Combined effect of eating speed instructions and food texture modification on eating rate, appetite and later food intake.

Modifying food texture and eating slowly each reduce appetite and energy intake. No study has evaluated the effect of combining these measures to slow eating speed and determine the effect on appetite. The aim of this study was to investigate whether there is a combined effect of manipulating oral processing behaviours (OPBs) in this manner on self-reported satiety and subsequent food intake. A 2 × 2 design was used with four breakfast conditions in total. Twenty-four participants attended four study visits where they were asked to consume one of two isocaloric fixed-portion breakfasts differing in texture: 1) granola with milk and 2) yogurt with muesli and conserve. Participants consumed each breakfast twice, with verbal instructions to chew slowly at one visit and at a normal rate at another. Consumption was video-recorded to behaviourally code OPBs. Participants completed visual analogue scales of self-reported appetite measures at the beginning of the test session, immediately prior to and immediately after breakfast consumption. They also completed a food diary documenting food intake for the remainder of the day. The breakfast designed to be eaten slowest (the harder-textured meal with instructions to eat slowly) was eaten at a slower rate, with a greater number of chews per bite and a slower bite rate (p < 0.001) compared to the other meals. No differences were observed between the breakfast conditions on subjective measures of post-prandial satiety, or subsequent energy or macronutrient consumption. Results of this study highlight that combined effects of texture and instructions are most effective at reducing eating rate, though eating slower was not shown to enhance post-meal satiety. Reduced eating speed has previously been shown to reduce ad-libitum energy intake. Future research should consider combined approaches to reduce eating speed, to mitigate the risk of overconsumption within meals.

Masticatory function after comprehensive dental treatment in children with severe early childhood caries.

BACKGROUND: Parents are frequently concerned that their child's mastication may be compromised after comprehensive dental treatment. AIM: To evaluate changes in masticatory function and food preferences after dental treatment in children with early childhood caries. DESIGN: This prospective study assessed masticatory function with the (1) mixing ability test using duo-coloured chewing gum and (2) the number of chews/g and time taken to eat six food items before and 3 months after dental treatment. A dental examination and a food preference questionnaire were also completed. RESULTS: Twenty-five children (age: 4.9 ± 0.5 years, baseline dmft/child: 11.4 ± 4.9) completed the study. The mean number of restorations/child, total extractions/child, and posterior extractions/child was 5.1 ± 2.9, 6.4 ± 5.2, and 3.6 ± 2.3, respectively. The number of chews/g of cereal (p = .014) and popcorn (p = .003) significantly increased after dental treatment. The number of chews/g and duration taken for cereal (chews/g: r = 0.795, p = .000, duration: r = 0.794, p = .000) and peanuts (chews/g: r = 0.459, p = .032) were significantly associated with more extractions. There was no change in mastication function for the other foods, mixing ability score, and child's food preferences after dental treatment. CONCLUSIONS: An increased number of chews/g is needed for certain hard foods after dental treatment, which was associated with an increased number of total and posterior extractions.

Increased oral processing and a slower eating rate increase glycaemic, insulin and satiety responses to a mixed meal tolerance test.

PURPOSE: Variations in specific oral processing behaviours may contribute to differences in glucose, insulin and satiety responses to a standardised test meal. This study tested how natural variations in oral processing between slower and faster eaters contribute to differences in post-prandial glucose (PP glucose), insulin response (PP insulin) and post-meal satiety for a standardised test meal. METHODS: Thirty-three participants with higher risk for type 2 diabetes consumed a standardised test-meal while being video recorded to derive specific oral processing behaviours. Plasma glucose, insulin and satiety measures were collected at baseline, during and post meal. Participants were split into slower and faster eaters using median split based on their eating rates and individual bolus properties were analysed at the point of swallow. RESULTS: There were large variations in eating rate (p < 0.001). While there was no significant difference in PP glucose response (p > 0.05), slower eaters showed significantly higher PP insulin between 45 and 60 min (p < 0.001). Slower eaters had longer oro-sensory exposure and increased bolus saliva uptake which was associated with higher PP glucose iAUC. Faster eating rate and larger bolus particle size at swallow correlated with lower PP glucose iAUC. A slower eating rate with greater chews per bite significantly increased insulin iAUC. Faster eaters also consistently rated their hunger and desire to eat higher than slower eaters (p < 0.05). CONCLUSIONS: Natural variations in eating rate and the associated oral processing contributed to differences in PP glucose, PP insulin and satiety responses. Encouraging increased chewing and longer oral-exposure time during consumption, may promote early glucose absorption and greater insulin and satiety responses, and help support euglycaemia. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04522063.

