Identifying subjective life expectancy risk factors in physically active and inactive middle-aged and older adults using machine learning models
Machine learning methods can effectively identify key risk factors influencing subjective life expectancy among middle-aged and older adults, and provide valuable guidance for targeted health management strategies tailored to populations with different levels of physical activity.
Authors
- Jian Yang (ORCID: https://orcid.org/0000-0002-5816-3799)
- Ming Wu (ORCID: https://orcid.org/0000-0002-9998-1608)
- Zhang Bianjiang
- Yuan Zhang (ORCID: https://orcid.org/0000-0003-2726-2855)
- Huan‐Zhong Shi (ORCID: https://orcid.org/0000-0002-1154-7920)
- Zhihui Li (ORCID: https://orcid.org/0009-0006-3035-9438)
Institutions
- Hunan University (CN)
- Zhengzhou University (CN)
- Education Department of Hunan Province (CN)
- East China Normal University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1186/s12889-025-24657-1
- Citations
- 1
- Primary Topic
- Physical Activity and Health
- Type
- article
- Field-Weighted Citation Impact
- 1.16
Funders
- Ministry of Education, India