Prenatal Exposure to PM2.5 Components and Preterm Birth: A Case-Crossover Study in Shijiazhuang, China (August 2025)-Prenatal Exposure to PM2.5 Components and Preterm Birth: A Case-Crossover Study in Shijiazhuang, China

Prenatal Exposure to PM2.5 Components and Preterm Birth: A Case-Crossover Study in Shijiazhuang, China

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This study investigated the association between maternal exposure to fine particulate matter (PM2.5) components and the risk of preterm birth (PTB) in Shijiazhuang, China, from 2014 to 2019. PTB, defined as birth before 37 weeks of gestation, is a major global health concern linked to infant mortality and long-term health issues. Although PM2.5 exposure has been associated with PTB, evidence regarding the impact of individual PM2.5 chemical components is limited and inconsistent.<br /><br />The researchers collected daily PTB hospitalization data from a major hospital and analyzed short-term exposures to five main PM2.5 constituents: sulfate (SO4²⁻), nitrate (NO3⁻), ammonium (NH4⁺), organic matter (OM), and black carbon (BC). Using a time-stratified case-crossover design and Bayesian kernel machine regression (BKMR), they assessed single-component and mixture effects on PTB risk, accounting for potential lag effects over seven days and adjusting for confounders such as temperature and humidity.<br /><br />Results showed that all five PM2.5 components were significantly associated with increased PTB risk, especially within 0–2 days post-exposure. Among the constituents, black carbon exhibited the strongest influence on PTB when considering combined exposures. No significant interactions among components were detected, indicating additive or independent effects.<br /><br />The study underscored that acute maternal exposure to PM2.5 components can elevate PTB risk, possibly via mechanisms involving systemic inflammation, oxidative stress, placental damage, and disruption of uterine environment leading to early labor. The use of BKMR allowed a sophisticated assessment of pollutant mixtures without assuming linearity or independence.<br /><br />Limitations include potential exposure misclassification due to using modeled pollutant data averaged across districts, lack of data on other pollutants like ozone, and unmeasured maternal factors such as nutrition and pregnancy complications. The findings support the need for air pollution control and targeted interventions to reduce preterm births and call for further research on long-term effects, pollutant interactions, and biological mechanisms.<br /><br />In conclusion, the study provides evidence that exposure to specific PM2.5 chemical components, especially black carbon, is linked to increased preterm birth risk, highlighting the importance of environmental health strategies to protect maternal and infant health.

Keywords

preterm birth

PM2.5 components

maternal exposure

black carbon

sulfate

nitrate

ammonium

organic matter

Bayesian kernel machine regression

Shijiazhuang China