Occupation-Based Life Expectancy: Actuarial Fairness in Determining Statutory Retirement Age.
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ABSTRACT:
SUBMITTER: Deeg DJH
PROVIDER: S-EPMC8419329 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Retirement years are ideally spent in good health. We aimed to produce new information using person-oriented methods by identifying groups of statutory retirees who did or did not achieve this objective and the factors that distinguish these groups from each other. Our particular focus was on the years directly after the transition into retirement, and the pre-retirement factors that explained the development of health, using a more severe health-related outcome-hospitalization. We studied the retirement, hospitalizations, education, and work characteristics of former employees of the City of Helsinki, Finland (N = 6569), from complete registers. We used group-based trajectory models and identified groups of constant low, constant high, decreasing, and temporarily occurring hospitalizations, and one group of increasing hospitalizations among women and two groups of earlier and later increasing hospitalizations among men. Multinomial regression models showed that among women, belonging to groups with less favourable health was associated with secondary education, older age at retirement, and reduced working hours. Education and work characteristics before retirement both contribute to the development of health, as indicated by hospitalizations directly after retirement. Our findings show that socioeconomic inequalities in health are persistent and should also be addressed after transition into retirement.
| S-EPMC10613168 | biostudies-literature
Project description:Subjective life expectancy (SLE) has been found to show a significant association with mortality. In this study, we aimed to investigate the major factors affecting SLE. We also examined whether any differences existed between SLE and actuarial life expectancy (LE) in Korea.A cross-sectional survey of 1000 individuals in Korea aged 20-59 was conducted. Participants were asked about SLE via a self-reported questionnaire. LE from the National Health Insurance database in Korea was used to evaluate differences between SLE and actuarial LE. Age-adjusted least-squares means, correlations, and regression analyses were used to test the relationship of SLE with four categories of predictors: demographic factors, socioeconomic factors, health behaviors, and psychosocial factors.Among the 1000 participants, women (mean SLE, 83.43 years; 95% confidence interval, 82.41 to 84.46 years; 48% of the total sample) had an expected LE 1.59 years longer than that of men. The socioeconomic factors of household income and housing arrangements were related to SLE. Among the health behaviors, smoking status, alcohol status, and physical activity were associated with SLE. Among the psychosocial factors, stress, self-rated health, and social connectedness were related to SLE. SLE had a positive correlation with actuarial estimates (r=0.61, p<0.001). Gender, household income, history of smoking, and distress were related to the presence of a gap between SLE and actuarial LE.Demographic factors, socioeconomic factors, health behaviors, and psychosocial factors showed significant associations with SLE, in the expected directions. Further studies are needed to determine the reasons for these results.
| S-EPMC5541275 | biostudies-other
Project description:BackgroundHealthy life expectancy (HLE) is becoming an important indicator of population health. While actuarial estimates of HLE are frequently studied, there is scarcity of research on the subjective expectations of people about their HLE. The objective of this study is to compare actuarial and subjective HLE (sHLE) estimates in the ≥50-year-old Hungarian general population. Furthermore, we assessed subjective life expectancy (sLE) and explored determinants of the individual variance of sHLE and sLE.MethodsWe conducted a cross-sectional online survey in 2019. Subjective health expectations were measured at 60, 70, 80 and 90 years of age via the Global Activity Limitation Indicator (GALI). Point-estimates of sLE and background variables were also recorded. sHLE was estimated from GALI and sLE responses. Actuarial estimates of life expectancy (LE) and HLE for 2019 were provided by the Central Statistical Office of Hungary.ResultsFive hundred and four respondents (female 51.6%) were included. Mean (±SD) age was 63 (±7.5) years. Median LE (81.5 years, 95%CI 81.1-81.7) and sLE (82 years, 95%CI 80-85) were similar (p = 0.142), while median sHLE (66.8 years, 95%CI 65.5-68.3) was lower than HLE (72.7 years, 95%CI 82.4-82.9) by 5.9 years (p<0.001). Despite the greater median actuarial LE of women compared to men (p<0.001), we found no gender differences between the median sLE (p = 0.930), HLE (p = 0.417) and sHLE (p = 0.403) values. With less apparent gender differences among the predictors when compared to sLE, sHLE was mainly determined by self-perceived health, age and place of residence, while self-perceived health, close relatives' longevity, social conditions, happiness and perceived lifestyle influenced sLE.ConclusionsAlong subjective life expectancy, subjective healthy life expectancy may be a feasible indicator and provide insights to individuals' subjective expectations underlying the demographic estimates of the healthy life expectancy of the population.
