A multilevel multimember model for smoothing a disease map of lung cancer rates

Abstract: Aim of this study is to assess the effect of smoothing, based on the assumption that hospitalization rates may be influenced by the neighboring municipalities, the health service organization (HSO) and environmental risk factors. To smooth rates two different Multilevel Multimembership Models are fitted: in the first the random effects where the municipality heterogeneity, the spatial dependence of the municipalities and the local HSO; in the second we replaced the local HSO effect with the environmental risk effect. The models were applied to spatially represent the rates of hospitalization for lung cancer in Apulia in the year 2006. Maps shaded with the rates obtained at the end of the smoothing procedure seem to express a geographical distribution pattern in specific areas of the region. The effect of smoothing was greater in municipalities with a more unstable Risk Adjusted Rate.