Evidence map›Paper›PMID 40018530›Full record

ArticleBMJ public health2024

Contribution of county-level socioeconomic indicators to racial or ethnic differences in neonatal anthropometry in the USA: a prospective cohort study.

Jessica L Gleason, Calvin Lambert, Zhen Chen, Kathryn A Wagner, Pauline Mendola, Marion Ouidir, William A Grobman, Roger Newman, Fasil Tekola-Ayele, Katherine L Grantz

Abstract read
In one paragraph

Article in BMJ public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Jessica L GleasonEpidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.ORCID 0000-0001-9877-7931
Calvin LambertDepartment of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Zhen ChenBiostatistics and Bioinformatics Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.
Kathryn A WagnerEpidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.
Pauline MendolaDepartment of Epidemiology and Environmental Health, University at Buffalo, Buffalo, New York, USA.
Marion OuidirInstitute for Advanced Biosciences, Inserm(U1209)-CNRS-Univ Grenoble Alpes, La tronche, France.ORCID 0000-0001-6027-1484
William A GrobmanDepartment of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio, USA.
Roger NewmanDepartment of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, South Carolina, USA.
Fasil Tekola-AyeleEpidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.
Katherine L GrantzEpidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.

Funding

Intramural NIH HHS Z99 HD999999NICHD NIH HHS HHSN275200800002CNICHD NIH HHS HHSN275200800002INICHD NIH HHS HHSN275200800003CNICHD NIH HHS HHSN275200800003INICHD NIH HHS HHSN275200800012CNICHD NIH HHS HHSN275200800013CNICHD NIH HHS HHSN275200800014CNICHD NIH HHS HHSN275200800028CNICHD NIH HHS HHSN275200800031CNICHD NIH HHS HHSN275201000009C
6 · The paper itself

Abstract

Introduction: Racial and ethnic differences in fetal growth and birth size in the USA have not been adequately explained by individual-level socioeconomic status (SES) factors. We explored whether differences may be partially explained by county-level indicators of SES. Methods: We linked participant zip codes from the National Institute of Child Health and Human Development Fetal Growth Studies (2009-2013; n=1614) to county-level US census data to calculate a neighbourhood deprivation index, education isolation index and two indices of segregation: racial isolation and evenness. Using causal mediation methods, we evaluated the extent to which racial/ethnic differences in neonatal anthropometrics could be eliminated in a hypothetical setting where everyone lived in counties with high resource availability and racial/ethnic integration. Results: Setting racial evenness to levels consistent with the highest diversity eliminated 79.9% of the difference in birth weight between non-Hispanic White and non-Hispanic Black and all the difference (106.3%) in birth weight between Hispanic and non-Hispanic White individuals. Setting racial evenness, racial isolation and education isolation to levels consistent with higher diversity and education was also associated with similar reductions in differences for other anthropometric measures. Conclusions: Our findings suggest that, in a hypothetical scenario where everyone lived in counties with low deprivation or segregation, race/ethnic differences in neonatal anthropometry may substantially decrease or be eliminated. Our results also highlight the importance of considering community-level and structural factors in analyses of race/ethnic health disparities.

Indexed as

EpidemiologyPublic HealthSociodemographic Factors

Identifiers

PMID40018530
PMCPMC11816393

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