Biomedical subjects

Arnold B Mitnitski

Publications and source records attributed to Arnold B Mitnitski.

5 recordsLinked to original sources

PubMed2004

The estimation of relative fitness and frailty in community-dwelling older adults using self-report data.

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.

Aged↗

PubMed2003

Techniques for knowledge discovery in existing biomedical databases: estimation of individual aging effects in cognition in relation to dementia.

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.

Aged↗

PubMed2002

The accumulation of deficits with age and possible invariants of aging.

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.

Aged↗

PubMed2002

Frailty, fitness and late-life mortality in relation to chronological and biological age.

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.

Journal Article↗

PubMed2002

The mortality rate as a function of accumulated deficits in a frailty index.

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.

Adolescent↗