Chrononutrition in traditional European medicine-Ideal meal timing for cardiometabolic health promotion.

Meal timing plays a crucial role for cardiometabolic health, given the circadian regulation of cardiometabolic function. However, to the best of our knowledge, no concept of meal timing exists in traditional European medicine (TEM). Therefore, in this narrative review, we aim to define the optimal time slot for energy intake and optimal energy distribution throughout the day in a context of TEM and explore further implications. By reviewing literature published between 2002 and 2022, we found that optimal timing for energy intake may be between 06:00 and 09:00, 12:00 and 14:00, and between 15:00 and 18:00, with high energy breakfast, medium energy lunch and low energy dinner and possibly further adjustments according to one's chronotype and genetics. Also, timing and distribution of energy intake may serve as a novel therapeutic strategy to optimize coction, a concept describing digestion and metabolism in TEM. Please cite this article as: Eberli NS, Colas L, Gimalac A. Chrononutrition in traditional European medicine-Ideal meal timing for cardiometabolic health promotion. J Integr Med. 2024; 22(2);115-125.

Conditioning by a Previous Experience Impairs the Rewarding Value of a Comfort Meal.

BACKGROUND: Meal ingestion induces a postprandial experience that involves homeostatic and hedonic sensations. Our aim was to determine the effect of aversive conditioning on the postprandial reward of a comfort meal. METHODS: A sham-controlled, randomised, parallel, single-blind study was performed on 12 healthy women (6 per group). A comfort meal was tested before and after coupling the meal with an aversive sensation (conditioning intervention), induced by infusion of lipids via a thin naso-duodenal catheter; in the pre- and post-conditioning tests and in the control group, a sham infusion was performed. Participants were instructed that two recipes of a tasty humus would be tested; however, the same meal was administered with a colour additive in the conditioning and post-conditioning tests. Digestive well-being (primary outcome) was measured every 10 min before and 60 min after ingestion using graded scales. RESULTS: In the aversive conditioning group, the comfort meal in the pre-conditioning test induced a pleasant postprandial experience, which was significantly lower in the post-conditioning test; the effect of aversive conditioning (change from pre- to post-conditioning) was significant as compared to sham conditioning in the control group, which showed no differences between study days. CONCLUSION: The hedonic postprandial response to a comfort meal in healthy women is impaired by aversive conditioning. CLINICALTRIALS: gov ID: NCT04938934.

Parents of preschoolers use multiple strategies to feed their children: Findings from an observational video pilot study.

The current study leveraged observational data collection methods to fill gaps in our understanding of parent approach to feeding as well as child responses to various parental approaches. Specifically, the study aimed to: 1) characterize the broad range of food parenting practices used by parents of preschoolers during shared mealtimes at home, including differences by child gender, and 2) describe child responses to specific parent feeding practices. Forty parent-child dyads participated by recording two in-home shared meals. Meals were coded using a behavioral coding scheme that coded the occurrence of 11 distinct food parenting practices (e.g. indirect and direct commands, praise, bribes) and eight child responses (e.g., eat, refuse, cry/whine) to food parenting practices. Results revealed that parents engaged in a broad range of food parenting practices at meals. On average, parents in our sample used 10.51 (SD 7.83; Range 0-30) total food parenting practices per mealtime with a mean use of 3.38 (SD 1.67; Range 0-8) unique food parenting practices per mealtime. Use of indirect and direct commands to eat were most common; direct and indirect commands were used by 97.5% (n = 39) and 87.5% (n = 35) of parents at meals, respectively. No statistically significant differences were observed by child gender. No one specific feeding practice consistently yielded compliance or refusal to eat from the child, instead child responses were often mixed (e.g., compliance followed by refusal and/or refusal followed by compliance). However, use of praise to prompt eating was the practice that most often resulted in child compliance; 80.8% of children complied following parent's use of praise as a prompt to eat. Findings deepen our understanding of the types and frequency of food parenting practices used by parents of preschoolers during meals eaten at home and illuminate child responses to specific food parenting practices.