Associations between inhibitory control, eating behaviours and adiposity in 6-year-old children.

BACKGROUND: Lower inhibitory control has been associated with obesity. One prediction is that lower inhibitory control underlies eating behaviours that promote increased energy intakes. This study examined the relationships between children's inhibitory control measured using the Stop Signal Task (SST), body composition and eating behaviours, which included self-served portion size, number of servings, eating rate, and energy intake at lunch and in an eating in the absence of hunger (EAH) task. METHODS: The sample included 255 6-year-old children from an Asian cohort. Stop-signal reaction time (SSRT) was used as an index of inhibitory control. Children participated in a recorded self-served lunchtime meal, followed by the EAH task where they were exposed to energy-dense snacks. Behavioural coding of oral processing was used to estimate eating rates (g/min). BMI, waist circumference and skinfolds were used as indices of adiposity. RESULTS: Children with lower inhibitory control tended to self-serve larger food portions (p = 0.054), had multiple food servings (p = 0.006) and significantly faster eating rates (p = 0.041). Inhibitory control did not predict energy intake at lunch (p = 0.17) or during the EAH task (p = 0.45), and was unrelated to measures of adiposity (p > 0.32). Twenty percent of the children in the sample had problems focusing on the SST and were described as 'restless'. Post-hoc analysis revealed that these children had lower inhibitory control (p < 0.001) and consumed more energy during the EAH task (p = 0.01), but did not differ in any other key outcomes from the rest of the sample (p > 0.1). CONCLUSIONS: Children with lower inhibitory control showed a trend to select larger food portions, had multiple food servings and faster eating rates, but were equally as responsive to snacks served in the absence of hunger as children with better inhibitory control. Inhibitory control may impact a number of eating behaviours, not limited to energy-dense snacks.

Maternal feeding practices and children's food intake during an ad libitum buffet meal: Results from the GUSTO cohort.

Parents' feeding practices have been shown to be associated with children's food intake and weight status, but little is known about feeding practices in Asian countries. This study used behavioral observation to explore the feeding practices of 201 mothers of 4.5 year-old children in Singapore during an ad libitum buffet lunch. Feeding practices were coded from videos, focusing on behaviors used to prompt the child to eat more food (autonomy-supportive and coercive-controlling prompts to eat, suggesting items from buffet), those to reduce intake (restriction, questioning food choice), and those related to eating rate (hurrying or slowing child eating). Child outcome measures included energy consumed, variety of food items selected, and BMI. Maternal restriction and trying to slow child eating rate were associated with higher energy consumed by the child (r = 0.19 and 0.13, respectively; p < 0.05). Maternal autonomy-supportive prompts and restriction were associated with a greater variety of items selected by children (r = 0.19 and 0.15, respectively; p < 0.05). The frequency of maternal feeding practice use differed across ethnic groups, with Malay mothers using the most prompts to eat (p < 0.05), Chinese mothers most likely to question a child's food choice (p < 0.01), and Indian mothers the last likely to tell the child to eat faster (p < 0.001). There were no differences between ethnic groups for other feeding practices. No associations were found between feeding practices and child BMI. It is possible that feeding practices related to restriction and slowing child eating are adopted in response to children who consume larger portions, although longitudinal or intervention studies are needed to confirm the direction of this relationship and create local recommendations.

