Functional Aging Index Complements Frailty in Prediction of Entry Into Care and Mortality

Effects from medications on functional biomarkers of aging in three longitudinal studies of aging in Sweden

Antihypertensive, lipid-lowering, and blood glucose-lowering drugs have slowed down the aging process in animal models. In humans, studies are limited, have short follow-up times, and show mixed results. Therefore, this study aimed to estimate the effects of commonly used medications on functional aging, cognitive function, and frailty. We included information on individuals from three Swedish longitudinal population-based studies collected between 1986 and 2014. Our exposures were the 21 most used groups of medications among individuals aged 65 years and older in the Swedish population in 2022. Functional aging index (n = 1191), cognitive function (n = 1094), and frailty index (n = 1361) were the outcomes of interest. To estimate the medication effects, we used a self-controlled analysis, where each individual is his/her own control, thereby adjusting for all time-stable confounders. The analysis was additionally adjusted for time-varying confounders (chronological age, Charlson Comorbidity Index, smoking, body mass index, and the number of drugs). The participants were 65.5-82.8 years at the first in-person assessment. Adrenergics/inhalants (effect size = 0.089) and lipid-modifying agents/plain (effect size = 0.082) were associated with higher values of cognitive function (improvement), and selective calcium channel blockers with mainly vascular effects (effect size = -0.129) were associated with lower values of the functional aging index (improvement). No beneficial effects were found on the frailty index. Adrenergics/inhalants, lipid-modifying agents/plain, and selective calcium channel blockers with mainly vascular effects may benefit functional biomarkers of aging. More research is needed to investigate their clinical value in preventing adverse aging outcomes.

Signs of aging in midlife: physical function and sex differences in microbiota

Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater β-diversity; however, β-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.

Interplay of body mass index and metabolic syndrome: association with physiological age from midlife to late-life

Obesity and metabolic syndrome (MetS) share common pathophysiological characteristics with aging. To better understand their interplay, we examined how body mass index (BMI) and MetS jointly associate with physiological age, and if the associations changed from midlife to late-life. We used longitudinal data from 1,825 Swedish twins. Physiological age was measured as frailty index (FI) and functional aging index (FAI) and modeled independently in linear mixed-effects models adjusted for chronological age, sex, education, and smoking. We assessed curvilinear associations of BMI and chronological age with physiological age, and interactions between BMI, MetS, and chronological age. We found a significant three-way interaction between BMI, MetS, and chronological age on FI (p-interaction = 0·006), not FAI. Consequently, we stratified FI analyses by age: < 65, 65-85, and ≥ 85 years, and modeled FAI across ages. Except for FI at ages ≥ 85, BMI had U-shaped associations with FI and FAI, where BMI around 26-28 kg/m2 was associated with the lowest physiological age. MetS was associated with higher FI and FAI, except for FI at ages < 65, and modified the BMI-FI association at ages 65-85 (p-interaction = 0·02), whereby the association between higher BMI levels and FI was stronger in individuals with MetS. Age modified the MetS-FI association in ages ≥ 85, such that it was stronger at higher ages (p-interaction = 0·01). Low BMI, high BMI, and metabolic syndrome were associated with higher physiological age, contributing to overall health status among older individuals and potentially accelerating aging.

Midlife cumulative deficit frailty predicts Alzheimer's disease-related plasma biomarkers in older adults

BACKGROUND

The study explores whether frailty at midlife predicts mortality and levels of biomarkers associated with Alzheimer's disease and related dementias (ADRD) and neurodegeneration by early old age. We also examine the heritability of frailty across this age period.

METHODS

Participants were 1,286 community-dwelling men from the Vietnam Era Twin Study of Aging at average ages 56, 62 and 68, all without ADRD at baseline. The cumulative deficit frailty index (FI) comprised 37 items assessing multiple physiological systems. Plasma biomarkers at age 68 included beta-amyloid (Aβ40, Aβ42), total tau (t-tau) and neurofilament light chain (NfL).

RESULTS

Being frail doubled the risk of all-cause mortality by age 68 (OR = 2.44). Age 56 FI significantly predicted age 68 NfL (P = 0.014), Aβ40 (P = 0.001) and Aβ42 (P = 0.023), but not t-tau. Age 62 FI predicted all biomarkers at age 68: NfL (P = 0.023), Aβ40 (P = 0.002), Aβ42 (P = 0.001) and t-tau (P = 0.001). Age 68 FI scores were associated with age 68 levels of NfL (P = 0.027), Aβ40 (P < 0.001), Aβ42 (P = 0.001) and t-tau (P = 0.003). Genetic influences accounted for 45-48% of the variance in frailty and significantly contributed to its stability across 11 years.

