Sleep, Glycemia, and Self-Management in Young Adults with Type 1 Diabetes Mellitus

项目摘要/摘要 在患有1型糖尿病(T1D)的新发成人(18-25岁)中，只有14%的人实现了血糖控制 (A1C&lt；7.0%)基于国家数据的目标。糖尿病自我管理需要高度的参与 和频繁的决策，再加上需要过渡到独立，因此出现了成年人 患糖尿病生活质量(DQOL)较差的风险也较高。复杂的高级神经认知技能(例如， 精神运动警觉和执行功能)是成功的糖尿病自我管理所必需的。沉睡 在患有T1D的年轻人中，缺乏血糖(持续6.5小时)与血糖控制较差有关，并且 睡眠可变性(睡眠持续时间的逐日变化)与血糖控制较差有关 青少年和中年T1D患者。在这个高风险的时代，许多现有的关于睡眠的知识 小组是基于研究对象之间的小横截面描述性设计(N&lt；30)，简短 测量时间范围(例如，超过3天)、自我报告的睡眠测量和间歇性血糖 而不是目前的监测技术(例如，连续血糖监测仪[CGM])。此外，A1C 单独使用不能解释T1D患者的血糖变异性或低血糖。据我们所知，只有 已经进行了初步工作，以延长患有T1D的新兴成年人(N=8名新兴成年人)的睡眠时间。完美无瑕 和同事们设计了一项干预措施，将111名青少年的睡眠时间延长1小时，这导致了 来自CGM的平均血糖水平的改善。本申请书是为回应PA-19-129而提交的 以下具体目标：1.使用自我报告(问卷、日记)和目标来描述睡眠 40名T1D大于14的新发成人的(肌动描记)方法、血糖控制和血糖变异性 天数(捕捉周末和工作日的差异)，并探索受试者(1a)和 在被试中(1b)(K99阶段)；2.适应糖尿病患者的行为睡眠自我管理(SSM) 管理教育(DSME)干预，采用社区参与的方法，对10名新兴成年人进行干预 T1D(R00阶段)；以及，3.进行随机初步研究以确定可行性和初步 SSM与DSME计划在改善神经认知功能方面的效果大小(精神运动警觉和 执行功能)、糖尿病自我管理、DQL、血糖控制和血糖变异性 从基线到干预后3个月和6个月(R00阶段)，新出现的成年人年龄为T1D。相遇 为了达到这些目标，我们将在研究的每个阶段招募40名新兴成年人。我们将使用描述性方法 对于K99阶段和R00阶段的目标2。对于目标3，我们将随机选择具有DSME的SSM 干预或注意力控制(仅限DSME)。手腕运动描记测量睡眠、CGM血糖、血糖 从A1C值控制，精神运动警觉和执行功能测试，以及自我报告的测量 睡眠症状、自我管理和DQL将在基线和随访时获得。数据将是 使用多变量技术进行分析，初步效果大小将在R00阶段计算(目标3)。

PROJECT SUMMARY/ABSTRACT Only 14% of emerging adults (age 18-25 years) with type 1 diabetes mellitus (T1D) achieve glycemic control (A1C < 7.0%) targets based on national data. Diabetes self-management entails a high degree of involvement and frequent decision making, and coupled with the need to transition to independence, thus emerging adults are also at high risk for poorer diabetes quality of life (DQOL). Complex higher order neurocognitive skills (e.g., psychomotor vigilance and executive function) are needed for successful diabetes self-management. Sleep deficiency (< 6.5h duration) is associated with poorer glycemic control among young adults with T1D, and sleep variability (day-to-day changes in sleep duration) is associated with poorer glycemic control in adolescents and middle-aged adults with T1D. Much of the existing knowledge on sleep in this high-risk age group is based on studies with small cross-sectional descriptive between-subjects designs (N < 30), short measurement time frames (e.g., over 3 days), self-reported sleep measures, and intermittent blood glucose monitoring rather than current monitoring technologies (e.g., continuous glucose monitor [CGM]). Further, A1C alone does not account for glucose variability or hypoglycemia for those with T1D. To our knowledge, only preliminary work has been done to extend sleep in emerging adults with T1D (N = 8 emerging adults). Perfect and colleagues designed an intervention to extend sleep by 1 hour in 111 adolescents which led to an improvement in mean glucose levels from CGM. This application submitted in response to PA-19-129 has the following specific aims: 1. To characterize sleep using self-report (questionnaires, diaries) and objective (actigraphy) methods, glycemic control, and glucose variability among 40 emerging adults with T1D over 14 days (to capture weekend and weekday differences) and explore associations between subjects (1a) and within subjects (1b) (K99 phase); 2. To adapt a behavioral Sleep Self-management (SSM) with Diabetes Self- Management Education (DSME) intervention using a community-engaged approach with 10 emerging adults with T1D (R00 phase); and, 3. To conduct a randomized pilot study to determine feasibility and preliminary effect sizes of the SSM with DSME program in improving neurocognitive function (psychomotor vigilance and executive function), diabetes self-management, DQOL, glycemic control, and glucose variability among 40 emerging adults age with T1D from baseline to post-intervention at 3 and 6 months (R00 phase). To meet these aims, we will enroll 40 emerging adults for each phase of the study. We will use descriptive approaches for the K99 phase and aim 2 of the R00 phase. For aim 3, we will randomize to the SSM with DSME intervention or an attention control (DSME only). Wrist actigraphy measures of sleep, CGM glucose, glycemic control from A1C values, psychomotor vigilance and executive function testing, and self-reported measures of sleep symptoms, self-management, and DQOL will be obtained at baseline and follow up. Data will be analyzed using multivariate techniques and preliminary effect sizes will be calculated in the R00 phase (aim 3).