Acute postprandial gut hormone, leptin, glucose and insulin responses to resistant starch in obese children: a single blind crossover study.

INTRODUCTION: Resistant starch (RS) has beneficial effects on postprandial glucose metabolism in both animals and adults. Hitherto, there have been no studies in children of the acute metabolic and hormonal effects of RS-containing meals. OBJECTIVES: We aimed to compare serial plasma glucose, insulin, gut hormone, leptin profiles and satiety scores in obese children after meals containing variable amounts of RS. METHODS: This was a single blind, non-randomised, crossover study of 20 obese children aged 10-14 years old without comorbidities. Three test meals containing rice (M1), rice cooked with coconut oil (M2), rice cooked in coconut oil with lentils (M3) were given in sequence after a 12-hour fast . Blood samples were analysed for glucose (PG), insulin, leptin, glucagon-like polypeptide (GLP) 1, ghrelin and peptide YY (PYY) at appropriate times between 0 and 180 min. RESULTS: Meal M2 resulted in significantly lower postprandial glucose values compared with meal M1 (maximal incremental glucose, ∆Cmax, p<0.05; area under the curve, ∆AUC0-3, p<0.01) and meal M3 (maximal concentration, Cmax, p<0.01; ∆Cmax, p<0.001, and ∆AUC0-3p<0.01). M2 also produced lower insulin values compared with M1 (p<0.05). Postprandial ghrelin was significantly higher after M1 compared with M3 (p<0.05). PYY, GLP1 and median satiety scores were not significantly different between the three meals. CONCLUSION: This study shows that M2, the meal containing RS alone, induced beneficial effects on acute postprandial glucose, insulin and ghrelin concentrations in obese children without diabetes. Acute postprandial satiety scores were not significantly affected by the three meals. TRIAL REGISTRATION NUMBER: SLCTR/2020/007.

Increased Meal Size but Reduced Meal-Stimulated Plasma Cholecystokinin Concentrations in Women With Obesity.

To better understand the physiological basis of obesity in women, we investigated whether obesity or menstrual cycle phase affects laboratory test-meal size or meal-stimulated plasma cholecystokinin (CCK) concentration. Women with healthy weight (body mass index [BMI] of 18.5-24.9 kg/m2, N = 16) or obesity (BMI 30-39.9 kg/m2, N = 20) were tested once in the late-follicular or peri-ovulatory phase (LF/PO) and once in the mid-luteal phase (ML). Meals of ham sandwiches were offered and blood was sampled. Menstrual cycle phases were verified with participants' reports of menses and measurements of progesterone and luteinizing hormone (LH) concentrations. Women with obesity ate significantly larger meals than women with healthy weight, (mean, 711 [95% CI, 402-1013] kJ, P = 0.001, during the LF/PO and 426 [105-734] kJ, P = 0.027, larger during the ML). Women with healthy weight ate smaller meals during LF/PO than ML (decrease, 510 [192-821 kJ], P = 0.008), but women with obesity did not (decrease, 226 [-87-542] kJ, P = 0.15). CCK concentrations 18 to 30 minutes after meal onset were lower in women with obesity than in women with healthy weight during LF/PO (3.6 [3.1-4.1] vs 6.1 [4.5-7.7] pmol/L; P = 0.004), but not during ML, with a significant interaction effect (1.8 [1.2-2.4] pmol/L, P = 0.048). Women with obesity consumed larger meals than women with healthy weight but displayed reduced meal-stimulated plasma CCK concentrations. These data are consistent with the hypothesis that a defect in CCK secretion compromises satiation in obese women and contributes to the development or maintenance of obesity.

A scoping review of intermittent fasting, chronobiology, and metabolism.

