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Clinical Studies and Practice

Beyond expectations: the physiological basis of sensory enhancement of satiety



Consumption of high-energy beverages has been implicated as a risk factor for weight gain, yet why nutrients ingested as beverages fail to generate adequate satiety remains unclear. In general, consumers do not expect drinks to be satiating, but drinks generate greater satiety when their sensory characteristics imply they may be filling. These findings challenge traditional bottom-up models of how gut-based satiety signals modify behaviour to suggest that beliefs at the point of ingestion modify gut-based satiety signalling.


Healthy volunteers (n=23) consumed four different beverages, combining an overt sensory manipulation (thin, low sensory (LS) or thicker and more creamy, enhanced sensory (ES)) and covert nutrient manipulation (low energy (LE), 78 kcal; high energy (HE), 267 kcal) on different days. Effects on satiety were assessed through rated appetite and levels of glucose, insulin, pancreatic polypeptide (PP) and cholesystokinin (CCK) recorded periodically over 90 min, and through intake at an ad libitum test lunch.


Intake at the test lunch and rated appetite were both altered by both the sensory and nutrient manipulations, with lowest intake and greatest suppression of hunger post-drink in the ESHE condition. Insulin increased more after HE than LE drinks, and after ES than LS drinks, whereas PP levels were higher after ES than LS versions. CCK levels only increased after the ESHE drink.


These data confirm acute sensitivity of satiety after consuming a drink both to the sensory characteristics and nutrient content of the drink, and suggest that this may be, at least in part, due to top-down modulation of release of satiety-related gut hormones.


The worldwide increase in incidence of obesity driven by excessive energy intake relative to energetic needs1 makes it imperative to better understand why products such as beverages appear to be ineffective at generating satiety and so may contribute to the risk of weight gain. Traditionally, research into satiety has focussed on physiological signals arising in the gut after nutrient ingestion.2, 3, 4 A cascade of hormonal signals arising from different areas of the gut, including cholecystokinin (CCK), glucagon-like peptide (GLP-1), polypeptide YY and pancreatic polypeptide (PP) among others have all been shown to have some role in the postingestive suppression of appetite.5, 6 These gut-derived signals then influence neural centres regulating appetite,4, 7 based on gut to brain signalling. However, these types of satiety models struggle to explain why nutrients ingested as beverages tend to generate weak satiety,8, 9 whereas similar levels of nutrients ingested in other forms, such as soups, typically generate much stronger satiety.10 One possible explanation is that cues before and during ingestion influence the way the gut responds to ingested nutrients, possibly through signals from the brain to gut.

The idea that cues before and during ingestion lead to preparatory physiological responses date back to Pavlov’s work on conditioned salivation in response to food-associated cues.11 These cephalic-phase processes have adaptive value in reducing the degree to which ingested nutrients impact on the body.12 One of the best known is cephalic-phase insulin release (CPIR), which has been widely demonstrated in humans13, 14 and other animals,15, 16 most notably as a response to sweet taste in the mouth.17, 18 As well as CPIR, studies have found conditioned release of PP in response to sham feeding of solid and liquid foods in human volunteers:19, 20, 21 cephalic-phase PP release is one of the more robust hormonal responses to orosensory cues.22 Although its precise physiological role remains unclear, PP release is known to be under vagal control,23, 24, 25 PP secretion is affected by food intake26, 27 and PP has been implicated in increased satiety in humans.28

Traditionally, responses such as CPIR have been interpreted in terms of associative conditioning,12, 22 with repeated associations between cues and postingestive nutrient effects leading to enhanced preparatory physiological responses. A recent study, however, provided evidence that explicit beliefs about a product can also alter gut responses.29 Participants consumed the same nutrients either as a beverage or gel and either with explicit expectations that the ingested item would be liquid or gel in the stomach. The experience of satiety after ingestion depended both on the oral experience (liquid or gel) and critically the belief of how this would be in the stomach. Moreover, these expectations altered the physiological gut responses: there were larger insulin and GLP-1 responses after the gel than liquid version, and the belief that the ingested item would be liquid in the stomach lead to faster gastric emptying. This implies that gut-based responses can be modulated by top-down control. However, in that study all ingested products had the same nutrient content, and so one interpretation might be that the top-down influence modulated the extent to which the actual nutrient signal generated hormone release. The implication is that beliefs should interact with the actual nutrient content to generate gut-based signals. A recent series of studies in our laboratory provides evidence for this sensory enhancement of nutrient-induced satiety.30 Participants consumed drink preloads varying overtly in sensory characteristics and covertly in nutrient content before a test lunch. When the drink was thinner in texture and lacked creamy flavour, participants were poor at compensating for covert addition of energy, only reducing lunch intake by 10–20% of the added energy.31, 32 In contrast, when the same drink was noticeably thicker and creamier, compensation for covert energy increased markedly, to 70–85%.31, 32, 33 A subsequent study that explicitly manipulated satiety expectations further confirmed how expectations alone altered response to nutrients.34 This approach makes an ideal system to explore whether explicit satiety expectations also modify gut-generated physiological satiety signals. The primary aim of the present study was therefore to examine changes in physiological signals implicated in cephalic-phase responses (PP, insulin and glucose) following ingestion of drinks varying overtly in sensory characteristics but covertly in nutrient content. We also tested effects of these manipulations on changes in CCK as a first test of whether sensory-enhanced, nutrient-based satiety involved changes in satiety signals beyond those implicated in cephalic-phase responses.

