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

• Published in: Environmetrics (London, Ont.) Vol. 23; no. 2; pp. 175 - 182
• Main Authors: Calculli, Crescenza, Pollice, Alessio, Serinelli, Maria
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.03.2012
• Subjects: environmental pollution sources; MCMC; multiple disease risk; spatial variation; thin-plate splines
• ISSN: 1180-4009; 1099-095X
• DOI: 10.1002/env.1138

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). Copyright © 2011 John Wiley & Sons, Ltd.