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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.

Research indicates that the rate of decline in functional impairment in people suffering from Alzheimer's disease is different from the normal aging process. Studies show the rate of functional decline accelerates with severity of the disease, while the decline rate distribution in aging without cognitive impairment is different from that in dementia. A log-normal distribution was exhibited by aged patients with any type of dementia.

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.

Examines the use of performance of equilibrium-point hypothesis model for motor control. Presentation of the model based on a logical system with an empirical data; Evaluation on the explanatory and predictive capacity of the model; Relationship between posture and movement.

In Plamondon & Alimi's target article, a hell-shaped velocity profile typically observed in fast movements is used as a basis for the 'kinematic theory' of motor control. In our opinion, kinematics is a necessary but insufficient ground for a theory of motor control. Relationships between different kinematic characteristics are an emergent property of the system dynamics controlled by the brain in a specific way. In particular, bell-shaped velocity profiles with or without additional waves are a trivial consequence of shifts in the equilibrium state of the system as suggested, for example, in the [Lambda]-model of motor control.

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. [ABSTRACT FROM PUBLISHER]

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]