Materials and methods


A repeated-measures preload paradigm contrasted the satiating effects of four fruit yoghurt beverages combining two energy levels (high (HE), 274 kcal or low (LE), 78 kcal) and two levels of sensory quality (low (LS) or enhanced (ES)), giving four preloads (LSLE, ESLE, LSHE and ESHE). Satiety responses were assessed as changes in rated appetite and blood concentrations of glucose, insulin, PP and CCK over the 90 min following preload ingestion, and intake at a test lunch consumed 90 min after each preload.


Participants were recruited from Leatherhead Food Research’s volunteer database, and adverts were placed in papers, shops and companies in the local area. Potential participants had to meet the following inclusion criteria: men, apparently healthy, non-smoking, aged 18–55 years, not taking prescription medication. Those with diabetes, who reported allergy or aversion to the test products, any history of an eating disorder or who scored 7 or more on the restraint scale from the Three Factor Eating Questionnaire35 were excluded. Participants were 24 healthy volunteer men with an average age of 31 years (range 19–52 years) and an average BMI of 24.0 kg/m2 (range 20.0–28.9 kg/m2).

The study was approved by the London Queens Square Ethics Committee (REC reference: 12/LO/0737). All participants gave written informed consent to participate in the study and the study was conducted in accordance with the ethical standards laid down by the 1964 Declaration of Helsinki and in accordance with Good Clinical Practice guidelines.


Participants acted as their own controls and consumed each version of the test beverage on four separate occasions (days 2–5), following an initial acclimatisation (day 1). There was a 1-week washout period between test days, and the order of presentation of the test beverages was counterbalanced using a William’s design. On the day before each test session, participants were required to refrain from consuming alcohol and from doing any strenuous exercise. They arrived at the Nutrition Unit at Leatherhead Food Research between 0800 and 0900 hours in a fasted state having consumed only water from 2200 hours on the night before, and remained in the Unit for the duration of testing. After eating a standard breakfast (~500 kcal), participants relaxed in the test centre and were permitted to do non-strenuous activities (reading, TV watching, internet browsing, and so on). At 1 h 15 min post-breakfast, they had an indwelling catheter inserted for regular blood sampling and 45 min later were served the appropriate test beverage and asked to evaluate its flavour and then consume all of it (2 min given to consume entire portion). After 90 min, they were provided with an ad libitum lunch and intake was recorded. Appetite ratings were collected pre-preload and post-preload at 30 min intervals up until lunch and post-lunch. On the last day, height and weight were measured and participants debriefed. On day 1, the protocol was identical with the exception that participants were served water as the preload.

Appetite ratings

Ratings of appetite were recorded before and after preload consumption, between the preload and test meal and at the end of the meal. Responses were recorded using validated electronic VAS on handheld computers (iPAQs; Hull et al.36,37), which were programmed to prompt participants at the relevant times. Scales were end-anchored at one end with the lowest intensity feelings and the opposing term at the high end. Participants indicated on the 64-mm scale the place that best reflected their feelings at that moment, which was transformed into a score between 0 and 100. The questions asked were: ‘How hungry are you?’; ‘How full are you?’; ‘How satiated are you?’; ‘How strong is your desire to eat?’, based on the form of ratings recommended for satiety studies.38

Blood analyses

GastrointestinaI hormone levels were determined from plasma drawn before the beverage was served (time=−15 and 0 min: baseline measures) and then at 1, 3, 5, 10, 15, 30, 60 and 90 min after beverage ingestion. These times were selected based on previous research on cephalic-phase hormone release.17, 19 Immediately after each blood draw, the plasma was extracted by adding the samples to centrifuge tubes containing enough mixed K3EDTA to achieve a final concentration of 1.735 mg/ml and the sample aliquoted and stored in a −70 °C freezer. Because of the short duration between samples immediately after consumption, if blood could not be drawn within 30 s of the target time post-ingestion, no sample was taken at that time. This meant there were occasional missing samples because of problems with the catheters, and for three participants on one day and two test days for one participant, it was not possible to draw blood on at least four missing occasions per participant.

