Volume 20 - Article 18 | Pages 435–466

Geographical mortality patterns in Italy: A Bayesian analysis

By Fabio Divino, Viviana Egidi, Michele Antonio Salvatore

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Date received:03 Jun 2008
Date published:24 Apr 2009
Word count:6837
Keywords:clustering effect, heterogeneity effect, hierarchical spatio-temporal model, relative risks


In this paper, we present a hierarchical spatial model for the analysis of geographical variation in mortality between the Italian provinces in the year 2001, according to gender, age class, and cause of death. When analysing counts data specific to geographical locations, classical empirical rates or standardised mortality ratios may produce estimates that show a very high level of overdispersion due to the effect of spatial autocorrelation among the observations, and due to the presence of heterogeneity among the population sizes. We adopt a Bayesian approach and a Markov chain Monte Carlo computation with the goal of making more consistent inferences about the quantities of interest. While considering information for the year 1991, we also take into account a temporal effect from the previous geographical pattern. Results have demonstrated the flexibility of our proposal in evaluating specific aspects of a counts spatial process, such as the clustering effect and the heterogeneity effect.

Author's Affiliation

Fabio Divino - Università degli Studi del Molise, Italy [Email]
Viviana Egidi - Università degli Studi di Roma La Sapienza, Italy [Email]
Michele Antonio Salvatore - Istituto Nazionale di Statistica (ISTAT), Italy [Email]

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