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Race, Ethnicity, and Air pollution in COVID-19 Hospitalization OUTcomes (REACH OUT)

Principal Investigator: 
,

Columbia University

In this study the investigators will conduct a retrospective evaluation of the interactions between long-term exposure to air pollution and neighborhood vulnerability to adverse COVID-19 outcomes. They will investigate both single and multipollutant air pollution exposures in relation to COVID-19 hospitalization, inpatient length of stay, ICU admission, ventilator use, and death among a racially diverse population in New York City.

Funded under
Status: 
Ongoing
Abstract

Poster abstract for HEI Annual Conference 2022

Association between Chronic Neighborhood Air Pollution Levels and COVID-19 Mortality within a Retrospective Analysis of New York City Hospitalization Data

Jeanette A Stingone PhD, MPH1 Sandra Albrecht, PhD, MPH1, Earle C. Chambers, PhD, MPH2, Perry E. Sheffield, MD, MPH,3 Azure Thompson, DrPH, MPH4, Jennifer Woo-Baidel, MD, MPH5, Stephanie Lovinsky-Desir, MD, MS5

1Columbia University, Mailman School of Public Health, New York, NY. USA

2Albert Einstein College of Medicine, Bronx, NY USA

3Icahn School of Medicine at Mount Sinai, New York, NY USA

4SUNY Downstate Health Sciences University, School of Public Health Brooklyn, NY USA

5Columbia University, Vagelos College of Physicians and Surgeons New York, NY USA

 

Background New York City has experienced geographic disparities in COVID19-related morbidity and mortality. The objective of this analysis was to estimate the association between fine particulate matter (PM2.5) exposure and COVID-19 mortality, adjusting for neighborhood-level socioeconomic vulnerabilities.

Methods This analysis is nested within the Race Ethnicity and COVID-19 Hospitalization Outcomes (REACH-OUT) study. The goals of REACH-OUT are to estimate the relationship between air pollution and COVID-19 outcomes and determine if air pollution exposure interacts with socioeconomic vulnerabilities at the neighborhood level to contribute to observed racial disparities. Our study population was drawn from a repository of electronic health record data from 5 large health systems in New York City. Our population included individuals hospitalized with a diagnosis of COVID-19 from March 1, 2020 to August 31, 2020 and living within New York City. The primary outcome was mortality. We assigned PM2.5 exposure using ZIP Code area estimates from the 2019 New York City Community Air Survey. We constructed Poisson regression models with robust standard errors to estimate the relative risk of mortality associated with PM2.5, adjusting for age, sex and a neighborhood-level measure of sociodemographic vulnerability.

Results Our study population consisted of 10,120 individuals, hospitalized with COVID-19 and living within New York City. Overall, 22% of the population was reported as Black, non-Latinx, 21.3% Latinx of any race, 18.8% as White, non-Latinx, 5.4% as Asian, non-Latinx with the remainder missing race information. There were 1992 deaths (19.7%). PM2.5 exposure was similar in those who survived and those who died (median of 6.83 µg/m3 vs 6.82 µg/m3). Distributions were right-skewed. Compared to individuals living in areas with the lowest quintile of PM2.5 levels, individuals in the second (RR 1.13 95%CI 1.01, 1.27), and third quintiles (RR 1.12 95%CI 0.99, 1.27) had elevated risk of mortality while those in the top two quintiles had lower risk of mortality (4th quintile RR 0.88 95%CI 0.77, 1.01 and 5th quintile RR 0.86 95%CI 0.75, 0.98). Results were stronger in magnitude, although less precise, within populations less than 65 years old.

Conclusions This preliminary analysis of the initial phase of the pandemic suggests increased COVID-19 mortality associated with living in a neighborhood with mid-range PM2.5 exposure, after adjusting for socioeconomic vulnerability. Future work will explore specific methods to account for non-linearity as well as include other air pollutants and spatially varying factors that may confound these results.