Evidence map›Paper›PMID 36689262›Full record

ArticleJMIR public health and surveillance2023

Risk of De Novo Hypertensive Disorders of Pregnancy After Exposure to PM1 and PM2.5 During the Period From Preconception to Delivery: Birth Cohort Study.

Zhichao Yuan, Hai-Jun Wang, Qin Li, Tao Su, Jie Yang, Junjun Chen, Yuanzhou Peng, Shuang Zhou, Heling Bao, Shusheng Luo and 5 more

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 23% of its field
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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. 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

15 authors at 4 institutions in 3 countries.

Zhichao Yuan *Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0002-1264-3084
Hai-Jun Wang *Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0003-0849-2903
Qin LiDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0002-8633-8859
Tao SuTongzhou Maternal and Child Health Care Hospital of Beijing, Beijing, China.ORCID 0000-0001-6311-0707
Jie YangTongzhou Maternal and Child Health Care Hospital of Beijing, Beijing, China.ORCID 0000-0003-0438-0963
Junjun ChenDepartment of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0002-3783-6085
Yuanzhou PengDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0001-8848-4908
Shuang ZhouDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0003-0387-5489
Heling BaoDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0003-3538-0245
Shusheng LuoDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0003-4796-4985
Hui WangDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0002-7639-5702
Jue LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.ORCID 0000-0002-1938-9365
Na HanTongzhou Maternal and Child Health Care Hospital of Beijing, Beijing, China.ORCID 0000-0002-2356-0882
Yuming GuoDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0000-0002-1766-6592
Yuelong JiDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.ORCID 0000-0001-6901-5030
Peking University · CNChongqing Maternal and Child Health Hospital · CNJohns Hopkins University · USMonash University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParticulate matter (PM) is detrimental to the respiratory and circulatory systems. However, no study has evaluated the lag effects of weekly exposure to fine PM during the period from preconception to delivery on the risk of hypertensive disorders of pregnancy (HDPs).

objectiveWe set out to investigate the lag effect windows of PM on the risk of HDPs on a weekly scale.

methodsData from women with de novo HDPs and normotensive pregnant women who were part of the Peking University Retrospective Birth Cohort, based on the hospital information system of Tongzhou district, were obtained for this study. Meteorological data and data on exposure to fine PM were predicted by satellite remote sensing data based on maternal residential address. The de novo HDP group consisted of pregnant women who were diagnosed with gestational hypertension or preeclampsia. Fine PM was defined as PM

resultsA total of 22,570 pregnant women (mean age 29.1 years) for whom data were available between 2013 and 2017 were included in this study. The prevalence of de novo HDPs was 6.7% (1520/22,570). Our findings showed that PM

conclusionsExposure to PM

Indexed as

Air PollutantsHypertension, Pregnancy-InducedAdultCohort StudiesFemaleHumansMaternal ExposureParticulate MatterPregnancyRetrospective StudiesAir PollutantsParticulate Matterair pollutionexposurehypertensionhypertensive disordershypertensive disorders of pregnancylag effectmaternal healthperinatal healthPM1PM2.5pollutantspollutionpreconceptional periodpregnancyrisk

Identifiers

PMID36689262
PMCPMC9903185
OpenAlexW4312994148

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.