models with township as a random intercept., Results: After adjusting for potential confounding factors, a 1 μg/m 3 increase in PM 2.5 or PM 10 was associated with a 0.037 or 0.030 ng/ml increase in serum testosterone, respectively, in females and with a 0.111 or 0.182 ng/ml decrease in serum progesterone, respectively, in males. A 1 μg/m 3 increase in PM 1 , PM 2.5 or PM 10 was associated with a 0.222, 0.306, or 0.295 ng/ml decrease in serum progesterone, respectively, among females. Moreover, a 0.1-unit increase in NDVI was associated with a 0.310 ng/ml increase in serum testosterone and a 0.170 ng/ml increased in serum progesterone in males, as well as with a 0.143 ng/ml increase in serum progesterone in females. Interaction effects of PM and residential greenness on serum testosterone and progesterone levels were observed, indicating that the effects of residential greenness on serum testosterone and progesterone were modified by high levels of PM. In addition, physical activity significantly mediated 2.92% of the estimated association between greenness and testosterone levels., Conclusions: Our study suggested that long-term exposure to PM was positively associated with serum testosterone in males but negatively associated with progesterone levels in both genderssin. In addition, positive associations of residential greenness with serum testosterone and progesterone levels were observed, but they were modified by high levels of PM. Furthermore, the estimated effects of residential greenness on testosterone levels were partly mediated by physical activity., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Although long-term exposure to higher air pollutants and lower residing greenness related to disorders of glucose homeostasis have been reported, their interaction effects on glucose homeostasis in developing countries remained unclear., Methods: A total of 35, 482 participants were obtained from the Henan Rural Cohort (n = 39, 259). Exposure to air pollutants (PM 1 , PM 2.5 , PM 10 and NO 2 ) were predicted by using a spatiotemporal model-based on satellites data. Residing greenness was reflected by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) which were derived from satellites data. Independent associations of single or mixture of air pollutant or residing greenness with glucose homeostasis markers were analyzed by quantile regression models and quantile g (qg)-computation method, respectively. Furthermore, interaction effects of residing greenness and air pollution on glucose homeostasis markers were analyzed by generalized additive models., Results: Positive associations of single or mixture of air pollutants (PM 1 , PM 2.5 , PM 10 or NO 2 ) with fasting plasma glucose (FPG) were observed, while negative associations of single or mixture of air pollutants with insulin or HOMA-β were observed. Residing greenness was negatively associated with FPG but positively related to insulin or HOMA-β. Quantile regression revealed the heterogeneity were observed in the associations the residing greenness or air pollutants with glucose homeostasis markers (insulin or HOMA-β) across deciles of the glucose homeostasis markers distributions. Furthermore, joint associations of single air pollutant and residing greenness on glucose homeostasis markers were found., Conclusions: The results indicated that exposure to air pollution had negative effect on glucose homeostasis markers and these effects may be modified by living in higher green space. These findings suggest that increased residing greenness and air pollution control may have joint effect on decreased the risk of diabetes., Clinical Trial Registration: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Although short-term exposure to particulate matter (PM) was associated with increased glucocorticoids (GCs) levels, available evidence on associations of long-term exposure to PM and GCs levels is still scant. Previous studies has showed that meat intake is associated with sex hormones levels, but it is unknown whether meat intake is associated with GCs levels. Furthermore, the role of meat intake in the associations between PM and GCs levels remains unclear., Aims: The aims of this study were to explore the associations of long-term exposure to PM and GCs levels among Chinese rural adults, and the role of meat intake in these associations., Materials and Methods: A total of 6223 subjects were recruited from the Henan Rural Cohort Study. Serum GCs levels were measured with liquid chromatography-tandem mass spectrometry. The concentrations of PM (PM 1 and PM 2.5 ) for each subject were assessed with machine learning algorithms. The food frequency questionnaire (FFQ) was used to obtain each participant' information on meat intake. The effects of PM and meat intake on GCs levels were