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隗瑛琦, 马爱娟, 谢瑾, 方凯, 董晶, 谢晨, 董忠. 北京市18~79岁居民不良睡眠状况与慢性病共病患病关系[J]. 中国公共卫生, 2022, 38(11): 1412-1416. DOI: 10.11847/zgggws1136854
引用本文: 隗瑛琦, 马爱娟, 谢瑾, 方凯, 董晶, 谢晨, 董忠. 北京市18~79岁居民不良睡眠状况与慢性病共病患病关系[J]. 中国公共卫生, 2022, 38(11): 1412-1416. DOI: 10.11847/zgggws1136854
WEI Ying-qi, MA Ai-juan, XIE Jin, . Association of poor sleep with multiple chronic conditions among adult residents in Beijing: a cross-sectional survey[J]. Chinese Journal of Public Health, 2022, 38(11): 1412-1416. DOI: 10.11847/zgggws1136854
Citation: WEI Ying-qi, MA Ai-juan, XIE Jin, . Association of poor sleep with multiple chronic conditions among adult residents in Beijing: a cross-sectional survey[J]. Chinese Journal of Public Health, 2022, 38(11): 1412-1416. DOI: 10.11847/zgggws1136854

北京市18~79岁居民不良睡眠状况与慢性病共病患病关系

Association of poor sleep with multiple chronic conditions among adult residents in Beijing: a cross-sectional survey

  • 摘要:
      目的  了解北京市18~79岁居民不良睡眠状况与慢性病共病患病的关系,为慢性病共病的预防控制提供参考依据。
      方法  于2017年8 — 12月采用多阶段分层整群随机抽样方法在北京市16个区抽取13 240名18~79岁常住居民进行问卷调查、体格检查和实验室检测;采用复杂抽样加权方法估计居民不良睡眠率和慢性病共病患病率,并应用多因素非条件logistic回归模型分析打鼾/窒息、中间觉醒 ≥ 2次、早醒、入睡困难、服用安眠药5种不良睡眠状况与慢性病共病患病的关系。
      结果  北京市13 240名18~79岁居民中,自述30 d内每周 ≥ 3 d出现打鼾/窒息3413人(25.8 %)、入睡困难2536人(19.2 %)、中间觉醒 ≥ 2次3103人(23.4 %)、早醒2671人(20.2 %)、服用安眠药367人(2.8 %),有 ≥ 1种不良睡眠状况者6490人,复杂抽样加权后不良睡眠率为52.1 %;慢性病共病患病者4 980例,复杂抽样加权后慢性病共病患病率为41.7 %;在调整了性别、年龄、文化程度、婚姻状况、居住地、是否现在吸烟、近7 d是否饮酒、是否身体活动不足、是否主动体检和是否健康体重等混杂因素后,多因素非条件logistic回归分析结果显示,打鼾/窒息(OR = 1.955,95 % CI = 1.731~2.208)、中间觉醒 ≥ 2次(OR = 1.914,95 % CI = 1.591~2.202)、早醒(OR = 1.802,95 % CI = 1.534~2.117)、入睡困难(OR = 1.625,95 % CI = 1.380~1.913)、服用安眠药(OR = 2.617,95 % CI = 1.907~3.592)这5种不良睡眠状况均与北京市18~79岁居民慢性病共病的风险有关。
      结论  北京市18~79岁居民不良睡眠和慢性病共病患病状况均较为严重,且多种不良睡眠状况均与慢性病共病患病有关,应在治疗已有疾病的同时关注患者的睡眠问题。

     

    Abstract:
      Objective  To analyze the relationship between poor sleep and multiple chronic conditions (MCC) among residents aged 18 – 79 years in Beijing in 2017 for providing reference to the prevention and control of chronic disease comorbidity.
      Methods  A total of 13 240 permanent residents aged 18 – 79 years were recruited from 16 districts of Beijing municipality with stratified multistage cluster sampling. Face-to-face questionnaire interviews, physical examination and laboratory detections were conducted among the residents during August – December 2017. Complex sampling weighting method was used to estimate the prevalence of poor sleep status and MCC and correlations between poor sleep status and MCC were analyzed with unconditional multivariate logistic regression models.
      Results  All the residents completed the survey. The self-reported prevalence rate of poor sleep status at least three days in a week during past 30 days was 25.8% (n = 3 413) for snoring / sleep apnea, 19.2% (n = 2 536) for difficulty in falling asleep, 23.4% (n = 3 103) for two and more times of intermediate awakening in one night, 20.2% (n = 2 671) for early awakening, and 2.8% (n = 367) for taking sleeping pills; the complex sampling weighted prevalence rate of poor sleep (reporting one or more bad sleep conditions) was 52.1% (n = 6 490). Totally 4 980 sufferers of MCC were identified among all the participants, with a weighted MCC prevalence rate of 41.7%. Unconditional multivariate logistic regression analysis revealed that the participants reporting the poor sleep status were associated with MCC, with the odds ratios (95% confidence intervals) of 1.955 (1.731 – 2.208) for the participants reporting snoring / sleep apnea, 1.914 (1.591 – 2.202) for intermediate awakening of ≥ two times, 1.802 (1.534 – 2.117) for early awakening, 1.625 (1.380 – 1.913) for difficulty in falling asleep, and 2.617 (1.907 – 3.592) for taking sleeping pills after adjusting for confounding factors such as gender, age, education, marital status, place of residence, smoking, alcohol drinking during past 7 days, physical activity, active physical examination and body weight.
      Conclusion  Poor sleep status and MCC were prevalent and a variety of poor sleep conditions were related to MCC among 18 – 79 years old residents in Beijing.

     

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