Prospective associations between parental feeding practices and children's oral processing behaviours.

Previous research demonstrated that faster eating rates are linked with increased intake of energy during a meal. Here, we examined whether within-meal parental feeding practices show cross-sectional and prospective associations with children's oral processing behaviours and whether the previously demonstrated association between faster eating rates and higher energy intakes varies by parental feeding practices. A subset (n = 155) of children and their mothers from the Growing Up in Singapore Towards healthy Outcomes cohort participated in an ad libitum meal at age 4.5 years. Children's oral processing behaviours (eating rate, bite size, chews per gram, oral exposure time, and meal duration) and parental feeding practices (autonomy-supporting and coercive prompts, restrictions, hurrying, and slowing) were recorded during the meal. Subsequently, 94 of the children participated in a follow-up meal without their mothers at age 6 years. Parental feeding practices were not consistently associated with child oral processing behaviours overall. However, exploratory post hoc analyses revealed some sex differences. The mothers of girls with faster eating rates, larger bite sizes, and fewer chews were more likely to use hurrying, slowing, and restrictions, but similar associations were not observed among boys. Children who had the most problematic eating style and were eating fast and for long experienced more restrictions, instructions to slow down, and prompts. Faster eating rates were linked with the highest energy intakes if children were additionally prompted to eat. Prospective analyses showed that children who were more often prompted using coercive techniques and less frequently hurried at age 4.5 years had faster eating rates at 6 years and a larger increase in eating rates between ages 4.5 and 6 years but did not consume more energy. Although the direction of these associations cannot be assumed, these exploratory analyses suggest sex differences in the associations between feeding practices and oral processing behaviours and highlight the potential role of parents in the development of children's oral processing behaviours.

Oral processing behaviours that promote children's energy intake are associated with parent-reported appetitive traits: Results from the GUSTO cohort.

Oral processing behaviours associated with faster eating rates have been consistently linked to increased energy intakes, but little is known about their links to children's appetitive traits. This study used the Child Eating Behaviour Questionnaire (CEBQ) to explore cross-sectional and prospective associations between parent-reported appetitive traits and observed oral processing behaviours. Participants were 195 children from the Growing Up in Singapore Towards healthy Outcomes cohort, who participated in a video-recorded ad libitum lunch at 4.5 (Time 1) and 6 years (Time 2). Their mothers completed the CEBQ around the same time points. Children's bites, chews and swallows were coded, and used to calculate their eating rate, bite size, chews per bite, chew rate, oral exposure time and oral exposure per bite. At Time 1, children with higher scores in slowness in eating had lower eating and chew rates. At Time 2, higher scores for food enjoyment and lower for satiety responsiveness, slowness in eating, and food fussiness were linked with higher eating rates and greater energy intakes (r > 0.16, p < 0.05). Post-hoc analyses revealed that these associations were moderated by BMI and only present among children with higher BMI. Faster eating rates mediated the associations between greater food enjoyment, lower slowness in eating, lower food fussiness and higher intakes of energy. Children with higher slowness in eating scores had lower increases in eating rates over time, and children with higher BMI who had greater food enjoyment and food responsiveness scores had greater increases in eating rates over time. The findings suggest that oral processing behaviours linked with increased obesity risk may be underpinned by appetitive traits and may be one of the behavioural pathways through which these appetitive traits influence energy intakes.

Faster eating rates are associated with higher energy intakes during an ad libitum meal, higher BMI and greater adiposity among 4·5-year-old children: results from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort.

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.

Associations between oral processing, saliva, and bolus properties on daily glucose excursions amongst people at risk of type-2 diabetes.

