中国独居慢病老年人抑郁风险预测模型的构建  

Construction of a depression risk prediction model for elderly individuals living alone with chronic diseases in China

作　　者：王丽[1,2] 邵妍[1] 王萌 牛巧[1] 王婷婷 WANG Li;SHAO Yan;WANG Meng;NIU Qiao;WANG Tingting(Department of Gastroenterology,First Affiliated Hospital of Xinjiang Medical University,Urumqi 830054,China;School of Nursing,Xinjiang Medical University,Urumqi 830017,China)

机构地区：[1]新疆医科大学第一附属医院胃肠外科,乌鲁木齐830054 [2]新疆医科大学护理学院,乌鲁木齐830017

出　　处：《医学新知》2024年第12期1357-1368,共12页New Medicine

基　　金：新疆维吾尔自治区自然科学基金青年基金(2021D01C328);新疆医科大学教育研究与教学改革项目(YG2024196)。

摘　　要：目的构建独居慢病老年人抑郁发生风险预测模型,为老年人抑郁症的早期防控提供科学依据。方法基于第五轮中国健康与养老追踪调查(CHARLS)项目的数据进行分析,采用抑郁评定量表评估独居慢病老年人抑郁情绪,采用非参数检验和卡方检验进行单因素分析,Lasso回归筛选潜在预测因子,多因素Logistic回归分析独居慢病老年人抑郁的影响因素,构建风险预测列线图模型,采用随机拆分法按7∶3比例分为训练集和验证集,通过受试者工作特征(receiver operating characteristic,ROC)曲线下及其曲线下面积(area under curve,AUC)、H-L拟合优度检验、校准曲线图、临床决策曲线、临床影响曲线对模型进行评价。结果研究纳入522名独居慢病老年人,平均年龄为(69.54±6.56)岁,抑郁患病率为50.38%。多因素Logistic回归分析显示自评健康、生活满意度、疼痛难受、上网是独居慢病老年人抑郁风险的主要影响因素(P<0.05),训练集和验证集中的AUC分别为0.799[95%CI(0.755,0.843)]和0.805[95%CI(0.738,0.873)],训练集和验证集H-L检验无统计学意义(P>0.05),两组拟合优度较好,临床决策曲线与临床影响曲线结果显示风险预测模型具有较好的校准度和净收益。结论独居慢病老年人抑郁的患病率较高,自评健康下降、生活满意度下降、疼痛、不会上网是独居慢病老年人发生抑郁的危险因素,本研究开发的列线图模型为医务人员早期动态筛查独居慢病老年人抑郁提供依据。Objective Constructing a depression risk prediction model for elderly people with chronic diseases living alone,to provide a scientific basis for early prevention and control of depression in the elderly.Methods Empirical analysis was conducted using the fifth round of China Health and Retirement Longitudinal Study(CHARLS)survey project.The Center for Epidemiological Studies Depression Scale(CSE-D)was used to evaluate the depressive mood of elderly people living alone with chronic diseases.Non-parametric tests and chi-square tests were used for univariate analysis,Lasso regression was used to screen potential predictive factors,and multiple Logistic regression was used to analyze the influencing factors of depression in elderly people living alone with chronic diseases.A depression risk prediction nomogram model for elderly people living alone with chronic diseases was constructed.The model was divided into a prediction set and a validation set by 7∶3 random splitting method.Receiver operating charcteristic(ROC)curve and area under cuve(AUC),H-L goodness of fit test,calibration curve graph,clinical decision curve,and clinical impact curve was used to evaluate the model.Results 522 elderly people with chronic diseases living alone were included in the study.The mean age was(69.54±6.56)years old.The prevalence of depression among elderly people with chronic diseases living alone in China was 50.38%.Self-rated health,life satisfaction,pain and discomfort,and internet use were the main influencing factors for depression in elderly people with chronic diseases living alone(P<0.05).The ROC curve and AUC sizes for the training and validation sets were 0.799[95%CI(0.755,0.843)]and 0.805[95%CI(0.738,0.873)],respectively.The H-L tests of training set and validation set were not statistically significant(P>0.05).The goodness of fit is better for both groups,and the result of desicion curve and clinical impact curve showed that the risk prediction model has better calibration and net benefit.Conclusion The prevalence of d

关 键 词：独居 慢性病 抑郁 老年人 风险预测模型 

分 类 号：R749.4[医药卫生—神经病学与精神病学]