Texture-Based Differences in Eating Rate Reduce the Impact of Increased Energy Density and Large Portions on Meal Size in Adults

Ultra-Processing or Oral Processing? A Role for Energy Density and Eating Rate in Moderating Energy Intake from Processed Foods

BACKGROUND

Recent observational data and a controlled in-patient crossover feeding trial show that consumption of "ultra-processed foods" (UPFs), as defined by the NOVA classification system, is associated with higher energy intake, adiposity, and at a population level, higher prevalence of obesity. A drawback of the NOVA classification is the lack of evidence supporting a causal mechanism for why UPFs lead to overconsumption of energy. In a recent study by Hall the energy intake rate in the UPF condition (48 kcal/min) was >50% higher than in the unprocessed condition (31 kcal/min). Extensive empirical evidence has shown the impact that higher energy density has on increasing ad libitum energy intake and body weight. A significant body of research has shown that consuming foods at higher eating rates is related to higher energy intake and a higher prevalence of obesity. Energy density can be combined with eating rate to create a measure of energy intake rate (kcal/min), providing an index of a food's potential to promote increased energy intake.

OBJECTIVE

The current paper compared the association between measured energy intake rate and level of processing as defined by the NOVA classification.

METHODS

Data were pooled from 5 published studies that measured energy intake rates across a total sample of 327 foods.

RESULTS

We show that going from unprocessed, to processed, to UPFs that the average energy intake rate increases from 35.5 ± 4.4, to 53.7 ± 4.3, to 69.4 ± 3.1 kcal/min (P < 0.05). However, within each processing category there is wide variability in the energy intake rate.

CONCLUSIONS

We conclude that reported relations between UPF consumption and obesity should account for differences in energy intake rates when comparing unprocessed and ultra-processed diets. Future research requires well-controlled human feeding trials to establish the causal mechanisms for why certain UPFs can promote higher energy intake.

Comparison of Self-Reported Speed of Eating with an Objective Measure of Eating Rate

Slow eating may be beneficial in reducing energy intake although there is limited research quantifying eating rate. Perceived speed of eating was self-reported by 78 adults using a standard question “On a scale of 1–5 (very slow–very fast), how fast do you believe you eat?” Timing the completion of meals on three occasions was used to assess objective eating rate. The mean (SD) speeds of eating by self-reported categories were 49 (13.7), 42 (12.2), and 35 (10.5) g/min for fast, medium, and slow eaters, respectively. Within each self-reported category, the range of timed speed of eating resulted in considerable overlap between self-identified ‘fast’, ‘medium’ and ‘slow’ eaters. There was 47.4% agreement (fair) between self-reported speed of eating and the objective measure of eating rate (κ = 0.219). Self-reported speed of eating was sufficient at a group level to detect a significant difference (10.9 g/min (95% CI: 2.7, 19.2 g/min, p = 0.009)) between fast and slow; and fast and medium eaters (6.0 g/min (0.5, 11.6 g/min p = 0.033)). The mean difference (95% CI) between slow and medium eaters was 4.9 (−3.4, 12.2) g/min (p = 0.250). At an individual level, self-report had poor sensitivity. Compared to objectively measured speed of eating, self-reported speed of eating was found to be an unreliable means of assessing an individual’s eating rate. There are no standard protocols for assessing speed of eating or eating rate. Establishing such protocols would enable the development of population reference ranges across various demographic groups that may be applicable for public health messages and in clinical management.

A review of evidence supporting current strategies, challenges, and opportunities to reduce portion sizes

Although there is considerable evidence for the portion-size effect and its potential impact on health, much of this has not been successfully applied to help consumers reduce portion sizes. The objective of this review is to provide an update on the strength of evidence supporting strategies with potential to reduce portion sizes across individuals and eating contexts. Three levels of action are considered: food-level strategies (targeting commercial snack and meal portion sizes, packaging, food labels, tableware, and food sensory properties), individual-level strategies (targeting eating rate and bite size, portion norms, plate-cleaning tendencies, and cognitive processes), and population approaches (targeting the physical, social, and economic environment and health policy). Food- and individual-level strategies are associated with small to moderate effects; however, in isolation, none seem to have sufficient impact on food intake to reverse the portion-size effect and its consequences. Wider changes to the portion-size environment will be necessary to support individual- and food-level strategies leading to portion control.

