Smoking, life expectancy, and chronic disease in South Korea, Singapore, and the United States: A microsimulation model.
Ontology highlight
ABSTRACT:
SUBMITTER: Kim D
PROVIDER: S-EPMC7269831 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
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:BackgroundGeographic inequality in US mortality has increased rapidly over the last 25 years, particularly between metropolitan and nonmetropolitan areas. These gaps are sizeable and rival life expectancy differences between the US and other high-income countries. This study determines the contribution of smoking, a key contributor to premature mortality in the US, to geographic inequality in mortality over the past quarter century.MethodsWe used death certificate and census data covering the entire US population aged 50+ between Jan 1, 1990 and Dec 31, 2019. We categorized counties into 40 geographic areas cross-classified by region and metropolitan category. We estimated life expectancy at age 50 and the index of dissimilarity for mortality, a measure of inequality in mortality, with and without smoking for these areas in 1990-1992 and 2017-2019. We estimated the changes in life expectancy levels and percent change in inequality in mortality due to smoking between these periods.ResultsWe find that the gap in life expectany between metros and nonmetros increased by 2.17 years for men and 2.77 years for women. Changes in smoking-related deaths are responsible for 19% and 22% of those increases, respectively. Among the 40 geographic areas, increases in life expectancy driven by changes in smoking ranged from 0.91 to 2.34 years for men while, for women, smoking-related changes ranged from a 0.61-year decline to a 0.45-year improvement. The most favorable trends in years of life lost to smoking tended to be concentrated in large central metros in the South and Midwest, while the least favorable trends occurred in nonmetros in these same regions. Smoking contributed to increases in mortality inequality for men aged 70+, with the contribution ranging from 8 to 24%, and for women aged 50-84, ranging from 14 to 44%.ConclusionsMortality attributable to smoking is declining fastest in large cities and coastal areas and more slowly in nonmetropolitan areas of the US. Increasing geographic inequalities in mortality are partly due to these geographic divergences in smoking patterns over the past several decades. Policies addressing smoking in non-metropolitan areas may reduce geographic inequality in mortality and contribute to future gains in life expectancy.
| S-EPMC9490306 | biostudies-literature
Project description:OBJECTIVES:Existing literature shows religion is associated with health and survival separately. We extend this literature by considering health and survival together using a multistate life table approach to estimate total, disability-free, and disabled life expectancy (LE), separately for women and men, for 2 disability measures, and by 2 indicators of religion. METHOD:Data come from the Health and Retirement Study (1998-2014 waves). Predictors include importance of religion and attendance at religious services. The disability measures are defined by ADLs and IADLs. Models control for sociodemographic and health covariates. RESULTS:Attendance at religious services shows a strong and consistent association with life and health expectancy. Men and women who attend services at least once a week (compared with those who attend less frequently or never) have between 1.1 and 5.1 years longer total LE and between 1.0 and 4.3 years longer ADL disability-free LE. Findings for IADL disability are similar. Importance of religion is related to total and disabled LE (both ADL and IADL), but the differentials are smaller and less consistent. Controlling for sociodemographic and health factors does not explain these associations. DISCUSSION:By estimating total, disability-free, and disabled LE, we are able to quantify the advantage of religion for health. Results are consistent with previous studies that have focused on health and mortality separately.
| S-EPMC6941211 | biostudies-literature
Project description:Importance:US life expectancy has not kept pace with that of other wealthy countries and is now decreasing. Objective:To examine vital statistics and review the history of changes in US life expectancy and increasing mortality rates; and to identify potential contributing factors, drawing insights from current literature and an analysis of state-level trends. Evidence:Life expectancy data for 1959-2016 and cause-specific mortality rates for 1999-2017 were obtained from the US Mortality Database and CDC WONDER, respectively. The analysis focused on midlife deaths (ages 25-64 years), stratified by sex, race/ethnicity, socioeconomic status, and geography (including the 50 states). Published research from January 1990 through August 2019 that examined relevant mortality trends and potential contributory factors was examined. Findings:Between 1959 and 2016, US life expectancy increased from 69.9 years to 78.9 years but declined for 3 consecutive years after 2014. The recent decrease in US life expectancy culminated a period of increasing cause-specific mortality among adults aged 25 to 64 years that began in the 1990s, ultimately producing an increase in all-cause mortality that began in 2010. During 2010-2017, midlife all-cause mortality rates increased from 328.5 deaths/100 000 to 348.2 deaths/100 000. By 2014, midlife mortality was increasing across all racial groups, caused by drug overdoses, alcohol abuse, suicides, and a diverse list of organ system diseases. The largest relative increases in midlife mortality rates occurred in New England (New Hampshire, 23.3%; Maine, 20.7%; Vermont, 19.9%) and the Ohio Valley (West Virginia, 23.0%; Ohio, 21.6%; Indiana, 14.8%; Kentucky, 14.7%). The increase in midlife mortality during 2010-2017 was associated with an estimated 33 307 excess US deaths, 32.8% of which occurred in 4 Ohio Valley states. Conclusions and Relevance:US life expectancy increased for most of the past 60 years, but the rate of increase slowed over time and life expectancy decreased after 2014. A major contributor has been an increase in mortality from specific causes (eg, drug overdoses, suicides, organ system diseases) among young and middle-aged adults of all racial groups, with an onset as early as the 1990s and with the largest relative increases occurring in the Ohio Valley and New England. The implications for public health and the economy are substantial, making it vital to understand the underlying causes.
