Going from bad to worse: a stochastic model of transitions in deficit accumulation, in relation to mortality

Deprivation as a fundamental cause of morbidity and reduced life expectancy: an observational study using German statutory health insurance data

Across all developed countries, there is a steep life expectancy gradient with respect to deprivation. This paper provides a theoretical underpinning for this gradient in line with the Grossman model, indicating that deprivation affects morbidity and, consequently, life expectancy in three ways: directly from deprivation to morbidity, and indirectly through lower income and a trade-off between investments in health and social status. Using rich German claims data covering 6.3 million insured people over four years, this paper illustrates that deprivation increases morbidity and reduces life expectancy. It was estimated that highly deprived individuals had approximately two more chronic diseases and a life expectancy reduced by 15 years compared to the least deprived individuals. This mechanism of deprivation is identified as fundamental, as deprived people remain trapped in their social status, and this status results in health investment decisions that affect long-term morbidity. However, in the German setting, the income and investment paths of the effects of deprivation were of minor relevance due to the broad national coverage of its SHI system. The most important aspects of deprivation were direct effects on morbidity, which accumulate over the lifespan. In this respect, personal aspects, such as social status, were found to be three times more important than spatial aspects, such as area deprivation.

The economics of aging with infectious and chronic diseases

We develop an economic model of aging in which the susceptibility and severity of infectious diseases depend on the accumulated health deficits (immunosenescence) and the life history of infections affects the accumulation of chronic health deficits (inflammaging). Individuals invest in their health to slow down health deficit accumulation and take measures to protect themselves from infectious diseases. We calibrate the model for an average American and explore how health expenditure, life expectancy, and the value of life depend on individual characteristics, medical technology, and the disease environment. We then use counterfactual computational experiments of the U.S. epidemiological transition 1860-2010 to show that the decline of infectious diseases caused a substantial decline of chronic diseases and contributed more to increasing life expectancy than advances in the treatment of chronic diseases.

Physiological aging in India: The role of the epidemiological transition

We construct a cohort-based frailty index from age-related health deficits to investigate physiological aging in India over the period 1990-2019. During this period, the Indian states underwent at different speeds the epidemiological transition and experienced unprecedented economic growth. We show that the rate of physiological aging remained remarkably stable to the changing environment. Age-related health deficits increased by about 3 percent per year of age with little variation across states, ages, cohorts, and over time. We find that, with advancing epidemiological transition, health deficits for given age declined at the individual level (within states and within cohorts). Across cohorts born between 1900 and 1995, we show that, for given age, health deficits are higher for later-born cohorts until birth years around 1940 and remained trendless afterwards. We propose a selection-based theory of aging during the epidemiological transition that explains these facts.

Understanding Alzheimer's disease in the context of aging: Findings from applications of stochastic process models to the Health and Retirement Study

There is growing literature on applications of biodemographic models, including stochastic process models (SPM), to studying regularities of age dynamics of biological variables in relation to aging and disease development. Alzheimer's disease (AD) is especially good candidate for SPM applications because age is a major risk factor for this heterogeneous complex trait. However, such applications are largely lacking. This paper starts filling this gap and applies SPM to data on onset of AD and longitudinal trajectories of body mass index (BMI) constructed from the Health and Retirement Study surveys and Medicare-linked data. We found that APOE e4 carriers are less robust to deviations of trajectories of BMI from the optimal levels compared to non-carriers. We also observed age-related decline in adaptive response (resilience) related to deviations of BMI from optimal levels as well as APOE- and age-dependence in other components related to variability of BMI around the mean allostatic values and accumulation of allostatic load. SPM applications thus allow revealing novel connections between age, genetic factors and longitudinal trajectories of risk factors in the context of AD and aging creating new opportunities for understanding AD development, forecasting trends in AD incidence and prevalence in populations, and studying disparities in those.

Progression of frailty as measured by a cumulative deficit index: A systematic review

BACKGROUND

Frailty is a risk factor for adverse health outcomes. There is a paucity of literature on frailty progression defined by a cumulative deficit model among community dwelling older people. The objective of this review was to synthesise evidence on these changes in health and mortality among community-dwelling older people.

METHODS

Six databases (Medline, Embase, CINAHL, Cochrane, PsycInfo, Web of Science) and a clinical trials registry were searched in July 2021. The inclusion criteria were studies using a frailty index and providing information on transition between frailty states or to death in community-dwelling older people aged ≥ 50. Exclusion criteria were studies examining specific health conditions, conference abstracts and non-English studies. To standardise the follow-up period and facilitate comparison, we converted the transition probabilities to annual transition rates.

RESULTS

Two reviewers independently screened 5078 studies and 61 studies were included for analysis. Of these, only three used the same frailty state cut-points to facilitate cross-cohort comparison. This review found that frailty tends to increase with time, people who are frail at baseline have greater likelihood to progress in frailty and die, and the main factor that accelerates frailty progression is age. Other risk factors for progression are having chronic disease, smoking, obesity, low-income or/and low-education levels. A frailty index is an accurate predictor of adverse outcomes and death.

DISCUSSION

This systematic review demonstrated that worsening in frailty was a common frailty transition, and older people who are frail at baseline are more likely to die. A frailty index has significant power to predict adverse health outcomes. It is a useful tool for within-cohort comparison but there are challenges comparing different cohorts due to dependence of frailty progression on age and differences in how frailty index is defined and measured.

Measurements of damage and repair of binary health attributes in aging mice and humans reveal that robustness and resilience decrease with age, operate over broad timescales, and are affected differently by interventions

As an organism ages, its health-state is determined by a balance between the processes of damage and repair. Measuring these processes requires longitudinal data. We extract damage and repair transition rates from repeated observations of binary health attributes in mice and humans to explore robustness and resilience, which respectively represent resisting or recovering from damage. We assess differences in robustness and resilience using changes in damage rates and repair rates of binary health attributes. We find a conserved decline with age in robustness and resilience in mice and humans, implying that both contribute to worsening aging health - as assessed by the frailty index (FI). A decline in robustness, however, has a greater effect than a decline in resilience on the accelerated increase of the FI with age, and a greater association with reduced survival. We also find that deficits are damaged and repaired over a wide range of timescales ranging from the shortest measurement scales toward organismal lifetime timescales. We explore the effect of systemic interventions that have been shown to improve health, including the angiotensin-converting enzyme inhibitor enalapril and voluntary exercise for mice. We have also explored the correlations with household wealth for humans. We find that these interventions and factors affect both damage and repair rates, and hence robustness and resilience, in age and sex-dependent manners.

A frailty index based on routine laboratory data predicts increased risk of mortality in Chinese community-dwelling adults aged over 55 years: a five-year prospective study

Background

Frailty can be operationalized based on the accumulation of deficits using a frailty index (FI) and is associated with an increased risk of adverse health outcomes. Here, we aim to compare validity of a FI from laboratory data with that of the common clinical FI for prediction of mortality in adults aged 55 + years, also examine whether combined FI could improve identification of adults aged 55 + years at increased risk of death.

