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Relationships of daily mortality and hospital admissions to air pollution in Castilla-León, Spain

Author(s): F. De Pablo | A. López | L. Rivas Soriano | C. Tomás | L. Diego | M. González | M. Barrueco

Journal: Atmósfera
ISSN 0187-6236

Volume: 19;
Issue: 1;
Start page: 23;
Date: 2006;
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Keywords: Mortality and morbidity | pollutants and meteorological variables | multiple linear regression analysis | Spain

We examined the possible relationships between pollutant concentrations and mortality at seven different locations of Castilla-León, Spain, and the relationships between such concentration levels and emergency admissions (morbidity) at four hospitals in the region, taking into account the possible masking effect of other atmospheric variables. The study was based on daily mortality and morbidity data from 1995 to 1997 (ICD-9 codes: 390-459 cardiovascular; 460-519 respiratory; 520-579 digestive causes); moreover, data for meteorological variables (air temperature, relative humidity, solar radiation, atmospheric pressure and wind velocity) and air pollution data (SO2, O3, NO, NO2 and CO) were used. A minimum set of weather and pollutant predictors was selected using forward inclusion stepwise linear regression methods and these were used to produce a multivariate model of the different causes of mortality and morbidity. For the whole period, the mortality attributable to cardiovascular causes had an incidence higher than the mortality due to respiratory and digestive causes. The frequency distributions corresponding to the different diseases as classified by ages revealed that the population older than 69 is the most affected, the proportion of cardiovascular disease-related deaths in this age sector being 7-fold higher than for the rest of the groups. Mortality and morbidity due to respiratory and cardiovascular-related diseases showed a high correlation coefficient with temperature, solar radiation and ozone, and in general significant correlations were also seen with SO2. Key words: Mortality and morbidity, pollutants and meteorological variables, multiple linear regression analysis, Spain.
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