Health losses at the end of life: a Bayesian mixed beta regression approach

Abstract

The relationship between aging, health and healthcare expenditures is of central importance to academics and public policy makers. Generally, it is observed that, with advancing age, health deteriorates and healthcare expenditures increase. This seems to imply that increases in life expectancy would strongly increase both the demand for healthcare expenditures and the number of years lived in poor health. Previous research has shown that such straightforward conclusions may be flawed. For example, it has been established that not age but ‘time to death’ is the main driver of increased healthcare expenditures at advanced ages. The paper extends this line of research by investigating the relationship between age, time to death and health, the last being longitudinally measured via a health-related quality-of-life questionnaire. We propose an approach for modelling the health-related quality-of-life outcome that accounts for both the non-standard nature of this response variable (e.g. bounded, left skewed or heteroscedastic) and the panel structure of the data. Analyses were performed within a Bayesian framework. We found that health losses are centred in the final phase of life, which indicates that future increases in longevity will not necessarily increase life years spent in poor health. This may alleviate the consequences of population aging.