Food consumption is thought to induce sleepiness. However, little is known about how postprandial sleep is regulated. Here, we simultaneously measured sleep and food intake of individual flies and found a transient rise in sleep following meals. Depending on the amount consumed, the effect ranged from slightly arousing to strongly sleep inducing. Postprandial sleep was positively correlated with ingested volume, protein, and salt-but not sucrose-revealing meal property-specific regulation. Silencing of leucokinin receptor (Lkr) neurons specifically reduced sleep induced by protein consumption. Thermogenetic stimulation of leucokinin (Lk) neurons decreased whereas Lk downregulation by RNAi increased postprandial sleep, suggestive of an inhibitory connection in the Lk-Lkr circuit. We further identified a subset of non-leucokininergic cells proximal to Lkr neurons that rhythmically increased postprandial sleep when silenced, suggesting that these cells are cyclically gated inhibitory inputs to Lkr neurons. Together, these findings reveal the dynamic nature of postprandial sleep.
BACKGROUND: Misreporting food intake is common because most health screenings rely on self-reports. The more accurate methods (eg, weighing food) are costly, time consuming, and impractical. OBJECTIVES: We developed a new instrument for reporting food intake-an Internet-based interactive virtual food plate. The objective of this study was to validate this instrument’s ability to assess lunch intake. METHODS: Participants were asked to compose an ordinary lunch meal using both a virtual and a real lunch plate (with real food on a real plate). The participants ate their real lunch meals on-site. Before and after pictures of the composed lunch meals were taken. Both meals included identical food items. Participants were randomized to start with either instrument. The 2 instruments were compared using correlation and concordance measures (total energy intake, nutritional components, quantity of food, and participant characteristics). RESULTS: A total of 55 men (median age: 45 years, median body mass index [BMI]: 25.8 kg/m(2)) participated. We found an overall overestimation of reported median energy intake using the computer plate (3044 kJ, interquartile range [IQR] 1202 kJ) compared with the real lunch plate (2734 kJ, IQR 1051 kJ, P<.001). Spearman rank correlations and concordance correlations for energy intake and nutritional components ranged between 0.58 to 0.79 and 0.65 to 0.81, respectively. CONCLUSION: Although it slightly overestimated, our computer plate provides promising results in assessing lunch intake.
Background:There is emerging literature demonstrating a relationship between the timing of feeding and weight regulation in animals. However, whether the timing of food intake influences the success of a weight-loss diet in humans is unknown.Objective:To evaluate the role of food timing in weight-loss effectiveness in a sample of 420 individuals who followed a 20-week weight-loss treatment.Methods:Participants (49.5% female subjects; age (mean±s.d.): 42±11 years; BMI: 31.4±5.4 kg m(-2)) were grouped in early eaters and late eaters, according to the timing of the main meal (lunch in this Mediterranean population). 51% of the subjects were early eaters and 49% were late eaters (lunch time before and after 1500 hours, respectively), energy intake and expenditure, appetite hormones, CLOCK genotype, sleep duration and chronotype were studied.Results:Late lunch eaters lost less weight and displayed a slower weight-loss rate during the 20 weeks of treatment than early eaters (P=0.002). Surprisingly, energy intake, dietary composition, estimated energy expenditure, appetite hormones and sleep duration was similar between both groups. Nevertheless, late eaters were more evening types, had less energetic breakfasts and skipped breakfast more frequently that early eaters (all; P<0.05). CLOCK rs4580704 single nucleotide polymorphism (SNP) associated with the timing of the main meal (P=0.015) with a higher frequency of minor allele (C) carriers among the late eaters (P=0.041). Neither sleep duration, nor CLOCK SNPs or morning/evening chronotype was independently associated with weight loss (all; P>0.05).Conclusions:Eating late may influence the success of weight-loss therapy. Novel therapeutic strategies should incorporate not only the caloric intake and macronutrient distribution-as is classically done-but also the timing of food.International Journal of Obesity advance online publication, 29 January 2013; doi:10.1038/ijo.2012.229.
OBJECTIVE: Few studies examined the association between time-of-day of nutrient intake and the metabolic syndrome. Our goal was to compare a weight loss diet with high caloric intake during breakfast to an isocaloric diet with high caloric intake at dinner. DESIGN AND METHODS: Overweight and obese women (BMI 32.4±1.8 kg/m(2) ) with metabolic syndrome were randomized into two isocaloric (∼1400kcal) weight loss groups, a breakfast (BF) (700kcal breakfast, 500kcal lunch, 200kcal dinner) or a dinner (D) group (200kcal breakfast, 500kcal lunch, 700kcal dinner) for 12 weeks. RESULTS: The BF group showed greater weight loss and waist circumference reduction. Although fasting glucose, insulin and ghrelin were reduced in both groups, fasting glucose, insulin and HOMA-IR decreased significantly to a greater extent in the BF group. Mean triglyceride levels decreased by 33.6% in the BF group, but increased by 14.6% in the D group. Oral glucose tolerance test led to a greater decrease of glucose and insulin in the BF. In response to meal challenges, the overall daily glucose, insulin, ghrelin and mean hunger scores were significantly lower, whereas mean satiety scores were significantly higher in the BF group. CONCLUSIONS: High-calorie breakfast with reduced intake at dinner is beneficial and might be a useful alternative for the management of obesity and metabolic syndrome.
