AMERICAN INDIAN CHronic disEase RIsk and Sleep Health (AI-CHERISH)

摘要：无论是比较研究还是单一种族研究都表明，睡眠障碍至少与 流行于美国印第安人和阿拉斯加原住民(AI/ANS)，因为他们在所有种族的人口中都是如此。沉睡 众所周知，问题是所有人口中慢性病和早期死亡的重要因素，而 对睡眠障碍的有效治疗改善了对各种健康状况的管理。我们建议 开展一项创新的混合方法研究--美国印第安人慢性病风险与睡眠健康(AI- 评估心血管疾病与新陈代谢风险和睡眠健康的关系 文化。在头两个项目年，我们将举办5个焦点小组(共15个小组，每个小组12人) 以及两轮与5名关键线人的半结构化访谈(共30次访谈)。由此产生的定性 数据将为患者报告的睡眠健康结果测量(PROM)的发展提供信息，以增强 既定的措施，考虑到土著社区特有的因素，并以文化为基础， 改善睡眠的补充指南。在这项工作的数量部分，我们将实施 迄今为止最大的睡眠健康流行病学研究，使用AI/AN样本评估人群患病率 睡眠不足及其与特定心血管疾病危险因素的关联。流行病学研究的参与者 之前曾参加过心脏强健家族研究(SHFS)。对于流行病学研究，我们将招募 来自每个地理区域的250名年龄在30-50岁之间的人工智能参与者(N=750)，并收集每个人的睡眠数据 参与者在单个9个月内进行2次考察访问，访问时间最长的月份和 日照时间最短(5-7月和11-1月)。在每次数据收集访问之前的7天， 参与者将佩戴腕式活动记录器来测量睡眠和清醒的活动，并将记录下 记录醒着的活动以及睡眠持续时间、巩固和时间安排。当他们归还活动记录仪时， 他们将完成4个有效的自我报告工具：匹兹堡睡眠质量指数，Epworth嗜睡 量表、睡眠卫生指数、失眠严重程度指数和Stop-Bang问卷。他们还将 提供有关社会人口学和心血管疾病危险因素(血脂、糖化血红蛋白、血压、 BMI)被认为受睡眠的影响。我们的具体目标是：1)开发一种适合文化的舞会 通过使用焦点小组，根据每个研究地点影响睡眠的当地背景，确定睡眠健康状况。2)输入关键字 与举报人面谈，评估现有指南，并阐明具有文化基础的补充指南 用于改善每个研究地点的睡眠健康，以补充人工智能社区的现有指南。3)估算 客观分析在3个研究地点750名人工智能成人中睡眠不足的患病率和性质 来自动作记录仪的数据和来自睡眠/清醒日记和标准化睡眠仪器的主观数据收集 在9个月内的两个时间点。4)评估睡眠健康不良的横向关联，如 由我们的客观和主观睡眠指标定义，有心血管疾病和代谢风险因素。

ABSTRACT: Both comparative and single-race studies suggest that sleep disorders are at least as prevalent among American Indians and Alaska Natives (AI/ANs) as they are in the all-races population. Sleep problems are known to be important contributors to chronic disease and early mortality in all populations, while effective treatment of sleep disorders improves the management of diverse health conditions. We propose to conduct an innovative mixed-methods study – American Indian CHronic disEase RIsk and Sleep Health (AI- CHERISH) – to assess the relationship between CVD and metabolic risk and sleep health in the context of Native culture. During the first 2 project years, we will conduct 5 focus groups (15 groups total; 12 participants each) and 2 rounds of semi-structured interviews with 5 key informants (30 interviews total). The resulting qualitative data will inform the development of a patient-reported outcome measure (PROM) of sleep health, to augment established measures accounting for factors specific to Native communities, and culturally-grounded, complementary guidelines for improving sleep. In the quantitative portion of this work, we will implement the largest epidemiologic study of sleep health to date with an AI/AN sample to assess the population prevalence of sleep deficiencies and their association with specific CVD risk factors. Participants in the epidemiologic study were previously enrolled in the Strong Heart Family Study (SHFS). For the epidemiologic study, we will recruit 250 AI participants aged 30–50 years from each geographic region (N=750) and collect sleep data from each participant during 2 study visits in a single 9-month period, with a visit during the months with the longest and shortest daylight exposure (May–July and November–January). For 7 days before each data collection visit, participants will wear wrist actigraphs to measure sleeping and waking activities, and will keep a diary to document waking activities as well as sleep duration, consolidation, and timing. When they return the actigraphs, they will complete 4 validated self-report instruments: the Pittsburgh Sleep Quality Index, the Epworth Sleepiness Scale, the Sleep Hygiene Index, the Insomnia Severity Index, and the STOP-Bang questionnaire. They will also provide data on sociodemographics and on CVD risk factors (blood lipids, hemoglobin A1C, blood pressure, BMI) known to be influenced by sleep. Our Specific Aims are to: 1) Develop a culturally appropriate PROM of sleep health based on the local context affecting sleep at each study site by using focus groups. 2) In key informant interviews, evaluate existing guidelines and elucidate complementary culturally-grounded guidelines for improving sleep health at each study site to augment existing guidelines for AI communities. 3) Estimate the prevalence and nature of sleep deficiencies in a sample of 750 AI adults at 3 study sites by analyzing objective data from actigraphy and subjective data from sleep/wake diaries and standardized sleep instruments collected at 2 time points during a 9-month period. 4) Assess the cross-sectional associations of poor sleep health, as defined by our objective and subjective sleep measures, with CVD and metabolic risk factors.