Hormone assays were conducted using commercial ELISA Kits: for PP (EMD Millipore, Watford, UK) and CCK (BioSupply plc, Bradford, UK), these kits used the sandwich ELISA approach. Blood glucose levels were measured using finger-prick blood sample collection. Samples were analysed immediately using a Yellow Springs Instruments (YSI; Tunbridge Wells, UK) analysis machine.

Test food and drink

The test fruit juice/yoghurt beverages used as preload stimuli were based on those we have used previously,32, 33, 39 and were the same as in a recent paper,40 with a 300 ml served portion (full ingredient list in Table 1). All drinks had a base of 100 g of a proprietary fruit juice (mango and papaya juice, Tropicana UK), combined with fat-free fromage frais (Sainsbury plc, London, UK) and a low-calorie fruit squash (low-calorie peach and barley; Robinson's Brand, Britvic plc, Hemel Hempstead, UK). Maltodextrin (C-dry md01910; Cargill plc, Weybridge, UK) was used to increase the caloric content, so that the HE version had ~200 kcal more than the LE (HE 274 kcal, LE 78 kcal). Sensory characteristics were manipulated by the addition of milk caramel flavouring (Symrise, Holzminden, Germany) and tara gum (Kalys Gastronomie, Bernin, France), and small quantities of aspartame were added to LE versions to counter the slight sweet taste of the added maltodextrin, and commercial food colours used to match the drinks visually. The final versions had been tested extensively to ensure that the ES manipulations generated satiety expectations and that the LE and HE versions were sensorially matched, as detailed elsewhere.40

Table 1 Composition of the test preload drinks

The two-course test lunch consisted of a large serving (1500 g) of pasta with tomato and cheese sauce. This was prepared on-site using a proprietary pasta sauce (tomato sauce, Dolmio brand), penne pasta (Sainsbury plc), vegetable oil and mozzarella cheese (Sainsbury plc), followed by a chocolate mousse (250 g portion; Sainsbury plc). Participants were permitted to eat as much or as little as they liked.

Data analysis

For intake data, one person did not complete two sessions and their data were discounted from analysis. Total mass and total calories consumed at the lunch were contrasted using a two-way analysis of variance with preload energy (LE or HE) and sensory (LS or ES) as factors.

Owing to problems getting blood drawn at the specified times, occasional sample loss during the assay process, and one participant not completing two sessions, there was at least one data point missing from blood samples for 14/23 participants. To assess effects of the preloads on changes in blood glucose and hormone levels, data from the two pre-preload samples were averaged to give a baseline level. These baseline values were then subtracted from all available post-preload samples giving a possible nine post-preload values. These data were then analysed using mixed linear modelling, with energy (LE or HE), sensory (LS or ES) and time (1, 3, 5, 10, 15, 30, 60 and 90 min post-preload) as fixed factors and participant as repeated random factor. This approach allowed us to make maximum use of available data. Appropriate contrasts were then conducted to determine the source of any significant effects.

For the appetite ratings (hunger, fullness, satiation and desire to eat), the IPAQ devices failed on several occasions, with data missing for 4/23 participants. Consequently, mixed linear modelling, with energy (LE or HE), sensory (LS or ES) and time (13, 28, 43,58, 73 and 90 min post-preload) as fixed factors and participant as repeated random factor, was used.


Test meal intake

As expected, the total weight of the lunch (pasta and dessert) was less following HE than LE drinks (F(1,22)=13.06, P=0.002, η2=0.37: Figure 1a), but this depended on the sensory characteristics of the test drink (energy × sensory interaction, F(1,22)=4.55, P=0.044, η2=0.17), with significantly lower lunch intake in the ESHE compared with LSLE (P=0.002) and ESLE (P<0.001) conditions, with LSHE intermediate. There was no significant difference in intake between the two LS conditions. The same data pattern was seen when caloric intake at the test meal was calculated (Figure 1b), with lower caloric intake following consumption of the HE drinks compared with the LE versions (F(1,22)=12.56, P=0.002, η2=0.36) and again this was affected by the drink’s sensory characteristics (energy × sensory interaction: F(1,22)=4.45, P=0.047, η2=0.17). When the difference in lunch intake was expressed as a percentage of the actual energy difference between equivalent HE and LE versions (a measure of compensation, COMPX: REF), this differed between sensory conditions (F(1,22)=4.45, P=0.047, η2=0.17), with higher compensation in the ES (92±17%) compared with LS condition (32±31%).

