Evidence map›Paper›PMID 39164399›Full record

ArticleScientific reports2024

Community level factors and racial inequities in delivery hospitalizations involving severe maternal morbidity in the United States, 2016-2019.

Mechelle D Claridy, Natalie Hernandez-Green, Stephen L Rathbun, José F Cordero

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In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mechelle D ClaridyDepartment of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, 30602, Athens, Georgia. mechelle.claridy@uga.edu.
Natalie Hernandez-GreenCenter for Maternal Health Equity, Morehouse School of Medicine, 720 Westview Drive, Atlanta, Georgia.
Stephen L RathbunDepartment of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, 30602, Athens, Georgia.
José F CorderoDepartment of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, 30602, Athens, Georgia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to evaluate the racial and ethnic disparities in delivery hospitalizations involving severe maternal morbidity (SMM) by location of residence and community income. We used the 2016 to 2019 Healthcare Cost and Utilization Project National Inpatient Sample. International Classification of Diseases, Tenth Revision, Clinical Modification codes were used to identify delivery hospitalizations with SMM. Using logistic regression models, we examined the association between race and ethnicity and delivery hospitalizations involving SMM. In adjusted analyses, the models were stratified by location of residence and community income and adjusted for patient and hospital characteristics. In rural areas, non-Hispanic Black women (AOR 1.50; 95% CI 1.25-1.79) and women of other races (AOR 1.32; 95% CI 1.03-1.69) had an increased odds of experiencing a delivery hospitalization involving SMM when compared to non-Hispanic White women. In micropolitan areas, non-Hispanic Black women (AOR 1.88; 95% CI 1.79-1.97), non-Hispanic Asian/Pacific Islander women (AOR 1.54; 95% CI 1.16-2.05), and women of other races (AOR 1.31; 95% CI 1.03-1.67) had an increased odds of experiencing a delivery hospitalization involving SMM when compared to non-Hispanic White women. Non-Hispanic Black women also had increased odds of experiencing a delivery hospitalization involving SMM in communities with the lowest income (quartile 1) (AOR 1.59; 95% CI 1.49-1.66), middle income (quartiles 2 and 3) (AOR 1.81; 95% CI 1.72-1.91), and highest income (AOR 2.09; 95% CI 1.90-2.29) when compared to non-Hispanic White women. We found that location of residence and community income are associated with racial and ethnic differences in SMM in the United States. These factors, outside of individual factors assessed in previous studies, provide a better understanding of some of the structural and systemic factors that may contribute to SMM.

Indexed as

Healthcare DisparitiesHospitalizationAdolescentAdultDelivery, ObstetricEthnicityFemaleHumansMorbidityPregnancyPregnancy ComplicationsRacial GroupsSocioeconomic FactorsUnited StatesYoung AdultDisparitiesMaternal mortalityMaternal outcomesNISPregnancySevere maternal morbiditySocial determinants of healthStructural determinants of health

Identifiers

PMID39164399
PMCPMC11336213

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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.