Chronobiology plays a crucial role in modulating many physiologic systems in which there is nutritional synergism with meal timing. Given that intermittent fasting (IF) has grown as a flexible dietary method consisting of delayed or early eating windows, this scoping review addresses the effects of IF protocols on metabolism as they relate to clinical nutrition and the circadian system. Although nocturnal habits are associated with circadian misalignments and impaired cardiometabolic profile-and nutritional physiology is better orchestrated during the day-most findings are based on animal experiments or human studies with observational designs or acute meal tests. Well-controlled randomized clinical trials employing IF protocols of delayed or early eating windows have sometimes demonstrated clinical benefits, such as improved glycemic and lipid profiles, as well as weight loss. However, IF does not appear to be more effective than traditional diets at the group level, and its effects largely depend on energy restriction. Thus, efforts must be made to identify patient biological rhythms, preferences, routines, and medical conditions before individual dietary prescription in clinical practice.

Interplay of Dinner Timing and MTNR1B Type 2 Diabetes Risk Variant on Glucose Tolerance and Insulin Secretion: A Randomized Crossover Trial.

OBJECTIVE: We tested whether the concurrence of food intake and elevated concentrations of endogenous melatonin, as occurs with late eating, results in impaired glucose control, in particular in carriers of the type 2 diabetes-associated G allele in the melatonin receptor-1B gene (MTNR1B). RESEARCH DESIGN AND METHODS: In a Spanish natural late-eating population, a randomized, crossover study was performed. Each participant (n = 845) underwent two evening 2-h 75-g oral glucose tolerance tests following an 8-h fast: an early condition scheduled 4 h prior to habitual bedtime ("early dinner timing") and a late condition scheduled 1 h prior to habitual bedtime ("late dinner timing"), simulating an early and a late dinner timing, respectively. Differences in postprandial glucose and insulin responses between early and late dinner timing were determined using incremental area under the curve (AUC) calculated by the trapezoidal method. RESULTS: Melatonin serum levels were 3.5-fold higher in the late versus early condition, with late dinner timing resulting in 6.7% lower insulin AUC and 8.3% higher glucose AUC. The effect of late eating impairing glucose tolerance was stronger in the MTNR1B G-allele carriers than in noncarriers. Genotype differences in glucose tolerance were attributed to reductions in ß-cell function (P for interaction, Pint glucose area under the curve = 0.009, Pint corrected insulin response = 0.022, and Pint disposition index = 0.018). CONCLUSIONS: Concurrently high endogenous melatonin and carbohydrate intake, as typical for late eating, impairs glucose tolerance, especially in MTNR1B G-risk allele carriers, attributable to insulin secretion defects.

Face Validity of Observed Meal Patterns Reported with 7-Day Diet Diaries in a Large Population-Based Cohort Using Diurnal Variation in Concentration Biomarkers of Dietary Intake.

In a cross-sectional analysis of a population-based cohort (United Kingdom, N = 21,318, 1993-1998), we studied how associations between meal patterns and non-fasting triglyceride and glucose concentrations were influenced by the hour of day at which the blood sample was collected to ascertain face validity of reported meal patterns, as well as the influence of reporting bias (assessed using formula of energy expenditure) on this association. Meal size (i.e., reported energy content), mealtime and meal frequency were reported using pre-structured 7-day diet diaries. In ANCOVA, sex-specific means of biomarker concentrations were calculated by hour of blood sample collection for quartiles of reported energy intake at breakfast, lunch and dinner (meal size). Significant interactions were observed between breakfast size, sampling time and triglyceride concentrations and between lunch size, sampling time and triglyceride, as well as glucose concentrations. Those skipping breakfast had the lowest triglyceride concentrations in the morning and those skipping lunch had the lowest triglyceride and glucose concentrations in the afternoon, especially among acceptable energy reporters. Eating and drinking occasion frequency was weakly associated with glucose concentrations in women and positively associated with triglyceride concentrations in both sexes; stronger associations were observed for larger vs. smaller meals and among acceptable energy reporters. Associations between meal patterns and concentration biomarkers can be observed when accounting for diurnal variation and underreporting. These findings support the use of 7-day diet diaries for studying associations between meal patterns and health.

