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Excess body weight is a major global health concern, particularly due to its associated increased health risks. Several strategies have been proposed to prevent overweight and obesity onset. In the past decade, it has been suggested that eating speed/rate and eating frequency might be related to obesity. The main aim of this narrative review was to summarize existing evidence regarding the impact of eating speed/rate and eating frequency on adiposity, metabolic syndrome (MetS), or diet quality (DQ). For this purpose, a literature search of observational and interventional trials was conducted between June and September 2020 in PubMed and Web of Sciences databases, without any data filters and no limitations for publication date. Results suggest that children and adults with a faster eating speed/rate may be associated with a higher risk of developing adiposity, MetS or its components. Furthermore, a higher eating frequency could be associated with diet quality improvement, lower adiposity, and lower risk of developing MetS or its components. Further interventional trials are warranted to clarify the mechanism by which these eating behaviors might have a potential impact on health.

Fast self-reported eating rate (SRER) has been associated with increased adiposity in children and adults. No studies have been conducted among high-school students, and SRER has not been validated vs. objective eating rate (OBER) in such populations. The objectives were to investigate (among high-school student populations) the association between OBER and BMI z-scores (BMIz), the validity of SRER vs. OBER, and potential differences in BMIz between SRER categories. Three studies were conducted. Study 1 included 116 Swedish students (mean ± SD age: 16.5 ± 0.8, 59% females) who were eating school lunch. Food intake and meal duration were objectively recorded, and OBER was calculated. Additionally, students provided SRER. Study 2 included students (n = 50, mean ± SD age: 16.7 ± 0.6, 58% females) from Study 1 who ate another objectively recorded school lunch. Study 3 included 1832 high-school students (mean ± SD age: 15.8 ± 0.9, 51% females) from Sweden (n = 748) and Greece (n = 1084) who provided SRER. In Study 1, students with BMIz ≥ 0 had faster OBER vs. students with BMIz &lt, 0 (mean difference: +7.7 g/min or +27%, p = 0.012), while students with fast SRER had higher OBER vs. students with slow SRER (mean difference: +13.7 g/min or +56%, p = 0.001). However, there was “minimal” agreement between SRER and OBER categories (κ = 0.31, p &lt, 0.001). In Study 2, OBER during lunch 1 had a “large” correlation with OBER during lunch 2 (r = 0.75, p &lt, 0.001). In Study 3, fast SRER students had higher BMIz vs. slow SRER students (mean difference: 0.37, p &lt, 0.001). Similar observations were found among both Swedish and Greek students. For the first time in high-school students, we confirm the association between fast eating and increased adiposity. Our validation analysis suggests that SRER could be used as a proxy for OBER in studies with large sample sizes on a group level. With smaller samples, OBER should be used instead. To assess eating rate on an individual level, OBER can be used while SRER should be avoided.

The link between eating rate and energy intake has long been a matter of extensive research. A better understanding of the effect of food intake speed on body weight and glycemia in the long term could serve as a means to prevent weight gain and/or dysglycemia. Whether a fast eating rate plays an important role in increased energy intake and body weight depends on various factors related to the studied food such as texture, viscosity and taste, but seems to be also influenced by the habitual characteristics of the studied subjects as well. Hunger and satiety quantified via test meals in acute experiments with subsequent energy intake measurements and their association with anorexigenic and orexigenic regulating peptides provide further insight to the complicated pathogenesis of obesity. The present review examines data from the abundant literature on the subject of eating rate, and highlights the main findings in people with normal weight, obesity, and type 2 diabetes, with the aim of clarifying the association between rate of food intake and hunger, satiety, glycemia, and energy intake in the short and long term.

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 (β = 0.178, p = 0.041) and saliva uptake was a significant predictor (β = 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.

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.

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 &ldquo, On a scale of 1&ndash, 5 (very slow&ndash, very fast), how fast do you believe you eat?&rdquo, 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 &lsquo, fast&rsquo, &lsquo, medium&rsquo, and &lsquo, slow&rsquo, eaters. There was 47.4% agreement (fair) between self-reported speed of eating and the objective measure of eating rate ( = 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&rsquo, 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.