assessed using generalized linear models. In addition, modification analyses were performed to identify the role of meat intake played in the associations of PM with serum GCs levels., Results: Per 1 μg/m 3 increment in PM 1 or PM 2.5 concentration was associated with a 0.364 ng/ml (95% confidence interval (CI): 0.234, 0.494) or 0.227 ng/ml (95%CI: 0.110, 0.343) increase in serum cortisone, respectively. In addition, the moderation effects of total meat intake and red meat intake on the associations of long-term exposure to PM 1 or PM 2.5 with serum cortisone were observed (P < 0.05), indicating that individuals who had high levels of PM 1 or PM 2.5 and meat intake were more susceptible to have a higher state of serum cortisone., Conclusions: Our findings suggested that long-term exposure to PM 1 or PM 2.5 was associated with serum cortisone. Moreover, meat intake was found to be a significant moderator in the association of PM 1 or PM 2.5 with serum cortisone levels., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Exposure to single air pollutant and physical activity (PA) were associated with an altered mitochondrial DNA copy number (mtDNA-CN). However, studies on the interactive effects of single or a mixture of air pollutants and PA on mtDNA-CN were limited., Methods: A total of 2707 Chinese adults were obtained from the Henan Rural Cohort Study. Spatiotemporal models were used to estimate particulate matter (PMs) (PM with an aerodynamic diameter ≤ 1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ) or ≤ 10 μm (PM 10 )) and nitrogen dioxide (NO 2 ) concentrations. Relative mtDNA-CN was measured by quantitative real-time polymerase chain reaction. Linear regression and quantile g-computation models were applied to examine associations of single or mixture of air pollutants with relative mtDNA-CN. The interactive effects of single or mixture of air pollutants and PA on relative mtDNA-CN were visualized by using Interaction plots., Results: Each 1 μg/m 3 increment in PM 1 , PM 2.5 , PM 10 or NO 2 was associated with a 5.11% (95% confidence interval: 3.71%, 6.53%), 6.77% (4.81%, 8.76%), 3.05% (2.22%, 3.87%) or 4.99% (3.45%, 6.55%) increase in relative mtDNA-CN. Each one-quartile increment in mixture of the four air pollutants was related to a 0.053 (0.032, 0.075) increase in relative mtDNA-CN. Negative interaction effects of single or mixture of air pollutants and PA on relative mtDNA-CN were observed., Conclusions: The positive associations of single or mixture of air pollutants with relative mtDNA-CN were counteracted by PA at certain levels, implying that PA may be a costless and effective approach to decrease negative effects of air pollution on mtDNA-CN., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Although obesity reflected by BMI can enhance the association of air pollution with increase blood pressures (BP) and prevalent hypertension in susceptible population, there remains lack evidence on interactive effects of different obesity indices and air pollutants on BP and prevalent hypertension in rural adults. 39,259 individuals were recruited from the Henan Rural Cohort. Concentrations of air pollutants (PM 1 , PM 2.5 , PM 10 and NO 2 ) were evaluated by a spatio-temporal model based on satellites data. Independent associations of air pollutants and obesity reflected by BMI, WC, WHR, WHtR, BFP and VFI on BP indicators (SBP, DBP, MAP and PP) and prevalent hypertension were analyzed by linear regression and logistic regression models, respectively. Furthermore, their additive effects were quantified by RERI, AP and S. Six obesity indices enhanced the associations of four air pollutants and BP indicators. Individuals with high PM 1 concentrations plus obesity classified by BMI, WC, WHR, WHtR, BFP and VFI had a 4.18-fold (95% CI: 3.86, 4.53), 3.58-fold (95% CI: 3.34, 3.84), 3.53-fold (95% CI: 3.28, 3.81), 4.02-fold (95% CI: 3.72, 4.35), 3.89-fold (95% CI: 3.59, 4.23), 3.87-fold (95% CI: 3.62, 4.14) increase in prevalent hypertension, respectively, compared to non-obese individuals with low PM 1 concentrations; similar results were observed for combined effect of PM 2.5 , PM 10 or NO 2 and obesity indices on prevalent hypertension. The significant values of RERI, AP and S indicated additive effects of air pollutants and obesity indices on hypertension. Obesity amplified the effects of exposure to high levels of air pollutants on increased BP values and prevalent hypertension, implying that obese individuals may be susceptible to elevate BP and prevalent hypertension in relation to air pollution exposure. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375)., Competing Interests: Conflicts of interest All authors had declared no conflict of interest., (Copyright © 2021 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.)

