Development and Validation of a Depression Risk Prediction Model for Home-Dwelling Middle-Aged and Older Adults in China Based on CHARLS Data

Summary

This study developed and validated a depression risk prediction model for home-dwelling middle-aged and older adults using CHARLS data. This model incorporates five key predictive factors. The nomogram demonstrated acceptable discrimination (0.766/0.664), which is suitable for risk stratification at the population level and is an effective screening tool.

Abstract

There is a lack of research on risk prediction models for depressive symptoms among home-dwelling middle-aged and elderly adults in China. This study aimed to develop a risk prediction model and identify the risk factors for depression among home-dwelling middle-aged and elderly adults in China, with the goal of informing evidence-based prevention strategies and public health policy. Using the latest nationally representative CHARLS 2020 wave (n = 14,466), we developed the first parsimonious nomogram to predict depressive symptoms (CES-D-10 ≥ 10) in home-living middle-aged and older Chinese. After chi-square and multivariable logistic screens, LASSO with 10-fold cross-validation identified the five most influential predictors. Model discrimination (AUC), calibration (Hosmer-Lemeshow, calibration plot), and clinical utility (decision-curve analysis) were assessed in training–test splits (7:3). Among the 14,466 home-dwelling middle-aged and elderly adults, 5,488 (37.1%) had depressive symptoms, and 8,978 (62.9%) did not meet the criteria for depressive symptoms. The final nomogram comprised five variables: female sex, rural hukou, primary or less education, unmarried status, and age over 60. The tool achieved AUCs of 0.766 (95% CI 0.752-0.780) in the training set and 0.664 (0.637-0.691) in the test set, with excellent calibration (P = 0.28) and positive net benefit between 30% and 50% risk thresholds. This model can predict the risk of depression in Chinese home-dwelling middle-aged and elderly adults and can serve as a convenient screening tool for early identification and risk management of depression in this population.

Introduction

Depression, as a mental disorder characterized by high prevalence¹, low treatment acceptance rates, and high recurrence rates, has become a major threat to the physical and mental health of middle-aged and elderly individuals². Globally, it is estimated that 5% of adults suffer from depression, while among elderly adults this figure is approximately 30%^3,4. In China, a recent study revealed that an estimated 50.6 million people are affected by depressive disorders, accounting for 17.8% of the global burden⁵. Zhu et al. reported that the in....

Protocol

The research was approved by the Biomedical Ethics Committee of Peking University (IRB00001052-11015). All subjects provided informed consent.

Study population
The data for this study were obtained from CHARLS 2020, which covers 150 county-level units and 450 village-level units across the country, encompassing approximately 10,000 households and 19,395 middle-aged and elderly individuals aged 45 and above²¹. The survey employed a multi-stage probability sampling approach. Individuals were included if they met the following criteria: age of 45 years or older; selected home-dwelling in response to....

Results

Sample characteristics
The study comprised 14,466 participants with the following characteristics: 46.8% were aged 60-74 years, 52.2% were female, and 75.2% held agricultural household registration status. In terms of educational level, 62.9% had a primary school education or lower. Regarding mental health status, 37.1% of participants exhibited depressive symptoms, while the remaining 62.9% showed no depressive symptoms. Detailed information was presented in Table 1.

Discussion

This study yielded several key findings regarding the risk factors and prediction of depressive symptoms among home-dwelling middle-aged and elderly adults in China. First, the study found that 37.1% of home-dwelling middle-aged and elderly adults exhibited depressive symptoms in China, indicating a high burden of depressive symptoms in this population. The results of this study were inconsistent with the findings of a global meta-analysis on the prevalence of depressive symptoms in older adults, which reported a figure .......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
(pROC)(shapviz)(patchwork)(xgboost)(ggplot2)(rms)(rmda)(caret)(randomForest)(glmnet)(dplyr)(ggrepel)(readr)	CRAN	N/A	R package for risk prediction model decision curve analysis
CHARLS dataset	CHARLS team	N/A	China Health and Retirement Longitudinal Study dataset, used for model development and validation
R	R Foundation for Statistical Computing	4.3.2	Statistical software used for data analysis and modeling.
SPSS Statistics	IBM	21	Software used for supplementary statistical analysis.