Modeling the Rate of Senescence: Can Estimated Biological Age Predict Mortality More Accurately Than Chronological Age?

被引:590
作者
Levine, Morgan E. [1 ]
机构
[1] Univ So Calif, Davis Sch Gerontol, Los Angeles, CA 90089 USA
来源
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES | 2013年 / 68卷 / 06期
关键词
Biological age; Biomarkers; Mortality; REGRESSION-ANALYSIS; BIOMARKERS; POPULATION; PARAMETERS; MECHANISMS; STRESS; HUMANS; INDEX;
D O I
10.1093/gerona/gls233
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
030301 [社会学]; 100201 [内科学];
摘要
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 3075 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.
引用
收藏
页码:667 / 674
页数:8
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