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VOLUME 32, ISSUE 04

SLEEP ARCHITECTURE AND BODY COMPOSITION
Association Between Sleep Architecture and Measures of Body Composition

Madhu N. Rao, MD1; Terri Blackwell, MA2; Susan Redline, MD, MPH3; Marcia L. Stefanick, PhD4; Sonia Ancoli-Israel, PhD5; Katie L. Stone, PhD2; for the Osteoporotic Fractures in Men (MrOS) Study Group

1Division of Endocrinology, University of California San Francisco, San Francisco, CA; 2Research Institute, California Pacific Medical Center, San Francisco, CA; 3Case Western Reserve University, Cleveland, OH; 4Stanford Prevention Research Center, Department of Medicine, Stanford University, Palo Alto, CA; 5Department of Psychiatry, University of California, San Diego, San Diego, CA



 
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Study Objectives: To determine whether slow wave sleep (SWS) is inversely associated with body mass index (BMI) and other measures of body composition.
Design: Cross-sectional, observational study.
Setting: Community-based.
Participants: 2745 older men from the MrOS Sleep Study who completed polysomnography.
Interventions: N/A
Measurements and Results: SWS as a percentage of total sleep duration was obtained from in-home, overnight polysomnography. Measures of body composition including BMI, weight, waist circumference and total body fat mass were determined by standard techniques. Other covariates in the analysis were age, race/ethnicity, clinic site, physical activity, respiratory disturbance index (RDI), total sleep time, and sleep efficiency. In the multivariate analysis, there was a significant inverse association between quartiles of SWS and BMI (P-trend = 0.0095). Older men in the lowest quartile of SWS had an average BMI of 27.4 kg/m2, compared to 26.8 for those in the highest quartile of SWS. This association was attenuated in men with RDI ≥ 15. Furthermore, participants in the lowest quartile of SWS had a 1.4-fold increased odds for obesity (P = 0.03, 95% CI 1.0, 1.8) compared to those in the highest quartile. A similar inverse association between SWS and waist circumference as well as weight was observed. REM sleep was not associated with measures of body composition.
Conclusions: Independent of sleep duration, percentage time in SWS is inversely associated with BMI and other measures of body composition in this population of older men. Participants in the lowest quartile of SWS (compared to those in the highest quartile) are at increased risk for obesity.
Keywords: slow wave sleep, obesity, weight, body composition, sleep architecture
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