Search

Foods consumed at lower eating rates (ER) lead to reductions in energy intake. Previous research has shown that texture-based differences in eating rateER can reduce meal size. The effect size and consistency of these effects across a wide range of composite and complex meals differing considerably in texture and varying in meal occasion have not been reported. We determined how consistently texture-based differences in ER can influence food and energy intake across a wide variety of meals. In a crossover design, healthy participants consumed twelve breakfast and twelve lunch meals that differed in texture to produce a fast or slow ER. A breakfast group (n = 15) and lunch group (n = 15) completed twelve ad libitum meal sessions each (six 'fast' and six 'slow' meals), where intake was measured and behavioural video annotation was used to characterise eating behaviour. Liking did not differ significantly between fast and slow breakfasts (P = 0·44) or lunches (P = 0·76). The slow meals were consumed on average 39 % ± 9 % (breakfast) and 45 % ± 7 % (lunch) slower than the fast meals (both P < 0·001). Participants consumed on average 22 % ± 5 % less food (84 g) and 13 % ± 6 % less energy (71 kcal) from slow compared with fast meals (mean ± SE; P < 0·001). Consuming meals with a slower ER led to a reduction in food intake, where an average decrease of 20 % in ER produced an 11 % ± 1 % decrease in food intake (mean ± SE). These findings add to the growing body of evidence showing that ER can be manipulated using food texture and that this has aits consistent effect on food and energy intake across a wide variety of Hedonically equivalent meals. [ABSTRACT FROM AUTHOR]

Objectives: Maintaining an appropriate gestational weight gain (GWG) is essential for a safe pregnancy and delivery. This study aimed to determine the association between the habit of eating quickly and the risk of excessive GWG. Methods: We administered a questionnaire on eating habits to 1246 pregnant Japanese women in their second to third trimesters. We categorized the participants into three groups according to their answers to the question ?Do you eat quickly?? Group 1, ?always? or ?usually?; Group 2, ?sometimes?; and Group 3, ?rarely? or ?never.? We assessed GWG according to the ?The Optimal Weight Gain Chart? (Ministry of Health, Labor and Welfare, Japan), and those who exceeded the criteria were considered ?excessive.? Logistic regression analysis was performed with the risk of excess GWG as the dependent variable and quick food intake as the independent variable, to obtain relevant odds ratios (ORs) and 95% confidence intervals (CIs). Model 1 was unadjusted, and Model 2 was adjusted for age, prepregnancy body mass index, energy intake, mother's educational attainment, household income, exercise habits, and childbearing experience. Results: The OR (95% CI) for Groups 2 and 3 in Model 1, compared with Group 1, was 0.80 (0.62?1.05) and 0.61 (0.43?0.88), respectively (p for trend?=?0.047). In Model 2, the OR (95% CI) for Groups 2 and 3 were 0.73 (0.55?0.96) and 0.59 (0.40?0.86), respectively (p for trend?=?0.003). Conclusion: These results suggest that quick food ingestion increases the risk of excessive GWG.

Food-based dietary guidelines have been the basis of public health recommendations for over half a century, but more recently, there has been a trend to classify the health properties of food not by its nutrient composition, but by the degree to which it has been processed. This concept has been supported by many association studies, narrative reviews and the findings from one randomised controlled feeding trial, which demonstrated the sustained effect of ultra-processed diets on increasing both energy intake and body weight. This has led to widespread speculation as to specific features of ultra-processed foods that promote increased energy intakes. Rising interest in the ultra-processed topic has led to proposals to include guidance and restrictions on the consumption of processed foods in national dietary guidelines, with some countries encouraging consumers to avoid highly processed foods completely, and only choose minimally processed foods. However, there remains a lack of consensus on the role of processed foods in human health when faced with the challenges of securing the food supply for a growing global population, that is, healthy, affordable and sustainable. There has also been criticism of the subjective nature of definitions used to differentiate foods by their degree of processing, and there is currently a lack of empirical data to support a clear mechanism by which highly processed foods promote greater energy intakes. Recommendations to avoid all highly processed foods are potentially harmful if they remove affordable sources of nutrients and will be impractical for most when an estimated two-thirds of current energy purchased are from processed or ultra-processed foods. The current review highlights some considerations when interpreting the dietary association studies that link processed food intake to health and offers a critique on some of the mechanisms proposed to explain the link between ultra-processed food and poor health. Recent research suggests a combination of higher energy density and faster meal eating rates are likely to influence meal size and energy intakes from processed foods and offers new perspectives on how to manage this in the future. In going beyond the ultra-processed debate, the aim is to summarise some important considerations when interpreting existing data and identify the important gaps for future research on the role of processed food in health. [ABSTRACT FROM AUTHOR]

Most intake models for dairy cows have been developed to make predictions under normal conditions, in which animals can meet their nutritional requirements. To estimate intake under constraining conditions, i.e. when intake is defined by the environment and not by the animal’s requirements, it is necessary to develop models that take into account environmentally driven effects. The aim of this work was to develop a framework to represent the links between environmental variables (food quality and quantity, as well as ambient temperature, season, and farm type) and intake. The framework integrates time as the major constraint on intake and proposes the environmentally attainable intake (EAI) as the product of the Eating Rate (ER) and the Eating Time (ET). ER is the maximum sustainable rate (gr DM/min) at which animals bite the food, and ET is the daily time (min/d) that animals have to eat. The architecture of the framework is easily extensible to add constraints such as predation pressure, reproductive costs, competition, parasitism, or diseases. Data from grazing and indoor dairy farms were used to test the usability of the framework. The results show that a time use-based framework is a reliable approach to estimate intake considering environmental variables with minimum use of animals’ characteristics. In conclusion, a high-level framework of feeding behaviour, that captures the main underlying mechanisms of intake in constrained environments, can be used to predict the EAI and the effects of the environment on animal performance.

