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. 2013 Apr 2;110(14):5695-700.
doi: 10.1073/pnas.1216951110. Epub 2013 Mar 11.

Impact of Insufficient Sleep on Total Daily Energy Expenditure, Food Intake, and Weight Gain

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Impact of Insufficient Sleep on Total Daily Energy Expenditure, Food Intake, and Weight Gain

Rachel R Markwald et al. Proc Natl Acad Sci U S A. .
Free PMC article

Abstract

Insufficient sleep is associated with obesity, yet little is known about how repeated nights of insufficient sleep influence energy expenditure and balance. We studied 16 adults in a 14- to 15-d-long inpatient study and quantified effects of 5 d of insufficient sleep, equivalent to a work week, on energy expenditure and energy intake compared with adequate sleep. We found that insufficient sleep increased total daily energy expenditure by ∼5%; however, energy intake--especially at night after dinner--was in excess of energy needed to maintain energy balance. Insufficient sleep led to 0.82 ± 0.47 kg (±SD) weight gain despite changes in hunger and satiety hormones ghrelin and leptin, and peptide YY, which signaled excess energy stores. Insufficient sleep delayed circadian melatonin phase and also led to an earlier circadian phase of wake time. Sex differences showed women, not men, maintained weight during adequate sleep, whereas insufficient sleep reduced dietary restraint and led to weight gain in women. Our findings suggest that increased food intake during insufficient sleep is a physiological adaptation to provide energy needed to sustain additional wakefulness; yet when food is easily accessible, intake surpasses that needed. We also found that transitioning from an insufficient to adequate/recovery sleep schedule decreased energy intake, especially of fats and carbohydrates, and led to -0.03 ± 0.50 kg weight loss. These findings provide evidence that sleep plays a key role in energy metabolism. Importantly, they demonstrate physiological and behavioral mechanisms by which insufficient sleep may contribute to overweight and obesity.

Conflict of interest statement

Conflict of interest statement: There are no conflicts of interest directly related to this project. L.P. has received speakers fees from Merck. R.H.E. has current funding through a Sanofi research grant (fellowship–education grant), Diadexus, and GlaxoSmithKline, and also serves as a consultant for the following: Amylin, GTC Nutrition, Genfit, Lilly, Pfizer, Johnson & Johnson, and Esperion. Additionally, R.H.E. has financial and/or material support with the following: Cardiometabolic Health Congress, Vindico (honorarium), Metabolic Syndrome Institute, CME Incite (honorarium), Voxmedia (honorarium). K.P.W. serves as a consultant for Takeda Pharmaceuticals and Zeo, Inc. K.P.W. is chair of the Scientific Advisory Board and has stock options at Zeo, Inc. and has received honoraria from Potomac Center for Medical Education, the Associated Professional Sleep Societies, and the National Institutes of Health.

Figures

Fig. 1.
Fig. 1.
Sleep and circadian timing. Average timing of sleep episodes (boxes), melatonin onset (black upward triangles), and melatonin offset (black downward triangles). Error bars are SEM. P values are calculated by mixed model ANOVAs. Melatonin onset significantly delayed in the 5-h condition (P < 0.01 versus BL and 9 h), whereas melatonin offset was similar for conditions (P = 0.77). Durations between melatonin onset and bedtime and between melatonin onset and melatonin offset were similar for conditions (both P > 0.39), whereas duration between melatonin offset and wake time was significantly longer in the 5-h condition (P < 0.001 versus BL and 9 h).
Fig. 2.
Fig. 2.
Effect of sleep loss on energy expenditure, intake, balance, and weight gain. P values calculated by mixed model ANOVAs for condition (Left, n = 16, two-tailed) and planned comparisons for condition by order (Right, n = 8 each order, one-tailed dependent t tests). Error bars are SEM. *Significant difference between 5-h and 9-h conditions (P < 0.05).
Fig. 3.
Fig. 3.
Hourly energy expenditure in the calorimetry room. Energy expenditure expressed as kilocalories per minute on the Left axis and kilojoules per minute on the Right axis relative to scheduled wake time. Gray lines represent low-intensity stepping sessions. Error bars are SEM. P values are calculated by dependent t test with modified Bonferonni correction P < 0.0159. *Significant difference between the 5-h condition and baseline and 9-h conditions; ▲ represents significant difference between the baseline and 5-h and 9-h conditions. In addition to significant effects noted, there was a significant difference between baseline and 9-h conditions at hours awake 9.
Fig. 4.
Fig. 4.
Energy intake of meals. Energy intake for 9-h and 5-h sleep conditions during ad libitum food availability expressed in kilocalories. Error bars are SEM. P values are calculated by mixed model ANOVAs for main effect of condition (n = 16). *Significant difference between 5 h and 9 h (P < 0.05).

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