Christodoulou Nausicaa, Bertrand Léa, Palagini Laura, Frija-Masson Justine, d'Ortho Marie-Pia, Lejoyeux Michel, Riemann Dieter, Maruani Julia, Geoffroy Pierre A
Université Paris Cité, Paris, France.
Département de psychiatrie et d'addictologie, AP-HP, GHU Paris Nord, DMU Neurosciences, Hospital Bichat - Claude Bernard, Paris, France.
J Sleep Res. 2023 Feb;32(1):e13752. doi: 10.1111/jsr.13752. Epub 2022 Oct 11.
Insomnia is the most frequent sleep disorder and a public health concern that increased during the Covid 19 pandemic. Fully restrictive lockdowns during Covid are interesting periods to examine the impact of environmental and behavioural changes on the emergence of insomnia symptoms. In this cross-sectional study we aimed to (1) determine the main factors associated with insomnia symptoms during a Covid-19 fully restrictive lockdown examining the associated daily life alterations and (2) create a predictive model of insomnia symptoms. We used the data drawn from the "Covid-RythmE" study that reached volunteers from the general French population through an online survey during the last 2 weeks of the 2 month full lockdown. Associations with insomnia symptoms were tested and significant associations were entered in a Backward Stepwise Logistic Regression (BSLR) to assess the best combination to classify individuals with or without insomnia symptoms. From the 1624 participants, 50.64% suffered from mild to severe insomnia symptoms as assessed by the ISI. The best combination for explaining insomnia symptoms with 74.26% of accuracy included: age (OR = 1.15), females (OR = 1.26), smaller home sizes (OR = 0.77), environmental noises (OR = 1.59), anxiety symptoms (OR = 1.24), depressive symptoms (OR = 1.15), regularity of sleep-wake schedules (OR = 1.25), exposure to screen during the morning (OR = 1.13), and LED light during the evening (OR = 1.17). Thus, lifestyle schedule and exposure to natural synchronizers such as light, are primordial in considering in insomnia physiopathology, prevention and treatment, as well as the associated mental health status.
失眠是最常见的睡眠障碍,也是一个公共卫生问题,在新冠疫情期间有所增加。新冠疫情期间的全面封锁是研究环境和行为变化对失眠症状出现的影响的有趣时期。在这项横断面研究中,我们旨在:(1)确定在新冠疫情全面封锁期间与失眠症状相关的主要因素,研究相关的日常生活变化;(2)创建一个失眠症状预测模型。我们使用了从“Covid-RythmE”研究中提取的数据,该研究在为期2个月的全面封锁的最后2周通过在线调查从法国普通人群中招募志愿者。测试了与失眠症状的关联,并将显著关联纳入向后逐步逻辑回归(BSLR),以评估对有或无失眠症状个体进行分类的最佳组合。在1624名参与者中,50.64%的人根据失眠严重程度指数(ISI)评估患有轻度至重度失眠症状。以74.26%的准确率解释失眠症状的最佳组合包括:年龄(OR = 1.15)、女性(OR = 1.26)、住房面积较小(OR = 0.77)、环境噪音(OR = 1.59)、焦虑症状(OR = 1.24)、抑郁症状(OR = 1.15)、睡眠-觉醒时间表的规律性(OR = 1.25)、早晨接触屏幕(OR = 1.13)以及晚上接触LED灯(OR = 1.17)。因此,生活方式时间表以及对自然同步因素(如光线)的接触,在考虑失眠的生理病理学、预防和治疗以及相关心理健康状况方面至关重要。