| S-EPMC7146991 | biostudies-literature
Project description:BACKGROUND:During the previous century the average lifespan in the United States (US) increased by over 30 years, with much of this increase attributed to public health initiatives. This report examines further gains that might be achieved through reduced occurrence of injury-related death. METHODS:US life tables and injury death rate data were used to estimate potential increases in life expectancy assuming various reductions in the rate of fatal injuries. Corresponding numbers of deaths potentially averted annually were also estimated; unit (per death) medical and lifetime work loss costs were employed to estimate total costs potentially averted annually. RESULTS:Through elimination of injury as a cause of death, average US life expectancy at birth could be increased by approximately 1.5 years, with notable variations by sex, ethnicity, and race. More conservatively, average life expectancy at birth could be increased by 0.41 years assuming that the national injury death rate could be brought into line with the lowest state-specific rate. Under this more conservative but plausible assumption, an estimated 48,400 injury deaths and $61 billion in medical and work loss costs would be averted annually. CONCLUSIONS:Increases in life expectancy of the magnitude considered in this report are arguably attainable based on long-term historical reductions in the US injury death rate, as well as significant continuing reductions seen in other developed countries. Contemporary evidence-based interventions can play an important role in reducing injury-related deaths, such as those due to drug overdoses and older adult falls, as well as suicides.
| S-EPMC5577772 | biostudies-literature
Project description:Introduction:Although end-stage renal disease (ESRD) and surrogate markers for renal dysfunction are frequently used as outcome markers for IgA nephropathy, the clinical course after reaching ESRD is not well documented. This study examined outcomes of progression to ESRD and age at death in a cohort of adults with IgA nephropathy with a long duration of follow-up. Methods:Patient and kidney survival of 251 adult patients with IgA nephropathy from the southeastern United States diagnosed between January 1, 1976 and December 31, 2005 were analyzed. Results:Median age at diagnosis was 36.9 years. Most patients were men (69%) and Caucasian (95%). Only 46% had an estimated glomerular filtration rate >60 ml/min per 1.73 m2 at diagnosis. Mean follow-up time from time of diagnostic biopsy to death or end of study was 19.3 years. Of 251 patients, 132 (53%) progressed to ESRD and 97 (39%) died. Life expectancy was reduced by 10.1 years, with a median observed age of death at 65.7 years and a median expected age at death of 75.8 years. Eighty-three percent of the deaths occurred after progression to ESRD. Conclusion:Life expectancy is substantially reduced for patients diagnosed with IgA nephropathy in the southeastern United States.
| S-EPMC5762959 | biostudies-literature
Project description:ImportanceThe relationship between income and life expectancy is well established but remains poorly understood.ObjectivesTo measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation.Design and settingIncome data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy.ExposurePretax household earnings as a measure of income.Main outcomes and measuresRelationship between income and life expectancy; trends in life expectancy by income group; geographic variation in life expectancy levels and trends by income group; and factors associated with differences in life expectancy across areas.ResultsThe sample consisted of 1,408,287,218 person-year observations for individuals aged 40 to 76 years (mean age, 53.0 years; median household earnings among working individuals, $61,175 per year). There were 4,114,380 deaths among men (mortality rate, 596.3 per 100,000) and 2,694,808 deaths among women (mortality rate, 375.1 per 100,000). The analysis yielded 4 results. First, higher income was associated with greater longevity throughout the income distribution. The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% (P < .001 for the differences for both sexes). Third, life expectancy for low-income individuals varied substantially across local areas. In the bottom income quartile, life expectancy differed by approximately 4.5 years between areas with the highest and lowest longevity. Changes in life expectancy between 2001 and 2014 ranged from gains of more than 4 years to losses of more than 2 years across areas. Fourth, geographic differences in life expectancy for individuals in the lowest income quartile were significantly correlated with health behaviors such as smoking (r = -0.69, P < .001), but were not significantly correlated with access to medical care, physical environmental factors, income inequality, or labor market conditions. Life expectancy for low-income individuals was positively correlated with the local area fraction of immigrants (r = 0.72, P < .001), fraction of college graduates (r = 0.42, P < .001), and government expenditures (r = 0.57, P < .001).Conclusions and relevanceIn the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time. However, the association between life expectancy and income varied substantially across areas; differences in longevity across income groups decreased in some areas and increased in others. The differences in life expectancy were correlated with health behaviors and local area characteristics.
