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Common methods of biological age estimation

Linpei Jia, Weiguang Zhang, Xiangmei Chen

Clinical Interventions in Aging · 2017 · ▲ 185 citations

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.

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Provenance

Source
OpenAlex
DOI
10.2147/cia.s134921
Canonical
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2026-07-25 MST

Cite this

APA
Jia, L., Zhang, W., &amp; Chen, X. (2017). Common methods of biological age estimation. <em>Clinical Interventions in Aging</em>. https://doi.org/10.2147/cia.s134921
Vancouver
Jia L, Zhang W, Chen X. Common methods of biological age estimation. Clinical Interventions in Aging. 2017. doi:10.2147/cia.s134921.
BibTeX
@article{linpei2017Common, title = {Common methods of biological age estimation}, author = {Linpei Jia and Weiguang Zhang and Xiangmei Chen}, journal = {Clinical Interventions in Aging}, year = {2017}, doi = {10.2147/cia.s134921}, }

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