Timing of daily calorie loading affects appetite and hunger responses without changes in energy metabolism in healthy subjects with obesity.

Morning loaded calorie intake in humans has been advocated as a dietary strategy to improve weight loss. This is also supported by animal studies suggesting time of eating can prevent weight gain. However, the underlying mechanisms through which timing of eating could promote weight loss in humans are unclear. In a randomized crossover trial (NCT03305237), 30 subjects with obesity/overweight underwent two 4-week calorie-restricted but isoenergetic weight loss diets, with morning loaded or evening loaded calories (45%:35%:20% versus 20%:35%:45% calories at breakfast, lunch, and dinner, respectively). We demonstrate no differences in total daily energy expenditure or resting metabolic rate related to the timing of calorie distribution, and no difference in weight loss. Participants consuming the morning loaded diet reported significantly lower hunger. Thus, morning loaded intake (big breakfast) may assist with compliance to weight loss regime through a greater suppression of appetite.

Circadian Rhythms in Resting Metabolic Rate Account for Apparent Daily Rhythms in the Thermic Effect of Food.

CONTEXT: Daily variation in the thermic effect of food (TEF) is commonly reported and proposed as a contributing factor to weight gain with late eating. However, underlying circadian variability in resting metabolic rate (RMR) is an overlooked factor when calculating TEF associated with eating at different times of the day. OBJECTIVE: This work aimed to determine whether methodological approaches to calculating TEF contribute to the reported phenomena of daily variation in TEF. METHODS: Fourteen overweight to obese but otherwise healthy individuals had their resting and postprandial energy expenditure (EE) measured over 15.5 hours at a clinical research unit. TEF was calculated for breakfast, lunch, and dinner using standard methods (above a baseline and premeal RMR measure) and compared to a method incorporating a circadian RMR by which RMR was derived from a sinusoid curve model and TEF was calculated over and above the continuously changing RMR. Main outcome measures were TEF at breakfast, lunch, and dinner calculated by different methods. RESULTS: Standard methods of calculating TEF above a premeal measured RMR showed that morning TEF (60.8 kcal ±â€…5.6) (mean ±â€…SEM) was 1.6 times greater than TEF at lunch (36.3 kcal ±â€…8.4) and 2.4 times greater than dinner TEF (25.2 kcal ±â€…9.6) (P = .022). However, adjusting for modeled circadian RMR nullified any differences between breakfast (54.1 kcal ±â€…30.8), lunch (49.5 kcal ±â€…29.4), and dinner (49.1 kcal ±â€…25.7) (P = .680). CONCLUSION: Differences in TEF between morning and evening can be explained by the underlying circadian resting EE, which is independent of an acute effect of eating.

Mealtime: A circadian disruptor and determinant of energy balance?

Circadian rhythms play a critical role in the physiological processes involved in energy metabolism and energy balance (EB). A large array of metabolic processes, including the expression of many energy-regulating endocrine hormones, display temporal rhythms that are driven by both the circadian clock and food intake. Mealtime has been shown to be a compelling zeitgeber in peripheral tissue rhythms. Inconsistent signalling to the periphery, because of mismatched input from the central clock vs time of eating, results in circadian disruption in which central and/or peripheral rhythms are asynchronously time shifted or their amplitudes reduced. A growing body of evidence supports the negative health effects of circadian disruption, with strong evidence in murine models that mealtime-induced circadian disruption results in various metabolic consequences, including energy imbalance and weight gain. Increased weight gain has been reported to occur even without differences in energy intake, indicating an effect of circadian disruption on energy expenditure. However, the translation of these findings to humans is not well established because the ability to undertake rigorously controlled dietary studies that explore the chronic effects on energy regulation is challenging. Establishing the neuroendocrine changes in response to both acute and chronic variations in mealtime, along with observations in populations with routinely abnormal mealtimes, may provide greater insight into underlying mechanisms that influence long-term weight management under different meal patterns. Human studies should explore mechanisms through relevant biomarkers; for example, cortisol, leptin, ghrelin and other energy-regulating neuroendocrine factors. Mistiming between aggregate hormonal signals, or between hormones with their receptors, may cause reduced signalling intensity and hormonal resistance. Understanding how mealtimes may impact on the coordination of endocrine factors is essential for untangling the complex regulation of EB. Here a review is provided on current evidence of the impacts of mealtime on energy metabolism and the underlying neuroendocrine mechanisms, with a specific focus on human research.