| S-EPMC4866586 | biostudies-literature
Project description:Wage theft - employers not paying workers their legally entitled wages and benefits - costs workers billions of dollars annually. We tested whether preventing wage theft could increase U.S. life expectancy and decrease inequities therein. We obtained nationally representative estimates of the 2001-2014 association between income and expected age at death for 40-year-olds (40 plus life expectancy at age 40) compiled from tax and Social Security Administration records, and estimates of the burden of wage theft from several sources, including estimates regarding minimum-wage violations (not paying workers the minimum wage) developed from Current Population Survey data. After modeling the relationship between income and expected age at death, we simulated the effects of scenarios preventing wage theft on mean expected age at death, assuming a causal effect of income on expected age at death. We simulated several scenarios, including one using data suggesting minimum-wage violations constituted 38% of all wage theft and caused 58% of affected workers' losses. Among women in the lowest income decile, mean expected age at death was 0.17 years longer in the counterfactual scenario than observed (95% confidence interval [CI]: 0.11-0.22), corresponding to 528,685 (95% CI: 346,018-711,353) years extended in the total 2001-2014 age-40 population. Among men in the lowest decile, the estimates were 0.12 (95% CI: 0.07-0.17) and 380,502 (95% CI: 229,630-531,374). Moreover, among women, mean expected age at death in the counterfactual scenario increased 0.16 (95% CI: 0.06-0.27) years more among the lowest decile than among the highest decile; among men, the estimate was 0.12 (95% CI: 0.03-0.21).
| S-EPMC9246227 | biostudies-literature
Project description:The educational gradient in life expectancy is well documented in the United States and in other low-mortality countries. Highly educated Americans, on average, live longer than their low-educated counterparts, who have recently seen declines in adult life expectancy. However, limiting the discussion on lifespan inequality to mean differences alone overlooks other dimensions of inequality and particularly disparities in lifespan variation. The latter represents a unique form of inequality, with higher variation translating into greater uncertainty in the time of death from an individual standpoint, and higher group heterogeneity from a population perspective. Using data from the National Vital Statistics System from 1990 to 2010, this is the first study to document trends in both life expectancy and S25--the standard deviation of age at death above 25--by educational attainment. Among low-educated whites, adult life expectancy declined by 3.1 years for women and by 0.6 years for men. At the same time, S25 increased by about 1.5 years among high school-educated whites of both genders, becoming an increasingly important component of total lifespan inequality. By contrast, college-educated whites benefited from rising life expectancy and record low variation in age at death, consistent with the shifting mortality scenario. Among blacks, adult life expectancy increased, and S25 plateaued or declined in nearly all educational attainment groups, although blacks generally lagged behind whites of the same gender on both measures. Documenting trends in lifespan variation can therefore improve our understanding of lifespan inequality and point to diverging trajectories in adult mortality across socioeconomic strata.
| S-EPMC4819799 | biostudies-literature
Project description:Interval-censored longitudinal data taken from a Norwegian study of individuals with Parkinson's disease are investigated with respect to the onset of dementia. Of interest are risk factors for dementia and the subdivision of total life expectancy (LE) into LE with and without dementia. To estimate LEs using extrapolation, a parametric continuous-time 3-state illness-death Markov model is presented in a Bayesian framework. The framework is well suited to allow for heterogeneity via random effects and to investigate additional computation using model parameters. In the estimation of LEs, microsimulation is used to take into account random effects. Intensities of moving between the states are allowed to change in a piecewise-constant fashion by linking them to age as a time-dependent covariate. Possible right censoring at the end of the follow-up can be incorporated. The model is applicable in many situations where individuals are followed over a long time period. In describing how a disease develops over time, the model can help to predict future need for health care.
| S-EPMC2742499 | biostudies-literature