IntroductionObservational coding of eating behaviors (e.g., bites, eating rate) captures behavioral characteristics but is limited in its ability to capture dynamic patterns (e.g., temporal changes) across a meal. While the Universal Eating Monitor captures dynamic patterns of eating through cumulative intake curves, it is not commonly used in children due to strict behavioral protocols. Therefore, the objective of this study was to test the ability of computational models to characterize cumulative intake curves from video-coded meals without the use of continuous meal weight measurement.MethodsCumulative intake curves were estimated using Kisslieff’s Quadratic model and Thomas’s logistic ordinary differential equation (LODE) model. To test if cumulative intake curves could be characterized from video-coded meals, three different types of data were simulated: (1) Constant Bite: simplified cumulative intake data; (2) Variable Bite: continuously measured meal weight data; and (3) Bite Measurement Error: video-coded meals that require the use of average bite size rather than measured bite size.ResultsPerformance did not differ by condition, which was assessed by examining model parameter recovery, goodness of fit, and prediction error. Therefore, the additional error incurred by using average bite size as one would with video-coded meals did not impact the ability to accurately estimate cumulative intake curves. While the Quadratic and LODE models were comparable in their ability to characterize cumulative intake curves, the LODE model parameters were more distinct than the Quadradic model. Greater distinctness suggests the LODE model may be more sensitive to individual differences in cumulative intake curves.DiscussionCharacterizing cumulative intake curves from video-coded meals expands our ability to capture dynamic patterns of eating behaviors in populations that are less amenable to strict protocols such as children and individuals with disordered eating. This will improve our ability to identify patterns of eating behavior associated with overconsumption and provide new opportunities for treatment.

Background Consumption of ultra-processed foods has been linked with higher energy intakes. Food texture is known to influence eating rate (ER) and energy intake to satiation, yet it remains unclear whether food texture influences energy intakes from minimally processed and ultra-processed meals. Objectives We examined the independent and combined effects of food texture and degree of processing on ad libitum food intake. We also investigated whether differences in energy intake during lunch influenced postmeal feelings of satiety and later food intake. Methods In this crossover study, 50 healthy-weight participants [ n  = 50 (24 men); mean ± SD age: 24.4 ± 3.1 y; BMI: 21.3 ± 1.9 kg/m2] consumed 4 ad libitum lunch meals consisting of "soft minimally processed," "hard minimally processed," "soft ultra-processed," and "hard ultra-processed" components. Meals were matched for total energy served, with some variation in meal energy density (±0.20 kcal/g). Ad libitum food intake (kcal and g) was measured and ER derived using behavioral coding of videos. Subsequent food intake was self-reported by food diary. Results There was a main effect of food texture on intake, whereby "hard minimally processed" and "hard ultra-processed" meals were consumed slower overall, produced a 21% and 26% reduction in food weight (g) and energy (kcal) consumed, respectively. Intakes were higher for "soft ultra-processed" and "soft minimally processed" meals (P  < 0.001), after correcting for meal pleasantness. The effect of texture on food weight consumed was not influenced by processing levels (weight of food: texture*processing-effect, P  = 0.376), but the effect of food texture on energy intake was (energy consumed: texture*processing-effect, P  = 0.015). The least energy was consumed from the "hard minimally processed" meal (482.9 kcal; 95% CI: 431.9, 531.0 kcal) and the most from the "soft ultra-processed" meal (789.4 kcal; 95% CI: 725.9, 852.8 kcal; Δ=↓∼300 kcal). Energy intake was lowest when harder texture was combined with the "minimally processed" meals. Total energy intake across the day varied directly with energy intakes of the test meals (Δ15%, P  < 0.001). Conclusions Findings suggest that food texture–based differences in ER and meal energy density contribute to observed differences in energy intake between minimally processed and ultra-processed meals. This trial was registered at clinicaltrials.gov as NCT04589221. [ABSTRACT FROM AUTHOR]