| S-EPMC8912206 | biostudies-literature
Project description:The identification of genes and interventions that slow or reverse aging is hampered by the lack of non-invasive metrics that can predict the life expectancy of pre-clinical models. Frailty Indices (FIs) in mice are composite measures of health that are cost-effective and non-invasive, but whether they can accurately predict health and lifespan is not known. Here, mouse FIs are scored longitudinally until death and machine learning is employed to develop two clocks. A random forest regression is trained on FI components for chronological age to generate the FRIGHT (Frailty Inferred Geriatric Health Timeline) clock, a strong predictor of chronological age. A second model is trained on remaining lifespan to generate the AFRAID (Analysis of Frailty and Death) clock, which accurately predicts life expectancy and the efficacy of a lifespan-extending intervention up to a year in advance. Adoption of these clocks should accelerate the identification of longevity genes and aging interventions.
| S-EPMC7492249 | biostudies-literature
Project description:BackgroundHuman life expectancy continues to rise in most populations. This rise not only leads to longer lives but also is accompanied by improved health at a given age, that is, recent cohorts show a reduction of biological age for a given chronological age. Despite or even because of the diversity of biomarkers of aging, an accurate quantification of a general shift in biological age across time has been challenging.MethodsHere, we compared age perception of facial images taken in 2001 over a decade and related these changes in age perception to changes in life expectancy.ResultsWe show that age perception changes substantially across time and parallels the progress in life expectancy. In 2012, people aged more than 70 years needed to look 2.3 years younger to be rated the same age as in 2002.ConclusionsOur results suggest that age perception reflects the past life events better than predicts future length of life, that is, it is written in your face how much you have aged so far. We draw this conclusion as age perception among elderly individuals paralleled changes in life expectancy at birth but not changes in remaining life expectancies. We suggest that changes in age perception should be explored for younger age classes to inform on aging processes, including whether aging is delayed or slowed with increasing life expectancy.
| S-EPMC7530473 | biostudies-literature
Project description:BackgroundInequalities in mortality are often attributed to socioeconomic differences in education level, income, and wealth. Low socioeconomic status (SES) is generally related to worse health and survival across the life course. Yet, disadvantaged people are also more likely to hold jobs requiring heavy physical labor, repetitive movement, ergonomic strain, and safety hazards.ObjectiveWe examine the link between primary lifetime occupation, together with education and net worth, on survival among older adults in Mexico.MethodsWe use data from four waves (2001, 2003, 2012, and 2015) of the Mexican Health and Aging Study (MHAS). We estimate age-specific mortality rates for ages 50 and over using a hazards model based on a two-parameter Gompertz function.ResultsPrimary lifetime occupations have a stronger association with survival for women than men. Women with higher socioeconomic status have significantly lower mortality rates than lower status women, whether SES is assessed in terms of schooling, wealth, or occupation. Occupational categories are not jointly related to survival among men, even without controls for education and wealth. There are significant survival differences by wealth among men, but no disparities in mortality by education.ConclusionsConsistent with recent studies of the Mexican population, we fail to find the expected gradient in the association between some measures of SES and better survival among men.ContributionOur estimates extend this anomalous pattern among Mexican men to another dimension of SES, occupation. SES differentials in mortality are substantially larger for Mexican women, highlighting an important gender disparity.
| S-EPMC9917739 | biostudies-literature
Project description:BackgroundKnowledge about the expected life years gained from intensive care unit (ICU) admission could inform priority-setting decisions across groups of ICU patients and across medical specialties. The aim of this study was to estimate expected remaining lifetime for patients admitted to ICUs during 2008-2010 and to estimate the gain in life years from ICU admission.MethodsThis is a descriptive, population modelling study of 30,712 adult mixed ICU admissions from the Norwegian Intensive Care Registry. The expected remaining lifetime for each patient was estimated using a decision-analytical model. Transition probabilities were based on registered Simplified Acute Physiology Score (SAPS) II, and standard and adjusted Norwegian life-tables.ResultsThe hospital mortality was 19.4% (n = 5,958 deaths). 24% of the patients were estimated to die within the first year after ICU admission in our model. Under an intermediate (base case), optimistic (O), and pessimistic (P) scenario with respect to long-term mortality, the average expected remaining lifetime was 19.4, 19.9, and 12.7 years. The majority of patients had a life expectancy of more than five years (84.8% in the base case, 89.4% in scenario O, and 55.6% in scenario P), and few had a life expectancy of less than one year (0.7%, 0.1%, and 12.7%). The incremental gain from ICU admission compared to counterfactual general ward care was estimated to be 0.04 (scenario P, age 85+) to 1.14 (scenario O, age < 45) extra life years per patient.ConclusionsOur research demonstrated a novel way of using routinely collected registry data to estimate and evaluate the expected lifetime outcomes for ICU patients upon admission. The majority had high life expectancies. The youngest age groups seemed to benefit the most from ICU admission. The study raises the question whether availability and rationing of ICU services are too strict in Norway.
