RESUMO
INTRODUCTION: Ambient air pollution might increase the risk of obesity; however, the evidence regarding the relationship between air pollution and obesity in comparable urban and rural areas is limited. Therefore, our aim was to contrast the effect estimates of varying air pollution particulate matter on obesity between urban and rural areas. METHODS: Four obesity indicators were evaluated in this study, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Exposure to ambient air pollution (e.g., particulate matter with aerodynamic diameters 1.0 µm [PM1], PM2.5, and PM10) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between air pollution particulate matter and obesity. Furthermore, the effect estimates of different air pollution particulates were contrasted between urban and rural areas. RESULTS: A total of 36,998 participants in urban areas and 31, 256 in rural areas were included. We found positive associations between long-term exposure to PM1, PM2.5, and PM10 and obesity. Of these air pollutants, PM2.5 had the strongest association. The results showed that the odds ratios (ORs) for general obesity were 1.8 (95% CI, 1.64 to 1.98) per interquartile range (IQR) µg/m3 increase in PM1, 1.89 (95% CI, 1.71 to 2.1) per IQR µg/m3 increase in PM2.5, and 1.74 (95% CI, 1.58 to 1.9) per IQR µg/m3 increase in PM10. The concentrations of air pollutants were lower in rural areas, but the effects of air pollution on obesity of rural residents were higher than those of urban residents. CONCLUSION: Long-term (3 years average) exposure to ambient air pollution was associated with an increased risk of obesity. We observed regional disparities in the effects of particulate matter exposure from air pollution on the risk of obesity, with higher effect estimates found in rural areas. Air quality interventions should be prioritized not only in urban areas but also in rural areas to reduce the risk of obesity.
