The obesity epidemic has prompted researchers to find effective weight-loss and maintenance tools. Weight loss and subsequent maintenance are reliant on energy balance—the net difference between ...energy intake and energy expenditure. Negative energy balance, lower intake than expenditure, results in weight loss whereas positive energy balance, greater intake than expenditure, results in weight gain. Resistant starch has many attributes, which could promote weight loss and/or maintenance including reduced postprandial insulinemia, increased release of gut satiety peptides, increased fat oxidation, lower fat storage in adipocytes, and preservation of lean body mass. Retention of lean body mass during weight loss or maintenance would prevent the decrease in basal metabolic rate and, therefore, the decrease in total energy expenditure, that occurs with weight loss. In addition, the fiber-like properties of resistant starch may increase the thermic effect of food, thereby increasing total energy expenditure. Due to its ability to increase fat oxidation and reduce fat storage in adipocytes, resistant starch has recently been promoted in the popular press as a “weight loss wonder food”. This review focuses on data describing the effects of resistant starch on body weight, energy intake, energy expenditure, and body composition to determine if there is sufficient evidence to warrant these claims.
People commonly increase sleep duration on the weekend to recover from sleep loss incurred during the workweek. Whether ad libitum weekend recovery sleep prevents metabolic dysregulation caused by ...recurrent insufficient sleep is unknown. Here, we assessed sleep, circadian timing, energy intake, weight gain, and insulin sensitivity during sustained insufficient sleep (9 nights) and during recurrent insufficient sleep following ad libitum weekend recovery sleep. Healthy, young adults were randomly assigned to one of three groups: (1) control (CON; 9-h sleep opportunities, n = 8), (2) sleep restriction without weekend recovery sleep (SR; 5-h sleep opportunities, n = 14), and (3) sleep restriction with weekend recovery sleep (WR; insufficient sleep for 5-day workweek, then 2 days of weekend recovery, then 2 nights of insufficient sleep, n = 14). For SR and WR groups, insufficient sleep increased after-dinner energy intake and body weight versus baseline. During ad libitum weekend recovery sleep, participants cumulatively slept ∼1.1 h more than baseline, and after-dinner energy intake decreased versus insufficient sleep. However, during recurrent insufficient sleep following the weekend, the circadian phase was delayed, and after-dinner energy intake and body weight increased versus baseline. In SR, whole-body insulin sensitivity decreased ∼13% during insufficient sleep versus baseline, and in WR, whole-body, hepatic, and muscle insulin sensitivity decreased ∼9%–27% during recurrent insufficient sleep versus baseline. Furthermore, during the weekend, total sleep duration was lower in women versus men, and energy intake decreased to baseline levels in women but not in men. Our findings suggest that weekend recovery sleep is not an effective strategy to prevent metabolic dysregulation associated with recurrent insufficient sleep.
•Sleep loss increased after-dinner energy intake and reduced insulin sensitivity•In total, participants slept an extra 1.1 h during weekend recovery versus baseline•After-dinner energy intake was reduced during weekend recovery sleep•Weekend recovery sleep did not prevent weight gain or reduced insulin sensitivity
Weekend recovery sleep is a common sleep-loss countermeasure. Depner et al. show that short sleep led to later timing of energy intake, weight gain, and reduced insulin sensitivity. Weekend recovery sleep failed to prevent later timing of energy intake, weight gain, or reduced insulin sensitivity during recurrent short sleep following the weekend.
Video observations have been widely used for providing ground truth for wearable systems for monitoring food intake in controlled laboratory conditions; however, video observation requires ...participants be confined to a defined space. The purpose of this analysis was to test an alternative approach for establishing activity types and food intake bouts in a relatively unconstrained environment. The accuracy of a wearable system for assessing food intake was compared with that from video observation, and inter-rater reliability of annotation was also evaluated. Forty participants were enrolled. Multiple participants were simultaneously monitored in a 4-bedroom apartment using six cameras for three days each. Participants could leave the apartment overnight and for short periods of time during the day, during which time monitoring did not take place. A wearable system (Automatic Ingestion Monitor, AIM) was used to detect and monitor participants' food intake at a resolution of 30 s using a neural network classifier. Two different food intake detection models were tested, one trained on the data from an earlier study and the other on current study data using leave-one-out cross validation. Three trained human raters annotated the videos for major activities of daily living including eating, drinking, resting, walking, and talking. They further annotated individual bites and chewing bouts for each food intake bout. Results for inter-rater reliability showed that, for activity annotation, the raters achieved an average (±standard deviation (STD)) kappa value of 0.74 (±0.02) and for food intake annotation the average kappa (Light's kappa) of 0.82 (±0.04). Validity results showed that AIM food intake detection matched human video-annotated food intake with a kappa of 0.77 (±0.10) and 0.78 (±0.12) for activity annotation and for food intake bout annotation, respectively. Results of one-way ANOVA suggest that there are no statistically significant differences among the average eating duration estimated from raters' annotations and AIM predictions (
-value = 0.19). These results suggest that the AIM provides accuracy comparable to video observation and may be used to reliably detect food intake in multi-day observational studies.
