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To explore the mechanistic relationships between aging, frailty and mortality, we developed a computational model in which possible health attributes are represented by the nodes of a complex network, with the connections showing a scale-free distribution. Each node can be either damaged (i.e. a deficit) or undamaged. Damage of connected nodes facilitates local damage and makes local recovery more difficult. Our model demonstrates the known patterns of frailty and mortality without any assumption of programmed aging. It helps us to understand how the observed maximum of the frailty index (FI) might arise. The model facilitates an initial understanding of how local damage caused by random perturbations propagates through a dynamic network of interconnected nodes. Very large model populations (here, 10 million individuals followed continuously) allow us to exploit new analytic tools, including information theory, showing, for example that highly connected nodes are more informative than less connected nodes. This model permits a better understanding of factors that influence the health trajectories of individuals., (Copyright © 2017 Elsevier Inc. All rights reserved.)

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&#95;{max}<1. The value of f&#95;{max} in observational studies appears to be nonuniversal, but f&#95;{max}≈0.7 is often reported. A previously developed network model of individual aging was unable to recover f&#95;{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&#95;{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.

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.

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., (© The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

We set out to describe the relationship between impaired balance, mobility and frailty, and relate these to risk of death. We examined a subsample of 1295 community-dwelling non-demented adults from the second wave of the Canadian Study of Health and Aging (CSHA), a prospective population-based cohort study. Frailty index (FI) scores were constructed from a standardized comprehensive geriatric assessment (FI-CGA). History of mobility impairments and falls were assessed. Timed-up-and-go (TUG) and functional reach (FR) performance were measured. The CSHA clinical frailty scale (CFS) was judged by a physician. Adverse outcomes were determined at CSHA-3, conducted 5 years later. The FI-CGA varied in association with impaired mobility and balance. A history of mobility problems was demonstrable at FI-CGA scores >0.12. This level of frailty also represented the most marked deterioration in performance measures (TUG and FR). FI-CGA scores best predicted mortality (HR 1.04±0.02), proving to be a dominating factor in multivariate regression models that included mobility and balance markers. Only at the upper range of FI-CGA reported (>0.45) did all participants demonstrate mobility impairment. Impaired balance and mobility contribute to frailty, but neither is sufficient to define a participant as frail., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

Objectives: To explore the associations between frailty and reproductive axis hormones (as an important regulatory system) in middle aged and older men., Design: Cross-sectional., Setting: The European Male Aging Study., Participants: Three thousand two hundred nineteen community-dwelling European men aged 40 to 79., Measurements: Interviewer-assisted questionnaires to assess physical activity, health status, and mood were administered. Testosterone (T), luteinizing hormone (LH), follicle-stimulating hormone (FSH), dehydroepiandrosterone sulfate (DHEAS), and sex hormone-binding globulin (SHBG) were measured in a fasting morning blood sample. Frailty was assessed as an index (FI) according to the number (out of 43 possible) of health deficits (symptoms, signs, and functional impairments). Relationships between FI and hormone levels (as outcomes) were explored using regression models., Results: Mean FI was 0.12 ± 0.11 (range 0-0.67) was highest in the oldest group. After adjustment for confounders, higher levels of FI were significantly associated with lower levels of total T, free T, and DHEAS and higher levels of gonadotropins and SHBG; a 1-standard deviation cross-sectional increase in FI was associated with a regression coefficient of -0.30 nmol/L (95% confidence interval (CI)=-0.53 to -0.07) decrease in total T and 0.66 U/L (95% CI=0.48-0.83) increase in LH., Conclusions: The associations between high FI, high gonadotropins, and well-maintained circulating T suggest that these changes are markers of aging-related disruptions of multiple physiological regulation, of which alterations in pituitary-testicular function represent a sensitive marker rather than an underlying pathogenic mechanism for frailty., (© 2011, Copyright the Authors. Journal compilation © 2011, The American Geriatrics Society.)

Background: Social vulnerability is related to the health of elderly people, but its measurement and relationship to frailty are controversial. The aims of the present study were to operationalize social vulnerability according to a deficit accumulation approach, to compare social vulnerability and frailty, and to study social vulnerability in relation to mortality., Methods and Findings: This is a secondary analysis of community-dwelling elderly people in two cohort studies, the Canadian Study of Health and Aging (CSHA, 1996/7-2001/2; N = 3707) and the National Population Health Survey (NPHS, 1994-2002; N = 2648). Social vulnerability index measures that used self-reported items (23 in NPHS, 40 in CSHA) were constructed. Each measure ranges from 0 (no vulnerability) to 1 (maximum vulnerability). The primary outcome measure was mortality over five (CHSA) or eight (NPHS) years. Associations with age, sex, and frailty (as measured by an analogously constructed frailty index) were also studied. All individuals had some degree of social vulnerability. Women had higher social vulnerability than men, and vulnerability increased with age. Frailty and social vulnerability were moderately correlated. Adjusting for age, sex, and frailty, each additional social 'deficit' was associated with an increased odds of mortality (5 years in CSHA, odds ratio = 1.05, 95% confidence interval: 1.02-1.07; 8 years in the NPHS, odds ratio = 1.08, 95% confidence interval: 1.03-1.14). We identified a meaningful survival gradient across quartiles of social vulnerability, and although women had better survival than men, survival for women with high social vulnerability was equivalent to that of men with low vulnerability., Conclusions: Social vulnerability is reproducibly related to individual frailty/fitness, but distinct from it. Greater social vulnerability is associated with mortality in older adults. Further study on the measurement and operationalization of social vulnerability, and of its relationships to other important health outcomes, is warranted.

