Association of an Index of Healthy Aging With Incident Cardiovascular Disease and Mortality in a Community-Based Sample of Older Adults

Association of a healthy ageing index with health-related outcomes in a multi-ethnic cohort from Singapore

BACKGROUND

The global population is ageing rapidly and it is important to promote healthy ageing. The Healthy Ageing Index (HAI) is a comprehensive measure of health, but there is limited research on its association with other age-related outcomes. The management of an aging population necessitates considerations even among generally healthy adults, as age-related diseases often remain unaccounted for until later stages of life. This study explores the association of risk factors with HAI and its association with peripheral artery disease (PAD), muscle strength, health-related quality of life (HRQoL), and psychological distress in the Singapore Multi-Ethnic Cohort study.

METHODS

This cross-sectional study involved 1909 participants (median (Q1, Q3) age: 53 (48, 60) years and 59.3% females) from Singapore Multi-Ethnic Cohort study. The risk factors of HAI included age, gender, ethnicity, education level, smoking, alcohol consumption, employment, BMI and past medical histories. PAD was assessed using ankle-brachial index (ABI), handgrip strength (HGS), HRQoL with the EQ-5D-5 L questionnaire and psychological distress via the Kessler Psychological Distress Scale (K10). HAI components were assessed using relevant marker tests.

RESULTS

Older age, Malay and Indian ethnicities, unemployment, high BMI and histories of CHD, hypercholesterolaemia, tumours and TIA/stroke were associated with lower HAI scores indicative of poorer health. Higher HAI scores were associated with females and higher education levels. Lower HAI scores were significantly associated with low ABI, high K10 scores, mobility and anxiety/depression dimensions of EQ-5D-5 L.

CONCLUSION

The most important factors associated with HAI were age, sex, ethnicity, education, unemployment, BMI and a history of health conditions. Lower HAI scores were significantly associated with PAD, lower HRQoL and psychological distress. Thus, the HAI demonstrates promise as an evaluation method for assessing PAD, overall muscle strength and HRQoL in a population-based setting.

Associations of healthy aging index and all-cause and cause-specific mortality: a prospective cohort study of UK Biobank participants

The healthy aging index (HAI) has been recently developed as a surrogate measure of biological age. However, to what extent the HAI is associated with all-cause and cause-specific mortality and whether this association differs in younger and older adults remains unknown. We aimed to quantify the association between the HAI and mortality in a population of UK adults. In the prospective cohort study, data are obtained from the UK Biobank. Five HAI components (systolic blood pressure, reaction time, cystatin C, serum glucose, forced vital capacity) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the HAI (range 0-10). Cox proportional hazard regression models were used to estimate the associations of the HAI with the risk of all-cause and cause-specific mortality. 387,794 middle-aged and older participants were followed up for a median of 8.9 years (IQR 8.3-9.5). A total of 14,112 all-cause deaths were documented. After adjustments, each 1-point increase in the HAI was related to a higher risk of all-cause mortality (hazards ratio [HR], 1.17; 95%CI, 1.15-1.18). Such association was stronger among adults younger than 60 years (1.19, 1.17-1.21) than that among those 60 years and older (1.15, 1.14-1.17) (P interaction < 0.001). For each unit increment of the HAI, the multivariate-adjusted HRs for risk of death were 1.28 (1.25-1.31) for cardiovascular diseases, 1.09 (1.07-1.10) for cancer, 1.36 (1.29-1.44) for digestive disease, 1.42 (1.35-1.48) for respiratory disease, 1.42 (1.33-1.51) for infectious diseases, and 1.15 (1.09-1.21) for neurodegenerative disease, respectively. Our findings indicate that the HAI is positively associated with all-cause and cause-specific mortality independent of chronological age. Our results further underscore the importance of effective early-life interventions to slow aging and prevent premature death.

