Future life expectancy in Europe taking into account the impact of smoking, obesity, and alcohol.
Ontology highlight
ABSTRACT:
SUBMITTER: Janssen F
PROVIDER: S-EPMC8337079 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundSmoking, obesity and alcohol abuse greatly affect mortality and exhibit a distinct time dynamic, with their prevalence and associated mortality rates increasing and (eventually) declining over time. Their combined impact on secular trends in life expectancy is unknown but is relevant for understanding these trends. We therefore estimate the combined impact of smoking, obesity and alcohol on life-expectancy trends in Europe.MethodsWe used estimated national age-specific smoking-, obesity- and alcohol-attributable mortality fractions for 30 European countries by sex, 1990-2014, which we aggregated multiplicatively to obtain lifestyle-attributable mortality. We estimated potential gains in life expectancy by eliminating lifestyle-attributable mortality and compared past trends in life expectancy at birth (e0) with and without lifestyle-attributable mortality. We examined all countries combined, by region and individually.ResultsAmong men, the combined impact of smoking, obesity and alcohol on e0 declined from 6.6 years in 1990 to 5.8 years in 2014, mainly due to declining smoking-attributable mortality. Among women, the combined impact increased from 1.9 to 2.3 years due to mortality increases in all three lifestyle-related factors. The observed increase in e0 over the 1990-2014 period was 5.0 years for men and 4.0 years for women. After excluding lifestyle-attributable mortality, this increase would have been 4.2-4.3 years for both men and women.ConclusionWithout the combined impact of smoking, obesity and alcohol, the increase over time in life expectancy at birth would have been smaller among men but larger among women, resulting in a stable increase in e0, parallel for men and women.
| S-EPMC8271206 | biostudies-literature
Project description:ObjectivesA policy model is a model that can evaluate the effectiveness and cost-effectiveness of interventions and inform policy decisions. In this study, we introduce a cardiovascular disease (CVD) policy model which can be used to model remaining life expectancy including a measure of socioeconomic deprivation as an independent risk factor for CVD.DesignA state transition model was developed using the Scottish Heart Health Extended Cohort (SHHEC) linked to Scottish morbidity and death records. Individuals start in a CVD-free state and can transit to three CVD event states plus a non-CVD death state. Individuals who have a non-fatal first event are then followed up until death. Taking a competing risk approach, the cause-specific hazards of a first event are modelled using parametric survival analysis. Survival following a first non-fatal event is also modelled parametrically. We assessed discrimination, validation and calibration of our model.ResultsOur model achieved a good level of discrimination in each component (c-statistics for men (women)-non-fatal coronary heart disease (CHD): 0.70 (0.74), non-fatal cerebrovascular disease (CBVD): 0.73 (0.76), fatal CVD: 0.77 (0.80), fatal non-CVD: 0.74 (0.72), survival after non-fatal CHD: 0.68 (0.67) and survival after non-fatal CBVD: 0.65 (0.66)). In general, our model predictions were comparable with observed event rates for a Scottish randomised statin trial population which has an overlapping follow-up period with SHHEC. After applying a calibration factor, our predictions of life expectancy closely match those published in recent national life tables.ConclusionsOur model can be used to estimate the impact of primary prevention interventions on life expectancy and can assess the impact of interventions on inequalities.
| S-EPMC4316925 | biostudies-literature
Project description:BackgroundSmoking and obesity are 2 modifiable risk factors for disability. We examine the impact of smoking and obesity on disability-free life expectancy (DFLE) at older ages, using 2 levels of disability.MethodWe used the DYNOPTA dataset, derived by harmonizing and pooling risk factors and disability outcomes from 5 Australian longitudinal aging studies. We defined mobility disability as inability to walk 1 km, and more severe (activities of daily living [ADL]) disability by the inability to dress or bathe. Mortality data for the analytic sample (N = 20 401; 81.2% women) were obtained from Government Records via data linkage. We estimated sex-specific total life expectancy, DFLE, and years spent with disability by Interpolated Markov Chain (IMaCh) software for each combination of smoking (never vs ever), obesity (body mass index ≥30 vs 18.5 to <30), and education (left school age 14 or younger vs age 15 or older).ResultsCompared to those without either risk factor, high educated nonobese smokers at age 65 lived shorter lives (men and women: 2.5 years) and fewer years free of mobility disability (men: 2.1 years; women: 2.0 years), with similar results for ADL disability. Obesity had the largest effect on mobility disability in women; high educated obese nonsmoking women lived 1.3 years less than nonsmoking, not obese women but had 5.1 years fewer free of mobility disability and 3.2 fewer free of ADL disability. Differences between risk factor groups were similar for the low educated.ConclusionsOur findings suggest eliminating obesity would lead to an absolute reduction of disability, particularly in women.
