Evidence map›Paper›PMID 33828166›Full record

ArticleScientific reports2021

Assessing the relationship between pregravid body mass index and risk of adverse maternal pregnancy and neonatal outcomes: prospective data in Southwest China.

Yue Chen, Ke Wan, Yunhui Gong, Xiao Zhang, Yi Liang, Xiaoyu Wang, Ping Feng, Fang He, Rong Zhou, Dagang Yang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Artificial Intelligence in Gestational Diabetes Care: A Systematic Review.Journal of diabetes science and technology · 2025
    Review
  6. Article
  7. Risk Factors for Gestational Diabetes Mellitus in Mainland China: A Systematic Review and Meta-Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. 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

13 authors at 5 institutions in 2 countries.

Yue ChenWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People's Republic of China.
Ke WanGraduate School of Information Science and Technology, Hokkaido University, Hokkaido, Japan.
Yunhui GongWest China Women's and Children's Hospital, Sichuan University, Chengdu, People's Republic of China.
Xiao ZhangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People's Republic of China.
Yi LiangDepartment of Clinical Nutrition, Affiliated Hospital of Guizhou Medical University, Guiyang, People's Republic of China.
Xiaoyu WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People's Republic of China.
Ping FengWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People's Republic of China.
Fang HeWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People's Republic of China.
Rong ZhouWest China Women's and Children's Hospital, Sichuan University, Chengdu, People's Republic of China.
Dagang YangDepartment of Clinical Nutrition, Affiliated Hospital of Guizhou Medical University, Guiyang, People's Republic of China.
Hong JiaDepartment of Epidemiology and Biostatistics, School of Public Health, Southwest Medical University, Luzhou, People's Republic of China.
Guo ChengLaboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, No.16, Section 3, Renmin Nan Road, Chengdu, 610041, Sichuan, People's Republic of China. gcheng@scu.edu.cn.
Toshio ShimokawaDepartment of Medical Data-Science, Graduate School of Medicine, Wakayama Medical University, Wakayama, Japan.
Sichuan University · CNGuiyang Medical University · CNHokkaido Information University · JPSouthwest Medical University · CNWakayama Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relevance of pregestational body mass index (BMI) on adverse pregnancy outcomes remained unclear in Southwest China. This study aimed to investigate the overall and age-category specific association between pre-gestational BMI and gestational diabetes mellitus (GDM), preeclampsia, cesarean delivery, preterm delivery, stillbirth, macrosomia, and small-for-gestational age (SGA) or large-for-gestational age (LGA) neonates in Southwest China. Furthermore, it explores the relative importance of influence of pregravid BMI and maternal age on pregnancy outcomes. 51,125 Chinese singleton pregnant women were recruited as study subjects. Multiple logistic regression models were used to examine the influence of pre-pregnancy BMI on adverse pregnancy outcomes. Gradient boosting machine was used to evaluate the relative importance of influence of pregravid BMI and maternal age on pregnancy outcomes. It is found that women who were overweight or obese before pregnancy are at higher risk of adverse pregnancy outcomes except for SGA neonates, while pre-pregnancy underweight is a protective factor for GDM, preeclampsia, cesarean delivery, macrosomia and LGA, but not SGA. Younger mothers are more susceptible to GDM and macrosomia neonates, while older mothers are more prone to preeclampsia. Pre-pregnancy BMI has more influence on various pregnancy outcomes than maternal age. To improve pregnancy outcomes, normal BMI weight as well as relatively young maternal ages are recommended for women in child-bearing age.

Indexed as

Body Mass IndexAdultAsian PeopleCesarean SectionChinaDiabetes, GestationalFemaleFetal MacrosomiaHumansInfant, Small for Gestational AgeMaternal AgeMiddle AgedObesityOverweightPre-EclampsiaPregnancy

Identifiers

PMID33828166
PMCPMC8027183
OpenAlexW3148642098

What OpenQuestion holds

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LicenceCC BY
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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.