BackgroundA fast rate of eating is associated with a higher risk for obesity but existing studies are limited by reliance on self-report and the consistency of eating rate has not been examined across all meals in a day. The goal of the current analysis was to examine associations between meal duration, rate of eating, and body mass index (BMI) and to assess the variance of meal duration and eating rate across different meals during the day.MethodsUsing an observational cross-sectional study design, non-smoking participants aged 18–45 years (N = 29) consumed all meals (breakfast, lunch, and dinner) on a single day in a pseudo free-living environment. Participants were allowed to choose any food and beverages from a University food court and consume their desired amount with no time restrictions. Weighed food records and a log of meal start and end times, to calculate duration, were obtained by a trained research assistant. Spearman's correlations and multiple linear regressions examined associations between BMI and meal duration and rate of eating.ResultsParticipants were 65% male and 48% white. A shorter meal duration was associated with a higher BMI at breakfast but not lunch or dinner, after adjusting for age and sex (p = 0.03). Faster rate of eating was associated with higher BMI across all meals (p = 0.04) and higher energy intake for all meals (p < 0.001). Intra-individual rates of eating were not significantly different across breakfast, lunch, and dinner (p = 0.96).ConclusionShorter beakfast and a faster rate of eating across all meals were associated with higher BMI in a pseudo free-living environment. An individual's rate of eating is constant over all meals in a day. These data support weight reduction interventions focusing on the rate of eating at all meals throughout the day and provide evidence for specifically directing attention to breakfast eating behaviors.

Liang Ding,1 Jianjun Yin,2 Wenbo Zhang,3 Ziqiang Wu,4 Shulei Chen4 1Department of Physical Education, Southeast University, Nanjing, People’s Republic of China; 2Department of Physical Education, Guangdong University of Finance and Economics, Guangzhou, People’s Republic of China; 3Department of Physical Education, Changchun Institute of Education, Changchun, People’s Republic of China; 4Department of Physical Education, Dalian Institute of Science and Technology, Dalian, People’s Republic of ChinaCorrespondence: Liang DingDepartment of Physical Education, Southeast University, 2 Sipailou, Nanjing 210009, People’s Republic of ChinaEmail dlseu1980@163.comPurpose: Poor eating behaviors are associated with imbalances in energy and food intake, which may directly or indirectly contribute to muscle strength loss. This study aimed to investigate the association between eating behaviors and hand grip strength in Chinese adults.Materials and Methods: We designed and conducted a cross-sectional study of 2009 Chinese individuals aged 25– 65 years in 2017. Eating behaviors, including breakfast consumption, snacking after dinner, and eating rate, were assessed using a self-administered questionnaire. Hand grip strength was assessed using a digital grip dynamometer. Age, sex, BMI, physical activity, educational level, occupation, living status, sleep duration, smoking and drinking status, hypertension, diabetes, and depressive symptoms were used as confounding factors.Results: After final adjustments for confounding factors, grip strength was measured as 35.2 (95% confidence interval [CI]: 34.7– 35.8), 36.0 (95% CI: 35.6– 36.4), and 36.9 (95% CI: 36.6– 37.3) for those who skipped, occasionally ate, and regularly ate breakfast, respectively (p for trend < 0.001). Those who always, sometimes, and seldom snacked after dinner (p for trend < 0.001) reported the following grip strength: 34.7 (95% CI: 34.0– 35.3), 36.2 (95% CI: 35.8– 36.6), and 36.9 (95% CI: 36.6– 37.2), respectively. Significant associations were not found between eating rate and grip strength.Conclusion: This study showed that higher frequency of breakfast consumption and lower frequency of snacking after dinner were associated with higher grip strength in Chinese adults. Therefore, eating behaviors may be involved in muscle function.Keywords: breakfast consumption, eating rate, snacking after dinner, grip strength, adult population

Abstract Background Eating rate is a basic determinant of appetite regulation: people who eat more slowly feel sated earlier and eat less. A high eating rate contributes to overeating and potentially to weight gain. Previous studies showed that an augmented fork that delivers real-time feedback on eating rate is a potentially effective intervention to decrease eating rate in naturalistic settings. This study assessed the impact of using the augmented fork during a 15-week period on eating rate and body weight. Methods In a parallel randomized controlled trial, 141 participants with overweight (age: 49.2 ± 12.3 y; BMI: 31.5 ± 4.48 kg/m2) were randomized to intervention groups (VFC, n = 51 or VFC+, n = 44) or control group (NFC, n = 46). First, we measured bite rate and success ratio on five consecutive days with the augmented fork without feedback (T1). The intervention groups (VFC, VFC+) then used the same fork, but now received vibrotactile feedback when they ate more than one bite per 10 s. Participants in VFC+ had additional access to a web portal with visual feedback. In the control group (NFC), participants ate with the fork without either feedback. The intervention period lasted four weeks, followed by a week of measurements only (T2) and another measurement week after eight weeks (T3). Body weight was assessed at T1, T2, and T3. Results Participants in VFC and VFC+ had a lower bite rate (p

Consuming foods with a form or a texture that requires longer oral processing is a way to decrease food intake. Although this approach is promising for leveraging healthier eating patterns in adults, it has never been explored in children. This study evaluated whether starting a mid-afternoon snack by eating either apple segments or applesauce would modify hunger and subsequent food intake during this meal. Forty-four children (8–10 years old) participated in two videotaped mid-afternoon snacks, during which they received one of the two forms of apple as a food preload followed 10 min later by ad libitum consumption of sweetened cottage cheese. They self-reported their level of hunger throughout consumption, and the weight of cottage cheese consumed was determined at the end of the snack. Children's chewing capabilities and eating traits were parent-reported. Eating a raw apple increased oral exposure time and decreased bite size compared to eating applesauce. However, neither the reported hunger nor consecutive food intake were modified. Regardless of the meal, children eating fast had a higher ad libitum energy intake. The individual eating rate for the cottage cheese was correlated with the eating rate observed for applesauce but not for apple segments, the latter being associated with children's chewing difficulties. This study suggests that the form of a fruit offered at the start of a mid-afternoon snack does not impact food intake; the findings clearly call for more exploration of satiation mechanisms related to food texture properties among children and indicate the need to consider children's oral processing skills.