| S-EPMC4444302 | biostudies-literature
Project description:The population of older cancer survivors in the United States is rapidly growing. However, little is currently known about how the health of older cancer survivors has changed over time and across successive birth cohorts. Using data from the US Health and Retirement Study, we parameterized a demographic microsimulation model to compare partial cohort life expectancy (LE) and disability-free LE for US men and women without cancer and with prevalent and incident cancer diagnoses for 4 successive 10-year birth cohorts, born 1918-1927 to 1948-1957. Disability was defined as being disabled in ≥1 activity of daily living. These cohorts had midpoint ages of 55-64, 65-74, and 75-84 years during the periods 1998-2008 (the "early" period) and 2008-2018 (the "later" period). Across all cohorts and periods, those with incident cancer had the lowest LE, followed by those with prevalent cancer and cancer-free individuals. We observed declines in partial LE and an expansion of life spent disabled among more recent birth cohorts of prevalent-cancer survivors. Our findings suggest that advances in treatments that prolong life for individual cancer patients may have led to population-level declines in conditional LE and disability-free LE across successive cohorts of older cancer survivors.
| S-EPMC8751799 | biostudies-literature
Project description:Objective: To characterize miRNAs in 41-year archived plasma in relation to life expectancy independent of genes. Method: Plasma miRNAs from nine identical male twins were profiled using next-generation sequencing. Results: The average absolute difference in the minimum life expectancy was 9.68 years. Intra-class correlation coefficients were above 0.4 for 50% of miRNAs. Comparing deceased twins with their alive co-twin brothers, the concentrations were increased for 34 but decreased for 30 miRNAs. Conclusion: Identical twins discordant in life expectancy were unlike in the majority of miRNAs, suggesting that environmental factors are pivotal in miRNAs related to life expectancy.
2016-12-30 | GSE80730 | GEO
Project description:Although retirement ages are rising in the United Kingdom and other countries, the average number of years people in England can expect to spend both healthy and work from age 50 (Healthy Working Life Expectancy; HWLE) is less than the number of years to the State Pension age. This study aimed to estimate HWLE with the presence and absence of selected health, socio-demographic, physical activity, and workplace factors relevant to stakeholders focusing on improving work participation. Data from 11,540 adults in the English Longitudinal Study of Ageing were analysed using a continuous time 3-state multi-state model. Age-adjusted hazard rate ratios (aHRR) were estimated for transitions between health and work states associated with individual and combinations of health, socio-demographic, and workplace factors. HWLE from age 50 was 3.3 years fewer on average for people with pain interference (6.54 years with 95% confidence interval [6.07, 7.01]) compared to those without (9.79 [9.50, 10.08]). Osteoarthritis and mental health problems were associated with 2.2 and 2.9 fewer healthy working years respectively (HWLE for people without osteoarthritis: 9.50 years [9.22, 9.79]; HWLE with osteoarthritis: 7.29 years [6.20, 8.39]; HWLE without mental health problems: 9.76 years [9.48, 10.05]; HWLE with mental health problems: 6.87 years [1.58, 12.15]). Obesity and physical inactivity were associated with 0.9 and 2.0 fewer healthy working years respectively (HWLE without obesity: 9.31 years [9.01, 9.62]; HWLE with obesity: 8.44 years [8.02, 8.86]; HWLE without physical inactivity: 9.62 years [9.32, 9.91]; HWLE with physical inactivity: 7.67 years [7.23, 8.12]). Workers without autonomy at work or with inadequate support at work were expected to lose 1.8 and 1.7 years respectively in work with good health from age 50 (HWLE for workers with autonomy: 9.50 years [9.20, 9.79]; HWLE for workers lacking autonomy: 7.67 years [7.22, 8.12]; HWLE for workers with support: 9.52 years [9.22, 9.82]; HWLE for workers with inadequate support: 7.86 years [7.22, 8.12]). This study identified demographic, health, physical activity, and workplace factors associated with lower HWLE and life expectancy at age 50. Identifying the extent of the impact on healthy working life highlights these factors as targets and the potential to mitigate against premature work exit is encouraging to policy-makers seeking to extend working life as well as people with musculoskeletal and mental health conditions and their employers. The HWLE gaps suggest that interventions are needed to promote the health, wellbeing and work outcomes of subpopulations with long-term health conditions.
| S-EPMC10928117 | biostudies-literature