| S-EPMC8202145 | biostudies-literature
Project description:We estimate the effects of declining smoking and increasing obesity on mortality in the United States over the period 2010-2040. Data on cohort behavioral histories are integrated into these estimates. Future distributions of body mass indices are projected using transition matrices applied to the initial distribution in 2010. In addition to projections of current obesity, we project distributions of obesity when cohorts are age 25. To these distributions, we apply death rates by current and age-25 obesity status observed in the National Health and Nutrition Examination Survey, 1988-2006. Estimates of the effects of smoking changes are based on observed relations between cohort smoking patterns and cohort death rates from lung cancer. We find that changes in both smoking and obesity are expected to have large effects on U.S. mortality. For males, the reductions in smoking have larger effects than the rise in obesity throughout the projection period. By 2040, male life expectancy at age 40 is expected to have gained 0.83 years from the combined effects. Among women, however, the two sets of effects largely offset one another throughout the projection period, with a small gain of 0.09 years expected by 2040.
| S-EPMC4495773 | biostudies-literature
Project description:BackgroundAlthough increases in obesity over the past 30 years have adversely affected the health of the U.S. population, there have been concomitant improvements in health because of reductions in smoking. Having a better understanding of the joint effects of these trends on longevity and quality of life will facilitate more efficient targeting of health care resources.MethodsFor each year from 2005 through 2020, we forecasted life expectancy and quality-adjusted life expectancy for a representative 18-year-old, assuming a continuation of past trends in smoking (based on data from the National Health Interview Survey for 1978 through 1979, 1990 through 1991, 1999 through 2001, and 2004 through 2006) and past trends in body-mass index (BMI) (based on data from the National Health and Nutrition Examination Survey for 1971 through 1975, 1988 through 1994, 1999 through 2002, and 2003 through 2006). The 2003 Medical Expenditure Panel Survey was used to examine the effects of smoking and BMI on health-related quality of life.ResultsThe negative effects of increasing BMI overwhelmed the positive effects of declines in smoking in multiple scenarios. In the base case, increases in the remaining life expectancy of a typical 18-year-old are held back by 0.71 years or 0.91 quality-adjusted years between 2005 and 2020. If all U.S. adults became nonsmokers of normal weight by 2020, we forecast that the life expectancy of an 18-year-old would increase by 3.76 life-years or 5.16 quality-adjusted years.ConclusionsIf past obesity trends continue unchecked, the negative effects on the health of the U.S. population will increasingly outweigh the positive effects gained from declining smoking rates. Failure to address continued increases in obesity could result in an erosion of the pattern of steady gains in health observed since early in the 20th century.
| S-EPMC4394736 | biostudies-literature
Project description:IntroductionSmoking contributes substantially to mortality levels and trends. Its role in country differences in mortality has, however, hardly been quantified. The current study formally assesses the-so far unknown-changing contribution of smoking to country differences in life expectancy at birth (e0) across Europe.MethodsUsing all-cause mortality data and indirectly estimated smoking-attributable mortality rates by age and sex for 30 European countries from 1985 to 2014, the differences in e0 between each individual European country and the weighted average were decomposed into a smoking- and a nonsmoking-related part.ResultsIn 2014, e0 ranged from 70.8 years in Russia to 83.1 years in Switzerland. Men exhibited larger country differences than women (variance of 21.9 and 7.0 years, respectively). Country differences in e0 increased up to 2005 and declined thereafter. Among men, the average contribution of smoking to the country differences in e0 was highest around 1990 (47%) and declined to 35% in 2014. Among women, the average relative contribution of smoking declined from 1991 to 2011, and smoking resulted in smaller differences with the average e0 level in the majority of European countries. For both sexes combined, the contribution of smoking to country differences in e0 was higher than 20% throughout the period.ConclusionsSmoking contributed substantially to the country differences in e0 in Europe, their increases up to 1991, and their decreases since 2005, especially among men. Policies that discourage smoking can help to reduce inequalities in mortality levels across Europe in the long run.ImplicationsSmoking contributes substantially to country differences in life expectancy at birth (e0) in Europe, particularly among men, for whom the contribution was highest around 1990 (47%) and declined to 35% in 2014. In line with the anticipated progression of the smoking epidemic, the differences between European countries in e0 due to smoking are expected to further decline among men, but to increase among women. The role of smoking in mortality convergence since 2005 illustrates that smoking policies can help to reduce inequalities in life expectancy levels across Europe, particularly when they target smoking in countries with low e0.
