Statistical modeling and estimating number of healthy life years lost and healthy life expectancy in India, 2000–2019
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SUBMITTER: Jena D
PROVIDER: S-EPMC10792328 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
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Project description:BackgroundPrevious research has shown that people who have been diagnosed autistic are more likely to die prematurely than the general population. However, statistics on premature mortality in autistic people have often been misinterpreted. In this study we aimed to estimate the life expectancy and years of life lost experienced by autistic people living in the UK.MethodsWe studied people in the IQVIA Medical Research Database with an autism diagnosis between January 1, 1989 and January 16, 2019. For each participant diagnosed autistic, we included ten comparison participants without an autism diagnosis, matched by age, sex, and primary care practice. We calculated age- and sex-standardised mortality ratios comparing people diagnosed autistic to the reference group. We used Poisson regression to estimate age-specific mortality rates, and life tables to estimate life expectancy at age 18 and years of life lost. We analysed the data separately by sex, and for people with and without a record of intellectual disability. We discuss the findings in the light of the prevalence of recorded diagnosis of autism in primary care compared to community estimates.FindingsFrom a cohort of nearly 10 million people, we identified 17,130 participants diagnosed autistic without an intellectual disability (matched with 171,300 comparison participants), and 6450 participants diagnosed autistic with an intellectual disability (matched with 64,500 comparison participants). The apparent estimates indicated that people diagnosed with autism but not intellectual disability had 1.71 (95% CI: 1.39-2.11) times the mortality rate of people without these diagnoses. People diagnosed with autism and intellectual disability had 2.83 (95% CI: 2.33-3.43) times the mortality rate of people without these diagnoses. Likewise, the apparent reduction in life expectancy for people diagnosed with autism but not intellectual disability was 6.14 years (95% CI: 2.84-9.07) for men and 6.45 years (95% CI: 1.37-11.58 years) for women. The apparent reduction in life expectancy for people diagnosed with autism and intellectual disability was 7.28 years (95% CI: 3.78-10.27) for men and 14.59 years (95% CI: 9.45-19.02 years) for women. However, these findings are likely to be subject to exposure misclassification biases: very few autistic adults and older-adults have been diagnosed, meaning that we could only study a fraction of the total autistic population. Those who have been diagnosed may well be those with greater support needs and more co-occurring health conditions than autistic people on average.InterpretationThe findings indicate that there is a group of autistic people who experience premature mortality, which is of significant concern. There is an urgent need for investigation into the reasons behind this. However, our estimates suggest that the widely reported statistic that autistic people live 16-years less on average is likely incorrect. Nine out of 10 autistic people may have been undiagnosed across the time-period studied. Hence, the results of our study do not generalise to all autistic people. Diagnosed autistic adults, and particularly older adults, are likely those with greater-than-average support needs. Therefore, we may have over-estimated the reduction in life expectancy experienced by autistic people on average. The larger reduction in life expectancy for women diagnosed with autism and intellectual disability vs. men may in part reflect disproportionate underdiagnosis of autism and/or intellectual disability in women.FundingDunhill Medical Trust, Medical Research Council, National Institute for Health and Care Research, and the Royal College of Psychiatrists.
| S-EPMC10769892 | biostudies-literature
Project description:ObjectivesTo examine changes in Healthy Life Expectancy (HLE) against the backdrop of rising mortality among less-educated white Americans during the first decade of the twenty-first century.MethodsThis study documented changes in HLE by education among U.S. non-Hispanic whites, using data from the U.S. Multiple Cause of Death public-use files, the Integrated Public Use Microdata Sample (IPUMS) of the 2000 Census and the 2010 American Community Survey, and the Health and Retirement Study (HRS). Changes in HLE were decomposed into contributions from: (i) change in age-specific mortality rates; and (ii) change in disability prevalence, measured via Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL).ResultsBetween 2000 and 2010, HLE significantly decreased for white men and women with less than 12 years of schooling. In contrast, HLE increased among college-educated white men and women. Declines or stagnation in HLE among less-educated whites reflected increases in disability prevalence over the study period, whereas improvements among the college educated reflected decreases in both age-specific mortality rates and disability prevalence at older ages.DiscussionDifferences in HLE between education groups increased among non-Hispanic whites from 2000 to 2010. In fact, education-based differences in HLE were larger than differences in total life expectancy. Thus, the lives of less-educated whites were not only shorter, on average, compared with their college-educated counterparts, but they were also more burdened with disability.
