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.calorimetry | misalignment | dysregulated eating | deprivation | restriction M ore than 1.4 billion adults, 150 million school-aged children, and 43 million preschool children are estimated to be overweight or obese worldwide (1-3), substantially raising risk for cardiovascular diseases (4) hyperlipidemia (5), diabetes (5, 6), osteoarthritis (6), sleep apnea (7), depression (8), and cancer (9). Excessive food consumption and inadequate physical activity are primary factors contributing to the obesity epidemic. When daily energy intake is in excess of energy expenditure (EE) a state of positive energy balance occurs. Over weeks, months, or years, a small cumulative impact of sustained positive energy balance results in weight gain and obesity (10). Alongside the rise in obesity there has been a decline in the number of individuals who report obtaining the recommended 7-9 h of sleep, with many obtaining less than 6 h per night (11). Insufficient sleep is a risk factor of weight gain and obesity (11-13), yet how insufficient sleep contributes to this risk is unclear. Sleep influences energy metabolism (14, 15), and one function of sleep is to conserve energy (16). Proposed mechanisms that associate insufficient sleep and higher body mass index (BMI) include changes in satiety and hunger hormones altering food intake and changes in EE (17). Insufficient sleep is associated with decreases...

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Abbreviations: A1C = hemoglobin A1C; AACE = American Association of Clinical Endocrinologists; ABCD = adiposity-based chronic disease; ACCORD = Action to Control Cardiovascular Risk in Diabetes; ACCORD BP = Action to Control Cardiovascular Risk in Diabetes Blood Pressure; ACE = American College of Endocrinology; ACEI = angiotensin-converting enzyme inhibitor; AGI = alpha-glucosidase inhibitor; apo B = apolipoprotein B; ARB = angiotensin II receptor blocker; ASCVD = atherosclerotic cardiovascular disease; BAS = bile acid sequestrant; BMI = body mass index; BP = blood pressure; CCB = calcium channel blocker; CGM = continuous glucose monitoring; CHD = coronary heart disease; CKD = chronic kidney disease; DKA = diabetic ketoacidosis; DPP4 = dipeptidyl peptidase 4; eGFR = estimated glomerular filtration rate; EPA = eicosapentaenoic acid; ER = extended release; FDA = Food and Drug Administration; GLP1 = glucagon-like peptide 1; HDL-C = high-density-lipoprotein cholesterol; HeFH = heterozygous familial hypercholesterolemia; LDL-C = low-density-lipoprotein cholesterol; LDL-P = low-density-lipoprotein particle; Look AHEAD = Look Action for Health in Diabetes; NPH = neutral protamine Hagedorn; OSA = obstructive sleep apnea; PCSK9 = proprotein convertase subtilisin-kexin type 9 serine protease; RCT = randomized controlled trial; SU = sulfonylurea; SGLT2 = sodium-glucose cotransporter 2; SMBG = self-monitoring of blood glucose; T2D = type 2 diabetes; TZD = thiazolidinedione

Background Our objective was to quantify and predict diabetes risk reduction during the Diabetes Prevention Program Outcomes Study (DPPOS) among those who returned to normal glucose regulation (NGR) at least once during DPP compared to those who were consistently considered to have pre-diabetes. Methods Diabetes cumulative incidence in DPPOS was calculated for subjects with NGR or pre-diabetes status during DPP with and without stratification by prior randomized treatment group. Cox proportional hazards modeling and generalized linear mixed models were used to quantify the impact of previous (DPP) glycemic status on risk of later (DPPOS) diabetes and NGR status, respectively, per standard deviation in change. Included in this analysis are 1990 participants of DPPOS (who had been randomized during DPP: N=736 in intensive lifestyle (ILS), N=647 to metformin (MET), and N=607 to placebo (PLB)). Findings Diabetes risk during DPPOS was 56% lower in NGR vs. pre-diabetes (HR=0.44, 95% CI 0.37-0.55, p<0.0001) and was unaffected by prior group assignment (interaction test for NGR*ILS, p=0.1722; NGR*MET, p=0.3304). Many, but not all, of the variables that increased diabetes risk were inversely associated with the chance of reaching NGR status in DPPOS. Specifically, having had prior NGR (OR=3.18, 95% CI 2.71-3.72, p<0.0001), higher β-cell function (OR=1.28; 95% CI 1.18-1.39, p<0.0001) and insulin sensitivity (OR=1.16, 95% CI 1.08-1.25, p<0.0001) were associated with NGR in DPPOS, whereas the opposite was true for predicting diabetes (HR=0.80, 95% CI 0.71-0.89; HR=0.83, 95% CI 0.74-0.94, respectively, p<0.0001 for both). Surprisingly, among subjects who failed to return to NGR in DPP, those randomized to ILS had a higher diabetes risk (HR=1.31, 95% CI 1.03-1.68, p=0.0304) and lower chance of NGR (OR=0.59, 95% CI 0.42-0.82, p=0.0014) vs. placebo in DPPOS. Interpretation We conclude that pre-diabetes represents a high-risk state for diabetes, especially among those who remain so despite ILS. Reversion to NGR, even if transient, is associated with a significantly lower risk of future diabetes independent of prior treatment group.

