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Evidence of the correlation between air pollution and different types of birth defects

Based on a distribution-lag non-linear model

Dados Bibliográficos

ID22070366
AutoresWen Sun (0000-0003-4316-5350, Shanxi Medical University), Qingqing Dong (Changzhi University), Yingying Zhang (0009-0003-0758-2832), Ying‐Ying Zhang (0000-0002-6279-3662, Shanxi Medical University), Hui Wang (0000-0001-5109-8691, Changzhi University), Youqiang Wang (0000-0003-1701-1382, Changzhi University), Wenjie Yuan (0000-0002-2262-2738, Changzhi University), Leyao Wang (0000-0001-5165-4838, Changzhi University), Xianhong Shi (Changzhi University), Yuhong Feng (0000-0002-6138-5229, Changzhi University), Haiwei Wang (0000-0002-5258-0073, Changzhi University), Xiaodan Wang (0000-0003-0216-5135, Changzhi University), Yingbin Ren (Changzhi University), Lihong Wang (0009-0002-7085-301X, Changzhi University), Lijian Lei (0000-0003-2321-3482, Shanxi Medical University, autor correspondente), Wenxia Song (0000-0001-8795-8657, Changzhi University, autor correspondente)
Ano2025
Volume13
Páginas1562461-1562461
Data de publicação2025-04-09
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Public Health (JOURNAL)
Identificadores do periódicoISSN: 2296-2565 • E-ISSN: 2296-2565
EditoraFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1562461
PMID40270732
OpenAlexW4409308419
IdiomaEN
Citações recebidas1
Referências citadas56

Introduction As global fertility rates decline, exploring the root causes of birth defects (BDs) becomes urgent. Air pollution, with its ability to penetrate the placental barrier as exogenous toxins, has garnered notable attention in this regard. Methods BD data was collected from five hospitals in Changzhi City birth from 2019 to 2021, air quality data originated from hourly observations at five monitoring stations within the city. Using the distributed lag non-linear model (DLNM), the study aimed to determine the non-linear exposure-lag-effect relationship, evaluating the delayed impact of weekly air pollution on fetal BD risk. During the period under study, the prevalence of BDs was 19.95‰. Results Our findings indicate that exposure to air pollutants during early and mid-pregnancy elevated the risk of BDs. Specifically, for each 10 μg/m 3 increase of SO 2 , NO 2 , PM 10 , PM 2.5 , O 3 , and CO, the risk of congenital heart defects (CHDs) increased. Peaking at specific gestational weeks: SO 2 at week 17, NO 2 at week 23, PM 10 at week 21, PM 2.5 at week 16, O 3 at week 8, and CO at week 40. Additionally, a rise of 10 μg/m 3 in PM 10 during weeks 4–10 of gestation significantly elevated the risk of polydactyly, peaking at week 6. Increases in PM2.5 and CO were associated with an elevated risk of external ear malformations, peaking at week 18 and week 19, respectively. Furthermore, higher concentrations of NO X and NO increased the risk of syndactyly, peaking at week 0 for both pollutants. Finally, increments of 10 μg/m 3 in NO 2 , NO X , NO, and PM 10 were all significantly associated with an increased risk of cleft lip and/or palate, peaking at week 3 for NO 2 , NO X , NO, and PM 10 . Exposure to air pollutants elevates BD risk, with critical periods during the first and second trimesters. The association between different pollutants and the classification of BDs also varies. Discussion Exposure to pollutants during pregnancy increases the risk of birth defects in newborns, especially SO 2 , PM 10 , PM 2.5 and O 3 . In light of these findings, we recommend that, while overall regional air quality improvements remain essential, specific targeted measures should be implemented for pregnant women, who represent a particularly vulnerable population. These targeted recommendations not only aim to reduce exposure risks for pregnant women and their fetuses but also offer practical insights for public health policy and interventions

Air pollution · Biological system · Biology · Correlation · Distributed lag · Econometrics · Environmental health · Lag · Lag time · Statistics · Air Quality and Health Impacts · Atmospheric chemistry and aerosols · Computer Science · Energy and Environment Impacts · Environmental Science · Mathematics · Medicine · Ecology

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Obras citantes distintas1
Citações por ano1
Intervalo de citações2026 - 2026 (1)
Velocidade de citaçãocurrent
Altamente citadoNão
Tipos de citaçãoNeutras: 1
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