Association Between Sleep Architecture And Measures of Body Composition

Prevalence of Obesity has doubled within the USA over the course of recent decades, during this same time frame self reported sleep duration has also decreased.

It is now estimated that less than one quarter of adults sleep at least 8 hours each day, and there are numerous epidemiologic studies suggesting associations between total sleep time and the risks of obesity. BMI has been shown to increase as total sleep duration decreases, but few studies have investigated and assessed relationships between sleep architecture and BMI.

Two distinct processes regulate sleep: circadian processes driven by an endogenous pacemaker; and a homeostatic process depending on the amount of prior sleep and wakefulness. Slow wave sleep is the deepest stage with the highest arousal threshold among the various stages of sleep, and is thought to be important for consolidation of memory. Roles of slow wave sleep in metabolism and energy conservations is not fully understood in humans as most studies have yielded inconsistent results.

To determine whether slow wave sleep is universally associated with BMI and other measures of body compositions researchers conducted a community based, cross sectional, observational study involving a cohort of 2745 older men from the MrOS Sleep Study who had completed polysomnography. Secondary goal of the study was to determine where REM sleep is associated with measures of body composition independent of other confounding factors.

Slow wave sleep as a percentage of total sleep duration was obtained from home overnight polysomnography. Measure of body composition included weight, BMI, waist circumference, and total body fat mass. Other covariates in analysis included physical activity, clinic site, age, race/ethnicity, sleep efficiency, total sleep time, and respiratory disturbance index.

The multivariate analysis showed significant inverse association between quartiles of SWS and BMI (P-trend=0.0095); older men in the lowest quartile of SWS were found to have an average BMI of 27.4kg/m2; those in the highest were 26.8kg/m2. The association was attenuated in men with RDI ≥ 15. Subjects in the lowest quartile of SWS had 1.4 times increased odds for obesity (P=0.03, 95% CI 1.0, 1.8). Similar inverse associations were found between SWS and waist circumference and weight; REM was not associated with measures of body composition.

Increased amounts of slow wave sleep were associated with younger age, lower RDI, longer TST, greater sleep efficiency, more physical activity. Comorbidities such as smoking status and central apnea index were not associated with SWS. Covariates associated with REM sleep included age, physical activity, TST, RDI, sleep efficiency, and comorbid conditions. RDI, age, and comorbid conditions were inversely associated with REM sleep, while TST, sleep efficiency, and physical activity were associated positively. After adjusting for several factors SWS was significantly associated with BMI.

The study had limitations such as the participants were predominantly caucasian men with a mean age of 76 years, nearly 73% had one or more comorbidities including CVD, hypertension, diabetes, and chronic lung disease. Due to self reporting on sleep at home and the observational nature of this study no firm conclusions can be made about causal effect.

The researchers were confident in their findings suggesting independent of sleep duration the percentage of time in slow wave sleep is inversely associated with BMI and other measures of body composition among this population of older male subjects; subjects in the lowest quartile of slow wave sleep are at increased risk for obesity.