Characterizing individual differences in the reciprocal relationship between sleep deprivation and binge drinking within the context of college life

摘要 有强有力的证据表明，适应不良的行为，包括不良的睡眠卫生和酗酒， 在大学环境中。当在循环中重复时，习惯发展的风险增加。这可能有助于 成瘾、精神疾病和身体疾病的发展。慢性睡眠剥夺和 频繁过量饮酒会扰乱行为和生理功能， 相互的关于酒精与睡眠关系的个体差异的研究在很大程度上尚未探索，但可能 确定酒精滥用的直接和长期风险的推定生物标志物。这项提案的公共卫生 其重要性源于它有可能减少大学生中与酒精有关的直接伤害， 为改善睡眠和酒精使用障碍患者的生活制定科学前提。提出 研究建立在一项正在进行的大学生纵向研究（R 01 AA 027017）的基础上，使用其参与者， 每周饮酒数据和生理记录它将睡眠与酒精的关系映射到个人 喝酒。它将自我报告的睡眠质量与睡眠行为的客观测量（活动记录）结合起来， 生理学（多导睡眠图）在饮酒回合之前、期间和之后收集。睡眠是 作为一个多维和动态的行为，是可衡量的内部和跨离散 情节。自我报告的酒精使用和后果与心血管反应性测试配对， 客观地评估饮酒的近端生理反应。研究1（n= 150）是一项为期一周的研究， 睡眠持续时间、时间和片段的活动记录研究。目标1侧重于睡眠前的行为， 饮酒事件（即，中毒前），并评估累积的睡眠债务和睡眠不规律如何影响 从自我报告和心血管测量饮酒直接后果的个体差异 反应性目标2针对饮酒事件当晚的睡眠（即，中毒期间），并评估个人 急性酒精对睡眠数量和质量的影响的差异，以及与酒精使用的关联 在接下来的一周和两年中的行为。研究2（n=25）涉及在家过夜 在饮酒后的夜晚和不饮酒后的夜晚进行多导睡眠图检查， 评估睡眠结构（例如，在快速眼动（REM）和慢波睡眠中花费的时间）变化。目的 3探讨了睡眠在恢复过程中是如何改变的（即，醉酒后），如果个人 睡眠生理学的差异涉及睡眠行为和心血管生理学。本申请 通过使用睡眠和酒精使用的多层次评估进行创新;同时收集客观的 数据可能有助于分离自我报告的背景影响。它还创新了多PI设计， 确保在酒精和睡眠领域的专业知识。拟议研究的附加值来自 从产生的密集的、日级的、纵向的数据中，有可能产生二次分析 专注于跨时间的受试者内酒精-睡眠关系的事件水平数据。

Abstract There is strong evidence that maladaptive behaviors, including poor sleep hygiene and binge drinking, emerge in the college environment. When repeated in cycles, risk of habit development increases. This may contribute to the development of addiction, psychiatric illness, and physical disease. Both chronic sleep deprivation and frequent excessive alcohol use disrupt behavioral and physiological functioning, and their relationship appears reciprocal. Research on individual differences in the alcohol-sleep relationship is largely unexplored, but may identify putative biomarkers for immediate and long-term risks of alcohol misuse. This proposal's public health significance stems from its potential to reduce immediate alcohol-related harms in college students and develop scientific premise for improving the lives of individuals with sleep and alcohol use disorders. Proposed studies build from an ongoing longitudinal study of college students (R01 AA027017), using its participants, weekly drinking data, and physiological protocols. It maps the sleep-alcohol relationship onto individual drinking bouts. It pairs self-reported sleep quality with objective measures of sleep behavior (actigraphy) and physiology (polysomnography) that are collected before, during, and after a drinking bout. Sleep is operationalized as a multidimensional and dynamic behavior that is measurable within and across discrete episodes. Self-reported alcohol use and consequences are paired with a cardiovascular reactivity test that objectively assesses proximal physiological repercussions of drinking. Study 1 (n= 150) is a one-week actigraphy study of sleep duration, timing, and fragmentation. Aim 1 focuses on sleep behaviors preceding a drinking event (i.e., pre-intoxication) and assesses how cumulative sleep debt and sleep irregularity influence individual differences in the immediate consequences of drinking measured from self-report and cardiovascular reactivity. Aim 2 targets sleep on the night of a drinking event (i.e., during intoxication) and assesses individual differences in acute alcohol effects on sleep quantity and quality, as well as associations with alcohol use behaviors across the subsequent week and over 2-years. Study 2 (n=25) involves at-home, overnight polysomnography sessions on a night following a drinking night and on a night that does not follow drinking to assess sleep architecture (e.g., time spent in rapid eye movement (REM) and slow-wave sleep) changes. Aim 3 explores how sleep is altered during recovery (i.e., post-intoxication) from drinking and if individual differences in sleep physiology relate to sleep behavior and cardiovascular physiology. This application innovates through its use of multi-level assessments of sleep and alcohol use; concurrently collecting objective data may help dissociate contextual influences on self-report. It also innovates with a multi-PI design that ensures primary expertise in both the alcohol and sleep fields. Added value for the proposed studies comes from the resulting intensive, day-level, longitudinal data that has the potential to generate secondary analyses focused on event-level data of within-subject alcohol-sleep relationships across time.