Predicting cognitive function based on physical performance: findings from the China Health and Retirement...

Area of Science:

• Gerontology
• Neurology
• Biomedical Engineering

Background:

• Physical performance tests offer a simple method for assessing an individual's risk of cognitive decline.
• Aging populations necessitate reliable tools for predicting and managing cognitive health.
• Early identification of cognitive decline risk is crucial for timely interventions.

Purpose of the Study:

• To evaluate the predictive capability of physical performance tests for cognitive function.
• To develop and validate predictive models for cognitive decline using physical performance data.
• To assess the association between physical performance and cognitive function trajectories over time.

Main Methods:

• Cognitive function (mental intactness, episodic memory, global cognition) assessed biennially.
• Generalized estimating equations (GEE) used to analyze physical performance tests as predictors of cognitive decline.
• Multivariate linear regression models (MLRM) developed for cognitive function prediction, validated with Bland-Altman and bootstrap analyses.

Main Results:

• Improved physical performance, excluding standing balance, correlated with slower cognitive decline and better long-term cognitive function.
• Predictive models incorporated all physical tests for men, but only the five-chair stands test for women.
• Bland-Altman analysis confirmed good agreement between measured and estimated cognition in both sexes; bootstrap analysis demonstrated model stability.

Conclusions:

• Physical performance tests are clinically relevant, accessible markers for cognitive aging.
• Developed predictive models based on physical performance demonstrate stability and accuracy.
• These models can be utilized to predict cognitive function, supporting proactive health management in older adults.