International audience; Early attempts at the objective measurement of food intake in humans followed many heuristic pioneer studies in laboratory animals, which revealed how homeostatic and hedonic factors interact to shape the daily eating patterns. Early studies in humans examined the characteristics of intake responses at discrete ingestive events. Described for the first time in 1969, the edogram consisted of a parallel recording of chewing and swallowing responses during standardized lunches, allowing parameters of the "microstructure of meals" to be quantified under varying conditions of deprivation or sensory stimulation, in parallel with overall meal size, meal duration, and eating rate. Edographic studies showed consistent changes in the microstructure of meals in response to palatability level (increased eating rate, decreased chewing time and number of chews per food unit, shorter intrameal pauses, and increased prandial drinking under improved palatability). Longer premeal deprivation affected the eating responses at the beginning of meals (decreased chewing time and number of chews per food unit) but not at the end. Eating rate decelerated during the course of meals in normal-weight participants but not in participants with obesity. These observations largely agreed with contemporary works using other objective measurement methods. They were confirmed and expanded in later studies, notably in the investigation of satiation mechanisms affecting weight control. Importantly, research has demonstrated that the parameters of the microstructure of meals not only reflect the influence of stimulatory/inhibitory factors but can, per se, exert a causal role in satiation and satiety. The early edographic recording instruments were improved over the years and taken out of laboratory settings in order to address the measurement of spontaneous intake responses in free-living individuals. Much remains to be done to make these instruments entirely reliable under the immense variety of situations where food consumption occurs.

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.

A major proportion of the costs of pork production is related to feed. The feed conversion rate (FCR) or residual feed intake (RFI) is thus commonly included in breeding programmes. Feeding behaviour traits do not directly have economic value but, if correlated with production traits, can be used as auxiliary traits. The aim of this study was to estimate the heritability of feeding behaviour traits and their genetic correlations with production traits in the Finnish Yorkshire pig population. The data were available from 3,235 pigs. Feeding behaviour was measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent feeding per visit (TPV), feed intake per visit (FPV) and feed intake rate (FR). The test station phase was divided into five periods. Estimates of heritabilities of feeding behaviour traits varied from 0.17 to 0.47. Strong genetic correlations were obtained between behaviour traits in all periods. However, only DFI was strongly correlated with the production traits. Interestingly, a moderate positive genetic correlation was obtained between FR and backfat thickness (0.1?0.5) and between FR and average daily gain (0.3?0.4), depending on the period. Based on the results, there is no additional benefit from including feeding-related traits other than those commonly used (FCR and RFI) in the breeding programme. However, if correlated with animal welfare, the feeding behaviour traits could be valuable in the breeding programme.

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 p p Conclusions The findings of this study indicate that an augmented fork with vibrotactile feedback is a viable tool to reduce eating rate in naturalistic settings. Further investigation may confirm that the augmented fork could support long-term weight loss strategies. Trial registration The research reported in this manuscript was registered on 4 November 2015 in the Netherlands Trial Register with number NL5432 (https://www.trialregister.nl/trial/5432).

Little is known whether small modifications of food texture are sufficient to influence satiation. This study used four iso-caloric yogurts differing in viscosity (low/high) and granola particle size (small/large) to investigate the influence of small texture modifications on oral processing behaviour, eating rate and ad libitum intake. Yogurt viscosity differed by a factor of 1.57x to 1.81x. Granola particle size was 6 mm and 12 mm (2-fold difference). Granola particle concentration based on weight was constant (15% w/w). Oral processing behaviour was quantified by video recording consumers eating yogurt ad libitum (n = 104). Ratings for appetite, liking and product familiarity were also quantified. A decrease in yogurt viscosity significantly decreased spoon size, number of chews per spoon and oral exposure time per spoon but did not significantly affect eating rate and ad libitum intake. A decrease in granola particle size from 12 mm to 6 mm at constant weight concentration significantly increased number of chews per spoon and decreased spoon size, eating rate and ad libitum intake without affecting liking. The differences in eating rate and ad libitum intake between yogurts containing small and large granola particles were 5 g/min (7%) and 17 g (5%), respectively. We suggest that the volume of granola particles added to the yogurt and not the size of particles per se was the driver of oral processing behaviour. We conclude that relatively small modifications in yogurt texture, especially granola particle size, are sufficient to change oral processing behaviour and ad libitum intake. These findings demonstrate that small texture modifications of foods, such as the size of granola particles added to yogurt, can be used to modulate eating rate and food intake within a meal.