CONCLUSIONS

Frailty during one's 50s doubled the risk of mortality by age 68. A mechanism linking frailty and ADRD may be through its associations with biomarkers related to neurodegeneration. Cumulative deficit frailty increases with age but remains moderately heritable across the age range studied. With environmental factors accounting for about half of its variance, early interventions aimed at reducing frailty may help to reduce risk for ADRD.

Quantifying Healthy Aging in Older Veterans Using Computational Audio Analysis

BACKGROUND

Researchers are increasingly interested in better methods for assessing the pace of aging in older adults, including vocal analysis. The present study sought to determine whether paralinguistic vocal attributes improve estimates of the age and risk of mortality in older adults.

METHODS

To measure vocal age, we curated interviews provided by male U.S. World War II Veterans in the Library of Congress collection. We used diarization to identify speakers and measure vocal features and matched recording data to mortality information. Veterans (N = 2 447) were randomly split into testing (n = 1 467) and validation (n = 980) subsets to generate estimations of vocal age and years of life remaining. Results were replicated to examine out-of-sample utility using Korean War Veterans (N = 352).

RESULTS

World War II Veterans' average age was 86.08 at the time of recording and 91.28 at the time of death. Overall, 7.4% were prisoners of war, 43.3% were Army Veterans, and 29.3% were drafted. Vocal age estimates (mean absolute error = 3.255) were within 5 years of chronological age, 78.5% of the time. With chronological age held constant, older vocal age estimation was correlated with shorter life expectancy (aHR = 1.10; 95% confidence interval: 1.06-1.15; p < .001), even when adjusting for age at vocal assessment.

CONCLUSIONS

Computational analyses reduced estimation error by 71.94% (approximately 8 years) and produced vocal age estimates that were correlated with both age and predicted time until death when age was held constant. Paralinguistic analyses augment other assessments for individuals when oral patient histories are recorded.

A Scoping Review of the Predictive Qualities of Walking Speed in Older Adults

BACKGROUND AND PURPOSE

Walking speed (WS) is an easily assessable and interpretable functional outcome measure with great utility for the physical therapist providing care to older adults. Since WS was proposed as the sixth vital sign, research into its interpretation and use has flourished. The purpose of this scoping review is to identify the current prognostic value of WS for the older adult.

METHODS

A scoping review was conducted using PubMed, CINAHL, and SPORTDiscus to find relevant articles highlighting the predictive capabilities of WS for older adults. Titles and abstracts were reviewed to identify relevant articles. Articles were excluded based on the following criteria: sample included both younger and older adults without separate analyses, sample was focused on a particular disease, if the study was published before 2017, or if the study did not report relevant cut points for interpretation of WS. The search returned 1064 results. Following removal of articles not meeting inclusion criteria and critical appraisal, relevant cut points were extracted from 47 original research publications.

RESULTS AND DISCUSSION

A preliminary review of the included articles showed that WS is a valuable prognostic tool across many health domains, including mental health, mortality, disability, pain, bone and joint health, falls, cognition, physical activity, metabolic health, risk for cardiovascular disease, socialization, and metabolic health. The fastest WS of 1.32 meters per second (m/s) served as a cutoff for decreased risk for incident development of type 2 diabetes, while the slowest WS of less than 0.2 m/s was associated with increased duration of hospitalization. Multiple studies reported on the prognostic value of WS slower than 1.0 m/s.

CONCLUSION

Although the reported range of predictive WS values was broad, multiple studies found WS of approximately 1.0 m/s to be a useful marker for delineating risk or decline across a variety of health domains. Clinicians may find it useful to use a WS slower than 1.0 m/s as a "yellow flag" to guide evaluation and intervention for their older adult clients.

The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations

Global initiatives call for further understanding of the impact of inequity on aging across underserved populations. Previous research in low- and middle-income countries (LMICs) presents limitations in assessing combined sources of inequity and outcomes (i.e., cognition and functionality). In this study, we assessed how social determinants of health (SDH), cardiometabolic factors (CMFs), and other medical/social factors predict cognition and functionality in an aging Colombian population. We ran a cross-sectional study that combined theory- (structural equation models) and data-driven (machine learning) approaches in a population-based study (N = 23,694; M = 69.8 years) to assess the best predictors of cognition and functionality. We found that a combination of SDH and CMF accurately predicted cognition and functionality, although SDH was the stronger predictor. Cognition was predicted with the highest accuracy by SDH, followed by demographics, CMF, and other factors. A combination of SDH, age, CMF, and additional physical/psychological factors were the best predictors of functional status. Results highlight the role of inequity in predicting brain health and advancing solutions to reduce the cognitive and functional decline in LMICs.