| S-EPMC7813204 | biostudies-literature
Project description:BackgroundThis study aimed to quantify the contribution of narrowing the life expectancy gap between urban and rural areas to the overall life expectancy at birth in Korea and examine the age and death cause-specific contribution to changes in the life expectancy gap between urban and rural areas.MethodsWe used the registration population and death statistics from Statistics Korea from 2000 to 2019. Assuming two hypothetical scenarios, namely, the same age-specific mortality change rate in urban and rural areas and a 20% faster decline than the observed decline rate in rural areas, we compared the increase in life expectancy with the actual increase. Changes in the life expectancy gap between urban and rural areas were decomposed into age- and cause-specific contributions.ResultsRural disadvantages of life expectancy were evident. However, life expectancies in rural areas increased more rapidly than in urban areas. Life expectancy would have increased 0.3-0.5 less if the decline rate of age-specific mortality in small-to-middle urban and rural areas were the same as that of large urban areas. Life expectancy would have increased 0.7-0.9 years further if the decline rate of age-specific mortality in small-to-middle urban and rural areas had been 20% higher. The age groups 15-39 and 40-64, and chronic diseases, such as neoplasms and diseases of the digestive system, and external causes significantly contributed to narrowing the life expectancy gap between urban and rural areas.ConclusionPro-health equity interventions would be a good strategy to reduce the life expectancy gap and increase overall life expectancy, particularly in societies where life expectancies have already increased.
| S-EPMC10375755 | biostudies-literature
Project description:BackgroundKorea's life expectancy at birth has consistently increased in the 21st century. This study compared the age and cause-specific contribution to the increase in life expectancy at birth in Korea before and after 2010.MethodsThe population and death numbers by year, sex, 5-year age group, and cause of death from 2000 to 2019 were acquired. Life expectancy at birth was calculated using an abridged life table by sex and year. The annual age-standardized and age-specific mortality by cause of death was also estimated. Lastly, the age and cause-specific contribution to the increase in life expectancy at birth in the two periods were compared using a stepwise replacement algorithm.ResultsLife expectancy at birth in Korea increased consistently from 2010 to 2019, though slightly slower than from 2000 to 2009. The cause-specific mortality and life expectancy decomposition analysis showed a significant decrease in mortality in chronic diseases, such as neoplasms and diseases of the circulatory system, in the middle and old-aged groups. External causes, such as transport injuries and suicide, mortality in younger age groups also increased life expectancy. However, mortality from diseases of the respiratory system increased in the very old age group during 2010-2019.ConclusionsLife expectancy at birth in Korea continued to increase mainly due to decreased mortality from chronic diseases and external causes during the study period. However, the aging of the population structure increased vulnerability to respiratory diseases. The factors behind the higher death rate from respiratory disease should be studied in the future.
| S-EPMC10859017 | biostudies-literature
Project description:In population-based health research, the so-called population attributable fraction is an important quantity that calculates the percentage of excess risk of morbidity and mortality associated with modifiable risk factors for a given population. While the concept of "risk" is usually measured by event probabilities, in practice it may be of a more direct interest to know the excess life expectancy associated with the modifiable risk factors instead, particularly when mortality is of the ultimate concern. In this paper, we thus propose to study a novel quantity, termed "attributable life expectancy," to measure the population attributable fraction of life expectancy. We further develop a model-based approach for the attributable life expectancy under the Oakes-Dasu proportional mean residual life model, and establish its asymptotic properties for inferences. Numerical studies that includes Monte-Carlo simulations and an actual analysis of the mortality associated with smoking cessation in an Asia Cohort Consortium, are conducted to evaluate the performance of our proposed method.
| S-EPMC11580499 | biostudies-literature
Project description:BackgroundFew studies have investigated the change in life expectancy (LE) and the healthy lifespan among patients with advanced schistosomiasis. This study was to evaluate the LE and healthy life expectancy (HLE) for patients and assess the mechanism responsible for the LE inequality.MethodsWe utilized data from a dynamic advanced schistosomiasis cohort (10,362 patients) for the period from January 2008 to December 2019 in Hunan Province, China, to calculate the LEs of patients, and made a comparison with that of general population (19,642 schistosomiasis-free individuals) in the schistosomiasis endemic areas. LEs were estimated from 15 years of age by constructing period life tables. Arriaga's decomposition method was applied to quantify the influence of the age structure on the difference in LE. HLE for advanced schistosomiasis patients was calculated by using Sullivan method with age-specific disability weight. The LE and HLE were calculated for both males and females to perform further analyses on gender gap.ResultsThe estimated LE for advanced schistosomiasis patients aged 15-19 was 49.51 years (48.86 years for males and 51.07 years for females), which was 20.14 years lower compared with general population (69.65 years), and the LE gap between patients and general population decreased with age. The largest age-specific mortality contribution to the gap (32.06%) occurred at age 80-84 years. Women had a lower LE and HLE than men at age ≥ 60 years (both gender gaps in LE and HLE < 0). For advanced schistosomiasis patients, the gender gap in LE was largely attributed to the difference in mortality among those under the age of 55; the age-specific mortality in women exerted positive influence on the gap at age 25-64 and 75-79 years, with the contribution rate ranging from 0.59% to 57.02%, and made the negative contribution at other age groups.ConclusionsThe LE of advanced schistosomiasis patients was still much lower compared with general population. Strengthened prevention strategies and targeted treatments are needed to reduce morbidity and mortality due to advanced schistosomiasis, especially for younger population and elderly female patients.
