Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model
IntroductionAs 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.MethodsBD data was collected from five hospitals in Ch...
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Frontiers Media S.A.
2025-04-01
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| author | Wen Sun Qingqing Dong Yingying Zhang Hui Wang Youqiang Wang Wenjie Yuan Leyao Wang Xianhong Shi Yuhong Feng Haiwei Wang Xiaodan Wang Yingbin Ren Lihong Wang Lijian Lei Wenxia Song |
| author_facet | Wen Sun Qingqing Dong Yingying Zhang Hui Wang Youqiang Wang Wenjie Yuan Leyao Wang Xianhong Shi Yuhong Feng Haiwei Wang Xiaodan Wang Yingbin Ren Lihong Wang Lijian Lei Wenxia Song |
| author_sort | Wen Sun |
| collection | DOAJ |
| description | IntroductionAs 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.MethodsBD 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‰.ResultsOur findings indicate that exposure to air pollutants during early and mid-pregnancy elevated the risk of BDs. Specifically, for each 10 μg/m3 increase of SO2, NO2, PM10, PM2.5, O3, and CO, the risk of congenital heart defects (CHDs) increased. Peaking at specific gestational weeks: SO2 at week 17, NO2 at week 23, PM10 at week 21, PM2.5 at week 16, O3 at week 8, and CO at week 40. Additionally, a rise of 10 μg/m3 in PM10 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 NOX and NO increased the risk of syndactyly, peaking at week 0 for both pollutants. Finally, increments of 10 μg/m3 in NO2, NOX, NO, and PM10 were all significantly associated with an increased risk of cleft lip and/or palate, peaking at week 3 for NO2, NOX, NO, and PM10. 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.DiscussionExposure to pollutants during pregnancy increases the risk of birth defects in newborns, especially SO2, PM10, PM2.5 and O3. 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. |
| format | Article |
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| publishDate | 2025-04-01 |
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| spelling | doaj-art-9a3d35c6832e4c9ea5c5ae35c0e9fe8f2025-08-20T02:08:31ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-04-011310.3389/fpubh.2025.15624611562461Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear modelWen Sun0Qingqing Dong1Yingying Zhang2Hui Wang3Youqiang Wang4Wenjie Yuan5Leyao Wang6Xianhong Shi7Yuhong Feng8Haiwei Wang9Xiaodan Wang10Yingbin Ren11Lihong Wang12Lijian Lei13Wenxia Song14Department of Epidemiology, School of Public Health, Shanxi Medical University, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, NHC Key Laboratory of Pneumoconiosis, MOE Key Laboratory of Coal Environmental, Taiyuan, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, NHC Key Laboratory of Pneumoconiosis, MOE Key Laboratory of Coal Environmental, Taiyuan, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, NHC Key Laboratory of Pneumoconiosis, MOE Key Laboratory of Coal Environmental, Taiyuan, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, NHC Key Laboratory of Pneumoconiosis, MOE Key Laboratory of Coal Environmental, Taiyuan, Shanxi, ChinaChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, ChinaIntroductionAs 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.MethodsBD 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‰.ResultsOur findings indicate that exposure to air pollutants during early and mid-pregnancy elevated the risk of BDs. Specifically, for each 10 μg/m3 increase of SO2, NO2, PM10, PM2.5, O3, and CO, the risk of congenital heart defects (CHDs) increased. Peaking at specific gestational weeks: SO2 at week 17, NO2 at week 23, PM10 at week 21, PM2.5 at week 16, O3 at week 8, and CO at week 40. Additionally, a rise of 10 μg/m3 in PM10 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 NOX and NO increased the risk of syndactyly, peaking at week 0 for both pollutants. Finally, increments of 10 μg/m3 in NO2, NOX, NO, and PM10 were all significantly associated with an increased risk of cleft lip and/or palate, peaking at week 3 for NO2, NOX, NO, and PM10. 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.DiscussionExposure to pollutants during pregnancy increases the risk of birth defects in newborns, especially SO2, PM10, PM2.5 and O3. 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.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1562461/fullair pollutionBDsdistribution lag non-linear modellagexpose |
| spellingShingle | Wen Sun Qingqing Dong Yingying Zhang Hui Wang Youqiang Wang Wenjie Yuan Leyao Wang Xianhong Shi Yuhong Feng Haiwei Wang Xiaodan Wang Yingbin Ren Lihong Wang Lijian Lei Wenxia Song Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model Frontiers in Public Health air pollution BDs distribution lag non-linear model lag expose |
| title | Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model |
| title_full | Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model |
| title_fullStr | Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model |
| title_full_unstemmed | Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model |
| title_short | Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model |
| title_sort | evidence of the correlation between air pollution and different types of birth defects based on a distribution lag non linear model |
| topic | air pollution BDs distribution lag non-linear model lag expose |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1562461/full |
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