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Abstract 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.

This paper introduces the concept of vector diagnostics. In contrast to the conventional approach where one diagnosis takes precedence, the authors propose an alternative strategy that addresses the clinical reality of comorbidity and multiple diagnoses for an individual. Based on a Bayesian approach, the probability distribution for the etiologically heterogeneous dementia diagnoses is estimated from the Canadian Study of Health and Aging database. These data were collected between February 1991 and May 1992. This method facilitates the establishment of a probability for more than one diagnosis within a given individual. By analyzing the correspondence between diagnostic groups, it is demonstrated that some clinical diagnoses are not reliably distinguished on the basis of the considered subset of symptoms and signs. As a consequence, the conventional diagnostic categories might require revision. The resulting probabilistic algorithm allows for the mining of existing epidemiologic databases for patterns of signs and symptoms that characterize emerging diagnostic categories which might better account for the heterogeneity of the dementia subtypes and individual variability. [ABSTRACT FROM AUTHOR]

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.