Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Global Development Institute, School of Environment, Education and Development, Faculty of Humanities, The University of Manchester, Manchester, UK.
J Sleep Res. 2020 Jun;29(3):e12898. doi: 10.1111/jsr.12898. Epub 2019 Jul 16.
The relationships between older age and sleep efficiency have traditionally been assessed using cross-sectional studies that ignore changes within individuals as they age. This research examines the determinants of sleep efficiency, the heterogeneity in an individual's sleep efficiency trajectory across a period of up to 27 years in later life and its associations with health. The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age cohort (n = 6,375; age 42-94 years) was used in this study. Depression and health data were collected using self-report validated instruments (Cornell Medical Index, Beck Depression Inventory and Geriatric Depression Scale). Longitudinal sleep and sociodemographic data were collected using a study-specific self-report questionnaire. A mixed-effect model was performed for sleep efficiency with adjustments for time-invariant and time-variant predictors. Latent class analysis was used to demonstrate subgroups of sleep efficiency trajectories and associations between sleep efficiency clusters and health history of the participants were investigated. Older adults have decreased sleep efficiency over time, with 18.6% decline between 40 and 100 years of age. Three sleep efficiency trajectory clusters were identified: high (32%), medium (50%) and low sleep efficiency (18%). Belonging to the high sleep efficiency cluster was associated with having lower prevalence of hypertension, circulatory problems, general arthritis, breathing problems and recurrent episodes of depression compared to the low efficiency cluster. Overall, ageing decreases sleep efficiency. However, there are detectable subgroups of sleep efficiency that are related to prevalence of different diseases.
传统上，使用忽略个体随年龄变化的横断面研究来评估年龄与睡眠效率之间的关系。本研究考察了睡眠效率的决定因素、个体在长达 27 年的老年期内睡眠效率轨迹的异质性及其与健康的关联。本研究使用了曼彻斯特大学认知正常健康老龄化纵向研究（n=6375；年龄 42-94 岁）的数据。使用经过验证的自我报告工具（康奈尔医学指数、贝克抑郁量表和老年抑郁量表）收集抑郁和健康数据。使用特定于研究的自我报告问卷收集纵向睡眠和社会人口统计学数据。使用混合效应模型对睡眠效率进行调整，以考虑时间不变和时变预测因素。采用潜在类别分析显示睡眠效率轨迹的亚组，并研究睡眠效率聚类与参与者健康史之间的关联。随着时间的推移，老年人的睡眠效率逐渐下降，40 岁至 100 岁之间下降了 18.6%。确定了三种睡眠效率轨迹聚类：高（32%）、中（50%）和低睡眠效率（18%）。与低效率聚类相比，属于高效睡眠聚类与高血压、循环问题、一般性关节炎、呼吸问题和复发性抑郁的患病率较低相关。总的来说，衰老会降低睡眠效率。然而，存在可检测的睡眠效率亚组，与不同疾病的患病率相关。
