Evidence map›Paper›PMID 26581753›Full record

SynthesisBMC pregnancy and childbirth2015

The association between fine particulate matter exposure during pregnancy and preterm birth: a meta-analysis.

Xiaoli Sun, Xiping Luo, Chunmei Zhao, Rachel Wai Chung Ng, Chi Eung Danforn Lim, Bo Zhang, Tao Liu

Abstract readMeta-Analysis
In one paragraph

Synthesis in BMC pregnancy and childbirth, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 9 pooled it
–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

49 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Maternal fine particulate matter (PMEnvironmental science and pollution research international · 2019
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  10. Review
  11. Association between ambient PMFrontiers in public health · 2026
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  14. Review
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  19. Air Pollution and Birth Outcomes: Health Impact and Economic Value Assessment in Spain.International journal of environmental research and public health · 2023
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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

7 authors.

Xiaoli SunGynecology Department, Guangdong Women and Children Hospital, No. 521, Xingnan Road, Panyu District, Guangzhou, 511442, China. sxl1390@126.com.
Xiping LuoGynecology Department, Guangdong Women and Children Hospital, No. 521, Xingnan Road, Panyu District, Guangzhou, 511442, China. luoxiping07@aliyun.com.
Chunmei ZhaoGynecology Department, Guangdong Women and Children Hospital, No. 521, Xingnan Road, Panyu District, Guangzhou, 511442, China. 1093413164@qq.com.
Rachel Wai Chung NgSydney South West Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia. rachelwcng@gmail.com.
Chi Eung Danforn LimSydney South West Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia. limdanforn@gmail.com.
Bo ZhangDepartment of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China. zhangb65@mail.sysu.edu.cn.
Tao LiuGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, No. 160, Qunxian Road, Panyu District, Guangzhou, 511430, China. gztt_2002@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough several previous studies have assessed the association of fine particulate matter (PM2.5) exposure during pregnancy with preterm birth, the results have been inconsistent and remain controversial. This meta-analysis aims to quantitatively summarize the association between maternal PM2.5 exposure and preterm birth and to further explore the sources of heterogeneity in findings on this association.

methodsWe searched for all studies published before December 2014 on the association between PM2.5 exposure during pregnancy and preterm birth in the MEDLINE, PUBMED and Embase databases as well as the China Biological Medicine and Wanfang databases. A pooled OR for preterm birth in association with each 10 μg/m(3) increase in PM2.5 exposure was calculated by a random-effects model (for studies with significant heterogeneity) or a fixed-effects model (for studies without significant heterogeneity).

resultsA total of 18 studies were included in this analysis. The pooled OR for PM2.5 exposure (per 10 μg/m(3) increment) during the entire pregnancy on preterm birth was 1.13 (95% CI = 1.03-1.24) in 13 studies with a significant heterogeneity (Q = 80.51, p < 0.001). The pooled ORs of PM2.5 exposure in the first, second and third trimester were 1.08 (95% CI = 0.92-1.26), 1.09 (95% CI = 0.82-1.44) and 1.08 (95% CI = 0.99-1.17), respectively. The corresponding meta-estimates of PM2.5 effects in studies assessing PM2.5 exposure at individual, semi-individual and regional level were 1.11 (95% CI = 0.89-1.37), 1.14 (95% CI = 0.97-1.35) and 1.07 (95% CI = 0.94-1.23). In addition, significant meta-estimates of PM2.5 exposures were found in retrospective studies (OR = 1.10, 95% CI = 1.01-1.21), prospective studies (OR = 1.42, 95% CI = 1.08-1.85), and studies conducted in the USA (OR = 1.16, 95 % CI = 1.05-1.29).

conclusionsMaternal PM2.5 exposure during pregnancy may increase the risk of preterm birth,but significant heterogeneity was found between studies. Exposure assessment methods, study designs and study settings might be important sources of heterogeneity, and should be taken into account in future meta-analyses.

Indexed as

Air PollutionFemaleHumansInfant, NewbornMaternal ExposureParticulate MatterPregnancyPregnancy ComplicationsPremature BirthProspective StudiesRetrospective StudiesParticulate Matter

Identifiers

PMID26581753
PMCPMC4650291

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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.