IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.
Psychogeriatrics. 2023 May;23(3):487-493. doi: 10.1111/psyg.12959. Epub 2023 Mar 26.
Very few studies have investigated sleep characteristics in the oldest-old individuals (aged ≥85 years) and data collected often rely on self-reported information. This study had three aims: (i) to objectively assess, using a wearable device, the sleep characteristics of a large community of oldest-old subjects; (ii) to assess differences in sleep parameters between self-reported 'good sleepers' and 'bad sleepers'; (iii) to assess whether there was a relationship between sleep parameters and cognitive status in this community-dwelling population.
There were 178 subjects (74.2% women, median age 92 years) included in the 'Mugello study', who wore an armband 24 h/day for at least two consecutive nights to estimate sleep parameters. The perceived sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), the cognitive status through the Mini-Mental State Examination. Continuous variables were compared between men/women, and good/bad sleepers with the independent t-test or Mann-Whitney U-test, according to data distribution. Chi-square test was used for categorical/dichotomous variables. An ordinal logistic regression model was used to study the possible association between sleep parameters and cognitive function.
Participants spent in bed nearly 9 h, with a total sleep time of 7 h, a sleep onset latency of 17 min, and a sleep efficiency of 83%. Sleep onset latency was significantly associated with different cognitive levels when age and education level were considered. No significant difference in sleep parameters estimated using the SenseWear armband were found between poor (n = 136, 76.4%) and good sleepers (n = 42, 23.6%), identified according to the PSQI.
In this study, actigraphic measurements revealed that subjects with a cognitive decline were more prone to increased sleep onset latency. Sleep quality assessed using the PSQI was not coherent with actigraphic measurements in this sample, supporting the need for objective measures when investigating sleep quality in the oldest-old population.
很少有研究调查过 85 岁以上的老年人的睡眠特征，而且收集的数据通常依赖于自我报告的信息。本研究有三个目的：(i) 使用可穿戴设备客观评估一大群最年长老年人的睡眠特征；(ii) 评估自我报告的“睡眠良好者”和“睡眠不良者”之间睡眠参数的差异；(iii) 评估在这个社区居住的人群中，睡眠参数与认知状态之间是否存在关系。
共有 178 名受试者（74.2%为女性，中位年龄 92 岁）参加了“Mugello 研究”，他们每天佩戴臂带 24 小时，至少连续两天以估计睡眠参数。使用匹兹堡睡眠质量指数（PSQI）评估睡眠质量，使用简易精神状态检查（Mini-Mental State Examination）评估认知状态。根据数据分布，使用独立样本 t 检验或 Mann-Whitney U 检验比较男性/女性和睡眠良好者/睡眠不良者之间的连续变量。使用卡方检验比较分类/二分类变量。使用有序逻辑回归模型研究睡眠参数与认知功能之间的可能关联。
参与者在床上的时间接近 9 小时，总睡眠时间为 7 小时，入睡潜伏期为 17 分钟，睡眠效率为 83%。考虑到年龄和教育水平，入睡潜伏期与不同的认知水平显著相关。根据 PSQI 识别的睡眠不良者（n=136，76.4%）和睡眠良好者（n=42，23.6%）之间，使用 SenseWear 臂带估计的睡眠参数没有显著差异。
在这项研究中，活动记录仪测量结果显示，认知能力下降的受试者更容易出现入睡潜伏期延长。在这个样本中，使用 PSQI 评估的睡眠质量与活动记录仪测量结果不一致，这支持在调查最年长老年人的睡眠质量时需要使用客观测量。
