Investigating the Factors of Active Health among Chinese Elderly: Based on CHARLS

Corresponding author: zhangcan, zhangcanyyy@163.com

DOI: 10.12201/bmr.202604.00046

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  Abstract: Abstract Purpose/Significance: This study aims to investigate the key influencing factors of active health behaviors among older adults in China, and provide reference for better promoting active health in the elderly and addressing the challenges of rapid population aging. Methods/Process: Using the Harmonized CHARLS dataset from the China Health and Retirement Longitudinal Study (CHARLS), this study combines the strengths of machine learning models and traditional regression models to construct a mixed analysis framework of feature selection - model validation - effect quantification and accurately analyze the active health influence mechanism of the elderly. Results/Conclusion: The findings indicate that internet usage is the primary influencing factor for active health among older adults. Self-rated health status, Activities of Daily Living (ADL), and Instrumental Activities of Daily Living (IADL) also play critical roles. Factors like Gender and household registration (hukou) are significant influencing factors as well. The application of the hybrid analytical approach represents a productive step toward identifying important determinants of active health among older adults in China. These results provide evidence-based recommendations for policies and practices aimed at promoting active health in the elderly.

  Key words: Active Health Aging CHARLS Machine Learning

  Submit time: 7 April 2026

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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