Background: A greater time spent with glucose above the normal range (TAR) has been associated with poorer glycaemic control amongst pre-diabetic individuals. Individual differences in oral processing behaviours and saliva amylase activity have been shown to influence glucose responses. Objective: The current study is a preliminary exploration of the associations of oral processing behaviours, bolus characteristics, and salivary amylase activity with the variability in daily glucose excursions within a free-living setting in populations with an elevated risk of type-2 diabetes. Method: Participant oral processing behaviour was derived from video recordings while they consumed a test meal. Post-meal bolus characteristics and saliva properties were measured. Participants were fitted with a continuous glucose monitor (CGM) which monitored blood glucose fluctuation over 7 consecutive free-living days. Dietary intake was recorded through a smartphone application and physical activity was monitored using a wrist worn accelerometer. Results: Participants varied in daily time spent with glucose above the normal range (>7.8 mmol l-1) from 0% to 15%. Greater saliva uptake in the bolus was associated with a higher time spent above the normal range for glucose (ß = 0.067 [95% CI = 0.015, 0.120]; p < 0.05), which remained significant after adjustment for dietary carbohydrate intake and BMI. Salivary amylase and saliva flow rate were not significantly associated with the time spent above the normal range. Conclusion: In addition to conventional dietary factors, more research is needed to understand how eating behaviours such as oro-sensory exposure, bolus surface area, and saliva uptake contribute to daily variations in postprandial glucose excursions among populations with a higher risk of developing type-2 diabetes.

Texture-based differences in eating rate influence energy intake for minimally processed and ultra-processed meals.

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.

Independent and combined impact of texture manipulation on oral processing behaviours among faster and slower eaters.

Background: Food texture can moderate eating rate and ad libitum energy intake. Many foods are combined with condiments when consumed and the texture and eating properties differ considerably between condiments and carrier foods. Little is known about how combinations of textures impact oral processing or whether these differences are affected by individual eating-styles. Objective: We investigated the impact of texture parameters (unit size, thickness, hardness and lubrication) on oral processing behaviours for carrots and rice-crackers, and tested whether these behaviours differ between 'faster' and 'slower' eaters. Method: Seventy participants (34 males, 26.0 ± 5.4 years, BMI = 21.5 ± 1.7 kg m-2) consumed 24 weight-matched carrot samples varying in unit size (large/medium/small), thickness (thick/thin), hardness (hard/soft) and lubrication (with/without mayonnaise). In a second step, participants consumed 8 weight-matched cracker samples varying in unit size (large/small), hardness (hard/soft) and lubrication (with/without mayonnaise). Sample consumption was video-recorded for post hoc behavioural annotation to derive specific oral processing behaviours. Participants were divided into 'faster' or 'slower' eater groups using a post hoc median split based on eating rate of raw carrot. Results: Across texture parameters, hardness had the largest influence (p < 0.001) on eating rate for both carrots and crackers. The independent texture differences for carrot ranked from most to least impact on eating rate was hardness > thickness > lubrication > unit size. For crackers, the rank order of eating rate was hardness > lubrication > unit size. Harder carrot samples with decreased unit size and reduced thickness combined had a larger synergistic effect in reducing eating rate (p < 0.001) than manipulation of any single texture parameter alone. Reducing the unit size of crackers while increasing hardness without lubrication combined (p = 0.015) to produce the largest reduction in eating rate. There were no significant differences between fast and slow eaters on their oral processing behaviours across texture manipulations. Conclusions: Combinations of texture manipulations have the largest impact in moderating oral processing behaviours, and this is consistent across 'faster' and 'slower' eaters. Changing food-texture presents an effective strategy to guide reformulation of product sensory properties to better regulate eating rate and energy intake, regardless of an individual's natural eating-style.

Impact of Individual Differences in Eating Rate on Oral Processing, Bolus Properties and Post-Meal Glucose Responses.