Sleep has been proposed to be a physiological adaptation to conserve energy, but little research has examined this proposed function of sleep in humans. We quantified effects of sleep, sleep deprivation and recovery sleep on whole-body total daily energy expenditure (EE) and on EE during the habitual day and nighttime. We also determined effects of sleep stage during baseline and recovery sleep on EE. Seven healthy participants aged 22 ± 5 years (mean ± s.d.) maintained ∼8 h per night sleep schedules for 1 week before the study and consumed a weight-maintenance diet for 3 days prior to and during the laboratory protocol. Following a habituation night, subjects lived in a whole-room indirect calorimeter for 3 days. The first 24 h served as baseline – 16 h wakefulness, 8 h scheduled sleep – and this was followed by 40 h sleep deprivation and 8 h scheduled recovery sleep. Findings show that, compared to baseline, 24 h EE was significantly increased by ∼7% during the first 24 h of sleep deprivation and was significantly decreased by ∼5% during recovery, which included hours awake 25–40 and 8 h recovery sleep. During the night time, EE was significantly increased by ∼32% on the sleep deprivation night and significantly decreased by ∼4% during recovery sleep compared to baseline. Small differences in EE were observed among sleep stages, but wakefulness during the sleep episode was associated with increased energy expenditure. These findings provide support for the hypothesis that sleep conserves energy and that sleep deprivation increases total daily EE in humans.

OBJECTIVEOver 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes–associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP).RESEARCH DESIGN AND METHODSWe genotyped 34 type 2 diabetes–associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment.RESULTSIn multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00–1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93–0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in β-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001).CONCLUSIONSA high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk.

National Institutes of Health General Clinical Research Center (RR-00036), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (R01DK089170), NIDDK (T32 DK07658), and Colorado Nutrition Obesity Research Center (P30DK048520).

OBJECTIVEParticipants in the Diabetes Prevention Program (DPP) randomized to intensive lifestyle modification (ILS) or metformin had a significantly reduced incidence of diabetes compared with those randomized to placebo, yet most were still at risk because they had pre-diabetes. We explored the effect of baseline characteristics, weight change, ILS, and metformin on regression from pre-diabetes to the lowest-risk state of normal glucose regulation (NGR) defined by American Diabetes Association criteria.RESEARCH DESIGN AND METHODSThe DPP was a prospective randomized trial. Cox proportional hazards modeling was used to identify predictors of regression from pre-diabetes to NGR over 3 years of follow-up.RESULTSLower baseline fasting (hazard ratio 1.52, P < 0.01) and 2-h (1.24, P < 0.01) glucose predicted regression to NGR, as did younger age (1.07, P < 0.01) and greater insulin secretion (1.09, P = 0.04). ILS (2.05, P < 0.01) and weight loss (1.34, P < 0.01) had significant and independent effects on regression. A nonsignificant trend for regression was also observed for metformin (1.25, P = 0.06), male sex (1.17, P = 0.08), and insulin sensitivity (1.07, P = 0.09). In those entering the study with both impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), male sex and insulin sensitivity predicted regression to isolated IFG, whereas ILS, metformin, female sex, and greater insulin secretion predicted regression to isolated IGT.CONCLUSIONSInsulin secretion, and other biologic processes retained with younger age, are key in restoring NGR in people with pre-diabetes. However, NGR may also be attained through weight loss and additional aspects of ILS.