The Potential Role of C-Reactive Protein in Metabolic-Dysfunction-Associated Fatty Liver Disease and Aging

Nonalcoholic fatty liver disease (NAFLD), recently redefined as metabolic-dysfunction-associated fatty liver disease (MASLD), is liver-metabolism-associated steatohepatitis caused by nonalcoholic factors. NAFLD/MASLD is currently the most prevalent liver disease in the world, affecting one-fourth of the global population, and its prevalence increases with age. Current treatments are limited; one important reason hindering drug development is the insufficient understanding of the onset and pathogenesis of NAFLD/MASLD. C-reactive protein (CRP), a marker of inflammation, has been linked to NAFLD and aging in recent studies. As a conserved acute-phase protein, CRP is widely characterized for its host defense functions, but the link between CRP and NAFLD/MASLD remains unclear. Herein, we discuss the currently available evidence for the involvement of CRP in MASLD to identify areas where further research is needed. We hope this review can provide new insights into the development of aging-associated NAFLD biomarkers and suggest that modulation of CRP signaling is a potential therapeutic target.

Construction of healthy aging index from two different datasets

Introduction

The aging population presents both unique challenges and opportunities for societies around the world. To develop an effective healthy aging strategy, a tool for assessing aging process is needed. Numerous attempts to quantify the aging process have been made. However, there is still a challenge in developing and choosing a good enough score that is easy to apply, has a construct of variables that are available in most nationwide surveys for comparable results, and at the same time reflects the aging process of older individuals. The purpose of this study is to present our approach to construct a comparable Healthy Aging Index (HAI).

Materials and methods

In Latvia, data from Wave 8 of the Survey of Health, Aging and Retirement in Europe (SHARE), involving 420 respondents, were used. For comparative analysis, data from a HL20 study on the health and wellbeing of the older adults in Iceland, which included 1,033 respondents, were used.

Results

For Latvia, 13 items were selected, and for Iceland, nine items were selected. We constructed the HAI with four similar subscales for both countries-"Autonomy," "Health," "Wellbeing," and "Activities," and an additional subscale "Cognitive" for Latvia. We found matching items in all four subscales. For the Autonomy subscale, they were related to difficulties with everyday and daily tasks. In the Health subscale, the only matching item was self-rated physical health. One item related to loneliness was found for the Wellbeing subscale and one item related to social participation for the Activities subscale.

Discussion

In our study, we found evidence for the successful construction of a HAI in two different datasets. The strength of our construct lies in the use of data from one of the largest social science panel studies in Europe (SHARE). As we were able to apply the construct to the Icelandic study, we believe that items presented in our approach are available in other population-based studies as well, and, therefore, can be easily replicated by others. By examining the existing SHARE data, HAI could be used to analyze long-term changes and could provide a foundation for comparing and monitoring the evolution of aging over time as well as comparing the aging process across societies. This is required for the authorities to conduct further analyses, proposals, and action plans in support of healthy aging.

60 years of healthy aging: On definitions, biomarkers, scores and challenges

BACKGROUND AND OBJECTIVE

As the proportion of aging people in our population increases steadily, global strategies accompanied by extensive research are necessary to tackle society and health service challenges. The World Health Organization recently published an action plan: "Decade of healthy aging 2020-2030", which calls for concerted collaboration to prevent poverty of older people to provide quality education, job opportunities, and an age-inclusive infrastructure. However, scientists worldwide still struggle to find definitions and appropriate measurements of aging per se and healthy aging in particular. This literature review aims to compile concepts of healthy aging and provide a condensed overview of the challenges in defining and measuring it, along with suggestions for further research.

MATERIALS AND METHODS

We conducted three independent systematic literature searches covering the main scopes addressed in this review: (1) concepts and definitions of healthy aging, (2) outcomes and measures in (healthy) aging studies and (3) scores and indices of healthy aging. For each scope, the retrieved literature body was screened and subsequently synthesized.

RESULTS

We provide a historical overview of the concepts of healthy aging over the past 60 years. Furthermore, we identifiy current difficulties in identifying healthy agers, including dichotomous measurements, illness-centered views, study populations & designs. Secondly, markers and measures of healthy aging are discussed, including points to consider, like plausibility, consistency, and robustness. Finally, we present healthy aging scores as measurements, which combine multiple aspects to avoid a dichotomous categorization and display the bio-psycho-social concept of healthy aging.

DISCUSSION AND CONCLUSION

When deducting research, scientists need to consider the diverse challenges in defining and measuring healthy aging. Considering that, we recommend scores that combine multiple aspects of healthy aging, such as the Healthy Ageing Index or the ATHLOS score, among others. Further efforts are to be made on a harmonized definition of healthy aging and validated measuring instruments that are modular, easy to apply and provide comparable results in different studies and cohorts to enhance the generalization of results.

