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SUBOPTIMAL SLEEP AND ADIPOSITY IN COLLEGE STUDENTS

Abstract

Grace Holmes, Simon Higgins. Elon University, Elon, NC.

BACKGROUND: In adolescents and adults, suboptimal sleep characteristics have been associated with increased adiposity. Several sleep disturbances such as short sleep, and variability in sleep duration, quality, and timing are prevalent among college students due to social and academic pressures that impact sleep hygiene. However, it is unknown whether these sleep characteristics are related to adiposity during a time where excess weight gain is prevalent and which, if any, are most influential. Moreover, the interplay between sleep and lifestyle behaviors such as physical activity (PA) and nutrition are well documented, but it is unclear whether these factors mediate the relationship between sleep characteristics and adiposity. Therefore, our aims are twofold, - first to assess cross-sectional and prospective associations among sleep characteristics and adiposity and second, to perform an exploratory analysis to identify if behavioral variables (e.g., PA and nutrition) might mediate this relationship. METHODS: The sample will include college students aged 18-22 years (n=100, 50% Female) with no history of eating or sleep disorders, no orthopedic injuries preventing physical activity and no use of medications know to alter sleep. Participants will be assessed prospectively over two academic semesters to allow for changes in sleep characteristics relative to changing academic schedules. Anthropometric measurements including height, weight, waist and hip circumference will be collected. Sleep characteristics, diet, and PA will be assessed subjectively using various validated online questionnaires. Sleep, PA, and sedentary behavior will also be assessed objectively using a wrist-worn tri-axial accelerometer for 7 days following each testing visit. Lastly, adiposity will be assessed using Bioelectric Impedance Spectroscopy where fat mass (% and kg) as well as fat free mass (kg) will be collected. The data will be analyzed using linear mixed models including sleep variables and known behavioral covariates. ANTICIPATED REDULTS: We anticipate that sleep characteristics including short sleep duration, night-to-night variability in sleep duration, and sleep timing will be associated with increases in adiposity. Further, we also anticipate that changes in diet such as late-night snacking, decreased PA, or increases in sedentary behavior will mediate the relationship between the sleep variables and adiposity. FUNDING: Funding for this project was provided by Undergraduate Research Program at Elon University.

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