Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Sleep Disorders Center, University of Manitoba, Winnipeg, MB, Canada.
Sci Total Environ. 2022 Jan 20;805:150191. doi: 10.1016/j.scitotenv.2021.150191. Epub 2021 Sep 7.
Nocturnal traffic noise can disrupt sleep and impair physical and mental restoration, but classical sleep scoring techniques may not fully capture subtle yet clinically relevant alterations of sleep induced by noise. We used a validated continuous measure of sleep depth and quality based on automatic analysis of physiologic sleep data, termed Wake Propensity (WP), to investigate temporal changes of sleep in response to nocturnal noise events in 3-s epochs. Seventy-two healthy participants (mean age 40.3 years, range 18-71 years, 40 females, 32 males) slept for 11 nights in a laboratory, during which we measured sleep with polysomnography. In 8 nights, participants were exposed to 40, 80 or 120 road, rail and/or aircraft noise events with maximum noise levels of 45-65 dB L during 8-h sleep opportunities. We analyzed sleep macrostructure and event-related change of WP during noise exposure with linear mixed models. Nocturnal traffic noise led to event-related shifts towards wakefulness and less deep, more unstable sleep (increase in WP relative to pre-noise baseline ranging from +29.5% at 45 dB to +38.3% at 65 dB; type III effect p < 0.0001). Sleep depth decreased dynamically with increasing noise level, peaking when L was highest. This change in WP was stronger and occurred more quickly for events where the noise onset was more rapid (road and rail) compared to more gradually time-varying noise (aircraft). Sleep depth did not immediately recover to pre-noise WP, leading to decreased sleep stability across the night compared to quiet nights, which was greater with an increasing number of noise events (standardized β = 0.053, p = 0.003). Further, WP was more sensitive to noise than classical arousals. Results demonstrate the usefulness of WP as a measure of the effects of external stimuli on sleep, and show WP is a more sensitive measure of noise-induced sleep disruption than traditional methods of sleep analysis.
夜间交通噪音会干扰睡眠，影响身心健康恢复，但传统的睡眠评分技术可能无法完全捕捉到噪音引起的睡眠细微但具有临床意义的变化。我们使用一种经过验证的基于生理睡眠数据自动分析的深度和睡眠质量连续测量方法，称为觉醒倾向（Wake Propensity，WP），以研究在 3 秒的时间段内，睡眠对夜间噪音事件的时间变化。72 名健康参与者（平均年龄 40.3 岁，范围 18-71 岁，女性 40 名，男性 32 名）在实验室中睡眠 11 晚，在此期间我们使用多导睡眠图测量睡眠。在 8 晚中，参与者暴露于 40、80 或 120 个道路交通、铁路和/或航空噪声事件中，最大噪声水平为 45-65 dB L 在 8 小时的睡眠机会中。我们使用线性混合模型分析了噪声暴露期间的睡眠宏观结构和与事件相关的 WP 变化。夜间交通噪声导致与觉醒相关的转变和睡眠深度变浅、更不稳定（与噪声前基线相比，WP 增加幅度为 45 dB 时为+29.5%，65 dB 时为+38.3%；III 型效应 p<0.0001）。随着噪声水平的增加，睡眠深度呈动态变化，在 L 最高时达到峰值。这种 WP 的变化在噪声起始更快的事件中更强且发生更快（道路和铁路）与时间变化更缓慢的噪声（飞机）相比。WP 并没有立即恢复到噪声前的水平，导致与安静夜晚相比，整个夜晚的睡眠稳定性降低，噪声事件数量增加时这种情况更为严重（标准化 β=0.053，p=0.003）。此外，WP 比传统的觉醒对噪声更为敏感。研究结果表明 WP 作为衡量外部刺激对睡眠影响的一种有用方法，并且表明 WP 是一种比传统的睡眠分析方法更敏感的测量噪声引起的睡眠中断的方法。
