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Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health

BACKGROUND: The objective of this study was to identify which air pollutants, atmospheric variables and health determinants could influence COVID-19 mortality in Spain. This study used information from 41 of the 52 provinces in Spain (from Feb. 1, to May 31, 2021). Generalized Linear Models (GLM) wi...

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Autores principales: Culqui Lévano, Dante R., Díaz, Julio, Blanco, Alejandro, Lopez, José A., Navas, Miguel A., Sánchez-Martínez, Gerardo, Luna, M. Yolanda, Hervella, Beatriz, Belda, Fernando, Linares, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040357/
https://www.ncbi.nlm.nih.gov/pubmed/35498506
http://dx.doi.org/10.1186/s12302-022-00617-z
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author Culqui Lévano, Dante R.
Díaz, Julio
Blanco, Alejandro
Lopez, José A.
Navas, Miguel A.
Sánchez-Martínez, Gerardo
Luna, M. Yolanda
Hervella, Beatriz
Belda, Fernando
Linares, Cristina
author_facet Culqui Lévano, Dante R.
Díaz, Julio
Blanco, Alejandro
Lopez, José A.
Navas, Miguel A.
Sánchez-Martínez, Gerardo
Luna, M. Yolanda
Hervella, Beatriz
Belda, Fernando
Linares, Cristina
author_sort Culqui Lévano, Dante R.
collection PubMed
description BACKGROUND: The objective of this study was to identify which air pollutants, atmospheric variables and health determinants could influence COVID-19 mortality in Spain. This study used information from 41 of the 52 provinces in Spain (from Feb. 1, to May 31, 2021). Generalized Linear Models (GLM) with Poisson link were carried out for the provinces, using the Rate of Mortality due to COVID-19 (CM) per 1,000,000 inhabitants as dependent variables, and average daily concentrations of PM(10) and NO(2) as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). The GLM model controlled for trend, seasonalities and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 g/m(3) in PM(10) and NO(2) and by 1 ℃ in the case of Tmax and 1 g/m(3) in the case of HA. Later, a linear regression was carried out that included the social determinants of health. RESULTS: Statistically significant associations were found between PM(10), NO(2) and the CM. These associations had a positive value. In the case of temperature and humidity, the associations had a negative value. PM(10) being the variable that showed greater association, with the CM followed of NO(2) in the majority of provinces. Anyone of the health determinants considered, could explain the differential geographic behavior. CONCLUSIONS: The role of PM(10) is worth highlighting, as the chemical air pollutant for which there was a greater number of provinces in which it was associated with CM. The role of the meteorological variables—temperature and HA—was much less compared to that of the air pollutants. None of the social determinants we proposed could explain the heterogeneous geographical distribution identified in this study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12302-022-00617-z.
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spelling pubmed-90403572022-04-26 Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health Culqui Lévano, Dante R. Díaz, Julio Blanco, Alejandro Lopez, José A. Navas, Miguel A. Sánchez-Martínez, Gerardo Luna, M. Yolanda Hervella, Beatriz Belda, Fernando Linares, Cristina Environ Sci Eur Research BACKGROUND: The objective of this study was to identify which air pollutants, atmospheric variables and health determinants could influence COVID-19 mortality in Spain. This study used information from 41 of the 52 provinces in Spain (from Feb. 1, to May 31, 2021). Generalized Linear Models (GLM) with Poisson link were carried out for the provinces, using the Rate of Mortality due to COVID-19 (CM) per 1,000,000 inhabitants as dependent variables, and average daily concentrations of PM(10) and NO(2) as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). The GLM model controlled for trend, seasonalities and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 g/m(3) in PM(10) and NO(2) and by 1 ℃ in the case of Tmax and 1 g/m(3) in the case of HA. Later, a linear regression was carried out that included the social determinants of health. RESULTS: Statistically significant associations were found between PM(10), NO(2) and the CM. These associations had a positive value. In the case of temperature and humidity, the associations had a negative value. PM(10) being the variable that showed greater association, with the CM followed of NO(2) in the majority of provinces. Anyone of the health determinants considered, could explain the differential geographic behavior. CONCLUSIONS: The role of PM(10) is worth highlighting, as the chemical air pollutant for which there was a greater number of provinces in which it was associated with CM. The role of the meteorological variables—temperature and HA—was much less compared to that of the air pollutants. None of the social determinants we proposed could explain the heterogeneous geographical distribution identified in this study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12302-022-00617-z. Springer Berlin Heidelberg 2022-04-26 2022 /pmc/articles/PMC9040357/ /pubmed/35498506 http://dx.doi.org/10.1186/s12302-022-00617-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Culqui Lévano, Dante R.
Díaz, Julio
Blanco, Alejandro
Lopez, José A.
Navas, Miguel A.
Sánchez-Martínez, Gerardo
Luna, M. Yolanda
Hervella, Beatriz
Belda, Fernando
Linares, Cristina
Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health
title Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health
title_full Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health
title_fullStr Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health
title_full_unstemmed Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health
title_short Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health
title_sort mortality due to covid-19 in spain and its association with environmental factors and determinants of health
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040357/
https://www.ncbi.nlm.nih.gov/pubmed/35498506
http://dx.doi.org/10.1186/s12302-022-00617-z
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