PURPOSE: Modifying food texture has been shown to influence oral processing behaviour. We explored the impact of food texture on oral processing, bolus formation and post-prandial glucose responses (PPG) among fast and slow eaters. METHODS: Male participants (N=39) were split into fast or slow eaters based on natural differences in eating rate when consuming two carbohydrate-equivalent test-meals differing in texture (white rice and rice cake). PPG and satiety responses were compared for fast and slow eaters over 120-min for each test-meal. Each groups test-meal PPG was compared for bolus and saliva properties at the point of swallow. RESULTS: White rice displayed lower instrumental hardness, chewiness and Young's modulus and was perceived less chewy, springy and sticky than rice cake. Slow eaters (n=24, white rice: 13.3 g/min; rice cake: 15.1 g/min) required an average 42% more chews per bite (p < 0.001), had 60% longer oral exposure time (OET), and consumed both test-meals (p < 0.001) at half the eating rate of fast eaters (n=15). Slow eaters had higher PPG following the rice cake meal at 15 (p = 0.046) and 45 min (p = 0.034) than fast eaters. A longer OET was a positive predictor of early PPG at 30-min after the white rice meal (ß = 0.178, p = 0.041) and saliva uptake was a significant predictor (ß = 0.458, p = 0.045) of PPG for slow eaters when consuming rice cake. Increasing food hardness and stiffness (Young's modulus) had a greater impact on eating rate for slow eaters than fast eaters. CONCLUSIONS: Eating rate, oral exposure time and bolus saliva uptake were the predictors of an individual's post-prandial glycaemic response amongst slow eaters. Increasing the number of chews per bite with a longer oral exposure time increased saliva uptake in the bolus at the moment of swallowing and enhanced temporal changes in PPG, leading to greater glycaemic peaks in rice cake meal. Differences in eating rate between slow and fast eaters when consuming rice cake meal influenced temporal changes in PPG but not total PPG, and bolus properties did not differ between eating rate groups.

Eating behaviors moderate the associations between risk factors in the first 1000 days and adiposity outcomes at 6 years of age.

BACKGROUND: Several risk factors in the first 1000 d are linked with increased obesity risk in later childhood. The role of potentially modifiable eating behaviors in this association is unclear. OBJECTIVES: This study examined whether the association between cumulated risk factors in the first 1000 d and adiposity at 6 y is moderated by eating behaviors. METHODS: Participants were 302 children from the GUSTO (Growing Up in Singapore Towards healthy Outcomes) cohort. Risk factors included maternal prepregnancy and paternal overweight, excessive gestational weight gain, raised fasting plasma glucose during pregnancy, short breastfeeding duration, and early introduction of solid foods. Composite risk scores reflecting the prevalence and the importance of the risk factors present were computed. Adiposity outcomes were child BMI and sum of skinfolds (SSF), and candidate eating behavior moderators were portion size, eating rate, and energy intake during lunch and in an eating in the absence of hunger task. RESULTS: Higher composite risk score predicted higher BMI z scores (B = 0.08; 95% CI: 0.04, 0.13) and larger SSF (0.70 mm; 0.23, 1.18 mm), and was associated with larger self-served food portions (5.03 kcal; 0.47, 9.60 kcal), faster eating rates (0.40 g/min; 0.21, 0.59 g/min), and larger lunch intakes (7.05 kcal; 3.37, 10.74 kcal). Importantly, the association between composite risk score and adiposity was moderated by eating behaviors. The composite risk score was unrelated to SSF in children who selected smaller food portions, ate slower, and consumed less energy, but was positively associated with SSF among children who selected larger food portions, ate faster, and consumed more energy (eating behavior × risk score interactions: P < 0.05). CONCLUSIONS: The association between risk factors in the first 1000 d and adiposity at 6 y varies by eating behaviors, highlighting modifiable behavioral targets for interventions.This trial was registered at clinicaltrials.gov as NCT01174875.

Basal Metabolic Rate and Body Composition Predict Habitual Food and Macronutrient Intakes: Gender Differences.

