Sleep Health in the Rural South and Its Relationships With Cardiometabolic Health Disparities

Rural communities in the southern U.S. suffer a disproportionate burden of morbidity and mortality from cardiometabolic disease, with traditional risk factors explaining only a modest proportion of the excess burden of disease. Growing evidence implicates poor sleep health as an important risk factor for cardiometabolic disease. While this is most well established for sleep apnea and insomnia, there is considerable evidence that multiple dimensions of sleep health, including sleep duration, efficiency, timing, and regularity, also affect cardiometabolic disease risk. Moreover, rural Southern communities are likely to experience high rates of impaired sleep health, reflecting high levels of psychosocial and environmental stressors, such as financial stress, social isolation, environmental pollution, and poor built environment in addition to high rates of smoking and obesity. However, there is currently a lack of systematically developed sleep data in rural populations.

Recognizing the paucity of research on cardiometabolic risk in this high-risk rural population, the NHLBI recently initiated a new longitudinal epidemiology study in rural Appalachia and Mississippi Delta (the RURAL Study) to identify the complex individual, social and environmental factors contributing to this high burden of disease. The proposed RURAL Sleep Study will complement the RURAL Study by incorporating minimally burdensome measures of multiple dimensions of sleep health at the time of baseline cohort assessment in approximately 4000 adults age 25-64 years, utilizing mobile health technologies to

1. measure sleep apnea over seven consecutive nights;
2. measure sleep duration, timing, regularity and fragmentation over multiple weeks; and
3. administer standardized questionnaires to assess insomnia, chronotype, sleep quality, sleep-related impairment, and fatigue.

These data will allow us to leverage the planned extensive assessments of cardiometabolic risk factors, subclinical disease, and psychosocial and environmental stressors (and resilience factors) to address the following specific aims:

Aim 1a. Quantify population distributions of sleep health measures in a rural cohort along dimensions of sleep apnea, insomnia, chronotype, and sleep duration, efficiency, timing, and regularity.