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

项目总结/摘要 只有14%的1型糖尿病（T1 D）新发成人（年龄18-25岁）实现血糖控制 (A1C< 7.0%）的目标。糖尿病自我管理需要高度参与 和频繁的决策，再加上需要过渡到独立，因此出现的成年人 糖尿病患者的生活质量（DQOL）也很差。复杂的高阶神经认知技能（例如， 精神警觉性和执行功能）是成功的糖尿病自我管理所必需的。睡眠 缺乏（持续时间<6.5小时）与T1 D年轻人的血糖控制较差相关，并且 睡眠变异性（睡眠持续时间的逐日变化）与血糖控制较差相关， 青少年和中年T1 D患者。在这个高风险的年龄， 组是基于小的横断面描述性受试者间设计（N < 30），短 测量时间帧（例如，超过3天），自我报告的睡眠测量和间歇性血糖 监控而不是当前的监控技术（例如，连续血糖监测仪[CGM]）。此外，A1 C 不能单独解释T1 D患者的血糖变异性或低血糖。据我们所知，只有 已经进行了初步的工作，以延长患有T1 D的新兴成年人（N = 8个新兴成年人）的睡眠。完美 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， CGM平均葡萄糖水平改善。本申请是根据PA-19-129提交的， 具体目标：1。使用自我报告（问卷调查、日记）和客观评估来描述睡眠特征 在40名14岁以上的T1 D新兴成人中使用活动记录法、血糖控制和血糖变异性 天（以捕捉周末和工作日的差异），并探讨受试者（1a）和 受试者内（1b）（K99期）; 2.为了适应糖尿病自我行为睡眠自我管理（SSM）， 管理教育（DSME）干预，采用社区参与的方法，有10名新成年人参与 具有T1 D（R 00相）;以及，3.进行一项随机试点研究，以确定可行性和初步 SSM与DSME计划在改善神经认知功能（精神警觉性和 执行功能）、糖尿病自我管理、DQOL、血糖控制和血糖变异性， 从基线到干预后3个月和6个月（R 00阶段）的T1 D新兴成人。满足 为了达到这些目标，我们将在研究的每个阶段招募40名新生成年人。我们将使用描述性方法 K99阶段和R 00阶段的目标2。对于目标3，我们将随机分配到带有DSME的SSM 干预或注意力控制（仅限DSME）。腕动计测量睡眠、CGM葡萄糖、血糖 A1 C值控制，精神警觉性和执行功能测试，以及自我报告的 将在基线和随访时获得睡眠症状、自我管理和DQOL。数据将 使用多变量技术进行分析，并在R 00阶段计算初步效应量（目的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).