Ethnic disparities in the association between ambient air pollution and risk for cardiometabolic abnormalities in China

Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease and subtypes: A retrospective cohort study of the employed population of Southwest China

BACKGROUND

While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear.

OBJECTIVE

To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes.

METHODS

Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3-, SO42-, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD.

RESULTS

Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42-, NO3-, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42- (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD.

CONCLUSIONS

Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.

The role of liver enzymes in the association between ozone exposure and diabetes risk: a cross-sectional study of Zhuang adults in China

Background: Growing evidence has demonstrated the role of ambient air pollutants in driving diabetes incidence. However, epidemiological evidence linking ozone (O3) exposure to diabetes risk has been scarcely studied in Zhuang adults in China. We aimed to investigate the associations of long-term exposure to O3 with diabetes prevalence and fasting plasma glucose (FPG) and estimate the mediating role of liver enzymes in Zhuang adults. Methods: We recruited 13 843 ethnic minority adults during 2018-2019 based on a cross-sectional study covering nine districts/counties in Guangxi. Generalized linear mixed models were implemented to estimate the relationships between O3 exposure and diabetes prevalence and FPG. Mediation effect models were constructed to investigate the roles of liver enzymes in the associations of O3 exposure with diabetes prevalence and FPG. Subgroup analyses were conducted to identify potential effect modifications. Results: Long-term exposure to O3 was positively associated with diabetes prevalence and FPG levels in Zhuang adults, with an excess risk of 7.32% (95% confidence interval [CI]: 2.56%, 12.30%) and an increase of 0.047 mmol L-1 (95% CI: 0.032, 0.063) for diabetes prevalence and FPG levels, respectively, for each interquartile range (IQR, 1.18 μg m-3) increment in O3 concentrations. Alanine aminotransferase (ALT) significantly mediated 8.10% and 29.89% of the associations of O3 with FPG and diabetes prevalence, respectively, and the corresponding mediation proportions of alkaline phosphatase (ALP) were 8.48% and 30.00%. Greater adverse effects were observed in females, obese subjects, people with a low education level, rural residents, non-clean fuel users, and people with a history of stroke and hypertension in the associations of O3 exposure with diabetes prevalence and/or FPG levels (all P values for interaction < 0.05). Conclusion: Long-term exposure to O3 is related to an increased risk of diabetes, which is partially mediated by liver enzymes in Chinese Zhuang adults. Promoting clean air policies and reducing exposure to environmental pollutants should be a priority for public health policies geared toward preventing diabetes.

Role of metabolic risk factors in the relationship between ambient fine particulate matter and depressive symptoms: Evidence from a longitudinal population study

BACKGROUND

There is growing evidence indicating a connection between fine particulate matter (PM2.5) and depressive symptoms. Metabolic risk factors are critical determinants of depressive symptoms. However, the mediating role of these factors on the association between PM2.5 and depressive symptoms remains elusive. We aimed to investigate whether and to what extent metabolic risk factors mediated the link between long-term PM2.5 exposure and depressive symptoms.

METHODS

This study comprised 7794 individuals aged between 30 and 79 years who participated in two waves of the on-site surveys in the China Multi-Ethnic Cohort. Ambient PM2.5 concentrations were assessed utilizing a random forest method based on satellite data. We employed the Patient Health Questionnaire-9 to assess depressive symptoms at wave 2, and the overall as well as three sub-domain symptom scores (emotional, neurovegetative, and neurocognitive symptoms) were calculated. Three metabolic risk factors, including hypertension, diabetes, and dyslipidemia, were considered. Mediation analyses were conducted to assess the indirect effects of PM2.5 on depressive symptoms through metabolic risk factors.

RESULTS

We found a positive association between chronic exposure to ambient PM2.5 and overall depressive symptoms as well as the three sub-domains. In mediation analyses, metabolic risk factors partially mediated the associations of PM2.5 on depressive symptoms. The natural indirect effects (RR, 95% CI) of PM2.5 on overall, emotional, neurovegetative, and neurocognitive symptoms mediated through metabolic risk factors were 1.004(1.001, 1.007), 1.004 (1.001, 1.008), 1.004 (1.001, 1.007), and 1.003(0.999, 1.007), respectively. Larger indirect effects were found in elderly participants (mediated proportion, 29.3%), females (13.3%), and people who did not consume alcohol (19.6%).

