Predicting Future Years of Life, Health, and Functional Ability: A Healthy Life Calculator for Older Adults

Social networks, social support, and life expectancy in older adults: the Cardiovascular Health Study

BACKGROUND

Social support and social networks have long been postulated to impact health outcomes but their impact on life expectancy and disability in older adults remains poorly quantified.

METHODS

As part of the Cardiovascular Health Study, we followed 5,749 adults aged 65 years and older from 4 US field centers for 25 years. We assessed the Lubben social network score [range 0-50] and a social support score [range 0-24] derived from the Interpersonal Support Evaluation List (ISEL-12) in two consecutive years starting at study recruitment. We used remaining years of life (YOL) from study enrollment to death to approximate life expectancy. We defined years of active life (YAL) as the number of study years in which participants lived without any difficulties in activities of daily living. We used compression of disability to reflect the proportion of life lived able (YAL/YOL). We used linear regression to adjust for socio-demographics and comorbidity.

RESULTS

The mean (standard deviation [SD]) scores were 32.3 ± 6.8 points for social network score and 8.3 ± 2.4 points for social support score. For every 1-SD increase in social network score, adjusted participant life expectancy was 0.40 years higher (95% CI 0.22-0.58; p<0.0001) and disability-free life expectancy 0.35 years higher (95% CI 0.18-0.53; p<0.0001). The association with life expectancy was modified by participant age (p<0.001), but it remained significant even among participants aged ≥75 years (3 months per SD; 95% CI 0.1-6 months, p = 0.04). Further adjustment for frailty did not attenuate the estimates. The social support scale was not significantly associated with YOL or YAL after adjustment for social network score, and neither measure was associated with compression of disability.

DISCUSSION

In older adults, higher social network scores are significantly associated with longer life expectancy and disability-free life expectancy.

Deciphering the "obesity paradox" in the elderly: A systematic review and meta-analysis of sarcopenic obesity

Aging and obesity are two global concerns in public health. Sarcopenic obesity (SO), defined as the combination of age-related sarcopenia and obesity, has become a pressing issue. This systematic review and meta-analysis summarize the current clinical evidence relevant to SO. PubMed, Embase, and Web of Science were searched, and 106 clinical studies with 167,151 elderlies were included. The estimated prevalence of SO was 9% in both men and women. Obesity was associated with 34% reduced risk of sarcopenia (odds ratio [OR] 0.66, 95% CI 0.48-0.91; p < 0.001). The pooled hazard ratio (HR) of all-cause mortality was 1.51 (95% CI 1.14-2.02; p < 0.001) for people with SO compared with healthy individuals. SO was associated with increased risk of cardiovascular disease and related mortality, metabolic disorders, cognitive impairment, arthritis, functional limitation, and lung diseases (all ORs > 1.0, p < 0.05). The attenuated risk of sarcopenia in elderlies with obesity ("obesity paradox") was dependent on higher muscle mass and strength. Apart from unifying the diagnosis of SO, more research is needed to subphenotype people with obesity and sarcopenia for individualized treatment. Meanwhile, the maintenance of proper body composition of muscle and fat may delay or attenuate the adverse outcomes of aging.

Characterizing the Heterogeneity of Aging: A Vision for a Staging System for Aging

Introduction: Older adulthood encompasses several decades of change and heterogeneity. Primary care providers need a geriatric comprehensive vision for defining older adult subpopulations.

Methods: Using PubMed and Google searches, we reviewed the literature on epidemiology of age-related physiological changes, age-related diseases and geriatric syndromes, functional state, and emotional and social changes. We divided old age into strata based on chronological age and strata based on functional state, disease burden, and geriatric syndromes.

Results: We describe 4 chronological-age strata beginning at age 60, and 4 functional-age strata based on frailty according to a modified clinical frailty scale. We provide clinical considerations and anticipatory guidance topics for each of the age strata and functional strata.

Conclusion: Chronological age, functional status, chronic disease burden and geriatric syndromes, and life expectancy are all important domains that impact clinical care and appropriate anticipatory guidance for individual older adults. Better knowledge for differentiating subpopulations of older adults may improve clinical care, reduce medical overuse, improve personalized anticipatory guidance, and focus on the impact of functional state on the quality of life.

Features and impact of missing values in the association of self-rated health with mortality in care homes: a longitudinal study

BACKGROUND

Self-rated health (SRH) is a health measure used in studies of older adults. The objective of this study is to analyze SRH as a predictor of mortality in the institutionalized older population and the characteristics of those who do not provide information about their SRH on health questionnaires.

METHODS

This is a 15-year follow-up study of older adult residents in nursing or care homes in of Madrid, Spain. SRH was measured on a 5-point Likert type scale. The association between answering the SRH question and socio-demographic and health characteristics was evaluated through prevalence ratio (PR), estimated by Poisson regression models. Survival rates associated with SRH were studied through a multivariate Cox regression.

RESULTS

The sample has a mean age of 83.4 (standard deviation, SD = 7.3), with 75.7% women. Twelve percent did not answer the SRH item. Those who did not answer showed a higher probability of disability (Barthel index, PR = 0.76, 95% confidence interval = 0.67-0.86) and/or dementia (PR = 8.03, 3.38-19.03). A trend for higher mortality was observed in those persons who did not respond (adjusted hazard ratio HR = 1.26, 0.75-2.11). The mortality rate was 32% higher for those who declared poor SRH in comparison with those who reported good SRH (adjusted HR = 1.32, 1.08-1.6).