Evidence from numerous epidemiological studies for the relationship between mental disorder and sleep quality was inconclusive and few studies assessed the modification effect of exposure to ambient air PM 1 (particulate matter with an aerodynamic diameter ≤ 1.0 µm) on this association. In this study, 27,572 participants aged 18-79 years from The Henan Rural Cohort study were included in the final analyses. The Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder-2 (GAD-2) scales were used to estimate the frequency of depression and anxiety symptoms of all participants, respectively. The Pittsburgh Sleep Quality Index (PSQI) scale was used to assess night sleep quality and PSQI global score (GSC) ≥ 6 was classified as poor sleep quality. The three-year average exposure concentration of PM 1 before the baseline survey was determined as long-term exposure concentration of ambient PM 1 . Logistic regression model was conducted to estimate the independent or joint effect of depression/anxiety symptoms and ambient PM 1 exposure on poor sleep quality. In the adjusted models, the odds ratios (ORs) and 95% confidence intervals (95% CIs) of poor sleep quality associated with depression and anxiety symptoms were 3.75 (3.37, 4.17) and 3.42 (3.06, 3.81), respectively, and that associated with long-term exposure to PM 1 was 1.06 (1.03, 1.09). An interaction effect was observed between anxiety symptoms score and PM 1 concentration on poor sleep quality. With the increment of PM 1 concentration, the association was strengthened between depression/anxiety symptoms and poor sleep quality. Besides, compared with the reference group, the ORs (95% CIs) of poor sleep quality in those with comorbidity of depression and anxiety symptoms were 4.98 (3.95, 6.29), 5.23 (3.98, 6.87), 5.76 (4.42, 7.49), and 5.58 (3.83, 8.14), respectively, from the first to the fourth quartile level of the PM 1 concentration. These findings suggested that long-term exposure to PM 1 strengthened the association of depression/anxiety symptoms with poor sleep quality in rural China., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Exposure to air pollutants (nitrogen dioxide (NO 2 ) and particulate matters (PMs)) or physical inactivity is linked to telomere length (TL) shortening. However, there is a lack of research on combined effects of either NO 2 or PMs and physical activity (PA) on TL. This study aimed to explore the joint associations of air pollutants (NO 2 or PMs) and PA with relative TL in rural Chinese adults., Methods: This study was conducted among 2704 participants aged 18-79 years in rural China. Concentrations of NO 2 and PMs (PM with an aerodynamics diameter ≤ 1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ) or ≤10 μm (PM 10 )) were estimated using random forest models incorporated with satellites data, meteorological data, and land use information. Relative TL of each participant was measured by a quantitative real-time polymerase chain reaction. Linear regression models were applied to examine the independent associations between PA, NO 2 or PMs and relative TL. Interaction plots were used to depict the altered associations between NO 2 , PM 1 , PM 2.5 , or PM 10 and relative TL along with increasing PA levels., Results: Each 1 μg/m 3 increment in NO 2 , PM 1 , PM 2.5 , or PM 10 was associated with a 0.038 (95% confidence intervals (CI): -0.044, -0.033), 0.036 (95% CI: -0.041, -0.031), 0.052 (95% CI: -0.059, -0.045), or 0.022 (95% CI: -0.025, -0.019) decrease in relative TL among all participants; similar findings were observed among normal glucose tolerance or impaired fasting glucose (IFG) participants as well as type 2 diabetes mellitus (T2DM) patients. PA at certain levels counteracted the association of air pollutants (NO 2 , PM 1 , PM 2.5 , and PM 10 ) with relative TL among IFG participants or T2DM patients., Conclusions: Long-term exposure to NO 2 and PMs was associated with relative TL shortening and these effects may be counteracted by PA at certain levels in IFG participants or T2DM patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objectives: Socio-economic status (SES) and air pollutants are thought to play an important role in human obesity. The evidence of interactive effect between SES and long-term exposure to mixture of air pollutants on obesity is limited, thus, this study is aimed to investigate their interactive effects on obesity among a rural Chinese population., Methods: A total of 38,817 individuals were selected from the Henan Rural Cohort Study. Structural equation modeling (SEM) was applied to construct the latent variables of low SES (educational level, marital status, family yearly income, and number of family members), air pollution (particulate matter with aerodynamics diameters ≤ 1.0 μm, ≤ 2.5 μm or ≤ 10 μm, and nitrogen dioxide) and obesity (body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, body fat percentage and visceral fat index). Generalized linear regression models were used to assess associations between the constructed latent variables. Interaction plots were applied to describe interactive effect of air pollution and low SES on obesity and biological interaction indicators (the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (S)) were also calculated., Results: Increased latent variables of low SES and mixture of air pollution were associated with a higher odds of latent variable of obesity (odds ratios (OR) (95% confidence interval (CI)) were 1.055 (1.049, 1.060) and 1.050 (1.045, 1.055)). The