Evidence map›Paper›PMID 38689215›Full record

ArticleBMC pregnancy and childbirth2024

Social inequalities in pregnancy metabolic profile: findings from the multi-ethnic Born in Bradford cohort study.

Ahmed Elhakeem, Gemma L Clayton, Ana Goncalves Soares, Kurt Taylor, Léa Maitre, Gillian Santorelli, John Wright, Deborah A Lawlor, Martine Vrijheid

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 91% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

9 authors at 6 institutions in 2 countries.

Ahmed ElhakeemMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. a.elhakeem@bristol.ac.uk.
Gemma L ClaytonMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Ana Goncalves SoaresMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Kurt TaylorMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Léa MaitreISGlobal, Barcelona, Spain.
Gillian SantorelliBradford Institute for Health Research, Bradford Teaching Hospitals National Health Service Foundation Trust, Bradford, UK.
John WrightBradford Institute for Health Research, Bradford Teaching Hospitals National Health Service Foundation Trust, Bradford, UK.
Deborah A LawlorMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Martine VrijheidISGlobal, Barcelona, Spain.
University of Bristol · GBMRC Epidemiology Unit · GBBarcelona Institute for Global Health · ESBradford Teaching Hospitals NHS Foundation Trust · GBCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública · ESNational Health Service · GB

Funding

Horizon 2020 Framework Programme 101021566Horizon 2020 Framework Programme 874583Horizon 2020 Framework Programme 874739
6 · The paper itself

Abstract

backgroundLower socioeconomic position (SEP) associates with adverse pregnancy and perinatal outcomes and with less favourable metabolic profile in nonpregnant adults. Socioeconomic differences in pregnancy metabolic profile are unknown. We investigated association between a composite measure of SEP and pregnancy metabolic profile in White European (WE) and South Asian (SA) women.

methodsWe included 3,905 WE and 4,404 SA pregnant women from a population-based UK cohort. Latent class analysis was applied to nineteen individual, household, and area-based SEP indicators (collected by questionnaires or linkage to residential address) to derive a composite SEP latent variable. Targeted nuclear magnetic resonance spectroscopy was used to determine 148 metabolic traits from mid-pregnancy serum samples. Associations between SEP and metabolic traits were examined using linear regressions adjusted for gestational age and weighted by latent class probabilities.

resultsFive SEP sub-groups were identified and labelled 'Highest SEP' (48% WE and 52% SA), 'High-Medium SEP' (77% and 23%), 'Medium SEP' (56% and 44%) 'Low-Medium SEP' (21% and 79%), and 'Lowest SEP' (52% and 48%). Lower SEP was associated with more adverse levels of 113 metabolic traits, including lower high-density lipoprotein (HDL) and higher triglycerides and very low-density lipoprotein (VLDL) traits. For example, mean standardized difference (95%CI) in concentration of small VLDL particles (vs. Highest SEP) was 0.12 standard deviation (SD) units (0.05 to 0.20) for 'Medium SEP' and 0.25SD (0.18 to 0.32) for 'Lowest SEP'. There was statistical evidence of ethnic differences in associations of SEP with 31 traits, primarily characterised by stronger associations in WE women e.g., mean difference in HDL cholesterol in WE and SA women respectively (vs. Highest-SEP) was -0.30SD (-0.41 to -0.20) and -0.16SD (-0.27 to -0.05) for 'Medium SEP', and -0.62SD (-0.72 to -0.52) and -0.29SD (-0.40 to -0.20) for 'Lowest SEP'.

conclusionsWe found widespread socioeconomic differences in metabolic traits in pregnant WE and SA women residing in the UK. Further research is needed to understand whether the socioeconomic differences we observe here reflect pre-conception differences or differences in the metabolic pregnancy response. If replicated, it would be important to explore if these differences contribute to socioeconomic differences in pregnancy outcomes.

Indexed as

TriglyceridesWhite PeopleAdultCohort StudiesFemaleHumansLatent Class AnalysisLipoproteins, HDLLipoproteins, VLDLMetabolomePregnancySocial ClassSocioeconomic FactorsSouth Asian PeopleUnited KingdomYoung AdultLipoproteins, HDLLipoproteins, VLDLTriglyceridesEthnicityMetabolomicsPregnancySocioeconomic

Identifiers

PMID38689215
PMCPMC11061950
OpenAlexW4396559120

What OpenQuestion holds

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LicenceCC BY
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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.