Nutrient timing and metabolic regulation.

Daily (circadian) rhythms coordinate our physiology and behaviour with regular environmental changes. Molecular clocks in peripheral tissues (e.g. liver, skeletal muscle and adipose) give rise to rhythms in macronutrient metabolism, appetite regulation and the components of energy balance such that our bodies can align the periodic delivery of nutrients with ongoing metabolic requirements. The timing of meals both in absolute terms (i.e. relative to clock time) and in relative terms (i.e. relative to other daily events) is therefore relevant to metabolism and health. Experimental manipulation of feeding-fasting cycles can advance understanding of the effect of absolute and relative timing of meals on metabolism and health. Such studies have extended the overnight fast by regular breakfast omission and revealed that morning fasting can alter the metabolic response to subsequent meals later in the day, whilst also eliciting compensatory behavioural responses (i.e. reduced physical activity). Similarly, restricting energy intake via alternate-day fasting also has the potential to elicit a compensatory reduction in physical activity, and so can undermine weight-loss efforts (i.e. to preserve body fat stores). Interrupting the usual overnight fast (and therefore also the usual sleep cycle) by nocturnal feeding has also been examined and further research is needed to understand the importance of this period for either nutritional intervention or nutritional withdrawal. In summary, it is important for dietary guidelines for human health to consider nutrient timing (i.e. when we eat) alongside the conventional focus on nutrient quantity and nutrient quality (i.e. how much we eat and what we eat).

Predicting the Macronutrient Composition of Mixed Meals From Dietary Biomarkers in Blood.

Diet monitoring is an essential intervention component for a number of diseases, from type 2 diabetes to cardiovascular diseases. However, current methods for diet monitoring are burdensome and often inaccurate. In prior work, we showed that continuous glucose monitors (CGMs) may be used to predict meal macronutrients (e.g., carbohydrates, protein, fat) by analyzing the shape of the post-prandial glucose response. In this study, we examine a number of additional dietary biomarkers in blood by their ability to improve macronutrient prediction, compared to using CGMs alone. For this purpose, we conducted a nutritional study where (n = 10) participants consumed nine different mixed meals with varied but known macronutrient amounts, and we analyzed the concentration of 33 dietary biomarkers (including amino acids, insulin, triglycerides, and glucose) at various times post-prandially. Then, we built machine learning models to predict macronutrient amounts from (1) individual biomarkers and (2) their combinations. We find that the additional blood biomarkers provide complementary information, and more importantly, achieve lower normalized root mean squared error (NRMSE) for the three macronutrients (carbohydrates: 22.9%; protein: 23.4%; fat: 32.3%) than CGMs alone (carbohydrates: 28.9%, t(18) =1.64, p =0.060; protein: 46.4%, t(18) =5.38, p 0.001; fat: 40.0%, t(18) =2.09, p =0.025). Our main conclusion is that augmenting CGMs to measure these additional dietary biomarkers improves macronutrient prediction performance, and may ultimately lead to the development of automated methods to monitor nutritional intake. This work is significant to biomedical research as it provides a potential solution to the long-standing problem of diet monitoring, facilitating new interventions for a number of diseases.

Prediction of Personal Glycemic Responses to Food for Individuals With Type 1 Diabetes Through Integration of Clinical and Microbial Data.

