Dementia Rehabilitation Needs and Risk Prediction in Chinese Middle-Aged and Older Adults: Insights From GBD-WHO and CHARLS.

Authors

Yaqiong Fang, Kejia Cao

Published in

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry. Jul 31, 2026. Epub Jul 31, 2026.

Abstract

Dementia poses a growing public health challenge in China, driving increasing demand for rehabilitation. Quantifying population-level rehabilitation needs and developing individual-level risk stratification tools are essential for targeted policy formulation and efficient resource allocation.
This two-part study integrated population- and individual-level analyses. Using the GBD-WHO Rehabilitation Database (1990-2019), we estimated and forecasted dementia rehabilitation needs among Chinese adults aged 45 years and older. Using the China Health and Retirement Longitudinal Study cohort (n = 10,146), we developed and validated machine learning (ML) models to stratify individual dementia risk and conducted variable importance analysis to identify key predictors.
From 1990 to 2019, the number of prevalent dementia cases requiring rehabilitation in China increased 3.6-fold, reaching 15.19 million; while years lived with disability rose 3.7-fold, reaching 3.33 million. The age-standardized prevalence rate increased from 2,447.48 to 2,942.26 per 100,000 [AAPC: 0.63 (95% CI: 0.61-0.66)], and the age-standardized YLDs rate rose from 538.77 to 654.25 per 100,000 [AAPC: 0.67 (95% CI: 0.64-0.69)]. This upward trajectory is projected to continue through 2030. Among the developed ML models, Distributed Random Forest (DRF; test AUC = 0.728) and the gradient boosting machine (GBM; test AUC = 0.712) demonstrated the best overall predictive performance. Key predictors identified included older age, lower educational attainment, pain, self-rated health expectations, and several blood biomarkers.
Dementia rehabilitation needs in China are both substantial and rapidly increasing. The developed ML stratification model provides a practical tool for population-level risk assessment, highlighting the urgent need to integrate population-level forecasting with individual-level stratification in national dementia rehabilitation strategies.

PMID:
42624699
Bibliographic data and abstract were imported from PubMed on 21 Aug 2026.

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