Methods

Data for this analysis were obtained from the Beijing Longitudinal Study of Aging that involved 1,257 community-dwelling Chinese people, aged 55 + years at baseline. The main outcome measure was 5-year mortality. An FI-self-report based on 30 self-reported health-related data was constructed. An FI-lab was developed using laboratory data, in addition to pulse, systolic and diastolic blood pressure, pulse pressure, body mass index (BMI) and waist. A combined FI comprised all items from each FI. Kaplan–Meier survival curve and Cox proportional hazards models were performed to evaluate the risk of each FI on death. The area under receiver operating characteristic(ROC) curves were used to compare the discriminative performance of each FI.

Results

Of 1257 participants, 155 died and 156 lost at the end of the 5-year follow-up. The mean FI-self-report score was 0.11 ± 0.10, the FI-lab score was 0.33 ± 0.14 and FI-combined score was 0.19 ± 0.09. Higher frailty level defined by each FI was associated with higher risk of death. After adjustment for age and sex, Cox proportional hazards models showed that the higher scores of frailty were associated with a higher risk of mortality for each FI, the hazard ratios for the FI-self-report and FI-lab and FI-combined were 1.04 (1.03 to 1.05) and 1.02 (1.01 to 1.03) and 1.05 (1.04 to 1.07), respectively. The areas under the ROC curve were 0.79 (0.77–0.82) for the FI-self-report, 0.77(0.75–0.80) for the FI-lab and 0.81(0.78–0.82) for FI-combined.

Conclusions

A FI from laboratory data can stratify older adults at increased risk of death alone and in combination with FI based on self-report data. Assessment in clinical settings of creating an FI using routine collected laboratory data needs to be further developed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03374-z.

A health economic theory of occupational choice, aging, and longevity

In this paper, I propose a life cycle model of occupational choice with endogenous health behavior, aging, and longevity. Health-demanding work leads to a faster accumulation of health deficits and is remunerated with a hazard markup on wages. Health deficit accumulation is also influenced by unhealthy consumption and health care expenditure. I calibrate the model for a 20 year old average American in 2010 and show the following results, among others. Health-demanding work is ceteris paribus preferred by male, young, and healthy individuals with a relatively low level of education. Health demanding work has a negligible effect on health behavior because income and health investment effects largely offset each other, implying that health effects can be attributed almost fully to the direct health burden of work. Better medical technology induces low-skilled individuals to spend a greater part of their life in health-demanding work and thus increases the health gradient of education. High wealth endowments protect against unhealthy occupational choices. I show robustness of the results in an extension of the model with regard to endogenous retirement.

Feature Selection Algorithms Enhance the Accuracy of Frailty Indexes as Measures of Biological Age

Biological age captures some of the variance in life expectancy for which chronological age is not accountable, and it quantifies the heterogeneity in the presentation of the aging phenotype in various individuals. Among the many quantitative measures of biological age, the mathematically uncomplicated frailty/deficit index is simply the proportion of the total health deficits in various health items surveyed in different individuals. We used 3 different statistical methods that are popular in machine learning to select 17-28 health items that together are highly predictive of survival/mortality, from independent study cohorts. From the selected sets, we calculated frailty indexes and Klemera-Doubal's biological age estimates, and then compared their mortality prediction performance using Cox proportional hazards regression models. Our results indicate that the frailty index outperforms age and Klemera-Doubal's biological age estimates, especially among the oldest old who are most prone to biological aging-caused mortality. We also showed that a DNA methylation index, which was generated by applying the frailty/deficit index calculation method to 38 CpG sites that were selected using the same machine learning algorithms, can predict mortality even better than the best performing frailty index constructed from health, function, and blood chemistry.

Cumulative Deficits Frailty Index Predicts Outcomes for Solid Organ Transplant Candidates

Supplemental Digital Content is available in the text.

Despite comprehensive multidisciplinary candidacy assessments to determine appropriateness for solid organ transplantation, limitations persist in identifying candidates at risk of adverse outcomes. Frailty measures may help inform candidacy evaluation. Our main objective was to create a solid organ transplant frailty index (FI), using the cumulative deficits model, from data routinely collected during candidacy assessments. Secondary objectives included creating a social vulnerability index (SVI) from assessment data and evaluating associations between the FI and assessment, waitlist, and posttransplant outcomes.

Clinical outcomes in patients with atrial fibrillation and frailty: insights from the ENGAGE AF-TIMI 48 trial

BACKGROUND

Atrial fibrillation (AF) is common in older people with frailty and is associated with an increased risk of stroke and systemic embolism. Whilst oral anticoagulation is associated with a reduction in this risk, there is a lack of data on the safety and efficacy of direct oral anticoagulants (DOACs) in people with frailty. This study aims to report clinical outcomes of patients with AF in the Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48 (ENGAGE AF-TIMI 48) trial by frailty status.

METHODS

Post hoc analysis of 20,867 participants in the ENGAGE AF-TIMI 48 trial, representing 98.8% of those randomised. This double-blinded double-dummy trial compared two once-daily regimens of edoxaban (a DOAC) with warfarin. Participants were categorised as fit, living with pre-frailty, mild-moderate, or severe frailty according to a standardised index, based upon the cumulative deficit model. The primary efficacy endpoint was stroke or systemic embolism and the safety endpoint was major bleeding.

RESULTS

A fifth (19.6%) of the study population had frailty (fit: n = 4459, pre-frailty: n = 12,326, mild-moderate frailty: n = 3722, severe frailty: n = 360). On average over the follow-up period, the risk of stroke or systemic embolism increased by 37% (adjusted HR 1.37, 95% CI 1.19-1.58) and major bleeding by 42% (adjusted HR 1.42, 1.27-1.59) for each 0.1 increase in the frailty index (four additional health deficits). Edoxaban was associated with similar efficacy to warfarin in every frailty category, and a lower risk of bleeding than warfarin in all but those living with severe frailty.

CONCLUSIONS

Edoxaban was similarly efficacious to warfarin across the frailty spectrum and was associated with lower rates of bleeding except in those with severe frailty. Overall, with increasing frailty, there was an increase in stroke and bleeding risk. There is a need for high-quality, frailty-specific population randomised control trials to guide therapy in this vulnerable population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00781391 . First registered on 28 October 2008.

Aging in the USA: similarities and disparities across time and space

We study biological aging of elderly U.S. Americans born 1904-1966. We use thirteen waves of the Health and Retirement Study and construct a frailty index as the number of health deficits present in a person measured relative to the number of potential deficits. We find that, on average, Americans develop 5% more health deficits per year, that men age slightly faster than women, and that, at any age above 50, Caucasians display significantly fewer health deficits than African Americans. We also document a steady time trend of health improvements. For each year of later birth, health deficits decline on average by about 1%. This health trend is about the same across regions and for men and women, but significantly lower for African Americans compared to Caucasians. In non-linear regressions, we find that regional differences in aging follow a particular regularity, akin to the compensation effect of mortality. Health deficits converge for men and women and across American regions and suggest a life span of the American population of about 97 years.

