Search

Background: Breakfast skipping has been related to poor mood, but the role of sleep in this relationship remains unclear. Aim: To evaluate whether breakfast skipping associated with mood independently of sleep, and whether sleep interacted with breakfast skipping. Methods: During an in-person research visit, a sample of 329 adults completed questionnaires regarding last night’s sleep, current morning breakfast intake, and mid-morning mood states. Sex-stratified linear regression models examined associations between breakfast skipping and mood and interactions with sleep. Results: Among males, those who did not consume breakfast had less vigor independent of sleep (β=−2.72 with 95% CI −4.91, −0.53). Among females, those who did not consume breakfast had higher feelings of anxiety (β=1.21 with 95% CI −0.04, 2.47). Interaction analyses revealed that males with longer time to fall asleep and longer night-time awake time had higher depression scores in the presence of breakfast skipping, and females with more night-time awake time and shorter duration had higher fatigue and less vigor if they were also breakfast skippers. Conclusion: Breakfast skipping and poor sleep may jointly affect mood.

FFQ, the primary method of dietary assessment in large-scale nutritional epidemiological studies, preclude an informed evaluation of the timing of dietary intake and meal-specific dietary intake. In this study, we developed the Meal-based Diet History Questionnaire (MDHQ), a self-administered questionnaire designed for estimating food and nutrient intakes for each meal type separately. The development was done based on a 16-d dietary record obtained from 242 Japanese adults. The MDHQ consisted of the three different parts, with a total of 196 items. Part 1 of the MDHQ asks about consumption frequency of generic food groups (n 24) for each meal type: breakfast, morning snack, lunch, afternoon snack, dinner and night snack. Part 2 of the MDHQ asks about relative consumption frequency of sub-food groups within one of the generic food groups which are asked in Part 1. Combining information derived from Parts 1 and 2 enables us to increase the number of foods we can estimate efficiently but within a limited number of questions. Part 3 of the MDHQ asks about general eating behaviours, which are intended to use in a variety of ways during dietary intake calculation. A series of calculation algorithms for food groups, energy and nutrients was also prepared. Given that the MDHQ was empirically developed based on comprehensive information on actual food consumption, this innovative tool may be promising for future epidemiological research on meal patterns and time of day of dietary intake, or chrono-nutrition research. A rigorous evaluation of validity of the MDHQ is warranted.

Insulin degludec/insulin aspart (IDegAsp) is a fixed‐ratio co‐formulation of insulin degludec, which provides long‐lasting basal insulin coverage, and insulin aspart, which targets postprandial glycaemia. This review provides expert opinion on the practical clinical use of IDegAsp, including: dose timings relative to meals, when and how to intensify treatment from once‐daily (OD) to twice‐daily (BID) dose adjustments, and use in special populations (including hospitalized patients). IDegAsp could be considered as one among the choices for initiating insulin treatment, preferential to starting on basal insulin alone, particularly for people with severe hyperglycaemia and/or when postprandial hyperglycaemia is a major concern. The recommended starting dose of IDegAsp is 10 units with the most carbohydrate‐rich meal(s), followed by individualized dose adjustments. Insulin doses should be titrated once weekly in two‐unit steps, guided by individualized fasting plasma glucose targets and based on patient goals, preferences and hypoglycaemia risk. Options for intensification from IDegAsp OD are discussed, which should be guided by HbA1c, prandial glucose levels, meal patterns and patient preferences. Recommendations for switching to IDegAsp from basal insulin, premixed insulins OD/BID, and basal‐plus/basal–bolus regimens are discussed. IDegAsp can be co‐administered with other antihyperglycaemic drugs; however, sulphonylureas frequently need to be discontinued or the dose reduced, and the IDegAsp dose may need to be decreased when sodium‐glucose co‐transporter‐2 inhibitors or glucagon‐like peptide‐1 receptor agonists are added. Considerations around the initiation or continuation of IDegAsp in hospitalized individuals are discussed, as well as in those undergoing medical procedures.

