Evidence map›Paper›PMID 41160387›Full record

SynthesisMaternal and child health journal2025

The Effects of Air Pollutants on Antenatal and Postpartum Depression: A Systematic Review and Meta-Analysis.

Zhanhong Fan, Ziyi Yang, Li Sun, Zhiqiu Cao, Feng Zhang

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Maternal and child health journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Zhanhong FanSchool of Nursing and Rehabilitation, Nantong University, Nantong City, Jiangsu Province, China.
Ziyi YangSchool of Nursing and Rehabilitation, Nantong University, Nantong City, Jiangsu Province, China.
Li SunSchool of Nursing and Rehabilitation, Nantong University, Nantong City, Jiangsu Province, China.
Zhiqiu CaoSchool of Nursing and Rehabilitation, Nantong University, Nantong City, Jiangsu Province, China.
Feng ZhangSchool of Nursing and Rehabilitation, Nantong University, Nantong City, Jiangsu Province, China. zhangfeng820909@163.com.ORCID http://orcid.org/0000-0003-4798-5145

Funding

National Natural Science Foundation of China 72274100Postgraduate Research & Practice Innovation Program of Jiangsu Province KYCX24_3590
6 · The paper itself

Abstract

aimsThis meta-analysis aimed to investigate the association between maternal depression and exposure to air pollution. REVIEW

methodsA meta-analysis following PRISMA methodology was conducted to examine the association between maternal depression and exposure to air pollution. From inception to February 2025, five online databases (PubMed, Cochrane Library, Web of Science, Embase, and PsycINFO) were used to search studies. Summary estimates with 95% confidence intervals were calculated to assess the correlation between each pollutant and the risk of depression. We aggregated the cumulative estimates were pooled using random-effects models. To evaluate within-study heterogeneity, Cochran's Q test and I

resultsThe analysis revealed distinct associations between various air pollutants and depression. While no significant correlation was found for CO, PM

conclusionsThis meta-analysis highlights air pollution as a potential risk factor for maternal depression, revealing variations in risk across different pollutants. These findings emphasize the importance of tailored interventions and the need for further research to gain a deeper understanding and effectively address the impact of air pollution on maternal mental health.

Indexed as

Air PollutantsAir PollutionDepressionDepression, PostpartumFemaleHumansPregnancyRisk FactorsAir PollutantsAir pollutionMaternal depressionMaternal mental healthMeta-analysis

Identifiers

What OpenQuestion holds

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Registered trials

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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.