Abstract Background Slowing eating rate using the Mandolean® previously helped obese adolescents to self-select smaller portion sizes, with no reduction in satiety, and enhanced ghrelin suppression. The objective of this pilot, randomised trial was to investigate the neural response to food cues following Mandolean® training using functional Magnetic Resonance Imaging (fMRI), and measures of ghrelin, PYY, glucose and self-reported appetite. Method Twenty-four obese adolescents (11–18 years; BMI ≥ 95th centile) were randomised (but stratified by age and gender) to receive six-months of standard care in an obesity clinic, or standard care plus short-term Mandolean® training. Two fMRI sessions were conducted: at baseline and post-intervention. These sessions were structured as an oral glucose tolerance test, with food cue-reactivity fMRI, cannulation for blood samples, and appetite ratings taken at baseline, 30 (no fMRI), 60 and 90 min post-glucose. As this was a pilot trial, a conservative approach to the statistical analysis of the behavioural data used Cliff’s delta as a non-parametric measure of effect size between groups. fMRI data was analysed using non-parametric permutation analysis (RANDOMISE, FSL). Results Following Mandolean® training: (i) relatively less activation was seen in brain regions associated with food cue reactivity after glucose consumption compared to standard care group; (ii) 22% reduction in self-selected portion size was found with no reduction in post-meal satiety. However, usage of the Mandolean® by the young people involved was variable and considerably less than planned at the outset (on average, 28 meals with the Mandolean® over six-months). Conclusion This pilot trial provides preliminary evidence that Mandolean® training may be associated with changes in how food cues in the environment are processed, supporting previous studies showing a reduction in portion size with no reduction in satiety. In this regard, the study supports targeting eating behaviour in weight-management interventions in young people. However, given the variable usage of the Mandolean® during the trial, further work is required to design more engaging interventions reducing eating speed. Trial registration ISRCTN, ISRCTN84202126, retrospectively registered 22/02/2018.

Background Longer oral processing decreases food intake. This can be attributed to greater oro-sensory exposure (OSE) and a lower eating rate (ER). How these factors contribute to food intake, and the underlying physiological mechanisms, remain unclear. Objectives We aimed to determine the independent and simultaneous effects of OSE and ER on satiation and associated endocrine responses. Methods Forty participants in study 1 [mean ± SD age: 24 ± 4 y; BMI (in kg/m2): 22 ± 2] and 20 in study 2 (mean ± SD age: 23 ± 3 y; BMI: 23 ± 2) participated in a 2 × 2 randomized trial. In both studies, participants ate chocolate custard with added caramel sauce (low OSE) or caramel fudge (high OSE) and with short (fast ER) or long breaks (slow ER) in between bites, until fullness. In study 2, endocrine responses were measured during the meal. Results In study 1, participants ate (mean ± SEM) 42 ± 15 g less in the slow- than in the fast-ER condition, only within the high-OSE condition (P  = 0.04). In study 2, participants ate 66 ± 21 g less in the high- than in the low-OSE condition and there were no intake differences between slow and fast ER (P  = 0.35). Eight minutes after starting to eat, insulin concentrations increased by 42%–65% in all treatments compared with the control. At the end of the meal, insulin concentrations were 81% higher in the high-OSE, slow-ER than in the low-OSE, fast-ER condition (P  = 0.049). Pancreatic polypeptide (PP) increased by 62%, 5 min after meal onset in the low-OSE, fast-ER condition (P  = 0.005). Ghrelin concentrations did not change. Conclusions Greater OSE increases insulin responsiveness. In contrast, PP responses are stronger when OSE is reduced and ER is fast. Insulin and PP responses may mediate the independent effects of OSE and ER on food intake. These may be beneficial eating strategies, particularly for type 2 diabetic patients, to control food intake and maintain glucose homeostasis. This trial was registered at trialregister.nl as NL6544. [ABSTRACT FROM AUTHOR]

Objective: Treatment of paediatric obesity focuses on changes of nutrition and eating behaviour and physical activity. The evaluation of the patient education programme by KgAS was utilised to analyse the association of changes of portion size, eating rate and dietary habits with BMI-SDS reductions. Methods: Patients (n = 297) were examined at the beginning and at the end of treatment and after 1-year follow-up at different out-patient centres. Their parents completed questionnaires including estimation of children's portion size, eating rate and frequency of food intake. Associations of 1- and 2-year changes in BMI-SDS and behaviour were calculated for patients with complete data in BMI-SDS, portion size, eating rate, frequency of green, yellow and red food intake (n = 131) by multiple linear regression models. Results: Significant changes were found in the desired direction for BMI-SDS, portion size, eating rate and the intake of unfavourable red food items both after 1 and 2 years as well as for the consumption of favourable green food items after 1 year. Significant positive associations with BMI-SDS reduction after 1 and 2 years were detected for portion size (Cohen's f2 0.13 and 0.09) and eating rate (Cohen's f2 0.20 and 0.10), respectively. Conclusion: Reduced portion sizes and eating rates are associated with BMI-SDS reduction after 1 and 2 years. These findings suggest to focus on appropriate portion sizes and reduced eating rates in patient education programmes.

