Decline in Health for Older Adults: 5-Year Change in 13 Key Measures of Standardized Health

Introduction The health of older adults declines over time, but there are many ways of measuring health. We examined whether all measures declined at the same rate, or whether some aspects of health were less sensitive to aging than others. Methods We compared the decline in 13 measures of physical, mental, and functional health from the Cardiovascular Health Study: hospitalization, bed days, cognition, extremity strength, feelings about life as a whole, satisfaction with the purpose of life, self-rated health, depression, digit symbol substitution test, grip strength, ADLs, IADLs, and gait speed. Each measure was standardized against self-rated health. We compared the 5-year change to see which of the 13 measures declined the fastest and the slowest. Results The 5-year change in standardized health varied from a decline of 12 points (out of 100) for hospitalization to a decline of 17 points for gait speed. In most comparisons, standardized health from hospitalization and bed days declined the least while health measured by ADLs, IADLs, and gait speed declined the most. These rankings were independent of age, sex, mortality patterns, and the method of standardization. Discussion All of the health variables declined, on average, with advancing age, but at significantly different rates. Standardized measures of mental health, cognition, quality of life and hospital utilization did not decline as fast as gait speed, ADLs, and IADLs. Public health interventions to address problems with gait speed, ADLs, and IADLs may help older adults to remain healthier in all dimensions

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

Introduction Planning for the future would be easier if we knew how long we will live and, more importantly, how many years we will be healthy and able to enjoy it. There are few well-documented aids for predicting our future health. We attempted to meet this need for persons 65 years of age and older. Methods Data came from the Cardiovascular Health Study, a large longitudinal study of older adults that began in 1990. Years of life (YOL) were defined by measuring time to death. Years of healthy life (YHL) were defined by an annual question about self-rated health, and years of able life (YABL) by questions about activities of daily living. Years of healthy and able life (YHABL) were the number of years the person was both Healthy and Able. We created prediction equations for YOL, YHL, YABL, and YHABL based on the demographic and health characteristics that best predicted outcomes. Internal and external validity were assessed. The resulting CHS Healthy Life Calculator (CHSHLC) was created and underwent three waves of beta testing. Findings A regression equation based on 11 variables accounted for about 40% of the variability for each outcome. Internal validity was excellent, and external validity was satisfactory. As an example, a very healthy 70-year-old woman might expect an additional 20 YOL, 16.8 YHL, 16.5 YABL, and 14.2 YHABL. The CHSHLC also provides the percent in the sample who differed by more than 5 years from the estimate, to remind the user of variability. Discussion The CHSHLC is currently the only available calculator for YHL, YABL, and YHABL. It may have limitations if today’s users have better prospects for health than persons in 1990. But the external validity results were encouraging. The remaining variability is substantial, but this is one of the few calculators that describes the possible accuracy of the estimates. Conclusion The CHSHLC, currently at http://diehr.com/paula/healthspan, meets the need for a straightforward and well-documented estimate of future years of healthy and able life that older adults can use in planning for the future

Mendelian adult-onset leukodystrophy genes in Alzheimer´s disease. Critical influence of CSF1R and NOTCH3

Mendelian adult-onset leukodystrophies are a spectrum of rare inherited progressive neurodegenerative disorders affecting the white matter of the central nervous system. Among these, Cerebral Autosomal Dominant and Recessive Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL and CARASIL), Cerebroretinal vasculopathy (CRV), Metachromatic leukodystrophy (MLD), Hereditary diffuse Leukoencephalopathy with spheroids (HDLS), Vanishing white matter disease (VWM) present with rapidly progressive dementia as dominant feature and are caused by mutations in NOTCH3, HTRA1, TREX1, ARSA, CSF1R, EIF2B1, EIF2B2, EIF2B3, EIF2B4, EIF2B5, respectively. Given the rare incidence of these disorders and the lack of unequivocally diagnostic features, leukodystrophies are frequently misdiagnosed with common sporadic dementing diseases such as Alzheimer’s disease (AD), raising the question of whether these overlapping phenotypes may be explained by shared genetic risk factors. To investigate this intriguing hypothesis, we have combined gene expression analysis 1) in 6 different AD mouse strains (APPPS1, HOTASTPM, HETASTPM, TPM, TAS10 and TAU), at 5 different developmental stages (Embryo [E15], 2 months, 4 months, 8 months and 18 months), 2) in APPPS1 primary cortical neurons under stress conditions (oxygen-glucose deprivation) and single-variant and single-gene (c-alpha and SKAT tests) based genetic screening in a cohort composed of 332 Caucasian late-onset AD patients and 676 Caucasian elderly controls. Csf1r was significantly overexpressed (Log2FC>1, adj. p-val<0.05) in the cortex and hippocampus of aged HOTASTPM mice with extensive Aβ core dense plaque pathology. We identified 3 likely pathogenic mutations in CSF1R TK domain (p.L868R, p.Q691H and p.H703Y) in our discovery and validation cohort, composed of 465 AD and MCI Caucasian patients from the UK. Moreover, NOTCH3 was a significant hit in the c-alpha test (adj p-val = 0.01). Adult onset Mendelian leukodystrophy genes are not common factors implicated in AD. Nevertheless, our study suggests a potential pathogenic link between NOTCH3, CSF1R and sporadic LOAD, that warrants further investigation

Transitions Among Health States Using 12 Measures of Successful Aging: Results from the Cardiovascular Health Study

Introduction Successful aging has many dimensions, which may manifest differently in men and women and at different ages. We sought to characterize one-year transitions in 12 measures of successful aging among a large cohort of older adults. Methods We analyzed twelve different measures of health in the Cardiovascular Health Study: self-rated health, ADLs, IADLs, depression, cognition, timed walk, number of days spent in bed, number of blocks walked, extremity strength, recent hospitalizations, feelings about life as a whole, and life satisfaction. We dichotomized responses for each variable into “healthy” or “sick”, and estimated the prevalence of the healthy state and the probability of transitioning from one state to another, or dying, during yearly intervals. We compared men and women, and three age groups (65-74, 75-84, and 85-94). Findings All measures of successful aging showed similar results, except for hospitalizations and cognition. Most participants remained healthy even into advanced ages, although health declined for all measures. Men had a higher death rate than women, regardless of health status, and were also more likely to be healthy. Discussion The results suggest a qualitatively different experience of successful aging between men and women, with men showing a more square mortality curve. Men did not simply age faster than women. Conclusion Men and women age differently with regard to health status, with consistency among various health measures

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

Transitions among Health States Using 12 Measures of Successful Aging in Men and Women: Results from the Cardiovascular Health Study

Introduction. Successful aging has many dimensions, which may manifest differently in men and women at different ages. Methods. We characterized one-year transitions among health states in 12 measures of successful aging among adults in the Cardiovascular Health Study. The measures included self-rated health, ADLs, IADLs, depression, cognition, timed walk, number of days spent in bed, number of blocks walked, extremity strength, recent hospitalizations, feelings about life as a whole, and life satisfaction. We dichotomized variables into “healthy” or “sick,” states, and estimated the prevalence of the healthy state and the probability of transitioning from one state to another, or dying, during yearly intervals. We compared men and women and three age groups (65–74, 75–84, and 85–94). Findings. Measures of successful aging showed similar results by gender. Most participants remained healthy even into advanced ages, although health declined for all measures. Recuperation, although less common with age, still occurred frequently. Men had a higher death rate than women regardless of health status, and were also more likely to remain in the healthy state. Discussion. The results suggest a qualitatively different experience of successful aging between men and women. Men did not simply “age faster” than women