The underlying mechanisms that regulate energy homeostasis and food intake are not fully understood. Moreover, little research has been performed on the relation of body composition with habitual macronutrient intake among free-living populations. Since body composition and energy metabolism differ between males and females, we aimed to determine whether the relationship between body composition and habitual macronutrient intakes is gender-dependent. In this cross-sectional study, 261 participants (99 males) were recruited from Singapore. Macronutrient intake was evaluated from a three-day self-reported dietary record. Body composition and basal metabolic rate (BMR) were determined by using dual-energy X-ray absorptiometry (DEXA) and indirect calorimetry, respectively. Our results show that both BMR (p < 0.001) and lean body mass (LBM, p < 0.001) predicted daily energy intake (EI). LBM was positively associated with intakes of protein (PRO) and fat (FAT) in females, but not in males. This relationship persisted even after adjustment for fat mass (FM). On the other hand, no significant associations between FM and macronutrient intake were observed in both males and females. Therefore, the relationship between habitual macronutrient intake, LBM, and BMR is gender-dependent. Elucidating the gender differences in energy metabolism is important for understanding the factors that regulate energy homeostasis and can subsequently help better manage energy balance.

Validation of the Children's Eating Behavior Questionnaire in 5 and 6 Year-Old Children: The GUSTO Cohort Study.

Revised subscales of the Children's Eating Behavior Questionnaire (CEBQ) have been proposed to be more appropriate for assessing appetitive traits in Singaporean 3 year-olds, but the CEBQ has not yet been validated in older children in this population. The current study aimed to validate the CEBQ at ages 5 (n = 653) and 6 (n = 449) in the ethnically diverse GUSTO cohort. Confirmatory factor analysis (CFA) examined whether the established eight-factor model of the CEBQ was supported in this sample. Overall, the CFA showed a poor model fit at both ages 5 and 6. At both ages 5 and 6, an exploratory factor analysis revealed a six-factor structure: food fussiness, enjoyment of food, slowness in eating, emotional undereating, emotional overeating and desire to drink. Cronbach's alpha estimates ranged from 0.70 to 0.85 for all subscales. Criterion validity was tested by correlating subscales with the weight status of 6 years of age. At age 5 and 6, lower scores of slowness of eating while higher scores of enjoyment of food was associated with child overweight. At age 6, higher scores of desire to drink was also associated child overweight. In conclusion, a revised six factor-structure of the CEBQ at ages 5 and 6 were more appropriate for examining appetitive traits in this sample.

Correlation of instrumental texture properties from textural profile analysis (TPA) with eating behaviours and macronutrient composition for a wide range of solid foods.

Faster eating rates have previously been associated with higher ad libitum energy intakes, and several studies have manipulated eating rates and intake by changing food textures. Food texture based changes to slow eating rates can produce reductions in energy intake without affecting post-meal satisfaction or re-bound hunger. However, an understanding of how specific food textures and instrumental texture properties influence oral processing behaviour remains limited. The current study sought to establish relationships between objective measures of oral processing behaviour (i.e. number of bites, average bite size, total chews, chews per bite, oro-sensory exposure time and eating rate) and instrumental measures of a food texture including hardness, adhesiveness, springiness, cohesiveness, chewiness, resilience and modulus. Across two studies, behavioural coding analysis was completed on video-recordings of participants consuming fixed portions of a wide range of different solid foods (n = 59) to derive objective measures of oral processing behaviours. These measures were correlated with instrumental Textural Profile Analysis (TPA) for the same set of foods. Significant correlations (p < 0.05) were found between oral processing parameters and texture properties (i.e. springiness, cohesiveness, chewiness and resilience). No significant correlations were found between hardness and modulus and oral processing parameters. Protein content of the food was associated with springiness and chewiness, which may help to further reduce eating rates. In terms of the 'breakdown path model', hardness and modulus might represent degree of initial food structure while springiness, cohesiveness, chewiness and resilience seem to determine how fast the degree of structure is reduced to the swallowing plane. Water content and adhesiveness were associated with level of lubrication that is required before reaching the swallowing plane. The current study highlights opportunities to understand eating rate (g min-1) through the breakdown path model and the potential for specific features of a foods texture to influence rate and extent of energy intake. The correlation between instrumental texture properties and oral processing patterns provides guidance on the parameters that are likely to produce 'faster' and 'slower' versions of foods, and suggests how texture modifications could be applied to moderate eating rate and energy intake within meals.

