Biological age models based on a healthy Han Chinese population

Li, Zhe; Zhang, Weiguang; Duan, Yuting; Niu, Yue; He, Yan; Chen, Yizhi; Liu, Xiaomin; Dong, Zheyi; Zheng, Ying; Chen, Xizhao; Feng, Zhe; Wang, Yong; Zhao, Delong; Sun, Xuefeng; Cai, Guangyan; Jiang, Hongwei; Chen, Xiangmei

doi:10.1016/j.archger.2022.104905

Cited by 9 publications

(7 citation statements)

References 25 publications

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“…In contrast, Δage is superior, which response to the acceleration of biological age. The validity of the model was recently confirmed by Li and Zhang et al who trained the BA model using a healthy Beijing population and later validated the acceleration of aging by disease in a diseased population ( 77 ). However, the value of ∆age may only serve a qualitative purpose, as relative acceleration or retardation of aging compared to a healthy population with the same CA.…”

Section: Biological Age Assessment Methodsmentioning

confidence: 80%

Progress in biological age research

Zhang

Duan

et al. 2023

Front. Public Health

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Biological age (BA) is a common model to evaluate the function of aging individuals as it may provide a more accurate measure of the extent of human aging than chronological age (CA). Biological age is influenced by the used biomarkers and standards in selected aging biomarkers and the statistical method to construct BA. Traditional used BA estimation approaches include multiple linear regression (MLR), principal component analysis (PCA), Klemera and Doubal’s method (KDM), and, in recent years, deep learning methods. This review summarizes the markers for each organ/system used to construct biological age and published literature using methods in BA research. Future research needs to explore the new aging markers and the standard in select markers and new methods in building BA models.

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Section: Biological Age Assessment Methodsmentioning

confidence: 80%

Progress in biological age research

Zhang

Duan

et al. 2023

Front. Public Health

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“…Zhang et al ( 10 , 17 ) constructed a biological age equation using several aging markers. Li et al ( 16 ) used nine markers and eight methods to assess BA in the Chinese Han population.…”

Section: Functional Perspectivementioning

confidence: 99%

“…We combine previous research from our center (10,(13)(14)(15)(16)(17) and categorize the criteria into three levels based on their importance. Level 1, the following criteria must be met: ① aging markers should reflect the fundamental biological process of aging; ② aging markers can predict the occurrence of adverse events; and ③ aging markers should be noninvasive or minimally invasive and be repeatable.…”

Section: Summary and Prospectsmentioning

confidence: 99%

“…There are similarities and differences in the screening criteria proposed by previous studies (10)(11)(12). In this review, we combine previous research from our center (10,(13)(14)(15)(16)(17), summarize and discuss the current views on screening criteria for aging markers, related problems of existing criteria, and solutions, and compare their use. Finally, an assessment framework has been established, and the criteria are categorized into three levels based on their importance.…”

Section: Introductionmentioning

confidence: 99%

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Progress in the study of aging marker criteria in human populations

He,

Li,

Niu

et al. 2024

Front. Public Health

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The use of human aging markers, which are physiological, biochemical and molecular indicators of structural or functional degeneration associated with aging, is the fundamental basis of individualized aging assessments. Identifying methods for selecting markers has become a primary and vital aspect of aging research. However, there is no clear consensus or uniform principle on the criteria for screening aging markers. Therefore, we combine previous research from our center and summarize the criteria for screening aging markers in previous population studies, which are discussed in three aspects: functional perspective, operational implementation perspective and methodological perspective. Finally, an evaluation framework has been established, and the criteria are categorized into three levels based on their importance, which can help assess the extent to which a candidate biomarker may be feasible, valid, and useful for a specific use context.

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“…The physical tness level is considered an important indicator of the health of the general public [11][12][13][14], and in particular, the physical tness of the elderly people is an important criterion for determining the possibility of independent living [15,16]. Physical tness includes factors related to health conditions such as musculoskeletal and cardiorespiratory tness [14,17]. Typical physical tness tests include muscle strength (hand grip strength tests) [11,12,18], muscular endurance (30-s chair stand test and situps test) [11,18,19], exibility (chair sit-and-reach test) [18,20], balance (time up-and-go) [12], and cardiopulmonary endurance (graded exercise test and 2-minute step test) [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

A Study on the Development of a Fitness Age Prediction Model: The National Fitness Award Cohort Study 2017-2021

Yoon,

Lee,

Kim

2024

Preprint

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Background Physical fitness is considered an important indicator of the health of the general public, and in particular, the physical fitness of the elderly people is an important criterion for determining the possibility of independent living. Therefore, the purpose of this study was to examine the association between chronological age and physical fitness variables in the National Fitness Award Cohort study data and to develop multiple linear regression analyses to predict fitness age using dependent variables. Methods Data from 501,774 (359,303 adults, 142,471 elderly) individuals who participated in the Korea National Fitness Award Cohort Study from 2017 to 2021 were collected. The physical fitness tests consisted of 5 candidate markers for adults and 6 candidate markers for the elderly adults to measure muscle strength, muscle endurance, cardiopulmonary endurance, flexibility, balance, and agility. Pearson’s correlation and stepwise regression analyses were used to analyze the data. Results We obtained a predicted individual fitness age values from physical fitness indicators for adults and elderly individuals, and the mean explanatory power of the fitness age for adults was [100.882 – (.029 × VO2max) – (1.171 × Relative HGS) – (.032 × Sit-up) + (.769 × Gender Male = 1; Female = 2) + (.769 × Gender = 2)] was 93.6% (adjusted R2); additionally, the fitness age for elderly individuals was [79.807 – (.017 × 2-minute step test) – (.203 × 30-second chair stand) – (.031 × 30-second chair stand) – (.052 × TUG) + (.985 × TUG) – (3.468 × Gender Male = 1; Female = 2)] was 24.3% (adjusted R2). Conclusions We suggest the use of fitness age as a valid indicator of fitness in adults and the elderly individuals as well as a useful motivational tool for undertaking exercise prescription programs along with exercise recommendations at the national level.

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Biological age models based on a healthy Han Chinese population

Cited by 9 publications

References 25 publications

Progress in biological age research

Progress in biological age research

Progress in the study of aging marker criteria in human populations

A Study on the Development of a Fitness Age Prediction Model: The National Fitness Award Cohort Study 2017-2021

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