Association between daily activities and cognitive impairment among elderly adults with depression: A nomogram prediction model

Abstract

Objective: We aim to use the Chinese Longitudinal Healthy Longevity Survey (CLHLS) to develop and validate a targeted model for predicting the risk of cognitive impairment in elderly adults with depression. Methods: 3658 and 1569 patients from CLHLS were enrolled in the training and validation cohort, respectively. Cognitive function was tested by the Chinese version of the Mini-Mental State Examination (MMSE). Forward stepwise multivariable logistic regression analysis was performed to identify independent risk factors for cognitive impairment in elderly adults with depression, and a visible nomogram was conducted. The evaluation of nomogram’s performance was measured by the area under curve (AUC), calibration curve and decision curve analysis (DCA). Results: In the final prediction model for cognitive impairment risk, seven essential factors were selected: age, education, frequency of reading newspaper, frequency of watching TV, ability to shop independently, ability to dress independently, and ability to cook. The model performed well, with AUCs of 0.857 and 0.831 in the training and validation cohorts, respectively. Based on the above-mentioned analytical results, a nomogram was created. The calibration curve indicated that the nomogram was well-calibrated. The DCA demonstrated the nomogram's clinical utility. Conclusion: A model for predicting the risk of cognitive impairment in elderly adults with depression was successfully developed.