Age-Associated Disorders As A Proxy Measure Of Biological Age: Findings From the NLTCS Data

Details Age-Associated Disorders As A Proxy Measure Of Biological Age: Findings From the NLTCS Data Age-Associated Disorders As A Proxy Measure Of Biological Age: Findings From the NLTCS Data

2005-09-25

arxiv.org/abs/q-bio/0509034v1

Biology

Quantitative Biology

Populations and Evolution

14 pages, 3 figures, and 5 tables

Scientific paper

Background: The relative contribution of different aging-associated processes to the age phenotype may differ among individuals, creating variability in aging manifestations among age-peers. Capturing this variability can significantly advance understanding the aging and mortality. An index of age-associated health disorders (deficits), called a "frailty index" (FI), appears to be a promising characteristic of such processes. In this study we address the connections of the FI with age focusing on disabled individuals who might be at excessive risk of frailty. Methods: The National Long Term Care Survey (NLTCS) assessed health and functioning of the U.S. elderly in 1982, 1984, 1989, 1994, and 1999. Detailed information for our sample was assessed from about 26,700 interviews. The individual FI is defined as a proportion of deficits for a given person. We perform cross-sectional empirical analysis of the FI age-patterns. Results: FI in the NLTCS exhibits accelerated (quadratic) increase with age. Deficits might accumulate faster among the elderly who, at younger ages, had a low mean FI ("healthy" group) than a high FI ("disabled" group). Age-patterns for "healthy" and "disabled" groups converge at advanced ages. The rate of deficit accumulation is sex-sensitive. Convergence of the (sex-specific) FI for "healthy" and "disabled" groups in later ages determines biological age limits, associated with given levels of health-maintenance in the society, which correspond to 109.4 years for females and 92.5 years for males. Conclusions: The FI can be employed as a measure of biological age and population heterogeneity for modeling aging processes and mortality in elderly individuals.

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