Objective:To examine whether skipping breakfast or lunch increased the next meal’s energy content and changed total daily energy content and the quality of food intake measured by the 2010 Healthy Eating Index (HEI-2010).Design:Means were compared across intake days and meal patterns. Multivariate individual fixed-effects model was used to account for individual food intake and diet quality preferences.Setting:National Health and Nutrition Examination Survey, 2007–2016.Participants:Adults aged 18 years or older who reported 2 d (24-h periods) of dietary intake and were not pregnant or lactating (n 23 488).Results:Adults consumed 193 more kJ at lunch after skipping breakfast and 783 more kJ at dinner after skipping breakfast and lunch. Skipping at least one meal reduced total daily intake between 1053 (breakfast) and 1464 (dinner) kJ and reduced the daily HEI score. Skipping breakfast or skipping lunch reduced the HEI component scores for fruit, whole grains, dairy and empty energy; skipping lunch reduced the component scores for fruit, vegetables, whole grain, dairy, seafood and plant protein, and empty energy. Skipping dinner reduced component scores for vegetables, greens and beans, dairy, protein food, seafood and plant proteins, and empty energy. Skipping one or more meals increased component scores for total vegetables (breakfast), whole grains (dinner), Na (lunch or dinner) and refined grains (breakfast, lunch or dinner).Conclusions:Skipping meals (particularly dinner) reduces daily energy intake, but the reduction in daily diet quality (particularly when skipping breakfast) may impact health negatively over time.

Objective:To synthesise evidence of urban dietary behaviours (macronutrients, types of foods, dietary diversity and dietary practices) in two African countries in relation to postulated changes in the context of nutrition transition.Design:Systematic review and meta-analyses, including six online databases and grey literature, 1971–2018 (Protocol CRD42017067718).Setting:Urban Ghana and Kenya.Participants:Population-based studies of healthy adolescents and adults.Results:The forty-seven included studies encompassed 20 726 individuals plus 6526 households. Macronutrients were within WHO-recommended ranges: mean energy intake was 1867 kcal/d (95 % CI 1764, 1969) and the proportions of macronutrients were carbohydrate 61·2 % (58·4, 64·0), fat 25·3 % (22·8, 28·0) and protein 13·7 % (12·3, 15·1). The proportion of population consuming fruit and vegetables was 51·6 %; unhealthy foods, 29·4 %; and sugar-sweetened beverages (SSBs), 39·9 %. Two-thirds (68·8 %) consumed animal-source proteins. Dietary diversity scores were within the mid-range. Meal patterns were structured (typically three meals per day), with evidence lacking on snacking or eating out.Conclusions:Population-level diets fell within WHO macronutrient recommendations, were relatively diverse with structured meal patterns, but some indications of nutrition transition were apparent. The proportion of population consuming fruit and vegetables was low compared to healthy-eating recommendations, and consumption of SSBs was widespread. A paucity of evidence from 1971 to 2010 precluded a longitudinal analysis of nutrition transition. Evidence from these two countries indicates which aspects of dietary behaviours may be contributing to increasing overweight/obesity, namely a low proportion of population consuming fruit and vegetables and widespread consumption of SSBs. These are potential targets for promoting healthier diets.

Over half of the annual guests at Swedish hotels are supplied by the corporate sector. These guests are made up of individuals who travel for meetings, conferences, or presentations as a part of their job. Access to meals while travelling is essential and introduces added complexity to business travelers' everyday lives. These meals, and the pattern in which they are consumed, are part of the individual traveler's personal and group identities. Therefore, the aim of this article is to study if business travelers deviate from their habitual meal patterns and, if so, what changes they make. To further the understanding of this group's meal patterns, a questionnaire was created and distributed. It was answered by 538 self-identified business travelers. These business travelers were made up of three groups: solo travelers, group travelers, and individuals who traveled both in groups as well as alone. Pearson's chi-squared test was used to analyze differences in actions related to the meal pattern between groups. The analysis showed that changes in the meal pattern did occur in some instances. However, the majority of the business travelers adhered to their habitual meal pattern while adjusting their behavior depending on the time of day. Managers of catering suppliers gaining insight into the meal habits of business travelers could help to ease an otherwise stressful situation by supplying meals, as a context, that fit with the business traveler's habitual patterns and meal contexts.