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.
Significance Demands of modern society force many work operations into the night, when the intrinsic circadian timing system promotes sleep. Overnight shiftwork is associated with increased risk for ...adverse metabolic health and sleep disruption. Uncovering potential physiological mechanisms that contribute to metabolic dysregulation when work and eating occur at inappropriate circadian times is vital to the development of effective treatment strategies. In this study, healthy volunteers underwent a commonly used simulated shiftwork protocol to quantify changes in metabolic, sleep, and circadian physiology when working and eating during the night as compared with a traditional day work schedule. We demonstrate that nightshift work reduces total daily energy expenditure, representing a contributing mechanism for unwanted weight gain and obesity.
Eating at a time when the internal circadian clock promotes sleep is a novel risk factor for weight gain and obesity, yet little is known about mechanisms by which circadian misalignment leads to metabolic dysregulation in humans. We studied 14 adults in a 6-d inpatient simulated shiftwork protocol and quantified changes in energy expenditure, macronutrient utilization, appetitive hormones, sleep, and circadian phase during day versus nightshift work. We found that total daily energy expenditure increased by ∼4% on the transition day to the first nightshift, which consisted of an afternoon nap and extended wakefulness, whereas total daily energy expenditure decreased by ∼3% on each of the second and third nightshift days, which consisted of daytime sleep followed by afternoon and nighttime wakefulness. Contrary to expectations, energy expenditure decreased by ∼12–16% during scheduled daytime sleep opportunities despite disturbed sleep. The thermic effect of feeding also decreased in response to a late dinner on the first nightshift. Total daily fat utilization increased on the first and second nightshift days, contrary to expectations, and carbohydrate and protein utilization were reduced on the second nightshift day. Ratings of hunger were decreased during nightshift days despite decreases in 24-h levels of the satiety hormones leptin and peptide-YY. Findings suggest that reduced total daily energy expenditure during nightshift schedules and reduced energy expenditure in response to dinner represent contributing mechanisms by which humans working and eating during the biological night, when the circadian clock is promoting sleep, may increase the risk of weight gain and obesity.
Accurate and objective assessment of energy intake remains an ongoing problem. We used features derived from annotated video observation and a chewing sensor to predict mass and energy intake during ...a meal without participant self-report. 30 participants each consumed 4 different meals in a laboratory setting and wore a chewing sensor while being videotaped. Subject-independent models were derived from bite, chew, and swallow features obtained from either video observation or information extracted from the chewing sensor. With multiple regression analysis, a forward selection procedure was used to choose the best model. The best estimates of meal mass and energy intake had (mean ± standard deviation) absolute percentage errors of 25.2% ± 18.9% and 30.1% ± 33.8%, respectively, and mean ± standard deviation estimation errors of -17.7 ± 226.9 g and -6.1 ± 273.8 kcal using features derived from both video observations and sensor data. Both video annotation and sensor-derived features may be utilized to objectively quantify energy intake.
Obesity and adult weight gain are linked to increased breast cancer risk and poorer clinical outcomes in postmenopausal women, particularly for hormone-dependent tumors. Menopause is a time when ...significant weight gain occurs in many women, and clinical and preclinical studies have identified menopause (or ovariectomy) as a period of vulnerability for breast cancer development and promotion.
We hypothesized that preventing weight gain after ovariectomy (OVX) may be sufficient to prevent the formation of new tumors and decrease growth of existing mammary tumors. We tested this hypothesis in a rat model of obesity and carcinogen-induced postmenopausal mammary cancer and validated our findings in a murine xenograft model with implanted human tumors.
In both models, preventing weight gain after OVX significantly decreased obesity-associated tumor development and growth. Importantly, we did not induce weight loss in these animals, but simply prevented weight gain. In both lean and obese rats, preventing weight gain reduced visceral fat accumulation and associated insulin resistance. Similarly, the intervention decreased circulating tumor-promoting growth factors and inflammatory cytokines (i.e., BDNF, TNFα, FGF-2), with greater effects in obese compared to lean rats. In obese rats, preventing weight gain decreased adipocyte size, adipose tissue macrophage infiltration, reduced expression of the tumor-promoting growth factor FGF-1 in mammary adipose, and reduced phosphorylated FGFR indicating reduced FGF signaling in tumors.
Together, these findings suggest that the underlying mechanisms associated with the anti-tumor effects of weight maintenance are multi-factorial, and that weight maintenance during the peri-/postmenopausal period may be a viable strategy for reducing obesity-associated breast cancer risk and progression in women.