Figure 1

Intake at the test lunch after the four drink preloads (LE, low energy; HE, high energy; LS, low sensory; ES, enhanced sensory) expressed both as the mass consumed (a) and total energy consumed (b). Data are mean±s.e.m.

Hormone and glucose response

Blood glucose increased after preload ingestion after all four drinks, but this was significantly greater for HE than LE drinks (F(1,669=78.16, P<0.001: Figure 2a). There was no significant effect of the sensory manipulation on changes in blood glucose levels (F(1,669)=0.01, P=0.93), but there was a significant effect of time of rating (F(7,699)=34.50, P<0.001) and significant interaction between time of rating and energy (F(7,669)=8.65, P<0.001). Glucose levels rose within minutes of drink consumption and peaked around 30 min for HE drinks, earlier for LE (Figure 2a).

Figure 2

Changes in blood concentrations of (a) glucose, (b) insulin, (c) PP and (d) cholecystokinin across the 90 min post-preload drink in the LSLE (open circles, broken line), ESLE (open squares, broken line), LSHE (closed circle, solid line) and ESHE (solid squares, solid line) conditions.

Insulin levels also increased after drink ingestion (Figure 2b), and increased more overall after HE than LE drinks (F(1,665)=194.83, P<0.001). However, this increase in insulin was significantly greater after ES than LS drinks as well (F(1,665)=16.68, P<0.001), and the energy × sensory interaction was also significant (F(1,665)=5.70, P=0.017). The change in insulin varied with time (F(7,665)=52.10, P<0.001), and the peak increase was around 30 min in all conditions, but the change with time depended on energy (F(7665)=16.21, P<0.001).

In contrast to insulin and glucose, although levels of PP also increased post-ingestion, this was only significant in response to the sensory manipulation (F(1,665)=30.11, P<0.001), with no significant effect of energy (F(1,665)=0.95, P=0.33). Although there was a significant effect of time (F(7,665)=6.62, P<0.001), none of the interactions involving time were significant, nor was the energy × sensory interaction. As can be seen (Figure 2c), there was a small initial increase in PP soon after ingestion in all four conditions, but PP returned to baseline within 15 min in both LS conditions, but PP levels remained higher compared with baseline throughout the 90 min post-ingestion in both ES conditions.

The pattern of change in CCK after drink ingestion was complex, with significant overall effects of energy (F(1,665)=5.50, P=0.019), sensory (F(1,665)=23.01, P<0.001) and time (F(7,665)=2.47, P=0.016), and a significant sensory × energy interaction (F(1665)=3.86, P=0.05), but no other significant interactions. From Figure 2d it can be seen that in the first 15 min after ingestion, CCK only increased in the condition where additional energy was ingested in the ES context (i.e. ESHE): changes in the other conditions showed little difference from baselines during this time. There were then no significant differences between conditions at 30 and 60 min, but at 90 min, surprisingly, CCK increased again in the ESHE condition.

Rated appetite

The changes in hunger (Figure 3a) and desire to eat (Figure 3b) across the 90 min post-preload were similar: both varied significantly with time of rating (hunger (F(5,522)=14.98, P<0.001), desire (F(5,521)=14.18, P<0.001)), and were also affected by drink energy (hunger (F(1,522)=4.75, P=0.03), desire (F(1,521)=4.33, P=0.039)) and sensory (hunger (F(1,522)=3.78, P=0.045), desire (F(1,521)=4.40, P=0.036)). Hunger and desire to eat decreased in all conditions after drink consumption (13 min ratings), although these decreases tended to be greater after ES than LS drinks. Both hunger and desire to eat then increased up to lunch, but at no time was there a significant difference between the LSLE and LSHE conditions for either rating. Both hunger and desire to eat remained lower in the ESHE condition compared with any of the other conditions, whereas these ratings recovered most rapidly in the ESLE condition, so that the contrasts between ESHE and ESLE were significant for both ratings at 73 and 90 min (both P<0.05).

Figure 3

Changes in ratings of (a) hunger, (b) fullness, (c) desire to eat and (d) satiation across the 90 min post-preload drink in the LSLE (open circles, broken line), ESLE (open squares, broken line), LSHE (closed circle, solid line) and ESHE (solid squares, solid line) conditions.