OBJECTIVE: Despite technological advances, results from various clinical trials have repeatedly shown that many individuals with type 1 diabetes (T1D) do not achieve their glycemic goals. One of the major challenges in disease management is the administration of an accurate amount of insulin for each meal that will match the expected postprandial glycemic response (PPGR). The objective of this study was to develop a prediction model for PPGR in individuals with T1D. RESEARCH DESIGN AND METHODS: We recruited individuals with T1D who were using continuous glucose monitoring and continuous subcutaneous insulin infusion devices simultaneously to a prospective cohort and profiled them for 2 weeks. Participants were asked to report real-time dietary intake using a designated mobile app. We measured their PPGRs and devised machine learning algorithms for PPGR prediction, which integrate glucose measurements, insulin dosages, dietary habits, blood parameters, anthropometrics, exercise, and gut microbiota. Data of the PPGR of 900 healthy individuals to 41,371 meals were also integrated into the model. The performance of the models was evaluated with 10-fold cross validation. RESULTS: A total of 121 individuals with T1D, 75 adults and 46 children, were included in the study. PPGR to 6,377 meals was measured. Our PPGR prediction model substantially outperforms a baseline model with emulation of standard of care (correlation of R = 0.59 compared with R = 0.40 for predicted and observed PPGR respectively; P < 10-10). The model was robust across different subpopulations. Feature attribution analysis revealed that glucose levels at meal initiation, glucose trend 30 min prior to meal, meal carbohydrate content, and meal's carbohydrate-to-fat ratio were the most influential features for the model. CONCLUSIONS: Our model enables a more accurate prediction of PPGR and therefore may allow a better adjustment of the required insulin dosage for meals. It can be further implemented in closed loop systems and may lead to rationally designed nutritional interventions personally tailored for individuals with T1D on the basis of meals with expected low glycemic response.

Effect of acute dietary- versus combined dietary and exercise-induced energy deficits on subsequent energy intake, appetite and food reward in adolescents with obesity.

BACKGROUND: Acute dietary-induced energy deficits have been shown to favor compensatory appetitive responses. The aim of this study was to compare energy intake (EI), appetite sensations and the hedonic responses to equivalent energy deficits induced by dietary restriction alone and combined with exercise in adolescents with obesity. METHODS: In a within-subjects design, seventeen adolescents with obesity (12-16 years, Tanner stage 3-5, 6 males) randomly completed three 14 h conditions: (i) control (CON); (ii) deficit induced by diet only (Def-EI) and; (iii) deficit induced by combined diet and physical exercise (Def-mixed). Breakfast and lunch were calibrated to generate a 500 kcal deficit in Def-EI and 250 kcal deficit in Def-mixed. A 250 kcal deficit was created through a cycling exercise set at 65% VO2peak in Def-mixed. Ad libitum EI, macronutrients and relative EI (REI) were assessed at dinner, subjective appetite sensations taken at regular intervals, and food reward measured before dinner. RESULTS: EI at dinner was significantly lower in Def-EI compared to CON (p = 0.014; Effect size (ES): -0.59 [-1.07; -0.12]), with no difference between Def-mixed and both CON and Def-EI. Total REI was lower in both deficit conditions compared with CON (Def-mixed: p < 0.001; ES: -3.80 [-4.27; -3.32], Def-EI: p < 0.001; ES: -4.90 [-5.37; -4.42] respectively), indicating incomplete compensation for the energy deficits. Absolute protein ingestion at dinner was lower in Def-EI than Def-mixed (p = 0.037; ES: -0.50 [-0.98; -0.03]) and absolute lipid ingestion was lower in Def-EI than in CON (p = 0.033; ES: -0.51 [-0.99; -0.04]). A higher proportion of protein and a lower proportion of carbohydrates was observed in Def-mixed than in Def-EI (p = 0.078; ES: -0.42 [-0.90; 0.04] and p = 0.067; ES: 0.44 [-0.03; 0.92] respectively). Total area under the curve for appetite sensations were similar between conditions. Explicit liking for sweet relative to savoury food was lower in Def-mixed compared to CON (p = 0.027; ES: -0.53 [-1.01; -0.06]) with no difference in food reward between Def-EI and CON. CONCLUSION: Neither of the two acute isoenergetic deficits led to subsequent appetitive compensation, with the dietary deficit even inducing a lower ad libitum EI at the subsequent dinner. Further studies are needed to better understand the appetitive response to dietary and exercise energy balance manipulations in this population.

