Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert
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 ne...
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Elsevier
2025-01-01
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| Series: | Ecotoxicology and Environmental Safety |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651324016014 |
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| author | Zhe Wang Weidong Ji Yushan Wang Lin Li Kai Wang Hongze Liu Yining Yang Yi Zhou |
| author_facet | Zhe Wang Weidong Ji Yushan Wang Lin Li Kai Wang Hongze Liu Yining Yang Yi Zhou |
| author_sort | Zhe Wang |
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| description | 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 µm (PM1), 2.5 µm (PM2.5), and 10 µm (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 μg/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. |
| format | Article |
| id | doaj-art-a5b2a42a4a094516b27f27fd43a3dd56 |
| institution | Kabale University |
| issn | 0147-6513 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj-art-a5b2a42a4a094516b27f27fd43a3dd562025-02-12T05:29:29ZengElsevierEcotoxicology and Environmental Safety0147-65132025-01-01290117525Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan DesertZhe Wang0Weidong Ji1Yushan Wang2Lin Li3Kai Wang4Hongze Liu5Yining Yang6Yi Zhou7Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, ChinaZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, ChinaCenter of Health Management, People's Hospital of Xinjiang Uyghur Autonomous Region, Urumqi 830000, China; Xinjiang Key Laboratory of Cardiovascular Homeostasis and Regeneration Research, People's Hospital of Xinjiang Uyghur Autonomous Region, Urumqi 830000, ChinaSchool of Nursing, Xinjiang Medical University, Urumqi, Xinjiang 830054, ChinaDepartment of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, Xinjiang 830054, ChinaZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, ChinaXinjiang Key Laboratory of Cardiovascular Homeostasis and Regeneration Research, People's Hospital of Xinjiang Uyghur Autonomous Region, Urumqi 830000, China; Department of Cardiology, People's Hospital of Xinjiang Uyghur Autonomous Region, Urumqi 830000, China; Correspondence to: Zhongshan School of Medicine, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou 510080, China.Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, China; Correspondence to: Xinjiang Key Laboratory of Cardiovascular Homeostasis and Regeneration Research, Department of Cardiology, People's Hospital of Xinjiang Uyghur Autonomous Region, Urumqi 830000, ChinaBackground: 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 µm (PM1), 2.5 µm (PM2.5), and 10 µm (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 μg/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.http://www.sciencedirect.com/science/article/pii/S0147651324016014Air pollutantMetabolic syndromeParticulate matterDesert areaCross-sectional study |
| spellingShingle | Zhe Wang Weidong Ji Yushan Wang Lin Li Kai Wang Hongze Liu Yining Yang Yi Zhou Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert Ecotoxicology and Environmental Safety Air pollutant Metabolic syndrome Particulate matter Desert area Cross-sectional study |
| title | Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert |
| title_full | Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert |
| title_fullStr | Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert |
| title_full_unstemmed | Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert |
| title_short | Association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the Taklamakan Desert |
| title_sort | association between exposure to ambient air pollutants and metabolic syndrome in the vicinity of the taklamakan desert |
| topic | Air pollutant Metabolic syndrome Particulate matter Desert area Cross-sectional study |
| url | http://www.sciencedirect.com/science/article/pii/S0147651324016014 |
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