CONCLUSIONS

Metabolic risk factors may act as mediators in the relationship between chronic PM2.5 exposure and depression. Treatment of metabolic risk factors may be an opportunity to reduce the burden of depression caused by long-term exposure to PM2.5.

Environmental inequalities and multimorbidity: Insights from the Southwest China Multi-Ethnic Cohort Study

Multimorbidity is an increasingly significant public health challenge worldwide. Although the association between environmental factors and the morbidity and mortality of individual chronic diseases is well-established, the relationship between environmental inequalities and multimorbidity, as well as the patterns of multimorbidity across different areas and ethnic groups, remains unclear. We first focus on analyzing the differences in environmental exposures and patterns of multimorbidity across diverse areas and ethnic groups. The results show that individuals of Han ethnicity residing in Chongqing and Sichuan are exposure to higher levels of air pollutants such as PM2.5, PM10, and NO2. Conversely, Tibetans in Tibet and Yi people in Yunnan face elevated concentrations of O3. Furthermore, the Dong, Miao, Buyi ethnicities in Guizhou and Bai in Yunnan have greater access to green spaces. The key multimorbidity patterns observed in Southwest China are related to metabolic abnormalities combined with digestive system diseases. However, significant differences in multimorbidity patterns exist among different regions and ethnic groups. Further utilizing the logistic regression model, the analysis demonstrates that increased exposure to environmental pollutants (PM2.5, PM10, NO2, O3) is significantly associated with higher odds ratios of multimorbidity. Conversely, a greater presence of green spaces (NDVI 250, NDVI 500, NDVI 1000) significantly reduces the risk of multimorbidity. This large-scale epidemiological study provides some evidence of a significant association between environmental inequalities and multimorbidity. By addressing these environmental inequalities and promoting healthy environments for all, we can work towards reducing the prevalence of multimorbidity and improving overall population health.

The impact of air pollution on neurocognitive development: Adverse effects and health disparities

Air pollution is recognized as a major public health concern. The number of deaths related to ambient air pollution has increased in recent years and is projected to continue rising. Additionally, both short- and long-term air pollution exposure has been linked with deleterious effects on neurocognitive function and development. While air pollution poses as a threat to everyone, people of color and individuals of lower socioeconomic status are often exposed to elevated levels of air pollution as a function of systemic racism and classism. Further, given additional disparities in access to healthcare and other compounding stressors, adverse effects of air pollution on neurocognitive health are exacerbated among individuals who hold marginalized identities-making effects both less likely to be detected and treated. This review examines evidence of the effects of air pollution on neurocognitive development across the lifespan and incorporates an environmental justice perspective to highlight disparities in air pollution exposure across race and socioeconomic status. Last, upon the reviewed evidence, limitations of past research and recommendations for policy are discussed.

Long-Term Exposure to Fine Particulate Constituents and Vascular Damage in a Population with Metabolic Abnormality in China

AIM

To date, PM2.5-associated vascular damage in metabolic abnormalities has remained controversial. We knew little about the vascular damage of PM2.5 constituents. Thus, this study aimed to investigate the relationship between long-term exposure to PM2.5 and its constituents and vascular damage in metabolic abnormalities.

METHODS

A total of 124,387 participants with metabolic abnormalities (defined as at least one metabolic disorder, such as obesity, elevated blood pressure, elevated triglyceride level, elevated fasting glucose level, or low HDL cholesterol level) were recruited in this study from 11 representative centers in China between January 2011 and December 2017. PM2.5 and its constituents (black carbon [BC], organic matter [OM], sulfate [SO42-], nitrate [NO3-], and ammonium salts [NH4＋]) were extracted. Elevated brachial-ankle pulse wave velocity (baPWV) (≥ 1,400 cm/s) and declined ankle-brachial index (ABI) (＜0.9) indicated vascular damage. Multivariable logistic regression and Quantile g-Computation models were utilized to explore the impact on outcomes.

RESULTS

Of the 124,387 participants (median age, 49 years), 87,870 (70.64%) were men. One-year lag exposure to PM2.5 and its constituents was significantly associated with vascular damage in single pollutant models. The adjusted odds ratios (OR) for each 1-µg/m3 increase in PM2.5 was 1.013 (95% CI, 1.012-1.015) and 1.031 (95% CI, 1.025-1.037) for elevated baPWV and decreased ABI, respectively. PM2.5 constituents were also associated with vascular damage in multi-pollutant models. Among the PM2.5 constituents, BC (47.17%), SO42- (33.59%), and NH4＋ (19.23%) have the highest contribution to elevated baPWV and NO3- (47.89%) and BC (23.50%) to declined ABI.

