Dataset Information

Race, ethnicity, poverty and the social determinants of the coronavirus divide: U.S. county-level disparities and risk factors.

ABSTRACT:

Background

Communities with more Black or Hispanic residents have higher coronavirus rates than communities with more White residents, but relevant community characteristics are underexplored. The purpose of this study was to investigate poverty-, race- and ethnic-based disparities and associated economic, housing, transit, population health and health care characteristics.

Methods

Six-month cumulative coronavirus incidence and mortality were examined using adjusted negative binomial models among all U.S. counties (n = 3142). County-level independent variables included percentages in poverty and within racial/ethnic groups (Black, Hispanic, Native American, Asian), and rates of unemployment, lacking a high school diploma, housing cost burden, single parent households, limited English proficiency, diabetes, obesity, smoking, uninsured, preventable hospitalizations, primary care physicians, hospitals, ICU beds and households that were crowded, in multi-unit buildings or without a vehicle.

Results

Counties with higher percentages of Black (IRR = 1.03, 95% CI: 1.02-1.03) or Hispanic (IRR = 1.02, 95% CI: 1.01-1.03) residents had more coronavirus cases. Counties with higher percentages of Black (IRR = 1.02, 95% CI: 1.02-1.03) or Native American (IRR = 1.02, 95% CI: 1.01-1.04) residents had more deaths. Higher rates of lacking a high school diploma was associated with higher counts of cases (IRR = 1.03, 95% CI: 1.01-1.05) and deaths (IRR = 1.04, 95% CI: 1.01-1.07). Higher percentages of multi-unit households were associated with higher (IRR = 1.02, 95% CI: 1.01-1.04) and unemployment with lower (IRR = 0.96, 95% CI: 0.94-0.98) incidence. Higher percentages of individuals with limited English proficiency (IRR = 1.09, 95% CI: 1.04-1.14) and households without a vehicle (IRR = 1.04, 95% CI: 1.01-1.07) were associated with more deaths.

Conclusions

These results document differential pandemic impact in counties with more residents who are Black, Hispanic or Native American, highlighting the roles of residential racial segregation and other forms of discrimination. Factors including economic opportunities, occupational risk, public transit and housing conditions should be addressed in pandemic-related public health strategies to mitigate disparities across counties for the current pandemic and future population health events.

SUBMITTER: Samuel LJ

PROVIDER: S-EPMC8240081 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background Persistent racial/ethnic disparities in cardiovascular disease (CVD) mortality are partially explained by healthcare access and socioeconomic, demographic, and behavioral factors. Little is known about the association between race/ethnicity-specific CVD mortality and county-level factors. Methods and Results Using 2017 county-level data, we studied the association between race/ethnicity-specific CVD age-adjusted mortality rate (AAMR) and county-level factors (demographics, census region, socioeconomics, CVD risk factors, and healthcare access). Univariate and multivariable linear regressions were used to estimate the association between these factors; R2 values were used to assess the factors that accounted for the greatest variation in CVD AAMR by race/ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx individuals). There were 659 740 CVD deaths among non-Hispanic White individuals in 2698 counties; 100 475 deaths among non-Hispanic Black individuals in 717 counties; and 49 493 deaths among Hispanic/Latinx individuals across 267 counties. Non-Hispanic Black individuals had the highest mean CVD AAMR (320.04 deaths per 100 000 individuals), whereas Hispanic/Latinx individuals had the lowest (168.42 deaths per 100 000 individuals). The highest CVD AAMRs across all racial/ethnic groups were observed in the South. In unadjusted analyses, the greatest variation (R2) in CVD AAMR was explained by physical inactivity for non-Hispanic White individuals (32.3%), median household income for non-Hispanic Black individuals (24.7%), and population size for Hispanic/Latinx individuals (28.4%). In multivariable regressions using county-level factor categories, the greatest variation in CVD AAMR was explained by CVD risk factors for non-Hispanic White individuals (35.3%), socioeconomic factors for non-Hispanic Black (25.8%), and demographic factors for Hispanic/Latinx individuals (34.9%). Conclusions The associations between race/ethnicity-specific age-adjusted CVD mortality and county-level factors differ significantly. Interventions to reduce disparities may benefit from being designed accordingly.

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