Background and Objectives: The relationship between eating rate (ER) and increased risk of obesity in relation to body mass index (BMI, i.e., total body fat) and waist circumference (WC, i.e., abdominal fat) has not been fully examined. Considering gender differences, we identified unknown confounding factors (CFs) for each risk, and then assessed the two actual obesity risks, adjusting for the CFs.Methods and Study Design: Using a questionnaire, we collected data for ER (slow, normal as "reference," and fast) and related factors and measured BMI and WC for 3,393 men and 2,495 women. Using multiple logistic regression models, odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated adjusting for both conventional and candidate CFs.Results: The following factors were identified as appropriate CFs, but were differed between the two obesity types: fast food consumption in both genders, sleep duration and restaurants/food service use in men, and family structure and packed lunch in women. In men, actual risks of BMI obesity and WC obesity were negatively associated with slow ER (ORs and 95% CIs; 0.70 and 0.52-0.96, and 0.69 and 0.50-0.96), but positively associated with fast ER (1.48 and 1.25-1.76, and 1.45 and 1.21-1.74). In women, those risks were positively related to fast ER (1.78 and 1.39-2.26, and 1.34 and 1.11-1.61).Conclusions: For both BMI obesity risk and WC obesity risk, we conclude that slow and fast ER were related to decreased and increased risks when adjusted for appropriate CFs, which differed by gender and the obesity type. [ABSTRACT FROM AUTHOR]

No integrated risk assessment tools that include lifestyle factors and uric acid have been developed. In accordance with the Industrial Safety and Health Law in Japan, a follow-up examination of 63 495 normotensive individuals (mean age 42.8 years) who underwent a health checkup in 2010 was conducted every year for 5 years. The primary endpoint was new-onset hypertension (systolic blood pressure [SBP]/diastolic blood pressure [DBP] ≥ 140/90 mm Hg and/or the initiation of antihypertensive medications with self-reported hypertension). During the mean 3.4 years of follow-up, 7402 participants (11.7%) developed hypertension. The prediction model included age, sex, body mass index (BMI), SBP, DBP, low-density lipoprotein cholesterol, uric acid, proteinuria, current smoking, alcohol intake, eating rate, DBP by age, and BMI by age at baseline and was created by using Cox proportional hazards models to calculate 3-year absolute risks. The derivation analysis confirmed that the model performed well both with respect to discrimination and calibration (n = 63 495; C-statistic = 0.885, 95% confidence interval [CI], 0.865-0.903; χ2 statistic = 13.6, degree of freedom [df] = 7). In the external validation analysis, moreover, the model performed well both in its discrimination and calibration characteristics (n = 14 168; C-statistic = 0.846; 95%CI, 0.775-0.905; χ2 statistic = 8.7, df = 7). Adding LDL cholesterol, uric acid, proteinuria, alcohol intake, eating rate, and BMI by age to the base model yielded a significantly higher C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement, especially NRInon-event (NRI = 0.127, 95%CI = 0.100-0.152; NRInon-event  = 0.108, 95%CI = 0.102-0.117). In conclusion, a highly precise model with good performance was developed for predicting incident hypertension using the new parameters of eating rate, uric acid, proteinuria, and BMI by age. [ABSTRACT FROM AUTHOR]

Objective: Treatment of paediatric obesity focuses on changes of nutrition and eating behaviour and physical activity. The evaluation of the patient education programme by KgAS was utilised to analyse the association of changes of portion size, eating rate and dietary habits with BMI-SDS reductions. Methods: Patients (n = 297) were examined at the beginning and at the end of treatment and after 1-year follow-up at different out-patient centres. Their parents completed questionnaires including estimation of children's portion size, eating rate and frequency of food intake. Associations of 1- and 2-year changes in BMI-SDS and behaviour were calculated for patients with complete data in BMI-SDS, portion size, eating rate, frequency of green, yellow and red food intake (n = 131) by multiple linear regression models. Results: Significant changes were found in the desired direction for BMI-SDS, portion size, eating rate and the intake of unfavourable red food items both after 1 and 2 years as well as for the consumption of favourable green food items after 1 year. Significant positive associations with BMI-SDS reduction after 1 and 2 years were detected for portion size (Cohen's f2 0.13 and 0.09) and eating rate (Cohen's f2 0.20 and 0.10), respectively. Conclusion: Reduced portion sizes and eating rates are associated with BMI-SDS reduction after 1 and 2 years. These findings suggest to focus on appropriate portion sizes and reduced eating rates in patient education programmes. [ABSTRACT FROM AUTHOR]