association of the mixture of air pollutants on obesity was aggravated by increased values of the latent variable of low SES (P < 0.001). Furthermore, the values of RERI, AP and S were 0.073 (0.051, 0.094), 0.057 (0.040, 0.073) and 1.340 (1.214, 1.479), respectively, indicating an additive effect of estimated latent variable of low SES and air pollution on obesity., Conclusions: These findings suggested that low SES aggravated the negative effect of mixture of air pollutants on obesity, implying that individuals with low SES may be more susceptible to exposure to high levels of mixture of air pollutants related to increased risk of prevalent obesity., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Epidemiological studies on the association of residential greenness with sleep quality are limited in China., Objective: This study aims to investigate the association of long-term exposure to residential greenness with sleep quality in rural China., Methods: In our study, 27,654 rural residents were selected from 4 counties of Henan Province by a multi-stage stratified cluster sampling method. Participants' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), two satellite-derived vegetation indexes, were used to assess the level of residential greenness. Long-term greenness exposure was defined as the averages of NDVI and EVI during the three years prior to the baseline survey. The relationship between sleep quality and greenness was assessed using the mixed-effect linear regression models., Results: Among 27,654 rural residents, the mean age was 55.89 years (standard deviation, SD = 12.22) and 60.18% of them were female. In the crude model, the PSQI score decreased with per interquartile range (IQR) increase in EVI and NDVI [ΔPSQI score (95% confidence interval, 95%CI): -0.073 (-0.115, -0.030) and -0.047 (-0.089, -0.002)]. After controlling potential confounders, ΔPSQI scores and 95%CIs were -0.055 (-0.095, -0.012) and -0.090 (-0.151, -0.025) associated with per IQR increment in EVI and NDVI. The results of stratified analyses showed the effect of residential greenness on sleep was stronger among males and individuals with higher household income and educational attainment than females and those with lower household income and educational attainment. Moreover, the modification effect of air pollution was observed in the greenness-sleep association., Conclusions: Our study indicated that higher residential greenness was significantly associated with better sleep quality in Chinese rural population, which highlights the significant effect of green space on human health., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Long-term exposure to air pollutants relate to increase risk of cardiovascular diseases that may be partially attributable to platelet dysfunction. Physical activity (PA) may attenuate inflammation to modulate platelet function. Thus, this study aimed to evaluate associations of air pollutants and PA with platelet traits of cardiovascular risk., Methods: A total of 31,282 participants were obtained from the Henan Rural Cohort (n = 39,259). The concentrations of particulate matter (PM) (PM with an aerodynamic diameter ≤1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ), or ≤10 μm (PM 10 )) and nitrogen dioxide (NO 2 ) were evaluated by using a spatiotemporal model incorporated into satellites data. Independent and combined effects of air pollutants and PA on platelet traits were analyzed by linear mixed models., Results: Positive associations of PM 1 , PM 2.5 , PM 10 and NO 2 with platelet indices (mean platelet volume (MPV), platelet distribution width (PDW) and platelet large cell ratio (P-LCR), the MPV to platelet counts (PLT) ratio (MPVP)) were observed, whereas negative associations of PM 10 and NO 2 with PLT or plateletcrit (PCT) were observed; negative interaction effects of PM 2.5 PM 10 and NO 2 and PA on MPV, PDW or P-LCR were found; negative interaction effects of PM 1 , PM 2.5 and PM 10 and PA on PCT were observed., Conclusions: Long-term exposure to air pollutants were related to increase platelet size and these associations were attenuated by increased PA, implying that PA is a costless and affordable method to decrease adverse effects on platelet traits in relation to air pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Aim: We aimed to assess if snoring and ambient air pollutants were jointly associated with prevalent hypertension in a cross-sectional study., Methods: A total of 28440 participants aged 18-79 years were obtained from the Henan Rural Cohort. Snoring evaluated using Pittsburgh sleep quality index (PSQI) scale was classified into 'Never', '<3 times/week' and '≥3 times/week' groups. Concentrations of air pollutants (PM 1 , PM 2.5 , PM 10 , and NO 2 ) were evaluated by a satellite-based spatiotemporal model. The independent and joint associations between snoring and air pollutants on prevalence of hypertension were analyzed by logistic regression models., Results: The mean age of all participants was 56.0 ± 12.2 years. The frequencies and prevalence of participants with hypertension were 3666 (32.39%) in men and 5576(32.57%) in women, respectively. The odds ratio (OR) and 95% confidence interval (CI) of participants with snoring frequency of <3 times/week, ≥3 times/week was 1.10(1.02-1.20), and 1.15(1.08-1.23) for hypertension, compared to those without snoring. Participants with a snoring (≥3 times/week) and higher exposure concentrations of PM 1 , PM 2.5 , PM 10 , and NO 2 had 