Social Determinants Predict Outcomes in Data From a Multi-Ethnic Cohort of 20,899 Patients Investigated for COVID-19

Frontiers in Public Health

article

Dara J. Lundon¹  Nihal Mohamed¹  Anna Lantz¹  Heather H. Goltz⁵  Brian D. Kelly⁶  Ashutosh K. Tewari¹ 

[1] Department of Urology, Icahn School of Medicine at Mount Sinai Hospitals, United States;The Center for Scientific Diversity, The Icahn School of Medicine at Mount Sinai, United States;The Tisch Cancer Institute, The Icahn School of Medicine at Mount Sinai, United States;Department of Medical Epidemiology and Biostatistics, Karolinska Institutet;College of Public Service, University of Houston-Downtown, United States;Department of Urology, Austin Health

关键词: COVID-19;    SARS-CoV-2;    social determinants of health;    multi-ethnic;    outcomes;   

DOI  :  10.3389/fpubh.2020.571364

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Importance: The COVID-19 pandemic exploits existing inequalities in social determinants of health (SDOH) in disease burden and access to healthcare. Few studies have examined these emerging disparities using indicators of SDOH. Objective: To evaluate predictors of COVID-19 test positivity, morbidity, and mortality and their implications for inequalities in SDOH and for future policies and health care improvements. Design, Setting, and Participants: A cross sectional analysis was performed on all patients tested for COVID-19 on the basis of symptoms with either a history of travel to at risk regions or close contact with a confirmed case, across the Mount Sinai Health System (MSHS) up until April 26th 2020. Main Outcomes and Measures: Primary outcome was death from COVID-19 and secondary outcomes were test positivity, and morbidity (e.g., hospitalization and intubation caused by COVID-19). Results: Of 20,899 tested patients, 8,928 tested positive, 1,701 were hospitalized, 684 were intubated, and 1,179 died from COVID-19. Age, sex, race/ethnicity, New York City borough (derived from first 3 digits of zip-code), and English as preferred language were significant predictors of test positivity, hospitalization, intubation and COVID-19 mortality following multivariable logistic regression analyses. Conclusions and Relevance: People residing in poorer boroughs were more likely to be burdened by and die from COVID-19. Our results highlight the importance of integrating comprehensive SDOH data into healthcare efforts with at-risk patient populations.

【 授权许可】

CC BY