Associations of Modified Healthy Aging Index With Major Adverse Cardiac Events, Major Coronary Events, and Ischemic Heart Disease

Background The Healthy Aging Index (HAI) has been regarded as useful in capturing the health status of multiple organ systems. However, to what extent the HAI is associated with major cardiovascular events remains largely unknown. The authors constructed a modified HAI (mHAI) to quantify the association of physiological aging with major vascular events and explored how the effects of a healthy lifestyle can modify this association. Methods and Results The participants with either missing values of any individual mHAI component or major illnesses such as heart attack, angina and stroke, and self-reported cancer at baseline were excluded. The mHAI components include systolic blood pressure, reaction time, forced vital capacity, serum cystatin c, and serum glucose. The authors used Cox proportional hazard models to quantify the association of mHAI with major adverse cardiac events, major coronary events, and ischemic heart disease. Cumulative incidence at 5 and 10 years was estimated, and joint analyses were stratified by age group and 4 mHAI categories. The mHAI was significantly correlated with major cardiovascular events, which is a better reflection of the aging level of the body than chronological age. An mHAI was calculated in 338 044 participants aged 38 to 73 years in the UK Biobank. Each point increase in the mHAI was associated with a 44% higher risk of major adverse cardiac events (adjusted hazard ratio [aHR], 1.44 [95% CI, 1.40-1.49]), 44% higher risk of major coronary events (aHR, 1.44 [95% CI, 1.40-1.48]), and 36% higher risk of ischemic heart disease (aHR, 1.36 [95% CI, 1.33-1.39]). The percentage of population-attribution risk was 51% (95% CI, 47-55) for major adverse cardiac events, 49% (95% CI, 45-53) for major coronary events, and 47% (95% CI, 44-50) for ischemic heart disease, which means that a substantial portion of these events could be prevented. Systolic blood pressure was the factor most significantly associated with major adverse cardiac events (aHR, 1.94 [95% CI, 1.82-2.08]; percentage of population-attribution risk, 36%), major coronary events (aHR, 2.01 [95% CI, 1.85-2.17]; percentage of population-attribution risk, 38%), and ischemic heart disease (aHR, 1.80 [95% CI, 1.71-1.89]; percentage of population-attribution risk, 32%). A healthy lifestyle significantly attenuated mHAI associations with incidence of vascular events. Conclusions Our findings indicate that higher mHAI is associated with increased major vascular events. A healthy lifestyle may attenuate these associations.

Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study

BACKGROUND

Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations.

METHODS

Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20-29/30-39/40-49/50-59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46-85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors.

RESULTS

The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model's performance was modest with an R² of 17%.

CONCLUSIONS

Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations.

The Relationship Between Successful Aging and All-Cause Mortality Risk in Older Adults: A Systematic Review and Meta-Analysis of Cohort Studies

Background

This meta-analysis aimed to explore the effect of successful aging (SA) on all-cause mortality risk in older people to provide a theoretical basis for promoting SA.

Methods

PubMed, Embase, CINAHL, CNKI, and WanFang databases (inception to March 4, 2021) were searched for cohort studies to evaluate the relationship between SA and mortality in older people. A random-effects model was used to synthesis hazard ratio and 95% confidence intervals. Quality assessment was performed using the Newcastle–Ottawa scale. All statistical analyses were conducted in STATA 16.0.

Results

In total, 21,158 older adults from 10 studies were included in the current systematic review and meta-analysis. The SA group tended to have 50% lower risk of all-cause mortality than the non-SA group (pooled hazard ratio = 0.50, 95% confidence intervals: 0.35–0.65, P < 0.001; I² = 58.3%). The risk of all-cause mortality in older people increased by 17% for each unit increment in the healthy aging index (HAI) (I² = 0%, P = 0.964). Compared with the reference group (HAI 0-2), older people with HAI 3-4, HAI 5-6, and HAI 7-10 had 1.31-fold, 1.73-fold, and 2.58-fold greater risk of all-cause mortality, respectively. Subgroup analysis did not reveal possible sources of heterogeneity.

