Family, frailty, and fatal futures? Own-health and family-health predictors of subjective life expectancy

How does chronic disease influence subjective life expectancy among middle-aged and older adults? Evidence from the China Health and Retirement Longitudinal Study (CHARLS) 2018 cross-sectional data

Chronic diseases have become one of the most important factors threatening human health. Subjective life expectancy (SLE) describes an individual's expectation or subjective perception of lifespan. This article aims to explore the relationship between chronic diseases and SLE, as well as the differences among different age groups and different types of chronic diseases in this relationship. China Health and Retirement Longitudinal Study (CHARLS) is a nationwide longitudinal study that evaluates the social, economic, and health conditions of middle-aged and older adult families and individuals aged 45 and above in China. In this study, CHARLS used probability proportional to size sampling (PPS sampling) to ensure the breadth and representativeness of the sample. This study selected cross-sectional data from CHARLS 2018, removed missing values, and obtained a valid sample of 10,658 middle-aged and older individuals, of whom 8564 had chronic diseases. After controlling demographic, health behavior, socioeconomic, psychological, and social security factors, an ordered logistic regression was performed to explore the relationship between chronic disease and SLE in middle-aged and older adults. The results show that chronic diseases negatively correlate with SLE in middle-aged and older adults. Middle-aged and older adults with chronic diseases are 36.2% less likely to have high life expectancy than those without chronic diseases. Many different types of chronic diseases are negatively correlated with SLE. Cancer is most negatively correlated with SLE, far exceeding other chronic diseases. Chronic disease and SLE of middle-aged and older adults have age-heterogeneous differences. For middle-aged people aged 45-59 and young older adults aged 60-79, there is a significant correlation between chronic diseases and SLE. However, there is no correlation between chronic diseases and subjective life expectancy in the older population aged 80 and above. The government and society should pay close attention to the prevention and treatment of chronic diseases among middle-aged and older adults and adjust policies and measures according to the population's age structure. In addition, the government and society should pay attention to the spiritual needs of middle-aged and older adults. The government and society should pay more attention to cancer patients. Finally, the scientific research team should also strengthen research on chronic diseases, research and development of specific drugs and vaccines, improve the cure rate of chronic diseases, promote people's health, and make people no longer afraid of diseases.

Associations between existing and newly diagnosed chronic health conditions and change in subjective life expectancy: Results from a panel study

Background

Subjective life expectancy (SLE) is a vital predictor of mortality, health and retirement. Nevertheless, we have sparse knowledge about what drives changes in SLE. Having a chronic health condition (CHC) is probably associated with a change SLE. However, how CHCs are associated with changes in SLE may depend on whether the CHC was newly diagnosed and the type of CHC.

Aim

We hypothesize that newly diagnosed CHCs will be strongly negatively associated with changes in SLE than existing CHCs. As CHCs vary in their presentation and prognosis, we differentiate associations between five CHCs - arthritis, cardiovascular diseases, sleep disorders, psychological disorders and life-threatening conditions - and changes in SLE.

Method

Data from two waves of a Dutch pension panel survey, collected 3 years apart in 2015 and 2018, were used. The analytical sample included 4824 older workers between the ages of 60-65 years at wave 1. Data were analysed longitudinally using a conditional change ordered logistic regression model.

Results

In general, newly diagnosed CHCs were strongly negatively associated with changes in SLE, relative to having no CHCs. Existing CHCs were also negatively associated with changes in SLE, but to a weaker strength. Interestingly, associations between CHCs and the change in SLE differed based on the CHC in question.

Conclusion

Newly diagnosed life-threatening conditions, psychological disorders and cardiovascular diseases are strongly negatively associated with changes in SLE. These results provide insight into the differences in how older workers with CHCs experience late career work and how these experiences influence their SLE.

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

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.

The subjective life course framework: Integrating life course sociology with gerontological perspectives on subjective aging

The expansion of life expectancy has precipitated a cultural transformation of the life course - altering the perceived temporal contours of middle and later life. However, our understanding of these perceptions is limited by the absence of a framework within which to examine them. This paper builds on the life course perspective - which emphasizes the objective patterning of lives - by focusing on the subjective side of the life course. Drawing on theoretically, methodologically, and substantively diverse studies, this paper develops the concept of the subjective life course - a term we use to denote individuals' perceptions of the life course, including its structure and timing and their advancing location in it. We outline two dimensions of the subjective life course - the target of the perception (i.e., generalized other versus self) and the temporal frame of reference (i.e., past, present, or future). Using the resulting framework as an organizational tool, we then discuss key constructs located at each intersection along these dimensions, providing examples, where possible, of empirical studies examining them. We close with a discussion of two broad directions for research: leveraging the framework to yield insight on the subjective life course and exploring links between objective and subjective dimensions of the life course.