CONCLUSION

Chronic exposure to PM2.5 and PM2.5 constituents was related to vascular damage in the abnormal metabolic population in China. The heterogeneous contribution of different PM2.5 constituents to vessel bed damage is worthy of attention when developing targeted strategies.

Development and validation of an age-sex-ethnicity-specific metabolic syndrome score in the Chinese adults

Metabolic syndrome (MetS) is characterized by metabolic dysfunctions and could predict future risk for cardiovascular diseases (CVDs). However, the traditionally defined dichotomous MetS neither reflected MetS severity nor considered demographic variations. Here we develop a continuous, age-sex-ethnicity-specific MetS score based on continuous measures of the five metabolic dysfunctions (waist circumference [WC], triglycerides [TG], high-density lipoprotein cholesterol [HDL-C], mean arterial pressure [MAP], and fasting blood glucose [FBG]). We find that the weights of metabolic dysfunctions in the score vary across age-sex-ethnicity-specific subgroups, with higher weights for TG, HDL-C, and WC. Each unit increase in the score is associated with increased risks for hyperlipidemia, diabetes, and hypertension, and elevated levels of HbA1c, cholesterol, body mass index, and serum uric acid. The score shows high sensitivity and accuracy for detecting CVD-related risk factors and is validated in different geographical regions. Our study would advance early identification of CVD risks and, more broadly, preventive medicine and sustainable development goals.

Mediating effect of body fat percentage in the association between ambient particulate matter exposure and hypertension: a subset analysis of China hypertension survey

BACKGROUND

Hypertension caused by air pollution exposure is a growing concern in China. The association between air pollutant exposure and hypertension has been found to be potentiated by obesity, however, little is known about the processes mediating this association. This study investigated the association between fine particulate matter (aerodynamic equivalent diameter ≤ 2.5 microns, PM2.5) exposure and the prevalence of hypertension in a representative population in southern China and tested whether obesity mediated this association.

METHODS

A total of 14,308 adults from 48 communities/villages in southern China were selected from January 2015 to December 2015 using a stratified multistage random sampling method. Hourly PM2.5 measurements were collected from the China National Environmental Monitoring Centre. Restricted cubic splines were used to analyze the nonlinear dose-response relationship between PM2.5 exposure and hypertension risk. The mediating effect mechanism of obesity on PM2.5-associated hypertension was tested in a causal inference framework following the approach proposed by Imai and Keele.

RESULTS

A total of 20.7% (2966/14,308) of participants in the present study were diagnosed with hypertension. Nonlinear exposure-response analysis revealed that exposure to an annual mean PM2.5 concentration above 41.8 µg/m3 was associated with increased hypertension risk at an incremental gradient. 9.1% of the hypertension burden could be attributed to exposure to elevated annual average concentrations of PM2.5. It is noteworthy that an increased body fat percentage positively mediated 59.3% of the association between PM2.5 exposure and hypertension risk, whereas body mass index mediated 34.3% of this association.

CONCLUSIONS

This study suggests that a significant portion of the estimated effect of exposure to PM2.5 on the risk of hypertension appears to be attributed to its effect on alterations in body composition and the development of obesity. These findings could inform intersectoral actions in future studies to protect populations with excessive fine particle exposure from developing hypertension.

Long-term exposure to air pollution and increased risk of atrial fibrillation prevalence in China

BACKGROUND

Atrial fibrillation (AF) is the most common type of treated heart arrhythmia contributing to adverse cardiovascular events. The association between short-term air pollution exposure and AF episodes has been recognized. But the evidence of the association between long-term air pollution exposure and AF was limited, especially in developing countries.

METHODS

We performed a nationwide cross-sectional study among 1,374,423 individuals aged ≥35 years from 13 health check-up centers. Using logistic regression models, we assessed the association between long-term exposure to single air pollution and AF prevalence, including particulate matter (PM_2.5 and PM₁₀), ozone (O₃) and PM_2.5 compositions, which were estimated by high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants for China. The quantile g-computation model was used to explore the joint effect of all exposures to air pollution and the contribution of an individual component to the mixture.