Conclusions

This meta-analysis suggests that older adults with SA reduced the risk of all-cause mortality by 50%. However, few interventional studies have been conducted. Therefore, healthcare providers must be aware of the relationship between SA and mortality risk and actively develop intervention methods for helping old people achieve SA.

Hematopoiesis, Inflammation and Aging-The Biological Background and Clinical Impact of Anemia and Increased C-Reactive Protein Levels on Elderly Individuals

Anemia and systemic signs of inflammation are common in elderly individuals and are associated with decreased survival. The common biological context for these two states is then the hallmarks of aging, i.e., genomic instability, telomere shortening, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion and altered intercellular communication. Such aging-associated alterations of hematopoietic stem cells are probably caused by complex mechanisms and depend on both the aging of hematopoietic (stem) cells and on the supporting stromal cells. The function of inflammatory or immunocompetent cells is also altered by aging. The intracellular signaling initiated by soluble proinflammatory mediators (e.g., IL1, IL6 and TNFα) is altered during aging and contributes to the development of both the inhibition of erythropoiesis with anemia as well as to the development of the acute-phase reaction as a systemic sign of inflammation with increased CRP levels. Both anemia and increased CRP levels are associated with decreased overall survival and increased cardiovascular mortality. The handling of elderly patients with inflammation and/or anemia should in our opinion be individualized; all of them should have a limited evaluation with regard to the cause of the abnormalities, but the extent of additional and especially invasive diagnostic evaluation should be based on an overall clinical evaluation and the possible therapeutic consequences.

Effect of Diet, Exercise, or Both on Biological Age and Healthy Aging in Older Adults with Obesity: Secondary Analysis of a Randomized Controlled Trial

OBJECTIVES

To determine the effect of diet, exercise, and diet-exercise in combination on measures of biological age.

DESIGN

Secondary analysis of a 1-year randomized, controlled trial.

SETTING

University-based Medical Center.

PARTICIPANTS

One-hundred-seven older (age≥65 yrs.) adults with obesity (BMI≥30 kg/m2) were randomized and 93 completed the study. Analyses used intention-to-treat.

INTERVENTIONS

Participants were randomized to a control group, a weight-management (diet) group, an exercise group, or a weight-management-plus-exercise (diet-exercise) group.

MAIN OUTCOME MEASURES

We calculated Klemera-Doubal Method (KDM) biological age, Homeostatic Dysregulation (HD) score, and Health Aging Index (HAI) score at baseline, and changes at 6- and 12-months.

RESULTS

Diet and diet-exercise decreased KDM biological age more than exercise and control (-2.4±0.4, -2.2±0.3, -0.2±0.4, and 0.2±0.5, respectively, P<0.05 for the between group-differences). Diet and diet-exercise also decreased HD score more than exercise and control (-1.0±0.3, -1.1±0.3, 0.1±0.3, and 0.3±0.3 respectively, P<0.05). Moreover, diet-exercise decreased HAI score more than exercise, diet, or control (-1.1±0.2, -0.5±0.2, -0.5±0.2, and 0.0±0.2, respectively, P<0.05).

CONCLUSIONS

These findings suggest that diet and diet-exercise are both effective methods of improving biological age, and that biological age may be a valuable method of assessing geroprotective interventions in older humans.

High-Sensitivity C-Reactive Protein Relationship with Metabolic Disorders and Cardiovascular Diseases Risk Factors

Background. Chronic inflammation is considered to be involved in the development of CVD. It is important to find a simple test that enables the identification of patients at risk and that may be used in primary care. The aim of this study is to investigate the associations of high-sensitivity C-reactive protein (hsCRP) with selected factors—age, gender, obesity, dyslipidemia, diabetes, hyperuricemia, vitamin D-25(OH)D, cardiovascular diseases (CVD), coronary heart disease, cerebrovascular disease, and hypertension. Results. Statistically significant correlations were found between hsCRP and the following: age (rs = 0.304, p = 0.0000); gender (female) (p = 0.0173); BMI (rs = 0.295, p = 0.0001); waist circumference (rs = 0.250, p = 0.0007); dyslipidemia (p = 0.0159); glycemia (rs = 0.173, p = 0.0207); and significant negative correlations between hsCRP and 25(OH)D (rs = −0.203, p = 0.0065). In patients with CVD, hypertension, diabetes, or visceral obesity, hsCRP was significantly higher than in the subgroup without these disorders. There was a statistically significant relationship between hsCRP and the number of the metabolic syndrome elements (p = 0.0053). Conclusions. The hsCRP test seem to be a simple test that may be used at the primary care level to identify patients at risk of metabolic disorders, CVD, and hypertension. Vitamin D concentration may be a determining factor of systemic inflammation (it may have a modulating effect).

