Gains in life expectancy after elimination of major causes of death: revised estimates taking into account the effect of competing causes

BACKGROUND: It is generally acknowledged that conventional estimates of the potential number of life years to be gained by elimination of causes of death are too generous. This is because these estimates fail to take into account the fact that those who are saved from the cause are likely to have one or more other conditions ("competing" causes of death), which may increase their risks of dying. It is unknown to what extent this introduces bias in comparisons of life years to be gained between underlying causes of death. The purpose of the study was to assess this bias. DATA AND METHODS: A sam... Mehr ...

Verfasser: Mackenbach, J.P. (Johan)
Kunst, A.E. (Anton)
Lautenbach, H.
Oei, Y.B.
Bijlsma, F.
Dokumenttyp: Artikel
Erscheinungsdatum: 1999
Schlagwörter: *Cause of Death / *Life Expectancy / Adolescent / Adult / Age Factors / Aged / 80 and over / Child / Preschool / Female / Humans / Infant / Newborn / Logistic Models / Male / Middle aged / Netherlands/epidemiology / Prevalence / Research Support / Non-U.S. Gov't / Sex Factors
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26833263
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://repub.eur.nl/pub/9097

BACKGROUND: It is generally acknowledged that conventional estimates of the potential number of life years to be gained by elimination of causes of death are too generous. This is because these estimates fail to take into account the fact that those who are saved from the cause are likely to have one or more other conditions ("competing" causes of death), which may increase their risks of dying. It is unknown to what extent this introduces bias in comparisons of life years to be gained between underlying causes of death. The purpose of the study was to assess this bias. DATA AND METHODS: A sample of 5975 death certificates from the Netherlands, 1990, was coded for the presence of diseases that, according to a set of explicit rules, could be regarded as potential causes of death "competing" with the underlying cause. Logistic regression analysis was used to quantify age and sex adjusted differences between four main underlying causes of death (neoplasms, cardiovascular diseases, respiratory diseases, all other diseases) in prevalence of the six most frequent competing causes of death (neoplasms, ischaemic heart disease, cerebrovascular disease, other cardiovascular diseases, chronic obstructive lung disease, all other diseases). These prevalence differences were then used to revise conventional calculations of gains in l