Association of Lower Socioeconomic Status and SARS-CoV-2 Positivity in Los Angeles, California
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Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads heterogeneously, disproportionately impacting poor and minority communities. The relationship between poverty and race is complex, with a diverse set of structural and systemic factors driving higher rates of poverty among minority populations. The factors that specifically contribute to the disproportionate rates of SARS-CoV-2 infection, however, are not clearly understood. Methods: We evaluated SARS-CoV-2 test results from community-based testing sites in Los Angeles, California, between June and December, 2020. We used tester zip code data to link those results with United States Census report data on average annual household income, rates of healthcare coverage, and employment status by zip code. Results: We analyzed 2 141 127 SARS-CoV-2 test results, of which 245 154 (11.4%) were positive. Multivariable modeling showed a higher likelihood of SARS-CoV-2 test positivity among Hispanic communities than among other races. We found an increased risk for SARS-CoV-2 positivity among individuals from zip codes with an average annual household income <US$65 000 (adjusted odds ratio [aOR], 1.77; 95% confidence interval [CI], 1.72 to 1.82), as well as from zip codes with <85% of individuals with health insurance (aOR, 1.29; 95% CI, 1.25 to 1.33), and <60% of individuals employed (aOR, 1.42; 95% CI, 1.41 to 1.44). Conclusions: Residence in zip codes with lower average annual household income, lower rates of employment, or lower rates of health insurance was associated with SARS-CoV-2 positivity. Further research is needed into how those factors increase the spread of SARS-CoV-2 infection among populations of lower socioeconomic status in order to develop targeted public health interventions.
Abstract
Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads heterogeneously, disproportionately impacting poor and minority communities. The relationship between poverty and race is complex, with a diverse set of structural and systemic factors driving higher rates of poverty among minority populations. The factors that specifically contribute to the disproportionate rates of SARS-CoV-2 infection, however, are not clearly understood. Methods: We evaluated SARS-CoV-2 test results from community-based testing sites in Los Angeles, California, between June and December, 2020. We used tester zip code data to link those results with United States Census report data on average annual household income, rates of healthcare coverage, and employment status by zip code. Results: We analyzed 2 141 127 SARS-CoV-2 test results, of which 245 154 (11.4%) were positive. Multivariable modeling showed a higher likelihood of SARS-CoV-2 test positivity among Hispanic communities than among other races. We found an increased risk for SARS-CoV-2 positivity among individuals from zip codes with an average annual household income <US$65 000 (adjusted odds ratio [aOR], 1.77; 95% confidence interval [CI], 1.72 to 1.82), as well as from zip codes with <85% of individuals with health insurance (aOR, 1.29; 95% CI, 1.25 to 1.33), and <60% of individuals employed (aOR, 1.42; 95% CI, 1.41 to 1.44). Conclusions: Residence in zip codes with lower average annual household income, lower rates of employment, or lower rates of health insurance was associated with SARS-CoV-2 positivity. Further research is needed into how those factors increase the spread of SARS-CoV-2 infection among populations of lower socioeconomic status in order to develop targeted public health interventions.
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