The relationship between meal carbohydrate quantity and the insulin to carbohydrate ratio required to maintain glycaemia is non-linear in young people with type 1 diabetes: A randomized crossover trial.

OBJECTIVE: To determine if the relationship between meal carbohydrate quantity and the insulin to carbohydrate ratio (ICR) required to maintain glycaemia is linear in people with type 1 diabetes. METHODS: We used an open labelled randomized four-arm cross-over study design. Participants (N = 31) aged 12-27 years, HbA1c ≤ 64 mmol/mol (8.0%) received insulin doses based on the individual's ICR and the study breakfast carbohydrate quantity and then consumed four breakfasts containing 20, 50, 100 and 150 g of carbohydrate over four consecutive days in randomized order. The breakfast fat and protein percentages were standardized. Postprandial glycaemia was assessed by 5 h continuous glucose monitoring. The primary outcome was percent time in range (TIR) and secondary outcomes included hypoglycaemia, glucose excursion and incremental area under the curve. Statistical analysis included linear mixed modelling and Wilcoxon signed rank tests. RESULTS: The 20 g carbohydrate breakfast had the largest proportion of TIR (0.74 ± 0.29 p < 0.04). Hypoglycaemia was more frequent in the 50 g (n = 13, 42%) and 100 g (n = 15, 50%) breakfasts compared to the 20 g (n = 6, 20%) and 150 g (n = 7, 26%) breakfasts (p < 0.029). The 150 g breakfast glucose excursion pattern was different from the smaller breakfasts with the lowest glucose excursion 0-2 h and the highest excursion from 3.5 to 5 h. CONCLUSIONS: A non-linear relationship between insulin requirement and breakfast carbohydrate content was observed, suggesting that strengthened ICRs are needed for meals with ≤20 and ≥150 g of carbohydrate. Meals with ≥150 g of carbohydrate may benefit from dual wave bolusing.

Impact of isoenergetic intake of irregular meal patterns on thermogenesis, glucose metabolism, and appetite: a randomized controlled trial.

BACKGROUND: Evidence is emerging that interdaily meal pattern variability potentially affects response such as thermic effect of food (TEF), macronutrient metabolism, and appetite. OBJECTIVES: To investigate the effect of irregular meal pattern on TEF, glucose, insulin, lipid profile, and appetite regulation in women who are overweight or with obesity and confirmed insulin resistance. DESIGN: In a randomized crossover trial, 9 women [mean ± SD BMI (in kg/m2): 33.3 ± 3.1] with confirmed insulin resistance consumed a regular (14 d; 6 meals/d) and an irregular (14 d; 3-9 meals/d) meal pattern separated by a 14-d washout interval. Identical foods were provided during the interventions, and at the start and end of each meal pattern, participants attended the laboratory after an overnight fast. Energy expenditure, glucose, insulin, lipids, adiponectin, leptin, glucagon-like peptide 1 (GLP-1), peptide YY (PYY), and ghrelin were measured at baseline and for 3 h after consumption of a test drink, after which an ad libitum test meal was offered. Subjective appetite ratings were recorded before and after the test drink, after the ad libitum meal, and during the intervention. Continuous interstitial glucose monitoring was undertaken for 7 consecutive days during each intervention. RESULTS: TEF (over 3 h) was significantly lower postirregular intervention compared with postregular (97.7 ± 19.2 kJ*3 h in postregular visit and 76.7 ± 35.2 kJ*3 h in postirregular visit, paired t test, P = 0.048). Differences in HOMA-IR between the 2 interventions (3.3 ± 1.7 and 3.6 ± 1.6 in postregular and postirregular meal pattern, respectively) were not significant. Net incremental AUC for GLP-1 concentrations (over 3 h) for the postregular meal pattern were higher (864.9 ± 456.1 pmol/L*3 h) than the postirregular meal pattern (487.6 ± 271.7 pmol/L*3 h, paired t test, P = 0.005). CONCLUSIONS: Following a 14-d period of an irregular meal pattern, TEF was significantly less than following a regular meal pattern, potentially compromising weight management if sustained long term. This study was registered at www.clinicaltrials.gov as NCT02582606.

