Portuguese Older Population Mortality: Spatiotemporal Analysis by Cause-of-Death and Sex

Abstract

There are indicators that suggest that the Portuguese population is aging uneven (Índice de dependência de idosos (N.) por Local de residência; Índice de envelhecimento (N.) por Local de residência; Índice de envelhecimento (N.) por Local de residência). Considering this fact, we propose to identify mortality patterns and regional differences amongst the older Portuguese population (65 or more years). The study of the spatio-temporal distribution of mortality in older people is essential to understand its dynamics and emergent trends as well as to promote health in aging populations. It was used the spatial scan statistic Kulldorff (Commun. Stat. Theor. Meth. 26, 1481–1496, 1997), a method for detecting space-time clusters. This method has a long tradition in spatial epidemiology, particularly, in many applications of public health areas Elliott and Wartenberg (Environ. Health Perspect. 112, 998–1006, 2004) and Nunes et al. (Rev. Port. Sau. Pub. 26, 5–14, 2008). We use stochastic space-time processes (according to the level of available geographical disaggregation data) to describe the mortality rates of the older Portuguese population (from 1992 to 2006) associated with diseases of the circulatory system and neoplasms. Results show statistically significant space-time clusters, for different age groups, by sex and cause of death. Those space-time units correspond to simultaneous occurrence of high mortality rates in different regions of the Portuguese mainland. These critical areas were consistent over age groups and sex, concerning diseases of the circulatory system as cause of death; for neoplasm, space-time critical areas presented some variations over age groups for both males and females.

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Lagarto, S., Nunes, C., Gomes, D., Mendes, M. F., 2013. “Portuguese Older Population Mortality: Spatiotemporal Analysis by Cause-of-Death and Sex”. Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications. Series Studies in Theoretical and Applied Statistics. Springer Series. Subseries Selected Papers of the Statistical Societies. Lita da Silva, J.; Caeiro, F.; Natário, I.; Braumann, C.A. (Eds.)

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