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Association between atmospheric particulate matter (PM 2.5) pollution during pregnancy and premature birth: a systematic review and meta-analysis

Sep 2026 · Advances in Life Sciences · 0 citations

Abstract

Background: Preterm birth (PTB) remains a major public health challenge and one of the leading contributors to neonatal morbidity, mortality, and the global burden of disease. Increasing evidence suggests that exposure to ambient air pollution, particularly fine particulate matter (PM 2.5), may contribute to adverse pregnancy outcomes. This study aimed to estimate the global prevalence of PTB and evaluate the association between PM 2.5 exposure during different stages of pregnancy and PTB risk.Methods: A systematic review and meta-analysis were conducted using studies retrieved from PubMed/Medline, Scopus, and Web of Science databases published between January 1, 2020, and March 1, 2025. Thirty studies (27 cohort, 2 time-series, and 1 cross-sectional) involving 40,142,804 participants were included. Pooled prevalence estimates and effect sizes were calculated to assess the relationship between PM 2.5 exposure and PTB.Results: The pooled global prevalence of PTB was 6.2% (95% CI: 4.2–8.2%), with the highest prevalence observed in North America (8.5%). Exposure to PM 2.5 during the second trimester was significantly associated with an increased risk of PTB. Specifically, each 10 µg/m³ increase in PM 2.5 concentration was associated with a 2% increase in PTB risk (HR = 1.02; 95% CI: 1.00–1.03; p = 0.01). No statistically significant associations were identified for PM 2.5 exposure during the first or third trimesters.Conclusion: The findings indicate that PM 2.5 exposure during the second trimester of pregnancy is associated with an elevated risk of PTB. These results highlight the importance of improving air quality and implementing targeted public health interventions to reduce environmental risks for pregnant women and improve maternal and neonatal health outcomes.KeywordsPreterm birth, PM 2.5, Pregnancy, Air pollution, Meta-analysis, Systematic review

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