Background and Aims: Relatively little is known about how region of residence influences frailty of seniors. Frailty indexes can be used to investigate these effects. We constructed and validated a frailty index, to investigate the differences in health status between rural and urban seniors., Methods: We studied rural (n=949) and urban (n=7598) older adults in the Canadian Study of Health and Aging, of whom 22% died over 72 months. The frailty index was generated from 40 self-reported health deficits (symptoms, diseases, disabilities, unfavourable living conditions)., Results: The average value of the frailty index increased exponentially with age in both groups (rural: r=0.94; urban: r=0.97, p<0.01) and was highly correlated with mortality (r=0.96 for rural, r=0.97 for urban, p<0.01). Up to age 80, there were few rural-urban differences in frailty. After age 80, the rural sample showed higher mortality than the urban sample. The hazard ratio for death for each increment in the frailty index was 1.38 (1.14-1.72) in rural participants vs 1.18 (1.11-1.26) in urban participants. Women lived longer than men at any index value., Conclusions: Frailty index analysis readily summarizes health and mortality differences between very old rural and urban dwellers, which reflect differences in deficit accumulation, and in the impact of gender on survival. The frailty index provides efficient dimensionality reduction for studying group differences in the health of older adults.

Background: While on average health declines with age, it also becomes more variable with age. As a consequence of this marked variability, it becomes more important as people age to have a means of summarizing health status, but how precisely to do so remains controversial. We developed one measure of health status, personal biological age, from a frailty index. The index itself is a count of deficits derived, in the first instance, from a clinical database. In our earlier investigations, personal biological age demonstrated a strong relationship with 6-year survival. Here we extend this approach to self-reported data., Methods: This is a secondary analysis of community-dwelling people aged 65 years and older (n = 9008) in the Canadian Study of Health and Aging. The frailty index was calculated from 40 self-reported variables, representing symptoms, attitudes, illnesses, and function. Personal biological age was estimated for each individual as the age corresponding to the mean chronological age for the index value. Individual frailty (and the related construct of fitness) was calculated as the difference between chronological and personal biological age., Results: The frailty index showed, on average, an exponential increase with age at an average rate of 3% per year. Although women, on average, demonstrate more frailty than men of the same chronological age, their survival chances are greater. The frailty index strongly correlated (Pearson r =.992 for women and.955 for men) with survival., Conclusions: A frailty index, based on self-report data, can be used as a tool for capturing heterogeneity in the health status of older adults.

New interest is being expressed in the systematic application of modeling techniques to existing datasets. Under the rubric of Knowledge Discovery in Databases (KDD) large databases are being exploited for commercial and scientific purposes. This article reviews the development and applications of KDD techniques to dementia, using the longitudinal Canadian Study of Health and Aging dataset. KDD has demonstrated usefulness at the group level. For example, as in the course of functional impairment between Alzheimer's disease and no cognitive impairment suggest damage control-protection mechanisms for the former compared with noncompensated random accumulation of deficits for the latter. At the individual level, KDD suggests that more precise diagnosis seems possible as well as individual life expectancy prediction. Biomedical databases appear to hold the potential for novel insights when explored by systematic modeling.

In a representative Canadian population survey (n=66589) the proportion of accumulated deficits in a frailty index showed a linear relationship with mortality in a log-log plot, such that the mortality rate was a power-law function of the frailty index. Represented in this way, the frailty index readily summarizes individual differences in health status. The exponent and amplitude parameters of the power function are gender specific, reflecting that while, on average, women accumulate more deficits than men of the same age, their risk of mortality is lower. The dependence of the mortality rate on the frailty index points to the merit of the index as a simple and accessible tool for estimating individual risks of mortality.

This paper extends a method of apprising health status to a broad range of ages from adolescence to old age. The "frailty index" is based on the accumulation of deficits (symptoms, signs, disease classifications) as analyzed in the National Population Health Survey, a representative Canadian population sample (n = 81,859). The accumulation of deficits has both an age-independent (background) component and an age-dependent (exponential) component, akin to the well-known Gompertz-Makeham model for the risk of mortality. While women accumulate more deficits than men of the same age, on average, their rate of accumulation is lower, so the difference in the level of deficits between men and women decreases with age. Two possible invariants of the process of accumulation of deficits were found: (1) the age at which the average proportion of deficits coincides for men and women is 94 years, which closely matches the species-specific lifespan in humans (95 +/- 2); (2) the value of the frailty index (proportion of deficits), which corresponds to that age (0.18). The similarity between mortality kinetics and the accumulation of deficits (frailty kinetics), and the coincidence of the time parameters in the frailty and mortality models make it possible to express mortality risk in terms of accumulated deficits. This provides a simple and accessible tool that might have potential in a number of biomedical applications.

Background: People age at remarkably different rates, but how to estimate trajectories of senescence is controversial., Methods: In a secondary analysis of a representative cohort of Canadians aged 65 and over (n = 2914) we estimated a frailty index based on the proportion of 20 deficits observed in a structured clinical examination. The construct validity of the index was examined through its relationship to chronological age (CA). The criterion validity was examined in its ability to predict mortality, and in relation to other predictions about aging. From the frailty index, relative (to CA) fitness and frailty were estimated, as was an individual's biological age., Results: The average value of the frailty index increased with age in a log-linear relationship (r = 0.91; p < 0.001). In a Cox regression analysis, biological age was significantly more highly associated with death than chronological age. The average increase in the frailty index (i.e. the average accumulation of deficits) amongst those with no cognitive impairment was 3 per cent per year., Conclusions: The frailty index is a sensitive predictor of survival. As the index includes items not traditionally related to adverse health outcomes, the finding is compatible with a view of frailty as the failure to integrate the complex responses required to maintain function.