Wendy K Tam Cho1,2,3,4,5,6,7,8, David G Hwang9. 1. Department of Ophthalmology, School of Medicine, University of California San Francisco, San Francisco, CA, USA. wendycho@illinois.edu. 2. Department of Political Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 3. Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 4. Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 5. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 6. Department of Asian American Studies, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 7. College of Law, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 8. National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA. wendycho@illinois.edu. 9. Department of Ophthalmology, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
Abstract
BACKGROUND: The COVID-19 pandemic has uncovered clinically meaningful racial/ethnic disparities in COVID-19-related health outcomes. Current understanding of the basis for such an observation remains incomplete, with both biomedical and social/contextual variables proposed as potential factors. PURPOSE: Using a logistic regression model, we examined the relative contributions of race/ethnicity, biomedical, and socioeconomic factors to COVID-19 test positivity and hospitalization rates in a large academic health care system in the San Francisco Bay Area prior to the advent of vaccination and other pharmaceutical interventions for COVID-19. RESULTS: Whereas socioeconomic factors, particularly those contributing to increased social vulnerability, were associated with test positivity for COVID-19, biomedical factors and disease co-morbidities were the major factors associated with increased risk of COVID-19 hospitalization. Hispanic individuals had a higher rate of COVID-19 positivity, while Asian persons had higher rates of COVID-19 hospitalization. The excess hospitalization risk attributed to Asian race was not explained by differences in the examined biomedical or sociodemographic variables. Diabetes was an important risk factor for COVID-19 hospitalization, particularly among Asian patients, for whom diabetes tended to be more frequently undiagnosed and higher in severity. CONCLUSION: We observed that biomedical, racial/ethnic, and socioeconomic factors all contributed in varying but distinct ways to COVID-19 test positivity and hospitalization rates in a large, multi-racial, socioeconomically diverse metropolitan area of the United States. The impact of a number of these factors differed according to race/ethnicity. Improving overall COVID-19 health outcomes and addressing racial and ethnic disparities in COVID-19 outcomes will likely require a comprehensive approach that incorporates strategies that target both individual-specific and group contextual factors.
BACKGROUND: The COVID-19 pandemic has uncovered clinically meaningful racial/ethnic disparities in COVID-19-related health outcomes. Current understanding of the basis for such an observation remains incomplete, with both biomedical and social/contextual variables proposed as potential factors. PURPOSE: Using a logistic regression model, we examined the relative contributions of race/ethnicity, biomedical, and socioeconomic factors to COVID-19 test positivity and hospitalization rates in a large academic health care system in the San Francisco Bay Area prior to the advent of vaccination and other pharmaceutical interventions for COVID-19. RESULTS: Whereas socioeconomic factors, particularly those contributing to increased social vulnerability, were associated with test positivity for COVID-19, biomedical factors and disease co-morbidities were the major factors associated with increased risk of COVID-19 hospitalization. Hispanic individuals had a higher rate of COVID-19 positivity, while Asian persons had higher rates of COVID-19 hospitalization. The excess hospitalization risk attributed to Asian race was not explained by differences in the examined biomedical or sociodemographic variables. Diabetes was an important risk factor for COVID-19 hospitalization, particularly among Asian patients, for whom diabetes tended to be more frequently undiagnosed and higher in severity. CONCLUSION: We observed that biomedical, racial/ethnic, and socioeconomic factors all contributed in varying but distinct ways to COVID-19 test positivity and hospitalization rates in a large, multi-racial, socioeconomically diverse metropolitan area of the United States. The impact of a number of these factors differed according to race/ethnicity. Improving overall COVID-19 health outcomes and addressing racial and ethnic disparities in COVID-19 outcomes will likely require a comprehensive approach that incorporates strategies that target both individual-specific and group contextual factors.