The change in fullness (Figure 3c) and satiation (Figure 3d) ratings after preload ingestion largely mirrored the pattern seen with hunger and desire to eat, although the clearest dissociation between the four drinks was seen with fullness ratings, with large overall effects of time (F(5,522)=8.39, P<0.001), energy (F(1,522)=10.10, P=0.002) and sensory (F(1,522)=7.47, P=0.006), as well as a significant energy × sensory interaction (F(1,522)=4.29, P=0.039). Fullness increased significantly after drink ingestion for all four drinks but then remained higher in the ESHE condition than the other three drinks, where changes were similar. At no time was the contrast between LSHE and LSLE significant, but the contrast between ESHE and ESLE was significant at the 58, 73 and 90 min time points. The changes in satiation ratings followed the same essential pattern as fullness, as would be expected, but only the effects of time (F(5,522)=8.40, P<0.001) and energy (F(1,522)=14.75, P<0.001) were significant. Figure 3d shows much less dissociation between the ESHE and LSHE for this rating than the other three, but although effects of sensory were not significant the decrease in satiation for ESLE follows a similar pattern, faster recovery than in LSLE, that was seen with fullness ratings.


The key finding from this study was that increases in plasma levels of PP, insulin and CCK after consuming drinks depended both on the energy content and sensory characteristics of the beverage consumed. These manipulations also altered satiety responses in response to covert nutrient manipulations, replicating previous research.31, 32, 33, 34

The ability of the present study to assess cued hormonal release in response to manipulated sensory characteristics of the test beverages relied on replication of our earlier behavioural findings using similar drink manipulations. The present lunch intake data confirmed this: participants consumed less after covert energy manipulation, but this effect was larger when nutrients were added to a thicker, more creamy beverage (ES). Data for rated appetite also supported this sensory-enhanced satiety, and also provided evidence of 'rebound hunger' in the situation where sensory characteristics predicted a more nutrient-rich drink, but the actual nutrient content was minimal (78 kcal). Initially, consuming the ES drink reduced hunger regardless of nutrient content. However, from 30 min onwards hunger recovered more rapidly after ESLE than ESHE versions, consistent with the rebound hunger we have reported in related studies.32 This question attempts to develop new food products with reduced energy content without altering sensory characteristics: where the experienced effects of nutrients fall short of what is expected, this mismatch could lead to subsequent increased hunger and consequent increased intake.30

Analysis of hormone data provided evidence to support the predicted sensory-modulation of responses to ingested nutrients. Given that some earlier studies reported no cephalic-phase responses to liquids,17, 20 the present study is the first to find changes in a drink context. The hypothesis that the ES manipulation would stimulate insulin release, based on CPIR,20, 22 was supported, with larger increases in plasma insulin after ESHE than LSHE drinks, as well as expected effects of nutrient intake on both insulin and glucose response. However, if this was purely down to CPIR the prediction would have been that these effects would be strongest shortly after drink ingestion,20, 22 whereas actual increases in insulin after ES drinks peaked between 10 and 30 min. Could this then be a physiological response to the tara gum used to increase drink thickness? Previous research does not suggest that the galactomannan found in tara gum would have been predicted to have had the opposite effect to that seen here, as there is considerable evidence that soluble fibres reduced both postprandial insulin responses and hyperglycaemia associated with glucose ingestion.41, 42, 43 Thus, the most plausible explanation for effects of sensory manipulations on insulin is through top-down modulation of the insulin response.

The clearest effects of sensory manipulations on hormonal responses were with PP. PP levels were significantly elevated after ES but not LS drinks, with this effect evident shortly after drink ingestion and sustained for the 90 min measurement period. The lack of effect of covert energy manipulations on PP levels was notable. PP has been implicated as a satiety signal: infusion of PP reduces food intake in humans,44, 45 and PP levels can be increased for as long as 6 h after a meal.46 What was surprising in the present study was that ingestion of the ESLE drink significantly increased PP levels, but this increase was neither associated with decreased hunger or decreased food intake: on the contrary, people were more hungry prelunch after the ESLE than LSLE drink. Thus, PP release may be a signal of potential satiety, which is integrated with actual nutrient detection to achieve actual satiety. This pattern of response contrasted with the effects of the same drinks on CCK, where increased CCK was only seen with the ESHE drink: neither consumption of the ESLE or LSHE drinks resulted in increased CCK. Thus, our data suggest that physiological satiety cues require integration of cues predictive of nutrient content (the ES manipulation) with actual sensed nutrient intake (covert energy manipulation). This clearly implies much greater top-down control of how the gut responds to nutrient ingestion than had been previously credited.