2.58-fold(95% CI: 2.30-2.90), 3.03-fold(95% CI: 2.69-3.41), 2.89-fold(95% CI: 2.57-3.25) and 2.75-fold(95% CI: 2.44-3.10) for hypertension, compared to those without snoring and low concentrations of air pollutants. Additionally, participants with high PM 1 and ≥3 times/week snoring (OR: 1.32, 95% CI: 1.18-1.48) was at a higher likelihood for prevalent hypertension, compared to those without snoring and with high PM 1 ., Conclusions: Snoring and high ambient air pollutants might be important predictors of hypertension, and higher concentration of PM 1 might aggravate the association between snoring and hypertension., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: The association between ambient air pollutants exposure and suicidal ideation (SI) has rarely been explored, especially in Chinese population. Therefore, we aimed to investigate the long-term effects of ambient air pollutants on SI among a Chinese rural population., Method: We recruited 29997 participants from the Henan Rural Cohort study in 2016-2017. SI was evaluated by using the ninth item of the Patient Health Questionnaire-9 (PHQ-9) in the baseline survey. We adopted a satellite-based spatiotemporal model to estimate participants' exposure to particulate matters (PMs) (PM with an aerodynamic diameter ≤1 μm (PM 1 ), ≤2.5 μm (PM 2.5 ) or ≤10 μm (PM 10 ), respectively) and nitrogen dioxide (NO 2 ), and then calculated the 3-year average concentrations of the four pollutants. We used logistic regression models to explore the association between long-term exposure to ambient air pollutants and SI. In addition, we conducted several stratified analyses to examine effect modification of selected factors., Results: The odds ratios (95% confidence intervals [CI]) of SI in response to each 1 μg/m 3 increase in PM 1 , PM 2.5 , PM 10 and NO 2 concentrations were 1.08 (1.01, 1.15), 1.10 (1.02, 1.19), 1.05 (1.01, 1.09) and 1.12 (1.04, 1.21), respectively. Individuals exposed to PM 1 , PM 2.5 , PM 10 or NO 2 concentrations in the fourth quartile had a 1.36-fold (95%CI: 1.08, 1.72), 1.69-fold (95%CI: 1.05, 2.72), 1.49-fold (95%CI: 1.09, 2.05) or 1.71-fold (95%CI: 1.15, 2.85) risks of SI, compared to the ones with corresponding air pollutants in the first quartile. Besides, the risks of SI increased with the quartiles of air pollutants (PM 1 : P trend  = 0.002, PM 2.5 : P trend  = 0.003, PM 10 : P trend  = 0.010, NO 2 : P trend  = 0.010). Stratified analyses suggested that males, highly educated participants, ever-drinkers and people aged range 36-64 years were more vulnerable to the adverse effects of air pollutants., Conclusions: This study provided evidence for the long-term effects of ambient PMs and NO 2 on SI in rural Chinese adults, particularly for males, highly educated participants, ever-drinkers and people aged range 36-64 years., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Although long-term exposure to air pollution and physical inactivity are linked to increased risk for atherosclerotic cardiovascular diseases (ASCVD), however, the interactive effect of air pollution and physical activity (PA) on high 10-year ASCVD risk is largely unknown., Methods: A total of 31,162 individuals aged 35-74 years were derived from the Henan Rural Cohort Study, after individuals with personal histories of ASCVD or missing data on predictors of high 10-year ASCVD risk were excluded. Concentrations of air pollutants (nitrogen dioxide (NO 2 ), particulate matter with an aerodynamics diameters ≤ 1.0 µm (PM 1 ), ≤2.5 µm (PM 2.5 ) or ≤10 µm (PM 10 )) of individuals were estimated using a spatiotemporal model based on satellites data. The metabolic equivalent (MET) of PA of each individual was evaluated using the formula: duration (hour/time) × frequency/week × MET coefficient of each type of activity. Logistic regression models were used to analyze associations between air pollutants, PA and high 10-year ASCVD risk. Interaction plots were used to describe interactive effects of air pollutants and PA on high 10-year ASCVD risk., Results: Each 1 µg/m 3 increase in PM 1 , PM 2.5 , PM 10 and NO 2 were related to a 4.4% (odds ratio (OR): 1.044, 95% confidence interval (CI): 1.034, 1.056), 9.1% (OR: 1.091, 95% CI: 1.079, 1.104), 4.6% (OR: 1.046, 95% CI: 1.040, 1.051) or 6.4% (OR: 1.064, 95% CI: 1.055, 1.072) increase in high 10-year ASCVD risk (all p < 0.001), respectively; each one unit-increase in PA MET (hour/day) value was related to a 1.8% (OR: 0.982, 95% CI: 0.980, 0.985) decrease in high 10-year ASCVD risk. Negative interactive effects of PA and PM 1 , PM 2.5 , PM 10 and NO 2 on high 10-year ASCVD risk were observed (all p < 0.001)., Conclusion: Exposure to high levels of air pollutants were related to increase high 10-year ASCVD risk and these associations were attenuated by PA, implying that PA may be an effective method to the prevention of high 10-year ASCVD risk in highly polluted rural regions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Association between long-term exposure to ambient air pollution and obesity remains inconclusive, and the evidence from rural areas was limited. Thus, this study aimed to assess the association between ambient air pollution and obesity based on different anthropometric indices in Chinese rural adults, and further to compare the effect sizes of different air pollution types. A total of 38,824 participants (aged 18-79 years) were recruited from the Henan Rural Cohort Study. Logistic and multivariable linear regression model were used to examine