Energy-containing liquids are claimed to have relatively low satiating power, although energy in liquids is not without effect on appetite. Using the preload test-meal method, effects on fullness and energy intake compensation were compared across four drinks (water, blackcurrant squash, milk and fruit smoothie) and the fresh fruit equivalent of the smoothie. Preload volumes were similar, and the energy value of each preload was 569 kJ, except for water (0 kJ). Healthy, adult participants rated the preloads for liking, enjoyment, satisfaction, familiarity and how ‘food-like’ they seemed. The preload to test-meal interval was 2 min (n = 23) or 2 h (n = 24). The effects of the preloads on fullness varied with food-likeness and the rate at which they were consumed. In contrast, energy intake compensation versus water did not differ between the energy-containing preloads, although it decreased over time (from 82% at 2 min to 12% at 2 h). In conclusion, although fullness increased with food-likeness, subsequent energy intake compensation did not differ for energy/nutrients consumed in drinks compared with a food. The results also support the proposal that food intake is influenced predominantly by the immediate, but rapidly waning, post-ingestive effects of the previous ‘meal’ (rather than by changes in energy balance).

Subjects eat food from a plate that sits on a scale connected to a computer that records the weight loss of the plate during the meal and makes up a curve of food intake, meal duration and rate of eating modeled by a quadratic equation. The purpose of the method is to change eating behavior by providing visual feedback on the computer screen that the subject can adapt to because her/his own rate of eating appears on the screen during the meal. The data generated by the method is automatically analyzed and fitted to the quadratic equation using a custom made algorithm. The method has the advantage of recording eating behavior objectively and offers the possibility of changing eating behavior both in experiments and in clinical practice. A limitation may be that experimental subjects are affected by the method. The same limitation may be an advantage in clinical practice, as eating behavior is more easily stabilized by the method. A treatment that uses this method has normalized body weight and restored the health of several hundred patients with anorexia nervosa and other eating disorders and has reduced the weight and improved the health of severely overweight patients.

There have been recent advances in our understanding of the drivers of energy intake (EI). However, the biological drivers of differences in eating rate (ER) remain less clear. Studies have reported that the fat-free mass (FFM) and basal metabolic rate (BMR) are both major components that contribute to daily energy expenditure (EE) and drive EI. More recently, a number of observations report that higher ER can lead to greater EI. The current study proposed that adults with a higher BMR and higher energy requirements would also exhibit higher ERs. Data on BMR, FFM, and ER were collected from 272 Chinese adults (91 males and 181 females) in a cross-sectional study. Analysis showed significant positive associations between BMR and ER (rs = 0.405, p < 0.001), and between FFM and ER (rs = 0.459, p < 0.001). BMR explained about 15% of the variation in ER which was taken to be metabolically significant. This association provides metabolic explanation that the differences in an individual's BMR (hence energy requirements) may be correlated with ERs. This merits further research.

Item does not contain fulltext Eating rate is a basic determinant of appetite regulation, as people who eat more slowly feel sated earlier and eat less. Without assistance, eating rate is difficult to modify due to its automatic nature. In the current study, participants used an augmented fork that aimed to decelerate their rate of eating. A total of 114 participants were randomly assigned to the Feedback Condition (FC), in which they received vibrotactile feedback from their fork when eating too fast (i.e., taking more than one bite per 10 s), or a Non-Feedback Condition (NFC). Participants in the FC took fewer bites per minute than did those in the NFC. Participants in the FC also had a higher success ratio, indicating that they had significantly more bites outside the designated time interval of 10 s than did participants in the NFC. A slower eating rate, however, did not lead to a significant reduction in the amount of food consumed or level of satiation. These findings indicate that real-time vibrotactile feedback delivered through an augmented fork is capable of reducing eating rate, but there is no evidence from this study that this reduction in eating rate is translated into an increase in satiation or reduction in food consumption. Overall, this study shows that real-time vibrotactile feedback may be a viable tool in interventions that aim to reduce eating rate. The long-term effectiveness of this form of feedback on satiation and food consumption, however, awaits further investigation. 7 p.