Capturing Subjective Age, Subjective Life Expectancy, and Their Links With Older Adults' Health: The Dutch Longitudinal Aging Study Amsterdam

Objectives: This study compares the associations of two subjective lifetime perspectives, subjective age (SA) and subjective life expectancy (SLE), with physical performance, self-rated health, and depressive symptoms. Methods: 64 91-year-old participants were selected from three waves of the Longitudinal Aging Study Amsterdam (2008/09, 2011/12, 2015/16; n = 1822 participants, n = 3500 observations) that included graphical and numerical measures of SA and SLE. We used generalized estimating equations to examine their associations with health. Results: Associations of SA/SLE with health were weaker for physical performance than for self-rated health and depressive symptoms. The associations of SA and SLE with physical performance were of similar magnitude but with self-rated health depended on the type of measure. Depressive symptoms, instead, showed a stronger association with SA than with SLE. Graphical measures showed weaker associations than numerical measures. Discussion: The way in which subjective lifetime perspectives and health are conceptualized and measured influences the strength of their associations.

Do Informal Caregivers Expect to Die Earlier? A Longitudinal Study with a Population-Based Sample on Subjective Life Expectancy of Informal Caregivers

INTRODUCTION

Subjective life expectancy is a good predictor of health and could therefore be a relevant factor in the informal caregiving context. However, no research has been conducted on the perception of life expectancy by informal caregivers. This is the first study that examines the association between transitioning into, and out of, informal caregiving, and subjective life expectancy, and the relevance of employment status and gender for these associations.

METHODS

A longitudinal study was conducted with data from the German Ageing Survey (waves 2008, 2011, 2014, and 2017). Up to 20,774 observations pooled over all waves were included in the main models. In total, 1,219 transitions into and 1,198 transitions out of informal caregiving were observed. Fixed effects (FE) regression analysis was used. Moderator and stratified analyses were conducted with gender and employment status used as moderator variables and to stratify the sample. Sociodemographic information, health, and lifestyle factors were controlled for.

RESULTS

Results of adjusted FE regression analyses indicated a significant reduction of subjective life expectancy when transitioning into informal caregiving. No significant change was found when transitioning out of informal caregiving. Subjective life expectancy was significantly decreased when employed individuals transitioned into informal caregiving and significantly increased when they transitioned out of caregiving. Findings for women transitioning into informal caregiving indicated a significant decrease in subjective life expectancy, while no significant change was found among men.

CONCLUSION

The study's findings indicate that informal caregivers, female and employed caregivers in particular, perceive informal care provision as dangerous for their longevity and expect to die earlier when transitioning into informal caregiving. Thus, supportive interventions for informal caregivers, particularly employed and female informal caregivers, are recommended.

Subjective life expectancy and actual mortality: results of a 10-year panel study among older workers

This research examined the judgemental process underlying subjective life expectancy (SLE) and the predictive value of SLE on actual mortality in older adults in the Netherlands. We integrated theoretical insights from life satisfaction research with existing models of SLE. Our model differentiates between bottom-up (objective data of any type) and top-down factors (psychological variables). The study used data from the first wave of the Netherlands Interdisciplinary Demographic Institute Work and Retirement Panel. This is a prospective cohort study among Dutch older workers. The analytical sample included 2278 individuals, assessed at age 50-64 in 2001, with vital statistics tracked through 2011. We used a linear regression model to estimate the impact of bottom-up and top-down factors on SLE. Cox proportional hazard regression was used to determine the impact of SLE on the timing of mortality, crude and adjusted for actuarial correlates of general life expectancy, family history, health and trait-like dispositions. Results reveal that psychological variables play a role in the formation of SLE. Further, the results indicate that SLE predicts actual mortality, crude and adjusted for socio-demographic, biomedical and psychological confounders. Education has an additional effect on mortality. Those with higher educational attainment were less likely to die within the follow-up period. This SES gradient in mortality was not captured in SLE. The findings indicate that SLE is an independent predictor of mortality in a pre-retirement cohort in the Netherlands. SLE does not fully capture educational differences in mortality. Particularly, higher-educated individuals underestimate their life expectancy.

Do you want to live to be 100? Answers from older people

BACKGROUND

little is known about the oldest-olds' views on ageing.

OBJECTIVE

to investigate older people's desire and the reasons they give for wanting to live to 100.

DESIGN

a postal questionnaire, analysed both quantitatively and qualitatively.

SETTING

population based in Helsinki, Finland.

SUBJECTS

a random sample (response rate 64%; N = 1,405) of community-dwelling older people (aged 75-96).

METHODS

a structured self-completed questionnaire with an open-ended question on the reasons why/why not participants wished/did not wish to live to 100.

RESULTS

one-third (32.9%) of home-dwelling older people wanted to live to be 100. Those who did were older, more often male and self-rated their health better than those who did not. Often the desire for long life was conditional: 'Yes, if I stay healthy'. Among the reasons is that many were curious to see what would happen. Many stated that they loved life, they had twinkle in their eye or significant life roles. Those who did not want to live extremely long lives gave various rationales: they would become disabled, life would be meaningless, they were reluctant to become a burden to others or they feared loss of autonomy or suffering pain or loneliness. Some people also shared the view that they should not intervene in destiny or they felt that they had accomplished what they wanted in life.

CONCLUSIONS

one-third of the oldest-old participants wanted to live to 100. Identifying what motivated them to desire long life could be a resource in their care plans.