the association between ambient air pollution exposure (including particulate matter with aerodynamic diameters ≤ 1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ), and ≤10 μm (PM 10 ), and nitrogen dioxide (NO 2 )) and obesity as well as obese anthropometric indices (including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI)). The potential effect modifications were also examined. Positive associations were found between long-term exposure to PM 1 , PM 2.5 , PM 10 and NO 2 and obesity regardless of how obesity was defined (false discovery rate (FDR) < 0.05). Moreover, BMI, WC, WHR, WHtR, BFP, and VFI displayed increased trends with PM 1 , PM 2.5 , PM 10 and NO 2 concentrations increasing (all FDR<0.05). PM 10 had the largest effects on obesity among the four types of air pollution. The elderly, women, individuals with low level of education and income, and those who had high fat diet were more vulnerable to the adverse effects of air pollution. In addition, the results of the sensitivity analysis showed that those associations between ambient air pollution and obesity remained robust. These findings suggest that long-term exposure to ambient air pollutant (particularly PM 10 ) may be positively associated with obesity in Chinese rural adults, especially among the elderly, women, individuals with low education and income, as well as unhealthy lifestyles., Competing Interests: Declaration of competing interest All authors declare no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: The associations of long-term exposure to air pollution with osteoporosis are rarely reported, especially in rural China. This study aimed to explore the association among rural Chinese population., Methods: A total of 8033 participants (18-79 years) derived from the Henan Rural Cohort Study (n = 39,259) were included in this cross-sectional study. Exposure to air pollutants was estimated using machine learning algorithms with satellite remote sensing, land use information, and meteorological data [including particulate matter with aerodynamic diameters ≤1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ), and ≤10 μm (PM 10 ), and nitrogen dioxide (NO 2 )]. The bone mineral density of each individual was measured by using ultrasonic bone density apparatus and osteoporosis was defined based on the T-score ≤ -2.5. Multiple logistic regression models were used to examine the association of air pollution and osteoporosis prevalence., Results: We observed that per 1 μg/m 3 increase in PM 1 , PM 2.5 , PM 10 and NO 2 were associated with a 14.9%, 14.6%, 7.3%, and 16.5% elevated risk of osteoporosis. Compared with individuals in the first quartile, individuals in the fourth quartile had higher odds ratio (OR) of osteoporosis (P-trend < 0.001), the ORs (95% confidence interval) were 2.08 (1.72, 2.50) for PM 1 , 2.28 (1.90, 2.74) for PM 2.5 , 1.93 (1.60, 2.32) for PM 10 , and 2.02 (1.68, 2.41) for NO 2 . It was estimated that 20.29%-24.36% of osteoporosis cases could be attributable to air pollution in the rural population from China., Conclusions: Long-term exposure to air pollutants were positively associated with high-risk of osteoporosis, indicated that improving air quality may be beneficial to improve rural residents health., Competing Interests: Declaration of competing interest All authors have read and approved this version of the article, and declared that they had no competing or financial interests to disclosure., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Long-term exposure to ambient air pollution and physical activity are linked to metabolic syndrome (MetS). However, the joint effect of physical activity and ambient air pollution on MetS remains largely unknown in rural Chinese adult population., Methods: In this study, 39 089 individuals were included from the Henan Rural Cohort study that recruited 39 259 individuals at the baseline. Participants' exposure to air pollutants (including particulate matter with an aerodynamic diameter ≤ 1.0 µm (PM 1 ), ≤2.5 µm (PM 2.5 ), or ≤ 10 µm (PM 10 ) and nitrogen dioxide (NO 2 )) were evaluated by using a spatiotemporal model based on satellites data. Individuals were defined as MetS according to the recommendation of the Joint Interim Societies. Physical activity-metabolic equivalent (MET) was calculated based on the formula of MET coefficient of activity × duration (hour per time) × frequency (times per week). Generalized linear models were used to analyze the individual air pollutant or physical activity and their interaction on MetS. Interaction effects of individual air pollutant and physical activity on MetS were assessed by using Interaction plots which exhibited the estimated effect of physical activity on MetS as a function of individual air pollutant., Results: The prevalence of MetS was 30.8%. The adjusted odd ratio of MetS with a per 5 µg/m 3 increase in PM 1 , PM 2.5 , PM 10 , NO 2 or a 10 MET (hour/day) of physical activity increment was 1.251(1.199, 1.306), 1.424(1.360, 1.491), 1.228(1.203, 1.254), 1.408(1.363, 1.455) or 0.814(0.796, 0.833). The protective effect of physical activity on MetS was decreased with accompanying air pollutant concentrations increased., Conclusions: The results indicated that long-term exposure to ambient air pollutants related to increased risk of MetS and physical activity attenuated the effects of ambient air pollutants on increased risk for MetS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background and Purpose: Limited research