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.

项目总结