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建模衰老率:估计生物年龄是否比实际年龄更能准确预测死亡率?

Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age?

机构信息

Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089-0191, USA.

出版信息

J Gerontol A Biol Sci Med Sci. 2013 Jun;68(6):667-74. doi: 10.1093/gerona/gls233. Epub 2012 Dec 3.

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.

摘要

生物年龄(BA)可用于检查衰老速度的差异。然而,关于计算 BA 的最佳方法尚未达成共识。本研究旨在比较五种 BA 算法的预测能力。该样本包括来自国家健康和营养检查调查 III 的 9389 名 30-75 岁的人。在 18 年的随访中,共记录了 1843 例死亡。根据预测敏感性和与死亡率的关联强度,将每个 BA 算法与实际年龄进行比较。结果发现,Klemera 和 Doubal 方法是死亡率最可靠的预测指标,其表现明显优于实际年龄。此外,当将 Klemera 和 Doubal 方法与实际年龄一起纳入模型时,其具有更强大的预测能力,且实际年龄与死亡率不再显著相关。鉴于 BA 具有突出异质性的潜力,Klemera 和 Doubal 方法算法可能有助于研究有关衰老生物学的许多问题。

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