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The pattern of longevity in the Italian north-eastern region of Emilia Romagna was investigated at the municipality level, considering a modified version of the centenarian rate (CR) in two different periods (1995-1999 and 2005-2009). Due to the rareness of such events in small areas, spatio-temporal modelling was used to tackle the random variations in the occurrence of long-lived individuals. This approach allowed us to exploit the spatial proximity to smooth the observed data, as well as controlling for the effects of a set of covariates. As a result, clusters of areas characterised by extreme indexes of longevity could be identified and the temporal evolution of the phenomenon depicted. A persistence of areas of lower and higher occurrences of long-lived subjects was observed across time. In particular, mean and median values higher than the regional ones, showed up in areas belonging to the provinces of Ravenna and Forli-Cesena, on one side spreading out along the Adriatic coast and, on the other stretching into the Apennine municipalities of Bologna and Modena. Further, a longitudinal perspective was added by carrying out a spatial analysis including the territorial patterns of past mortality. We evaluated the effects of the structure of mortality on the cohort of long-lived subjects in the second period. The major causes of death were considered in order to deepen the analysis of the observed geographical differences. The circulatory diseases seem to mostly affect the presence of long-lived individuals and a prominent effect of altitude and population density also emerges.

In this paper, we investigate the pattern of longevity during the last 15 years in Emilia Romagna, a North-Eastern region of Italy, at a municipality level. We consider a specific index of extreme longevity based on people aged 95 and over in two different periods (1995-1999 and 2005-2009). Spatio-temporal modeling is used to tackle at both periods the random variations in the occurrence of people 95+, due to the increasingly rareness of such events, especially in small areas. This method exploits the spatial proximity and the consequent interaction of the geographical areas to smooth the observations, as well as to control for the effects of a set of regressors. As a result, clusters of areas characterized by high and low indexes of longevity are well identified and the temporal evolution of the phenomenon can be depicted. In a parallel analysis, we consider the past levels of mortality on the same cohort of individuals reaching 95 years and over in the second period and when they were aged 80-89 and 90-99. Within this longitudinal framework, the longevity outcome is modeled by a spatial regression. The area-specific structures of mortality are included as regressors, whose effects represent the causal link between the occurrence of people 95+ and the causes of death in the same cohort.