Evidence map›Paper›PMID 24838804›Full record

ArticleAmerican journal of epidemiology2014

Passive smoking and preterm birth in urban China.

Jie Qiu, Xiaochun He, Hongmei Cui, Chong Zhang, Honghong Zhang, Yun Dang, Xudong Han, Ya Chen, Zhongfeng Tang, Hanru Zhang and 22 more

Abstract read
In one paragraph

Article in American journal of epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 5 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

51 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  16. Secondhand Smoking and the Fetus: A Bibliometric Analysis.Medical journal of the Islamic Republic of Iran · 2023
    Article
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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

32 authors.

Jie Qiu
Xiaochun He
Hongmei Cui
Chong Zhang
Honghong Zhang
Yun Dang
Xudong Han
Ya Chen
Zhongfeng Tang
Hanru Zhang
Haiya Bai
Ruifeng Xu
Daling Zhu
Xiaojuan Lin
Ling Lv
Xiaoying Xu
Ru Lin
Tingting Yao
Jie Su
Xiaohui Liu
Wendi Wang
Yueyuan Wang
Bin Ma
Sufen Liu
Huang Huang
Catherine Lerro
Nan Zhao
Jiaxin Liang
Shuangge Ma
Richard A Ehrenkranz
Qing Liu
Yawei Zhang

Funding

Air pollution and fetal growth in ChinaK02HD070324 · NICHD · YALE UNIVERSITY · PI ZHANG, YAWEI · 2011 to 2015
$582k
NICHD NIH HHS K02 HD070324NICHD NIH HHS K02HD70324
6 · The paper itself

Abstract

Studies investigating the relationship between maternal passive smoking and the risk of preterm birth have reached inconsistent conclusions. A birth cohort study that included 10,095 nonsmoking women who delivered a singleton live birth was carried out in Lanzhou, China, between 2010 and 2012. Exposure to passive smoking during pregnancy was associated with an increased risk of very preterm birth (<32 completed weeks of gestation; odds ratio = 1.98, 95% confidence interval: 1.41, 2.76) but not moderate preterm birth (32-36 completed weeks of gestation; odds ratio = 0.98, 95% confidence interval: 0.81, 1.19). Risk of very preterm birth increased with the duration of exposure (P for trend = 0.0014). There was no variability in exposures by trimester. The associations were consistent for both medically indicated and spontaneous preterm births. Overall, our findings support a positive association between passive smoking and the risk of very preterm birth.

Indexed as

AdolescentAdultChinaEducational StatusFemaleGestational AgeHumansInfant, NewbornMaleMaternal AgeParityPregnancyPremature BirthRisk FactorsSurveys and QuestionnairesTobacco Smoke PollutionTobacco Smoke Pollutionbirth cohortChinapassive smokingpreterm birth

Identifiers

PMID24838804
PMCPMC4070933

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.