Understanding COVID-19 Health Disparities With Birth Country and Language Data

M. Kumi Smith, Kirsten R. Ehresmann, Gregory S. Knowlton, Amy B. LaFrance, Gabriela Vazquez Benitez, Nasreen S. Quadri, Terese A. DeFor, Erin M. Mann, Jonathan D. Alpern, William M. Stauffer

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Introduction: Understanding of COVID-19–related disparities in the U.S. is largely informed by traditional race/ethnicity categories that mask important social group differences. This analysis utilizes granular information on patients’ country of birth and preferred language from a large health system to provide more nuanced insights into health disparities. Methods: Data from patients seeking care from a large Midwestern health system between January 1, 2019 and July 31, 2021 and COVID-19–related events occurring from March 18, 2020 to July 31, 2021 were used to describe COVID-19 disparities. Statistics were performed between January 1, 2022 and March 15, 2023. Age-adjusted generalized linear models estimated RR across race/ethnicity, country of birth grouping, preferred language, and multiple stratified groups. Results: The majority of the 1,114,895 patients were born in western advanced economies (58.6%). Those who were Hispanic/Latino, were born in Latin America and the Caribbean, and preferred Spanish language had highest RRs of infection and hospitalization. Black-identifying patients born in sub-Saharan African countries had a higher risk of infection than their western advanced economies counterparts. Subanalyses revealed elevated hospitalization and death risk for White-identifying patients from Eastern Europe and Central Asia and Asian-identifying patients from Southeast Asia and the Pacific. All non-English languages had a higher risk of all COVID-19 outcomes, most notably Hmong and languages from Burma/Myanmar. Conclusions: Stratifications by country of birth grouping and preferred language identified culturally distinct groups whose vulnerability to COVID-19 would have otherwise been masked by traditional racial/ethnic labels. Routine collection of these data is critical for identifying social groups at high risk and for informing linguistically and culturally relevant interventions.

Original languageEnglish (US)
Pages (from-to)993-1002
Number of pages10
JournalAmerican journal of preventive medicine
Issue number6
StatePublished - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023 American Journal of Preventive Medicine

PubMed: MeSH publication types

  • Journal Article
  • Research Support, U.S. Gov't, P.H.S.


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