目的 了解安徽省市属医院女性职工围绝经期综合征发生情况及其相关因素。方法 采用分层整群抽样方法,抽取宿州市、滁州市和池州市895名40~60岁市属医院女性职工为研究对象,采用改良Kupperman评分量表、匹兹堡睡眠质量指数量表(PSQI)进行问卷调查,调查女性职工围绝经期综合征发生水平及影响因素。结果 895名调查对象,出现围绝经期综合征419人,发生率为46.8%。前3位常见围绝经期症状依次为:疲乏、骨关节肌肉痛、烦躁易怒。多因素logistic回归分析,淮北地区(OR=1.964,95CI:1.335~2.890)、孕次较多(OR=1.517,95CI:1.059~2.175)、月经紊乱(OR=2.443,95CI:1.463~4.082)或已绝经(OR=2.975,95CI:1.929~4.588)、睡眠质量较差(OR=6.589,95CI:4.439~10.081)与医院女性职工围绝经期综合征的发生呈正性相关,每天喝牛奶(OR=0.659,95CI:0.483~0.898)与医院职工围绝经期综合征的发生呈负性相关。结论 调查的40~60岁医院女性职工,围绝经期综合征发生率46.8%,地区、孕次、月经情况、牛奶饮用、睡眠质量是影响围绝经期综合征发生的相关因素。
Abstract
Objective To understand the status and related factors of perimenopausal syndrome among female staffs in municipal hospitals in Anhui Province. Methods A total of 895 female hospital staffs aged 40~60 were selected as research objects from Suzhou,Chuzhou and Chizhou by stratified cluster sampling method. Modified Kupperman Scale and Pittsburgh Sleep Quality Index (PSQI) were used to conduct the survey. Results Among 895 survey objects,419 suffered from perimenopausal syndrome with an incidence of 46.8%. The top three common symptoms were: fatigue,Arthralgia/myalgia,and irritability. Multivariate logistic regression analysis showed that Huaibei area (OR=1.964,95CI:1.335~2.890),more pregnancies (OR=1.517,95CI:1.059~2.175),menstrual disorders (OR=2.443,95CI:1.463~4.082) or amenorrhea (OR=2.975,95CI:1.929~4.588),and poor sleep quality (OR=6.702,95CI:4.44~10.106) were positively associated with the incidence of perimenopausal syndrome among female staffs in municipal hospitals,while drink milk regularly (OR=0.659,95CI:0.483~0.898) were negatively associated with the incidence of perimenopausal syndrome among female staffs in municipal hospitals. Conclusion The incidence of perimenopausal syndrome among female staffs in municipal hospitals aged 40 to 60 years was 46.8%. Area,number of pregnancies,menstrual conditions,milk consumption,and sleep quality were the related factors that affecting perimenopausal syndrome.
关键词
医院职工 /
围绝经期综合征 /
睡眠质量 /
影响因素 /
现况调查
Key words
Hospital staffs /
Perimenopause syndrome /
Sleep quality /
Factor analysis /
Status survey
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