Huang Jing, McPhillips Miranda V, Li Mengchi, Spira Adam P, Calderon Russell, Li Junxin
School of Nursing, Johns Hopkins University, Baltimore, MD, USA.
School of Nursing, University of Pennsylvania, Philadelphia, PA, USA.
J Geriatr Psychiatry Neurol. 2025 Jul;38(4):303-308. doi: 10.1177/08919887241304769. Epub 2024 Dec 6.
BackgroundThere is limited and inconsistent evidence on the association between electroencephalography (EEG) measured sleep and depressive symptoms among community-dwelling older adults. This study aimed to investigate the cross-sectional association between EEG-measured sleep and depressive symptoms.MethodsUsing baseline data from a randomized clinical trial, we included 66 sedentary community-dwelling older adults with sleep complaints (≥ 1 self-reported insomnia symptom). Sleep was measured using an in-home sleep EEG (Sleep Profiler™) for 2 nights and the Geriatric Depression Scale (GDS-15) was used to measure depressive symptoms. Multiple linear regression analyses were conducted with each sleep parameter as the primary predictor and GDS score as the outcome, adjusting for age, sex, race, education, marital status, chronic conditions, and Montreal Cognitive Assessment (MoCA) score.ResultsSeveral sleep variables were associated with depressive symptoms (GDS score), including a higher percentage of sleep stage N1 (B = 0.11, 95% confidence interval [CI]: 0.02 - 0.20) and N2 (B = 0.04, 95% CI: 0.00 - 0.08), a lower percentage of N3 sleep (B = -0.04, 95% CI: -0.08 to -0.01), greater wake after sleep onset (B = 0.01, 95% CI: 0.00 - 0.02), and a greater number of awakenings ≥90s/hour (B = 0.87, 95% CI: 0.21-1.53).ConclusionsOur study reveals that among sedentary community-dwelling older adults with sleep complaints, more lighter sleep (stage N1, N2), less deep (N3) sleep, and increased awakenings are associated with more depressive symptoms. Sleep interventions aimed at enhancing sleep architecture may also help alleviate depressive symptoms in this population.
背景
关于社区居住的老年人中，通过脑电图（EEG）测量的睡眠与抑郁症状之间的关联，证据有限且不一致。本研究旨在调查通过EEG测量的睡眠与抑郁症状之间的横断面关联。
方法
利用一项随机临床试验的基线数据，我们纳入了66名久坐不动的社区居住老年人，他们有睡眠问题（≥1项自我报告的失眠症状）。使用家用睡眠EEG（Sleep Profiler™）测量2晚的睡眠情况，并使用老年抑郁量表（GDS-15）测量抑郁症状。进行了多项线性回归分析，以每个睡眠参数作为主要预测因素，GDS分数作为结果，并对年龄、性别、种族族、教育程度、婚姻状况、慢性病和蒙特利尔认知评估（MoCA）分数进行了调整。
结果
几个睡眠变量与抑郁症状（GDS分数）相关，包括较高比例的N1睡眠阶段（B = 0.11，95%置信区间[CI]：0.02 - 0.20）和N2睡眠阶段（B = 0.04，95% CI：0.00 - 0.08），较低比例的N3睡眠（B = -0.04，95% CI：-0.08至-0.01），睡眠开始后更多的觉醒时间（B = 0.01，95% CI：0.00 - 0.02），以及每小时≥90秒的觉醒次数更多（B = 0.87，95% CI：0.21 - 1.53）。
结论
我们的研究表明，在有睡眠问题的久坐不动的社区居住老年人中，更多的浅睡眠（N1、N2阶段）、更少的深睡眠（N3）和更多的觉醒与更多的抑郁症状相关。旨在改善睡眠结构的睡眠干预措施也可能有助于减轻该人群的抑郁症状。