| S-EPMC9883924 | biostudies-literature
Project description:BackgroundThe role of smoking in racial disparities in mortality and life expectancy in the United States has been examined previously, but up-to-date estimates are generally unavailable, even though smoking prevalence has declined in recent decades.ObjectiveWe estimate the contribution of smoking-attributable mortality to observed differences in mortality and life expectancy for US African-American and white adults from 2000-2019.MethodsThe indirect Preston-Glei-Wilmoth method was used with national vital statistics and population data and nationally representative never-smoker lung cancer death rates to estimate the smoking-attributable fraction (SAF) of deaths in the United States by sex-race group from 2000-2019. Mortality rates without smoking-attributable mortality were used to estimate life expectancy at age 50 (e 50) by group during the period.ResultsAfrican-American men had the highest estimated SAF during the period, beginning at 26.4% (95% CI:25.0%-27.8%) in 2000 and ending at 12.1% (95% CI:11.4%-12.8%) in 2019. The proportion of the difference in e 50 for white and African-American men that was due to smoking decreased from 27.7% to 14.8%. For African-American and white women, the estimated differences in e 50 without smoking-attributable mortality were similar to observed differences.ConclusionsSmoking continues to contribute to racial disparities in mortality and life expectancy among men in the United States.ContributionWe present updated estimates of the contribution of smoking to mortality differences in the United States using nationally representative data sources.
| S-EPMC9134211 | biostudies-literature
Project description:BackgroundInterpreting and utilizing the findings of nutritional research can be challenging to clinicians, policy makers, and even researchers. To make better decisions about diet, innovative methods that integrate best evidence are needed. We have developed a decision support model that predicts how dietary choices affect life expectancy (LE).Methods and findingsBased on meta-analyses and data from the Global Burden of Disease study (2019), we used life table methodology to estimate how LE changes with sustained changes in the intake of fruits, vegetables, whole grains, refined grains, nuts, legumes, fish, eggs, milk/dairy, red meat, processed meat, and sugar-sweetened beverages. We present estimates (with 95% uncertainty intervals [95% UIs]) for an optimized diet and a feasibility approach diet. An optimal diet had substantially higher intake than a typical diet of whole grains, legumes, fish, fruits, vegetables, and included a handful of nuts, while reducing red and processed meats, sugar-sweetened beverages, and refined grains. A feasibility approach diet was a midpoint between an optimal and a typical Western diet. A sustained change from a typical Western diet to the optimal diet from age 20 years would increase LE by more than a decade for women from the United States (10.7 [95% UI 8.4 to 12.3] years) and men (13.0 [95% UI 9.4 to 14.3] years). The largest gains would be made by eating more legumes (females: 2.2 [95% UI 1.1 to 3.4]; males: 2.5 [95% UI 1.1 to 3.9]), whole grains (females: 2.0 [95% UI 1.3 to 2.7]; males: 2.3 [95% UI 1.6 to 3.0]), and nuts (females: 1.7 [95% UI 1.5 to 2.0]; males: 2.0 [95% UI 1.7 to 2.3]), and less red meat (females: 1.6 [95% UI 1.5 to 1.8]; males: 1.9 [95% UI 1.7 to 2.1]) and processed meat (females: 1.6 [95% UI 1.5 to 1.8]; males: 1.9 [95% UI 1.7 to 2.1]). Changing from a typical diet to the optimized diet at age 60 years would increase LE by 8.0 (95% UI 6.2 to 9.3) years for women and 8.8 (95% UI 6.8 to 10.0) years for men, and 80-year-olds would gain 3.4 years (95% UI females: 2.6 to 3.8/males: 2.7 to 3.9). Change from typical to feasibility approach diet would increase LE by 6.2 (95% UI 3.5 to 8.1) years for 20-year-old women from the United States and 7.3 (95% UI 4.7 to 9.5) years for men. Using NutriGrade, the overall quality of evidence was assessed as moderate. The methodology provides population estimates under given assumptions and is not meant as individualized forecasting, with study limitations that include uncertainty for time to achieve full effects, the effect of eggs, white meat, and oils, individual variation in protective and risk factors, uncertainties for future development of medical treatments; and changes in lifestyle.ConclusionsA sustained dietary change may give substantial health gains for people of all ages both for optimized and feasible changes. Gains are predicted to be larger the earlier the dietary changes are initiated in life. The Food4HealthyLife calculator that we provide online could be useful for clinicians, policy makers, and laypeople to understand the health impact of dietary choices.
