Wu Xinrui, Dunietz Galit Levi, Shedden Kerby, Chervin Ronald D, Jansen Erica C, Lyu Xiru, O'Brien Louise M, Baylin Ana, Wactawski-Wende Jean, Schisterman Enrique F, Mumford Sunni L
Department of Statistics, University of Michigan, Ann Arbor, MI, United States.
Division of Sleep Medicine, Department of Neurology, University of Michigan, Ann Arbor, MI, United States.
Sleep Epidemiol. 2024 Dec;4. doi: 10.1016/j.sleepe.2024.100093. Epub 2024 Jul 31.
To identify sleep dimensions (characteristics) that co-occur in premenopausal women. The second aim was to examine associations between multiple dimensions of sleep and a set of demographic, lifestyle, and health correlates. The overarching goal was to uncover patterns of poor-sleep correlates that might inform interventions to improve sleep health of women in this age group.
The BioCycle Study included 259 healthy women aged 18-44y recruited between 2005 and 2007 from Western New York. Participants reported sleep data through daily diaries and questionnaires that were used to create five sleep health dimensions (duration, variability, timing, latency, and continuity). We used multivariate analysis - canonical correlation methods - to identify links among dimensions of sleep health and patterns of demographic, psychological, and occupational correlates.
Two distinct combinations of sleep dimensions were identified. The first - primarily determined by low variability in nightly sleep duration, low variability in bedtime (timing), greater nocturnal awakening, and less sleep onset latency - was distinguished from the second - primarily determined by sleep duration.The first combination of sleep dimensions was associated with older age and higher parity, fewer depressive symptoms, and higher stress level. The second combination of sleep dimensions was associated with perception of longer sleep duration as optimal, lower parity, not engaging in shift work, older age, lower stress level, higher prevalence of depressive symptoms, and White race.
Among premenopausal women, we demonstrated distinct patterns of sleep dimensions that co-occur and vary by demographic, health, and lifestyle correlates. These findings shed light on the correlates of sleep health vulnerabilities among young women.
确定绝经前女性中共同出现的睡眠维度（特征）。第二个目标是研究睡眠的多个维度与一系列人口统计学、生活方式和健康相关因素之间的关联。总体目标是揭示睡眠不佳相关因素的模式，这些模式可能为改善该年龄组女性睡眠健康的干预措施提供依据。
生物周期研究纳入了2005年至2007年从纽约西部招募的259名18 - 44岁的健康女性。参与者通过每日日记和问卷报告睡眠数据，这些数据用于创建五个睡眠健康维度（时长、变异性、时间、潜伏期和连续性）。我们使用多变量分析——典型相关方法——来确定睡眠健康维度与人口统计学、心理和职业相关因素模式之间的联系。
确定了两种不同的睡眠维度组合。第一种——主要由夜间睡眠时间变异性低、就寝时间（时间）变异性低、夜间觉醒次数多和入睡潜伏期短决定——与第二种——主要由睡眠时间决定——不同。第一种睡眠维度组合与年龄较大、生育次数较多、抑郁症状较少和压力水平较高有关。第二种睡眠维度组合与认为较长睡眠时间为最佳、生育次数较少、不从事轮班工作、年龄较大、压力水平较低、抑郁症状患病率较高以及白人种族有关。
在绝经前女性中，我们证明了睡眠维度的不同模式会共同出现，并因人口统计学、健康和生活方式相关因素而有所不同。这些发现揭示了年轻女性睡眠健康脆弱性的相关因素。
