Literature DB >> 17889950

Development of models for predicting biological age (BA) with physical, biochemical, and hormonal parameters.

Chul-Young Bae1, Young Gon Kang, Sehyun Kim, Chooyon Cho, Hee Cheol Kang, Byung Yeon Yu, Sang-Wha Lee, Kyung Hee Cho, Duk Chul Lee, Kyurae Lee, Jong Sung Kim, Kyung Kyun Shin.   

Abstract

Individual differences are the hallmark of aging. Chronological age (CHA) is known that fails to provide an accurate indicator of the aging but biological age (BA) estimates the functional status of an individual in reference to his or her chronological peers on the basis of how well he or she functions in comparison with others of the same CHA. Therefore, we developed models for predicting BA that can be applicable in clinical practice settings. This was a community-based cross-sectional study. Subjects were recruited from the health promotion center in Korea from 2001 to 2005. Among these, data obtained from the 3575 participants (1302 men and 2273 women) was used for clinical evaluation and statistical analysis. For our test battery we selected 25 parameters among the routine tests. For males, the best models were developed using 15, 7, 5, and 4 of the 25 chosen parameters for total, physical, biochemical and hormonal characteristics, respectively (R(2)=0.62, 0.38, 0.33, and 0.36, respectively). Similar to males, for the females, 14, 6, 8, and 3 parameters were developed as the models (R(2)=0.66, 0.40, 0.42, and 0.37, respectively). Our BA prediction models may be used as supplementary tools adding knowledge in the evaluation of aging status.

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Year:  2007        PMID: 17889950     DOI: 10.1016/j.archger.2007.08.009

Source DB:  PubMed          Journal:  Arch Gerontol Geriatr        ISSN: 0167-4943            Impact factor:   3.250


  18 in total

1.  Select aging biomarkers based on telomere length and chronological age to build a biological age equation.

Authors:  Wei-Guang Zhang; Shu-Ying Zhu; Xiao-Juan Bai; De-Long Zhao; Shi-Min Jian; Juan Li; Zuo-Xiang Li; Bo Fu; Guang-Yan Cai; Xue-Feng Sun; Xiang-Mei Chen
Journal:  Age (Dordr)       Date:  2014-06

2.  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

3.  Sex-related differences in behavioural markers in adult mice for the prediction of lifespan.

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Journal:  Biogerontology       Date:  2020-10-16       Impact factor: 4.277

4.  Construction of an integral formula of biological age for a healthy Chinese population using principle component analysis.

Authors:  W-G Zhang; X-J Bai; X-F Sun; G-Y Cai; X-Y Bai; S-Y Zhu; M Zhang; X-M Chen
Journal:  J Nutr Health Aging       Date:  2014       Impact factor: 4.075

5.  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

6.  A model for estimating body shape biological age based on clinical parameters associated with body composition.

Authors:  Chul-Young Bae; Young Gon Kang; Young-Sung Suh; Jee Hye Han; Sung-Soo Kim; Kyung Won Shim
Journal:  Clin Interv Aging       Date:  2012-12-28       Impact factor: 4.458

7.  A Model for Estimating Biological Age From Physiological Biomarkers of Healthy Aging: Cross-sectional Study.

Authors:  Karina Louise Skov Husted; Andreas Brink-Kjær; Mathilde Fogelstrøm; Pernille Hulst; Akita Bleibach; Kaj-Åge Henneberg; Helge Bjarup Dissing Sørensen; Flemming Dela; Jens Christian Brings Jacobsen; Jørn Wulff Helge
Journal:  JMIR Aging       Date:  2022-05-10

8.  Immune function parameters as markers of biological age and predictors of longevity.

Authors:  Irene Martínez de Toda; Ianire Maté; Carmen Vida; Julia Cruces; Mónica De la Fuente
Journal:  Aging (Albany NY)       Date:  2016-11-28       Impact factor: 5.682

9.  Models for estimating the metabolic syndrome biological age as the new index for evaluation and management of metabolic syndrome.

Authors:  Young Gon Kang; Eunkyung Suh; Hyejin Chun; Sun-Hyun Kim; Deog Ki Kim; Chul-Young Bae
Journal:  Clin Interv Aging       Date:  2017-02-01       Impact factor: 4.458

10.  Aging-Related Correlation between Serum Sirtuin 1 Activities and Basal Metabolic Rate in Women, but not in Men.

Authors:  Hee Jae Lee; Soo Jin Yang
Journal:  Clin Nutr Res       Date:  2017-01-17
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