RESULTS

In single-pollutant models, an increase of 10 μg/m³ in PM_2.5 (OR 1.031[95%CI 1.010,1.053]) and PM₁₀ (OR = 1.021 [95%CI 1.009,1.033]) was positively associated with AF prevalence. The stratified analyses revealed that these associations were significantly stronger in females, people <65 years old, and those with hypertension and diabetes. In the further exploration of the joint effect of PM_2.5 compositions (OR 1.060 [95%CI 1.022,1.101]) per quintile increase in all five PM_2.5 components), we found that PM_2.5 sulfate contributed the most.

CONCLUSIONS

These findings provide important evidence for the positive relationship between long-term exposure to air pollution and AF prevalence in China and identify sulfate particles of PM_2.5 as having the highest contribution to the overall mixture effects among all PM2.5 chemical constituents.

Associations between residential greenness and the predicted 10-year risk for atherosclerosis cardiovascular disease among Chinese adults

BACKGROUND

Exposure to build environments, especially residential greenness, offers benefits to reduce the development of atherosclerotic cardiovascular diseases (ASCVD). The 10-year ASCVD risk is a useful indicator for long-term ASCVD risk, but the evidence on the association and potential pathway of residential greenness in mitigating its development remains unclear.

OBJECTIVES

This study aimed to investigate the associations between residential greenness and the 10-year predicted ASCVD risks, and potentially mediation effect on this association by air pollution, body mass index (BMI) and physical activity (PA).

METHODS

The baseline of the China Multi-Ethnic Cohort (CMEC) study, enrolling 99,556 adults during 2018-2019, was used in this cross-sectional study. The participants' 10-year ASCVD risks were predicted as low-, moderate-, and high-risk groups, based on the six risk factors: age, smoking, hypertension, low-density lipoprotein cholesterol (LDL-C), high high-density lipoprotein cholesterol (HDL-C), and high total cholesterol (TC). The 3-year mean value within the circular buffer of 500 m and 1000 m of Enhanced Vegetation Index (EVI_500m and EVI_1000m) were used to assess greenness exposure. Multiple logistic regression was used to evaluate the association between residential greenness and the 10-year ASCVD risks. Stratified analyses by sex, age and smoking status were performed to identify susceptible populations. Causal mediation analysis was used to explore the mediation effects of air pollution, BMI and PA.

RESULTS

A total of 75,975 participants were included, of which 17.9 % (n = 13,614) and 5.6 % (n = 4253) had the moderate and high 10-year ASCVD risks, respectively. Compared to the low-risk group, each interquartile increase in EVI_500m and EVI_1000m reduced the ASCVD risk of the moderate-risk group by 4 % (OR = 0.96 [0.94, 0.98]) and 4 % (OR = 0.96 [0.94, 0.98]), respectively; and reduced the risk of the high-risk group by 8 % (OR = 0.92 [0.90, 0.96]) and 7 % (OR = 0.93 [0.90, 0.97]), respectively. However, the increased greenness did not affect the ASCVD risk of the high-risk group when compared to the moderate-risk group. Effects of residential greenness on the ASCVD risk were stronger in women than in men (p < 0.05), and were not observed in those aged ≥55. PA and BMI partially mediated the association between greenness and the 10-year ASCVD risk.

CONCLUSIONS

ASCVD prevention strategies should be tailored to maximize the effectiveness within the groups with different ASCVD risks, better at early stages when the ASCVD risk is low.

Sulfur dioxide may predominate in the adverse effects of ambient air pollutants on semen quality among the general population in Hefei, China