How then might sensory manipulations result in enhanced PP and CCK release? Traditional bottom-up models of appetite control postulate that nutrient detection in the gut stimulates release of satiety-related gut hormones, which in turn act to suppress subsequent intake.47, 48, 49 However, such models cannot readily explain the present data. Similarly, the ideas that cues that predict nutrients lead to preparatory physiological responses in preparation for nutrient processing are well known and established,12 but these models are based on conditioned responses that arise from multiple pairings of stimuli. What the present, and other recent,29 data suggest is that in humans the expectation that a food will be filling may be sufficient to produce top-down preparatory responses that lead to modifications in the way nutrients are subsequently processed. Thus, this explanation suggests that the observed hormonal responses were a result of some form of priming of hormone release. For PP this appears adequate as enhanced PP was only seen after ES manipulations. However, CCK release was dependent on both the sensory and nutrient manipulations, implying that the top-down priming of CCK release integrated with actual nutrient sensing. These explanations at present are descriptive: the key aim of future work must now be to examine these at a mechanistic level.

A clear limitation of the present study was that the hormonal response data were limited to CCK, insulin and PP: budget limitations precluded assays of ghrelin, GLP-1 or polypeptide YY. Further work is needed to test whether other hormones implicated with appetite control show similar top-down control. Ghrelin and GLP-1 may be especially interesting in this context: the recovery of ghrelin post-ingestion has been found to vary with beliefs about the nature of the drink,50 whereas belief of whether a product is solid or liquid in the gut influenced the GLP-1 response.29 Similarly, effects on rates of gastric emptying, and so on, need to be investigated. However, the present data clearly show that small modifications to the characteristics of a beverage are sufficient to alter gut responses within the range of responses measured by this study.


  1. 1

    Hill JO, Wyatt HR, Peters JC . Energy balance and obesity. Circulation 2012; 126: 126–132.

    Article  Google Scholar 

  2. 2

    Sclafani A, Ackroff K . Role of gut nutrient sensing in stimulating appetite and conditioning food preferences. Am J Physiol 2012; 302: R1119–R1133.

    CAS  Article  Google Scholar 

  3. 3

    Sam AH, Troke RC, Tan TM, Bewick GA . The role of the gut/brain axis in modulating food intake. Neuropharmacology 2012; 63: 46–56.

    CAS  Article  Google Scholar 

  4. 4

    Hussain S, Bloom S . The regulation of food intake by the gut–brain axis: implications for obesity. Int J Obes 2013; 37: 625–633.

    CAS  Article  Google Scholar 

  5. 5

    Hellström PM . Satiety signals and obesity. Curr Opin Gastroenterol 2013; 29: 222–227.

    Article  Google Scholar 

  6. 6

    Perry B, Wang Y . Appetite regulation and weight control: the role of gut hormones. Nutr Diabetes 2012; 2: e26.

    CAS  Article  Google Scholar 

  7. 7

    Holzer P, Reichmann F, Farzi A, . Neuropeptide Y, peptide YY and pancreatic polypeptide in the gut–brain axis. Neuropeptides 2012; 46: 261–274.

    CAS  Article  Google Scholar 

  8. 8

    Stubbs J, Whybrow S Beverages, appetite and energy balance. In: Wilson T Temple NJ (eds). Beverages in Nutrition and Health. Humana Press: Totowa, NJ, USA, 2003, pp 261–278.

    Google Scholar 

  9. 9

    de Graaf C . Why liquid energy results in overconsumption. P Nutr Soc 2011; 70: 162–170.

    Article  Google Scholar 

  10. 10

    Mattes R . Soup and satiety. Physiol Behav 2005; 83: 739–747.

    CAS  Article  Google Scholar 

  11. 11

    Pavlov IP, Gantt WH, Volborth G, Cannon WB . Conditioned Reflexes and Psychiatry, vol 2. International Publishers: New York, NY, USA, 1941.

    Google Scholar 

  12. 12

    Woods SC . The eating paradox: how we tolerate food. Psychol Rev 1991; 98: 488–505.

    CAS  Article  Google Scholar 

  13. 13

    Teff KL, Mattes RD, Engelman K . Cephalic phase insulin release in normal weight males: verification and reliability. Am J Physiol 1991; 261: E430–E436.

    CAS  PubMed  Google Scholar 

  14. 14

    Teff KL, Mattes RD, Engelman K, Mattern J . Cephalic-phase insulin in obese and normal-weight men: relation to postprandial insulin. Metabolism 1993; 42: 1600–1608.

