Recent Changes in Human Mortality: The Case Study of Greece

Panagiotis Andreopoulos (), Fragkiskos G. Bersimis (), Kleomenis Kalogeropoulos () and Alexandra Tragaki ()
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Panagiotis Andreopoulos: Harokopio University, Department of Geography
Fragkiskos G. Bersimis: Harokopio University, Department of Informatics and Telematics
Kleomenis Kalogeropoulos: University of West Attica, Department of Surveying and Geoinformatics Engineering
Alexandra Tragaki: Harokopio University, Department of Geography

Chapter Chapter 17 in Quantitative Demography and Health Estimates, 2023, pp 217-231 from Springer

Abstract: Abstract In the light of Mathematical Statistics, mortality can be expressed with different parameters through multiparametric prediction models. By Beta Gompertz Generalized Makeham (BGGM) probabilistic distribution aided, the present study aims to evaluate and map four such parameters for the region of Greece, during the period 1980–2030. The current level of population mortality in Greece is a result of long-term changes in its trends. The changes were positive and meant a reduction in mortality rates and, above all, the elimination of unnecessary deaths. But, recently a number of negative factors brought a reducing impact on mortality, but also the overall demographic development of the population in Greece. The level and structure of mortality achieved reflect the complex relationship between the individual, biological factors, and their action, on the one hand, and living conditions over time, through the influence of numerous factors of a socio-economic nature, on the other. BGGM is a probabilistic distribution expressing a multidimensional model able to estimate the course of human mortality affected by infant mortality, population aging, and individual and collective mortality intensity, which changes due to unexpected events. The aim of this study is to draw attention to recent changes in the level and structure of mortality and to highlight the most important issues and challenges for further reducing mortality and extending life expectancy. A GIS framework is used to map the spatial patterns of these estimated parameters as well as these variants during the period under consideration for both men and women.

Keywords: Mortality; Demography; BGGM probabilistic distribution; GIS; Cartography (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-031-28697-1_17

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DOI: 10.1007/978-3-031-28697-1_17

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