Faster eating has been identified as a risk factor for obesity and the current study tested whether eating rate is consistent within an individual and linked to energy intake across multiple meals. Measures of ad libitum intake, eating rate, and oral processing at the same or similar test meal were recorded on four non-consecutive days for 146 participants (117 male, 29 female) recruited across four separate studies. All the meals were video recorded, and oral processing behaviours were derived through behavioural coding. Eating behaviours showed good to excellent consistency across the meals (intra-class correlation coefficients > 0.76, p < 0.001) and participants who ate faster took larger bites (β ≥ 0.39, p < 0.001) and consistently consumed more energy, independent of meal palatability, sex, body composition and reported appetite (β ≥ 0.17, p ≤ 0.025). Importantly, eating faster at one meal predicted faster eating and increased energy intake at subsequent meals (β > 0.20, p < 0.05). Faster eating is relatively consistent within individuals and is predictive of faster eating and increased energy intake at subsequent similar meals consumed in a laboratory context, independent of individual differences in body composition. [ABSTRACT FROM AUTHOR]

Background: Large portions and high dietary energy density promote overconsumption at meal times. This could be reduced by eating slowly.Objective: Two studies investigated whether texture-based reductions in eating rate and oral processing moderate consumption at breakfast in combination with variations in energy density and portion size.Methods: Adults attended 4 breakfast sessions (2 × 2 repeated-measures design) to consume rice porridge, combining a 45% reduction in eating rate [thin porridge (140 g/min) compared with thick porridge (77 g/min)] with a 77% increase in energy density (0.57 compared with 1.01 kcal/g) in study 1 [n = 61; aged 21-48 y; body mass index (BMI; in kg/m2): 16-29] and a 50% increase in portion size (100% compared with 150%) in study 2 (n = 53; aged 21-42 y; BMI: 16-29). Oral processing behaviors were coded by using webcams. Porridge intake was measured alongside changes in rated appetite.Results: Increases in energy density and portion size led to increases of 80% and 13% in energy intake at breakfast, respectively (P < 0.001), but only portion size increased the weight of food consumed (13%). The thicker porridges were consumed at a slower rate and led to 11-13% reductions in food weight and energy intake compared with the thin versions (P < 0.001). Combined, the least energy was consumed when the thick "slow" porridge was served with a lower energy density or smaller portion (P < 0.05). Although intake was reduced for the thick porridges, they were expected to be more filling than the thin versions and experienced as equally satiating postconsumption.Conclusions: Adults eat in response to external features of the food environment. An opportunity exists to use a combination of energy-density dilution, smaller portions, and natural variations in food texture to design meals that promote reductions in energy intake while maintaining satiety. [ABSTRACT FROM AUTHOR]

Faster eating rates are associated with increased energy intake, but little is known about the relationship between children’s eating rate, food intake and adiposity. We examined whether children who eat faster consume more energy and whether this is associated with higher weight status and adiposity. We hypothesised that eating rate mediates the relationship between child weight and ad libitum energy intake. Children (n 386) from the Growing Up in Singapore Towards Healthy Outcomes cohort participated in a video-recorded ad libitum lunch at 4·5 years to measure acute energy intake. Videos were coded for three eating-behaviours (bites, chews and swallows) to derive a measure of eating rate (g/min). BMI and anthropometric indices of adiposity were measured. A subset of children underwent MRI scanning (n 153) to measure abdominal subcutaneous and visceral adiposity. Children above/below the median eating rate were categorised as slower and faster eaters, and compared across body composition measures. There was a strong positive relationship between eating rate and energy intake (r 0·61, P<0·001) and a positive linear relationship between eating rate and children’s BMI status. Faster eaters consumed 75 % more energy content than slower eating children (Δ548 kJ (Δ131 kcal); 95 % CI 107·6, 154·4, P<0·001), and had higher whole-body (P<0·05) and subcutaneous abdominal adiposity (Δ118·3 cc; 95 % CI 24·0, 212·7, P=0·014). Mediation analysis showed that eating rate mediates the link between child weight and energy intake during a meal (b 13·59; 95 % CI 7·48, 21·83). Children who ate faster had higher energy intake, and this was associated with increased BMI z-score and adiposity. [ABSTRACT FROM PUBLISHER]

• Time and eating speed limit intake in constraining environments. • Attainable intake depends on food, temperature, season, and farm type. • Framework easily expands for more constraints. • Intake estimation with minimal use of animal characteristics, tested with data. • Tool can improve breeding programmes and evaluate management strategies for constraining environments. Most intake models for dairy cows have been developed to make predictions under normal conditions, in which animals can meet their nutritional requirements. To estimate intake under constraining conditions, i.e. when intake is defined by the environment and not by the animal's requirements, it is necessary to develop models that take into account environmentally driven effects. The aim of this work was to develop a framework to represent the links between environmental variables (food quality and quantity, as well as ambient temperature, season, and farm type) and intake. The framework integrates time as the major constraint on intake and proposes the environmentally attainable intake (EAI) as the product of the Eating Rate (ER) and the Eating Time (ET). ER is the maximum sustainable rate (gr DM/min) at which animals bite the food, and ET is the daily time (min/d) that animals have to eat. The architecture of the framework is easily extensible to add constraints such as predation pressure, reproductive costs, competition, parasitism, or diseases. Data from grazing and indoor dairy farms were used to test the usability of the framework. The results show that a time use-based framework is a reliable approach to estimate intake considering environmental variables with minimum use of animals' characteristics. In conclusion, a high-level framework of feeding behaviour, that captures the main underlying mechanisms of intake in constrained environments, can be used to predict the EAI and the effects of the environment on animal performance. [ABSTRACT FROM AUTHOR]