| S-EPMC8824353 | biostudies-literature
Project description:Background. Reference life expectancies inform frequently used health metrics, which play an integral role in determining resource allocation and health policy decision making. Existing reference life expectancies are not able to account for variation in geographies, populations, and disease states. Using a computer simulation, we developed a reference life expectancy estimation that considers competing causes of mortality, and is tailored to population characteristics. Methods. We developed a Monte Carlo microsimulation model that explicitly represented the top causes of US mortality in 2014 and the risk factors associated with their onset. The microsimulation follows a birth cohort of hypothetical individuals resembling the population of the United States. To estimate a reference life expectancy, we compared current circumstances with an idealized scenario in which all modifiable risk factors were eliminated and adherence to evidence-based therapies was perfect. We compared estimations of years of potential years life lost with alternative approaches. Results. In the idealized scenario, we estimated that overall life expectancy in the United States would increase by 5.9 years to 84.7 years. Life expectancy for men would increase from 76.4 years to 82.5 years, and life expectancy for women would increase from 81.3 years to 86.8 years. Using age-75 truncation to estimate potential years life lost compared to using the idealized life expectancy underestimated potential health gains overall (38%), disproportionately underestimated potential health gains for women (by 70%) compared to men (by 40%), and disproportionately underestimated the importance of heart disease for white women and black men. Conclusion. Mathematical simulations can be used to estimate an idealized reference life expectancy among a population to better inform and assess progress toward targets to improve population health.
| S-EPMC6360479 | biostudies-literature
Project description:BackgroundThe United States' opioid crisis is worsening, with the number of deaths reaching 81,806 in 2022 after more than tripling over the past decade. This study aimed to comprehensively characterize changes in burden of opioid overdose mortality in terms of life expectancy reduction and years of life lost between 2019 and 2022, including differential burden across demographic groups and the contribution of polysubstance use.MethodsUsing life tables and counts for all-cause and opioid overdose deaths from the National Center for Health Statistics, we constructed cause-eliminated life tables to estimate mortality by age in the absence of opioid-related deaths. We calculated the loss in life expectancy at birth (LLE) and total years of life lost (YLL) due to opioid overdose deaths by state of residency, sex, racial/ethnic group, and co-involvement of cocaine and psychostimulants.FindingsOpioid-related deaths in the US led to an estimated 3.1 million years of life lost in 2022 (38 years per death), compared to 2.0 million years lost in 2019. Relative to a scenario with no opioid mortality, we estimate that opioid-related deaths reduced life expectancy nationally by 0.67 years in 2022 vs 0.52 years in 2019. This LLE worsened in all racial/ethnic groups during the study period: 0.76 y-0.96 y for white men, 0.36 y-0.55 y for white women, 0.59 y-1.1 y for Black men, 0.27 y-0.53 y for Black women, 0.31 y-0.82 y for Hispanic men, 0.19 y-0.31 y for Hispanic women, 0.62 y-1.5 y for American Indian/Alaska Native (AI/AN) men, 0.43 y-1 y for AI/AN women, 0.09 y-0.2 y for Asian men, and 0.08 y-0.13 y for Asian women. Nearly all states experienced an increase in years of life lost (YLL) per capita from 2019 to 2022, with YLL more than doubling in 16 states. Cocaine or psychostimulants with abuse potential (incl. methamphetamines) were involved in half of all deaths and years of life lost in 2022, with substantial variation in the predominant drug class by state and racial/ethnic group.InterpretationThe burden of opioid-related mortality increased dramatically in the US between 2019 and 2022, coinciding with the period of the COVID-19 pandemic and the associated disruptions to social, economic, and health systems. Opioid overdose deaths are an important contributor to decreasing US life expectancy, and Black, Hispanic, and Native Americans now experience mortality burdens approaching or exceeding white Americans.FundingNone.
| S-EPMC11228948 | biostudies-literature