Multimorbidity Predicts Quality of Life but not Motor Severity in Early Parkinson's Disease

Recent guidance by the National Institute for Health and Care Excellence (NICE) focuses on the management of people with multimorbidity, including Parkinson's disease (PD). To date there has been little exploration of this in neurodegenerative diseases. This study aimed to explore the associations between multimorbidity, motor severity and quality of life (QoL) in early PD. Regression analyses determined whether multimorbidity was significantly associated with disease severity and QoL. Multimorbidity was a small but significant predictor of QoL in people with incident PD, but not motor severity, suggesting that they may benefit from a tailored multidisciplinary approach to care.

Tracking changes in frailty throughout later life: results from a 17-year longitudinal study in the Netherlands

Background

to better understand the development of frailty with ageing requires longitudinal studies over an extended time period.

Objective

to investigate changes in the degree of frailty during later life, and the extent to which changes are determined by socio-demographic characteristics.

Methods

six measurement waves of 1,659 Dutch older adults aged 65 years and over in the Longitudinal Aging Study Amsterdam (LASA) yielded 5,211 observations over 17 years. At each wave, the degree of frailty was measured with a 32-item frailty index (FI), employing the deficit accumulation approach. Socio-demographic characteristics included age, sex, educational level and partner status. Generalized Estimating Equation (GEE) analyses were performed to study longitudinal frailty trajectories.

Results

higher baseline FI scores were observed in older people, women, and those with lower education or without partner. The overall mean FI score at baseline was 0.17, and increased to 0.39 after 17 years. The average doubling time in the number of deficits was 12.6 years, and this was similar in those aged 65-74 years and those aged 75+. Partner status was associated with changes over time in FI score, whereas sex and educational level were not.

Conclusions

this longitudinal study showed that the degree of frailty increased with ageing, faster than the age-related increase previously observed in cross-sectional studies. Even so, the rate of deficit accumulation was relatively stable during later life.

Predictors of transitions in frailty severity and mortality among people aging with HIV

BACKGROUND

People aging with HIV show variable health trajectories. Our objective was to identify longitudinal predictors of frailty severity and mortality among a group aging with HIV.

METHODS

Exploratory analyses employing a multistate transition model, with data from the prospective Modena HIV Metabolic Clinic Cohort Study, based in Northern Italy, begun in 2004. Participants were followed over four years from their first available visit. We included all 963 participants (mean age 46.8±7.1; 29% female; 89% undetectable HIV viral load; median current CD4 count 549, IQR 405-720; nadir CD4 count 180, 81-280) with four-year data. Frailty was quantified using a 31-item frailty index. Outcomes were frailty index score or mortality at four-year follow-up. Candidate predictor variables were baseline frailty index score, demographic (age, sex), HIV-disease related (undetectable HIV viral load, current CD4+ T-cell count, nadir CD4 count, duration of HIV infection, and duration of antiretroviral therapy [ARV] exposure), and behavioral factors (smoking, injection drug use (IDU), and hepatitis C virus co-infection).

RESULTS

Four-year mortality was 3.0% (n = 29). In multivariable analyses, independent predictors of frailty index at follow-up were baseline frailty index (RR 1.06, 95% CI 1.05-1.07), female sex (RR 0.93, 95% CI 0.87-0.98), nadir CD4 cell count (RR 0.96, 95% CI 0.93-0.99), duration of HIV infection (RR 1.06, 95% CI 1.01-1.12), duration of ARV exposure (RR 1.08, 95% CI 1.02-1.14), and smoking pack-years (1.03, 1.01-1.05). Independent predictors of mortality were baseline frailty index (OR 1.19, 1.02-1.38), current CD4 count (0.34, 0.20-0.60), and IDU (2.89, 1.30-6.42).

CONCLUSIONS

Demographic, HIV-disease related, and social and behavioral factors appear to confer risk for changes in frailty severity and mortality among people aging with HIV.

Integrating Frailty Research into the Medical Specialties-Report from a U13 Conference

Although the field of frailty research has expanded rapidly, it is still a nascent concept within the clinical specialties. Frailty, conceptualized as greater vulnerability to stressors because of significant depletion of physiological reserves, predicts poorer outcomes in several medical specialties, including cardiology, human immunodeficiency virus care, and nephrology, and in the behavioral and social sciences. Lack of a consensus definition, proliferation of measurement tools, inadequate understanding of the biology of frailty, and lack of validated clinical algorithms for frail individuals hinders incorporation of frailty assessment and frailty research into the specialties. In 2015, the American Geriatrics Society, the National Institute on Aging (NIA), and the Alliance for Academic Internal Medicine held a conference for awardees of the NIA-sponsored Grants for Early Medical/Surgical Specialists Transition into Aging Research program to review the current state of knowledge regarding frailty in the subspecialties and to highlight examples of integrating frailty research into the medical specialties. Research questions to advance frailty research into specialty medicine are proposed.

Aging, frailty and complex networks

When people age their mortality rate increases exponentially, following Gompertz's law. Even so, individuals do not die from old age. Instead, they accumulate age-related illnesses and conditions and so become increasingly vulnerable to death from various external and internal stressors. As a measure of such vulnerability, frailty can be quantified using the frailty index (FI). Larger values of the FI are strongly associated with mortality and other adverse health outcomes. This association, and the insensitivity of the FI to the particular health variables that are included in its construction, makes it a powerful, convenient, and increasingly popular integrative health measure. Still, little is known about why the FI works so well. Our group has recently developed a theoretical network model of health deficits to better understand how changes in health are captured by the FI. In our model, health-related variables are represented by the nodes of a complex network. The network has a scale-free shape or "topology": a few nodes have many connections with other nodes, whereas most nodes have few connections. These nodes can be in two states, either damaged or undamaged. Transitions between damaged and non-damaged states are governed by the stochastic environment of individual nodes. Changes in the degree of damage of connected nodes change the local environment and make further damage more likely. Our model shows how age-dependent acceleration of the FI and of mortality emerges, even without specifying an age-damage relationship or any other time-dependent parameter. We have also used our model to assess how informative individual deficits are with respect to mortality. We find that the information is larger for nodes that are well connected than for nodes that are not. The model supports the idea that aging occurs as an emergent phenomenon, and not as a result of age-specific programming. Instead, aging reflects how damage propagates through a complex network of interconnected elements.