The Modified Healthy Ageing Index Is Associated with Mortality and Disability: The Rugao Longevity and Ageing Study

INTRODUCTION

The Healthy Ageing Index (HAI) has been shown not only to have wider applicability and predictive ability but also to adequately predict mortality in Western populations. There is still a lack of studies validating the applicability of the HAI in China.

OBJECTIVE

To evaluate the applicability of the HAI and validate whether the HAI is suitable for monitoring ageing in the elderly population in China.

METHODS

Data were obtained from the Rugao Longevity and Ageing Study. The modified HAI was constructed based on systolic blood pressure, chronic pulmonary diseases, cognitive function, fasting glucose, and kidney function. It was calculated in 1719 individuals aged 70-84 years at baseline. The adverse outcomes were mortality and disability. Demographic, physiologic, and clinical data were collected. Cox proportional hazards and logistic regression models were used to analyze the relationship between the modified HAI and adverse outcomes.

RESULTS

A total of 1,719 older adults were analyzed in our study. A total of 793 (46.13%) males were recruited. The mean age was 75.69 ± 3.93 years. At the 5-year follow-up, there were 266 deaths and 275 individuals with disabilities. In the multivariable models, the modified HAI was associated with mortality (hazard ratio = 1.11, 95% confidence interval [CI]: 1.03-1.20) and disability (odds ratio = 1.11, 95% CI: 1.05-1.18). In the sensitivity analyses, similar associations remained after imputing missing data using multiple imputation and excluding participants with major cardiovascular disease at baseline.

CONCLUSION

The modified HAI was a robust and independent predictor of adverse outcomes. It is a valid and feasible tool for monitoring ageing in older adults.

The Healthy Aging Index analyzed over 15 years in the general population: The Doetinchem Cohort Study

The Healthy Aging Index (HAI), an index of physiological aging, has been demonstrated to predicts mortality, morbidity and disability. We studied the longitudinal development of the HAI to identify aging trajectories and evaluated the role of baseline sociodemographic characteristics and lifestyle factors of the trajectories. Four measurements with intervals of 5 years were included from the Doetinchem Cohort Study. The HAI reflects levels of systolic blood pressure, non-fasting plasma glucose levels, global cognitive functioning, plasma creatinine levels and lung functioning. The HAI score ranges from 0 to 10: higher scores indicate a better health profile. Latent class mixture modelling was used to model within-person change and to identify aging trajectories. Area under the curve was calculated per trajectory to estimate total healthy years. In total, 2324 women and 2013 men were included. One HAI trajectory was identified for women, and two trajectories for men, labelled 'gradual' aging (76%) and 'early' aging (24%). Men who were medium/high educated, below 36 years at baseline, complied with guidelines on physical activity and were not obese in any round were associated with increased odds to 'gradual' aging of 1.46 (CI: 1.18-1.81), 1.93 (CI: 1.42-2.62), 1.26 (1.02-1.57) and 1.76 (1.32-2.35), respectively. Between 30 and 70 years of age, men in the 'early' aging trajectory had the least healthy years (29.6 years), followed by women (30.1 years), and 'gradual' aging men (34.7 years). This study emphasizes that 'physiological aging' is not only an issue of older ages. Between 30 and 70 years of age, 'early' aging men and women had approximately five healthy years less compared to 'gradual' aging men. Lifestyle factors (e.g. nutrition and physical activity) seem to play an important role in optimal aging.

How are missing data in covariates handled in observational time-to-event studies in oncology? A systematic review

Background

Missing data in covariates can result in biased estimates and loss of power to detect associations. It can also lead to other challenges in time-to-event analyses including the handling of time-varying effects of covariates, selection of covariates and their flexible modelling. This review aims to describe how researchers approach time-to-event analyses with missing data.