Dietary energy density and appetite: A systematic review and meta-analysis of clinical trials

Studies have suggested that dietary energy density (DED) may affect weight gain by altering appetite. Although many studies have investigated the effect of DED on appetite, findings are inconsistent and, to our knowledge, there are no systematic reviews and meta-analyses on this topic. Therefore, the aim of this systematic review and meta-analysis was to summarize the effect of DED on appetite. The current meta-analysis revealed changing the DED had no significant effect on hunger but increased fullness. More high-quality randomized controlled trials are needed to investigate the effects of DED on appetite components. We searched titles, abstracts, and keywords of articles indexed in ScienceDirect, MEDLINE, and Google Scholar databases up to July 2018 to identify eligible RCT studies. Random effects model was used to estimate the pooled effect of DED on appetite. Among the 21 studies identified in the systematic literature search, 11 reports were included in the meta-analysis. Based on the Cochrane Collaboration Risk of Bias tool, 6 studies were considered as good quality, two were fair, and three studies were poor. The mean ± standard deviation for energy density, in studies which assessed fullness, was 1.65 ± 1 in high energy dense (HED) diet and 0.93 ± 0.93 in low energy dense (LED) diet. The corresponding values for hunger were 1.67 ± 0.69 and 0.70 ± 0.32, respectively. Compared with a LED diet, consumption of HED increased fullness (weighed mean difference [WMD] 2.95 mm; 95% CI 0.07-5.82, P = 0.044, I² 98.1%) but had no significant effect on hunger (WMD 1.31 mm; 95% CI -7.20 to 9.82, P = 0.763, I² 99.1%). The current meta-analysis revealed changing the DED had no significant effect on hunger but increased fullness. More high-quality RCTs are needed to investigate the effects of DED on appetite components.

Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake

We investigated whether ultra-processed foods affect energy intake in 20 weight-stable adults, aged (mean ± SE) 31.2 ± 1.6 years and BMI = 27 ± 1.5 kg/m². Subjects were admitted to the NIH Clinical Center and randomized to receive either ultra-processed or unprocessed diets for 2 weeks immediately followed by the alternate diet for 2 weeks. Meals were designed to be matched for presented calories, energy density, macronutrients, sugar, sodium, and fiber. Subjects were instructed to consume as much or as little as desired. Energy intake was greater during the ultra-processed diet (508 ± 106 kcal/day; p = 0.0001), with increased consumption of carbohydrate (280 ± 54 kcal/day; p < 0.0001) and fat (230 ± 53 kcal/day; p = 0.0004), but not protein (-2 ± 12 kcal/day; p = 0.85). Weight changes were highly correlated with energy intake (r = 0.8, p < 0.0001), with participants gaining 0.9 ± 0.3 kg (p = 0.009) during the ultra-processed diet and losing 0.9 ± 0.3 kg (p = 0.007) during the unprocessed diet. Limiting consumption of ultra-processed foods may be an effective strategy for obesity prevention and treatment.

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 six 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.

Potential moderators of the portion size effect

AIM

The robust effect of portion size on intake has led to growing interest in why individuals consume more food when served larger portions. A number of explanations have been proposed, and this review aims to provide insight into potential underlying factors by summarizing recent studies testing moderators of the portion size effect.

SUMMARY OF FINDINGS

Provision of portion size information, such as through labeling or training in portion control, failed to attenuate food intake in response to increasing meal size. This indicates that a lack of knowledge about appropriate portions may not be sufficient to explain the portion size effect. In contrast, there is evidence for a role of decision making in the response to large portions, with value being one consideration of importance. The portion size effect may be more closely related to the inherent value of food than monetary value, since provision of the opportunity to take away uneaten food after a meal, which can reduce food waste, attenuated the portion size effect but variations in pricing did not. A number of studies also support an influence of orosensory processing on the portion size effect; large portions have been shown to relate to increased bite size and faster eating rate. Reduced oral processing time when consuming large portions could contribute to the effect by delaying sensory-specific satiety. Findings from a recent study supported this by demonstrating that sensory-specific satiety did not differ between larger and smaller portions despite substantial differences in intake.

CONCLUSIONS

A number of moderators of the portion size effect have been identified, including factors related to the environment, the food, and the individual. It is likely that multiple variables contribute to the response to large portions. Future research should aim to determine the relative contribution of explanatory variables across different contexts and individuals.

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.

