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Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Int+J+Equity+Health 2020 ; 19 (1): 126 Nephropedia Template TP
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A model of disparities: risk factors associated with COVID-19 infection #MMPMID32727486
Int J Equity Health 2020[Jul]; 19 (1): 126 PMID32727486show ga
BACKGROUND: By mid-May 2020, there were over 1.5 million cases of (SARS-CoV-2) or COVID-19 across the U.S. with new confirmed cases continuing to rise following the re-opening of most states. Prior studies have focused mainly on clinical risk factors associated with serious illness and mortality of COVID-19. Less analysis has been conducted on the clinical, sociodemographic, and environmental variables associated with initial infection of COVID-19. METHODS: A multivariable statistical model was used to characterize risk factors in 34,503cases of laboratory-confirmed positive or negative COVID-19 infection in the Providence Health System (U.S.) between February 28 and April 27, 2020. Publicly available data were utilized as approximations for social determinants of health, and patient-level clinical and sociodemographic factors were extracted from the electronic medical record. RESULTS: Higher risk of COVID-19 infection was associated with older age (OR 1.69; 95% CI 1.41-2.02, p < 0.0001), male gender (OR 1.32; 95% CI 1.21-1.44, p < 0.0001), Asian race (OR 1.43; 95% CI 1.18-1.72, p = 0.0002), Black/African American race (OR 1.51; 95% CI 1.25-1.83, p < 0.0001), Latino ethnicity (OR 2.07; 95% CI 1.77-2.41, p < 0.0001), non-English language (OR 2.09; 95% CI 1.7-2.57, p < 0.0001), residing in a neighborhood with financial insecurity (OR 1.10; 95% CI 1.01-1.25, p = 0.04), low air quality (OR 1.01; 95% CI 1.0-1.04, p = 0.05), housing insecurity (OR 1.32; 95% CI 1.16-1.5, p < 0.0001) or transportation insecurity (OR 1.11; 95% CI 1.02-1.23, p = 0.03), and living in senior living communities (OR 1.69; 95% CI 1.23-2.32, p = 0.001). CONCLUSION: sisk of COVID-19 infection is higher among groups already affected by health disparities across age, race, ethnicity, language, income, and living conditions. Health promotion and disease prevention strategies should prioritize groups most vulnerable to infection and address structural inequities that contribute to risk through social and economic policy.