Speed limits: the effects of industrial food processing and food texture on daily energy intake and eating behaviour in healthy adults.

PURPOSE: Frequent consumption of industrially processed foods has been associated with obesity. However, it is unknown what drives this association. Food textures of industrially processed foods that stimulate energy overconsumption may be an important driver of this association. Therefore, this study aimed to determine the independent and combined effects of food texture and level of industrial food processing (based on the NOVA classification) on daily energy intake and eating behaviour. METHODS: Eighteen healthy adults (F/M: 11/7, 23 ± 3 y, 22.1 ± 2.0 kg/m2) participated in a 2 × 2 randomized crossover dietary intervention with four conditions (total of 288 meals): hard unprocessed, hard (ultra-)processed, soft unprocessed and soft (ultra-)processed. Daily diets were offered ad libitum and were equal in energy density (1 kcal/g). Food Intake (g) was measured by pre- and post-consumption weighing of the plates. Eating behaviour parameters were derived from video annotations. RESULTS: Daily energy intake and food intake were, respectively, 33% (571 ± 135 kcal) and 14% (247 ± 146 g) lower in the hard compared to the soft conditions (main texture p < 0.001). Energy intake was lower in both hard conditions compared to the (ultra)processed soft condition (Tukey p < 0.04). Eating rate (g/min) was on average 85% slower (P < 0.001) in the hard compared to the soft conditions (p < 0.001). Level of processing did not affect food intake. CONCLUSION: Consumption of hard-textured foods reduces daily energy intake of (ultra-) processed foods. This preliminary investigation shows that there is great variability in food properties that affect energy and food intake beyond industrial food processing. However, findings should be interpreted with precaution considering the limited sample size of this trial. Future classification systems for public health messaging should include energy intake rate to help reduce overconsumption. CLINICAL TRIAL REGISTRY: NCT04280146, https://www. CLINICALTRIALS: gov , February 21st 2020.

Study protocol of the sweet tooth study, randomized controlled trial with partial food provision on the effect of low, regular and high dietary sweetness exposure on sweetness preferences in Dutch adults.

BACKGROUND: Several health organizations recommend lowering the consumption of sweet-tasting foods. The rationale behind this recommendation is that a lower exposure to sweet foods may reduce preferences for sweet tasting foods, thus lowering sugar and energy intake, and in turn aiding in obesity prevention. However, empirical data supporting this narrative are lacking. In fact, relatively little is known about the contribution of long-term sweet taste exposure on one's sweetness preferences. METHODS: The primary objective of this randomized controlled trial is to assess the effect of low, regular and high dietary sweetness exposure on preference for sweet foods and beverages, and to compare these effects between intervention groups. One hundred and eighty adults aged 18-65 years with a BMI of 18.5-30.0 kg/m2 will be recruited and randomly allocated to either: low dietary sweetness exposure (LSE) (10-15% daily energy from sweet tasting foods), regular dietary sweetness exposure (RSE) (25-30% daily energy from sweet tasting foods), or high dietary sweetness exposure (HSE) (40-45% daily energy from sweet tasting foods), for 6 months, followed by a 4-month follow up. Intervention foods are provided ad libitum, covering approximately 50% of the daily number of food items, to include sugar-sweetened, low-calorie-sweetener-sweetened and non-sweet foods. The primary outcome measure is the difference in change in sweetness preference from baseline to 6 months between intervention groups. Secondary outcomes include: change in sweet taste preferences at different time-points; taste intensity perception; behavioral outcomes: food choice and intake, sweet-liker type, food cravings, dietary taste preferences and dietary taste patterns; anthropometric outcomes: body composition, waist-hip circumference, body weight; and biochemical outcomes: glucose variability and biomarkers related to CVD and diabetes. DISCUSSION: This study will generate important data on the effect of dietary sweetness exposure on sweetness preferences in terms of effect size and change, duration of change and its impact on food intake, body weight status and associated health outcomes. TRIAL REGISTRATION: The study protocol has been registered on ClinicalTrials.gov (ID no. NCT04497974, Registered 4 August 2020, https://clinicaltrials.gov/ct2/show/NCT04497974 ) and approved by Wageningen's Medical Ethical Committee (ABR no. NL72134).

Does odour priming influence snack choice? - An eye-tracking study to understand food choice processes.

