Short-term influence of environmental factors and social variables COVID-19 disease in Spain during the first wave (February-May 2020)
This article was originally published here
About Sci Pollut Res Int. 2022 Mar 1. doi: 10.1007/s11356-022-19232-9. Online ahead of print.
This study aims to identify the combined role of environmental pollutants and short-term atmospheric variables on the incidence rate (TIC) and on the hospital admission rate (TIHC) due to COVID-19 disease in Spain. . This study used information from 41 of the 52 provinces of Spain (from February 1, 2021 to May 31, 2021). Use of TIC and TIHC as dependent variables and mean daily PM concentrationsten and no2 as independent variables. Meteorological variables included daily maximum temperature (Tmax) and mean daily absolute humidity (HA). Generalized linear models (GLM) with Poisson link were carried out for each province. The GLM model controlled for trend, seasonality, and autoregressive character of the series. Days with offsets have been established. The relative risk (RR) was calculated by increments of 10 μg/m3 in PMten and no2 and 1°C in the case of Tmax and 1 g/m3 in the case of HA. Later, a linear regression was performed which included the social determinants of health. Statistically significant associations were found between PMtenNO2, and the incidence rate of COVID-19. NO2 was the variable that showed the greatest association for both TIC and TIHC in the majority of provinces. Temperature and HA do not seem to have played an important role. The geographical distribution of RRs in the provinces studied was very heterogeneous. Some of the health determinants considered, including per capita income, presence of airports, average number of diesel cars per capita, average number of carers, and dwellings under 30 m2 could explain the differential geographic behavior. As the results indicate, only environmental factors could modulate the incidence and severity of COVID-19. Additionally, social determinants and public health measures could explain some well-founded geographic distribution patterns.