Evidence map›Paper›PMID 40270732›Full record

ArticleFrontiers in public health2025

Evidence of the correlation between air pollution and different types of birth defects: based on a distribution-lag non-linear model.

Wen Sun, Qingqing Dong, Yingying Zhang, Hui Wang, Youqiang Wang, Wenjie Yuan, Leyao Wang, Xianhong Shi, Yuhong Feng, Haiwei Wang and 5 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Wen Sun *Department 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, China.
Qingqing Dong *Changzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Yingying ZhangDepartment 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, China.
Hui WangChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Youqiang WangChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Wenjie YuanChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Leyao WangDepartment 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, China.
Xianhong ShiChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Yuhong FengChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Haiwei WangChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Xiaodan WangChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Yingbin RenChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Lihong WangChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.
Lijian LeiDepartment 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, China.
Wenxia SongChangzhi Maternal and Child Health Care Hospital, Changzhi City Key Laboratory of Birth Defect Prevention and Control, Changzhi, Shanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 Discussion: Exposure to pollutants during pregnancy increases the risk of birth defects in newborns, especially SO

Indexed as

Air PollutantsAir PollutionCongenital AbnormalitiesEnvironmental ExposureMaternal ExposureChinaFemaleHumansInfant, NewbornNonlinear DynamicsParticulate MatterPregnancyAir PollutantsParticulate Matterair pollutionBDsdistribution lag non-linear modelexposelag

Identifiers

PMID40270732
PMCPMC12014725

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.