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.

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 3 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.

Background: Food texture plays an important role in food intake regulation. In previous studies we showed a clear effect of viscosity on ad libitum food intake and found indications that eating rate, bite size, and oral processing time (OPT) could play a role. Objective: The objective was to determine the effect of bite size and OPT of a food on satiation, defined as ad libitum food intake. Design: Twenty-two healthy subjects participated in all 7 test conditions. Bite sizes were free or fixed to small bite sizes (˜5 g) or large bite sizes (˜15 g). OPT was free (only in combination with free bite size) or fixed to 3 or 9 s. Subjects consumed chocolate custard through a tube, which was connected to a peristaltic pump. Sound signals indicated OPT duration. Results: Subjects consumed significantly more when bite sizes were large than when they were small (bite size effect: P

Deliberately eating at a slower pace promotes satiation and eating quickly has been associated with a higher body mass index. Therefore, understanding factors that affect eating rate should be given high priority. Eating rate is affected by the physical/textural properties of a food, by motivational state, and by portion size and palatability. This study explored the prospect that eating rate is also influenced by a hitherto unexplored cognitive process that uses ongoing perceptual estimates of the volume of food remaining in a container to adjust intake during a meal. A 2 (amount seen; 300 ml or 500 ml) x 2 (amount eaten; 300 ml or 500 ml) between-subjects design was employed (10 participants in each condition). In two 'congruent' conditions, the same amount was seen at the outset and then subsequently consumed (300 ml or 500 ml). To dissociate visual feedback of portion size and actual amount consumed, food was covertly added or removed from a bowl using a peristaltic pump. This created two additional 'incongruent' conditions, in which 300 ml was seen but 500 ml was eaten or vice versa. We repeated these conditions using a savoury soup and a sweet dessert. Eating rate (ml per second) was assessed during lunch. After lunch we assessed fullness over a 60-minute period. In the congruent conditions, eating rate was unaffected by the actual volume of food that was consumed (300 ml or 500 ml). By contrast, we observed a marked difference across the incongruent conditions. Specifically, participants who saw 300 ml but actually consumed 500 ml ate at a faster rate than participants who saw 500 ml but actually consumed 300 ml. Participants were unaware that their portion size had been manipulated. Nevertheless, when it disappeared faster or slower than anticipated they adjusted their rate of eating accordingly. This suggests that the control of eating rate involves visual feedback and is not a simple reflexive response to orosensory stimulation.

Eating slowly is associated with a lower body mass index. However, the underlying mechanism is poorly understood. Here, our objective was to determine whether eating a meal at a slow rate improves episodic memory for the meal and promotes satiety. Participants (N = 40) consumed a 400 ml portion of tomato soup at either a fast (1.97 ml/s) or a slow (0.50 ml/s) rate. Appetite ratings were elicited at baseline and at the end of the meal (satiation). Satiety was assessed using; i) an ad libitum biscuit ‘taste test’ (3 h after the meal) and ii) appetite ratings (collected 2 h after the meal and after the ad libitum snack). Finally, to evaluate episodic memory for the meal, participants self-served the volume of soup that they believed they had consumed earlier (portion size memory) and completed a rating of memory ‘vividness’. Participants who consumed the soup slowly reported a greater increase in fullness, both at the end of the meal and during the inter-meal interval. However, we found little effect of eating rate on subsequent ad libitum snack intake. Importantly, after 3 h, participants who ate the soup slowly remembered eating a larger portion. These findings show that eating slowly promotes self-reported satiation and satiety. For the first time, they also suggest that eating rate influences portion size memory. However, eating slowly did not affect ratings of memory vividness and we found little evidence for a relationship between episodic memory and satiety. Therefore, we are unable to conclude that episodic memory mediates effects of eating rate on satiety., Highlights • Eating lunch at a slower rate promotes greater satiation and satiety. • Participants remember eating a larger meal if they eat it slowly. • Eating lunch at a slower rate does not affect subsequent snack-food intake. • Effects of eating rate on satiety might not be mediated by episodic memory.