Slow Down: Behavioural and Physiological Effects of Reducing Eating Rate

Slowing eating rate appears to be an effective strategy for reducing food intake. This feasibility study investigated the effect of eating rate on post-meal responses using functional magnetic resonance imaging (fMRI), plasma gastrointestinal hormone concentrations, appetite ratings, memory for recent eating, and snack consumption. Twenty-one participants (mean age 23 years with healthy body mass index) were randomly assigned to consume a 600 kcal meal at either a “normal” or “slow” rate (6 vs. 24 min). Immediately afterwards, participants rated meal enjoyment and satisfaction. FMRI was performed 2-h post-meal during a memory task about the meal. Appetite, peptide YY, and ghrelin were measured at baseline and every 30 min for 3 h. Participants were given an ad-libitum snack three hours post-meal. Results were reported as effect sizes (Cohen’s d) due to the feasibility sample size. The normal rate group found the meal more enjoyable (effect size = 0.5) and satisfying (effect size = 0.6). Two hours post-meal, the slow rate group reported greater fullness (effect size = 0.7) and more accurate portion size memory (effect sizes = 0.4), with a linear relationship between time taken to make portion size decisions and the BOLD response in satiety and reward brain regions. Ghrelin suppression post-meal was greater in the slow rate group (effect size = 0.8). Three hours post-meal, the slow rate group consumed on average 25% less energy from snacks (effect size = 0.5). These data offer novel insights about mechanisms underlying how eating rate affects food intake and have implications for the design of effective weight-management interventions.

Impact of composition and texture of protein-added yogurts on oral activity

Understanding how oral processing is altered in response to changes in the composition and mechanical properties of food provides useful information to design food with improved satiating capacity which is largely influenced by oral exposure. In turn, this information deepens the knowledge about the physiology of texture perception. Six yogurts were formulated with different amounts of protein and protein sources and addition of apple cubes: control (C), extra skimmed milk powder-added (MP), whey protein isolate-added (WPI), and whey protein microgels-added (WPM). In addition, MP was also added with maltodextrin (MPMD) and with fresh apple cubes (MPF). Activities of masseter, anterior temporalis and anterior digastric muscles during oral processing of each sample were recorded (electromyography), and jaw movement amplitudes in three dimensions were determined (jaw tracking system). The jaw muscle activities were highly dependent on the type of yogurt. Addition of apple cubes (MPF) almost doubled the oral processing time, number of chews, and muscle activity of all samples. MP and MPMD required similar but lower values of oral processing than MPF attributed to their reinforced network of milk protein. The lowest values were found for WPI, C and WPM, indicating a weaker, more fluid material. These behavioral results, which clearly differentiate the samples, are discussed in connection to the rheological and sensory properties of the yogurts. This study suggests that adding apple cubes significantly alters the oral processing pattern, such that they may be a more effective way of increasing the oral processing time (time exposure) compared to more subtle changes in the protein amount or source. Nevertheless, changes in the protein amount and source also affected, although to a lesser extent, the behavioral, rheological, and sensory properties of yogurt.

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.

The effect of mastication on food intake, satiety and body weight

As mastication is the major component of the oral processing of solid foods a better understanding of its influence on ingestion, digestion and metabolism may lead to new approaches to improve health. A growing number of studies provide evidence that mastication may influence energy balance through several routes: activation of histaminergic neurons, reducing eating rate, altered digestion kinetics, and changes in macronutrient availability. Indeed, accumulating evidence indicates that increasing the number of masticatory cycles before swallowing reduces food intake and increases satiety. However, while slowing eating rate has been shown to limit weight gain in children and adolescents it is not clear that slowing eating rate by increasing the number of masticatory cycles or slowing mastication rate is a viable method to aid weight management ([10], [15]). Further research is required to determine the influence of mastication on energy balance and how it could be manipulated to aid weight management. This narrative review will provide a brief overview of the effect of mastication on food intake, satiety and body weight.

