Determinants and risk prediction models for frailty among community-living older adults in eastern China
Older adults living in communities in eastern China showed slight frailty, and many factors influenced their frailty scores. Random forest and XGBoost models outperform decision tree models in predicting frailty in older adults, so identifying high-risk individuals early and developing personalized interventions can help slow the development of frailty and improve quality of life in older adults.
Authors
- Yan He (ORCID: https://orcid.org/0000-0002-4316-8298)
- Xinyi Cao (ORCID: https://orcid.org/0000-0002-3476-9833)
- Lin Qi (ORCID: https://orcid.org/0000-0003-3433-3252)
- Mengmeng Yang (ORCID: https://orcid.org/0000-0003-4770-0648)
- Jianyu Liu (ORCID: https://orcid.org/0000-0002-8150-5312)
- Xinle Wang (ORCID: https://orcid.org/0000-0002-4296-6060)
- Xiwei Song (ORCID: https://orcid.org/0009-0002-3820-7966)
Institutions
- Zhengzhou University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-03-11
- DOI
- https://doi.org/10.3389/fpubh.2025.1518472
- Citations
- 3
- Primary Topic
- Frailty in Older Adults
- Type
- article
- Field-Weighted Citation Impact
- 3.67