Improvement of reproduction in dairy cows has become a major challenge in dairy production. We have recently shown that dairy cows carrying the ‘fertil−’ haplotype for one quantitative trait locus (QTL), affecting female fertility and located on the bovine chromosome 3, had a significantly lower conception rate after the first artificial insemination than cows carrying the ‘fertil+’ haplotype. The objective of this paper was to study other phenotypic modifications linked to this QTL. In the present study, 23 ‘fertil+’ and 18 ‘fertil−’ cows were characterized for live weight, milk production, food intake, eating behaviour and plasma metabolites. These parameters were measured during the first lactation, from calving to 40 weeks postpartum (wkpp). In the first 7 weeks of lactation, ‘fertil+’ primiparous cows had a significantly higher live BW and milk production than ‘fertil−’ cows. Dry matter intake tended to be slightly higher for ‘fertil+’ than for ‘fertil−’ primiparous cows in this period. However, energy balance was similar for the two haplotypes in the whole lactation, except in the first wkpp, and consequently, could not explain their different fertility. The major observation concerned the eating behaviour. ‘Fertil+’ primiparous cows had a significantly lower eating rate than ‘fertil−’ cows during the 40 weeks of lactation. In parallel, ‘fertil+’ cows spent significantly more time at the feeder for a similar number of visits than ‘fertil−’ cows. Furthermore, no differences in plasma concentrations of non-esterified fatty acids and insulin were observed between the two haplotypes. Plasma glucose was significantly lower in ‘fertil+’ than in ‘fertil−’ cows in the second wkpp. Taken together, our results show that ‘fertil+’ and ‘fertil−’ dairy cows, with different fertility, have also different eating behaviour without any variation in energy balance, except in the first week of lactation.

Epidemiologic evidence supports a positive association between ultraprocessed food (UPF) consumption and body mass index. This has led to recommendations to avoid UPFs despite very limited evidence establishing causality. Many mechanisms have been proposed, and this review critically aimed to evaluate selected possibilities for specificity, clarity, and consistency related to food choice (i.e., low cost, shelf-life, food packaging, hyperpalatability, and stimulation of hunger/suppression of fullness); food composition (i.e., macronutrients, food texture, added sugar, fat and salt, energy density, low-calorie sweeteners, and additives); and digestive processes (i.e., oral processing/eating rate, gastric emptying time, gastrointestinal transit time, and microbiome). For some purported mechanisms (e.g., fiber content, texture, gastric emptying, and intestinal transit time), data directly contrasting the effects of UPF and non-UPF intake on the indices of appetite, food intake, and adiposity are available and do not support a unique contribution of UPFs. In other instances, data are not available (e.g., microbiome and food additives) or are insufficient (e.g., packaging, food cost, shelf-life, macronutrient intake, and appetite stimulation) to judge the benefits versus the risks of UPF avoidance. There are yet other evoked mechanisms in which the preponderance of evidence indicates ingredients in UPFs actually moderate body weight (e.g., low-calorie sweetener use for weight management; beverage consumption as it dilutes energy density; and higher fat content because it reduces glycemic responses). Because avoidance of UPFs holds potential adverse effects (e.g., reduced diet quality, increased risk of food poisoning, and food wastage), it is imprudent to make recommendations regarding their role in diets before causality and plausible mechanisms have been verified., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objectives: Maintaining an appropriate gestational weight gain (GWG) is essential for a safe pregnancy and delivery. This study aimed to determine the association between the habit of eating quickly and the risk of excessive GWG., Methods: We administered a questionnaire on eating habits to 1246 pregnant Japanese women in their second to third trimesters. We categorized the participants into three groups according to their answers to the question "Do you eat quickly?" Group 1, "always" or "usually"; Group 2, "sometimes"; and Group 3, "rarely" or "never." We assessed GWG according to the "The Optimal Weight Gain Chart" (Ministry of Health, Labor and Welfare, Japan), and those who exceeded the criteria were considered "excessive." Logistic regression analysis was performed with the risk of excess GWG as the dependent variable and quick food intake as the independent variable, to obtain relevant odds ratios (ORs) and 95% confidence intervals (CIs). Model 1 was unadjusted, and Model 2 was adjusted for age, prepregnancy body mass index, energy intake, mother's educational attainment, household income, exercise habits, and childbearing experience., Results: The OR (95% CI) for Groups 2 and 3 in Model 1, compared with Group 1, was 0.80 (0.62-1.05) and 0.61 (0.43-0.88), respectively ( p for trend = 0.047). In Model 2, the OR (95% CI) for Groups 2 and 3 were 0.73 (0.55-0.96) and 0.59 (0.40-0.86), respectively ( p for trend = 0.003)., Conclusion: These results suggest that quick food ingestion increases the risk of excessive GWG., Competing Interests: No competing financial interests exist., (© Eri Abe et al., 2023; Published by Mary Ann Liebert, Inc.)

