Affiliation:
1. Department of Epidemiology and Biostatistics, University of California San Francisco
2. UCSF Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital
3. Division of General Internal Medicine at Zuckerberg San Francisco General Hospital
4. Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA
Abstract
Background:Given the known disparities in COVID-19 within the Hispanic/Latinx community, we sought to examine the interaction between individual-level and neighborhood-level social determinants of health using linked electronic health record data.Methods:We examined electronic health record data linked to neighborhood data among Hispanic/Latinx patients tested for COVID-19 between March 1, 2020, and February 28, 2021, from 2 large health care systems in San Francisco. Hispanic/Latinx ethnic enclave is measured using an index of census-tract level indicators of ethnicity, nativity, and language. Multilevel logistic regression models examined associations between ethnic enclave and COVID-19 positivity (COVID-19+), adjusting for patient-level sociodemographic and clinical characteristics and health system. Cross-level interactions were used to test whether associations between ethnic enclave and COVID-19+ differed by patient language preference.Results:Among 26,871 patients, mean age was 37 years, 56% had Spanish-language preference, and 21% were COVID-19+. In unadjusted models, patients living in the highest versus lowest Hispanic/Latinx enclave had 3.2 higher odds of COVID-19+ (95% CI, 2.45–4.24). Adjusted, the relationship between ethnic enclave and COVID-19+ was attenuated, but not eliminated (odds ratio: 1.4; 95% CI, 1.13–1.17). Our results demonstrated a significant cross-level interaction, such that the influence of ethnic enclave was modified by patient language preference. For individuals with Spanish-language preference, risk of COVID-19+ was high regardless of neighborhood context, whereas for those with English preference, neighborhood ethnic enclave more than doubled the odds of infection.Conclusions:Findings suggest that a multilevel and intersectional approach to the study of COVID-19 inequities may illuminate dimensions of health inequity that affect marginalized communities and offer insights for targeted clinical and community-based interventions.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Public Health, Environmental and Occupational Health
Cited by
2 articles.
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