Construction of risk prediction model of depression in the elderly in China
LIU Shulian
ZHANG Yujing
ZHAO Peiwen
ZHANG Jina
GUO Yaming
Abstract：Objective:To construct a risk prediction model of depression in the elderly using the data of China Health and Retirement Longitudinal Study(CHARLS)in 2020.Methods:The study data were collected from the CHARLS 2020 national survey.A total of 901 elderly people were selected according to inclusion and exclusion criteria.The variables included demographic information,health status,function and working status.The risk prediction model was constructed based on Logistic regression.And the prediction performance of the model was evaluated by accuracy,sensitivity,specificity,area under receiver operating characteristic curve and other indicators.Results:The detection rate of depressive symptoms in 901 elderly patients was 36.51%.Logistic regression analysis showed that outpatient service utilization,whether to nap,whether to use the Internet,life satisfaction,children satisfaction,gender,education level,self-rated health status,sleep duration were the key influencing factors of depression in the elderly(P<0.05).Conclusions:The constructed risk prediction model of depression in the elderly had good predictive performance.The Nomogram of depression risk based on the model results can better screen out the high-risk elderly patients with depression risk,which can be used to guide the gerontological nursing practice.
Keywords：the elderlydepressionrisk prediction modelNomogramsecondary preventioninfluencing factors
Publication Date：2025-02-24
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 591-597 )