[Marquès M] Universitat Rovira i Virgili, Laboratory of Toxicology and Environmental Health, School of Medicine, IISPV, Reus, Spain. [Correig E] Universitat Rovira i Virgili, Department of Biostatistics, Reus, Spain. [Ibarretxe D] Universitat Rovira i Virgili, LIPIDCAS, University Hospital Sant Joan IISPV, CIBERDEM, Reus, Spain. [Anoro E] LIPIDCAS, Pius Hospital Valls, Valls, Spain. [Arroyo JA] Lipid Unit, University Hospital Santa Creu i Sant Pau, Barcelona Autonomous University, Barcelona, Spain. [Jericó C] Lipid Unit, Hospital Moises Broggi, Consorci Sanitari Integral, Sant Joan Despí, Spain. [Borrallo RM] Servei de Medicina Interna, Hospital de Terrassa, Consorci Sanitari de Terrassa, Terrassa, Spain. [Soler C] Hospital Santa Caterina, Girona, Spain. [Urquizu-Padilla M] Unitat de Lípid, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain
Consorci Sanitari de Terrassa
2023-05-25T12:39:45Z
2023-05-25T12:39:45Z
2022-01
Coronavirus; Atmospheric pollutants; World Health Organization
Coronavirus; Contaminantes atmosféricos; Organización Mundial de la Salud
Coronavirus; Contaminants atmosfèrics; Organització Mundial de la Salut
Background: Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course. Objectives: We aimed to assess the underlying effect of long-term exposure to NO2 and PM10 on the severity and mortality of COVID-19. Methods: A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO2 and PM10 and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated. Results: We found that the long-term exposure to PM10 is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM10 showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM10 (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m3 in PM10 concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths. Discussion: These results demonstrate that long-term PM10 burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.
Article
Published version
English
COVID-19 (Malaltia); Aire - Contaminació; Partícules (Matèria); CHEMICALS AND DRUGS::Chemical Actions and Uses::Toxic Actions::Environmental Pollutants::Air Pollutants; HEALTH CARE::Health Care Economics and Organizations::Organizations::International Agencies::United Nations::World Health Organization; DISEASES::Virus Diseases::RNA Virus Infections::Nidovirales Infections::Coronaviridae Infections::Coronavirus Infections; COMPUESTOS QUÍMICOS Y DROGAS::acciones y usos químicos::acciones tóxicas::contaminantes ambientales::contaminantes atmosféricos; ATENCIÓN DE SALUD::economía y organizaciones para la atención de la salud::organizaciones::instituciones internacionales::Naciones Unidas::Organización Mundial de la Salud; ENFERMEDADES::virosis::infecciones por virus ARN::infecciones por Nidovirales::infecciones por Coronaviridae::infecciones por Coronavirus
Elsevier
Environment International;158
https://doi.org/10.1016/j.envint.2021.106930
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
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