Key summary points
To determine the best machine learning (ML) regression model for predicting grip strength in adults above 65 years through physical performance and body composition.
AbstractSection FindingsWalking ability and grip strength are closely related, and the Figure-of-8 walk test is a reasonable indicator of grip strength in older adults.
AbstractSection MessageThis study can be used to develop more accurate predictive models of grip strength in older adults.
Abstract
Purpose
We aimed to determine the best machine learning (ML) regression model for predicting grip strength in adults above 65 years using various independent variables, such as body composition, blood pressure, and physical performance.
Methods
The data comprised 107,290 participants, of whom 33.3% were male and 66.7% were female in Korean National Fitness Award Data from 2009 to 2019. The dependent variable was grip strength, which was calculated as the mean of right and left grip strength values.
Results
The results showed that the CatBoost Regressor had the lowest mean squared error (M \(\pm\) SE:16.659 ± 0.549) and highest R2 value (M \(\pm\) SE:0.719 ± 0.009) among the seven prediction models tested. The importance of independent variables in facilitating model learning was also determined, with the Figure-of-8 walk test being the most significant. These findings suggest that walking ability and grip strength are closely related, and the Figure-of- 8 walk test is a reasonable indicator of grip strength in older adults.
Conclusion
The findings of this study can be used to develop more accurate predictive models of grip strength in older adults.
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Data availability
All data generated during the current study have been included in this published article and its original dataset and coding file are available from the corresponding author (Dae Yun Seo) on reasonable request.
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Acknowledgements
The authors would like to thank the anonymous subjects who agreed to participate in the study. The authors would also like to thank the Korea Sports Promotion Foundation for this study.
Funding
This work was supported by the Dong-A University research fund and the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021R1I1A1A01047419, NRF-2021S1A5A2A01065487).
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Jun-Hyun Bae & Xinxing Li contributed to the data collection, data analysis and writing of the manuscript; Jun-Hyun Bae & Xinxing Li contributed to the data collection, data analysis and writing of the manuscript; Dae Yun Seo & Sangho Lee contributed to the data collection and reviewed the manuscript; Taehun Kim & Hyun-Seok Bang contributed to the data collection and reviewed the manuscript. All authors approved the final draft of the manuscript.
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The authors have no competing interests to declare that are relevant to the content of this article.
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For this type of study, formal consent is not required. The dataset was approved by Research Ethics Committee, Hyupsung University (7002320-202303-HR-001), and all methods were performed in accordance with the relevant guidelines.
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Informed consent was obtained from all individual participants included in the study.
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Bae, JH., Li, X., Kim, T. et al. Prediction models of grip strength in adults above 65 years using Korean National Physical Fitness Award Data from 2009 to 2019. Eur Geriatr Med 14, 1059–1064 (2023). https://doi.org/10.1007/s41999-023-00817-7
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DOI: https://doi.org/10.1007/s41999-023-00817-7