Application of the double kernel density approach to the analysis of cancer incidence in a major metropolitan area

DKD models appear to be a more sensitive tool for assessing potential environmental risks than traditional SIR-based models, because DKD estimates do not depend on a priory geographic delineations of statistical zones and produce a smooth and continuous disease 'risk surface' covering the entire study area. We suggest using the DKD method in similar studies of the effect of ambient air pollution on chronic morbidity, especially in cases in which the number of statistical areas available for aggregation and comparison is small and recorded morbidity events are relatively rare.