Evidence map›Paper›PMID 33088625›Full record

ArticlePeerJ2020

Association of pre-pregnancy body mass index with adverse pregnancy outcome among first-time mothers.

Li Li, Yanhong Chen, Zhifeng Lin, Weiyan Lin, Yangqi Liu, Weilin Ou, Chengli Zeng, Li Ke

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-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, 13 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Li Li *Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Yanhong Chen *Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Zhifeng LinDepartment of Medical Record, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Weiyan LinDepartment of Medical Record, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Yangqi LiuDepartment of Medical Record, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Weilin OuDepartment of Medical Record, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Chengli ZengDepartment of Medical Record, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Li KeDepartment of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Guangzhou Medical University · CNThird Affiliated Hospital of Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStudies have reported an increased risk of adverse pregnancy outcome associated with pre-pregnancy body mass index (BMI). However, the data on such associations in urban areas of southern Chinese women is limited, which drive us to clarify the associations of pre-pregnancy BMI and the risks of adverse pregnancy outcomes (preterm birth (PTB) and low birth weight (LBW)) and maternal health outcomes (gestational hypertension and cesarean delivery).

methodsWe performed a hospital-based case-control study including 3,864 Southern Chinese women who gave first birth to a live singleton infant from January 2015 to December 2015. PTB was stratified into three subgroups according to gestational age (extremely PTB, very PTB and moderate PTB). Besides, we combined birth weight and gestational age to dichotomise as being small for gestational age (SGA, less than the tenth percentile of weight for gestation) and non-small for gestational age (NSGA, large than the tenth percentile of weight for gestation), gestational week was also classified into categories of term, 34-36 week and below 34 week.. We then divided newborns into six groups: (1) term and NSGA; (2) 34-36 week gestation and NSGA; (3) below 34 week gestation and NSGA; (4) term and SAG; (5) 34-36 week gestation and SAG; (6) below 34 week gestation and SAG. Adjusted logistic regression models was used to estimate the odds ratios of adverse outcomes.

resultsUnderweight women were more likely to give LBW (AOR = 1.44, 95% CI [1.11-1.89]), the similar result was seen in term and SAG as compared with term and NSAG (AOR = 1.78, 95% CI [1.45-2.17]), whereas underweight was significantly associated with a lower risk of gestational hypertension (AOR = 0.45, 95% CI [0.25-0.82) and caesarean delivery (AOR = 0.74, 95% CI [0.62-0.90]). The risk of extremely PTB is relatively higher among overweight and obese mothers in a subgroup analysis of PTB (AOR = 8.12, 95% CI [1.11-59.44]; AOR = 15.06, 95% CI [1.32-172.13], respectively). Both maternal overweight and obesity were associated with a greater risk of gestational hypertension (AOR = 1.71, 95% CI [1.06-2.77]; AOR = 5.54, 95% CI [3.02-10.17], respectively) and caesarean delivery (AOR = 1.91, 95% CI [1.53-2.38]; AOR = 1.85, 95% CI [1.21-2.82], respectively).

conclusionsOur study suggested that maternal overweight and obesity were associated with a significantly higher risk of gestational hypertension, caesarean delivery and extremely PTB. Underweight was correlated with an increased risk of LBW and conferred a protective effect regarding the risk for gestational hypertension and caesarean delivery for the first-time mothers among Southern Chinese.

Indexed as

BMICaesarean deliveryGestational hypertensionLow birth weightPregnancy outcomePreterm birth

Identifiers

PMID33088625
PMCPMC7568476
OpenAlexW3093139201

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.