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脑卒中筛查目标人群低睡眠质量现况及其影响因素分析 被引量:11

Prevalence and Influence Factors of Poor Sleep Quality in the Target Population of Stroke Screening
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摘要 背景研究显示睡眠质量与脑血管病关系密切。脑卒中筛查目标人群是指具有脑血管病危险因素的人群,但针对该人群睡眠质量问题的研究较少。目的调查脑卒中筛查目标人群低睡眠质量现况,并分析其影响因素。方法本研究以2016年12月—2017年6月参与河北省石家庄市裕华区社区脑卒中筛查的居民作为脑卒中筛查目标人群,采用《2016年度心脑血管病影响因素社区、乡镇人群追访干预调查表》和《匹兹堡睡眠质量指数量表(PSQI)》进行测试,并在受试者知情同意的基础上收集其基本测量指标(如身高、体质量、颈围、腰围、收缩压、舒张压),以PSQI总分>7分作为低睡眠质量,PSQI总分≤7分作为正常睡眠质量进行分析。调研过程中,调查人员为脑卒中筛查目标人群进行问卷讲解,由脑卒中筛查目标人群口述作答,调查人员填写调查问卷。由调查人员依据“8+2”项脑卒中影响因素及判定标准对脑卒中筛查目标人群进行脑卒中发生风险评级,采用多因素Logistic回归分析探究脑卒中筛查目标人群出现低睡眠质量的影响因素。结果共发放调查问卷4761份,回收有效问卷4716份,有效回收率为99.05%。共373例受试者存在低睡眠质量问题,发生率为7.91%。多因素Logistic回归分析结果显示,年龄〔OR=1.030,95%CI(1.018,1.043)〕、性别〔OR=1.478,95%CI(1.116,1.957)〕、婚姻状况〔OR=1.044,95%CI(1.005,1.085)〕、退休情况〔OR=2.402,95%CI(1.758,3.281)〕、饮酒情况〔OR=1.395,95%CI(1.157,1.681)〕、饮食情况〔OR=1.411,95%CI(1.221,1.630)〕、脑卒中发生风险评级〔OR=1.484,95%CI(1.176,1.873)〕是脑卒中筛查目标人群出现低睡眠质量的影响因素(P<0.05)。结论脑卒中筛查目标人群低睡眠质量问题不可忽视,年龄、性别、婚姻状况、退休情况、饮酒情况、饮食情况、脑卒中发生风险评级是该人群出现低睡眠质量的影响因素。 Background Studies showed that sleep quality is closely related to cerebrovascular disease.The target population of stroke screening is the population with influence factors of cerebrovascular disease,but their sleep quality has been seldom studied.Objective To investigate the prevalence and influence factors of poor sleep quality in the target population for stroke screening.Methods In this study,residents who participated in stroke screening in Yuhua District,Shijiazhuang City,Hebei Province from December 2016 to June 2017 were selected as the target population for a survey after obtaining their informed consent.During the survey,a self-developed questionnaire named 2016 Follow-up Intervention Targeting Cardio-cerebrovascular Influence factors in Community and Township Population was used to collect parameters such as height,weight,neck circumference,waist circumference,systolic blood pressure and diastolic blood pressure,and so on,and the Pittsburgh Sleep Quality Index(PSQI) was used to evaluate the sleep quality(PSQI>7 and PSQI ≤ 7 were defined as poor and normal sleep quality,respectively).The questionnaires were filled by the investigators according to participants’ verbal answers in response to the questionnaire questions(with oral explanation when necessary) asked by the investigators.Stroke risks were stratified in accordance with the diagnostic criteria of the "8+2" Stroke Risk Screening Program.Multivariate Logistic regression analysis was used to explore the influence factors of poor sleep quality.Results Among the participants,4 716(99.05%) completed the survey effectively,and 7.91%(373/4 716) were found with poor sleep quality.Multivariate Logistic regression analysis showed that age 〔OR=1.030,95%CI(1.018,1.043)〕,female 〔OR=1.478,95%CI(1.116,1.957)〕,marital status 〔OR=1.044,95%CI(1.005,1.085)〕,retired 〔OR=2.402,95%CI(1.758,3.281)〕,high alcohol consumption 〔OR=1.395,95%CI(1.157,1.681)〕,unhealthy diet 〔OR=1.411,95%CI(1.221,1.630)〕and stroke risks 〔OR=1.484,95%CI(1.176,1.873)〕were associated with increased risk of poor sleep quality in the target population of stroke screening(P<0.05).Conclusion The problem of poor sleep quality in the target population of stroke screening can not be ignored,which may be associated with age,female,marital status,retired,high alcohol consumption,unhealthy diet and stroke risks.
作者 马芹颖 李冰 许勇 刘萌 王铭维 王彦永 MA Qinying;LI Bing;XU Yong;LIU Meng;WANG Mingwei;WANG Yanyong(Department of Neurology,the First Hospital of Hebei Medical University,Shijiazhuang 050031,China;Brain Aging and Cognitive Neuroscience Laboratory of Hebei Province,Shijiazhuang 050031,China;Medical Consortium Office,the First Hospital of Hebei Medical University,Shijiazhuang 050031,China;Stroke Office,the First Hospital of Hebei Medical University,Shijiazhuang 050031,China)
出处 《中国全科医学》 CAS 北大核心 2020年第36期4609-4614,共6页 Chinese General Practice
基金 河北省健康医疗与生物医药专项(18277705D) 河北省老年病防治项目(LNB201807) 河北省政府专科能力建设和专科带头人培养项目(LS201806)。
关键词 睡眠异常 卒中 横断面研究 匹兹堡睡眠质量指数量表 影响因素分析 Dyssomnias Stroke Cross-sectional studies Pittsburgh sleep quality Index Root cause analysis
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