A short note on measuring subjective life expectancy: survival probabilities versus point estimates

Rappange, David R.; Exel, Job van; Brouwer, Werner

doi:10.1007/s10198-015-0754-1

Cited by 7 publications

(5 citation statements)

References 22 publications

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“…In general, two common elicitation formats are distinguished. The first approach is a direct measurement of the point estimate of SLE, and the second approach is the percentage chance of living to a certain age [ 20 ]. While the direct method is simple and straightforward, the indirect assessment can capture uncertainty easily [ 21 ].…”

Section: Methodsmentioning

confidence: 99%

Factors Associated With Subjective Life Expectancy: Comparison With Actuarial Life Expectancy

Bae

Kim

Lee

2017

J Prev Med Public Health

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ObjectivesSubjective 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. MethodsA 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. ResultsAmong 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.ConclusionsDemographic 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.

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Section: Methodsmentioning

confidence: 99%

Factors Associated With Subjective Life Expectancy: Comparison With Actuarial Life Expectancy

Bae

Kim

Lee

2017

J Prev Med Public Health

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“…It is necessary to reduce the risk factors for low life expectancy, in order to lower the incidence of cognitive impairment and dementia and to reduce the risk of mortality. As factors affecting subjective life expectancy, various demographic characteristics, including age, sex, socioeconomic position, educational level [32,33], health status [34], health promotion [35], and social relationships [36], can be addressed through policies.…”

Section: Discussionmentioning

confidence: 99%

Effects of Future Subjective Expectations on Cognitive Decline and Dementia among Middle-Aged and Older Adults

Sohn,

Che,

Park

2024

Behavioral Sciences

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This study investigated the impact of subjective expectations of the future (e.g., income, life expectancy, and national policies) on the onset of dementia and mild cognitive impairment by sex and age in middle-aged and older adults. The Korean Longitudinal Study of Aging (KLoSA) data from 2008 to 2020, comprising 4116 people above 45 years, were used. A time-series analysis and multiple panel logistic regression were conducted to highlight subjective expectation trends and their effect on dementia and mild cognitive impairment, respectively. Low subjective expectations of the future negatively affected cognitive impairment (total: odds ratio [OR] = 1.02, 95% confidence interval [CI] = 1.01–1.03) and dementia (total: OR = 1.05, 95% CI = 1.03–1.06), and those of national policies were the biggest risk factors for cognitive impairment (total: OR = 1.17, 95% CI = 1.12–1.22) and dementia (total: OR = 1.10, 95% CI = 1.07–1.13). Individuals about to retire and with low expectations of workability were more likely to develop cognitive impairment (total: OR = 1.03, 95% CI = 1.02–1.06). Subjective expectations of economic downturn also caused cognitive impairment, especially in women (OR = 1.04, 95% CI = 1.01–1.07) and early stage older adults (OR = 1.06, 95% CI = 1.02–1.10). Policymakers must consider the impact of changes in national policies and living environments on cognitive impairment and dementia in older adults.

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“…We inquired sLE by asking a subjective point-estimate from each respondent [ 47 ] (Section A in S1 Appendix ). Although survey answers were accepted without restriction, we included in our analysis respondents if their answers fell between their own age and the upper limit of 100 years.…”

Section: Methodsmentioning

confidence: 99%

Comparing actuarial and subjective healthy life expectancy estimates: A cross-sectional survey among the general population in Hungary

et al. 2022

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Background Healthy 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. Methods We 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. Results Five 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. Conclusions Along 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.

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A short note on measuring subjective life expectancy: survival probabilities versus point estimates

Cited by 7 publications

References 22 publications

Factors Associated With Subjective Life Expectancy: Comparison With Actuarial Life Expectancy

Factors Associated With Subjective Life Expectancy: Comparison With Actuarial Life Expectancy

Effects of Future Subjective Expectations on Cognitive Decline and Dementia among Middle-Aged and Older Adults

Comparing actuarial and subjective healthy life expectancy estimates: A cross-sectional survey among the general population in Hungary

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