key: cord-0973546-987pf84t
authors: Kim, Honghyok; Bell, Michelle L.
title: Air Pollution and COVID-19 Mortality in New York City
date: 2021-03-30
journal: American journal of respiratory and critical care medicine
DOI: 10.1164/rccm.202010-3844le
sha: 72b24030275f48f0dc873fa05439459e93d4beb6
doc_id: 973546
cord_uid: 987pf84t

nan

estimated using Poisson regression. We considered nonlinear terms (e.g., natural cubic spline) for associations between pollutants and COVID-19 mortality. A random MZCTA-level intercept and coordinates were included to consider overdispersion and adjust for spatial autocorrelation. We applied generalized propensity score (GPS) weighting to adjust for transmission (i.e., COVID-19 confirmed case rate), age, sex, race/ethnicity, population density, socioeconomic position, smoking, obesity, preexisting diseases (stroke, lung cancer, asthma, and poorly controlled diabetes), and healthcare availability (model 1). A list of variables is shown in Table 1 and its footnote. GPS was estimated by linear regression of the logarithm of PM 2.5 or O 3 on covariates. To test mediation through COVID-19 transmission and/or preexisting diseases, we omitted these variables (models 2-4). We further adjusted for covariates whose GPS-weighted absolute correlations with air pollutants exceeded 0.10. MZCTA-level associations between variables other than air pollution and COVID-19 mortality were also evaluated. Data For O 3 , covariates, including PM 2.5 , were generally well balanced. A few variables needed to be additionally adjusted using disease models. Figure 1 presents MZCTA-level associations between long-term O 3 exposure and COVID-19 mortality risk from models 1-4. Four models showed consistent associations. We should note that preexisting diseases and COVID-19 case rate were well balanced by GPS-weighting even for models 2-4. These well-balanced covariates suggest inability to isolate O 3 -COVID-19 infection and O 3 -preexisting disease condition mediation pathways. In model 2, a 1-ppb increase in O 3 concentration was associated with a 10.43% (95% confidence interval, 5.97-15.08%) increase in COVID-19 mortality. For PM 2.5 , covariates were not well balanced, so covariate adjustment was needed. A 1-mg/m 3 increase of PM 2.5 was associated with a 25.00% (95% confidence interval, 213.62% to 4.47%) increase in COVID-19 mortality. Table 1 presents MZCTA-level associations between neighborhood characteristics and COVID-19 mortality. We excluded preexisting disease variables because of their high correlation with obesity (.0.70) except for lung cancer. Results suggest that neighborhoods with a higher percentage of Black individuals, Hispanic individuals, individuals aged >65 years, individuals living below the poverty level, and individuals without health insurance are linked with higher COVID-19 mortality risk.

Our results indicate that populations living in neighborhoods with higher O 3 levels may have a poorer prognosis of COVID-19. This association was present at pollution levels below Environmental Protection Agency regulatory standards.

We speculate some reasons why we did not find associations for PM 2.5 . First, PM 2.5 was highly correlated with O 3 , suggesting possible residual confounding by O 3 Definition of abbreviations: CI = confidence interval; COVID-19 = coronavirus disease; MZCTA = modified ZIP code tabulation area; RR = relative rate; VIF = variance inflation factor. All variables were adjusted for one another. *The covariates in this table were selected based on their potential role as confounders and correlation analysis. The following covariates were not included because they were highly correlated with the covariates in this table: percentage of population age 15-44 years; percentage of population that is Asian/Pacific islanders; percentage of population age >25 years whose highest level of education is less than a high school diploma or General Education Development; median household income in the past 12 months; stroke hospitalization; preventable asthma hospitalization; poorly controlled diabetes; staffed beds; licensed beds. † for PM 2.5 -COVID-19 mortality association, unlike PM 2.5 , which was well balanced by GPS-weighting for O 3 -COVID-19 mortality association. There may exist residual confounding by factors other than O 3 , although we used GPS-weighting and covariate adjustments. Finally, residual variability of PM 2.5 and COVID-19 mortality after adjustment may be inadequate for detecting the association between them.

There are limitations. Our analysis is cross-sectional, so the temporality of links between air pollution and COVID-19 mortality rate is not established. The ecological fallacy may not be fully eliminated, although our spatial unit is the most highly resolved to date for this area of research in the United States. Undiagnosed COVID-19 deaths could not be considered. Future research should consider microclimate in exposures for within-neighborhood variability, the complex pollution mixture, and COVID-19 infection as well as mortality.

To the best of our knowledge, this is the first study to investigate associations between long-term PM 2.5 and O 3 exposure with COVID-19 mortality using neighborhood-level data in the United States, for which race/ethnicity, socioeconomic conditions, population density, availability of healthcare, and PM 2.5 and O 3 concentrations are heterogeneously distributed. Our findings also support the theory of disproportionate health burden of COVID-19 by socioeconomic conditions and race/ethnicity. Complex social, economic, cultural, and historical factors may contribute to these health disparities. Our results for multiple stressors may be generalizable to other areas and provide important scientific evidence to aid global efforts to tackle disproportionate impacts of COVID-19. Individual-level studies such as prospectivecohort studies shouldbeconducted to confirm links between air pollution and prognosis of COVID-19.

Extrapulmonary manifestations of COVID-19

American Heart Association Council on Epidemiology and Prevention; Council on the Kidney in Cardiovascular Disease; Council on Nutrition, Physical Activity and Metabolism. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association

Long-term exposure to ambient air pollution and risk of hospitalization with community-acquired pneumonia in older adults

Long-term exposure to air pollution and incidence of cardiovascular events in women

Long-term exposure to PM 2.5 and ozone and hospital admissions of Medicare participants in the Southeast USA

Air pollution, racial disparities, and COVID-19 mortality

Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis

Urban air pollution may enhance COVID-19 case-fatality and mortality rates in the United States

Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis

Do more hospital beds lead to higher hospitalization rates? A spatial examination of Roemer's Law

Author disclosures are available with the text of this letter at www.atsjournals.org.