Accepted for/Published in: JMIR Formative Research
Date Submitted: Feb 27, 2024
Date Accepted: Sep 24, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Cardiometabolic Disease Risk Factors are Associated with Sleep Duration and Obstructive Sleep Apnea in a Southeastern U.S. Community Sample: Early Findings from the SLUMBRx Study
ABSTRACT
Background:
Short sleep and obstructive sleep apnea (OSA) are underrecognized strains on the public health infrastructure. In the United States (U.S.), over 35% of adults report short sleep and more than 80% of individuals with OSA remain undiagnosed. The prevalence of inadequate sleep tracks closely with estimated rates of obesity, hypertension, and pre-diabetes among U.S. adults; 30.7%, 48.1%, and 38.0%, respectively. Although the relationship between inadequate sleep and risk factors for cardiometabolic disease has garnered increased attention, challenges persist in modeling these associations.
Objective:
To report early findings from the Short Sleep Undermines Cardiometabolic Health (SLUMBRx) observational cohort study.
Methods:
Data for the SLUMBRx study were collected cross-sectionally and longitudinally from a non-clinical, community sample (n=47) in the southeast U.S. Measures included sleep duration assessed through wrist-based actigraphy (e.g., mean of seven consecutive nights of total sleep time [TST7N]), one-night sleep apnea home testing (e.g., apnea-hypopnea index [AHI]), and cross-sectional collection of anthropometric (e.g., body mass index [BMI]), cardiovascular (e.g., blood pressure [BP]), and blood-based biomarkers (e.g., triglycerides [TRG] and glucose [GLU]). Correlations between the sleep and cardiometabolic indices were calculated. Significant associations were entered into regression models to investigate the relationship between sleep duration (e.g., TST7N) and OSA (e.g., AHI) and the significant cardiometabolic covariates.
Results:
Although no relationship was observed between BMI and TST7N (P = .401) or BMI and AHI (P = .817), a significant association was identified between diastolic BP (DBP) and TST7N (ρ = 0.337, P = .016). Additionally, triglycerides ([TRG] ρ= 0.289, P = .049) and glucose ([GLU] ρ = 0.338, P = .020) emerged as significant correlates of AHI. The regression model examining sleep duration revealed that DBP (β = 0.335; P = .021) explained 9.2% of the variance in TST7N (R2adjusted = 0.092; F1, 45 = 5.676, P = .021). The regression model investigating OSA found TRG (β = 0.265; P = .049) and GLU (β = 0.401; P = .004) explained 21.4% of the variance in AHI (R2adjusted = 0.214; F2, 44 = 7.245, P = .002).
Conclusions:
Results from the SLUMBRx study highlight the complex interplay between sleep indices and risk factors for cardiometabolic disease. Early findings underscore the need for further investigations incorporating the collection of clinical, epidemiological, and ambulatory measures to inform interventions addressing the cardiometabolic consequences of inadequate sleep. Clinical Trial: 1K01HL145128-01A1
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.