Awareness of food sensory cues in our surroundings may influence our eating behaviour in different ways. For example, exposure to non-consciously perceived odours may influence food choice but not appetite. Moreover, this type of exposure may mainly influence the food choice of starters or desserts but not of main courses. This infers that odour priming may influence impulsive or rewarding food choice but may not overrule our habits concerning the choice of a main meal. It is crucial to understand the role of odour priming on eating behaviour and how people can be steered towards healthier options. Implicit measures, such as visual attention, may be central to understand the food choice process. Therefore, we aimed to determine how non-conscious exposure to odours affect congruent snack choice (i.e. with similar taste characteristics) and whether this is modulated by visual attention. A total of 53 healthy young adults took part in a cross-over study which consisted of two test sessions. In each test session, they were non-consciously exposed to an odour that is associated to a sweet or savoury food. Visual attention was investigated by means of a wearable eye-tracker and subsequent snack choice was (covertly) measured. Our results showed that congruent snacks were fixated on first. However, sweet snacks were fixated on more frequently, and for a longer period of time, and were chosen most often, irrespective of the type of odour exposure. Our findings indicate that odour priming might steer the initial orientation towards congruent foods, but other factors (e.g. cognitive) may overrule its effect on the final choice.

Both Nonsmoking Youth and Smoking Adults Like Sweet and Minty E-liquid Flavors More Than Tobacco Flavor.

Smokers may reduce their health risk by switching to electronic cigarette (e-cigarette) use. As e-cigarettes are not harmless, concerns exist about e-cigarette use by nonsmokers and youth. E-liquids are available in many different flavors that increase sensory appeal. Flavor preferences may differ between user groups, which could open doors for product regulation. We investigated which e-liquid flavors are attractive to specific user groups by comparing liking between adolescent nonsmokers (n = 41; mean age 16.9 ± 0.8), young adult nonsmokers (n = 42; mean age 22.7 ± 1.7), and adult smokers (n = 56; mean age 39.7 ± 11.1). Participants smelled tobacco- (n = 6) and nontobacco (n = 24)-flavored e-liquids and rated liking on a 9-point labeled hedonic scale, and familiarity, overall intensity, perceived sweetness, perceived bitterness, and irritation of the odors on a 100-unit Visual Analog Scale. Mean liking ranged from 2.3 (whiskey) to 6.7 (peppermint). Within all groups, the typically sweet and minty flavors (e.g., wine gum, watermelon, peppermint, menthol) were liked significantly more than the tobacco-flavored e-liquids. The set of tobacco-flavored e-liquids was significantly, but slightly, less disliked by adult smokers (3.9 ± 0.2) than adolescent (3.1 ± 0.3) and young adult (3.4 ± 0.3) nonsmokers (P < 0.001). No between-group differences were observed for sweet and minty flavors. Liking correlated significantly positively with odor sweetness (R = 0.49) and familiarity (R = 0.48) and negatively with odor bitterness (R = -0.58), irritation (R = -0.47), and overall intensity (R = -0.27). Thus, sweet- and minty-flavored e-liquids are liked equally by young nonsmokers and adult smokers, and more than tobacco flavors. Banning all flavors except tobacco will likely reduce e-cigarette appeal; potentially more for young nonsmokers than adult smokers.

Nearly 20 000 e-liquids and 250 unique flavour descriptions: an overview of the Dutch market based on information from manufacturers.

OBJECTIVES: Flavours increase attractiveness of electronic cigarettes and stimulate use among vulnerable groups such as non-smoking adolescents. It is important for regulators to monitor the market to gain insight in, and regulate the range of e-liquid flavours that is available to consumers. E-liquid manufacturers are required to report key product information to authorities in the European Member States in which they plan to market their products. This information was used to provide an overview of e-liquid flavour descriptions marketed in the Netherlands in 2017. METHODS: Two researchers classified 19 266 e-liquids into the 16 main categories of the e-liquid flavour wheel, based on information from four variables in the European Common Entry Gate system. Flavour descriptions were further specified in subcategories. RESULTS: For 16 300 e-liquids (85%), sufficient information was available for classification. The categories containing the highest number of e-liquids were fruit (34%), tobacco (16%) and dessert (10%). For all e-liquids, excluding unflavoured ones, 245 subcategories were defined within the main categories. In addition to previously reported subcategories, various miscellaneous flavours such as sandwich, buttermilk and lavender were identified. CONCLUSIONS: In 2017, ~20 000 e-liquids were reported to be marketed in the Netherlands, in 245 unique flavour descriptions. The variety of marketed flavour descriptions reflects flavour preference of e-cigarette users as described in literature. Our systematic classification of e-liquids by flavour description provides a tool for organising the huge variety in market supply, serves as an example for other countries to generate similar overviews and can support regulators in developing flavour regulations.