Longitudinal analyses indicate bidirectional associations between loneliness and health

OBJECTIVES

To evaluate temporal dynamics between loneliness and both objective and subjective health (i.e. functional impairment and self-rated health) in mid- to late-adulthood.

METHOD

We applied bivariate dual-change-score models to longitudinal data from 3 Swedish twin studies (N = 1,939) to explore dynamic associations between loneliness and health across 3 age ranges (50-69, 70-81, and 82+ years) to investigate whether associations between loneliness and health change with age due to increasing incidence of chronic health conditions and bereavement.

RESULTS

Results showed bidirectional associations between loneliness and both objective and subjective health, with adverse impacts of loneliness observed on subsequent subjective and objective health beginning at age 70. Associations between health and subsequent loneliness were observed after age 82 and varied for subjective and objective health, with subjective health associated with less loneliness and objective health associated with greater loneliness.

CONCLUSIONS

Our results indicate dynamic associations between loneliness and health with age in mid- to late-adulthood, with earlier impacts of loneliness on health and later impacts of health on loneliness that vary for objective and subjective measures of health. These findings suggest impacts of health on loneliness may arise later in life when worsening health or mobility interfere with social interaction.

Quest for Biomarkers of Positive Health: A Review

The positive health of a person can be defined as the ability to live long in good health, possibly with no activity limitation. No method is yet available for its objective assessment in individuals, and we propose a framework in this communication that can operationalize this concept. Instead of distal factors, such as diet and lifestyle because these are subjective and difficult to measure, we concentrate on the objectively measurable biomarkers such as immunity level, endorphins, and handgrip strength. The focus is on the major parameters that may protect from diseases and infirmity and can be assessed by noninvasive methods. A combination of such parameters may signify positive health. This may be a novel way to measure positive health at the individual level. In this communication, we briefly review the literature and identify a few major biomarkers that provide a protective shield and could determine the status of positive health at the individual level. This exercise demonstrates that the assessment of the positive health of a person is feasible. A scale based on these and other relevant parameters can be developed later that could quantitatively measure the exact level of positive health. As the exact combination of the parameters that protects from ailments is not fully known yet, a framework such as this may help in identifying the data gaps that require attention in this context. The proposed framework may initiate a discussion on indicators of positive health and characterize the parameters for intervention that could increase a healthy life.

Longitudinal associations between use of antihypertensive, antidiabetic, and lipid-lowering medications and biological aging

Aging is a major risk factor for many chronic diseases. This study aimed to examine the effects of antihypertensive, lipid-lowering, and antidiabetic drugs on biological aging. We included 672 participants and 2746 repeated measurements from the Swedish Adoption/Twin Study of Aging. Self-reported medicine uses were categorized into antidiabetic, antihypertensive, and lipid-lowering drugs. A total of 12 biomarkers for biological aging (BA biomarkers) were included as outcomes. Conditional generalized estimating equations were applied conditioning on individuals to estimate the drug effect on BA biomarker level within the same person when using or not using the drug. Chronological age, body mass index, smoking status, number of multiple medication uses, blood pressure, blood glucose level, and apoB/apoA ratio were adjusted for as covariates in the model. Overall, using antihypertensive drugs was associated with a decrease in one DNA-methylation age (PCGrimAge: beta = - 0.39, 95%CI = - 0.67 to - 0.12). When looking into drug subcategories, calcium channel blockers (CCBs) were associated with a decrease in several DNA-methylation ages (PCHorvathAge beta = - 1.28, 95%CI = - 2.34 to - 0.21; PCSkin&bloodAge beta = - 1.34, 95%CI = - 2.61 to - 0.07; PCPhenoAge beta = - 1.74, 95%CI = - 2.58 to - 0.89; PCGrimAge beta = - 0.57, 95%CI = - 0.96 to - 0.17) and in functional biological ages (functional age index beta = - 2.18, 95%CI = - 3.65 to - 0.71; frailty index beta = - 1.31, 95%CI = - 2.43 to - 0.18). However, the results within other drug subcategories were inconsistent. Calcium channel blockers may decrease biological aging captured by the BA biomarkers measured at epigenetic and functional level. Future studies are warranted to confirm these effects and understand the underlying biological mechanisms.

