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Background <p>The simplified AnthropoAge (S-AnthropoAge) has emerged as a useful marker for characterizing aging trajectories and estimating mortality risk. Given the importance of physical attributes like muscle strength, sit-to-stand performance, and gait speed in assessing health and predicting outcomes in older adults, this study investigates the correlation between S-AnthropoAge and these physical performance indicators among older Chinese.</p> Methods <p>Data from participants aged 60 + were drawn from the second wave of the China Health and Retirement Longitudinal Study. Muscle strength was evaluated by recording the highest measurement of handgrip strength (HGS) from the dominant hand. Sit-to-stand performance was assessed by timing the completion of five times sit-to-stand tests (FTSST), and gait speed was measured as the average speed over two 2.5-meter walks. S-AnthropoAge was calculated through an online platform that required inputs chronological age (CA), height, weight, waist circumference and ethnicity. Multiple linear regression analysis was performed to examine the association between S-AnthropoAge and various functional performance metrics.</p> Results <p>5,106 participants were included in the analysis. After covariate adjustment, multiple linear regression models demonstrated that S-AnthropoAge exhibited modestly stronger associations than CA for HGS (males: β = −0.346 vs. −0.276, Δβ = − 0.070; females: β = −0.277 vs. −0.237, Δβ = − 0.040) and FTSST time (males: β = 0.270 vs. 0.240, Δβ = 0.030; females: β = 0.251 vs. 0.235, Δβ = 0.016), though absolute differences were small. For gait speed, both age metrics were significantly associated in males (<i>p</i> &lt; 0.001), though CA showed a slightly larger effect size (β = 0.085 vs. 0.070, Δβ = 0.015). Model fit indices further supported S-AnthropoAge’s relevance: adjusted R² values were marginally higher for HGS (males: 0.183 vs. 0.166; females: 0.130 vs. 0.115) and FTSST (females: 0.096 vs. 0.090), while male FTSST models showed equivalent explanatory power (adjusted R² = 0.089 for both). All gait speed models accounted for minimal variance (adjusted R² &lt; 0.01).</p> Conclusion <p>S-AnthropoAge shows modest advantages over CA in correlating with key physical function measures (HGS, FTSST) and may complement CA in assessing functional aging.</p>

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Association between simplified anthropometric age and functional performance metrics in older Chinese adults: A study on muscle strength, sit-to-stand ability, and gait speed

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月24日

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  • Jianlin Pu,
  • Heping Jiang,
  • Jianfei Wu,
  • Yu Liu,
  • Maoya Xu,
  • Yuandong Tang,
  • Youguo Tan,
  • Yilin Wang

摘要

Background

The simplified AnthropoAge (S-AnthropoAge) has emerged as a useful marker for characterizing aging trajectories and estimating mortality risk. Given the importance of physical attributes like muscle strength, sit-to-stand performance, and gait speed in assessing health and predicting outcomes in older adults, this study investigates the correlation between S-AnthropoAge and these physical performance indicators among older Chinese.

Methods

Data from participants aged 60 + were drawn from the second wave of the China Health and Retirement Longitudinal Study. Muscle strength was evaluated by recording the highest measurement of handgrip strength (HGS) from the dominant hand. Sit-to-stand performance was assessed by timing the completion of five times sit-to-stand tests (FTSST), and gait speed was measured as the average speed over two 2.5-meter walks. S-AnthropoAge was calculated through an online platform that required inputs chronological age (CA), height, weight, waist circumference and ethnicity. Multiple linear regression analysis was performed to examine the association between S-AnthropoAge and various functional performance metrics.

Results

5,106 participants were included in the analysis. After covariate adjustment, multiple linear regression models demonstrated that S-AnthropoAge exhibited modestly stronger associations than CA for HGS (males: β = −0.346 vs. −0.276, Δβ = − 0.070; females: β = −0.277 vs. −0.237, Δβ = − 0.040) and FTSST time (males: β = 0.270 vs. 0.240, Δβ = 0.030; females: β = 0.251 vs. 0.235, Δβ = 0.016), though absolute differences were small. For gait speed, both age metrics were significantly associated in males (p < 0.001), though CA showed a slightly larger effect size (β = 0.085 vs. 0.070, Δβ = 0.015). Model fit indices further supported S-AnthropoAge’s relevance: adjusted R² values were marginally higher for HGS (males: 0.183 vs. 0.166; females: 0.130 vs. 0.115) and FTSST (females: 0.096 vs. 0.090), while male FTSST models showed equivalent explanatory power (adjusted R² = 0.089 for both). All gait speed models accounted for minimal variance (adjusted R² < 0.01).

Conclusion

S-AnthropoAge shows modest advantages over CA in correlating with key physical function measures (HGS, FTSST) and may complement CA in assessing functional aging.