    CAS  Article  Google Scholar 

  15. 15

    Berthoud H, Jeanrenaud B . Sham feeding-induced cephalic phase insulin release in the rat. Am J Physiol 1982; 242: E280–E285.

    CAS  PubMed  Google Scholar 

  16. 16

    Bernstein IL, Woods SC . Ontogeny of cephalic insulin release by the rat. Physiol Behav 1980; 24: 529–532.

    CAS  Article  Google Scholar 

  17. 17

    Teff KL, Devine J, Engelman K . Sweet taste: effect on cephalic phase insulin release in men. Physiol Behav 1995; 57: 1089–1095.

    CAS  Article  Google Scholar 

  18. 18

    Just T, Pau HW, Engel U, Hummel T . Cephalic phase insulin release in healthy humans after taste stimulation? Appetite 2008; 51: 622–627.

    CAS  Article  Google Scholar 

  19. 19

    Teff KL . Cephalic phase pancreatic polypeptide responses to liquid and solid stimuli in humans. Physiol Behav 2010; 99: 317–323.

    CAS  Article  Google Scholar 

  20. 20

    Teff K . Nutritional implications of the cephalic-phase reflexes: endocrine responses. Appetite 2000; 34: 206–213.

    CAS  Article  Google Scholar 

  21. 21

    Schwartz T, Stenquist B, Olbe L . Cephalic phase of pancreatic-polypeptide secretion studied by sham feeding in man. Scand J Gastroenterol 1979; 14: 313–320.

    CAS  Article  Google Scholar 

  22. 22

    Smeets PAM, Erkner A, de Graaf C . Cephalic phase responses and appetite. Nutr Rev 2010; 68: 643–655.

    Article  Google Scholar 

  23. 23

    Schwartz T, Holst J, Fahrenkrug J, Jensen SL, Nielsen OV, Rehfeld J et al. Vagal, cholinergic regulation of pancreatic polypeptide secretion. J Clin Invest 1978; 61: 781.

    CAS  Article  Google Scholar 

  24. 24

    Schwartz TW . Pancreatic polypeptide: a unique model for vagal control of endocrine systems. J Auton Nerv Syst 1983; 9: 99–111.

    CAS  Article  Google Scholar 

  25. 25

    Taylor I, Feldman M . Effect of cephalic–vagal stimulation on insulin, gastric inhibitory polypeptide, and pancreatic polypeptide release in humans*. J Clin Endocrinol Metab 1982; 55: 1114–1117.

    CAS  Article  Google Scholar 

  26. 26

    Asakawa A, Inui A, Yuzuriha H, Ueno N, Katsuura G, Fujimiya M et al. Characterization of the effects of pancreatic polypeptide in the regulation of energy balance. Gastroenterology 2003; 124: 1325–1336.

    CAS  Article  Google Scholar 

  27. 27

    Kojima S, Ueno N, Asakawa A, Sagiyama K, Naruo T, Mizuno S et al. A role for pancreatic polypeptide in feeding and body weight regulation. Peptides 2007; 28: 459–463.

    CAS  Article  Google Scholar 

  28. 28

    Jayasena CN, Bloom SR . Role of gut hormones in obesity. Endocrin Metab Clin 2008; 37: 769–787.

    CAS  Article  Google Scholar 

  29. 29

    Cassady BA, Considine RV, Mattes RD . Beverage consumption, appetite, and energy intake: what did you expect? Am J Clin Nutr 2012; 95: 587–593.

    CAS  Article  Google Scholar 

  30. 30

    Chambers L, McCrickerd K, Yeomans MR . Optimising foods for satiety. Trends Food Sci Technol 2015; 41: 149–160.

    CAS  Article  Google Scholar 

  31. 31

    Chambers L, Ells H, Yeomans MR . Can the satiating power of a high energy beverage be improved by manipulating sensory characteristics and label information? Food Qual Prefer 2013; 28: 271–278.

    Article  Google Scholar 

  32. 32

    Yeomans MR, Chambers LC . Satiety-relevant sensory qualities enhance the satiating effects of mixed carbohydrate-protein preloads. Am J Clin Nutr 2011; 94: 1410–1417.

    CAS  Article  Google Scholar 

  33. 33

    Yeomans MR, McCrickerd K, Brunstrom JM, Chambers L . Effects of repeated consumption on sensory-enhanced satiety. Brit J Nutr 2014; 111: 1137–1144.

