This study evaluates the effect of eliminating a specific disease on the mortality, long-term disability, and overall health status of a population.
Primarily, it examines whether elimination leads to a compression of morbidity.
The Sullivan method was used to calculate disability-free life expectancy.
Cause-deleted disability prevalence was estimated with a multiple logistic regression model that used data from the Dutch National Survey of General Practice.
Cause-deleted probabilities of dying were derived with the cause-elimination life-table technique, assuming independence among competing causes of death.
Eliminating disabling nonfatal diseases such as arthritis/back complaints results in a decline in life expectancy with disability-that is, an absolute compression of morbidity.
Emilinating highly fatal diseases such as cancer leads to an increase in the number of years and the proporition of life with disability-that is, a relative expansion of morbidity.
While eliminating fatal diseases leads to an increase in disability-free life expectancy, life expectancy wiyh disability may increase as well.
This represents an increasing burden to society.
On the other hand, eliminating nonfatal disabling diseases leads to absolute compression of morbidity.
Mots-clés Pascal : Morbidité, Maladie, Chronique, Elimination, Régression logistique, Table mortalité, Etat sanitaire, Homme, Pays Bas, Europe, Méthodologie, Espérance vie sans incapacité
Mots-clés Pascal anglais : Morbidity, Disease, Chronic, Elimination, Logistic regression, Life table, Health status, Human, Netherlands, Europe, Methodology
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 96-0276358
Code Inist : 002B30A01A2. Création : 199608.