Healthiness of Food and Beverages for Sale at Two Public Hospitals in New South Wales, Australia

(1) Background: Our aim was to conduct objective, baseline food environment audits of two major western Sydney public hospitals and compare them to recently revised state nutritional guidelines. (2) Methods: A cross-sectional assessment was conducted (June-July2017) across 14 fixed food outlets and 70 vending machines in two hospitals using an audit tool designed to assess the guideline's key food environment parameters of availability, placement, and promotion of 'Everyday' (healthy) and 'Occasional' (less healthy) products. (3) Results: Availability: Overall, Everyday products made up 51% and 44% of all products available at the two hospitals. Only 1/14(7%) fixed outlets and 16/70(23%) vending machines met the guideline's availability benchmarks of ≥75% Everyday food and beverages. Proportion of Everyday products differed among different types of food outlets (café, cafeteria, convenience stores). Placement: On average, food outlets did not meet recommendations of limiting Occasional products in prominent positions, with checkout areas and countertops displaying over 60% Occasional items. Promotion: Over two-thirds of meal deals at both hospitals included Occasional products. (4) Conclusion: Baseline audit results show that substantial improvements in availability, placement, and promotion can be made at these public hospitals to meet the nutrition guidelines. Audits of other NSW hospitals using the developed tool are needed to investigate similarities and differences in food environment between sites. These findings highlight the need for ongoing tracking to inform whether the revised guidelines are leading to improved food environments in health facilities.

Effects of Consuming Preloads with Different Energy Density and Taste Quality on Energy Intake and Postprandial Blood Glucose

Consumption of reduced energy dense foods and drink has the potential to reduce energy intake and postprandial blood glucose concentrations. In addition, the taste quality of a meal (e.g., sweet or savoury) may play a role in satiation and food intake. The objective of this randomised crossover study was to examine whether energy density and taste quality has an impact on energy intake and postprandial blood glucose response. Using a preload design, participants were asked to consume a sweet ("Cheng Teng") or a savoury (broth) preload soup in high energy density (HED; around 0.50 kcal/g; 250 kcal) or low energy density (LED; around 0.12 kcal/g; 50 kcal) in mid-morning and an ad libitum lunch was provided an hour after the preload. Participants recorded their food intake for the rest of the day after they left the study site. Energy compensation and postprandial blood glucose response were measured in 32 healthy lean males (mean age = 28.9 years, mean BMI = 22.1 kg/m²). There was a significant difference in ad libitum lunch intake between treatments (p = 0.012), with higher intake in sweet LED and savoury LED compared to sweet HED and savoury HED. Energy intake at subsequent meals and total daily energy intake did not differ between the four treatments (both p ≥ 0.214). Consumption of HED preloads resulted in a larger spike in postprandial blood glucose response compared with LED preloads, irrespective of taste quality (p < 0.001). Energy density rather than taste quality plays an important role in energy compensation and postprandial blood glucose response. This suggests that regular consumption of low energy-dense foods has the potential to reduce overall energy intake and to improve glycemic control.

The Availability of Slow and Fast Calories in the Dutch Diet: The Current Situation and Opportunities for Interventions

Choosing foods that require more time to consume and have a low energy density might constitute an effective strategy to control energy intake, because of their satiating capacity. The current study assessed the eating rate of Dutch food, and investigated the associations between eating rate and other food properties. We also explored the opportunities for a diet with a low energy intake rate (kJ/min). Laboratory data on the eating rate of 240 foods-representing the whole Dutch diet-was obtained. The results show a wide variation in both eating rate (from 2 g/min for rice waffle to 641 g/min for apple juice) and energy intake rate (from 0 kJ/min (0 kcal/min) for water to 1766 kJ/min (422 kcal/min) for chocolate milk). Eating rate was lower when foods were more solid. Moreover, eating rate was positively associated with water content and inversely with energy density. Energy intake rate differed substantially between and within food groups, demonstrating that the available foods provide opportunities for selecting alternatives with a lower energy intake rate. These findings offer guidance when selecting foods to reduce energy intake.

A comparison of bite size and BMI in a cafeteria setting

Our study investigated the relationship between BMI and bite size in a cafeteria setting. Two hundred and seventy one participants consumed one meal each. Participants were free to select any food provided by the cafeteria and could return for additional food as desired. Bite weights were measured with a table embedded scale. Data were analyzed with ANOVAs, regressions, Kolmogorov-Smirnov tests, and a repeated measures general linear model for quartile analysis. Obese participants were found to take larger bites than both normal (p=0.002) and overweight participants (p=0.017). Average bite size increased by 0.20g per point increase in BMI. Food bites and drink bites were analyzed individually, showing 0.11g/BMI and 0.23g/BMI slopes, respectively. Quartiles of bites were also analyzed, and a significant interaction was found between normal and obese participants (p=0.034) such that the lower two quartiles were similar, but the upper two quartiles showed an increase in bite size for obese participants. The source of these effects could be the result of a combination of several uncontrolled factors.

Consistency of Eating Rate, Oral Processing Behaviours and Energy Intake across Meals

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.