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中国农村地区老年人抑郁症状发生情况及影响因素研究 被引量:33

Prevalence and Associated Factors of Depressive Symptoms in China's Rural Elderly
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摘要 背景随着我国老龄化进程的加快和健康老龄化理念的不断深化,农村老年人这一庞大群体的心理健康状况备受全社会关注。目的探讨我国农村老年人出现抑郁症状的相关因素,为促进我国农村地区健康老龄化提供依据。方法2020年11月,从北京大学组织的2018年中国健康与养老全国追踪调查(CHARLS)项目中选取60岁及以上的农村户籍老年人为研究对象(n=3068)。采用流行病学调查用抑郁量表(CES-D)简化版得分判定研究对象抑郁症状情况。采用随机森林算法筛选影响抑郁症状的项目并进行排序,并用二元Logistic回归分析探究影响农村地区老年人抑郁症状的因素。结果随机森林算法结果显示:15个指标中重要性排序前6位的变量分别是自评总体健康、午休时长、生活满意度、夜间睡眠时长、受教育程度、婚姻满意度。3068例农村地区老年人CES-D简化版得分为(9.9±6.9)分;无抑郁症状1679例(54.7%),有抑郁症状1389例(45.3%)。二元Logistic回归分析结果显示:性别〔女:OR=1.710,95%CI(1.422,2.057)〕、受教育程度〔初中及以上:OR=0.663,95%CI(0.507,0.866)〕、夜间睡眠时长〔6~8 h:OR=0.506,95%CI(0.425,0.601);>8 h:OR=0.435,95%CI(0.324,0.580)〕、代际情感支持〔较多:OR=1.297,95%CI(1.077,1.562)〕、生活满意度〔不满意:OR=5.179,95%CI(3.814,7.133)〕、婚姻满意度〔不满意:OR=3.181,95%CI(2.264,4.526);无配偶:OR=1.243,95%CI(1.004,1.538)〕、自评总体健康〔一般:OR=1.512,95%CI(1.199,1.915);不好:OR=3.918,95%CI(3.056,5.043)〕、慢性病〔有:OR=1.232,95%CI(1.041,1.457)〕、童年健康状况〔一般:OR=1.349,95%CI(1.107,1.644)〕是农村地区老年人发生抑郁症状的影响因素(P<0.05)。结论依据本研究数据,有近一半的农村老年人存在抑郁症状,情况不容乐观,且性别、受教育程度、夜间睡眠时长、代际情感支持、生活满意度、婚姻满意度、自评总体健康、慢性病、童年健康状况是农村地区老年人发生抑郁症状的影响因素,因此应针对高危人群从不同维度、有重点地进行防控,以推动我国健康老龄化进程。 Background Along with the population aging and deepening understanding of healthy aging,the mental health status of a large group,aged people in China's rural areas,has received considerable attention.Objective To explore the factors associated with depressive symptoms in China's rural elderly,providing evidence for promoting healthy aging in this group.Methods This study was conducted in November 2020.Participants(3068 China's rural elderly people aged 60 and over)were part of individuals who attended the 2018 CHARLS supported by Peking University.The short version of the Center for Epidemiologic Studies Depression Scale-Short Form(CES-D-SF)was used to assess the prevalence of depressive symptoms.The random forest algorithm was used to screen and sort the items associated with depression symptoms.Binary Logistic regression analysis was used to identify associated factors of depressive symptoms.Results The top six of the 15 items associated with depression symptoms ranked in terms of importance were:self-reported health status,nap duration,life satisfaction,night sleep duration,education level,and marital satisfaction.The average score of CES-D-SF for the participants was(9.9±6.9)points.It was found that 1679 cases(54.7%)had depressive symptoms,and 1389(45.3%)did not.Binary Logistic regression analysis indicated that gender〔female:OR=1.710,95%CI(1.422,2.057)〕,education level〔junior high school or above:OR=0.663,95%CI(0.507,0.866)〕,nap duration〔6-8 h:OR=0.506,95%CI(0.425,0.601);>8 h:OR=0.435,95%CI(0.324,0.580)〕,intergenerational emotional supports〔more:OR=1.297,95%CI(1.077,1.562)〕,life satisfaction〔unsatisfied:OR=5.179,95%CI(3.814,7.133)〕,marital satisfaction〔unsatisfied:OR=3.181,95%CI(2.264,4.526);no spouse:OR=1.243,95%CI(1.004,1.538)〕,overall self-rated health〔fair:OR=1.512,95%CI(1.199,1.915);poor:OR=3.918,95%CI(3.056,5.043)〕,chronic diseases〔have:OR=1.232,95%CI(1.041,1.457)〕,childhood health status〔fair:OR=1.349,95%CI(1.107,1.644)〕were associated with depressive symptoms(P<0.05).Conclusion The emotional status of the rural elderly was not optimistic,nearly half of them had depressive symptoms,which may be associated with gender,education level,nep duration,intergenerational emotional support,life satisfaction,marital satisfaction,overall self-rated health,chronic disease prevalence,and childhood health status.To promote the development of healthy aging in China,the prevention and control of depressive symptoms in high-risk individuals in this group shall be multifactorial with priority.
作者 李磊 马孟园 彭红叶 阎早芳 王蜜源 胡梦超 刘佳 赵振海 LI Lei;MA Mengyuan;PENG Hongye;YAN Zaofang;WANG Miyuan;HU Mengchao;LIU Jia;ZHAO Zhenhai(Beijing University of Chinese Medicine,Beijing 100029,China;Dongzhimen Hospital,Beijing University of Chinese Medicine,Beijing 100700,China)
出处 《中国全科医学》 CAS 北大核心 2021年第27期3432-3438,共7页 Chinese General Practice
关键词 抑郁 农村人口 老年人 中国健康与养老全国追踪调查 随机森林 LOGISTIC模型 影响因素分析 Depression Rural population Aged China health and retirement longitudinal survey Random forest Logistic models Root cause analysis
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