The frailty index outperforms DNA methylation age and its derivatives as an indicator of biological age

The measurement of biological age as opposed to chronological age is important to allow the study of factors that are responsible for the heterogeneity in the decline in health and function ability among individuals during aging. Various measures of biological aging have been proposed. Frailty indices based on health deficits in diverse body systems have been well studied, and we have documented the use of a frailty index (FI₃₄) composed of 34 health items, for measuring biological age. A different approach is based on leukocyte DNA methylation. It has been termed DNA methylation age, and derivatives of this metric called age acceleration difference and age acceleration residual have also been employed. Any useful measure of biological age must predict survival better than chronological age does. Meta-analyses indicate that age acceleration difference and age acceleration residual are significant predictors of mortality, qualifying them as indicators of biological age. In this article, we compared the measures based on DNA methylation with FI₃₄. Using a well-studied cohort, we assessed the efficiency of these measures side by side in predicting mortality. In the presence of chronological age as a covariate, FI₃₄ was a significant predictor of mortality, whereas none of the DNA methylation age-based metrics were. The outperformance of FI₃₄ over DNA methylation age measures was apparent when FI₃₄ and each of the DNA methylation age measures were used together as explanatory variables, along with chronological age: FI₃₄ remained significant but the DNA methylation measures did not. These results indicate that FI₃₄ is a robust predictor of biological age, while these DNA methylation measures are largely a statistical reflection of the passage of chronological time.

Reversible States of Physical and/or Cognitive Dysfunction: A 9-Year Longitudinal Study

OBJECTIVES

To determine 1) age-adjusted transition probabilities to worsening physical/cognitive function states, reversal to normal cognition/physical function, or maintenance of normal state; 2) whether these transitions are modulated by sex, BMI, education, hypertension (HTN), health status, or APOE4; 3) whether worsening gait speed preceded cognition change, or vice versa.

DESIGN

Analysis of 9-year prospective cohort data from the New Mexico Aging Process Study.

SETTING

Healthy independent-living adults.

PARTICIPANTS

60+ years of age (n= 598).

MEASUREMENTS

Gait speed, cognitive function (3MSE score), APOE4, HTN, BMI, education, health status.

RESULTS

Over 9 years, 2129 one-year transitions were observed. 32.6% stayed in the same state, while gait speed and cognitive function (3MSE scores) improved for 38% and 43% of participants per year, respectively. Transitions to improved function decreased with age (P< 0.001), APOE4 status (P=0.02), BMI (P=0.009), and health status (P=0.009). Transitions to worse function were significantly increased for the same factors (all P<0.05). Times to lower gait speed and cognitive function did not precede each other (P=0.91).

CONCLUSIONS

Transitions in gait speed and cognition were mutable with substantial likelihood of transition to improvement in physical and cognitive function even in oldest-old, which may have clinical implications for treatment interventions.

Network model of human aging: Frailty limits and information measures

Aging is associated with the accumulation of damage throughout a persons life. Individual health can be assessed by the Frailty Index (FI). The FI is calculated simply as the proportion f of accumulated age-related deficits relative to the total, leading to a theoretical maximum of f≤1. Observational studies have generally reported a much more stringent bound, with f≤f_{max}<1. The value of f_{max} in observational studies appears to be nonuniversal, but f_{max}≈0.7 is often reported. A previously developed network model of individual aging was unable to recover f_{max}<1 while retaining the other observed phenomenology of increasing f and mortality rates with age. We have developed a computationally accelerated network model that also allows us to tune the scale-free network exponent α. The network exponent α significantly affects the growth of mortality rates with age. However, we are only able to recover f_{max} by also introducing a deficit sensitivity parameter 1-q, which is equivalent to a false-negative rate q. Our value of q=0.3 is comparable to finite sensitivities of age-related deficits with respect to mortality that are often reported in the literature. In light of nonzero q, we use mutual information I to provide a nonparametric measure of the predictive value of the FI with respect to individual mortality. We find that I is only modestly degraded by q<1, and this degradation is mitigated when increasing number of deficits are included in the FI. We also find that the information spectrum, i.e., the mutual information of individual deficits versus connectivity, has an approximately power-law dependence that depends on the network exponent α. Mutual information I is therefore a useful tool for characterizing the network topology of aging populations.

A frailty index based on laboratory deficits in community-dwelling men predicted their risk of adverse health outcomes

BACKGROUND

abnormal laboratory test results accumulate with age and can be common in people with few clinically detectable health deficits. A frailty index (FI) based entirely on common physiological and laboratory tests (FI-Lab) might offer pragmatic and scientific advantages compared with a clinical FI (FI-Clin).

OBJECTIVES

to compare the FI-Lab with the FI-Clin and to assess their individual and combined relationships with mortality and other adverse health outcomes.

DESIGN AND SUBJECTS

secondary analysis of the eight-centre, longitudinal European Male Ageing Study (EMAS) of community-dwelling men aged 40-79 at baseline. Follow-up assessment occurred 4.4 ± 0.3 (mean ± SD) years later.

METHODS

we constructed a 23-item FI using common laboratory tests, blood pressure and pulse (FI-Lab), compared it with a previously validated 39-item FI using self-report and performance-based measures (FI-Clin) and finally combined both FIs to create a 62-item FI-Combined. Outcomes were all-cause mortality, institutionalisation, doctor visits, medication use, self-reported health, falls and fractures.

RESULTS

the mean FI-Lab score was 0.28 ± 0.11, the FI-Clin was 0.13 ± 0.11 and FI-Combined was 0.19 ± 0.09. Age-adjusted models demonstrated that each FI was associated with mortality [HR (CI) FI-Lab: 1.04 (1.03-1.06); FI-Clin: 1.05 (1.04-1.06); FI-Combined: 1.07 (1.06-1.09)], institutionalisation, doctor visits, medication use, self-reported health and falls. Combined in a model with FI-Clin, the FI-Lab remained independently associated with mortality, institutionalisation, doctor visits, medication use and self-reported health.

CONCLUSIONS

the FI-Lab detected an increased risk of adverse health outcomes alone and in combination with a clinical FI; further evaluation of the feasibility of the FI-Lab as a frailty screening tool within hospital care settings is needed.

Frailty Change and Major Osteoporotic Fracture in the Elderly: Data from the Global Longitudinal Study of Osteoporosis in Women 3-Year Hamilton Cohort

Investigating the cumulative rate of deficits and the change of a frailty index (FI) chronologically is helpful in clinical and research settings in the elderly. However, limited evidence for the change of frailty before and after some nonfatal adverse health event such as a major osteoporotic fracture (MOF) is available. Data from the Global Longitudinal Study of Osteoporosis in Women 3-Year Hamilton cohort were used in this study. The changes of FI before and after onset of MOF were compared between the women with and without incident MOF. We also evaluated the relationship between risk of MOF, falls, and death and the change of FI and the absolute FI measures. There were 3985 women included in this study (mean age 69.4 years). The change of FI was significantly larger in the women with MOF than those without MOF at year 1 (0.085 versus 0.067, p = 0.036) and year 2 (0.080 versus 0.052, p = 0.042) post-baseline. The FI change was not significantly related with risk of MOF independently of age. However, the absolute FI measures were significantly associated with increased risk of MOF, falls, and death independently of age. In summary, the increase of the FI is significantly larger in the elderly women experiencing a MOF than their peer controls, indicating their worsening frailty and greater deficit accumulation after a MOF. Measures of the FI change may aid in the understanding of cumulative aging nature in the elderly and serve as an instrument for intervention planning and assessment.

