Evidence map›Paper›PMID 26475596›Full record

ArticleBMC pregnancy and childbirth2015

Relationship between maternal obesity and prenatal, metabolic syndrome, obstetrical and perinatal complications of pregnancy in Indiana, 2008-2010.

Shingairai A Feresu, Yi Wang, Stephanie Dickinson

Abstract read
In one paragraph

Article 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 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Pathophysiology of Maternal Obesity and Hypertension in Pregnancy.Journal of cardiovascular development and disease · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Annals of translational medicine · 2020
    Article
  12. Article
  13. Article
  14. Observational
  15. Review
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

3 authors.

Shingairai A FeresuEpidemiology and Biostatistics Track, School of Health Systems and Public Health, University of Pretoria, 5-10 H.W. Snyman Building, 31 Bophelo Road, Gezina, 0031, Pretoria, South Africa. shinga.feresu@up.ac.za.
Yi WangDepartment of Statistics, Indiana University, Indiana Statistical Consulting Center, 309 N Park Ave, Bloomington, IN, 47405, USA. zephyrwang113@gmail.com.
Stephanie DickinsonDepartment of Statistics, Indiana University, Indiana Statistical Consulting Center, 309 N Park Ave, Bloomington, IN, 47405, USA. sd3@indiana.edu.

Funding

Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
NCATS NIH HHS UL1 TR001108
6 · The paper itself

Abstract

backgroundObesity is a serious medical condition affecting more than 30% of Indiana, and 25% of Unites States pregnant women. Obesity is related to maternal complications, and significantly impacts the health of pregnant women. The objective of this study was to describe the relationship between maternal complications and pre-pregnancy maternal weight.

methodsUsing logistic regression models, we analyzed 2008 to 2010 birth certificate data, for 255,773 live births abstracted from the Indiana Vital Statistics registry. We examined the risk of reproductive factors, obstetrical complications and perinatal (intrapartum) complications for underweight, healthy weight, overweight and obese women for this population.

resultsWomen who received prenatal care were more likely to be obese [adjusted odds ratio (AOR) = 1.82 (1.56-2.13)]. While women with parity of zero (0) were less likely to be obese [AOR = 0.89, 95% CI (0.86-0.91)]. Women giving birth to twins [AOR = 1.25, 95% CI (1.17- 1.33)], women delivering by Caesarian section [AOR = 2.31, 95% CI ( 2.26-2.37)], and women who previously had a Caesarian section [AOR = 1.95, 95% CI (1.88-2.02)] were more likely to be obese. There was evidence of metabolic like complication in this population, due to obesity. Obesity was significantly associated with obstetrical conditions of the metabolic syndrome, including pre-pregnancy diabetes, gestational diabetes, pre-pregnancy hypertension, pregnancy-induced hypertension and eclampsia [AOR = 5.12, 95% CI (4.47-5.85); AOR = 3.87, 95% CI (3.68-4.08); AOR = 7.66, 95% CI (6.77-8.65); AOR = 3.23, 95% CI (3.07-3.39); and AOR = 1.77, 95% CI (1.31-2.40), respectively. Maternal obesity modestly increased the risk of induction, epidural, post-delivery bleeding, and prolonged labor [AOR = 1.26, 95% CI (1.23-1.29); AOR = 1.15, 95% CI (1.13-1.18); AOR = 1.20, 95% CI (1.12-1.28); and AOR = 1.44, 95% CI (1.30-1.61)], respectively. Obese women were less likely to have blood transfusions [AOR = .74, 95% CI (0.58-96)], vaginal tears [AOR = 0.51, 95% CI (0.44-0.59)], or infections [AOR = 86, 95% CI (0.80-0.93)].

conclusionsOur results suggest that maternal obesity in Indiana, like other populations in the USA, is associated with high risks of maternal complications for pregnant women. Pre-pregnancy obesity prevention efforts should focus on targeting children, adolescent and young women, if the goal to reduce the risk of maternal complications related to obesity, is to be reached.

Indexed as

AdolescentAdultBody WeightCesarean SectionDelivery, ObstetricFemaleHumansIndianaMetabolic SyndromeObesityOdds RatioParityPregnancyPregnancy ComplicationsPregnancy OutcomeYoung Adult

Identifiers

PMID26475596
PMCPMC4609050

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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.