Journal of epidemiology and community health · 2026
Maternal exposure to PM2.5 and its major components and the risk of gestational diabetes mellitus: evidence from a case-control study in Southern China.
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Lin Xian, Qu Yanji, Wu Xiaoru, Wang Ximeng, Gao Xiangmin, Wu Yong, Zhou Xinli, Liu Xiaoqing, Chen Shirui, Tuohetasen Shanidewuhaxi, Chen Zhibing, Chen Dan, Chen Jimei, Zhang Wangjian
Аннотация
BACKGROUND: Evidence regarding the association between maternal exposure to PM2.5 and its major components and the risk of gestational diabetes mellitus (GDM) is still limited. Our study aimed to fill this research gap with a case-control study in Southern China.
METHODS: 191 cases and 764 controls were enrolled during 2013-2020. Daily mean PM2.5 and component concentrations were obtained from the ChinaHighAirPollutants. GDM was diagnosed using the WHO criteria. We used logistic regression integrated with inverse probability weighting and generalised weighted quantile sum regression models to estimate the association between PM2.5 components during multiple trimesters and GDM risk.
RESULTS: A positive association was observed between PM2.5 exposure and GDM risk, with ORs of 1.36 (95% CI 1.11 to 1.66) and 1.34 (95% CI 1.08 to 1.67) per IQR increase in the first (18.8 µg/m³) and second (20.6 µg/m³) trimesters, respectively. Women with low income and education levels were particularly vulnerable to GDM following particulate exposure. Black carbon (weight: 0.33), nitrate (weight: 0.22) and sulfate (weight: 0.20) contributed most of the overall PM2.5 mixture effect in the first trimester, while in the second trimester, sulfate (weight: 0.38) made the most significant contribution, followed by black carbon (weight: 0.22) and nitrate (weight: 0.20).
CONCLUSIONS: The risk of GDM was significantly associated with PM2.5 exposure in the first and second trimesters. The mixture impact in the first trimester was mainly attributed to black carbon, nitrate and sulfate, while that in the second trimester was mainly attributed to sulfate, black carbon and nitrate.
METHODS: 191 cases and 764 controls were enrolled during 2013-2020. Daily mean PM2.5 and component concentrations were obtained from the ChinaHighAirPollutants. GDM was diagnosed using the WHO criteria. We used logistic regression integrated with inverse probability weighting and generalised weighted quantile sum regression models to estimate the association between PM2.5 components during multiple trimesters and GDM risk.
RESULTS: A positive association was observed between PM2.5 exposure and GDM risk, with ORs of 1.36 (95% CI 1.11 to 1.66) and 1.34 (95% CI 1.08 to 1.67) per IQR increase in the first (18.8 µg/m³) and second (20.6 µg/m³) trimesters, respectively. Women with low income and education levels were particularly vulnerable to GDM following particulate exposure. Black carbon (weight: 0.33), nitrate (weight: 0.22) and sulfate (weight: 0.20) contributed most of the overall PM2.5 mixture effect in the first trimester, while in the second trimester, sulfate (weight: 0.38) made the most significant contribution, followed by black carbon (weight: 0.22) and nitrate (weight: 0.20).
CONCLUSIONS: The risk of GDM was significantly associated with PM2.5 exposure in the first and second trimesters. The mixture impact in the first trimester was mainly attributed to black carbon, nitrate and sulfate, while that in the second trimester was mainly attributed to sulfate, black carbon and nitrate.