Ultra-processed foods are associated with chronic diseases, cardiometabolic factors and obesity. According to the NOVA system, foods are classified into four categories (from 1 = unprocessed to 4 = ultra-processed foods). The purpose of the present study was to assess the consumption of minimally processed foods (MPF) and ultra-processed foods (UPF) in university students and their relationship with obesity, Mediterranean diet adherence and meal patterns. In total, 346 students (269 women) of the University of Peloponnese participated. A food frequency questionnaire was used, and the MedDietScore was calculated. The % energy contribution of MPF and UPF was calculated. The identification of meal patterns was performed via principal component analysis. Both multivariate regression and Spearman’s correlations were used to measure the association of UPF/MPF consumption with anthropometric indices (body mass index, BMI and waist circumference, WC), Mediterranean diet adherence and early/late meal patterns. UPF and MPF provided 40.7 ± 13.6% and 44.3 ± 11.9% (mean ± standard deviation) of energy intake, respectively. In multi-adjusted linear regression models UPF consumption (% energy) was positively associated with WC in men but it was not related to BMI (total sample, men, women). UPF consumption was negatively related to the MedDietScore (Spearman rho = −0.214, p < 0.001) and an “early eating” pattern (Spearman rho = −0.120, p = 0.029) and positively associated with a “late eating” meal pattern (Spearman rho = 0.190, p = 0.001). MPF consumption was positively associated with the MedDietScore (Spearman rho = 0.309, p < 0.001) and an “early eating” pattern (Spearman rho = 0.240, p < 0.001). In conclusion, UPF consumption was positively related to WC in male university students. Nutritional and sociodemographic correlates of UPF consumption, such as low Mediterranean diet adherence and having a “late eating” pattern serve as a basis to better understand the UPF consumption-central obesity relation in young adults and should be considered in nutrition education programs for young adults.

We aim to describe temporal eating patterns in a population of adults with overweight or obesity. In this cross-sectional analysis, data were combined from two separate pilot studies during which participants entered the timing of all eating occasions (>0 kcals) for 10–14 days. Data were aggregated to determine total eating occasions, local time of the first and last eating occasions, eating window, eating midpoint, and within-person variability of eating patterns. Eating patterns were compared between sexes, as well as between weekday and weekends. Participants (n = 85) had a median age of 56 ± 19 years, were mostly female (>70%), white (56.5%), and had a BMI of 31.8 ± 8.0 kg/m2. The median eating window was 14 h 04 min [12 h 57 min–15 h 21 min], which was significantly shorter on the weekend compared to weekdays (p < 0.0001). Only 13.1% of participants had an eating window 14 h/d). Future trials should examine the contribution of a prolonged eating window on adiposity independent of energy intake.

It is widely assumed that people with obesity have several common eating patterns, including breakfast skipping, eating during the night and high fast-food consumption. However, differences in individual meal and dietary patterns may be crucial to optimising obesity treatment. Therefore, we investigated the inter-individual variation in eating patterns, hypothesising that individuals with obesity show different dietary and meal patterns, and that these associate with self-reported energy intake (rEI) and/or anthropometric measures. Cross-sectional data from 192 participants (aged 20–55 years) with obesity, including 6 d of weighed food records, were analysed. Meal patterns and dietary patterns were derived using exploratory hierarchical cluster analysis and k-means cluster analysis, respectively. Five clear meal patterns were found based on the time-of-day with the highest mean rEI. The daily rEI was highest among ‘midnight-eaters’ (10 669 (sd 2301) kJ), and significantly (P < 0·05) higher than ‘dinner-eaters’ (8619 (sd 2301) kJ), ‘lunch-eaters’ (8703 (sd 2176) kJ) and ‘supper-eaters’ (8786 (sd 1925) kJ), but not ‘regular-eaters’ (9749 (sd 2720) kJ). Despite differences of up to 2050 kJ between meal patterns, there were no significant differences in anthropometric measures or physical activity level (PAL). Four dietary patterns were also found with significant differences in intake of specific food groups, but without significant differences in anthropometry, PAL or rEI. Our data highlight meal timing as a determinant of individual energy intake in people with obesity. The study supports the importance of considering a person’s specific meal pattern, with possible implications for more person-focused guidelines and targeted advice.