Background: Reductions in eating rate have been recommended as potential behavioural strategies to prevent and treat overweight [1–4]. Unfortunately, eating rate is difficult to modify, due to its highly automatic nature [5]. Training people to eat more slowly in everyday eating contexts, therefore, requires creative and engaging solutions. Aim: The present study examines the efficacy of a smart fork that helps people to eat more slowly. This adapted fork records eating speed and delivers vibrotactile feedback if users eat too quickly. In two studies, we tested the acceptability and user experience of the fork (Study 1), and its effect on eating rate and satiety levels in a controlled lab-setting (Study 2). Method: In study 1, 11 participants (all self-reported fast eaters) ate a meal using the fork in our laboratory and used the fork for three consecutive days in their home setting. Participants took part in semi-structured interviews after the first meal and upon returning the fork, covering perceived effect on eating rate, comfort of use, accuracy, and motivational and social aspects of fork use. Interviews were coded and a thematic classification analysis was performed. In study 2, 128 participants (all self-reported fast eaters) ate a standardized meal using the fork in our laboratory. We used a between-participants design with 2 conditions; participants ate their meal either with vibrotactile feedback from the fork (experimental condition) or ate their meal without vibrotactile feedback (control condition). Eating rate, meal duration, error rate (number of bites taken faster than 10 seconds after previous bite), total food intake, and satiety were recorded for every participant. Results: Study 1: All participants felt that the feedback was generally accurate and consistent. Fork size, weight, and intensity of the feedback were seen as comfortable and acceptable. All participants reported a heightened awareness of eating rate and all but one participant reported eating more slowly with the fork. Study 2: Participants in the experimental condition ate significantly slower, and with a lower error rate than those in the control condition. Feedback did not significantly affect the amount of food eaten. Conclusions: Our findings suggest that this smart fork is an acceptable and effective tool to disrupt and decelerate eating rate. Participants find the fork comfortable and accurate enough for use in natural contexts, and experimental results show that the fork does influence eating rate, but not the amount of food consumed. Future research should test the long-term effects of fork use on eating rate to assess whether this smart fork indeed leads to sustainable behavioural change.

Background: Attempts to model cumulative intake curves with quadratic functions have not simultaneously taken gustatory stimulation, satiation, and maximal food intake into account. Objective: Our aim was to develop a dynamic model for cumulative intake curves that captures gustatory stimulation, satiation, and maximal food intake. Design: We developed a first-principles model describing cumulative intake that universally describes gustatory stimulation, satiation, and maximal food intake using 3 key parameters: 1) the initial eating rate, 2) the effective duration of eating, and 3) the maximal food intake. These model parameters were estimated in a study (n = 49) where eating rates were deliberately changed. Baseline data was used to determine the quality of model's fit to data compared with the quadratic model. The 3 parameters were also calculated in a second study consisting of restrained and unrestrained eaters. Finally, we calculated when the gustatory stimulation phase is short or absent. Results: The mean sum squared error for the first-principles model was 337.1 ± 240.4 compared with 581.6 ± 563.5 for the quadratic model, or a 43% improvement in fit. Individual comparison demonstrated lower errors for 94% of the subjects. Both sex (P = 0.002) and eating duration (P = 0.002) were associated with the initial eating rate (adjusted R² = 0.23). Sex was also associated (P = 0.03 and P = 0.012) with the effective eating duration and maximum food intake (adjusted R² = 0.06 and 0.11). In participants directed to eat as much as they could compared with as much as they felt comfortable with, the maximal intake parameter was approximately double the amount. The model found that certain parameter regions resulted in both stimulation and satiation phases, whereas others only produced a satiation phase. Conclusions: The first-principles model better quantifies interindividual differences in food intake, shows how aspects of food intake differ across subpopulations, and can be applied to determine how eating behavior factors influence total food intake. [ABSTRACT FROM AUTHOR]

In this study, we investigated the association between food form (mixed vs separated) and eating rate. The experiment used a within-subjects design (n=29, young healthy women with normal weight). Test meals (white rice and side dishes) with the same content and volume were served at lunch in a mixed or separated form. The form in which the food was served had significant effects on consumption volume and eating rate; subjects ate significantly more (p<0.05) when a test meal was served as a mixed form (285 g, 575 kcal) compared to a separated form (244 g, 492 kcal). Moreover, subjects also ate significantly faster (p<0.05) when the test meal was served as a mixed form (22.4 g/min) as compared to a separated form (16.2 g/min). Despite consuming more when the test meal was served as a mixed form than when served as a separated form, the subjects did not feel significantly fuller. In conclusion, we confirmed that meals served in a separated form might lower the eating rate and, moreover, slower eating might be associated with less energy intake, without compromising satiety. [ABSTRACT FROM AUTHOR]