Dynamical network model for age-related health deficits and mortality

How long people live depends on their health, and how it changes with age. Individual health can be tracked by the accumulation of age-related health deficits. The fraction of age-related deficits is a simple quantitative measure of human aging. This quantitative frailty index (F) is as good as chronological age in predicting mortality. In this paper, we use a dynamical network model of deficits to explore the effects of interactions between deficits, deficit damage and repair processes, and the connection between the F and mortality. With our model, we qualitatively reproduce Gompertz's law of increasing human mortality with age, the broadening of the F distribution with age, the characteristic nonlinear increase of the F with age, and the increased mortality of high-frailty individuals. No explicit time-dependence in damage or repair rates is needed in our model. Instead, implicit time-dependence arises through deficit interactions-so that the average deficit damage rates increase, and deficit repair rates decrease, with age. We use a simple mortality criterion, where mortality occurs when the most connected node is damaged.

Predicting all-cause mortality from basic physiology in the Framingham Heart Study

Using longitudinal data from a cohort of 1349 participants in the Framingham Heart Study, we show that as early as 28-38 years of age, almost 10% of variation in future lifespan can be predicted from simple clinical parameters. Specifically, we found diastolic and systolic blood pressure, blood glucose, weight, and body mass index (BMI) to be relevant to lifespan. These and similar parameters have been well-characterized as risk factors in the relatively narrow context of cardiovascular disease and mortality in middle to old age. In contrast, we demonstrate here that such measures can be used to predict all-cause mortality from mid-adulthood onward. Further, we find that different clinical measurements are predictive of lifespan in different age regimes. Specifically, blood pressure and BMI are predictive of all-cause mortality from ages 35 to 60, while blood glucose is predictive from ages 57 to 73. Moreover, we find that several of these parameters are best considered as measures of a rate of 'damage accrual', such that total historical exposure, rather than current measurement values, is the most relevant risk factor (as with pack-years of cigarette smoking). In short, we show that simple physiological measurements have broader lifespan-predictive value than indicated by previous work and that incorporating information from multiple time points can significantly increase that predictive capacity. In general, our results apply equally to both men and women, although some differences exist.

Non-coding genomic regions possessing enhancer and silencer potential are associated with healthy aging and exceptional survival

We have completed a genome-wide linkage scan for healthy aging using data collected from a family study, followed by fine-mapping by association in a separate population, the first such attempt reported. The family cohort consisted of parents of age 90 or above and their children ranging in age from 50 to 80. As a quantitative measure of healthy aging, we used a frailty index, called FI34, based on 34 health and function variables. The linkage scan found a single significant linkage peak on chromosome 12. Using an independent cohort of unrelated nonagenarians, we carried out a fine-scale association mapping of the region suggestive of linkage and identified three sites associated with healthy aging. These healthy-aging sites (HASs) are located in intergenic regions at 12q13-14. HAS-1 has been previously associated with multiple diseases, and an enhancer was recently mapped and experimentally validated within the site. HAS-2 is a previously uncharacterized site possessing genomic features suggestive of enhancer activity. HAS-3 contains features associated with Polycomb repression. The HASs also contain variants associated with exceptional longevity, based on a separate analysis. Our results provide insight into functional genomic networks involving non-coding regulatory elements that are involved in healthy aging and longevity.

Quantitative measures of healthy aging and biological age

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including 'successful aging' and 'frailty', have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the 'frailty index', which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity.

Statistical distance as a measure of physiological dysregulation is largely robust to variation in its biomarker composition

Physiological dysregulation may underlie aging and many chronic diseases, but is challenging to quantify because of the complexity of the underlying systems. Recently, we described a measure of physiological dysregulation, D_M, that uses statistical distance to assess the degree to which an individual’s biomarker profile is normal versus aberrant. However, the sensitivity of D_M to details of the calculation method has not yet been systematically assessed. In particular, the number and choice of biomarkers and the definition of the reference population (RP, the population used to define a “normal” profile) may be important. Here, we address this question by validating the method on 44 common clinical biomarkers from three longitudinal cohort studies and one cross-sectional survey. D_Ms calculated on different biomarker subsets show that while the signal of physiological dysregulation increases with the number of biomarkers included, the value of additional markers diminishes as more are added and inclusion of 10-15 is generally sufficient. As long as enough markers are included, individual markers have little effect on the final metric, and even D_Ms calculated from mutually exclusive groups of markers correlate with each other at r~0.4-0.5. We also used data subsets to generate thousands of combinations of study populations and RPs to address sensitivity to differences in age range, sex, race, data set, sample size, and their interactions. Results were largely consistent (but not identical) regardless of the choice of RP; however, the signal was generally clearer with a younger and healthier RP, and RPs too different from the study population performed poorly. Accordingly, biomarker and RP choice are not particularly important in most cases, but caution should be used across very different populations or for fine-scale analyses. Biologically, the lack of sensitivity to marker choice and better performance of younger, healthier RPs confirm an interpretation of D_M physiological dysregulation and as an emergent property of a complex system.

No evidence that frailty modifies the positive impact of antihypertensive treatment in very elderly people: an investigation of the impact of frailty upon treatment effect in the HYpertension in the Very Elderly Trial (HYVET) study, a double-blind, placebo-controlled study of antihypertensives in people with hypertension aged 80 and over

BACKGROUND

Treatment for hypertension with antihypertensive medication has been shown to reduce stroke, cardiovascular events, and mortality in older adults, but there is concern that such treatment may not be appropriate in frailer older adults. To investigate whether there is an interaction between effect of treatment for hypertension and frailty in older adults, we calculated the frailty index (FI) for all available participants from the HYpertension in the Very Elderly Trial (HYVET) study, a double-blind, placebo-controlled study of antihypertensives in people with hypertension aged 80 and over, and obtained frailty adjusted estimates of the effect of treatment with antihypertensive medication on risk of stroke, cardiovascular events, and mortality.

METHODS

Participants in HYVET were randomised 1:1 to active treatment with indapamide sustained release 1.5 mg ± perindopril 2 to 4 mg or to matching placebo. Data relating to blood pressure, comorbidities, cognitive function, depression, and quality of life were collected at entry into the study and at subsequent follow-up visits. The FI was calculated at entry, based on 60 potential deficits. The distribution of FI was similar to that seen in population studies of adults aged 80 years and above (median FI, 0.17; IQR, 0.11-0.24). Cox regression was used to assess the impact of FI at entry to the study on subsequent risk of stroke, total mortality, and cardiovascular events. Models were stratified by region of recruitment and adjusted for sex and age at entry. Extending these models to include a term for a possible interaction between treatment for hypertension and FI provided a formula for the treatment effect as a function of FI. For all three models, the point estimates of the hazard ratios for the treatment effect decreased as FI increased, although to varying degrees and with varying certainty.

RESULTS

We found no evidence of an interaction between effect of treatment for hypertension and frailty as measured by the FI. Both the frailer and the fitter older adults with hypertension appeared to gain from treatment.

