摘要
目的探讨睡眠质量对城市社区围绝经期女性抑郁症状的影响。方法采用便利抽样法,于2019年3月在四川省雅安市、成都市、乐山市、德阳市4个城市的社区中选取2300名围绝经期女性为研究对象。采用一般资料调查表、患者健康问卷(PHQ-9)、匹兹堡睡眠质量指数(PSQI)对其进行调查。本研究共发放问卷2300份,回收有效问卷2300份,有效回收率为100%(2300/2300)。结果围绝经期女性抑郁症状的检出率为12.5%(288/2300)。优势分析结果表明,睡眠质量是抑郁症状最重要的影响因素,其次是生活事件、婚姻状况、慢性病、家庭人均月收入以及文化程度。结论睡眠质量是围绝经期女性抑郁症状最重要的影响因素,应重视围绝经期女性的睡眠质量,以改善围绝经期女性的抑郁水平。
Objective To explore the impact of sleep quality on depression symptoms in perimenopausal women in urban communities.Methods Using the convenient sampling method,a total of 2300 perimenopausal women were selected as the research subjects from communities in four cities of Ya'an,Chengdu,Leshan and Deyang in Sichuan Province in March 2019.General Information Questionnaire,Patients Health Questionnaire-9 Items(PHQ-9)and Pittsburgh Sleep Quality Index(PSQI)were used to investigate the perimenopausal women.A total of 2300 questionnaires were sent out in this study,and 2300 were effectively received,with the effective recovery of 100%(2300/2300).Results The detection rate of depressive symptoms in perimenopausal women was 12.5%(288/2300).The dominance analysis showed that sleep quality was the most important factor affecting depressive symptoms,followed by life events,marital status,chronic illness,per capita monthly household income and education level.Conclusions Sleep quality is the most important factor affecting the depressive symptoms of perimenopausal women.It should be emphasized to improve the level of depression in perimenopausal women.
作者
杨玉琼
廖书娟
罗碧如
Yang Yuqiong;Liao Shujuan;Luo Biru(Nursing Department,West China Second University Hospital,Sichuan University/West China School of Nursing,Sichuan University,Chengdu 610041,China;Nursing Department,West China Second University Hospital,Sichuan University,Chengdu 610041,China;Key Laboratory of Birth Defects and Related Diseases of Women and Children(Sichuan University),Ministry of Education,Chengdu 610041,China)
出处
《中华现代护理杂志》
2023年第14期1893-1898,共6页
Chinese Journal of Modern Nursing
关键词
围绝经期
睡眠质量
抑郁症状
优势分析
Perimenopause
Sleep quality
Depression
Dominance analysis