| Title: |
Modelling and forecasting healthy life expectancy. A Compositional Data Analysis approach |
| Authors: |
Marie–Pier Bergeron–Boucher; Cosmo Strozza; Violetta Simonacci; Jim Oeppen |
| Contributors: |
European association for population studies; Bergeron–boucher, Marie–pier; Strozza, Cosmo; Simonacci, Violetta; Oeppen, Jim |
| Publication Year: |
2022 |
| Collection: |
IRIS Università degli Studi di Napoli Federico II |
| Description: |
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 are based on multistate modelling, which can be data-demanding and requires separate forecasts of transition rates for mortality within different health statuses and the incidence rate. We here suggest a less data demanding model to forecast mortality and health prevalence simultaneously. The model is based on the Sullivan method, which uses cross-sectional data, and Compositional Data Analysis. The method is applied to Swedish female mortality aged 65 and above. We show that deaths have been shifted towards older ages and not-limited, leading to an increase in both life expectancy and disability-free life expectancy. |
| Document Type: |
conference object |
| Language: |
English |
| Relation: |
ispartofbook:European Population Conference 2022; European Population Conference 2022; firstpage:1; lastpage:5; numberofpages:5; https://hdl.handle.net/11588/894599; https://epc2022.eaps.nl/abstracts/210615 |
| Availability: |
https://hdl.handle.net/11588/894599; https://epc2022.eaps.nl/abstracts/210615 |
| Rights: |
info:eu-repo/semantics/openAccess ; license:Non specificato ; license uri:na |
| Accession Number: |
edsbas.C87CD8DD |
| Database: |
BASE |