focused on the association between household air pollution (HAP) and health-related quality of life (HRQoL). This study aimed to investigate the association of HAP with HRQoL and the effect modification of physical activity.Method: A total of 16,761 eligible participants were derived from the Henan Rural Cohort Study. Based on structured questionnaires, HAP was assessed by fuel type, cooking duration and kitchen ventilation; HRQoL was measured with utility index and VAS score from the European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L); physical activity was assessed by the International Physical Activity Questionnaire. Generalized linear models and tobit regression models were utilized to explore the relationship of HAP with HRQoL. Further sensitivity analyses were conducted using structural equation models.Results: Compared with those who cooked with clean fuels, short-duration, or good kitchen ventilation, participants who cooked with solid fuels, long-duration, and poor ventilation had lower utility index and VAS score (All P < 0.001). The decrease in utility index for solid fuel users vs. clean fuel users were 0.06 [95%confidence interval (CI) 003, 0.08], 0.03 (95%CI 0.01, 0.04) and 0.02 (95%CI 0.01, 0.04) in low, moderate and high physical activity group, respectively, which decreased with physical activity levels (Pfor interaction < 0.05). Similar results were observed in associations of kitchen ventilation with utility index and VAS score.Conclusion: HAP negatively associated with HRQoL in rural population, and potential intervention aimed at maintaining adequate physical activity.Trail Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375 . [ABSTRACT FROM AUTHOR]

There is little research on how long-term exposure to independent and multiple air pollutants changes cardiometabolic risk in adults. In addition, previous studies focused on only the effect of one or two lifestyles on cardiometabolic risk. The evidence on the interactive effects of the lifestyle score and exposure to independent and mixtures of air pollutants on cardiometabolic risk is lacking. A total of 33,638 rural residents were included in the cross-sectional study. The three-year average concentrations of air pollutants for participants were predicted by using a satellite-based prediction. The air pollution score was created to assess the combined exposure of four air pollutants (PM1, PM2.5, PM10, and NO2). A gender−age-specific cardiometabolic risk score was calculated. Multivariable-adjusted linear regression and quantile g-computation were used to investigate the associations between air pollutants and cardiometabolic risk. Interaction plots were applied to describe the interactive effects of air pollution and the healthy lifestyle score on cardiometabolic risk. Per interquartile range (IQR) unit increases in PM1, PM2.5, PM10, or NO2 were associated with 0.162 (95% CI: 0.091, 0.233), 0.473 (95% CI: 0.388, 0.559), 0.718 (95% CI: 0.627, 0.810), and 0.795 (95% CI: 0.691, 0.898) unit increases in cardiometabolic risk score (all p < 0.05), respectively. A 0.854 (95% CI: 0.768, 0.940) unit increase in cardiometabolic risk was associated with each IQR increase in air pollution score. Furthermore, the strengths of associations of PM1, PM2.5, PM10, NO2, and the air pollution score on cardiometabolic risk score were attenuated with the healthy lifestyle score increase. In addition, there was no statistical significance after the lifestyle score equal to four scores for the effect of PM1 on the cardiometabolic risk score. In conclusions, individual or joint air pollutants were associated with an increased cardiometabolic risk. Improving the healthy lifestyle may be an effective method to improve cardiometabolic health in highly polluted rural regions. [ABSTRACT FROM AUTHOR]

Although solid fuel use for cooking is linked to an increased risk for depression, there is limited evidence on the effects of cooking duration and kitchen ventilation on these associations in rural areas. Among 29 903 participants from the Henan Rural Cohort, the independent and combined associations of cooking fuel type, cooking duration, and kitchen ventilation with depressive and anxiety symptoms were examined by logistic regression models and restricted cubic spline. The adjusted odds ratios (aORs) and 95% confidence intervals (CIs) of solid fuel use for depressive and anxiety symptoms were 1.237 (1.041, 1.469) and 1.384 (1.153, 1.662), respectively. Increased cooking duration was associated with an increased prevalence of depressive symptoms (aOR: 1.098, 95% CI: 1.033, 1.166) and anxiety symptoms (aOR: 1.074, 95% CI: 1.009, 1.144). Solid fuel use and long‐duration cooking associated with increased prevalence of depressive and anxiety symptoms were only observed in individuals without kitchen ventilation. Kitchen ventilation may attenuate the positive associations of solid fuel use and long‐duration cooking with the prevalence of depressive and anxiety symptoms, which suggested popularizing clean fuel and promoting kitchen ventilation may be effective strategies to improve mental health related to household air pollution sourced from solid fuel use and long‐duration cooking. [ABSTRACT FROM AUTHOR]

