Modeling Risk Factors for Sleep- and Adiposity-Related Cardiometabolic Disease: Protocol for the Short Sleep Undermines Cardiometabolic Health (SLUMBRx) Observational Study

Abstract

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Obesity and short sleep duration are significant public health issues. Current evidence suggests these conditions are associated with cardiovascular disease, metabolic syndrome, inflammation, and premature mortality. Increased interest in the potential link between obesity and short sleep duration, and its health consequences, has been driven by: 1) the apparent parallel increase in prevalence of both conditions in recent decades; 2) their overlapping association with cardiometabolic outcomes; and 3) the potential causal connection between the two health issues. The Short Sleep Undermines Cardiometabolic Health (SLUMBRx) Study seeks to contribute to the development of a comprehensive adiposity-sleep model, while laying the groundwork for a future program of research that will be designed to prevent and treat adiposity and sleep-related cardiometabolic disease risk factors. Objective: SLUMBRx addresses four topics pertinent to the adiposity-sleep hypothesis: 1) the relationship between adiposity and sleep duration; 2) sex-based differences in the relationship between adiposity and sleep duration; 3) influence of adiposity indices and sleep duration on cardiometabolic outcomes; and 4) the role of socioecological factors as effect modifiers in the relationship between adiposity indices, sleep, and cardiometabolic outcomes. Methods: SLUMBRx will employ a large-scale survey (n=1,000) that recruits 159 participants (53 normal weight, 53 overweight, and 53 obese) to be assessed in two phases. Results: Phase 1, a lab-based study, will gather objective adiposity indices (air displacement plethysmography and anthropometrics) and cardiometabolic data (blood pressure, pulse wave velocity and pulse wave analysis, and blood-based biomarker). Phase 2, a one-week, home-based study, will gather sleep-related data (home sleep testing/sleep apnea, actigraphy, sleep diaries). During Phase 2, detailed demographic and socioecological data will be collected to contextualize hypothesized adiposity and sleep-associated cardiometabolic disease risk factors. Collection and analyses of these data will yield information necessary to customize future observational and intervention research. Conclusions: Precise implementation of the SLUMBRx protocol promises to provide objective, empirical data on the interaction between body composition and sleep duration. The hypotheses that will be tested by SLUMBRx are important for understanding the pathogenesis of cardiometabolic disease and for developing future public health interventions to prevent its conception and treat its consequences.