Frontiers in public health · 2026
Joint effects of prenatal PM2.5 and heavy metals on preterm birth: evidence from a nested case-control study in China.
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Feng Jinxiu, He Ziyi, Ming Xin, Yang Yunping, Li Yannan, Ting Dong, Chen Xinzhen, Zhang Min, Wang Yankun, Zhou Li, Zhou Wenzheng
Аннотация
BACKGROUND: Preterm birth (PTB) is a global health concern. The combined effects of prenatal PM2.5 and heavy metal exposures on PTB risk remain unclear.
METHODS: A nested case-control study included 111 PTB cases and 124 controls from Chongqing. Maternal blood concentrations of 18 trace elements were measured in mid-pregnancy. Fine particulate matter (PM2.5) exposure data were obtained from the Tracking Air Pollution in China (TAP). Residential addresses were geocoded and linked to these exposure estimates. Logistic regression, weighted quantile sum (WQS), grouped WQS (GWQS), and bayesian kernel machine regression (BKMR) models were used to evaluate individual, mixture and interaction effects.
RESULTS: Higher PM2.5 exposure during the second trimester and early-to-mid pregnancy was associated with increased PTB risk. Cadmium, selenium, and zinc were positively associated with PTB, whereas lithium and nickel were inversely associated. WQS models indicated the mixture was associated with elevated PTB risk (OR: 2.01, 95% CI: 1.09, 3.71), with PM2.5 contributing the largest weight, lithium and nickel were inversely associated (OR: 0.36, 95% CI: 0.18, 0.74). GWQS models showed that PM2.5 (OR: 2.24, 95% CI: 1.68, 3.07) and essential trace elements (ETE) (OR: 2.32, 95% CI: 1.60, 3.44) positively associated with PTB, whereas conditionally essential trace elements (CTE) were inversely associated (OR: 0.37, 95% CI: 0.23, 0.59). Seven-group GWQS analyses suggested potential interaction between PM2.5 and ETE (OR: 4.44, 95% CI: 2.33, 9.10) and inverse associations with CTE. BKMR revealed nonlinear mixture effects and a non-monotonic effect of lithium.
CONCLUSION: Pregnancy exposure to PM2.5 and heavy metal mixtures were associated PTB risk, with evidence of complex and potentially interactive associations. These findings highlight the importance of integrated assessments of multiple environmental exposures and targeted public health strategies to reduce maternal and child health risks.
METHODS: A nested case-control study included 111 PTB cases and 124 controls from Chongqing. Maternal blood concentrations of 18 trace elements were measured in mid-pregnancy. Fine particulate matter (PM2.5) exposure data were obtained from the Tracking Air Pollution in China (TAP). Residential addresses were geocoded and linked to these exposure estimates. Logistic regression, weighted quantile sum (WQS), grouped WQS (GWQS), and bayesian kernel machine regression (BKMR) models were used to evaluate individual, mixture and interaction effects.
RESULTS: Higher PM2.5 exposure during the second trimester and early-to-mid pregnancy was associated with increased PTB risk. Cadmium, selenium, and zinc were positively associated with PTB, whereas lithium and nickel were inversely associated. WQS models indicated the mixture was associated with elevated PTB risk (OR: 2.01, 95% CI: 1.09, 3.71), with PM2.5 contributing the largest weight, lithium and nickel were inversely associated (OR: 0.36, 95% CI: 0.18, 0.74). GWQS models showed that PM2.5 (OR: 2.24, 95% CI: 1.68, 3.07) and essential trace elements (ETE) (OR: 2.32, 95% CI: 1.60, 3.44) positively associated with PTB, whereas conditionally essential trace elements (CTE) were inversely associated (OR: 0.37, 95% CI: 0.23, 0.59). Seven-group GWQS analyses suggested potential interaction between PM2.5 and ETE (OR: 4.44, 95% CI: 2.33, 9.10) and inverse associations with CTE. BKMR revealed nonlinear mixture effects and a non-monotonic effect of lithium.
CONCLUSION: Pregnancy exposure to PM2.5 and heavy metal mixtures were associated PTB risk, with evidence of complex and potentially interactive associations. These findings highlight the importance of integrated assessments of multiple environmental exposures and targeted public health strategies to reduce maternal and child health risks.