Second results of the “Coherent mortality forecasts by cause of death and disability level” research project
Modelling and forecasting healthy life expectancy. A Compositional Data Analysis approach
As part of the “Coherent mortality forecasts by cause of death and disability level” research project, which is financed by SCOR Foundation, the main investigator Marie-Pier Bergeron Boucher presented the second results of the project during a seminar held in Paris on April 6, 2022. The seminar brought together SCOR’s Biometric Risk Modelling team and researchers from the Interdisciplinary Center on Population Dynamics.
Second Results of the Project [EN] – Author: Marie-Pier Bergeron-Boucher, Paris 6 April 2022
Modelling and forecasting healthy life expectancy. A Compositional Data Analysis approach.
“Will the extra years of life gained by the increase in life expectancy be lived in good or bad health? As forecasts support social, economic and medical decisions, as well as individuals' choices, there is a clear rationale for forecasting healthy life expectancy. However, only a limited number of models are available to forecast healthy life expectancy. Some require separate forecasts of transition rates for mortality within different health statuses, and of the incidence rate. We suggest two methods that can simultaneously forecast mortality and health prevalence, based respectively on the Sullivan and the multistate approach to estimate healthy life expectancy. Both forecast models use a Compositional Data Analysis (CoDA) approach, accounting for the correlation between ages and health statuses. The methods are applied to the mortality of Swedish females aged 60 and above. We show that deaths have shifted towards older ages and states that are not severely limited, leading to less years of life with severe disability.”