key: cord-0709406-w8qujht7 authors: Cheney‐Peters, Dianna R.; Lee, Crystal Y.; Mitsuhashi, Shuji; Zaret, Dina S.; Riley, Joshua M.; Venkataraman, Chantel M.; Schaefer, Joseph W.; George, Brandon J.; Li, Chris J.; Smaltz, Christa M.; Bradley, Conor G.; Fitzpatrick, Danielle M.; Ney, David B.; Chalikonda, Divya M.; Mairose, Joshua D.; Chauhan, Kashyap; Szot, Margaret V.; Jones, Robert B.; Bashir‐Hamidu, Rukaiya; Kubey, Alan A. title: Association of race/ethnicity and socioeconomic status with COVID‐19 30‐day mortality at a Philadelphia medical center using a retrospective cohort study date: 2021-10-11 journal: J Med Virol DOI: 10.1002/jmv.27365 sha: 6334e4c7aedfcdf543cdcd0c6da401b10c52f748 doc_id: 709406 cord_uid: w8qujht7 COVID‐19 has disproportionately affected low‐income communities and people of color. Previous studies demonstrated that race/ethnicity and socioeconomic status (SES) are not independently correlated with COVID‐19 mortality. The purpose of our study is to determine the effect of race/ethnicity and SES on COVID‐19 30‐day mortality in a diverse, Philadelphian population. This is a retrospective cohort study in a single‐center tertiary care hospital in Philadelphia, PA. The study includes adult patients hospitalized with polymerase‐chain‐reaction‐confirmed COVID‐19 between March 1, 2020 and June 6, 2020. The primary outcome was a composite of COVID‐19 death or hospice discharge within 30 days of discharge. The secondary outcome was intensive care unit (ICU) admission. The study included 426 patients: 16.7% died, 3.3% were discharged to hospice, and 20.0% were admitted to the ICU. Using multivariable analysis, race/ethnicity was not associated with the primary nor secondary outcome. In Model 4, age greater than 75 (odds ratio [OR]: 11.01; 95% confidence interval [CI]: 1.96–61.97) and renal disease (OR: 2.78; 95% CI: 1.31–5.90) were associated with higher odds of the composite primary outcome. Living in a “very‐low‐income area” (OR: 0.29; 95% CI: 0.12–0.71) and body mass index (BMI) 30–35 (OR: 0.24; 95% CI: 0.08–0.69) were associated with lower odds of the primary outcome. When controlling for demographics, SES, and comorbidities, race/ethnicity was not independently associated with the composite primary outcome. Very‐low SES, as extrapolated from census‐tract‐level income data, was associated with lower odds of the composite primary outcome. The severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2), responsible for COVID-19, has caused a pandemic with far-reaching implications worldwide. US-based studies have demonstrated a disproportionate number of infections and hospitalizations for COVID-19 in people of certain racial and ethnic backgrounds, such as Black and Hispanic persons, and people residing in low-income areas or experiencing homelessness. [1] [2] [3] [4] [5] [6] [7] Additionally, worldwide studies have attempted to identify other independent risk factors, such as comorbidities and patient demographics, for COVID-19 mortality and severe COVID-19. However, many of these studies utilized the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) codes, rather than chart review to assess for comorbidities, which facilitates data collection by integrating hospital billing data, but may not reflect the true number of patients' comorbidities. 8 This may have led to inaccurate proportions of covariates utilized in the studies' multivariable analysis. 8 Philadelphia, a diverse city where 44% of the population identifies as Black or African American (hereafter "Black"), 34% non-Hispanic White ("White"), 15% Hispanic, and 8% Asian, has been significantly affected by COVID-19. 9 Through July 28, 2021, Black Philadelphians represented 45% of the known positive cases in which race/ethnicity was reported (83% of cases), while White, Hispanic, and Asian populations accounted for 34%, 14%, and 6%, respectively. 10, 11 Hospitalization trends occurred in similar proportions. 12 COVID-19 mortality for Black, White, Hispanic, and Asian patients was 49%, 35%, 11%, and 5% of deaths, respectively. Philadelphia has the highest poverty rate among the top 10 largest cities, with 23.3% of Philadelphians living below the poverty level with a median household income of $47,474. 9, 13, 14 In 2016, the poverty rate among Hispanics was 37.9%, the highest among racial and ethnic groups, followed by Blacks, which had the second-highest poverty rate at 30.8%; both groups are also more likely to live in areas of racially or ethnically concentrated high-poverty areas. 14 This highlights the complex interaction between race/ethnicity and poverty in Philadelphia, although it is important to extricate, as they both have distinct implications for policy and intervention. Furthermore, comparing case positivity rates and poverty level by zip code, data suggest that poorer Philadelphians are also disproportionately affected by COVID-19. 