Evidence map›Paper›PMID 38178112›Full record

SynthesisBMC medicine2024

Maternal pre-pregnancy body mass index and risk of preterm birth: a collaboration using large routine health datasets.

R P Cornish, M C Magnus, S K Urhoj, G Santorelli, L G Smithers, D Odd, A Fraser, S E Håberg, A M Nybo Andersen, K Birnie and 3 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
23.9field-weighted citation impact, top 1% 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.

  1. FIGO good practice recommendations on preconception care: A strategy to prevent preterm birth.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
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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 6 institutions in 4 countries.

R P CornishPopulation Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Road, Bristol, BS8 2BN, UK. rosie.cornish@bristol.ac.uk.ORCID 0000-0002-2874-7646
M C MagnusCentre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
S K UrhojDepartment of Public Health, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
G SantorelliBradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.
L G SmithersSchool of Public Health, University of Adelaide, Adelaide, Australia.
D OddDivision of Population Medicine, Cardiff University School of Medicine, Cardiff, UK.
A FraserPopulation Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Road, Bristol, BS8 2BN, UK.
S E HåbergCentre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
A M Nybo AndersenDepartment of Public Health, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
K BirniePopulation Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Road, Bristol, BS8 2BN, UK.
J W LynchPopulation Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Road, Bristol, BS8 2BN, UK.
K Tilling *Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Road, Bristol, BS8 2BN, UK.
D A Lawlor *Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Road, Bristol, BS8 2BN, UK.
University of Bristol · GBNorwegian Institute of Public Health · NOUniversity of Copenhagen · DKBradford Royal Infirmary · GBCardiff University · GBUniversity of Wollongong · AU

Funding

British Heart Foundation AA/18/1/34219British Heart Foundation CH/F/20/90003British Heart Foundation PG/19/21/34190European Research Council 669545Medical Research Council MC_PC_21038Medical Research Council MC_UU_00011/3Medical Research Council MC_UU_00011/6Medical Research Council MC_UU_00032/2Medical Research Council MR/N024397/1
6 · The paper itself

Abstract

backgroundPreterm birth (PTB) is a leading cause of child morbidity and mortality. Evidence suggests an increased risk with both maternal underweight and obesity, with some studies suggesting underweight might be a greater factor in spontaneous PTB (SPTB) and that the relationship might vary by parity. Previous studies have largely explored established body mass index (BMI) categories. Our aim was to compare associations of maternal pre-pregnancy BMI with any PTB, SPTB and medically indicated PTB (MPTB) among nulliparous and parous women across populations with differing characteristics, and to identify the optimal BMI with lowest risk for these outcomes.

methodsWe used three UK datasets, two USA datasets and one each from South Australia, Norway and Denmark, together including just under 29 million pregnancies resulting in a live birth or stillbirth after 24 completed weeks gestation. Fractional polynomial multivariable logistic regression was used to examine the relationship of maternal BMI with any PTB, SPTB and MPTB, among nulliparous and parous women separately. The results were combined using a random effects meta-analysis. The estimated BMI at which risk was lowest was calculated via differentiation and a 95% confidence interval (CI) obtained using bootstrapping.

resultsWe found non-linear associations between BMI and all three outcomes, across all datasets. The adjusted risk of any PTB and MPTB was elevated at both low and high BMIs, whereas the risk of SPTB was increased at lower levels of BMI but remained low or increased only slightly with higher BMI. In the meta-analysed data, the lowest risk of any PTB was at a BMI of 22.5 kg/m

conclusionsConsistency of findings across different populations, despite differences between them in terms of the time period covered, the BMI distribution, missing data and control for key confounders, suggests that severe under- and overweight may play a role in PTB risk.

Indexed as

Body Mass IndexPremature BirthFemaleHumansInfant, NewbornObesityParityPregnancyRisk FactorsThinnessBody mass indexMaternalNon-linearParityPre-pregnancyPreterm birth

Identifiers

PMID38178112
PMCPMC10768428
OpenAlexW4390599261

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.