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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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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 |
Sumario: | 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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