    CAS  Article  Google Scholar 

  34. 34

    McCrickerd K, Chambers L, Yeomans MR . Fluid or fuel? The context of consuming a beverage is important for satiety. PLoS One 2014; 9: e100406.

    Article  Google Scholar 

  35. 35

    Stunkard AJ, Messick S . The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res 1985; 29: 71–83.

    CAS  Article  Google Scholar 

  36. 36

    Hull S, Re R, Tiihonen K, Viscione L, Wickham M . Consuming polydextrose in a mid-morning snack increases acute satiety measurements and reduces subsequent energy intake at lunch in healthy human subjects. Appetite 2012; 59: 706–712.

    CAS  Article  Google Scholar 

  37. 37

    Hull S, Re R, Chambers L, Echaniz A, Wickham MS . A mid-morning snack of almonds generates satiety and appropriate adjustment of subsequent food intake in healthy women. Eur J Nutr 2014; 1–8.

  38. 38

    Blundell J, De Graaf C, Hulshof T, Jebb S, Livingstone B, Lluch A et al. Appetite control: methodological aspects of the evaluation of foods. Obes Rev 2010; 11: 251–270.

    CAS  Article  Google Scholar 

  39. 39

    McCrickerd K, Chambers L, Brunstrom JM, Yeomans MR . Subtle changes in the flavour and texture of a drink enhance expectations of satiety. Flavour 2012; 1: 20.

    Article  Google Scholar 

  40. 40

    McCrickerd K, Chambers L, Yeomans MR . Does modifying the thick texture and creamy flavour of a drink change portion size selection and intake? Appetite 2014; 73: 114–120.

    Article  Google Scholar 

  41. 41

    Morgan L, Tredger J, Wright J, Marks V . The effect of soluble- and insoluble-fibre supplementation on post-prandial glucose tolerance, insulin and gastric inhibitory polypeptide secretion in healthy subjects. Br J Nutr 1990; 64: 103–110.

    CAS  Article  Google Scholar 

  42. 42

    Jenkins DJ, Axelsen M, Kendall CW, Augustin LS, Vuksan V, Smith U . Dietary fibre, lente carbohydrates and the insulin-resistant diseases. Br J Nutr 2000; 83: S157–S163.

    CAS  Article  Google Scholar 

  43. 43

    Slavin J, Green H . Dietary fibre and satiety. Nutr Bull 2007; 32: S32–S42.

    Article  Google Scholar 

  44. 44

    Batterham R, Le Roux C, Cohen M, Park A, Ellis S, Patterson M et al. Pancreatic polypeptide reduces appetite and food intake in humans. J Clin Endocrinol Metab 2003; 88: 3989–3992.

    CAS  Article  Google Scholar 

  45. 45

    Berntson GG, Zipf WB, O'Dorisio TM, Hoffman JA, Chance RE . Pancreatic polypeptide infusions reduce food intake in Prader-Willi syndrome. Peptides 1993; 14: 497–503.

    CAS  Article  Google Scholar 

  46. 46

    Adrian T, Bloom S, Bryant M, Polak J, Heitz P, Barnes A . Distribution and release of human pancreatic polypeptide. Gut 1976; 17: 940–944.

    CAS  Article  Google Scholar 

  47. 47

    Little T, Horowitz M, Feinle‐Bisset C . Role of cholecystokinin in appetite control and body weight regulation. Obes Rev 2005; 6: 297–306.

    CAS  Article  Google Scholar 

  48. 48

    Murphy KG, Bloom SR . Gut hormones and the regulation of energy homeostasis. Nature 2006; 444: 854–859.

    CAS  Article  Google Scholar 

  49. 49

    Chaudhri OB, Salem V, Murphy KG, Bloom SR . Gastrointestinal satiety signals. Annu Rev Physiol 2008; 70: 239–255.

    CAS  Article  Google Scholar 

  50. 50

    Crum AJ, Corbin WR, Brownell KD, Salovey P, Mind Over . Milkshakes: mindsets, not just nutrients, determine ghrelin response. Health Psychol 2011; 30: 424–429.

    Article  Google Scholar 

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Correspondence to M R Yeomans.

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Competing interests

This study was conducted as part of research grant BB/H004645/1 from the UK Biotechnology and Biological Sciences Research Council (BBSRC) as part of the DRINC initiative. The authors declare no conflict of interest relating to the outcomes of the reported study.

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Yeomans, M., Re, R., Wickham, M. et al. Beyond expectations: the physiological basis of sensory enhancement of satiety. Int J Obes 40, 1693–1698 (2016).

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