Bo-Yi Yang1, Zhengmin Min Qian2, Shanshan Li3, Gongbo Chen3, Michael S Bloom4, Michael Elliott5, Kevin W Syberg6, Joachim Heinrich7, Iana Markevych8, Si-Quan Wang9, Da Chen10, Huimin Ma11, Duo-Hong Chen12, Yimin Liu13, Mika Komppula14, Ari Leskinen14, Kang-Kang Liu1, Xiao-Wen Zeng1, Li-Wen Hu1, Yuming Guo15, Guang-Hui Dong16. 1. Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, China. 2. Department of Epidemiology, Saint Louis University, Saint Louis, MO, USA. 3. College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, USA; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. 4. Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, China; Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY, USA. 5. Department of Biostatistics, Saint Louis University, Saint Louis, MO, USA. 6. Department of Health Management and Policy, Saint Louis University, Saint Louis, MO, USA. 7. Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Munich, Germany. 8. Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Munich, Germany. 9. Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA. 10. School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China. 11. State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China. 12. Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, China. 13. Laboratory of Occupational Environment and Health Effects, Guangzhou Key Medical Discipline of Occupational Health Guardianship, Guangzhou Prevention and Treatment Center for Occupational Diseases, Guangzhou No 12 Hospital, Guangzhou, China. 14. Finnish Meteorological Institute, Atmospheric Research Center of Eastern Finland, Kuopio, Finland. 15. College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, USA; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. Electronic address: yuming.guo@monash.edu. 16. Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, China. Electronic address: donggh5@mail.sysu.edu.cn.
Abstract
BACKGROUND: Health effects of air pollution on diabetes have been scarcely studied in developing countries. We aimed to explore the associations of long-term exposure to ambient particulate matter (PM) and gaseous pollutants with diabetes prevalence and glucose-homoeostasis markers in China. METHODS: Between April 1 and Dec 31, 2009, we recruited a total of 15 477 participants aged 18-74 years using a random number generator and a four-staged, stratified and cluster sampling strategy from a large cross-sectional study (the 33 Communities Chinese Health Study) from three cities in Liaoning province, northeastern China. Fasting and 2 h insulin and glucose concentrations and the homoeostasis model assessment of insulin resistance index and β-cell function were used as glucose-homoeostasis markers. Diabetes was defined according to the American Diabetes Association's recommendations. We calculated exposure to air pollutants using data from monitoring stations (PM with an aerodynamic diameter of 10 μm or less [PM10], sulphur dioxide, nitrogen dioxide, and ozone) and a spatial statistical model (PM with an aerodynamic diameter of 1 μm or less [PM1] and 2·5 μm or less [PM2·5]). We used two-level logistic regression and linear regression analyses to assess associations between exposure and outcomes, controlling for confounders. FINDINGS: All the studied pollutants were significantly associated with increased diabetes prevalence (eg, the adjusted odds ratios associated with an increase in IQR for PM1, PM2·5, and PM10 were 1·13, 95% CI 1·04-1·22; 1·14, 1·03-1·25; and 1·20, 1·12-1·28, respectively). These air pollutants were also associated with higher concentrations of fasting glucose (0·04-0·09 mmol/L), 2 h glucose (0·10-0·19 mmol/L), and 2 h insulin (0·70-2·74 μU/L). No association was observed for the remaining biomarkers. Stratified analyses indicated greater effects on the individuals who were younger (<50 years) or overweight or obese. INTERPRETATION: Long-term exposure to air pollution was associated with increased risk of diabetes in a Chinese population, particularly in individuals who were younger or overweight or obese. FUNDING: The National Key Research and Development Program of China, the National Natural Science Foundation of China, the Fundamental Research Funds for the Central Universities, the Guangdong Province Natural Science Foundation, the Career Development Fellowship of Australian National Health and Medical Research Council, and the Early Career Fellowship of Australian National Health and Medical Research Council.
BACKGROUND: Health effects of air pollution on diabetes have been scarcely studied in developing countries. We aimed to explore the associations of long-term exposure to ambient particulate matter (PM) and gaseous pollutants with diabetes prevalence and glucose-homoeostasis markers in China. METHODS: Between April 1 and Dec 31, 2009, we recruited a total of 15 477 participants aged 18-74 years using a random number generator and a four-staged, stratified and cluster sampling strategy from a large cross-sectional study (the 33 Communities Chinese Health Study) from three cities in Liaoning province, northeastern China. Fasting and 2 h insulin and glucose concentrations and the homoeostasis model assessment of insulin resistance index and β-cell function were used as glucose-homoeostasis markers. Diabetes was defined according to the American Diabetes Association's recommendations. We calculated exposure to air pollutants using data from monitoring stations (PM with an aerodynamic diameter of 10 μm or less [PM10], sulphur dioxide, nitrogen dioxide, and ozone) and a spatial statistical model (PM with an aerodynamic diameter of 1 μm or less [PM1] and 2·5 μm or less [PM2·5]). We used two-level logistic regression and linear regression analyses to assess associations between exposure and outcomes, controlling for confounders. FINDINGS: All the studied pollutants were significantly associated with increased diabetes prevalence (eg, the adjusted odds ratios associated with an increase in IQR for PM1, PM2·5, and PM10 were 1·13, 95% CI 1·04-1·22; 1·14, 1·03-1·25; and 1·20, 1·12-1·28, respectively). These air pollutants were also associated with higher concentrations of fasting glucose (0·04-0·09 mmol/L), 2 h glucose (0·10-0·19 mmol/L), and 2 h insulin (0·70-2·74 μU/L). No association was observed for the remaining biomarkers. Stratified analyses indicated greater effects on the individuals who were younger (<50 years) or overweight or obese. INTERPRETATION: Long-term exposure to air pollution was associated with increased risk of diabetes in a Chinese population, particularly in individuals who were younger or overweight or obese. FUNDING: The National Key Research and Development Program of China, the National Natural Science Foundation of China, the Fundamental Research Funds for the Central Universities, the Guangdong Province Natural Science Foundation, the Career Development Fellowship of Australian National Health and Medical Research Council, and the Early Career Fellowship of Australian National Health and Medical Research Council.
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