Work

Fuzzy clustering of the healthy life expectancy decomposition: A multi-population analysis

Year: 2024

Type: article

Abstract: This work analyses healthy life expectancy, which combines information on the period life table with the age-specific disability prevalence data in a single indicator. We quantify how much mortality and disability contributed to changes in healthy life expectancy over a fixed time horizon by age group and population to understand if life expectancy is increasing faster than the decline of disability. The prominent heterogeneity in mortality and health worldwide calls for a cross-country comparative analysis. The methodology used is decomposition, which splits the difference between two times of an aggregate index by assigning the difference to its components. Besides, through a cluster analysis, we categorise countries according to the age-specific contributions of mortality and disability simultaneously, using the healthy life expectancy decomposition results. This allows us to ease the interpretation and better outline the outcomes. Since health is increasingly considered a crucial aspect of economic growth, monitoring health expectancies is essential to assess the financial sustainability of the health and social security system. Some policy implications are finally discussed.

Source: Socio-Economic Planning Sciences

DOI: 10.1016/j.seps.2024.101805

Authors: Leonardo Salvatore Alaimo, Susanna Levantesi, Andrea Nigri

Institutions: Sapienza University of Rome, University of Foggia

Language: English

Topic: Insurance, Mortality, Demography, Risk Management

Subfield: Demography

Field: Social Sciences

Domain: Social Sciences

SDGs: Good health and well-being, Reduced inequalities

Open Access status: hybrid

Estimated APC paid: $3,020