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County-Level Determinants of COVID-19 Testing and Cases: Are There Racial/Ethnic Disparities in Texas?
Omolola E Adepoju1, Chinedum O Ojinnaka2
1Department of Health Systems and Population Health Sciences, University of Houston College of Medicine, Houston, Texas, USA.
Abstract:
Reports suggest that COVID-19 affects people of color disproportionately. Texas ranks second in the count of confirmed US cases. This study examined the relationship between county-level racial/ethnic composition and COVID-19 testing/cases in Texas, adjusting for population-level demographic characteristics, health factors, and health care access measures. County-level testing and case data, obtained from the Texas Department of State Health Services, were combined with the 2020 Robert Wood Johnson Foundation County Health Rankings data. Outcome variables were tests per 100,000 population and cases per 100,000 population. The independent variable of interest was percent of racial and ethnic composition. Multivariable linear regression analyses were used. There was a statistically significant increase in COVID-19 testing/100,000 population with every 1% increase in the proportion of African Americans/Blacks (β = 2065.4; P = 0.009), Asians (β = 2056.2; P = 0.015), and Hispanics (β = 1641.1; P = 764.7). After controlling for county characteristics and cases/100,000 population, these relationships were no longer significant. However, primary care physician rate was significantly associated with testing/100,000 population (β = 64.0; P = 0.027), as was the percent of uninsured (β = -469.9; P = 0.024). An analysis of case data showed that African Americans had the largest number of cases/100,000 (β = 432.2; P = 0.001), followed by Hispanics (β = 422.8; P < 0.001) and Asians (β = 415.4; P = 0.004). As in other parts of the United States, African Americans and Hispanics are most affected by COVID-19 in Texas. Community-based strategies to improve access to testing or reduce community spread outside clinical settings should target counties with low primary care physician rates or a high proportion of uninsured residents.
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