PURPOSE OF REVIEWResistant starch represents a diverse range of indigestible starch-based dietary carbohydrates. Resistant starch has been investigated in the past for its effects on bowel health ...(pH, epithelial thickness, and apoptosis of colorectal cancer cells); reduction in postprandial glycemia; increased insulin sensitivity; and effects on the gut microbiome. This review highlights advances as resistant starch gains clinical relevance as a potential treatment/preventive tool for diseases such as colorectal cancer (CRC) and diabetes.
RECENT FINDINGSRecent articles have evaluated the comparative physiological effects of different types of resistant starch and investigated the effects of resistant starch on blood lipids, body weight, and defining resistant starch-induced changes to the micriobiome that may be important in health and disease. The most novel and relevant recent data describe a role for resistant starch in ameliorating inflammation; the use of resistant starch for optimal bowel health and prevention of CRC; and, further, that the systemic effects of resistant starch may be important for the treatment of other forms of cancer, such as breast cancer.
SUMMARYThis review describes advances in resistant starch research highlighting the gastrointestinal effects that are now being linked to systemic, whole body effects with clinical relevance. These effects have important implications for overall health and the prevention or amelioration of various chronic diseases.
Short sleep duration and circadian misalignment are hypothesized to causally contribute to health problems including obesity, diabetes, metabolic syndrome, heart disease, mood disorders, cognitive ...impairment, and accidents 1–7. Here, we investigated the influence of morning circadian misalignment induced by an imposed short nighttime sleep schedule on impaired insulin sensitivity, a precursor to diabetes. Imposed short sleep duration resulted in morning wakefulness occurring during the biological night (i.e., circadian misalignment)—a time when endogenous melatonin levels were still high indicating the internal circadian clock was still promoting sleep and related functions. We show the longer melatonin levels remained high after wake time, insulin sensitivity worsened. Overall, we find a simulated 5-day work week of 5-hr-per-night sleep opportunities and ad libitum food intake resulted in ∼20% reduced oral and intravenous insulin sensitivity in otherwise healthy men and women. Reduced insulin sensitivity was compensated by an increased insulin response to glucose, which may reflect an initial physiological adaptation to maintain normal blood sugar 8 levels during sleep loss. Furthermore, we find that transitioning from the imposed short sleep schedule to 9-hr sleep opportunities for 3 days restored oral insulin sensitivity to baseline, but 5 days with 9-hr sleep opportunities was insufficient to restore intravenous insulin sensitivity to baseline. These findings indicate morning wakefulness and eating during the biological night is a novel mechanism by which short sleep duration contributes to metabolic dysregulation and suggests food intake during the biological night may contribute to other health problems associated with short sleep duration.
•Short sleep and associated circadian misalignment reduces insulin sensitivity•Reduced insulin sensitivity was compensated by increased insulin secretion•3 days adequate sleep restored oral glucose insulin sensitivity to baseline•Circadian timing of food intake during sleep loss may elevate diabetes risk
Short sleep duration is associated with elevated diabetes risk. Eckel et al. provide evidence showing short sleep results in morning wakefulness during the biological night (i.e., circadian misalignment). Such circadian misalignment was associated with lower insulin sensitivity, indicating a novel way by which short sleep may elevate diabetes risk.
ObjectivesDietary assessment methods not relying on self-report are needed. The Automatic Ingestion Monitor 2 (AIM-2) combines a wearable camera that captures food images with sensors that detect ...food intake. We compared energy intake (EI) estimates of meals derived from AIM-2 chewing sensor signals, AIM-2 images, and an internet-based diet diary, with researcher conducted weighed food records (WFR) as the gold standard.Subjects/MethodsThirty adults wore the AIM-2 for meals self-selected from a university food court on one day in mixed laboratory and free-living conditions. Daily EI was determined from a sensor regression model, manual image analysis, and a diet diary and compared with that from WFR. A posteriori analysis identified sources of error for image analysis and WFR differences.ResultsSensor-derived EI from regression modeling (R2 = 0.331) showed the closest agreement with EI from WFR, followed by diet diary estimates. EI from image analysis differed significantly from that by WFR. Bland–Altman analysis showed wide limits of agreement for all three test methods with WFR, with the sensor method overestimating at lower and underestimating at higher EI. Nutritionist error in portion size estimation and irreconcilable differences in portion size between food and nutrient databases used for WFR and image analyses were the greatest contributors to image analysis and WFR differences (44.4% and 44.8% of WFR EI, respectively).ConclusionsEstimation of daily EI from meals using sensor-derived features offers a promising alternative to overcome limitations of self-report. Image analysis may benefit from computerized analytical procedures to reduce identified sources of error.
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