Comprehensive overview of common e-liquid ingredients and how they can be used to predict an e-liquid's flavour category.

OBJECTIVES: Flavours increase e-cigarette attractiveness and use and thereby exposure to potentially toxic ingredients. An overview of e-liquid ingredients is needed to select target ingredients for chemical analytical and toxicological research and for regulatory approaches aimed at reducing e-cigarette attractiveness. Using information from e-cigarette manufacturers, we aim to identify the flavouring ingredients most frequently added to e-liquids on the Dutch market. Additionally, we used flavouring compositions to automatically classify e-liquids into flavour categories, thereby generating an overview that can facilitate market surveillance. METHODS: We used a dataset containing 16 839 e-liquids that were manually classified into 16 flavour categories in our previous study. For the overall set and each flavour category, we identified flavourings present in more than 10% of the products and their median quantities. Next, quantitative and qualitative ingredient information was used to predict e-liquid flavour categories using a random forest algorithm. RESULTS: We identified 219 unique ingredients that were added to more than 100 e-liquids, of which 213 were flavourings. The mean number of flavourings per e-liquid was 10±15. The most frequently used flavourings were vanillin (present in 35% of all liquids), ethyl maltol (32%) and ethyl butyrate (28%). In addition, we identified 29 category-specific flavourings. Moreover, e-liquids' flavour categories were predicted with an overall accuracy of 70%. CONCLUSIONS: Information from manufacturers can be used to identify frequently used and category-specific flavourings. Qualitative and quantitative ingredient information can be used to successfully predict an e-liquid's flavour category, serving as an example for regulators that have similar datasets available.

Sensory Evaluation of E-Liquid Flavors by Smelling and Vaping Yields Similar Results.

INTRODUCTION: Sensory research on e-liquid flavors can be performed by means of smelling and vaping. However, data comparing smelling versus vaping e-liquid flavors are lacking. This study aims to investigate if smelling could be an alternative to vaping experiments by determining the correlation for hedonic flavor assessment between orthonasal smelling and vaping of e-liquids, for smokers and nonsmokers. METHODS: Twenty-four young adult smokers (mean age 24.8 ± 9.3) and 24 nonsmokers (mean age 24.9 ± 7.7) smelled and vaped 25 e-liquids in various flavors. Participants rated liking, intensity, familiarity, and irritation on a 100-mm Visual Analog Scale. Pearson correlations within and between smelling and vaping were calculated. Differences between user groups were calculated using t tests. RESULTS: Correlation coefficients between smelling and vaping based on mean group ratings were 0.84 for liking, 0.82 for intensity, 0.84 for familiarity, and 0.73 for irritation. Means of the within-subjects correlation coefficients were, respectively, 0.51, 0.37, 0.47, and 0.25. Correlations between smelling and vaping varied across individuals (ranging from -0.27 to 0.87) and flavors (-0.33 to 0.81). Correlations and mean liking ratings did not differ between smokers and nonsmokers. CONCLUSIONS: The strong group-level correlations between orthonasal smelling and vaping e-liquid flavors justify the use of smelling instead of vaping in future research. For example, smelling could be used to investigate differences in e-liquid flavor liking between (potential) user groups such as nicotine-naïve adolescents. The more modest within-subject correlations and variation across individuals and flavors merit caution in using smelling instead of vaping in other types of experiments. IMPLICATIONS: This study supports the use of orthonasal smelling (instead of vaping) e-liquids to measure hedonic flavor perception in some studies where vaping would be inappropriate or not feasible. Examples of research situations where smelling e-liquids may be sufficient are (1) investigating nicotine-naïve individuals (ie, nonusers), (2) investigating individuals under legal age for e-cigarette use (ie, youth and adolescents), (3) investigating brain responses to exposure of e-liquid flavors using functional magnetic resonance imaging or electroencephalogram, and (4) comparing hedonic flavor assessment between adolescent nonusers and current smokers to provide support for future regulations on e-liquid flavors.

Expert consensus on low-calorie sweeteners: facts, research gaps and suggested actions.