Previous studies have reported potential adverse effects of exposure to ambient air pollutants on semen quality in infertile men, but studies on the general population have been limited and inconsistent, and the pollutants that play a major role remain unclear. This study aimed to explore the potential association between exposure to six air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, O₃ and CO) during different sperm development periods and semen quality among the general population, and to explore the interaction between different air pollutant exposures. We included 1515 semen samples collected from the Human Sperm Bank. We improved individuals' exposure level estimation by combining inverse distance weighting (IDW) interpolation with satellite remote sensing data. Multivariate linear regression models, restricted cubic spline functions and double-pollutant models were used to assess the relationship between exposure to six air pollutants and sperm volume, concentration, total sperm number and sperm motility. A negative association was found between SO₂ exposure and progressive motility and total motility during 0-90 lag days and 70-90 lag days, and SO₂ exposure during 10-14 lag days adversely affected sperm concentration and total sperm number. Sensitive analyses for qualified sperm donors and the double-pollutant models obtained similar results. Additionally, there were nonlinear relationships between exposure to PM, NO₂, O₃, CO and a few semen parameters, with NO₂ and O₃ exposure above the threshold showing negative correlations with total motility and progressive motility, respectively. Our study suggested that SO₂ may play a dominant role in the adverse effects of ambient air pollutants on semen quality in the general population by decreasing sperm motility, sperm concentration and total sperm number. Also, even SO₂ exposure lower than the recommended standards of the World Health Organization (WHO) could still cause male reproductive toxicity, which deserves attention.

Rural-urban disparities in the associations of residential greenness with diabetes and prediabetes among adults in southeastern China

AIMS

Greenness offers health benefits to prevent diabetes in urban areas. However, urban-rural disparities in this association have not been explored, with the underlying pathways understudied as well. We aimed to investigate and compare the associations and potential pathways between residential greenness and the risks for diabetes and prediabetes in urban and rural areas.

METHODS

Diabetes and prediabetes were diagnosed by fasting blood glucose (FBG). The participants' residential greenness exposure was estimated by the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The association of residential greenness with the risks for diabetes and prediabetes was estimated by logistic regression and the generalized additive model. The potential mediation effects of air pollution, body mass index (BMI), and physical activity (PA) were examined by causal mediation analysis.

RESULTS

Of the 50,593 included participants, and the prevalence of prediabetes and diabetes were 21.22 % and 5.63 %, respectively. Each 0.1-unit increase in EVI_500m and NDVI_500m for healthy people reduced the risk for prediabetes by 12 % and 8 %, respectively, and substantially reduced the risk for diabetes by 23 % and 19 %, respectively. For those with prediabetes, each 0.1-unit increase in EVI_500m and NDVI_500m reduced the diabetes risk by 14 % and 12 %, respectively. Compared to the risks for diabetes at the 25th percentile of EVI_500m/NDVI_500m, such risks significantly reduced when EVI_500m (NDVI_500m) increased over 0.43 (0.48) and 0.28 (0.39) in urban and rural areas, respectively. The residential greenness-prediabetes/diabetes associations were mediated by air pollution and PA in urban areas and by air pollution and BMI in rural areas.

CONCLUSIONS

Exposure to residential greenness was associated with a lower risk for prediabetes and diabetes in urban areas and, more strongly, in rural areas, which were partly mediated by air pollution, PA, and BMI.

Associations and pathways between residential greenness and metabolic syndromes in Fujian Province

Background

Greenness exposure is beneficial to human health, but its potential mechanisms through which the risk for metabolic syndrome (MetS) could be reduced have been poorly studied. We aimed to estimate the greenness-MetS association in southeast China and investigate the independent and joint mediation effects of physical activity (PA), body mass index (BMI), and air pollutants on the association.

Methods

A cross-sectional study was conducted among the 38,288 adults based on the Fujian Behavior and Disease Surveillance (FBDS), established in 2018. MetS was defined as the presence of three or more of the five components: abdominal obesity, elevated triglyceride, reduced high-density lipoprotein cholesterol (HDL-C), high blood pressure, and elevated fasting glucose. The residential greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 250, 500, and 1,000 meters (m) buffer zones around the residential address of each participant. Logistic regression models were used to estimate the greenness-MetS association. The causal mediation analysis was used to estimate the independent and joint mediation effects of PA, BMI, particulate matter with an aerodynamic diameter of 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂).

Results

Each interquartile range (IQR) increase in greenness was associated with a decrease of 13% (OR = 0.87 [95%CI: 0.83, 0.92] for NDVI_500m and OR = 0.87 [95%CI: 0.82, 0.91] for EVI_500m) in MetS risk after adjusting for covariates. This association was stronger in those aged < 60 years (e.g., OR = 0.86 [95%CI: 0.81, 0.92] for NDVI_500m), males (e.g., OR = 0.73 [95%CI: 0.67, 0.80] for NDVI_500m), having an educational level of primary school or above (OR = 0.81 [95%CI: 0.74, 0.89] for NDVI_500m), married/cohabitation (OR = 0.86 [95%CI: 0.81, 0.91] for NDVI_500m), businessman (OR = 0.82 [95%CI: 0.68, 0.99] for NDVI_500m), other laborers (OR = 0.77 [95%CI: 0.68, 0.88] for NDVI_500m), and non-smokers (OR = 0.77 [95%CI: 0.70, 0.85] for NDVI_500m). The joint effect of all six mediators mediated about 48.1% and 44.6% of the total effect of NDVI_500m and EVI_500m on the MetS risk, respectively. Among them, BMI showed the strongest independent mediation effect (25.0% for NDVI_500m), followed by NO₂ and PM₁₀.