BACKGROUND: Strategies that may increase compliance to reduced energy intakes are needed to reduce the health burden of obesity. Conflicting evidence exists regarding the effects of snacking on satiety and energy intake. METHODS: This study compared short-term satiety from two common snack foods, low fat popcorn or potato chips. Using a counterbalanced within-subject design, 35 normal weight non-smoking participants (17 men, 18 women) ages 20–50 years (mean age 33 +/- 11, BMI 23 +/- 2 kg/m2) consumed four conditions each: 200 mL of water (control), one cup (4 g, 15 kcal) popcorn, 6 cups (27 g, 100 kcal) popcorn, and one cup (28 g, 150 kcal) potato chips, each with 200 mL water. Participants rated their hunger, satisfaction, prospective consumption, and thirst on 100 mm visual analogue scales 30 minutes after commencement of snack consumption. In addition, post-snack energy intake from an ad libitum meal (amount served less amount remaining) was measured, and the test food and meal combined energy intake and energy compensation were calculated. RESULTS: Participants expressed less hunger, more satisfaction, and lower estimates of prospective food consumption after six cups of popcorn compared to all other treatments (P < 0.05). Energy compensation was 220% +/- 967%, 76% +/- 143% and 42% +/- 75% after one cup popcorn, six cups popcorn and one cup potato chips, respectively. Combined energy intake was significantly greater (P < 0.01) during the potato chips condition (803 +/- 277 kcal) compared to control (716 +/- 279 kcal) or popcorn conditions (698 +/- 286 kcal for one cup and 739 +/- 294 kcal for six cups). Combined energy intakes from both popcorn conditions were not significantly different than control (p > 0.05). CONCLUSION: Popcorn exerted a stronger effect on short-term satiety than did potato chips as measured by subjective ratings and energy intake at a subsequent meal. This, combined with its relatively low calorie load, suggests that whole grain popcorn is a prudent choice for those wanting to reduce feelings of hunger while managing energy intake and ultimately, body weight.
Children consume much of their daily energy intake at school. School district policies, state laws, and national policies, such as revisions to the US Department of Agriculture’s school meals standards, may affect the types of foods and beverages offered in school lunches over time.
There are currently no national standards for school lunch period length and little is known about the association between the amount of time students have to eat and school food selection and consumption.
Background: Scientific evidence for the optimal number, timing, and size of meals is lacking.Objective: We investigated the relation between meal frequency and timing and changes in body mass index (BMI) in the Adventist Health Study 2 (AHS-2), a relatively healthy North American cohort.Methods: The analysis used data from 50,660 adult members aged ≥30 y of Seventh-day Adventist churches in the United States and Canada (mean ± SD follow-up: 7.42 ± 1.23 y). The number of meals per day, length of overnight fast, consumption of breakfast, and timing of the largest meal were exposure variables. The primary outcome was change in BMI per year. Linear regression analyses (stratified on baseline BMI) were adjusted for important demographic and lifestyle factors.Results: Subjects who ate 1 or 2 meals/d had a reduction in BMI per year (in kg · m(-2) · y(-1)) (-0.035; 95% CI: -0.065, -0.004 and -0.029; 95% CI: -0.041, -0.017, respectively) compared with those who ate 3 meals/d. On the other hand, eating >3 meals/d (snacking) was associated with a relative increase in BMI (P < 0.001). Correspondingly, the BMI of subjects who had a long overnight fast (≥18 h) decreased compared with those who had a medium overnight fast (12-17 h) (P < 0.001). Breakfast eaters (-0.029; 95% CI: -0.047, -0.012; P < 0.001) experienced a decreased BMI compared with breakfast skippers. Relative to subjects who ate their largest meal at dinner, those who consumed breakfast as the largest meal experienced a significant decrease in BMI (-0.038; 95% CI: -0.048, -0.028), and those who consumed a big lunch experienced a smaller but still significant decrease in BMI than did those who ate their largest meal at dinner. Conclusions: Our results suggest that in relatively healthy adults, eating less frequently, no snacking, consuming breakfast, and eating the largest meal in the morning may be effective methods for preventing long-term weight gain. Eating breakfast and lunch 5-6 h apart and making the overnight fast last 18-19 h may be a useful practical strategy.
Eating patterns are increasingly varied. Typical breakfast, lunch, and dinner meals are difficult to distinguish because skipping meals and snacking have become more prevalent. Such eating styles can have various effects on cardiometabolic health markers, namely obesity, lipid profile, insulin resistance, and blood pressure. In this statement, we review the cardiometabolic health effects of specific eating patterns: skipping breakfast, intermittent fasting, meal frequency (number of daily eating occasions), and timing of eating occasions. Furthermore, we propose definitions for meals, snacks, and eating occasions for use in research. Finally, data suggest that irregular eating patterns appear less favorable for achieving a healthy cardiometabolic profile. Intentional eating with mindful attention to the timing and frequency of eating occasions could lead to healthier lifestyle and cardiometabolic risk factor management.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 3 years ago
Although major research efforts have focused on how specific components of foodstuffs affect health, relatively little is known about a more fundamental aspect of diet, the frequency and circadian timing of meals, and potential benefits of intermittent periods with no or very low energy intakes. The most common eating pattern in modern societies, three meals plus snacks every day, is abnormal from an evolutionary perspective. Emerging findings from studies of animal models and human subjects suggest that intermittent energy restriction periods of as little as 16 h can improve health indicators and counteract disease processes. The mechanisms involve a metabolic shift to fat metabolism and ketone production, and stimulation of adaptive cellular stress responses that prevent and repair molecular damage. As data on the optimal frequency and timing of meals crystalizes, it will be critical to develop strategies to incorporate those eating patterns into health care policy and practice, and the lifestyles of the population.