Search

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.)

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: 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., Methods: 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., Results: 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., Conclusion: 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., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: 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., Material and Methods: 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., Results: The mean 3-year residential exposure concentrations of PM 1 , PM 2.5 and NO 2 was 57.4 μg/m 3 , 73.4 μg/m 3 and 39.9 μg/m 3 , respectively. Higher exposure concentrations of PM 1 , PM 2.5 , NO 2 by 1 μg/m 3 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/m 3 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., Conclusions: 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., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: 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., Methods: 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., Results: The IQRs (interquartile range) of mean levels of participants' exposures to PM 2.5 , PM 10 and NO 2 were 3.3 µg/m 3 , 8.8 µg/m 3 , and 4.8 µg/m 3 , 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., Conclusions: 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., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Evidence on the effect of long-term exposure to fine particulate matter (PM2.5) on erythrocytosis and thrombocytosis prevalence was limited. We aimed to investigate the association of PM2.5 and its constituents with the risks of erythrocytosis and thrombocytosis. The present study included a total of 33,585 participants from the Henan Rural Cohort at baseline between 2015 and 2017. A hybrid satellite-based model was employed to estimate the concentrations of PM2.5 mass and its constituents (including black carbon [BC], nitrate [NO3−], ammonium [NH4+], inorganic sulfate [SO42−], organic matter [OM], and soil particles [SOIL]). The logistic regression model was used to assess the associations of single exposure to PM2.5 and its constituents with the risks of erythrocytosis and thrombocytosis, and the quantile G-computation method was applied to evaluate their joint exposure risk. For the independent association, the odds ratios for erythrocytosis/thrombocytosis with 1 μg/m3 increase was 1.049/1.043 for PM2.5 mass, 1.596/1.610 for BC, 1.410/1.231 for NH4+, 1.205/1.139 for NO3−, 1.221/1.359 for OM, 1.300/1.143 for SO42−, and 1.197/1.313 for SOIL. Joint exposure to PM2.5 and its components was also positively associated with erythrocytosis and thrombocytosis. The estimated weight of NH4+ was found to be the largest for erythrocytosis, while OM had the largest weight for thrombocytosis. PM2.5 mass and its constituents were positively linked to prevalent erythrocytosis and thrombocytosis, both in single-exposure and joint-exposure models. Additionally, NH4+/OM was identified as a potentially responsible component for the association between PM2.5 and erythrocytosis/thrombocytosis. [ABSTRACT FROM AUTHOR]

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. 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). • High levels of air pollution related to increased blood pressure and hypertension. • Obesity related to increased blood pressure and hypertension in rural adults. • Obesity amplified associations of air pollutants with blood pressure and hypertension. [ABSTRACT FROM AUTHOR]

Residential greenness may be beneficial for cardiovascular health, but the evidence is still scarce, especially in developing countries. This study aimed to assess the associations between exposure to residential greenness and 10-year atherosclerotic cardiovascular disease (ASCVD) risk in a large rural Chinese adult population. This was a cross-sectional study based on 31,162 participants aged 35–74 years with complete data on predictors of the 10-year ASCVD risk from the Henan Rural Cohort Study. The satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used to quantify residential greenness in a buffer radius of 500 m, 1000 m, and 3000 m. The high 10-years ASCVD risk was defined as the estimated risk ≥10% based on prediction equations from the China-PAR Project for Chinese populations. Multivariable-adjusted logistic regression models were performed to estimate the associations of greenness exposures with high 10-year ASCVD risk, and mediation analyses were employed to the potential mediators. For per interquartile range (IQR) increase in NDVI 500−m , NDVI 1000−m , NDVI 3000−m , EVI 500−m , EVI 1000−m , and EVI 3000−m , the adjusted OR (95% CI) of high 10-years ASCVD risk was 0.828 (0.793–0.866), 0.850 (0.817–0.885), 0.823 (0.792–0.855), 0.848 (0.809–0.889), 0.863 (0.826–0.901), 0.843 (0.805–0.883), respectively. Strong associations of NDVI 500−m and EVI 500−m with high 10-years ASCVD risk were found among participants with lower education level and lower averaged monthly income. The associations of greenness exposures with high 10-year ASCVD risk were partially explained by particulate matter with an aerodynamic diameter ≤1 µm, BMI, and physical activity. Enhancing residential greenness exposure may be beneficial for reducing the high 10-year ASCVD risk in rural Chinese adults. [Display omitted] • This study explored the association of greenness with the 10-year ASCVD risk. • Residential greenness levels were inversely associated with 10-year ASCVD risk. • The stronger associations were observed in participants with lower education level. • The stronger effects were found among participants with lower monthly income. • The associations were partially explained by PM 1 , BMI and physical activity. [ABSTRACT FROM AUTHOR]

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. 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. 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. Per 1 μg/m3 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. 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. [Display omitted] • Long-term exposure to PM 1 or PM 2.5 was associated with serum cortisone among Chinese rural adults. • Meat intake was found to be a significant moderator in the positive associations of PM 1 or PM 2.5 with serum cortisone. • Our study implied that meat should be consumed reasonably and measures should be taken to control air pollution. [ABSTRACT FROM AUTHOR]

