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Early Impact of the COVID-19 Outbreak on Sleep in a Large Spanish Sample
Behavioral Sleep Medicine ( IF 2.2 ) Pub Date : 2021-03-02 , DOI: 10.1080/15402002.2021.1890597
Francesco Dal Santo 1, 2, 3, 4 , Leticia González-Blanco 1, 2, 3, 4, 5 , Julia Rodríguez-Revuelta 1, 2, 3, 4, 5 , Pedro A Marina González 3, 4 , Gonzalo Paniagua 4 , Leticia García-Álvarez 1, 2, 3, 5, 6 , Lorena de la Fuente-Tomás 1, 2, 3, 5 , Pilar A Sáiz 1, 2, 3, 4, 5 , María Paz García-Portilla 1, 2, 3, 4, 5 , Julio Bobes 1, 2, 3, 4, 5
Affiliation  

ABSTRACT

Introduction

Coronavirus disease 2019 (COVID-19) forced Spain to implement unprecedented lockdown restriction. In this context, different factors could worsen sleep quality, but the impact of the pandemic and lockdown on sleep is still mostly unknown. In this cross-sectional study, we describe self-reported sleep disturbances in people without mental health disorders from a large Spanish sample (n = 15,070).

Methods

During the early phase of the lockdown (19–26 March), an online survey was launched using a snowball sampling method and included sociodemographic and clinical data along with the Depression, Anxiety, and Stress Scale (DASS-21) and the Impact of Event Scale (IES). Two items of the IES were employed to assess sleep characteristics. Descriptive and bivariate analysis and logistic regression models were performed.

Results

Difficulty initiating or maintaining sleep were reported by 23.9% of the sample and was associated in the regression model with age (OR = 1.008, p = .003), female sex (OR = 1.344, p < .001), an income reduction >50% (OR = 1.248, p = .037), having one (OR = 1.208, p = .029) and two or more (OR = 1.299, p = .035) elderly dependents, drinking alcohol (OR = 1.129, p = .024), and a higher score on DASS-21 depression (OR = 1.148, p < .001), anxiety (OR = 1.218, p < .001), or stress (OR = 1.302, p < .001) subscales, whereas being able to enjoy free time (OR = 0.604, p < .001) and painting or listening to music (OR = 0.853, p = .012) were protective factors. Dreams related to COVID-19 were reported by 12.9% of the sample and were associated in the regression model with female sex (OR = 1.617, p < .001), being married (OR = 1.190, p = .015), self-employed (OR = 1.373, p = .032), or a civil servant (OR = 1.412, p = .010), having been tested for COVID-19 (OR = 1.583, p = .012), having infected family or friends (OR = 1.233, p = .001), reading news about coronavirus (OR = 1.139, p = .023), drinking alcohol (OR = 1.251, p < .001), and higher scores on DASS-21 depression (OR = 1.102, p < .001), anxiety (OR = 1.222, p < .001), or stress (OR = 1.213, p < .001) subscales, while protective factors were older age (OR = 0.983, p < .001) and being retired (OR = 0.625, p = .045).

Conclusions

These findings could help clinicians and public health systems design and deliver tailored interventions, such as internet-delivered campaigns, to promote sleep quality in the general population.



中文翻译:

西班牙大型样本中 COVID-19 爆发对睡眠的早期影响

摘要

介绍

2019 年冠状病毒病 (COVID-19) 迫使西班牙实施前所未有的封锁限制。在这种情况下,不同的因素可能会恶化睡眠质量,但大流行和封锁对睡眠的影响仍然大多未知。在这项横断面研究中,我们描述了来自大型西班牙样本(n = 15,070)的没有精神健康障碍的人自我报告的睡眠障碍。

方法

在锁定的早期阶段(3 月 19 日至 26 日),使用滚雪球抽样方法启动了一项在线调查,其中包括社会人口学和临床数据以及抑郁、焦虑和压力量表 (DASS-21) 以及事件的影响规模 (IES)。使用 IES 的两个项目来评估睡眠特征。进行了描述性和双变量分析以及逻辑回归模型。

结果

23.9% 的样本报告了开始或维持睡眠的困难,并且在回归模型中与年龄 (OR = 1.008, p = .003)、女性 (OR = 1.344, p < .001)、收入减少 > 50% (OR = 1.248, p = .037),有一个 (OR = 1.208, p = .029) 和两个或更多 (OR = 1.299, p = .035) 老年家属,饮酒 (OR = 1.129, p = .024),在 DASS-21 抑郁 (OR = 1.148, p < .001)、焦虑 (OR = 1.218, p < .001) 或压力 (OR = 1.302, p < .001) 分量表上得分更高, 而能够享受空闲时间 (OR = 0.604, p< .001) 和绘画或听音乐 (OR = 0.853, p = .012) 是保护因素。12.9% 的样本报告了与 COVID-19 相关的梦境,并在回归模型中与女性(OR = 1.617,p < .001)、已婚(OR = 1.190,p = .015)、自我受雇(OR = 1.373,p = .032)或公务员(OR = 1.412,p = .010),接受过 COVID-19 检测(OR = 1.583,p = .012),感染了家人或朋友(OR = 1.233, p = .001)、阅读有关冠状病毒的新闻 (OR = 1.139, p = .023)、饮酒 (OR = 1.251, p< .001),以及 DASS-21 抑郁 (OR = 1.102, p < .001)、焦虑 (OR = 1.222, p < .001) 或压力 (OR = 1.213, p < .001) 分量表的得分较高,而保护因素是年龄较大 (OR = 0.983, p < .001) 和退休 (OR = 0.625, p = .045)。

结论

这些发现可以帮助临床医生和公共卫生系统设计和提供量身定制的干预措施,例如通过互联网提供的活动,以提高普通人群的睡眠质量。

更新日期:2021-03-02
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