title: Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age?
abstract: Biological age (BA) is useful for examining differences in aging rates. Nevertheless, little consensus exists regarding optimal methods for calculating BA. The aim of this study is to compare the predictive ability of five BA algorithms. The sample included 9,389 persons, aged 30-75 years, from National Health and Nutrition Examination Survey III. During the 18-year follow-up, 1,843 deaths were counted. Each BA algorithm was compared with chronological age on the basis of predictive sensitivity and strength of association with mortality. Results found that the Klemera and Doubal method was the most reliable predictor of mortality and performed significantly better than chronological age. 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. 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.
authors.affiliation: Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089-0191, USA. canon@usc.edu
authors.forename: Morgan E
authors.initials: ME
authors.lastname: Levine
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging; D000465:Algorithms; D015415:Biomarkers; D003430:Cross-Sectional Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008017:Life Expectancy / Q000639:trends; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009026:Mortality / Q000639:trends; D015203:Reproducibility of Results; D012494:Sampling Studies
chemical_list: D015415:Biomarkers