Enhanced Measurement and Modeling of Sleep Electrophysiology to Better Understand Sleep Disparities

增强睡眠电生理学测量和建模，以更好地了解睡眠差异

• 批准号: 10020195
• 负责人: Shaun M Purcell
• 金额: $ 21.68万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-17 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10020195
• 关键词: African American; Age; Attenuated; Circadian Rhythms; Cognitive; Communities; Complement; Complex; Coupling; Data; Data Science; Development; Disease; Electrophysiology (science); Ethnic Origin; Ethnic group; Family; Frequencies; Gender; Health; Individual; Individual Differences; Inherited; Intervention; Life Cycle Stages; Life Style; Link; Machine Learning; Measurement; Measures; Mediating; Mediator of activation protein; Mental Health; Methods; Modeling; Nature; Outcome; Patient Self-Report; Pharmaceutical Preparations; Phenotype; Physiological; Polysomnography; Positioning Attribute; Process; Public Health; Race; Records; Reporting; Research; Research Personnel; Resources; Role; Sampling; Signal Transduction; Sleep; Sleep Architecture; Sleep disturbances; Slow-Wave Sleep; Social Environment; Socioeconomic Status; Techniques; Testing; United States; Ursidae Family; Variant; age effect; age related; allostatic load; analytical method; attenuation; base; behavioral pharmacology; cardiovascular disorder risk; causal model; cohort; computational neuroscience; contextual factors; demographics; density; ethnic difference; ethnic health disparity; ethnic minority population; gender difference; genetic makeup; health disparity; healthy aging; improved; indexing; lifestyle factors; novel; physical conditioning; physical state; population health; primary outcome; psychosocial; racial and ethnic; racial and ethnic disparities; racial difference; racial minority; sex; signal processing; sleep behavior; sleep pattern; sleep physiology; sleep quality; sleep quantity; sleep spindle; social; social disparities; socioeconomics; trait

Project Summary Health disparities associated with race and ethnicity are a major public health issue in the United States. Multiple lines of evidence suggest that differences in people's quality and quantity of sleep may account for part of this problem. Here we wish to study patterns of sleep, using full polysomnography data in a large and diverse cohort, to better understand what causes some individuals and groups to differ in their typical sleep, and to link this variation in sleep to relevant health outcomes. In order to study sleep as a mediator of health disparities associated with race/ethnicity, we propose to first unpack the “sleep” term into profiles of quantitative traits (Aim 1). Second, we will test for demographic moderators of the associations between race/ethnicity and sleep traits, which can point to likely socioeconomic and social/environmental contextual mediators (Aim 2). Finally, we will demonstrate the relevance of these findings by testing for association with health outcomes – primarily cardiovascular disease risk and measures of allostatic load – and estimating the extent to which sleep accounts for racial/ethnic health disparities (Aim 3). We will apply a targeted array of data-driven analytic methods, from data science, machine learning, computational neuroscience and causal modeling, to characterize individual differences in patterns of sleep. A more nuanced understanding of what constitutes “poor sleep” is important because different aspects of sleep are likely to have qualitatively different links to demographic and biomedical factors, including age, sex, lifestyle factors, inherited genetic makeup, circadian rhythms, medication effects and current state of physical and mental health. By disentangling this network of inter-related variables, we will be better positioned to understand – and ameliorate – the effects of the numerous factors that can induce racial/ethnic disparities in sleep, and consequently, in health too.

项目概要 与种族和民族相关的健康差异是美国的一个主要公共卫生问题 多项证据表明，人们的睡眠质量和数量可能存在差异。 在这里，我们希望使用完整的多导睡眠图来研究睡眠模式。 大量且多样化的群体中的数据，以更好地了解导致某些个人和群体的原因 他们的典型睡眠有所不同，并将这种睡眠差异与相关的健康结果联系起来。 为了研究睡眠作为与种族/民族相关的健康差异的中介因素，我们建议 首先将“睡眠”术语分解为数量性状（目标 1）。 种族/民族与睡眠特征之间关联的人口统计学调节因素，这可以指出 可能的社会经济和社会/环境背景中介（目标 2）。 通过测试与健康结果的关联来证明这些发现的相关性——主要是 心血管疾病风险和非稳态负荷测量——以及估计睡眠程度 解释种族/民族健康差异（目标 3）。 我们将应用一系列有针对性的数据驱动分析方法，包括数据科学、机器学习、 计算神经科学和因果模型，以表征个体差异模式 更细致地了解什么是“睡眠质量差”很重要，因为不同的情况。 睡眠的各个方面可能与人口和生物医学因素有着本质上不同的联系， 包括年龄、性别、生活方式因素、遗传基因构成、昼夜节律、药物作用 通过理清这个相互关联的变量网络， 我们将能够更好地理解并改善众多因素的影响 可能会导致睡眠方面的种族/民族差异，从而导致健康方面的差异。