Spatial patterns of survival and longevity in Italy

Elisabetta Barbi, Sapienza University of Rome

In recent years, there has been a growing interest among demographers and epidemiologists in spatial analyses of health and mortality data, also thanks to recent developments of user-friendly software and the increasing number of geographically referenced databases. Spatial analysis may lead to less biased results and better inferences, thus it is of crucial importance for a better understanding of the nature and the extent of demographic differentials in a region. The aim of this study is to identify areas with specific spatial survival and longevity patterns which are statistically significant, and to study their evolution over time. Mortality data are adequately mapped, accounting for spatial autocorrelation, so as to identify possible discontinuous areas with exceptionally low or high mortality (hotspots), and/or clusters of areas with similar mortality data. For each Italian province, Standardized Mortality Ratios (SMRs) are computed by sex and age groups (0-30, 31-60, 61-80, 80 and over), for both all-cause mortality and cause-specific mortality, in 1981, 1991 and 2002. SMRs are then analysed by using the Local Indicators of Spatial Association (LISA) proposed by Anselin in 1995. LISA evaluate the existence of local clusters in the spatial arrangement of a given variable, identifying those areas where the clustering of areas is significant. That is, LISA can select areas that can be statistically defined as hot from those that are not, plus rank each hotspot according to a significance threshold. Applications of LISA to Italian mortality data highlight clear spatial patterns of Italian cause-specific mortality that have substantially changed over time, and discover the existence of specific geographical subsets of longevity that would otherwise be difficult to identify. Results may be of great interest to policy makers for monitoring the territory and for identifying potential interventions and appropriate health policies.

Presented in Session 57: Spatial Differentials in Population Processes