Environmental cues recalling palatable foods motivate eating beyond metabolic need, yet the timing of this response and whether it can develop towards a less palatable but readily available food remain elusive. Increasing evidence indicates that external stimuli in the olfactory modality communicate with the major hub in the feeding neurocircuitry, namely the hypothalamic arcuate nucleus (Arc), but the neural substrates involved have been only partially uncovered. By means of a home-cage hidden palatable food paradigm, aiming to mimic ubiquitous exposure to olfactory food cues in Western societies, we investigated whether the latter could drive the overeating of plain chow in non-food-deprived male rats and explored the neural mechanisms involved, including the possible engagement of the orexigenic ghrelin system. The olfactory detection of a familiar, palatable food impacted upon meal patterns, by increasing meal frequency, to cause the persistent overconsumption of chow. In line with the orexigenic response observed, sensing the palatable food in the environment stimulated food-seeking and risk-taking behavior, which are intrinsic components of food acquisition, and caused active ghrelin release. Our results suggest that olfactory food cues recruited intermingled populations of cells embedded within the feeding circuitry within the Arc, including, notably, those containing the ghrelin receptor. These data demonstrate the leverage of ubiquitous food cues, not only for palatable food searching, but also to powerfully drive food consumption in ways that resonate with heightened hunger, for which the orexigenic ghrelin system is implicated.

OBJECTIVE Associations between food insecurity, meal patterns, beverage intake, and body mass index (BMI) were investigated using data from the Howard Meharry Adolescent Caries Study. METHODS Secondary analyses of food security status used the Wilcoxon rank sum, chi-square, and Fisher's exact tests. RESULTS The group of adolescents (n=627) was 42.1% male, 14.2±1.9 years, 86.9% African American, and 19.9% food-insecure. Meal frequency, meal structure, most beverage intake, and BMI did not differ by food-security status. Adolescents from Washington, DC were more likely to be food insecure than adolescents from Nashville, TN (P=0.003). Most had unstructured meal patterns and irregular breakfast intake. Median milk intake was below and sugar-sweetened beverage intake above dietary recommendations. CONCLUSIONS This study extends our knowledge concerning food insecurity in urban African American adolescents and suggests public health initiatives designed to encourage meal structure, increase milk intake, and reduce sugar-sweetened beverage intake can improve diet quality of underserved youth.

This contribution presents an individualized multistage model predictive control (MS-MPC) algorithm for blood glucose (BG) stabilization and improved postprandial BG control for people with type 1 diabetes (T1D) with consistent meal patterns. The multistage formulation utilizes different meal patterns as disturbance realizations entering the glucose-insulin system, then assesses the best possible control input among all of the probable scenarios. The disturbance realizations, in the form of glucose rate of appearance traces, are estimated by using meal records (time and carbohydrate amount) as the input into an individualized oral model. Meal signatures are then clustered with the k-medoids algorithm to obtain meal patterns. Two approaches, a hybrid closed-loop (HCL) and fully closed-loop (FCL) MS-MPC were tested and compared with their respective control treatments (hybrid and fully automated MPC, respectively) using the complete in silico adult cohort of the FDA-accepted UVA/Padova metabolic simulator. Results confirm an improvement in both postprandial and overall percent time in 70-180 mg/dL 85.2 ± 15.5 v. 89.6 ± 12.2 and 94.1 ± 6.3 v. 95.7 ±5.0, respectively, using the HCL approach, and 37.8 ± 15.7 v. 63.4± 16.6 and 65.8 ± 12.7 v. 82.2± 9.2, using the FCL approach.P

