• 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, and William M Stauffer.
• Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota.
• Am J Prev Med. 2023 Dec 1; 65 (6): 9931002993-1002.

IntroductionUnderstanding 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.MethodsData 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.ResultsThe 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.ConclusionsStratifications 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.Copyright © 2023 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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