摘要
目的调研湖南省社区老年人抑郁现状,了解各危险因素对老年人抑郁发病的预测程度,构建风险预测列线图模型并进行模型效能的内部验证。方法以湖南省社区老年人(≥60周岁)为研究对象,运用χ2检验和多因素Logistic回归分析老年人抑郁的危险因素,通过R软件建立相关列线图预测模型,采用C统计量和校准曲线对预测模型进行验证,利用临床决策曲线评价模型的实用性。结果湖南省社区老年人抑郁发生率34.11%。将区域位置、性别、居住地(城乡)、受教育水平、婚姻等与老年期抑郁相关的11项危险因素(P<0.05)纳入老年抑郁风险模型。构建的风险预测列线图模型灵敏度为0.083,特异度为0.709,ROC曲线下面积为0.812(95%CI:0.781-0.843)。结论湖南省社区老年人抑郁症发生率较高,总体上女性发生率高于男性,农村高于城市,应重点关注老年人群(特别是独居老人)的慢性病、躯体功能、听力、视力情况等;构建的老年抑郁风险预测列线图模型可用于老年期抑郁高危人群识别和风险预测,可以临床推广。
Objective:To investigate the current status of depression among the elderly in Hunan province,understand the predictive degree of various risk factors on the incidence of depression in the elderly,build a clinical risk prediction model,and internally validate model's performance.Methods:the study focused on the elderly(≥60 years old)in the Hunan province,usingχ2 testing and multi-factor logistic regression to analyze the risk factors of elderly depression.Use the R software to build the prediction model,and at the same time use the C statistical magnitude and calibration curve to verify it.Use the decision curve to evaluate the practicability.Results:The depression rate among the elderly in the communities in Hunan Province is 34.11%.Regional location,gender,residence(urban and rural),education level,marriage,income,deposit,drinking,chronic disease,disability,hearing,vision,physical function and living alone are the risk factors related to elderly depression(P<0.05).In multiple factors analysis,the constructed risk prediction line diagram model sensitivity is 0.083,the specific degree is 0.709,and the area under the ROC curve is 0.812(95%CI:0.781-0.843).Conclusion:The prevalence of depression symptoms among elderly people in the community in Hunan Province is relatively high.The rate of women is higher than that of men.The rate of rural areas are higher than that of the city.Attentions should be paid to the chronic diseases,physical function,hearing,vision conditions of the elderly(particularly those live alone).The elderly depression risk prediction line diagram models can be used to identify SD high-risk population recognition and predict risk,and can be clinically promoted.
作者
黄薇
邱志军
HUANG Wei;QIU Zhi-jun(Nursing School,Yueyang Vocational Technical College,Yueyang,Hunan 414000;Medical School,Yueyang Vocational Technical College,Yueyang,Hunan 414000)
出处
《岳阳职业技术学院学报》
2024年第1期71-78,共8页
Journal of Yueyang Vocational and Technical College
基金
2022年湖南省教育厅科学研究一般项目“湖南省老年抑郁障碍流行病学调查与风险预测模型构建研究”(22C1374)。
关键词
老年人
抑郁现状
风险预测模型
构建
the elderly
the survey of depression
risk prediction model
construction