Disruption of circadian rhythms has been associated with metabolic syndromes, including obesity and diabetes. A variety of metabolic activities are under circadian modulation, as local and global clock gene knockouts result in glucose imbalance and increased risk of metabolic diseases. Insulin release from the pancreatic β cells exhibits daily variation, and recent studies have found that insulin secretion, not production, is under circadian modulation. As consideration of daily variation in insulin secretion is necessary to accurately describe glucose-stimulated insulin secretion, we describe a mathematical model that incorporates the circadian modulation via insulin granule trafficking. We use this model to understand the effect of oscillatory characteristics on insulin secretion at different times of the day. Furthermore, we integrate the dynamics of clock genes under the influence of competing environmental signals (light/dark cycle and feeding/fasting cycle) and demonstrate how circadian disruption and meal size distribution change the insulin secretion pattern over a 24-h day.

This study examines the shifting patterns in meal consumption practices among Canadians and the sources of disruption of meal habits. It analyses the notion of breakfast, lunch, dinner, out-of-hous...

Feeding, which is essential for all animals, is regulated by homeostatic mechanisms. In addition, food consumption is temporally coordinated by the brain over the circadian (~24 h) cycle. A network of circadian clocks set daily windows during which food consumption can occur. These daily windows mostly overlap with the active phase. Brain clocks that ensure the circadian control of food intake include a master light-entrainable clock in the suprachiasmatic nuclei of the hypothalamus and secondary clocks in hypothalamic and brainstem regions. Metabolic hormones, circulating nutrients and visceral neural inputs transmit rhythmic cues that permit (via close and reciprocal molecular interactions that link metabolic processes and circadian clockwork) brain and peripheral organs to be synchronized to feeding time. As a consequence of these complex interactions, growing evidence shows that chronodisruption and mistimed eating have deleterious effects on metabolic health. Conversely, eating, even eating an unbalanced diet, during the normal active phase reduces metabolic disturbances. Therefore, in addition to energy intake and dietary composition, appropriately timed meal patterns are critical to prevent circadian desynchronization and limit metabolic risks. This Review provides insight into the dual modulation of food intake by homeostatic and circadian processes, describes the mechanisms regulating feeding time and highlights the beneficial effects of correctly timed eating, as opposed to the negative metabolic consequences of mistimed eating. In this Review, Etienne Challet discusses the dual modulation of food intake by homeostatic and circadian processes, describes the mechanisms regulating feeding time and highlights the beneficial effects of correctly timed eating, as opposed to the negative metabolic consequences of mistimed eating.

OBJECTIVE The present study was carried out to evaluate the effect of high dietary cation and anion difference (DCAD) rations on diurnal variations in eating and meal patterns, water intake and urination patterns in dairy goats fed under high ambient temperature (HTa). METHODS Ten crossbred dairy goats during peri-parturition period were selected and divided into two groups of five animals each. Experimental diets were control DCAD (control, 22.8 mEq/100 g dry matter [DM]) and high DCAD (DCAD, 39.1 mEq/100 g DM). The composition of two diets consisted of 44% corn silage and 56% concentrate. From the 2nd week to 8th week postpartum, goats were fed ad libitum twice daily either with the control or DCAD total mix ration with free access to water. The spontaneous eating and drinking patterns were determined. RESULTS The environmental conditions in the present experiment indicated that goats were fed under HTa conditions (average peak THI = 85.2) and were in heat stress. In addition to the typical HTa induced tachypnoea in both groups, the respiratory rate in the DCAD group was significantly higher than the control group (p