CONCLUSIONS

Further work to examine whether antihypertensive treatment modifies frailty as measured by the FI should be explored.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00122811 (July 2005).

Frailty in the Honolulu-Asia Aging Study: deficit accumulation in a male cohort followed to 90% mortality

BACKGROUND

A frailty index (FI) based on the accumulation of deficits typically has a submaximal limit at about 0.70. The objectives of this study were to examine how population characteristics of the FI change in the Honolulu-Asia Aging Study cohort, which has been followed to near-complete mortality. In particular, we were interested to see if the limit was exceeded.

METHODS

Secondary analysis of six waves of the Honolulu-Asia Aging Study. Men (n = 3,801) aged 71-93 years at baseline (1991) were followed until death (N = 3,455; 90.9%) or July 2012. FIs were calculated across six waves and the distribution at each wave was evaluated. Kaplan-Meier analyses and Cox proportional hazard models were performed to examine the relationship of frailty with mortality.

RESULTS

At each wave, frailty was nonlinearly associated with age, with acceleration in later years. The distributions of the FIs were skewed with long right tails. Despite the increasing mortality in each successive wave, the 99% submaximal limit never exceeded 0.65. The risk of death increased with increasing values of the FI (eg, the hazard rate increased by 1.44 [95% CI = 1.39-1.49] with each increment in the baseline FI grouping). Depending on the wave, the median survival of people with FI more than 0.5 ranged 0.84-2.04 years.

CONCLUSIONS

Even in a study population followed to almost complete mortality, the limit to deficit accumulation did not exceed 0.65, confirming a quantifiable, maximum number of health deficits that older men can tolerate.

Screening for frailty in primary care: a systematic review of the psychometric properties of the frailty index in community-dwelling older people

Background

To better accommodate for the complex care needs of frail, older people, general practitioners must be capable of easily identifying frailty in daily clinical practice, for example, by using the frailty index (FI). To explore whether the FI is a valid and adequate screening instrument for primary care, we conducted a systematic review of its psychometric properties.

Methods

We searched the Cochrane, PubMed and Embase databases and included original studies focusing on the criterion validity, construct validity and responsiveness of the FI when applied in community-dwelling older people. We evaluated the quality of the studies included using the Quality in Prognosis Studies (QUIPS) tool. This systematic review was conducted based on the PRISMA statement.

Results

Of the twenty studies identified, eighteen reported on FIs derived from research data, one reported upon an FI derived from an administrative database of home-care clients, and one reported upon an FI derived from routine primary care data. In general, the FI showed good criterion and construct validity but lacked studies on responsiveness. When compared with studies that used data gathered for research purposes, there are indications that the FI mean score and range might be different in datasets using routine primary care data; however, this finding needs further investigation.

Conclusions

Our results suggest that the FI is a valid frailty screening instrument. However, further research using routine Electronic Medical Record data is necessary to investigate whether the psychometric properties of the FI are generalizable to a primary care setting and to facilitate its interpretation and implementation in daily clinical practice.

Trial registration

PROSPERO systematic review register number: CRD42013003737.

Comparison of alternate scoring of variables on the performance of the frailty index

Background

The frailty index (FI) is used to measure the health status of ageing individuals. An FI is constructed as the proportion of deficits present in an individual out of the total number of age-related health variables considered. The purpose of this study was to systematically assess whether dichotomizing deficits included in an FI affects the information value of the whole index.

Methods

Secondary analysis of three population-based longitudinal studies of community dwelling individuals: Nova Scotia Health Survey (NSHS, n = 3227 aged 18+), Survey of Health, Ageing and Retirement in Europe (SHARE, n = 37546 aged 50+), and Yale Precipitating Events Project (Yale-PEP, n = 754 aged 70+). For each dataset, we constructed two FIs from baseline data using the deficit accumulation approach. In each dataset, both FIs included the same variables (23 in NSHS, 70 in SHARE, 33 in Yale-PEP). One FI was constructed with only dichotomous values (marking presence or absence of a deficit); in the other FI, as many variables as possible were coded as ordinal (graded severity of a deficit). Participants in each study were followed for different durations (NSHS: 10 years, SHARE: 5 years, Yale PEP: 12 years).

Results

Within each dataset, the difference in mean scores between the ordinal and dichotomous-only FIs ranged from 0 to 1.5 deficits. Their ability to predict mortality was identical; their absolute difference in area under the ROC curve ranged from 0.00 to 0.02, and their absolute difference between Cox Hazard Ratios ranged from 0.001 to 0.009.

Conclusions

Analyses from three diverse datasets suggest that variables included in an FI can be coded either as dichotomous or ordinal, with negligible impact on the performance of the index in predicting mortality.

Characteristics of the least frail adults with intellectual disabilities: a positive biology perspective

The current study focuses on the characteristics of older people with intellectual disabilities with the lowest frailty levels. Frailty is an increased risk of adverse health outcomes and dependency. Older adults with intellectual disabilities (ID) show more signs of early frailty than the general population. Knowledge of the least frail group characteristics may provide insight into possibilities to prevent early frailty in older people with intellectual disabilities. This study was part of the Healthy Aging and Intellectual Disability study (HA-ID) which incorporated 1050 adults aged 50 years and over with all levels of ID. Frailty was measured with a frailty index. The least frail group was selected based on a frailty index score ≤ 0.10. Odds ratios were used to compare the occurrence of health deficits in the least frail group to the remaining group. The least frail group consisted of 65 participants, corresponding with 6.6% of the study population. The least frail group was significantly younger, had less severe levels of ID, and less often Down syndrome than the remaining group. The lack of mobility and physical fitness limitations, dependence, no signs of depression/dementia, and little medical problems characterized the least frail group. The percentage of 50+ adults with intellectual disabilities within the least frail group is very low compared to that in the general aging population (>43%). Interventions to prevent or delay frailty in this population are highly recommended and can focus on health characteristics of the least frail group.

Association of healthy aging with parental longevity

Various measures incorporated in geriatric assessment have found their way into frailty indices (FIs), which have been used as indicators of survival/mortality and longevity. Our goal is to understand the genetic basis of healthy aging to enhance its evidence base and utility. We constructed a FI as a quantitative measure of healthy aging and examined its characteristics and potential for genetic analyses. Two groups were selected from two separate studies. One group (OLLP for offspring of long-lived parents) consisted of unrelated participants at least one of whose parents was age 90 or older, and the other group of unrelated participants (OSLP for offspring of short-lived parents), both of whose parents died before age 76. FI34 scores were computed from 34 common health variables and compared between the two groups. The FI34 was better correlated than chronological age with mortality. The mean FI34 value of the OSLP was 31 % higher than that of the OLLP (P = 0.0034). The FI34 increased exponentially, at an instantaneous rate that accelerated 2.0 % annually in the OLLP (P = 0.024) and 2.7 % in the OSLP (P < < 0.0001) consequently yielding a 63 % larger accumulation in the latter group (P = 0.0002). The results suggest that accumulation of health deficiencies over the life course is not the same in the two groups, likely due to inheritance related to parental longevity. Consistent with this, sib pairs were significantly correlated regarding FI34 scores, and heritability of the FI34 was estimated to be 0.39. Finally, hierarchical clustering suggests that the OLLP and OSLP differ in their aging patterns. Variation in the FI34 is, in part, due to genetic variation; thus, the FI34 can be a phenotypic measure suitable for genetic analyses of healthy aging.

