The University of Alabama, Tuscaloosa, AL 35487-0348, USA.
Sleep Med. 2010 Jan;11(1):65-8. doi: 10.1016/j.sleep.2009.07.009. Epub 2009 Sep 23.
The relationship between reports of insomnia and daytime functioning was investigated using hierarchical regression. The presence or absence of a report of insomnia was the predictor of primary interest. A number of covariates were included in the model: demographic variables, health variables, and quantitative sleep parameters.
Data were collected from a community sample in the Memphis, Tennessee area. Data from 734 volunteers, ranging in age from 20 to 96years were analyzed. The sample included 235 individuals who reported having chronic insomnia and 499 individuals who reported no sleep problems. Participants completed a 2-week sleep diary, a battery of daytime functioning questionnaires, and a medical disorders checklist. Demographic information was also collected. The daytime functioning assessment included the Beck Depression Inventory, the State-Trait Anxiety Inventory, the Epworth Sleepiness Scale, the Insomnia Impact Scale, and the Fatigue Severity Scale. The hierarchical regression model included four sets. The first three sets consisted of 18 variables capturing demographic, health, and sleep diary parameters. The fourth set included a single dichotomous variable representing the presence or absence of a report of insomnia.
Reports of insomnia were a significant predictor of all five daytime functioning measures, which is consistent with previous research. We also showed that reports of insomnia were able to uniquely explain a significant amount of variability in self-reported daytime functioning after controlling for demographics, health, and sleep diary variables. The pattern of individual variables that reached significance in the first three sets varied depending on which daytime functioning measure was predicted, however, age, the presence of pain, the presence of mental health problems, SOL, and WASO were the most commonly significant predictors of poor daytime functioning from these sets across measures.
Individuals' perceptions of their sleep are related to differences in their reported daytime functioning, which are not accounted for by demographic factors, health surveys, or quantitative sleep assessments. Reports of insomnia may be related to a set of common cognitive factors among individuals who report having insomnia which cause them to be distressed with their sleep and increase their dissatisfaction with daytime functioning. Relevance of the findings to insomnia research and clinical management are discussed.
使用分层回归研究报告的失眠与日间功能之间的关系。主要关注的预测变量是报告的失眠的存在或不存在。该模型纳入了许多协变量:人口统计学变量、健康变量和定量睡眠参数。
数据来自田纳西州孟菲斯地区的社区样本。对年龄在 20 至 96 岁之间的 734 名志愿者的数据进行了分析。该样本包括 235 名报告有慢性失眠的个体和 499 名报告无睡眠问题的个体。参与者完成了为期两周的睡眠日记、一系列日间功能问卷和一份医疗障碍清单。还收集了人口统计学信息。日间功能评估包括贝克抑郁量表、状态-特质焦虑量表、Epworth 嗜睡量表、失眠影响量表和疲劳严重程度量表。分层回归模型包括四组。前三组由 18 个变量组成,用于捕获人口统计学、健康和睡眠日记参数。第四组包括一个代表是否存在报告失眠的单一二分变量。
报告的失眠是所有五项日间功能测量的显著预测因子,这与先前的研究一致。我们还表明,在控制人口统计学、健康和睡眠日记变量后,报告的失眠能够独立地解释自我报告的日间功能中大量的可变性。然而,在前三组中,达到显著水平的个体变量的模式取决于预测的日间功能测量指标,年龄、疼痛的存在、心理健康问题的存在、SOL 和 WASO 是这些组中最常见的日间功能不良的显著预测因子。
个体对睡眠的感知与他们报告的日间功能的差异有关,这些差异不能用人口统计学因素、健康调查或定量睡眠评估来解释。失眠的报告可能与报告失眠的个体中存在的一组常见认知因素有关,这些因素使他们对自己的睡眠感到困扰,并增加了他们对日间功能的不满。讨论了这些发现对失眠研究和临床管理的意义。