Through the Healthy, Hunger-Free Kids Act of 2010, USDA (US Department of Agriculture) made the first major changes in the CACFP (Child and Adult Care Food Program) meal and snack menu patterns. Childcare centers that serve low-income families qualify to participate and receive reimbursement for meals and snacks served. The purpose of this study was to assess what changes in children’s dietary behaviors occurred as a result of the new CACFP meal pattern requirements. This study evaluated these changes at childcare centers operating in Houston and San Antonio, Texas, USA, areas enrolled in the CACFP, pre- (Spring 2016) and post-implementation (Fall 2016–Spring 2017) of the new meal patterns. Dietary intake was assessed via observations of children, 3–5 years old, conducted at breakfast, lunch, and snack times. Results showed improvements in adjusted means of several nutrients and food groups consumption, post-implementation of new CACFP meal guidelines compared to baseline, specifically intake of whole grains, milk, and juice. Additional studies are needed to confirm the impact of the revised CACFP meal patterns along with strategies to assist providers in meeting the new standards to increase the access to and intake of items in accordance with the CACFP meal pattern requirements in childcare settings.

Feeding is critical for survival, and disruption in the mechanisms that govern food intake underlies disorders such as obesity and anorexia nervosa. It is important to understand both food intake and food motivation to reveal mechanisms underlying feeding disorders. Operant behavioral testing can be used to measure the motivational component to feeding, but most food intake monitoring systems do not measure operant behavior. Here, we present a new solution for monitoring both food intake and motivation in rodent home-cages: the Feeding Experimentation Device version 3 (FED3). FED3 measures food intake and operant behavior in rodent home-cages, enabling longitudinal studies of feeding behavior with minimal experimenter intervention. It has a programmable output for synchronizing behavior with optogenetic stimulation or neural recordings. Finally, FED3 design files are open-source and freely available, allowing researchers to modify FED3 to suit their needs.Obesity and anorexia nervosa are two health conditions related to food intake. Researchers studying these disorders in animal models need to both measure food intake and assess behavioural factors: that is, why animals seek and consume food. Measuring an animal’s food intake is usually done by weighing food containers. However, this can be inaccurate due to the small amount of food that rodents eat. As for studying feeding motivation, this can involve calculating the number of times an animal presses a lever to receive a food pellet. These tests are typically conducted in hour-long sessions in temporary testing cages, called operant boxes. Yet, these tests only measure a brief period of a rodent's life. In addition, it takes rodents time to adjust to these foreign environments, which can introduce stress and may alter their feeding behaviour. To address this, Matikainen-Ankney, Earnest, Ali et al. developed a device for monitoring food intake and feeding behaviours around the clock in rodent home cages with minimal experimenter intervention. This ‘Feeding Experimentation Device’ (FED3) features a pellet dispenser and two ‘nose-poke’ sensors to measure total food intake, as well as motivation for and learning about food rewards. The battery-powered, wire-free device fits in standard home cages, enabling long-term studies of feeding behaviour with minimal intervention from investigators and less stress on the animals. This means researchers can relate data to circadian rhythms and meal patterns, as Matikainen-Ankney did here. Moreover, the device software is open-source so researchers can customise it to suit their experimental needs. It can also be programmed to synchronise with other instruments used in animal experiments, or across labs running the same behavioural tasks for multi-site studies. Used in this way, it could help improve reproducibility and reliability of results from such studies. In summary, Matikainen-Ankney et al. have presented a new practical solution for studying food-related behaviours in mice and rats. Not only could the device be useful to researchers, it may also be suitable to use in educational settings such as teaching labs and classrooms.