Excessive daytime sleepiness is associated with many adverse consequences, including cardiovascular diseases and mortality. Although exposure to air pollution has been suggested in connection with excessive daytime sleepiness, evidence in China is scarce. The study aimed to explore the association between long-term exposure to air pollution and excessive daytime sleepiness in rural China. A lot of 27935 participants (60% females) from the Henan Rural Cohort Study were included in this analysis. A satellite-based spatiotemporal model estimated a 3-year average air pollution exposure to NO 2 (nitrogen dioxide), PM 1 (particulate matter with aerodynamic diameters not more than 1 μm) and PM 2.5 (particulate matter with aerodynamic diameters not more than 2.5 μm) at the home address of participants before the baseline survey. Logistic regression was used to evaluate the odds ratio and 95% confidence interval between long-term air pollution and excessive daytime sleepiness. The average concentrations of NO 2 , PM 1 and PM 2.5 during three years preceding baseline survey were 38.22 μg/m³, 56.29 μg/m³ and 72.30 μg/m³. Exposure to NO 2 , PM 1 and PM 2.5 were all associated with excessive daytime sleepiness. Each 1 μg/m³ increment of NO 2 , PM 1 and PM 2.5 were related to a 20% (OR: 1.20, 95% CI: 1.13–1.27), 10% (OR: 1.10, 95% CI: 1.05–1.16) and 17% (OR: 1.17, 95% CI: 1.10–1.23) increase of the prevalence of excessive daytime sleepiness. The study demonstrated that long-term exposure to NO 2 , PM 1 and PM 2.5 were all associated with excessive daytime sleepiness. The impact of air pollution should be considered when treating individuals with excessive daytime sleepiness. • The survey studied the effect of air pollution on daytime sleepiness in rural China. • Exposure to ambient NO 2 , PM 1 and PM 2.5 were all associated with daytime sleepiness. • NO 2 showed higher effect on daytime sleepiness than PM 1 and PM 2.5 • Women and those of moderate exercise have higher odds ratios for daytime sleepiness. [ABSTRACT FROM AUTHOR]

• Long-term exposure to PM 2.5 was associated with poor sleep quality (OR = 1.15). • Long-term exposure to NO 2 was associated with poor sleep quality (OR = 1.14). • Exposure to air pollution showed adverse effects on sleep quality in rural China. • Health effects of air pollution in rural areas should be given more attention. Poor sleep quality is associated with poor quality of life and may even lead to mental illnesses. Several studies have indicated the association between exposure to air pollution and sleep quality. However, the evidence is very limited in China, especially in rural areas. Participants in this study were obtained from the Henan Rural Cohort established during 2015–2017. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI) in the baseline survey. Poor sleep quality was defined by the global score of PSQI > 5. Participants' exposures to PM 2.5 , PM 10 (particulate matter with aerodynamic diameters ≤2.5 μm and 10 μm, respectively) and NO 2 (nitrogen dioxide) during the three years before the baseline survey were estimated using a satellite-based prediction. The associations between long-term exposure to air pollutants and sleep quality were examined using both the linear regression and logistic regression models. The IQRs (interquartile range) of mean levels of participants' exposures to PM 2.5 , PM 10 and NO 2 were 3.3 µg/m3, 8.8 µg/m3, and 4.8 µg/m3, respectively. After adjusted for potential confounders, the global score of PSQI (and 95%CI, 95% confidence intervals) increased by 0.16 (0.04, 0.27), 0.09 (−0.01, 0.19) and 0.14 (0.03, 0.24), associated with per IQR increase in PM 2.5 , PM 10 and NO 2 , respectively. The odds ratios (and 95%CI) of poor sleep quality associated with per IQR increase in PM 2.5 , PM 10 and NO 2 were 1.15 (1.03, 1.29), 1.11 (1.02, 1.21) and 1.14 (1.03, 1.25), respectively. Long-term exposures to PM 2.5 , PM 10 and NO 2 were associated with poor sleep quality in rural China. Improvement of air quality may help to improve sleep quality among rural population of China. [ABSTRACT FROM AUTHOR]

• Higher PM 1 , PM 2.5 , NO 2 exposure concentrations were associated with increased odds of type 2 diabetes. • Higher levels of PM 1 , PM 2.5 , NO 2 exposure were associated with an elevated fasting blood glucose levels. • Males and populations aged 65 years or older may susceptible to air pollution. To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM 1 and PM 2.5), nitrogen dioxide (NO 2) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations. A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to September 2017 in rural areas of Henan province, China. Three-year average residential exposure levels of PM 1 , PM 2.5 , NO 2 for each subject were estimated by a spatiotemporal model. Logistic regression and linear regression models were applied to estimate the associations between PM 1 , PM 2.5 , NO 2 exposure and type 2 diabetes prevalence and fasting blood glucose levels. The mean 3-year residential exposure concentrations of PM 1 , PM 2.5 and NO 2 was 57.4 μg/m3, 73.4 μg/m3 and 39.9 μg/m3, respectively. Higher exposure concentrations of PM 1 , PM 2.5 , NO 2 by 1 μg/m3 was positively related to a 4.0% (95%CIs: 1.026, 1.054), 6.8% (1.052, 1.084) and 5.0% (1.039, 1.061) increase in odds of type 2 diabetes in the final adjusted models. Besides, a 1 μg/m3 increase of PM 1 , PM 2.5 and NO 2 was related to a 0.020 mmol/L (95%CIs: 0.014, 0.026), 0.036 mmol/L (95%CIs: 0.030, 0.042) and 0.030 mmol/L (95%CIs: 0.026, 0.034) mmol/L higher fasting blood glucose levels. Higher exposure concentrations of air pollutants were positively related to the increased odds of type 2 diabetes, as well as higher fasting blood glucose levels in Chinese rural populations. [ABSTRACT FROM AUTHOR]