Association between actigraphic sleep metrics and body composition

Abstract

Purpose Determine if individuals with poor sleep characteristics (i.e., late sleep onset or wake times, short sleep duration, long sleep latency, low sleep efficiency, high wake-after-sleep-onset [WASO]) have greater body mass index (BMI=kg/m2) or body fat. Methods Data for these cross-sectional analyses were from the Energy Balance Study (University of South Carolina). Participants were between 21 and 35 years of age and had a BMI of 20–35 kg/m2. Body fat percent was measured by dual X-ray absorptiometry. Sleep and physical activity were measured by actigraphy (BodyMedia’s SenseWear® physical activity armband). General linear models were used to estimate mean BMI and body fat percent by sleep metric categories. Results Greater BMI and body fat percent were associated with low sleep efficiency (BMI=25.5 vs. 24.8kg/m2, p<0.01; body fat=27.7 vs. 26.5%, p=0.04) and high WASO (BMI=25.6 vs. 25.0 kg/m2, p=0.02; body fat=28.0 vs. 26.7%, p=0.03). Elevated BMI or body fat percent also were observed for later wake times, shorter sleep duration, and longer sleep latency. Sex modified the association between wake times and body composition. Conclusions Understanding the complex relationships between sleep and health outcomes could help reduce chronic disease burden by incorporating sleep components, measured through novel non-invasive techniques (SenseWear® armband), into weight loss interventions.

Hadza sleep biology: Evidence for flexible sleep‐wake patterns in hunter‐gatherers

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Associations between Sleep Quality and Different Measures of Obesity in Saudi Adults

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Tailored lighting intervention for persons with dementia and caregivers living at home

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