Long-Term Exposure to AIR Pollution and COVID-19 Mortality and Morbidity in DENmark: Who Is Most Susceptible? (AIRCODEN).
Year: 2023
Type: article
Study design: Observational Study
Abstract: INTRODUCTION: Early ecological studies have suggested a link between air pollution and Coronavirus Diseases 2019 (COVID-19); however, the evidence from individual-level prospective cohort studies is still sparse. Here, we have examined, in a general population, whether long-term exposure to air pollution is associated with the risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and developing severe COVID-19, resulting in hospitalization or death and who is most susceptible. We also examined whether long-term exposure to air pollution is associated with hospitalization or death due to COVID-19 in those who have tested positive for SARS-CoV-2. METHODS: ) at cohort participants' residence in 2019 by the Danish Eulerian Hemispheric Model/Urban Background Model. We used Cox proportional hazard models to estimate the associations of air pollutants with COVID-19 incidence, hospitalization, and mortality adjusting for age, sex, and socioeconomic status (SES) at the individual and area levels. We examined effect modification by age, sex, SES (education, income, wealth, employment), and comorbidities with cardiovascular disease, respiratory disease, acute lower respiratory infections, diabetes, lung cancer, and dementia. We used logistic regression to examine association of air pollutants with COVID-19-related hospitalization or death among SARS-CoV-2 positive patients, adjusting for age, sex, individual- and area-level SES. RESULTS: and no association between any of the pollutants and COVID-19 mortality (N = 2,557). CONCLUSIONS: This large nationwide study provides strong new evidence in support of association between long-term exposure to air pollution and COVID-19.
Source: PubMed Central
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
Awards: G1386593725, G77239831, G8316514081
OpenAlex ID: W4394767109