12, 15 The extent to which SES, which is a combined factor of income, education, and occupation, affects mortality for hospitalized Philadelphians is not known. The objective of this study is to assess if Black, White, Hispanic, or Asian race/ethnicity, and/or SES are independent risk factors for mortality for patients hospitalized with COVID-19 at one Philadelphia hospital using manual chart review rather than ICD-10 codes. For data validation, when two reviewers disagreed, a third independent reviewer adjudicated discrepancies. For variables for which discrete data could be exported from the EHR (e.g., BMI), data was verified through comparison of the manual extraction to an automated export. For the purpose of comparing the manual chart review to an automated ICD-10-based export, comorbidities for which reliable ICD-10 code mapping existed were exported. Although SES is often measured as a combination of many different elements, income data is readily available and standardizable. As a proxy for SES, we established if patients lived in very-low or lowincome areas using the US Housing and Urban Development were other, which was statistically significant in the unadjusted analysis (p = 0.029). Race/ethnicity and SES were not associated with the secondary outcome in bivariate nor multivariable analysis (Table S2 ). In this retrospective cohort study including 426 racially and ethnically diverse patients at a tertiary academic center in Philadelphia, we demonstrate that race/ethnicity is not independently associated with 30-day mortality or discharge to hospice from COVID-19 when using multivariable analysis controlling for age, sex, living in a low-income area, population density, type of residence before hospitalization, the time frame of admission, days since symptom onset, and comorbidities. From our review of the literature, this is one of a limited number of studies thus far to assess risk factors for COVID-19 using a more accurate approach with manual chart review rather than ICD-10 codes. 31 Furthermore, this is one of the first studies to assess the effects of race/ethnicity on 30-day mortality for hospitalized patients with COVID-19 in the Philadelphia region. 3 A major strength of this study is the use of manual chart review to determine comorbidities, which distinguishes this study from most others that used ICD-10 codes in analyses of 30-day mortality from COVID-19. A post hoc analysis of our data suggested that the manual chart review was more sensitive than ICD-10 based methods with ICD-10-based data set comorbidity agreement ranging from 44% (renal disease) to 87% (diabetes). An additional strength is the use of census tract-level data rather than zip code for mean area income, our proxy for SES. This may be a better representation of SES as it is comparatively more homogenous regarding the economic position and living conditions, which is especially important in Philadelphia given its unique urban geography in which very poor and affluent census tracts are frequently adjacent. A limitation of our study is that we did not collect patient data on other aspects of SES, such as 26, 29 We note that several comorbidities found in other studies did not have clear effects in our multivariable models including coronary artery disease, cancer, cerebral vascular disease, chronic obstructive pulmonary disease, heart failure, and hypertension. 21, 23, 24, 26, 27, 29, 32, 33 Other studies have demonstrated an increased odds of death in those with elevated BMIs, but the present study reflects a protective effect with an OR: 0.24 (95% CI: 0.08-0.69) in those with BMI: 30-35, and a trend toward a U-shaped curve (e.g., BMI: 30-40 lower risk, BMI < 30 or >40 higher risk), which may be a product of grouping all BMIs < 30 but warrants further investigation. 21, 25, 29 Finally, while living in a high-density area has previously been demonstrated to increase risk of hospitalization in COVID-19, in the present study we did not demonstrate increase odds of death or discharge to hospice for patients living in densely populated areas who were hospitalized with COVID-19; this outcome may also have been an artifact of census-level tract data as noted above. 34,39 Our study demonstrates that among patients hospitalized for COVID-19, after controlling for mediating variables, self-reported race and ethnicity were not independent predictors of mortality while living in very-low income neighborhoods was protective against death or hospice discharge from COVID-19. 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COVID-19 (Coronavirus Disease) America's Families and Living Arrangements High household transmission of SARS-CoV-2 in the United States: living density, viral load, and disproportionate impact on communities of color. medRxiv How to cite this article: Cheney-Peters DR Association of race/ethnicity and socioeconomic status with COVID-19 30-day mortality at a Philadelphia medical center using a retrospective cohort study The team would like to acknowledge and thank Anita M. Rawls, PhD, Katherine T. Berg, MD, MPH, Lily L. Ackermann, MD, and Sarah E.Rosenberg, MD, for their selfless and important contributions to this study. This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The authors declare that there are no conflict of interests. Dianna R. Cheney-Peters, Robert B. Jones, and Alan A. Kubey conceived The data that support the findings of this study are available from the corresponding author upon reasonable request.