Predictors of Biological Age: The Implications for Wellness and Aging Research

As healthspan and lifespan research breakthroughs have become more commonplace, the need for valid, practical markers of biological age is becoming increasingly paramount. The accessibility and affordability of biological age predictors that can reveal information about mortality and morbidity risk, as well as remaining years of life, has profound clinical and research implications. In this review, we examine 5 groups of aging biomarkers capable of providing accurate biological age estimations. The unique capabilities of these biomarkers have far reaching implications for the testing of both pharmaceutical and non-pharmaceutical interventions designed to slow or reverse biological aging. Additionally, the enhanced validity and availability of these tools may have increasingly relevant clinical value. The authors of this review explore those implications, with an emphasis on lifestyle modification research, and provide an overview of the current evidence regarding 5 biological age predictor categories: Telomere length, composite biomarkers, DNA methylation “epigenetic clocks,” transcriptional predictors of biological age, and functional age predictors.

Early manifestation of gait alterations in the Tg2576 mouse model of Alzheimer's disease

There is strong clinical evidence that multifaceted gait abnormalities may be manifested at early stages of Alzheimer's disease (AD), are related to cognitive decline, and can be used as an early biomarker to identify patients at risk of progressing to full-blown dementia. Despite their importance, gait abnormalities have not been investigated in mouse models of AD, which replicate important aspects of the human disease. The Tg2576 is frequently used in AD research to test therapeutic interventions targeting cellular mechanisms contributing to the genesis of AD. This transgenic mouse strain overexpresses a mutant form of the 695 amino acid isoform of human amyloid precursor protein with K670N and M671L mutations (APPK670/671L) linked to early-onset familial AD. Tg2576 mice exhibit impaired cognitive functions and increased cortical and hippocampal soluble β-amyloid levels starting from 5 months of age and increased insoluble β-amyloid levels and amyloid plaques that resemble senile plaques associated with human AD by 13 months of age. To demonstrate early manifestations of gait dysfunction in this relevant preclinical model, we characterized gait and motor performance in 10-month-old Tg2576 mice and age-matched littermate controls using the semi-automated, highly sensitive, Catwalk XT system. We found that Tg2576 mice at the pre-plaque stage exhibited significantly altered duty cycle and step patterns and decreased stride length and stride time. Base-of-support, stride time variability, stride length variability, cadence, phase dispersions and gait symmetry indices were unaltered. The presence of measurable early gait abnormalities during the pre-plaque stages of AD in this relevant preclinical mouse model has direct translational relevance and supports the view that longitudinal monitoring of gait performance could be used in addition to behavioral testing to evaluate progression of the disease and to assess treatment efficacy.

Sex differences in biological aging with a focus on human studies

Aging is a complex biological process characterized by hallmark features accumulating over the life course, shaping the individual's aging trajectory and subsequent disease risks. There is substantial individual variability in the aging process between men and women. In general, women live longer than men, consistent with lower biological ages as assessed by molecular biomarkers, but there is a paradox. Women are frailer and have worse health at the end of life, while men still perform better in physical function examinations. Moreover, many age-related diseases show sex-specific patterns. In this review, we aim to summarize the current knowledge on sexual dimorphism in human studies, with support from animal research, on biological aging and illnesses. We also attempt to place it in the context of the theories of aging, as well as discuss the explanations for the sex differences, for example, the sex-chromosome linked mechanisms and hormonally driven differences.

Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up

Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50-90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality.

Unexplained periods of higher deaths contribute to marginal changes in health care demand and health insurance costs: International perspectives

Sudden and unexplained increases in hospital medical admissions and population total deaths have been characterized in the United Kingdom. These sudden increases appear to endure for around 1 to 3 years before they abate. This study demonstrates that the sudden increases in deaths also occur in 125 countries and occur at subnational geographies. The magnitude of the sudden increase diminishes as a power law function up to around 10 000 deaths. Above 10 000 deaths, there is only a small decline with increasing size (deaths). At around 10 000 deaths, a 10% maximum sudden increase applies across many countries or subnational regions. The nearness to death effect, where around half of a person's lifetime hospital admissions occurs in the last 6 months of life, results in higher associated increases in medical admissions. This paper confirms that the use of calendar year data can be misleading. Periods of unexplained higher deaths appear to occur in bursts across multiple countries and appear to show spatial spread within the neighbourhoods which constitute the whole country.