Methods

Medline and Embase were searched for observational time-to-event studies in oncology published from January 2012 to January 2018. The review focused on proportional hazards models or extended Cox models. We investigated the extent and reporting of missing data and how it was addressed in the analysis. Covariate modelling and selection, and assessment of the proportional hazards assumption were also investigated, alongside the treatment of missing data in these procedures.

Results

148 studies were included. The mean proportion of individuals with missingness in any covariate was 32%. 53% of studies used complete-case analysis, and 22% used multiple imputation. In total, 14% of studies stated an assumption concerning missing data and only 34% stated missingness as a limitation. The proportional hazards assumption was checked in 28% of studies, of which, 17% did not state the assessment method. 58% of 144 multivariable models stated their covariate selection procedure with use of a pre-selected set of covariates being the most popular followed by stepwise methods and univariable analyses. Of 69 studies that included continuous covariates, 81% did not assess the appropriateness of the functional form.

Conclusion

While guidelines for handling missing data in epidemiological studies are in place, this review indicates that few report implementing recommendations in practice. Although missing data are present in many studies, we found that few state clearly how they handled it or the assumptions they have made. Easy-to-implement but potentially biased approaches such as complete-case analysis are most commonly used despite these relying on strong assumptions and where often more appropriate methods should be employed. Authors should be encouraged to follow existing guidelines to address missing data, and increased levels of expectation from journals and editors could be used to improve practice.

Mortality in Relation to Changes in a Healthy Aging Index: The Health, Aging, and Body Composition Study

BACKGROUND

Baseline scores on a Healthy Aging Index (HAI), including five key physiologic domains, strongly predict health outcomes. This study aimed to characterize 9-year changes in a HAI and explore their relationship to subsequent mortality.

METHODS

Data are from the Health, Aging, and Body Composition study of well-functioning adults aged 70-79 years. A HAI, which ranges from 0 to 10, was constructed at years 1 and 10 of the study including systolic blood pressure, forced expiratory volume, digit symbol substitution test, cystatin C, and fasting glucose. The relationships between the HAI at years 1 and 10 and the change between years and subsequent mortality until year 17 were estimated from Cox proportional hazards models.

RESULTS

Two thousand two hundred sixty-four participants had complete data on a HAI at year 1, of these 1,122 had complete data at year 10. HAI scores tended to increase (i.e. get worse) over 9-year follow-up, from (mean [SD]) 4.3 (2.1) to 5.7 (2.1); mean within-person change 1.5 (1.6). After multivariable adjustment, HAI score was related to mortality from year 1 (hazard ratio [95% confidence interval] = 1.17 [1.13-1.21] per unit) and year 10 (1.20 [1.14-1.27] per unit). The change between years was also related to mortality (1.08 [1.02-1.15] per unit change).

CONCLUSIONS

HAI scores tended to increase with advancing age and stratified mortality rates among participants remaining at year 10. The HAI may prove useful to understand changes in health with aging.

Domains and Measurements of Healthy Aging in Epidemiological Studies: A Review

Purpose of the Study

Few studies have recommended the essential domains of healthy aging and their relevant measurement to assess healthy aging comprehensively. This review is to fill the gap, by conducting a literature review of domains and measures of healthy aging in epidemiological studies.

Design and Methods

A literature search was conducted up to March 31, 2017, supplemented by a search of references in all relevant articles in English. We made a final selection of 50 studies across 23 countries or regions.

Results

Nineteen studies applied Rowe and Kahn’s three standards to assess healthy aging. Thirty-seven studies measured physical capabilities mainly by (instrumental) activities of daily living. Cognitive functions were included in 33 studies. Nineteen of them applied Mini-Mental State Examination (MMSE). Twenty-six studies considered metabolic and physiological health, but they mainly asked the self-reported absence of diseases. Twenty-four studies assessed psychological well-being by employing diverse scales. Questions about participation in social activities were mainly asked to measure social well-being in 22 studies. Sixteen studies considered individuals’ general health status, which was mainly measured by self-rated health. Security questions were asked in five studies. Health behaviors were taken into account by three studies. Fifteen studies either applied SF-12/36 or developed health indices to assess healthy aging.

Implications

This review summarizes detailed scales or methods that have been used to assess healthy aging in previous epidemiological studies. It also discusses and recommends the essential domains of healthy aging, and the relevant instruments for further epidemiological research to use in the assessment of healthy aging.

