Applying distinct approaches to racial and ethnic classification to the surveillance of obstetric and neonatal outcomes in the U.S. military, 2010-2021.

Traditional, mutually exclusive approaches to racial and ethnic classification obscure important differences within major demographic groups and among multiracial populations. This study offers a novel examination of obstetric and neonatal outcomes among pregnant U.S. military service members, by applying multiple approaches to racial and ethnic classification and presenting disaggregated data. Overall, 235,608 births were identified among pregnant service members from 2010 through 2021. Inclusion of service members who identified with each racial group, whether alone or in combination with any other group, increased the American Indian or Alaska Native and Native Hawaiian or Pacific Islander birth populations by 209.7% and 94.0%, respectively, when compared to mutually exclusive classifications. Prevalences of obstetric outcomes such as cesarean delivery varied among racial and ethnic groups, particularly Asian and Latino populations, for example, Asian Indian, 36.7%; Filipino, 32.3%; Chinese, 26.5%; Puerto Rican, 30.2%; Mexican, 23.2%; and between distinct multiracial populations. Disaggregated estimates ultimately increased visibility of multiracial and Native service members and elucidated patterns indiscernible in aggregated data. Wider adoption of disaggregated racial and ethnic data methods is needed to improve understanding of health outcomes in the Military Health System. Reporting of non-mutually exclusive racial and ethnic groups as well as disaggregated Asian, Hispanic or Latino, and multiracial populations elucidates important differences in obstetric and neonatal outcomes.

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Journal
PubMed
Published
2026-02-24
Primary Topic
Migration, Health and Trauma
Type
article
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article

Applying distinct approaches to racial and ethnic classification to the surveillance of obstetric and neonatal outcomes in the U.S. military, 2010-2021.

Monica Burrell, Gia R. Gumbs, Ava Marie S. Conlin, Celeste J. Romano et al.
PubMed
Migration, Health and Trauma
article

Applying distinct approaches to racial and ethnic classification to the surveillance of obstetric and neonatal outcomes in the U.S. military, 2010-2021.

Monica Burrell, Gia R. Gumbs, Ava Marie S. Conlin, Celeste J. Romano, Sandra M. Magallon, Jackielyn Lanning, C H H Hall, Sandra Maduforo, Anna T Bukowinski, Zeina G. Khodr
article en

Abstract

Traditional, mutually exclusive approaches to racial and ethnic classification obscure important differences within major demographic groups and among multiracial populations. This study offers a novel examination of obstetric and neonatal outcomes among pregnant U.S. military service members, by applying multiple approaches to racial and ethnic classification and presenting disaggregated data. Overall, 235,608 births were identified among pregnant service members from 2010 through 2021. Inclusion of service members who identified with each racial group, whether alone or in combination with any other group, increased the American Indian or Alaska Native and Native Hawaiian or Pacific Islander birth populations by 209.7% and 94.0%, respectively, when compared to mutually exclusive classifications. Prevalences of obstetric outcomes such as cesarean delivery varied among racial and ethnic groups, particularly Asian and Latino populations, for example, Asian Indian, 36.7%; Filipino, 32.3%; Chinese, 26.5%; Puerto Rican, 30.2%; Mexican, 23.2%; and between distinct multiracial populations. Disaggregated estimates ultimately increased visibility of multiracial and Native service members and elucidated patterns indiscernible in aggregated data. Wider adoption of disaggregated racial and ethnic data methods is needed to improve understanding of health outcomes in the Military Health System. Reporting of non-mutually exclusive racial and ethnic groups as well as disaggregated Asian, Hispanic or Latino, and multiracial populations elucidates important differences in obstetric and neonatal outcomes.

PubMedVol. 33(1)
Leidos (United States) (US), Naval Health Research Center (US)
Reduced inequalities
Openalex Percentile: Top 36%
Migration, Health and Trauma
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