Evidence map›Paper›PMID 40081169›Full record

ArticleSocial science & medicine (1982)2025

Using spatial Bayesian models to estimate associations between structural racial discrimination and disparities in severe maternal morbidity.

Jasmin A Darville, Katherine Campbell, Kaitlyn K Stanhope, Alexis Kendall, Sierra Carter, Michael R Kramer, Ran Zhang, Sheree L Boulet

Abstract read
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Article in Social science & medicine (1982), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Jasmin A DarvilleGangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Katherine CampbellDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Kaitlyn K StanhopeDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Alexis KendallFlorida State University College of Medicine, Florida State University, Tallahassee, FL, USA.
Sierra CarterDepartment of Psychology, Georgia State University, Atlanta, GA, USA.
Michael R KramerCenter for Rural Health and Health Disparities, Mercer University School of Medicine, Macon, GA, USA.
Ran ZhangDepartment of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA.
Sheree L BouletDepartment of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA. Electronic address: sboulet@emory.edu.

Funding

Multidisciplinary Research Training to Reduce Inequities in Cardiovascular HealthT32HL130025 · NHLBI · EMORY UNIVERSITY · PI Tené T Lewis, Viola Vaccarino · 2016 to 2026
$6.4M
Investigating structural maternal health inequities among Black reproductive aged women in Georgia; a mixed methods and multi-level approachR01HD109005 · NICHD · EMORY UNIVERSITY · PI Sheree L Boulet · 2022 to 2026
$2.2M
NHLBI NIH HHS T32 HL130025NICHD NIH HHS R01 HD109005
6 · The paper itself

Abstract

introductionThe United States maternal health crisis is especially profound in Georgia, disproportionately affecting Black birthing people. In Georgia, 35% of all births are to Black-identifying people, with rates of severe maternal morbidity (SMM) significantly exceeding national averages.

methodsThe sample population comprised Georgia linked live birth/fetal death certificate and hospital discharge data for deliveries from 2013 to 2021. Structural racial discrimination (SRD) was defined at the county level using four domains. We estimated county-specific rates of SMM using Bayesian conditional autoregressive Poisson models and compared the rate difference in SMM for Black versus white birthing people across domain-specific strata of SRD.

resultsThe sample included 709,335 deliveries to Black and white birthing people. The prevalence of SMM was higher among births to Black individuals compared to white counterparts (3.2% vs. 1.7%), with a mean risk difference of 13.1 per 1000 deliveries between race groups. Results of the SRD-SMM regression demonstrated larger Black-white racial disparities in counties with the highest concentration of resource deprivation compared to the highest concentration of affluence (B: 4.5, 95% CI: 1.1, 8.0). Similarly, in counties with a greater polarization of Black and low-income residents, the disparity was larger compared to counties with greater racial and income homogeneity (B: 3.84, 95% CI: 0.22, 7.44).

conclusionsOur results highlight the nuanced relationship between structural racism and health outcomes in Georgia. SMM rates were higher among Black birthing people compared to their white counterparts.

Indexed as

Health Status DisparitiesRacismAdultBayes TheoremBlack or African AmericanFemaleGeorgiaHumansMorbidityPregnancySpatial AnalysisWhiteHealth disparitiesPregnancySevere maternal morbiditySpatial analysisStructural racism

Identifiers

PMID40081169
PMCPMC11963244

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