In the MEDEA I project, exposure to atmospheric pollution was estimated using stochastic spatial interpolation. Although this provided unbiased estimates of the pollution, which were able to be statistically significantly related with mortality at the level of census tracts in some cities, the estimation was rather inefficient. This lack of precision meant that few statistically significant relationships were found. The extra variation could be reduced i) by improving the estimates of exposure, introducing traffic into the models; ii) by using the ‘Regression according to land-use’ technique, incorporating other variables linked to localisation (distance to a road with heavy or medium traffic, population density, altitude and other topographic variables).
The exposure to pollution could present variations depending on different socio-economic conditions. Although not very conclusive, existing evidence suggests that the effects of atmospheric pollution are greater in more socio-economically deprived individuals. Little is known about the possible modification of the association between atmospheric pollution and mortality by factors measured at individual level (sex, age).
By combining stochastic spatial interpolation and GIS-based statistical methods, the intention is to analyse the relationship between the environmental variables and mortality by census tract.
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