Literature DB >> 11708217

On the use of regression analysis for the estimation of human biological age.

J Krøll1, O Saxtrup.   

Abstract

The present investigation compares three linear regression procedures for the definition of human biological age (bioage). As a model system for bioage definition is used the variations with age of blood hemoglobin (B-hemoglobin) in males in the age range 50-95 years. The bioage measures compared are: 1: P-bioage; defined from regression of chronological age on B-hemoglobin results. 2: AC-bioage; obtained by indirect regression, using in reverse the equation describing the regression of B-hemoglobin on age in a reference population. 3: BC-bioage; defined by orthogonal regression on the reference regression line of B-hemoglobin on age. It is demonstrated that the P-bioage measure gives an overestimation of the bioage in the younger and an underestimation in the older individuals. This 'regression to the mean' is avoided using the indirect regression procedures. Here the relatively low SD of the BC-bioage measure results from the inclusion of individual chronological age in the orthogonal regression procedure. Observations on male blood donors illustrates the variation of the AC- and BC-bioage measures in the individual.

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Year:  2000        PMID: 11708217     DOI: 10.1023/a:1026594602252

Source DB:  PubMed          Journal:  Biogerontology        ISSN: 1389-5729            Impact factor:   4.277


  6 in total

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

Authors:  Morgan E Levine
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-12-03       Impact factor: 6.053

2.  Evidence of accelerated aging among African Americans and its implications for mortality.

Authors:  M E Levine; E M Crimmins
Journal:  Soc Sci Med       Date:  2014-07-15       Impact factor: 4.634

Review 3.  Deep learning for biological age estimation.

Authors:  Syed Ashiqur Rahman; Peter Giacobbi; Lee Pyles; Charles Mullett; Gianfranco Doretto; Donald A Adjeroh
Journal:  Brief Bioinform       Date:  2021-03-22       Impact factor: 11.622

Review 4.  Common methods of biological age estimation.

Authors:  Linpei Jia; Weiguang Zhang; Xiangmei Chen
Journal:  Clin Interv Aging       Date:  2017-05-11       Impact factor: 4.458

5.  Biological age for chronic kidney disease patients using index model.

Authors:  Shaiful Anuar Abu Bakar; Sharifah Nazatul Shima Syed Mohamed Shahruddin; Noriszura Ismail; Wan Ahmad Hafiz Wan Md Adnan
Journal:  PeerJ       Date:  2022-08-01       Impact factor: 3.061

6.  Deep Learning using Convolutional LSTM estimates Biological Age from Physical Activity.

Authors:  Syed Ashiqur Rahman; Donald A Adjeroh
Journal:  Sci Rep       Date:  2019-08-06       Impact factor: 4.379

  6 in total

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