Aging is thought to be reliant upon a balance between exposure and resiliency ( 3), and as a result, heterogeneity arises within and between species due to variations in exposure to damaging properties-diverse environments-as well as the bodies’ innate ability to cope. Although aging can be seen in nearly all species, the rate of age-related decline is not universal ( 2). Given the potential of BA to highlight heterogeneity, the Klemera and Doubal method algorithm may be useful for studying a number of questions regarding the biology of aging.ĪGING is often defined as the gradual functional and structural decline of an organism, resulting in an increasing risk of disease, impairment, and mortality over the life span ( 1). Furthermore, when included with chronological age in a model, Klemera and Doubal method had more robust predictive ability and caused chronological age to no longer be significantly associated with mortality. Results found that the Klemera and Doubal method was the most reliable predictor of mortality and performed significantly better than chronological age. Each BA algorithm was compared with chronological age on the basis of predictive sensitivity and strength of association with mortality. During the 18-year follow-up, 1,843 deaths were counted. The sample included 9,389 persons, aged 30–75 years, from National Health and Nutrition Examination Survey III. The aim of this study is to compare the predictive ability of five BA algorithms. Nevertheless, little consensus exists regarding optimal methods for calculating BA. Biological age (BA) is useful for examining differences in aging rates.
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