JMIR Publications

ABSTRACT

Background:

The societal burden of cognitive impairments in China has prompted researchers to develop clinical prediction models aimed at making risk assessments that enable preventative interventions. However, it is unclear what types of risk factors best predict future cognitive impairment, if known risk factors make equally accurate predictions across different socioeconomic groups, and if existing prediction models are equally accurate across different subpopulations.

Objective:

This paper aimed to identify which domain of health information best predicts future cognitive impairment among elderly Chinese and to examine if discrepancies exist in predictive ability across different population subsets.

Methods:

Using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we quantified the ability of demographics, instrumental activities of daily living, activities of daily living, cognitive tests, social factors, psychological factors, diet, exercise and sleep, chronic diseases, and three recently published prediction models to predict 3-year risk of cognitive impairment in the general Chinese population and among male, female, rural, urban, educated, and uneducated elderly. Predictive ability was quantified using the Area Under the Curve (AUC) and sensitivity-specificity curves through twenty repeats of ten-fold cross-validation.

Results:

A total of 4047 participants were included in the study, of which 337 developed cognitive impairments 3-years after the baseline data collection. The risk factor groups with the most predictive ability in the general population were demographics (AUC: 0.78, 95% CI: 0.77-0.78), cognitive tests (AUC: 0.72, 95% CI: 0.72-0.73), and instrumental activities of daily living (AUC: 0.71, 95% CI: 0.70-0.71). Demographics, cognitive tests, instrumental activities of daily living, and all three re-created prediction models had significantly higher AUCs when making predictions among women compared to men and among the uneducated compared to the educated.

Conclusions:

This study suggests that demographics, cognitive tests, and instrumental activities of daily living are the most useful risk factors for predicting future cognitive impairment among elderly Chinese. However, the most predictive risk factors and existing models have lower predictive power among male, urban, and educated elderly. More efforts are needed to ensure that equally accurate risk assessments can be conducted across different socioeconomic groups in China.