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Common methods of biological age estimation

Authors Jia L, Zhang W, Chen X

Received 16 February 2017

Accepted for publication 18 April 2017

Published 11 May 2017 Volume 2017:12 Pages 759—772


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Zhi-Ying Wu

Linpei Jia,1–3 Weiguang Zhang,2,3 Xiangmei Chen1–3

1Department of Nephrology, Second Hospital of Jilin University, Changchun, Jilin Province, 2Department of Nephrology, Chinese People’s Liberation Army General Hospital, Beijing, 3State Key Laboratory of Kidney Disease, Chinese People’s Liberation Army General Hospital, Beijing, People’s Republic of China

Abstract: At present, no single indicator could be used as a golden index to estimate aging process. The biological age (BA), which combines several important biomarkers with mathematical modeling, has been proposed for >50 years as an aging estimation method to replace chronological age (CA). The common methods used for BA estimation include the multiple linear regression (MLR), the principal component analysis (PCA), the Hochschild’s method, and the Klemera and Doubal’s method (KDM). The fundamental differences in these four methods are the roles of CA and the selection criteria of aging biomarkers. In MLR and PCA, CA is treated as the selection criterion and an independent index. The Hochschild’s method and KDM share a similar concept, making CA an independent variable. Previous studies have either simply constructed the BA model by one or compared the four methods together. However, reviews have yet to illustrate and compare the four methods systematically. Since the BA model is a potential estimation of aging for clinical use, such as predicting onset and prognosis of diseases, improving the elderly’s living qualities, and realizing successful aging, here we summarize previous BA studies, illustrate the basic statistical steps, and thoroughly discuss the comparisons among the four common BA estimation methods.

Keywords: chronological age, statistical method, aging biomarker, statistical model

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