Eating in the absence of hunger: Stability over time and associations with eating behaviours and body composition in children.

BACKGROUND/OBJECTIVES: Eating in the absence of hunger (EAH) has been linked to obesity in adults and children. This study examined the stability of EAH in children between 4.5 and 6 years old, and associations with energy intake and portion selection, as well as cross-sectional and prospective associations with body composition. METHODS: The participants were 158 boys and girls from the Growing Up in Singapore Towards healthy Outcomes cohort. At ages 4.5 and 6 years old children were provided lunch ad libitum, and immediately afterwards were exposed to palatable snacks to measure energy intake in the absence of hunger. At age 6 children completed an additional computer-based task to measure ideal portion size, where they selected pictures of the portions they would like to eat across eight foods. Measures of anthropometry (height/weight/skinfolds) were collected at both ages. RESULTS: Children who consumed energy during the EAH task at age 4.5 years were 3 times more likely to also do so at age 6 years. Children with high EAH intakes at age 4.5 years had high EAH intakes at age 6, highlighting stability of this behaviour over time. Energy consumed at lunch was unrelated to energy consumed during the EAH task, but children who ate in the absence of hunger cumulatively consumed more energy over lunch and the EAH task. Children who showed EAH tended to select larger ideal portions of foods during the computer task. EAH was not associated with measures of body composition. CONCLUSIONS: EAH is a stable behavioural risk factor for increased energy intake, but was not associated with body composition in this cohort. The majority of children ate in the absence of hunger, suggesting that interventions aimed at reducing responsiveness to external food cues could help to reduce energy intakes. Trial Registry Number: NCT01174875; https://clinicaltrials.gov/.

A description of an 'obesogenic' eating style that promotes higher energy intake and is associated with greater adiposity in 4.5year-old children: Results from the GUSTO cohort.

Recent findings confirm that faster eating rates support higher energy intakes within a meal and are associated with increased body weight and adiposity in children. The current study sought to identify the eating behaviours that underpin faster eating rates and energy intake in children, and to investigate their variations by weight status and other individual differences. Children (N=386) from the Growing Up in Singapore towards Healthy Outcomes (GUSTO) cohort took part in a video-recorded ad libitum lunch at 4.5years of age 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) and measures of eating microstructure: eating rate (g/min), total oral exposure (min), average bite size (g/bite), chews per gram, oral exposure per bite (s), total bites and proportion of active to total mealtime. Children's BMIs were calculated and a subset of children underwent MRI scanning to establish abdominal adiposity. Children were grouped into faster and slower eaters, and into healthy and overweight groups to compare their eating behaviours. Results demonstrate that faster eating rates were correlated with larger average bite size (r=0.55, p<0.001), fewer chews per gram (r=-0.71, p<0.001) and shorter oral exposure time per bite (r=-0.25, p<0.001), and with higher energy intakes (r=0.61, p<0.001). Children with overweight and higher adiposity had faster eating rates (p<0.01) and higher energy intakes (p<0.01), driven by larger bite sizes (p<0.05). Eating behaviours varied by sex, ethnicity and early feeding regimes, partially attributable to BMI. We propose that these behaviours describe an 'obesogenic eating style' that is characterised by faster eating rates, achieved through larger bites, reduced chewing and shorter oral exposure time. This obesogenic eating style supports acute energy intake within a meal and is more prevalent among, though not exclusive to, children with overweight. Clinical Trial Registry Number: NCT01174875; https://clinicaltrials.gov/.