摘要
目的:探讨农村社区人群抑郁症患病影响因素。方法:采用分层多级随机抽样方法,共完成调查7347人,以SCID-I/P为诊断工具,共筛查出抑郁症患者295例,全部符合DSM-IV诊断标准。以同人群中未患抑郁症者7052人为正常对照组。结果:女性患病率(4.6%)高于男性(3.2%);不同年龄组间患病率的比较,以45岁～75岁中老年人群患病率较高。多因素Logistic回归分析结果,抑郁症的患病影响因素有性别为女性(OR=1.334,95%CI:1.040～1.711)、年龄(OR=1.012,1.002～1.022)、受教育程度较低(OR=1.428,1.048～1.946)、职业为农业劳动者(OR=1.490,1.050～2.115)、不稳定婚姻状况(OR=1.628,1.174～2.260)、低收入(OR=1.361,1.066～1.737)、常住人口数(OR=1.132,1.042～1.230)、现患躯体疾病(OR=3.020,2.345～3.888)等。结论:浏阳市农村居民抑郁症患病影响因素主要有性别、年龄、低受教育程度、工作为农业劳动者、不稳定婚姻状况、低收入和现患慢性躯体疾病等。
Objective： To explore the influential factors of depression in rural residents of Liuyang. Methods： A stratified multistage random sampling was conducted and 7347 individuals of ≥ 15 years were interviewed with SCID to assess major depressive episode （MDE） and dysthymic disorder according to DSM-IV criteria. 295 cases with depression and 7052 controls of the same population were investigated. Results： The depression prevalences are higher in females （4.6%） than in males （3.2%）, higher in 45 to 75 years than in other age groups, All of the differences are statistically significant （P〈0.05）. The results of multiple logistic regression analysis showed the influential factors of depression are female （0R=1.334, 95%CI： 1.040-1.711）, age （OR=1.012, 1.002-1.022）, lower education level （0R=1.428, 1.048-1.946）, being agricultural workers （OR=1.490, 1.050-2.115）, in unstable marital status （OR=1.628, 1.174-2.260）, lower income （OR=1.361, 1.066-1.737）, number of family usual resident members （OR=1.132, 1.042-1.230） and suffering with any chronic somatic disease （OR =3.020, 2.345-3.888）. Conclusion： The results suggest that the influential factors of depression are sex, age, lower education level, being an agricultural worker, in unstable marital status （deuterogamy, divorced or widowed）, low income and suffering with any chronic somatic disease.
出处
《中国临床心理学杂志》
CSSCI
CSCD
2009年第5期642-644,638,共4页
Chinese Journal of Clinical Psychology
基金
SPI(Suicide Prevention International)资助课题(AC202)
关键词
抑郁症
流行病学
农村
患病率
影响因素
Depression
Epidemiology
Rural area
Prevalence
Influential factors