Conclusion

Exposure to residential greenness was associated with a decreased risk for MetS. PA, BMI, and the four air pollutants jointly interpreted nearly half of the mediation effects on the greenness-MetS association.

Associations and pathways between residential greenness and hyperuricemia among adults in rural and urban China

BACKGROUND

Residential greenness may decrease the risk for hyperuricemia in rural areas, but the urban-rural disparities in this association and underlying pathways have not been studied.

OBJECTIVES

To investigate the associations and potential pathways between residential greenness and hyperuricemia in urban and rural areas.

METHODS

The baseline survey of the China Multi-Ethnic Cohort (CMEC) was used. Hyperuricemia was defined as serum uric acid (SUA) > 417 μmol/L for men and >357 μmol/L for women. The satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were used to capture residential greenness. A propensity score inverse-probability weighting method was used to assess urban-rural differences in the associations between residential greenness and hyperuricemia, with possible mediation effects of physical activity (PA), body mass index (BMI), PM_2.5, and NO₂ examined by causal mediation analyses.

RESULTS

A total of 72,372 participants were included. The increases in the EVI_500m and NDVI_500m residential greenness were associated with a decreased risk for hyperuricemia and the SUA level in both urban and rural areas. For example, each 0.1-unit increase in EVI_500m was associated with a decreased hyperuricemia risk of 7% (OR = 0.93 [0.91, 0.96]) and a decreased SUA level of -1.77 μmol/L [-2.60, -0.93], respectively; such associations were stronger in urban areas for both the risk for hyperuricemia (OR = 0.84 [0.83, 0.86]) and SUA level (-7.18 μmol/L [-7.91, -6.46]). The subgroup analysis showed that the greenness-hyperuricemia/SUA association varied by age, sex, and annual household income. The percentage of the joint mediation effect of PA, BMI, PM_2.5, and NO₂ on the association between EVI_500m and the risk for hyperuricemia was higher in urban (34.92%) than rural areas (15.40%). BMI, PM_2.5, and PA showed significantly independently mediation effects for the greenness-hyperuricemia association in both rural and urban areas.

CONCLUSIONS

Exposure to residential greenness was associated with a decreased risk for hyperuricemia, partially through the pathways of PA, BMI, PM_2.5, and NO₂, which varied in urban and rural areas.

Influence and prediction of PM2.5 through multiple environmental variables in China

Fine particulate matter (PM2.5) is an important indicator to measure the degree of air pollution. With the pursuit of sustainable development of China's economy and society, air pollution has been paid more and more attention. The spatial distribution of PM2.5 is affected by multiple factors. In this study, we selected Normalized Difference Vegetation Index (NDVI), precipitation, temperature, wind speed and elevation data to analyze the impact of each variable on PM2.5 in different regions of China. The results show that the high-value areas of PM2.5 were mainly concentrated in the North China Plain, the middle and lower reaches of the Yangtze River Plain, the Sichuan Basin, and the Tarim Basin. PM2.5 showed an upward trend in North China, Northeast China and Northwest China, while in most of South China, especially the Sichuan Basin, PM2.5 showed a downward trend. Therefore, the northern region of China needs to take measures to curb the growth of PM2.5. In Northwest China, wind speed and temperature had a greater impact on PM2.5. In North China, wind speed had a greater impact on PM2.5. In southern China, temperature and NDVI had a greater impact on PM2.5. The deep learning model can better simulate the spatial distribution of PM2.5 based on the selected variables. The clustering effect of single variable is better than multivariate spatial information clustering based on principal component analysis (PCA). It is difficult to explain which variable has the greatest impact on PCA clustering. This study can provide an important reference for PM2.5 prevention and control in different regions of China.