Assessing the influence of fasted and postprandial states on day-to-day variability of appetite and food preferences.

INTRODUCTION: Ratings of subjective appetite and food hedonics provide valuable information about energy and macronutrient intake. Ensuring reproducibility of measures of subjective appetite, and food liking and wanting is essential for accurate understanding about their implementation in intervention studies. METHODS: Nineteen participants participated in two separate 10-h test days consisting of 6 test meals. Subjective appetite was measured in the fasted state and periodically across the test day in a postprandial state. Liking and wanting were measured using the Leeds Food Preferences Questionnaire (LFPQ) immediately before and after breakfast, immediately before the second meal, and at the end of the test day. RESULTS: Reproducibility of appetite scores was similar to those previously reported in males, however females tended to have consistently higher CVs, wider CRs and wider 95% CIs. Variability in food hedonics was of a similar magnitude to subjective appetite with CVs for fasting explicit liking and wanting between 15.3 and 33.4%, correlations for both implicit and explicit liking and wanting between 0.18 and 0.87 and CRs indicating 95% of between-day changes for any given individual should fall within ±43.4 mm of the mean change. Averages of food hedonics during the test day reduced CVs, improved correlations and reduced CRs. Despite no mean change in preceding energy and nutrient intake, individual changes in prior energy and macronutrient intake appeared to influence individual between-day changes in appetite and food hedonics, and appetite and food hedonics were intricately linked. CONCLUSIONS: Larger subject numbers may be required for appetite studies with female participants due to greater appetite variability. The LFPQ as a tool for measuring implicit and explicit liking and wanting is sufficiently reproducible and improved by averaging multiple measures across a day.

Measurement duration affects the calculation of whole body protein turnover kinetics but not between-day variability.

BACKGROUND: Assessment of whole body protein turnover (WBPT) can provide fundamental information about protein kinetics which underpins the conservation of lean tissue. Reliability and methodology studies on the measurement of WBPT are scarce. This study aimed to assess the effects of urine collection duration (9 versus 12 h) and the reproducibility of WBPT with the end product method calculated from ammonia as the end product. METHODS: WBPT was assessed in 21 healthy participants (11M, 10F) on 2 test days. WBPT was assessed using the end product method with a single dose of 15N glycine with ammonia as end product in a postprandial state with 9 and 12-h urine collections. RESULTS: The CV for protein flux averaged 10% and 12% for 9 and 12-h urine collections respectively. Protein flux, synthesis and balance were significantly higher and protein breakdown significantly lower with 9-h urine collections compared to 12-h collections (P < 0.01) and there was a trend towards increasingly greater overestimation of 9-h calculated WBPT kinetics with greater overall rates of WBPT. Correlations between the 9 and 12-h values were strong (r > 0.962, P < 0.001 for all variables). CONCLUSIONS: The reproducibility of WBPT with ammonia as the end product was similar to previously reported reproducibility of the gold standard precursor technique. The use of a 12-h urine collection is more effective to achieve full turnover of the ammonia free amino acid (AA) pool.

Methodological considerations for meal-induced thermogenesis: measurement duration and reproducibility.

Meal-induced thermogenesis (MIT) research findings have been highly inconsistent, in part, due to the variety of durations and protocols used to measure MIT. In the present study, we aimed to determine the following: (1) the proportion of a 6 h MIT response completed at 3, 4 and 5 h; (2) the associations between the shorter durations and the 6 h measures; (3) whether shorter durations improved the reproducibility of the measurement. MIT was measured in response to a 2410 kJ mixed composition meal in ten individuals (five males and five females) on two occasions. Energy expenditure was measured continuously for 6 h post-meal using indirect calorimetry, and MIT was calculated as the increase in energy expenditure above the pre-meal RMR. On average, 76, 89 and 96 % of the 6 h MIT response was completed within 3, 4 and 5 h, respectively, and MIT at each of these time points was strongly correlated with the 6 h MIT response (range for correlations, r 0·990-0·998; P< 0·01). The between-day CV for the 6 h measurement was 33 %, but it was significantly lower after 3 h of measurement (CV 26 %; P= 0·02). Despite variability in the total MIT between days, the proportion of MIT that was completed at 3, 4 and 5 h was reproducible (mean CV: 5 %). While 6 h are typically required to measure the complete MIT response, the 3 h measures provide sufficient information about the magnitude of the MIT response and may be applicable for testing individuals on repeated occasions.