Individual healthy aging indices, measurements and scores

The positive gerontological approach to aging has resulted in successive terminologies to describe the process of aging, including successful aging, active aging, healthy aging, or healthy and active aging, amongst others. Each definition proposed by geriatricians, psychologists, sociologists or public health specialists has been based on specific aspects of aging that are most important to the authors' discipline, explaining the current difficulty in determining which is the best set of criteria to determine "good aging". Two successive analyses of the measurements used in longitudinal studies from 1989 to 2018 testify to this heterogeneity in the types of questions proposed to evaluate the quality of the individual aging process. To confront this complexity, new and integrated indices have successively been proposed to quantify and qualify the survival period of aging individuals. The present paper aims to describe and compare the value of the "healthy aging index", the "modified healthy aging index", the "healthy aging score" and the "selfie aging test". Attempts to date to identify the best individual measurement of "aging well" have been interesting, and certainly show promise, but their limitations to specific populations call for more concerted effort from the scientific community to obtain worldwide validation. Another option would be to identify the best self-assessment questionnaire and include it in a mobile device, enabling longer term personal follow-up of aging functions. There is a clear lack of data of this type at present, and an urgent need to obtain such information, to enable early and targeted interventions.

Effect of Intentional Weight Loss on Mortality Biomarkers in Older Adults With Obesity

BACKGROUND

Observational research has identified several mortality biomarkers; however, their responsiveness to change is unknown. We tested whether the Healthy Aging Index (HAI) and other mortality biomarkers were responsive to intentional weight loss (WL), which is associated with lower mortality risk in recent meta-analyses.

METHODS

Older adults (70.3 ± 3.7 years) with obesity were randomized into a 6-month WL (n = 47) or weight stability (WS: ±5% baseline weight; n = 48) program. Baseline and 6-month HAI score (0-10) was calculated from component sum (each 0-2: systolic blood pressure, forced vital capacity [FVC], creatinine, fasting blood glucose [FBG], Montreal Cognitive Assessment), and gait speed, grip strength, Digit Symbol Substitution Test, FEV1, Interleukin-6, C-Reactive Protein, and Cystatin-C were assessed at baseline and 6 months.

RESULTS

Mean baseline HAI was 3.2 ± 1.6. By 6 months, WL participants lost 8.87 (95% CI: -10.40, -7.34) kg, whereas WS participants remained weight stable. WL group reduced HAI score (WL: -0.75 [95% CI: -1.11, -0.39] vs WS: -0.22 [95% CI: -0.60, 0.15]; p = .04), and components changing the most were FBG (WL: -3.89 [95% CI: -7.78, 0.00] mg/dL vs WS: 1.45 [95% CI: -2.61, 5.50] mg/dL; p = .047) and FVC (WL: 0.11 [95% CI: -0.01, 0.23] L vs WS: -0.05 [95% CI: -0.17, 0.08] L; p = .06). Among other biomarkers, only Cystatin-C significantly changed (WL: -2.53 [95% CI: -4.38, -0.68] ng/mL vs WS: 0.07 [95% CI: -1.85, 1.98] ng/mL; p = .04). Combining treatment groups, 1 kg WL was associated with a 0.07 (95% CI: 0.03, 0.12) HAI reduction (p < .01).

CONCLUSION

Intentional WL via caloric restriction reduced HAI score by 0.53 points, largely attributable to metabolic and pulmonary improvements.

A framework for selection of blood-based biomarkers for geroscience-guided clinical trials: report from the TAME Biomarkers Workgroup

Recent advances indicate that biological aging is a potentially modifiable driver of late-life function and chronic disease and have led to the development of geroscience-guided therapeutic trials such as TAME (Targeting Aging with MEtformin). TAME is a proposed randomized clinical trial using metformin to affect molecular aging pathways to slow the incidence of age-related multi-morbidity and functional decline. In trials focusing on clinical end-points (e.g., disease diagnosis or death), biomarkers help show that the intervention is affecting the underlying aging biology before sufficient clinical events have accumulated to test the study hypothesis. Since there is no standard set of biomarkers of aging for clinical trials, an expert panel was convened and comprehensive literature reviews conducted to identify 258 initial candidate biomarkers of aging and age-related disease. Next selection criteria were derived and applied to refine this set emphasizing: (1) measurement reliability and feasibility; (2) relevance to aging; (3) robust and consistent ability to predict all-cause mortality, clinical and functional outcomes; and (4) responsiveness to intervention. Application of these selection criteria to the current literature resulted in a short list of blood-based biomarkers proposed for TAME: IL-6, TNFα-receptor I or II, CRP, GDF15, insulin, IGF1, cystatin C, NT-proBNP, and hemoglobin A1c. The present report provides a conceptual framework for the selection of blood-based biomarkers for use in geroscience-guided clinical trials. This work also revealed the scarcity of well-vetted biomarkers for human studies that reflect underlying biologic aging hallmarks, and the need to leverage proposed trials for future biomarker discovery and validation.