Assessing biological aging: the origin of deficit accumulation

The health of individuals is highly heterogeneous, as is the rate at which they age. To account for such heterogeneity, we have suggested that an individual’s health status can be represented by the number of health deficits (broadly defined by biological and clinical characteristics) that they accumulate. This allows health to be expressed in a single number: the frailty index (FI) is the ratio of the deficits present in a person to the total number of deficits considered (e.g. in a given database or experimental procedure). Changes in the FI characterize the rate of individual aging. The behavior of the FI is highly characteristic: it shows an age specific, nonlinear increase, (similar to Gompertz law), higher values in females, strong associations with adverse outcomes (e.g., mortality), and a universal limit to its increase (at FI ~0.7). These features have been demonstrated in dozens of studies. Even so, little is known about the origin of deficit accumulation. Here, we apply a stochastic dynamics framework to illustrate that the average number of deficits present in an individual is the product of the average intensity of the environmental stresses and the average recovery time. The age-associated increase in recovery time results in the accumulation of deficits. This not only explains why the number of deficits can be used to estimate individual differences in aging rates, but also suggests that targeting the recovery rate (e.g. by preventive or therapeutic interventions) will decrease the number of deficits that individuals accumulate and thereby benefit life expectancy.

New horizons in frailty: ageing and the deficit-scaling problem

All the current frailty measures count deficits. They differ chiefly in which items, and how many, they consider. These differences are related: if a measure considers only a few items, to define broad risks those items need to integrate across several systems (e.g. mobility or function). If many items are included, the cumulative effect of small deficits can be considered. Even so, it is not clear just how small deficits can be. To better understand how the scale of deficit accumulation might impact frailty measurement, we consider how age-related, subcellular deficits might become macroscopically visible and so give rise to frailty. Cellular deficits occur when subcellular damage has neither been repaired nor cleared. With greater cellular deficit accumulation, detection becomes more likely. Deficit detection can be done by either subclinical (e.g. laboratory, imaging, electrodiagnostic) or clinical methods. Not all clinically evident deficits need cross a disease threshold. The extent to which cellular deficit accumulation compromises organ function can reflect not just what is happening in that organ system, but deficit accumulation in other organ systems too. In general, frailty arises in relation to the number of organ systems in which deficits accumulate. This understanding of how subcellular deficits might scale has implications for understanding frailty as a vulnerability state. Considering the cumulative effects of many small deficits appears to allow important aspects of the behaviour of systems close to failure to be observed. It also suggests the potential to detect frailty with less reliance on clinical observation than current methods employ.

Identifying needs and improving palliative care of chronically ill patients: a community-oriented, population-based, public-health approach

PURPOSE OF REVIEW

We describe conceptual innovations in palliative care epidemiology and the methods to identify patients in need of palliative care, in all settings.In middle-high-income countries, more than 75% of the population will die from chronic progressive diseases. Around 1.2-1.4% of such populations suffer from chronic advanced conditions, with limited life expectancy. Clinical status deteriorates progressively with frequent crises of needs, high social impact, and high use of costly healthcare resources.

RECENT FINDINGS

The innovative concept of patients with advanced chronic diseases and limited life prognosis has been addressed recently, and several methods to identify them have been developed.

SUMMARY

The challenges are to promote early and shared interventions, extended to all patients in need, in all settings of the social care and healthcare systems; to design and develop Palliative Care Programmes with a Public Health perspective. The first action is to identify, using the appropriate tools early in the clinical evolution of the disease, all patients in need of palliative care in all settings of care, especially in primary care services, nursing homes, and healthcare services responsible for care provision for these patients; to promote appropriate care in patients with advanced diseases with prognosis of poor survival.

The impact of social vulnerability on the survival of the fittest older adults

BACKGROUND

even older adults who are fit experience adverse health outcomes; understanding their risks for adverse outcomes may offer insight into ambient population health. Here, we evaluated mortality risk in relation to social vulnerability among the fittest older adults in a representative community-dwelling sample of older Canadians.

METHODS

in this secondary analysis of the Canadian Study of Health and Aging, participants (n = 5,703) were aged 70+ years at baseline. A frailty index was used to grade relative levels of fitness/frailty, using 31 self-reported health deficits. The analysis was limited to the fittest people (those reporting 0-1 health deficit). Social vulnerability was trichotomised from a social vulnerability scale, which consisted of 40 self-reported social deficits.

RESULTS

five hundred and eighty-four individuals had 0-1 health deficit. Among them, absolute mortality risk rose with increasing social vulnerability. In those with the lowest level of social vulnerability, 5-year mortality was 10.8%, compared with 32.5% for those with the highest social vulnerability (adjusted hazard ratio 2.5, 95% CI: 1.5-4.3, P = 0.001).

CONCLUSIONS

a 22% absolute mortality difference in the fittest older adults is of considerable clinical and public health importance. Routine assessment of social vulnerability by clinicians could have value in predicting the risk of adverse health outcomes in older adults.

Persistent pain and frailty: a case for homeostenosis

OBJECTIVES

To compare the association between self-reported moderate to severe pain and frailty.

DESIGN

Cross-sectional analysis of the Canadian Study of Health and Aging Wave 2.

SETTING

Community.

PARTICIPANTS

Representative sample of persons aged 65 and older in Canada.

MEASUREMENTS

Pain (exposure) was categorized as no or very mild pain versus moderate or greater pain. Frailty (outcome) was operationalized as the accumulation of 33 possible self-reported health attitudes, illnesses, and functional abilities, subsequently divided into tertiles (not frail, prefrail, and frail). Multivariable logistic regression assessed for the association between pain and frailty.

RESULTS

Of participants who reported moderate or greater pain (35.5%, 1,765/4,968), 16.2% were not frail, 34.1% were prefrail, and 49.8% were frail. For persons with moderate or greater pain, the odds of being prefrail rather than not frail were higher by a factor of 2.52 (95% confidence interval (CI) = 2.13-2.99; P < .001). For persons with moderate or greater pain, the odds of being frail rather than not frail were higher by a factor of 5.52 (95% CI = 4.49-6.64 P < .001).

CONCLUSION

Moderate or higher pain was independently associated with frailty. Although causality cannot be ascertained in a cross-sectional analysis, interventions to improve pain management may help prevent or ameliorate frailty.

Transitions in cognitive status in relation to frailty in older adults: a comparison of three frailty measures

OBJECTIVES

Cognitive decline is related to frailty. Frailty can be operationalized in different ways, which have an unknown impact on the estimation of risk. Here, we compared 3 frailty measures in relation to cognitive changes and mortality in the Canadian Study of Health and Aging (CSHA).