| S-EPMC7789949 | biostudies-literature
Project description: Not available
| S-EPMC518904 | biostudies-literature
Project description:This article provides a detailed and overarching illustration of the contribution of smoking to sex differences in life expectancy at birth (e0) in Europe, focusing on changes over time and differences between both European countries and European regions. For this purpose, the sex difference in e0 for 31 European countries over the 1950-2014 period was decomposed into a smoking- and a non-smoking-related part, using all-cause mortality data and indirectly estimated smoking-attributable mortality rates by age and sex, and a formal decomposition analysis. It was found that smoking-attributable mortality contributed, on average, 3 years (43.5%) to the 7-year life expectancy difference between women and men in 2014. This contribution, was largest in 1995, at 5.2 out of 9.0 years, and subsequently declined in parallel with the average sex difference in life expectancy. The average contribution of smoking-attributable mortality was especially large in North-Western Europe around 1975; in Southern Europe around 1985; and in Eastern Europe around 1990-1995, when smoking-attributable mortality reached maximum levels among men, but was still low among women. The observed parallel decline from 1995 onwards in the sex differences in e0 and the absolute contribution of smoking to this sex difference suggests that this recent decline in the sex difference in e0 can be almost fully explained by historical changes in sex differences in smoking, and, consequently, smoking-attributable mortality. In line with the progression of the smoking epidemic, the sex differences in life expectancy in Europe are expected to further decline in the future.
| S-EPMC7524860 | biostudies-literature
Project description:The aim of this study was to provide decision makers with an assessment of potential future health effects of interventions against overweight and obesity (OWOB). By means of the DYNAMO-HIA tool we conducted a health impact assessment simulating future prevented disease (ischemic heart disease (IHD), diabetes, stroke, and multi morbidity) incidence, prevalence and life expectancy (LE) related to a scenario where OWOB is reduced by 25% and a scenario where obesity is eliminated. The study covered projected number of persons living in Copenhagen, Denmark during year 2014-2040 (n 2040 = 742,129). Reducing the proportion of men/women with OWOB with 25% will increase population LE by 2.4/1.2 months and at the same time decrease LE with diabetes by 3.1/2.2 months. As a result of eliminating obesity, total LE will increase by 6.0/3.6 months and LE with diabetes will decrease with 9.8/10.3 months for men/women. We found no important effects on LE with IHD and stroke. This illustrates that the positive effects of lowering OWOB levels on IHD and stroke incidence is offset due to increasing total LE. Although the population of Copenhagen is relatively lean, reducing obesity levels will result in significant benefits for population cardiometabolic health status and LE. Future public health prevention programs may use the results as reference data for potential impact of reductions in OWOB.
| S-EPMC7358723 | biostudies-literature
Project description:Cardiovascular disease and non-AIDS malignancies have become major causes of death among HIV-infected individuals. The relative impact of lifestyle and HIV-related factors are debated.We estimated associations of smoking with mortality more than 1 year after antiretroviral therapy (ART) initiation among HIV-infected individuals enrolled in European and North American cohorts. IDUs were excluded. Causes of death were assigned using standardized procedures. We used abridged life tables to estimate life expectancies. Life-years lost to HIV were estimated by comparison with the French background population.Among 17,995 HIV-infected individuals followed for 79,760 person-years, the proportion of smokers was 60%. The mortality rate ratio (MRR) comparing smokers with nonsmokers was 1.94 [95% confidence interval (95% CI) 1.56-2.41]. The MRRs comparing current and previous smokers with never smokers were 1.70 (95% CI 1.23-2.34) and 0.92 (95% CI 0.64-1.34), respectively. Smokers had substantially higher mortality from cardiovascular disease, non-AIDS malignancies than nonsmokers [MRR 6.28 (95% CI 2.19-18.0) and 3.31 (95% CI 1.80-5.45), respectively]. [corrected]. Among 35-year-old HIV-infected men, the loss of life-years associated with smoking and HIV was 7.9 (95% CI 7.1-8.7) and 5.9 (95% CI 4.9-6.9), respectively. The life expectancy of virally suppressed, never-smokers was 43.5 years (95% CI 41.7-45.3), compared with 44.4 years among 35-year-old men in the background population. Excess MRRs/1000 person-years associated with smoking increased from 0.6 (95% CI -1.3 to 2.6) at age 35 to 43.6 (95% CI 37.9-49.3) at age at least 65 years.Well treated HIV-infected individuals may lose more life years through smoking than through HIV. Excess mortality associated with smoking increases markedly with age. Therefore, increases in smoking-related mortality can be expected as the treated HIV-infected population ages. Interventions for smoking cessation should be prioritized.
| S-EPMC4284008 | biostudies-other