Objective: We aimed to examine whether meal patterns, as well as energy intake from three main meals and snacks, were associated with incident hypertension. Methods: We included 12 995 participants aged 18–59 years from the China Health and Nutrition Survey in the final analysis. Dietary intake was assessed using weighing methods in combination with 24-h food records. Cox proportional hazards regression models were used to examine the association of meal patterns, and energy intake from different meals with incident hypertension. Results: During a mean follow-up of 11.2 years, 4766 new hypertension cases were documented. Four meal patterns were derived according to energy intake: balanced, breakfast dominant, lunch dominant, and dinner dominant patterns. Dinner dominant meal pattern was associated with a lower risk of incident hypertension [hazard ratio (95% confidence interval): 0.90 (0.84–0.98)] compared with the balanced meal pattern. Breakfast energy intake was positively, but dinner energy intake was inversely associated with incident hypertension. The positive association between breakfast energy intake and incident hypertension was observed in rural residents only [1.22 (1.07–1.41) for rural residents, 0.98 (0.82–1.18) for urban residents; P interaction = 0.0348]. A positive association between energy intake from lunch and incident hypertension was observed in the urban residents only. Conclusion: Dinner dominant meal pattern was associated with a lower risk of hypertension compared with the balanced meal pattern in Chinese adults. A relatively small breakfast and large dinner may help to prevent or delay the development of hypertension, especially in urban residents.

Obesity is a major health risk, with junk food consumption playing a central role in weight gain, because of its high palatability and high-energy nutrients. The Cafeteria (CAF) diet model for animal experiments consists of the same tasty but unhealthy food products that people eat (e.g. hot dogs and muffins), and considers variety, novelty and secondary food features, such as smell and texture. This model, therefore, mimics human eating patterns better than other models. In this paper, we systematically review studies that have used a CAF diet in behavioral experiments and propose a standardized CAF diet protocol. The proposed diet is ad libitum and voluntary; combines different textures, nutrients and tastes, including salty and sweet products; and it is rotated and varied. Our summary of the behavioral effects of CAF diet show that it alters meal patterns, reduces the hedonic value of other rewards, and tends to reduce stress and spatial memory. So far, no clear effects of CAF diet were found on locomotor activity, impulsivity, coping and social behavior.

This study was carried out to evaluate the relation between meal patterns and the risk of eating disorders in university students. The study was conducted on a total of 331 volunteer students with a mean age of 22.08 ± 1.80 years, 56.5% female. Participants’ sociodemographic characteristics, health information and eating habits like meal skipping and dieting were questioned. Sick, Control, One stone, Fat, Food (SCOFF) Eating Disorders Scale and Eating Disorder Examination Questionnaire (EDE-Q) were used to determine eating behavior disorders, with face to face interviews by the researches. A significant correlation was found between dieting and skipping meals and the risk of eating disorders in both genders (p

There is a scarcity of dietary intake research focusing on the intake of whole meals rather than on the nutrients and foods of which those meals are composed. This growing area of research has recently begun to utilize advanced statistical techniques to manage the large number of variables and permutations associated with these complex meal patterns. The aim of this narrative review was to evaluate those techniques and the meal patterns they detect. The 10 observational studies identified used techniques such as principal components analysis, clustering, latent class analysis, and decision trees. They examined meal patterns under 3 categories: temporal patterns (relating to the timing and distribution of meals), content patterns (relating to combinations of foods within a meal and combinations of those meals over a day), and context patterns (relating to external elements of the meal, such as location, activities while eating, and the presence or absence of others). The most common temporal meal patterns were the 3 meals/d pattern, the skipped breakfast pattern, and a grazing pattern consisting of smaller but more frequent meals. The 3 meals/d pattern was associated with increased diet quality compared with the other 2 patterns. Studies identified between 7 and 12 content patterns with limited similarities between studies and no clear associations between the patterns and diet quality or health. One study simultaneously examined temporal and context meal patterns, finding limited associations with diet quality. No study simultaneously examined other combinations of meal patterns. Future research that further develops the statistical techniques required for meal pattern analysis is necessary to clarify the relations between meal patterns and diet quality and health.

