Aperçu

Résumé (français)

Veuillez noter que les résumés n'apparaissent que dans la langue de la publication et peuvent ne pas avoir de traduction.

Résumé (anglais)

This paper addresses the problem of quantifying aging in individuals and populations using available biomedical, epidemiological and demographic data. Health of individuals is highly heterogeneous so is the rate how they age, in that sense we can say that individuals differ by their ‘biological age’. To account for such heterogeneity we have suggested a deficit accumulation approach, representing health status by the number of health deficits (broadly defined). In this way, the health of an individual can be represented by a single number (we called it a fitness/frailty index or just a frailty index, fi). Changes in the ficharacterize the rate of individual aging. The non-specificity of the fireflects the nonspecificity of aging itself, which involves each and every system of the organism. The behavior of the fiis highly characteristic -age specific increase in deficit accumulation, sex-related differences, strong association with adverse outcomes, universal limit of its increase – all these features are reproducible across different settings. The stochastic nature of changes in the fican be represented by a Markov process with transitional probabilities modeled by a Poisson distribution. This allows us not only to model health deterioration (which is the emphasis of different regression models) but also to account for health improvement otherwise considered as ‘measurement error’. While the fiis calculated in individuals, its population average can be used to characterize that population. We show the fihas a clear pattern of relationships with GDP per capita, human development index (HDI) and life expectancy and therefore has a potential to characterize population health as well as it characterizes health of individuals.