Association of PM 2.5 and Its Chemical Compositions with Metabolic Syndrome: A Nationwide Study in Middle-Aged and Older Chinese Adults

Qian Guo, Yuchen Zhao, Tao Xue, Junfeng Zhang and Xiaoli Duan ()
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Qian Guo: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Yuchen Zhao: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Tao Xue: Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100083, China
Junfeng Zhang: Nicholas School of the Environment and Global Health Institute, Duke University, Durham, NC 27708, USA
Xiaoli Duan: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China

IJERPH, 2022, vol. 19, issue 22, 1-11

Abstract: Studies on the association of PM 2.5 and its compositions with metabolic syndrome (MetS) were limited, and it was unclear which was the most hazardous composition. In this study, we aimed to investigate the association between PM 2.5 and its compositions with MetS and identified the most hazardous composition. In this study, we included 13,418 adults over 45 years across 446 communities from 150 counties of 28 provinces in nationwide China in 2015. MetS was defined based on the five indicators of the Joint Interim Societies, including: blood pressure (SBP (systolic blood pressure) and DBP (diastolic blood pressure)); fasting blood glucose (FBG); fasting triglyceride (FTG); high density lipoprotein cholesterol (HDL-C); and waist circumference (WC). We used chemical transport models to estimate the concentration of PM 2.5 and its compositions, including black carbon, ammonium, nitrate, organic matter, and sulfate. We used a generalized linear regression model to examine the association of PM 2.5 and its compositions with MetS. In this study, we observed that the average age was 61.40 (standard deviation (SD): 9.59). Each IQR (29.76 μg/m 3 ) increase in PM 2.5 was associated with a 1.27 (95% CI: 1.17, 1.37) increase in the odds for MetS. We indicated that black carbon showed stronger associations than other compositions. The higher associations were observed among women, participants aged less than 60 years, who lived in urban areas and in the Northeast, smokers, drinkers, and the obese populations. In conclusion, our findings identified the most harmful composition and sensitive populations and regions that required attention, which would be helpful for policymakers.

Keywords: particulate matter; metabolic syndrome; adults; composition; cross-sectional (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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