The nutritional composition of special low protein foods (SLPFs) is controlled under EU legislation for &lsquo, Foods for Special Medical Purposes (FSMP)&rsquo, They are designed to meet the energy needs of patients unable to eat a normal protein containing diet. In phenylketonuria (PKU), the macronutrient contribution of SLPFs has been inadequately examined. Aim: A 3-year longitudinal prospective study investigating the contribution of SLPFs to the macronutrient intake of children with early treated PKU. Methods: 48 children (27 boys) with a mean recruitment age of 9.3 y were studied. Semi-quantitative dietary assessments and food frequency questionnaires (FFQ) were collected three to four times/year for 3 years. Results: The mean energy intake provided by SLPFs was 33% (SD &plusmn, 8), and this figure was 42% (SD &plusmn, 13) for normal food and 21% (SD &plusmn, 5) for protein substitutes (PS). SLPFs supplied a mean intake of 40% carbohydrate (SD &plusmn, 10), 51% starch (SD &plusmn, 18), 21% sugar (SD &plusmn, 8), and 38% fat (SD &plusmn, 13). Fibre intake met 83% of the Scientific Advisory Committee on Nutrition (SACN) reference value, with 50% coming from SLPFs with added gums and hydrocolloids. Low protein bread, pasta and milk provided the highest energy contribution, and the intake of sweet SLPFs (e.g., biscuits, cakes, and chocolate) was minimal. Children averaged three portions fruit/vegetable daily, and children aged &ge, 12 y had irregular meal patterns. Conclusion: SLPFs provide essential energy in phenylalanine restricted diets. Optimising the nutritional quality of SLPFs deserves more attention.

The U.S. Department of Agriculture&rsquo, s (USDA) Child and Adult Care Food Program (CACFP) updated meal pattern standards took effect in October 2017. The aim of this quasi-experimental, pre-post study is to identify changes in food and beverage practices of CACFP-participating centers due to implementation of updated CACFP meal patterns over a 21-month period. Eight hundred and fifty-eight centers located in 47 states and the District of Columbia completed a survey (primarily electronic) at both time points (67.6% follow-up response rate). Multivariable logistic regressions with robust standard errors assessed changes over time, accounting for repeated observations within each site. From baseline to follow-up, centers reported the increased familiarity and implementation, albeit with time, money, and staffing-related challenges. Significant improvements were seen in not serving sugary cereals or flavored milk, in serving 100% whole grains, and serving processed meats less than once a week. While CACFP-participating centers reported making significant progress in meeting the updated meal pattern standards and suggested best practices within 15&ndash, 19 months of their effective date, reported compliance and adherence to the standards and best practices was not universal. USDA, state agencies, and technical assistance providers should work to provide centers with additional guidance to help them with implementation.

Background: Circadian and ultradian rhythms in BG have been observed in individuals without diabetes and are regulated both by time of day and meal intake, with ultradian fluctuations generally of smaller amplitude than circadian fluctuations. We assessed relative stability of circadian and ultradian rhythms in individuals without T1D (n=16), and individuals with T1D using two different therapies: sensor-augmented pump therapy (SAPT, n=100) and DIY closed loop (n=30). Methods: Frequency decomposition using continuous morlet wavelet transformation (A to C) were created to assess change in rhythmic composition of normalized blood glucose data. Results: Example Wavelet (C) in T1D illustrates high power in the 1-6H range, and lower power in the ~24H range for nearly all time points. The ratio of power in the 23-25H (circadian) range to power in the 1-6H (ultradian) range was calculated to estimate relative stability of circadian to ultradian rhythms. Those without T1D showed higher circadian compared to ultradian power, whereas both groups with T1D showed a comparably lower ratio (D). Conclusion: Wavelet analysis of BG in individuals with and without T1D reveals a difference in relative strength of daily and hourly rhythms, independent of therapy type. These results suggest current therapies do not recreate expected daily rhythmicity in blood glucose, perhaps due the lifespan of rapid-acting insulin and meal patterns. Disclosure D.M. Lewis: Research Support; Self; JDRF. A.D. Grant: None. L. Kriegsfeld: None. Funding JDRF