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Modeling predicted that tobacco control policies targeted at lower educated will reduce the differences in life expectancy

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Author: Bemelmans, W.J.E. · Lenthe, F. van · Hoogenveen, R. · Kunst, A. · Deeg, D.J.H. · Brandt, P.A. van den · Goldbohm, R.A. · Verschuren, W.M.M.
Type:article
Date:2006
Institution: TNO Kwaliteit van Leven
Source:Journal of Clinical Epidemiology, 9, 59, 1002-1008
Identifier: 239445
doi: doi:10.1016/j.jclinepi.2006.02.008
Keywords: Health · Food and Chemical Risk Analysis · Educational differences · Life expectancy · Modeling · Mortality · Smoking · adult · aged · article · cohort analysis · controlled study · dynamics · female · health care policy · human · life expectancy · male · mortality · prevalence · priority journal · probability · risk assessment · smoking · socioeconomics · statistical model · theory · Adult · Aged · Cohort Studies · Educational Status · Female · Humans · Life Expectancy · Male · Middle Aged · Models, Statistical · Prevalence · Public Policy · Regression Analysis · Risk · Smoking · Smoking Cessation · Social Class · Time Factors

Abstract

Background and Objective: To estimate the effects of reducing the prevalence of smoking in lower educated groups on educational differences in life expectancy. Methods: A dynamic Markov-type multistate transition model estimated the effects on life expectancy of two scenarios. A "maximum scenario" where educational differences in prevalence of smoking disappear immediately, and a "policy target-scenario" where difference in prevalence of smoking is halved over a 20-year period. The two scenarios were compared to a reference scenario, where smoking prevalences do not change. Five Dutch cohort studies, involving over 67,000 participants aged 20 to 90 years, provided relative mortality risks by educational level, and smoking habits were assessed using national data of more than 120,000 persons. Results: In the reference scenario, the difference in life expectancy at age 40 between highest and lowest educated groups was 5.1 years for men and 2.7 years for women. In the "maximum scenario" these differences were reduced to 3.6 years for men and 1.7 years for women (reduction ≈30%), and in the "policy target-scenario" differences were 4.7 years for men and 2.4 years for women (reduction ≈10%). Conclusion: Theoretically, educational differences in life expectancy would be reduced by 30% at maximum, if variations in smoking prevalence were eliminated completely. In practice, tobacco control policies that are targeted at the lower educated may reduce the differences in life expectancy by approximately 10%. © 2006 Elsevier Inc. All rights reserved.