关云琦,张梅,张笑,赵振平,黄正京,李纯,王璇,王丽敏.我国就业流动人口睡眠状况及影响因素分析[J].Chinese journal of Epidemiology,2020,41(8):1242-1249 |
我国就业流动人口睡眠状况及影响因素分析 |
Status of sleep and influencing factors in employed floating population in China |
Received:December 11, 2019 |
DOI:10.3760/cma.j.cn112338-20191211-00876 |
KeyWord: 流动人口 睡眠状况 影响因素 |
English Key Word: Floating population Sleep status Influencing factors |
FundProject: |
Author Name | Affiliation | E-mail | Guan Yunqi | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Zhang Mei | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Zhang Xiao | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Zhao Zhenping | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Huang Zhengjing | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Li Chun | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Wang Xuan | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | | Wang Limin | Division of Chronic Disease Risk Factor Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China | wanglimin@ncncd.chinacdc.cn |
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Abstract: |
目的 了解我国18~59岁就业流动人口睡眠状况及其影响因素,为改善流动人口睡眠状况的相关政策提供依据。方法 利用2012年中国慢性病及其危险因素监测流动人口专题调查数据,该调查采用按行业分层多阶段整群抽样的方法在全国范围开展,以面对面访谈的方式,询问调查对象的人口学基本信息、行为危险因素、睡眠时间以及社会压力状况。对数据进行复杂加权后,采用多因素logistic回归模型,探讨就业流动人口睡眠状况及其影响因素。结果 共纳入43 521名研究对象,就业流动人口平均每天睡眠时间为7.77 h,女性(7.87 h)高于男性(7.69 h)。就业流动人口睡眠不足率为12.3%(95% CI:11.8%~12.7%),45~59岁人群(21.2%)高于18~岁人群(11.2%)。多因素logistic回归分析发现,性别、年龄、婚姻状况、文化程度、职业、流入地区、行为危险因素、BMI、社会压力、自评健康状况和自报患有慢性病是影响流动人口睡眠不足率的主要因素。男性流动人口睡眠不足率是女性的1.18倍(95% CI:1.07~1.31);吸烟人群是不吸烟人群的1.22倍(95% CI:1.11~1.33);过量饮酒人群是正常人群的1.31倍(95% CI:1.16~1.49);工作和生活压力较大的流动人口睡眠不足率是没有工作和生活压力人群的1.46倍(95% CI:1.29~1.65)和1.33倍(95% CI:1.18~1.50)。结论 我国就业流动人口睡眠不足率受多种因素的影响,政府有关部门应加强对流动人口睡眠状况的重视,不断提高流动人口的睡眠质量。 |
English Abstract: |
Objective To understand the sleep status and related influencing factors among 18-59 years old employed floating population and to provide evidence for policy development. Methods Data were gathered from the Chinese Floating Population Chronic Disease Surveillance (2012) program. Floating population were selected through multistage clustering sampling method and stratified by industries from China. Information on demographics, behavior-related risk factors, sleep duration and social pressure etc., were collected through face-to-face interview on questionnaires. After complex weighting of data, multivariable logistic regression method was used to explore the sleep status and related influencing factors among these employed floating people. Results A total of 43 521 subjects were included in the study. The average sleep duration per day was 7.77 h, with females (7.87 h) higher than males (7.69 h). The prevalence of insufficient sleep was 12.3% (95%CI:11.8%-12.7%), with 45-59 years old group (21.2%) higher than that of the 18-year olds (11.2%). Results from the multivariable logistic regression analysis showed that factors as gender, age, marital status, education, occupation, inflowing area, behavior-related risk factors, BMI, social pressure, self-rated health status and self-reported chronic diseases were the main factors that affecting the rates of sleep deficiency in this population. The prevalence rate of insufficient sleep was 1.18 times higher (95%CI:1.07-1.31) in males than that in females, and 1.22 (95%CI:1.11-1.33) times higher in smokers than that in the non-smokers, 1.31(95%CI:1.16-1.49) times higher in excessive drinkers than that of the normal population, 1.46 (95%CI:1.29-1.65) times and 1.33 (95%CI:1.18-1.50) times in those with heavier workload and stress than those without. Conclusion The prevalence of insufficient sleep among the employed floating population was affected by multiple factors that called for more attention by different departments of the government. |
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