Influence of Dairy Products on Bioavailability of Zinc from Other Food Products: A Review of Complementarity at a Meal Level.

In this paper, we reviewed the role of dairy products in dietary zinc absorption. Dairy products can have a reasonable contribution for dietary zinc intake in Western diets, where dairy consumption is high. However, the co-ingestion of dairy products can also improve zinc absorption from other food products. Such improvements have been observed when dairy products (e.g., milk or yoghurt) were ingested together with food such as rice, tortillas or bread products, all of which are considered to be high-phytate foods with low inherent zinc absorption. For foods low in phytate, the co-ingestion of dairy products did not improve zinc absorption. Improved zinc absorption of zinc from high-phytate foods following co-ingestion with dairy products may be related to the beneficial effects of the citrate and phosphopeptides present in dairy products. Considering that the main dietary zinc sources in areas in the world where zinc deficiency is most prevalent are typically high in phytate, the inclusion of dairy products in meals may be a viable dietary strategy to improve zinc absorption.

Lower Interstitial Glucose Concentrations but Higher Glucose Variability during Low-Energy Diet Compared to Regular Diet-An Observational Study in Females with Obesity.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

Substantial Intra-Individual Variability in Post-Prandial Time to Peak in Controlled and Free-Living Conditions in Children with Type 1 Diabetes.

The optimal time to bolus insulin for meals is challenging for children and adolescents with type 1 diabetes (T1D). Current guidelines to control glucose excursions do not account for individual differences in glycaemic responses to meals. This study aimed to examine the within- and between-person variability in time to peak (TTP) glycaemic responses after consuming meals under controlled and free-living conditions. Participants aged 8-15 years with T1D ≥ 1 year and using a continuous glucose monitor (CGM) were recruited. Participants consumed a standardised breakfast for six controlled days and maintained their usual daily routine for 14 free-living days. CGM traces were collected after eating. Linear mixed models were used to identify within- and between-person variability in the TTP after each of the controlled breakfasts, free-living breakfasts (FLB), and free-living dinners (FLD) conditions. Thirty participants completed the study (16 females; mean age and standard deviation (SD) 10.5 (1.9)). The TTP variability was greater within a person than the variability between people for all three meal types (between-person vs. within-person SD; controlled breakfast 18.5 vs. 38.9 min; FLB 14.1 vs. 49.6 min; FLD 5.7 vs. 64.5 min). For the first time, the study showed that within-person variability in TTP glycaemic responses is even greater than between-person variability.

Eucaloric Balanced Diet Improved Objective Sleep in Adolescents with Obesity.

BACKGROUND: A better understanding of the influence of energy balance on sleep in adolescents, particularly those with obesity, could help develop strategies to optimize sleep in these populations. The purpose of this study was to investigate sleep under ad libitum-vs-controlled diets adjusted to energy requirement (eucaloric) among adolescents with obesity and their normal weight controls. METHODS: Twenty-eight male adolescents aged between 12 and 15 years, n = 14 adolescents with obesity (OB: BMI ≥ 90th centile) and n = 14 normal weight age matched controls (NW), completed an experimental protocol comprising ad libitum or eucaloric meals for three days, in random order. During the third night of each condition, they underwent in home polysomnography (PSG). RESULTS: An interaction effect of energy intake (EI) was detected (p < 0.001). EI was higher during ad libitum compared to the eucaloric condition (p < 0.001) and in OB compared to NW (p < 0.001) in the absence of any substantial modification to macronutrient proportions. Analyses of energy intake distribution throughout the day showed a significant interaction with both a condition and group effect during lunch and dinner. Sleep improvements were noted in OB group during the eucaloric condition compared to ad libitum with reduced sleep onset latency and N1 stage. Sleep improvements were correlated to reduced EI, especially during the evening meal. CONCLUSION: Simply adjusting dietary intake to energy requirement and reducing the energy proportion of the evening meal could have therapeutic effects on sleep in adolescents with obesity. However, positive energy balance alone cannot justify worsened sleep among adolescents with obesity compared to normal weight counterparts.