Index of Healthy Aging in Chinese Older Adults: China Health and Retirement Longitudinal Study

OBJECTIVES

To characterize the distribution of an index of healthy aging-the Chinese Healthy Aging Index (CHAI)-in Chinese adults aged 60 and older according to sociodemographic characteristics and geographic region and to examine the association between the CHAI and mortality, disability, and functional limitation over 4 years.

DESIGN

Nationally representative cohort study.

SETTING

China Health and Retirement Longitudinal Study.

PARTICIPANTS

Chinese adults aged 60 and older (N=3,740).

MEASUREMENTS

Six CHAI components (systolic blood pressure, peak expiratory flow, Telephone Interview for Cognitive Status, estimated glomerular filtration rate, fasting glucose, C-reactive protein) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the CHAI (range 0-12).

RESULTS

Mean CHAI score was 5.6; 5.7% had a score of 0 to 2 (healthiest), 23.0% a score of 3 or 4, 37.5% a score of 5 or 6, and 33.8% a score of 7 to 12 (unhealthiest). Participants who were younger, more educated, and married were much more likely to have an ideal CHAI profile (score 0-2). Age-adjusted prevalence of an ideal CHAI profile ranged from 1.7% in the south to 8.1% in the north. After multivariable adjustment, persons with a CHAI score of 3 to 12 had substantially higher odds of mortality, disability, and functional limitation than those with a score of 0 to 2. The CHAI further stratified outcomes for persons with no clinically recognizable comorbidities.

CONCLUSION

Substantial variation exists in the CHAI according to sociodemographic characteristics and geographic regions. The CHAI could identify Chinese elderly adults with low risk of adverse outcomes and provide incremental value for risk prediction beyond clinically diagnosed comorbidities.

A Modified Healthy Aging Index and Its Association with Mortality: The National Health and Nutrition Examination Survey, 1999-2002

BACKGROUND

Comorbidity indices that are based on clinically recognized disease do not capture the full spectrum of health. The Healthy Aging Index (HAI) was recently developed to describe a wider range of health and disease across multiple organ systems. We characterized the distribution of a modified HAI (mHAI) by sociodemographics in a representative sample of the U.S. population. We also examined the association of the mHAI with mortality across individuals with different levels of clinically recognizable comorbidities.

METHODS

Data are from the National Health and Nutrition Examination Survey (1999-2000, 2001-2002) on 2,451 adults aged 60 years or older. Five mHAI components (systolic blood pressure, Digit Symbol Substitution Test, cystatin C, glucose, and respiratory problems) were scored 0 (healthiest), 1, or 2 (unhealthiest) by sex-specific tertiles or clinically relevant cutoffs and summed to construct the mHAI.

RESULTS

The mean mHAI score was 4.3; 20.6% had a score of 0-2. 33.2% had a score of 3-4, 31.0% had a score of 5-6, and 15.2% had a score of 7-10. Mean mHAI scores were lower in adults who were younger, non-Hispanic whites, more educated, and married/living with partner. After multivariate adjustment, per unit higher of the mHAI was associated with higher all-cause mortality (HR = 1.19, 95% CI = 1.11-1.27) and higher cardiovascular mortality (HR = 1.23, 95% CI = 1.11-1.35). Within each comorbidity category (0, 1, 2, 3, 4+), the mHAI was still widely distributed and further stratified mortality.

CONCLUSIONS

Substantial variation exists in the mHAI across sociodemographic subgroups. The mHAI could provide incremental value for mortality risk prediction beyond clinically diagnosed chronic diseases among elders.