Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert

被引:0
作者
Wang, Zhe [1 ]
Ji, Weidong [1 ]
Wang, Yushan [2 ,3 ]
Li, Lin [4 ]
Wang, Kai [5 ]
Liu, Hongze [1 ]
Yang, Yining [1 ,3 ,6 ]
Zhou, Yi [1 ]
机构
[1] Sun Yat Sen Univ, Zhongshan Sch Med, 74 Zhongshan 2nd Rd, Guangzhou 510080, Guangdong, Peoples R China
[2] Peoples Hosp XinJiang Uyghur Autonomous Reg, Ctr Hlth Management, Urumqi 830000, Peoples R China
[3] Peoples Hosp Xinjiang Uyghur Autonomous Reg, Xinjiang Key Lab Cardiovasc Homeostasis & Regenera, Urumqi 830000, Peoples R China
[4] Xinjiang Med Univ, Sch Nursing, Urumqi 830054, Xinjiang, Peoples R China
[5] Xinjiang Med Univ, Dept Med Engn & Technol, Urumqi 830054, Xinjiang, Peoples R China
[6] Peoples Hosp Xinjiang Uyghur Autonomous Reg, Dept Cardiol, Urumqi 830000, Peoples R China
关键词
Air pollutant; Metabolic syndrome; Particulate matter; Desert area; Cross-sectional study; LONG-TERM EXPOSURE; CARDIOVASCULAR-DISEASE RISK; AIRBORNE PARTICULATE MATTER; TYPE-2; DIABETES-MELLITUS; INSULIN-RESISTANCE; BLOOD-PRESSURE; POLLUTION; GLUCOSE; HEALTH; HYPERTENSION;
D O I
10.1016/j.ecoenv.2024.117525
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background: Air pollution is a recognized contributor to metabolic syndrome (MetS); but studies in developing regions, including China, remain limited, especially in severely polluted areas near the Taklamakan Desert. Methods: Health data from 2,689,455 individuals aged >= 18 years in five regions near the Taklamakan Desert were analyzed. MetS diagnosed followed the 2016 Chinese Adult Dyslipidaemias Management Guidelines. Spatio-temporal data from satellite observations were employed to estimate ambient pollution levels, encompassing particulate matter with diameters of up to 1.0 mu m (PM1), 2.5 mu m (PM2.5), and 10 mu m (PM10), along with Ozone (O3) and Carbon monoxide (CO). To investigate the association between air pollutants and the prevalence of MetS and its components, Spatial Generalized Linear Mixed Models were applied, with adjustments made for relevant covariates. Additional stratified and sensitivity analyses were conducted to further investigate these relationships. Results: The study observed a 20.43 % prevalence of MetS. Non-linear analysis indicated a significant association between all pollutants and MetS prevalence. A 10 mu g/m3 increase in concentration was associated with the following respective odds ratios: PM1 (1.341, 95 % CI: 1.331, 1.351), PM2.5 (1.036, 95 % CI: 1.034, 1.037), PM10 (1.006, 95 % CI: 1.005, 1.007), O3 (1.385, 95 % CI: 1.374, 1.396), and CO (1.015,95 %, CI: 1.0147, 1.016). The reliability of these associations was supported by further sensitivity analyses, accounting for variations in age, sex, physical activity, and smoking status. Additional analysis indicated links between pollutants and MetS components, including abdominal obesity, glucose metabolism, and lipid profiles. Conclusions: There is an observed association between long-term exposure to air pollution and a heightened risk of MetS, particularly in men, younger individuals, those who are physically inactive, and smokers.
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页数:9
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