Abstract
BACKGROUND: Maternal PM(2.5) exposure and lipid levels during pregnancy were independently detected associated with birth weight. Potential mediating factors still remain unclear. METHODS: This study aimed to examine the association of maternal PM(2.5) exposure and birth weight, and explore the potential mediation effect of maternal blood lipids in the relationship between PM(2.5) exposure and birth weight. 5,162 pregnant women from Zhejiang, China were included in the study during 2013-2014. We measured blood lipids for each participant in the second and third trimesters. Air pollution exposure in residential districts was estimated based on satellite data for each individual throughout three trimesters in pregnancy. Linear mixed-effects models were employed to examine associations between PM(2.5) and birth weight. Using a mediation analysis approach, we decomposed the total effect of PM(2.5) on birth weight into natural direct and indirect effects via blood lipid concentration. RESULTS: After adjusting for covariates, a 10 µg/m(3) increment in PM(2.5) during the second trimester was directly associated with an 11.65 g increase in birth weight (95% CI: 2.99, 20.31 g). The indirect effects of PM(2.5) exposure (each 10 µg/m(3) increase) on birth weight, mediated through elevated maternal lipid levels, were - 2.35 g (95% CI: -4.07, -0.63 g) for total cholesterol to high-density lipoprotein cholesterol ratio (TC: HDL ratio), -0.69 g (95% CI: -1.16, -0.22 g) for Triglycerides (TG), and - 1.80 g (95% CI: -3.19, -0.41 g) for HDL-C, during the second trimester. CONCLUSIONS: Findings suggest prenatal PM(2.5) exposure may impact term birth weight via direct biological effects and lipid-mediated pathways, underscoring the importance of incorporating air pollution mitigation into perinatal care and advancing biomarker-driven fetal monitoring. Future research should clarify PM(2.5) component-specific effects, decode placental-fetal lipid regulatory mechanisms, and validate pollution-metabolism-outcome relationships through multi-regional cohorts to inform precision environmental health interventions and clinical risk management.