• Long-term exposure to PM was associated with serum testosterone and progesterone. • Greenness was positively associated with serum testosterone and progesterone. • Associations of greenness with testosterone and progesterone were modified by PM. 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. 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. 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. After adjusting for potential confounding factors, a 1 μg/m3 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/m3 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. 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. [ABSTRACT FROM AUTHOR]

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. 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. Each 1 μg/m3 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. 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. [Display omitted] • High level of single-air pollutant was related to increased mtDNA-CN. • Exposure to mixture of air pollutants was positively related to mtDNA-CN. • Physical activity counteracted association of single or mixture of air pollutants with mtDNA-CN. [ABSTRACT FROM AUTHOR]

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. 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. Each 1 μg/m3 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. 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. Unlabelled Image • Exposure to high air pollutants was related to RTL shortening in rural adults. • Physical activity attenuated the negative associations of air pollutants with RTL. • Physical activity counteracted the effect of air pollutants on RTL in T2DM patients. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. • Low socioeconomic status was related to increased risk of obesity in rural adults. • Exposure to mixture of air pollutants was positively related to obesity in rural adults. • Low socioeconomic status aggravated the effect of mixture of air pollution on obesity. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. Unlabelled Image • Associations of air pollution with platelet traits were assessed in rural regions. • Air pollutants related to increase in platelet size among rural Chinese adults. • Physical activity attenuated negative effect of air pollutants on platelet indices. [ABSTRACT FROM AUTHOR]

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. 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. The odds ratios (95% confidence intervals [CI]) of SI in response to each 1 μg/m3 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. 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. • We explored effects of air pollutants on suicidal ideation in rural China. • Chronic air pollutants exposure was related to elevated risk of suicidal ideation. • Specific subgroups were more vulnerable to the adverse effects of air pollutants. • Our findings are of highly relevant to public health policy and practice in China. [ABSTRACT FROM AUTHOR]

• Air pollutants were positively associated with 10-year ASCVD risk in rural regions. • Negative association of physical activity with 10-year ASCVD risk was found. • Physical activity may be an effective method to reduce 10-year ASCVD risk. 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. 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. Each 1 µg/m3 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). 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. [ABSTRACT FROM AUTHOR]

• Rural residents in central China were exposed to high levels of PM 1. • PM 1 exposure was related to increased TC and LDL-C, and decreased TG and HDL-C. • High levels of PM 1 was associated with higher risk of dyslipidemias. • Males, older and overweight participants were vulnerable to adverse effects of PM 1. Air pollution has been shown to be associated with blood lipid levels. However, studies on long-term ambient particulate matter with aerodynamic diameter ≤1 μm (PM 1) exposure in high-exposure areas are still limited. This study aimed to explore the associations among long-term PM 1 exposure, blood lipids and dyslipidemias. Baseline data of The Henan Rural Cohort study was used in present study, including a total of 39,259 participants aged from 18 to 79 years. Daily levels of PM 1 were estimated by a spatiotemporal model using ground-level measurements of PM 1 , satellite remote sensing data and other predictors, according to participants' home addresses. Individual exposure to PM 1 was the 3-year average before baseline investigation. Linear regression and logistic regression models were applied to examine the associations among PM 1 , blood lipids ((total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)), and prevalence of dyslipidemias. The 3-year concentration of PM 1 was 55.7 ± 2.1 μg/m3. Each 1 μg/m3 increment of PM 1 was associated with an increase of 0.21% (95% confidence interval (CI): 0.11%–0.31%) in TC and 0.75% (95% CI: 0.61%–0.90%) in LDL-C, while decrease of 2.68% (95% CI: 2.43%–2.93%) in TG and 0.47% (95% CI: 0.35%–0.59%) in HDL-C. Each 1 μg/m3 increase in PM 1 was associated with 6% (95% CI: 4%–8%), 3% (95% CI: 2%–5%) and 5% (95% CI: 3%–7%) higher risks of hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia. Sex, age and BMI statistically modified the associations between PM 1 with blood lipid levels and dyslipidemias. Higher PM 1 exposure was associated with adverse changes of blood lipid levels and dyslipidemias. Males, older and overweight participants were susceptive to the adverse effects of PM 1. [ABSTRACT FROM AUTHOR]

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. 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. We observed that per 1 μg/m3 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. 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. • We explored effect of air pollution on osteoporosis in mainland China firstly. • Air pollution have to do with elevated prevalence of osteoporosis in rural China. • 20.29%–24.36% of the osteoporosis cases could be attributed to air pollution. • Our findings have great significance on development of environmental health policy. [ABSTRACT FROM AUTHOR]

• Positive associations of air pollutants with MetS were found in rural Chinese adults. • Physical activity was negatively associated with MetS in rural Chinese adults. • Air pollutants attenuated the negative association of physical activity with MetS. 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. 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. The prevalence of MetS was 30.8%. The adjusted odd ratio of MetS with a per 5 µg/m3 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. 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. [ABSTRACT FROM AUTHOR]