An external exposome-wide association study of COVID-19 mortality in the United States

https://doi.org/10.1016/j.scitotenv.2020.144832Get rights and content

Highlights

  • The first external exposome study of COVID-19 mortality

  • Confirmed some previously reported associations

  • Generated unexpected predictors that may warrant more focused evaluation

Abstract

The risk factors for severe COVID-19 beyond older age and certain underlying health conditions are largely unknown. Recent studies suggested that long-term environmental exposures may be important determinants of severe COVID-19. However, very few environmental factors have been studied, often separately, without considering the totality of the external environment (i.e., the external exposome). We conducted an external exposome-wide association study (ExWAS) using the nationwide county-level COVID-19 mortality data in the contiguous US. A total of 337 variables characterizing the external exposome from 8 data sources were integrated, harmonized, and spatiotemporally linked to each county. A two-phase procedure was used: (1) in Phase 1, a random 50:50 split divided the data into a discovery set and a replication set, and associations between COVID-19 mortality and individual factors were examined using mixed-effect negative binomial regression models, with multiple comparisons addressed, and (2) in Phase 2, a multivariable regression model including all variables that are significant from both the discovery and replication sets in Phase 1 was fitted. A total of 13 and 22 variables were significant in the discovery and replication sets in Phase 1, respectively. All the 4 variables that were significant in both sets in Phase 1 remained statistically significant in Phase 2, including two air toxicants (i.e., nitrogen dioxide or NO2, and benzidine), one vacant land measure, and one food environment measure. This is the first external exposome study of COVID-19 mortality. It confirmed some of the previously reported environmental factors associated with COVID-19 mortality, but also generated unexpected predictors that may warrant more focused evaluation.

Abbreviations

COVID-19
the 2019 novel coronavirus disease
US
The United States
DM
diabetes mellitus
CVD
cardiovascular diseases
ICU
intensive care unit
PM2.5
fine particulate matter with diameters that are 2.5 μm and smaller
NO2
nitrogen dioxide
ExWAS
exposome-wide association study
JHU CSSE
Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center
CDC
The Centers for Disease Control and Prevention
SO42−
sulfate
NH4+
ammonium
NO3
nitrate
OM
organic matter
BC
black carbon
DUST
mineral dust
SS
sea-salt
US EPA
The United States Environmental Protection Agency
O3
ozone
CO
carbon monoxide
SO2
sulfur dioxide
ACAG
The University of Washington at St. Louis Atmospheric Composition Analysis Group
CACES
The Center for Air, Climate, & Energy Solutions
NATA
National Air Toxics Assessment
USDA
US Department of Agriculture
HUD
Department of Housing and Urban Development
USPS
US Postal Service
NACIS
The North American Industry Classification System
AWS
Amazon Web Services
EWAS-MLR
environment-wide association study followed by a multivariable regression step including the identified hits
MMR
mortality rate ratio
95% CI
95% confidence interval

Keywords

COVID-19
External exposome
Air pollution
Food environment
Vacant land

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