Spatial analysis of the risk of multiple cancers in relation to a petrochemical plant

In Environmental Epidemiology studies, the effects of the presence of a source of pollution on the population health can be evaluated by models that consider the distance from the source as a possible risk factor. We introduce a hierarchical Bayesian model in order to investigate the association between the risk of multiple pathologies and the presence of a single pollution source. Our approach provides the possibility to incorporate spatial effects and other confounding factors within a logistic regression model. Spatial effects are decomposed into the sum of a disease-specific parametric component accounting for the distance from the point source and a common semi-parametric component that can be interpreted as a residual spatial variation. The model is applied to data from a spatial case–control study to evaluate the association of the incidence of different cancers with the residential location in the neighborhood of a petrochemical plant in the Brindisi area (Italy).