TY - JOUR
T1 - Understanding COVID-19 Health Disparities With Birth Country and Language Data
AU - Smith, M. Kumi
AU - Ehresmann, Kirsten R.
AU - Knowlton, Gregory S.
AU - LaFrance, Amy B.
AU - Vazquez Benitez, Gabriela
AU - Quadri, Nasreen S.
AU - DeFor, Terese A.
AU - Mann, Erin M.
AU - Alpern, Jonathan D.
AU - Stauffer, William M.
N1 - Publisher Copyright:
© 2023 American Journal of Preventive Medicine
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
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U2 - 10.1016/j.amepre.2023.06.018
DO - 10.1016/j.amepre.2023.06.018
M3 - Article
C2 - 37406745
AN - SCOPUS:85165380389
SN - 0749-3797
VL - 65
SP - 993
EP - 1002
JO - American journal of preventive medicine
JF - American journal of preventive medicine
IS - 6
ER -