Relationship between Energy Balance and Circulating Levels of Hepcidin and Ferritin in the Fasted and Postprandial States.

Markers of iron metabolism are altered in new-onset diabetes, but their relationship with metabolic signals involved in the maintenance of energy balance is poorly understood. The primary aim was to explore the associations between markers of iron metabolism (hepcidin and ferritin) and markers of energy balance (leptin, ghrelin, and the leptin/ghrelin ratio) in both the fasted and postprandial states. These associations were also studied in the sub-groups stratified by diabetes status. This was a cross-sectional study of individuals without disorders of iron metabolism who were investigated after an overnight fast and, in addition, some of these individuals underwent a mixed meal test to determine postprandial responses of metabolic signals. The associations between hepcidin, ferritin, and leptin, ghrelin, leptin/ghrelin ratio were studied using several multiple linear regression models. A total of 76 individuals in the fasted state and 34 individuals in the postprandial state were included. In the overall cohort, hepcidin was significantly inversely associated with leptin (in the most adjusted model, the ß coefficient ± SE was -883.45 ± 400.94; p = 0.031) and the leptin/ghrelin ratio (in the most adjusted model, the ß coefficient ± SE was -148.26 ± 61.20; p = 0.018) in the fasted state. The same associations were not statistically significant in the postprandial state. In individuals with new-onset prediabetes or diabetes (but not in those with normoglycaemia or longstanding prediabetes or diabetes), hepcidin was significantly inversely associated with leptin (in the most adjusted model, the ß coefficient ± SE was -806.09 ± 395.44; p = 0.050) and the leptin/ghrelin ratio (in the most adjusted model, the ß coefficient ± SE was -129.40 ± 59.14; p = 0.037). Leptin appears to be a mediator in the link between iron metabolism and new-onset diabetes mellitus. These findings add to the growing understanding of mechanisms underlying the derangements of glucose metabolism.

Genetic Studies of Metabolomics Change After a Liquid Meal Illuminate Novel Pathways for Glucose and Lipid Metabolism.

Humans spend the greater part of the day in a postprandial state. However, the genetic basis of postprandial blood measures is relatively uncharted territory. We examined the genetics of variation in concentrations of postprandial metabolites (t = 150 min) in response to a liquid mixed meal through genome-wide association studies (GWAS) performed in the Netherlands Epidemiology of Obesity (NEO) study (n = 5,705). The metabolite response GWAS identified an association between glucose change and rs10830963:G in the melatonin receptor 1B (ß [SE] -0.23 [0.03], P = 2.15 × 10-19). In addition, the ANKRD55 locus led by rs458741:C showed strong associations with extremely large VLDL (XXLVLDL) particle response (XXLVLDL total cholesterol: ß [SE] 0.17 [0.03], P = 5.76 × 10-10; XXLVLDL cholesterol ester: ß [SE] 0.17 [0.03], P = 9.74 × 10-10), which also revealed strong associations with body composition and diabetes in the UK Biobank (P < 5 × 10-8). Furthermore, the associations between XXLVLDL response and insulinogenic index, HOMA-ß, Matsuda insulin sensitivity index, and HbA1c in the NEO study implied the role of chylomicron synthesis in diabetes (with false discovery rate-corrected q <0.05). To conclude, genetic studies of metabolomics change after a liquid meal illuminate novel pathways for glucose and lipid metabolism. Further studies are warranted to corroborate biological pathways of the ANKRD55 locus underlying diabetes.