CONCLUSIONS

There is an elevated number of people who do not respond to the SRH item, mainly those with disabilities and cognitive deterioration. Lack of response to SRH is a good indicator of 15-year mortality for persons institutionalized in care or nursing homes.

Exceptional Human Longevity

Exceptional longevity represents an extreme phenotype. Current centenarians are survivors of a cohort who display delayed onset of age-related diseases and/or resistance to otherwise lethal illnesses occurring earlier in life. Characteristics of aging are heterogeneous, even among long-lived individuals. Associations between specific clinical or genetic biomarkers exist, but there is unlikely to be a single biomarker predictive of long life. Careful observations in the oldest old offer some empirical strategies that favor increased health span and life span, with implications for compression of disability, identification and implementation of lifestyle behaviors that promote independence, identification and measurement of more reliable markers associated with longevity, better guidance for appropriate health screenings, and promotion of anticipatory health discussions in the setting of more accurate prognostication. Comprehensive PubMed literature searches were performed, with an unbiased focus on mechanisms of longevity. Overall, the aggregate literature supports that the basis for exceptional longevity is multifactorial and involves disparate combinations of genes, environment, resiliency, and chance, all of which are influenced by culture and geography.

Can a Healthy Lifestyle Compress the Disabled Period in Older Adults?

OBJECTIVES

To determine whether lifestyle factors, measured late in life, could compress the disabled period toward the end of life.

DESIGN

Community-based cohort study of older adults followed from 1989 to 2015.

SETTING

Four U.S. communities.

PARTICIPANTS

Community-living men and women aged 65 and older (N = 5,248, mean age 72.7 ± 5.5, 57% female, 15.2% minority) who were not wheelchair dependent and were able to give informed consent at baseline.

MEASUREMENTS

Multiple lifestyle factors, including smoking, alcohol consumption, physical activity, diet, body mass index (BMI), social networks, and social support, were measured at baseline. Activities of daily living (ADLs) were assessed at baseline and throughout follow-up. Years of life (YoL) was defined as years until death. Years of able life (YAL) was defined as years without any ADL difficulty. YAL/YoL%, the proportion of life lived able, was used to indicate the relative compression or expansion of the disabled period.

RESULTS

The average duration of disabled years was 4.5 (out of 15.4 mean YoL) for women and 2.9 (out of 12.4 mean YoL) for men. In a multivariable model, obesity was associated with 7.3 percentage points (95% confidence interval (CI) = 5.4-9.2) lower YAL/YoL% than normal weight. Scores in the lowest quintile of the Alternate Healthy Eating Index were associated with a 3.7% (95% CI = 1.6-5.9) lower YAL/YoL% than scores in the highest quintile. Every 25 blocks walked in a week was associated with 0.5 percentage points (95% CI = 0.3-0.8) higher YAL/YoL%.

CONCLUSION

The effects of healthy lifestyle factors on the proportion of future life lived free of disability indicate that the disabled period can be compressed, given the right combination of these factors.

Sex, Race, and Age Differences in Observed Years of Life, Healthy Life, and Able Life among Older Adults in The Cardiovascular Health Study

Objective: Longevity fails to account for health and functional status during aging. We sought to quantify differences in years of total life, years of healthy life, and years of able life among groups defined by age, sex, and race. Design: Primary analysis of a cohort study. Setting: 18 years of annual evaluations in four U.S. communities. Participants: 5888 men and women aged 65 and older. Measurements: Years of life were calculated as the time from enrollment to death or 18 years. Years of total, healthy, and able life were determined from self-report during annual or semi-annual contacts. Cumulative years were summed across each of the age and sex groups. Results: White women had the best outcomes for all three measures, followed by white men, non-white women, and non-white men. For example, at the mean age of 73, a white female participant could expect 12.9 years of life, 8.9 of healthy life and 9.5 of able life, while a non-white female could expect 12.6, 7.0, and 8.0 years, respectively. A white male could expect 11.2, 8.1, and 8.9 years of life, healthy life, and able life, and a non-white male 10.3, 6.2, and 7.9 years. Regardless of starting age, individuals of the same race and sex groups spent similar amounts (not proportions) of time in an unhealthy or unable state. Conclusion: Gender had a greater effect on longevity than did race, but race had a greater effect on years spent healthy or able. The mean number of years spent in an unable or sick state was surprisingly independent of the lifespan.

Predicting Future Years of Life, Health, and Functional Ability: A Healthy Life Calculator for Older Adults

Objective: To create personalized estimates of future health and ability status for older adults. Method: Data came from the Cardiovascular Health Study (CHS), a large longitudinal study. Outcomes included years of life, years of healthy life (based on self-rated health), years of able life (based on activities of daily living), and years of healthy and able life. We developed regression estimates using the demographic and health characteristics that best predicted the four outcomes. Internal and external validity were assessed. Results: A prediction equation based on 11 variables accounted for about 40% of the variability for each outcome. Internal validity was excellent, and external validity was satisfactory. The resulting CHS Healthy Life Calculator (CHSHLC) is available at http://healthylifecalculator.org. Conclusion: CHSHLC provides a well-documented estimate of future years of healthy and able life for older adults, who may use it in planning for the future.