Background: Previous research has shown that oral processing characteristics like bite size and oral residence duration are related to the satiating efficiency of foods. Oral processing characteristics are influenced by food texture. Very little research has been done on the effect of food texture within solid foods on energy intake. Objectives: The first objective was to investigate the effect of hardness of food on energy intake at lunch, and to link this effect to differences in food oral processing characteristics. The second objective was to investigate whether the reduction in energy intake at lunch will be compensated for in the subsequent dinner. Design: Fifty subjects (11 male, BMI: 21 +/- 2 kg/m(2), age: 24 +/- 2 y) participated in a cross-over study in which they consumed ad libitum from a lunch with soft foods or hard foods on two separate days. Oral processing characteristics at lunch were assessed by coding video records. Later on the same days, subjects consumed dinner ad libitum. Results: Hard foods led to a similar to 13% lower energy intake at lunch compared to soft foods (P

Background Slow eating has been associated with enhanced satiation, but also with increased water intake. Therefore, the role of water ingestion in regard to eating rate needs to be discerned. This study examined the influence of eating rate on appetite regulation and energy intake when water intake is controlled. Methods In a randomized design, slow and fast eating rates were compared on two occasions, in 30 women (22.7±1.2y; BMI=22.4±0.4kg/m2) who consumed an ad libitum mixed-macronutrient lunch with water (300 mL). Satiation was examined as the main outcome by measuring energy intake during meals. At designated times, subjects rated hunger, satiety, desire-to-eat, thirst, and meal palatability on visual analogue scales. Paired t-tests were used to compare hypothesis-driven outcomes. Appetite ratings were compared across time points and conditions by repeated measures analysis of variance (ANOVA) using a within-subject model. Results Energy intake and appetite ratings did not differ between conditions at meal completion. However, subjects rated less hunger and tended to rate lower desire-to-eat and greater satiety at 1 hour following the slow condition. Conclusions Results tend to support a role of slow eating on decreased hunger and higher inter-meal satiety when water intake is controlled. However, the lack of significant differences in energy intake under these conditions indicates that water intake may account for the effects of eating rate on appetite regulation.

Background: The modern food supply is often dominated by a large variety of energy dense, softly textured foods that can be eaten quickly. Previous studies suggest that particular oral processing characteristics such as large bite size and lack of chewing activity contribute to the low satiating efficiency of these foods. To better design meals that promote greater feelings of satiation, we need an accurate picture of the oral processing characteristics of a range of solid food items that could be used to replace softer textures during a normal hot meal. Aim: The primary aim of this study was to establish an accurate picture of the oral processing characteristics of a set of solid savoury meal components. The secondary aim was to determine the associations between oral processing characteristics, food composition, sensory properties, and expected satiation. Methods: In a within subjects design, 15 subjects consumed 50 g of 35 different savoury food items over 5 sessions. The 35 foods represented various staples, vegetables and protein rich foods such a meat and fish. Subjects were video-recorded during consumption and measures included observed number of bites, number of chews, number of swallows and derived measures such as chewing rate, eating rate, bite size, and oral exposure time. Subjects rated expected satiation for a standard 200 g portion of each food using a 100 mm and the sensory differences between foods were quantified using descriptive analysis with a trained sensory panel. Statistical analysis focussed on the oral processing characteristics and associations between nutritional, sensory and expected satiation parameters of each food. Results: Average number of chews for 50 g of food varied from 27 for mashed potatoes to 488 for tortilla chips. Oral exposure time was highly correlated with the total number of chews, and varied from 27 s for canned tomatoes to 350 s for tortilla chips. Chewing rate was relatively constant with an overall average chewing rate of approximately 1 chew/s. Differences in oral processing were not correlated with any macronutrients specifically. Expected satiation was positively related to protein and the sensory attributes chewiness and saltiness. Foods that consumed in smaller bites, were chewed more and for longer and expected to impart a higher satiation. Discussion: This study shows a large and reliable variation in oral exposure time, number of required chews before swallowing and expected satiation across a wide variety of foods. We conclude that bite size and oral-sensory exposure time could contribute to higher satiation within a meal for equal calories.