Dataset Information

Potential impact of reduced tobacco use on life and health expectancies in Belgium.

ABSTRACT: OBJECTIVES:We investigated the potential impact of reduced tobacco use scenarios on total life expectancy and health expectancies, i.e., healthy life years and unhealthy life years. METHODS:Data from the Belgian Health Interview Survey 2013 were used to estimate smoking and disability prevalence. Disability was based on the Global Activity Limitation Indicator. We used DYNAMO-HIA to quantify the impacts of risk factor changes and to compare the "business-as-usual" with alternative scenarios. RESULTS:The "business-as-usual" scenario estimated that in 2028 the 15-year-old men/women would live additional 50/52 years without disability and 14/17 years with disability. The "smoking-free population" scenario added 3.4/2.8 healthy life years and reduced unhealthy life years by 0.79/1.9. Scenarios combining the prevention of smoking initiation with smoking cessation programs are the most effective, yielding the largest increase in healthy life years (1.9/1.7) and the largest decrease in unhealthy life years (-?0.80/-?1.47). CONCLUSIONS:Health impact assessment tools provide different scenarios for evidence-informed public health actions. New anti-smoking strategies or stricter enforcement of existing policies potentially gain more healthy life years and reduce unhealthy life years in Belgium.

SUBMITTER: Otavova M

PROVIDER: S-EPMC7049546 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Potential impact of reduced tobacco use on life and health expectancies in Belgium.

Otavova Martina M Van Oyen Herman H Yokota Renata T C RTC Charafeddine Rana R Joossens Luk L Molenberghs Geert G Nusselder Wilma J WJ Boshuizen Hendriek C HC Devleesschauwer Brecht B

International journal of public health 20191128 2

<h4>Objectives</h4>We investigated the potential impact of reduced tobacco use scenarios on total life expectancy and health expectancies, i.e., healthy life years and unhealthy life years.<h4>Methods</h4>Data from the Belgian Health Interview Survey 2013 were used to estimate smoking and disability prevalence. Disability was based on the Global Activity Limitation Indicator. We used DYNAMO-HIA to quantify the impacts of risk factor changes and to compare the "business-as-usual" with alternative ...[more]

PMID: 31781804

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Project description:Background:Reducing socio-economic health inequalities is a public health priority, necessitating careful monitoring that should take into account changes in the population composition. We analyzed the evolution of educational inequalities in life expectancy and disability-free life expectancy at age 25 (LE25 and DFLE25) in Belgium between 2001 and 2011. Methods:The 2001 and 2011 census data were linked with the national register data for a five-year mortality follow up. Disability prevalence estimates from the health interview surveys (2001 to 2013) were used to compute DFLE according to Sullivan's method. LE25 and DFLE25 were computed by educational level (EL). Absolute differentials of LE25 and DFLE25 were calculated for each EL and for each period, as well as composite inequality indices (CII) of population-level impact of inequality. Changes over the 10-year period were then calculated for each inequality index. Results:The LE25 increased in all ELs and both genders, except in the lowest EL for women. The increase was larger in the highest EL, leading in 2011 to 6.07 and 4.58?years for the low-versus-high LE25 gaps respectively in men and women, compared to 5.19 and 3.76 in 2001, namely 17 and 22% increases. The upwards shift of the EL distribution led to a limited 7% increase of the CII among men but no change in women.The substantial increase of the DFLE25 in males with high EL (+?4.5?years) and the decrease of the DFLE25 in women with low EL, results in a substantial increase of all considered DFLE25 inequality measures in both genders. In 2011, DFLE25 gaps were respectively 10.4 and 13.5?years in males and females compared to 6.51 and 9.30 in 2001, representing increases of 61 and 44% for the gaps, and 72 and 20% for the CII. Conclusion:The LE25 increased in all ELs, but at a higher pace in highly educated, leading to an increase in the LE25 gaps in both genders. After accounting for the upwards shift of the educational distribution, the population-level inequality index increased only for men. The DFLE25 increased only in highly educated men, and decreased in low educated women, leading to large increases of inequalities in both genders. A general plan to tackle health inequality should be set up, with particular efforts to improve the health of the low educated women.

Project description:BackgroundAmericans have a shorter life expectancy compared with residents of almost all other high-income countries. We aim to estimate the impact of lifestyle factors on premature mortality and life expectancy in the US population.MethodsUsing data from the Nurses' Health Study (1980-2014; n=78 865) and the Health Professionals Follow-up Study (1986-2014, n=44 354), we defined 5 low-risk lifestyle factors as never smoking, body mass index of 18.5 to 24.9 kg/m2, ≥30 min/d of moderate to vigorous physical activity, moderate alcohol intake, and a high diet quality score (upper 40%), and estimated hazard ratios for the association of total lifestyle score (0-5 scale) with mortality. We used data from the NHANES (National Health and Nutrition Examination Surveys; 2013-2014) to estimate the distribution of the lifestyle score and the US Centers for Disease Control and Prevention WONDER database to derive the age-specific death rates of Americans. We applied the life table method to estimate life expectancy by levels of the lifestyle score.ResultsDuring up to 34 years of follow-up, we documented 42 167 deaths. The multivariable-adjusted hazard ratios for mortality in adults with 5 compared with zero low-risk factors were 0.26 (95% confidence interval [CI], 0.22-0.31) for all-cause mortality, 0.35 (95% CI, 0.27-0.45) for cancer mortality, and 0.18 (95% CI, 0.12-0.26) for cardiovascular disease mortality. The population-attributable risk of nonadherence to 5 low-risk factors was 60.7% (95% CI, 53.6-66.7) for all-cause mortality, 51.7% (95% CI, 37.1-62.9) for cancer mortality, and 71.7% (95% CI, 58.1-81.0) for cardiovascular disease mortality. We estimated that the life expectancy at age 50 years was 29.0 years (95% CI, 28.3-29.8) for women and 25.5 years (95% CI, 24.7-26.2) for men who adopted zero low-risk lifestyle factors. In contrast, for those who adopted all 5 low-risk factors, we projected a life expectancy at age 50 years of 43.1 years (95% CI, 41.3-44.9) for women and 37.6 years (95% CI, 35.8-39.4) for men. The projected life expectancy at age 50 years was on average 14.0 years (95% CI, 11.8-16.2) longer among female Americans with 5 low-risk factors compared with those with zero low-risk factors; for men, the difference was 12.2 years (95% CI, 10.1-14.2).ConclusionsAdopting a healthy lifestyle could substantially reduce premature mortality and prolong life expectancy in US adults.

Dataset Information

Potential impact of reduced tobacco use on life and health expectancies in Belgium.

Publications

Potential impact of reduced tobacco use on life and health expectancies in Belgium.

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