DESIGN

Prospective population-based study, with 5 year follow up.

PARTICIPANTS/SETTING

2,305 subjects aged 70+ years.

METHODS

For each participant, cognitive status was measured by the errors in the Modified Mini-Mental State Examination (3MS) score. Three frailty measures were used: a Frailty Index based on the Comprehensive Geriatric Assessment (FI-CGA) evaluated from 47 potential deficits, a Clinical Frailty Score and the Fried frailty phenotype. Multivariate Poisson regression and multivariate logistic regression were used to examine the association between baseline cognitive errors and frailty and death, respectively, while controlling for possible confounders (age, sex, education, and baseline cognitive status).

RESULTS

Changes in cognitive status were strongly associated with baseline cognition and frailty, however defined. In multivariate models adjusted for age, sex and education, each frailty measure was associated with cognitive decline and with mortality. The frailest people (from the highest FI-CGA tertile) rarely showed cognitive improvement or stabilization (1.5%, 95% CI=0.002%-2.8%) compared with non-frail people (from the lowest tertile of the FI-CGA), of whom 27.8% (95% CI=24.5%-31.1%) did not deteriorate.

CONCLUSIONS

Frail elderly people have an increased risk of cognitive decline. All frailty measures allowed quantification of individual vulnerability and predict both cognitive changes and mortality.

A multi-state model for the analysis of changes in cognitive scores over a fixed time interval

In this article, we present the novel approach of using a multi-state model to describe longitudinal changes in cognitive test scores. Scores are modelled according to a truncated Poisson distribution, conditional on survival to a fixed endpoint, with the Poisson mean dependent upon the baseline score and covariates. The model provides a unified treatment of the distribution of cognitive scores, taking into account baseline scores and survival. It offers a simple framework for the simultaneous estimation of the effect of covariates modulating these distributions, over different baseline scores. A distinguishing feature is that this approach permits estimation of the probabilities of transitions in different directions: improvements, declines and death. The basic model is characterised by four parameters, two of which represent cognitive transitions in survivors, both for individuals with no cognitive errors at baseline and for those with non-zero errors, within the range of test scores. The two other parameters represent corresponding likelihoods of death. The model is applied to an analysis of data from the Canadian Study of Health and Aging (1991-2001) to identify the risk of death, and of changes in cognitive function as assessed by errors in the Modified Mini-Mental State Examination. The model performance is compared with more conventional approaches, such as multivariate linear and polytomous regressions. This model can also be readily applied to a wide variety of other cognitive test scores and phenomena which change with age.

Transitions in frailty status in older adults in relation to mobility: a multistate modeling approach employing a deficit count

OBJECTIVES

To investigate how changes in frailty status and mortality risk relate to baseline frailty state, mobility performance, age, and sex.

DESIGN

Cohort study.

SETTING

The Yale Precipitating Events Project, New Haven, Connecticut.

PARTICIPANTS

Seven hundred fifty-four community-dwelling people aged 70 and older at baseline followed up at 18, 36, and 54 months.

MEASUREMENTS

Frailty status, assessed at 18-month intervals, was defined using a frailty index (FI) as the number of deficits in 36 health variables. Mobility was defined as time in seconds on the rapid gait test, in which participants walked back and forth over a 20-foot course as quickly as possible. Multistate transition probabilities were calculated with baseline frailty, mobility, age, and sex estimated using Poisson and logistic regressions in survivors and those who died, respectively.

RESULTS

In multivariable analyses, baseline frailty status and age were significantly associated with changes in frailty status and risk of death, whereas mobility was significantly associated with the frailty but not with mortality. At all values of the FI, participants with better mobility were more likely than those with poor mobility to remain stable or to improve. For example, at 54 months, 20.6% (95% confidence interval (CI)=16-25.2) of participants with poor mobility had the same or fewer deficits, compared with 32.4% (95% CI=27.9-36.9) of those with better mobility.

CONCLUSION

A multistate transition model effectively measured the probability of change in frailty status and risk of death. Mobility, age, and baseline frailty were significant factors in frailty state transitions.

Frailty defined by deficit accumulation and geriatric medicine defined by frailty

As nonreplicative cells age, they commonly accumulate subcellular deficits that can compromise function. As people age, they too experience problems that can accumulate. As deficits (symptoms, signs, illnesses, disabilities) accumulate, people become more susceptible to adverse health outcomes, including worse health and even death. This state of increased risk of adverse health outcomes is indistinguishable from the idea of frailty, so deficit accumulation represents another way to define frailty. Counting deficits not only allows grades of frailty to be discerned but also provides insights into the complex problems of older adults. This process is potentially useful to geriatricians who need to be experts in managing complexity. A key to managing complexity is through instruments such as a comprehensive geriatric assessment, which can serve as the basis for routine clinical estimation of an individual's degree of frailty. Understanding people and their needs as deficits accumulate is an exciting challenge for clinical research on frailty and its management by geriatricians.

Modelling cognitive decline in the Hypertension in the Very Elderly Trial [HYVET] and proposed risk tables for population use

Introduction

Although, on average, cognition declines with age, cognition in older adults is a dynamic process. Hypertension is associated with greater decline in cognition with age, but whether treatment of hypertension affects this is uncertain. Here, we modelled dynamics of cognition in relation to the treatment of hypertension, to see if treatment effects might better be discerned by a model that included baseline measures of cognition and consequent mortality

Methodology/Principal Findings

This is a secondary analysis of the Hypertension in the Very Elderly Trial (HYVET), a double blind, placebo controlled trial of indapamide, with or without perindopril, in people aged 80+ years at enrollment. Cognitive states were defined in relation to errors on the Mini-Mental State Examination, with more errors signifying worse cognition. Change in cognitive state was evaluated using a dynamic model of cognitive transition. In the model, the probabilities of transitions between cognitive states is represented by a Poisson distribution, with the Poisson mean dependent on the baseline cognitive state.

The dynamic model of cognitive transition was good (R² = 0.74) both for those on placebo and (0.86) for those on active treatment. The probability of maintaining cognitive function, based on baseline function, was slightly higher in the actively treated group (e.g., for those with the fewest baseline errors, the chance of staying in that state was 63% for those on treatment, compared with 60% for those on placebo). Outcomes at two and four years could be predicted based on the initial state and treatment.

Conclusions/Significance

A dynamic model of cognition that allows all outcomes (cognitive worsening, stability improvement or death) to be categorized simultaneously detected small but consistent differences between treatment and control groups (in favour of treatment) amongst very elderly people treated for hypertension. The model showed good fit, and suggests that most change in cognition in very elderly people is small, and depends on their baseline state and on treatment. Additional work is needed to understand whether this modelling approach is well suited to the valuation of small effects, especially in the face of mortality differences between treatment groups.

Trial Registration

ClinicalTrials.gov NCT0012281