A consensus workshop on low-calorie sweeteners (LCS) was held in November 2018 where seventeen experts (the panel) discussed three themes identified as key to the science and policy of LCS: (1) weight management and glucose control; (2) consumption, safety and perception; (3) nutrition policy. The aims were to identify the reliable facts on LCS, suggest research gaps and propose future actions. The panel agreed that the safety of LCS is demonstrated by a substantial body of evidence reviewed by regulatory experts and current levels of consumption, even for high users, are within agreed safety margins. However, better risk communication is needed. More emphasis is required on the role of LCS in helping individuals reduce their sugar and energy intake, which is a public health priority. Based on reviews of clinical evidence to date, the panel concluded that LCS can be beneficial for weight management when they are used to replace sugar in products consumed in the diet (without energy substitution). The available evidence suggests no grounds for concerns about adverse effects of LCS on sweet preference, appetite or glucose control; indeed, LCS may improve diabetic control and dietary compliance. Regarding effects on the human gut microbiota, data are limited and do not provide adequate evidence that LCS affect gut health at doses relevant to human use. The panel identified research priorities, including collation of the totality of evidence on LCS and body weight control, monitoring and modelling of LCS intakes, impacts on sugar reduction and diet quality and developing effective communication strategies to foster informed choice. There is also a need to reconcile policy discrepancies between organisations and reduce regulatory hurdles that impede low-energy product development and reformulation.

Foraging minds in modern environments: High-calorie and savory-taste biases in human food spatial memory.

Human memory may show sensitivity to content that carried fitness-relevance throughout evolutionary history. We investigated whether biases in human food spatial memory exist and influence the eating behavior of individuals within the modern food environment. In two lab studies with distinct samples of 88 participants, individuals had to re-locate foods on a map in a computer-based spatial memory task using visual (Study 1) or olfactory (Study 2) cues that signaled sweet and savory high- and low-calorie foods. Individuals consistently displayed an enhanced memory for locations of high-calorie and savory-tasting foods - regardless of hedonic evaluations, personal experiences with foods, or the time taken to encode food locations. However, we did not find any clear effects of the high-calorie or savory-taste bias in food spatial memory on eating behavior. Findings highlight that content matters deeply for the faculty of human food spatial memory and indicate an implicit cognitive system presumably attuned to ancestral priorities of optimal foraging.

An E-Liquid Flavor Wheel: A Shared Vocabulary Based on Systematically Reviewing E-Liquid Flavor Classifications in Literature.

INTRODUCTION: E-liquids are available in a high variety of flavors. A systematic classification of e-liquid flavors is necessary to increase comparability of research results. In the food, alcohol, and fragrance industry, flavors are classified using flavor wheels. We systematically reviewed literature on flavors related to electronic cigarette use, to investigate how e-liquid flavors have been classified in research, and propose an e-liquid flavor wheel to classify e-liquids based on marketing descriptions. METHODS: The search was conducted in May 2017 using PubMed and Embase databases. Keywords included terms associated with electronic cigarette, flavors, liking, learning, and wanting in articles. Results were independently screened and reviewed. Flavor categories used in the articles reviewed were extracted. RESULTS: Searches yielded 386 unique articles of which 28 were included. Forty-three main flavor categories were reported in these articles (eg, tobacco, menthol, mint, fruit, bakery/dessert, alcohol, nuts, spice, candy, coffee/tea, beverages, chocolate, sweet flavors, vanilla, and unflavored). Flavor classifications of e-liquids in literature showed similarities and differences across studies. Our proposed e-liquid flavor wheel contains 13 main categories and 90 subcategories, which summarize flavor categories from literature to find a shared vocabulary. For classification of e-liquids using our flavor wheel, marketing descriptions should be used. CONCLUSIONS: We have proposed a flavor wheel for classification of e-liquids. Further research is needed to test the flavor wheels' empirical value. Consistently classifying e-liquid flavors using our flavor wheel in research (eg, experimental, marketing, or qualitative studies) minimizes interpretation differences and increases comparability of results. IMPLICATIONS: We reviewed e-liquid flavors and flavor categories used in research. A large variation in the naming of flavor categories was found and e-liquid flavors were not consistently classified. We developed an e-liquid flavor wheel and provided a guideline for systematic classification of e-liquids based on marketing descriptions. Our flavor wheel summarizes e-liquid flavors and categories used in literature in order to create a shared vocabulary. Applying our flavor wheel in research on e-liquids will improve data interpretation, increase comparability across studies, and support policy makers in developing rules for regulation of e-liquid flavors.

Small food texture modifications can be used to change oral processing behaviour and to control ad libitum food intake.

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.

Impact of food odors signaling specific taste qualities and macronutrient content on saliva secretion and composition.

Olfactory food cues can induce appetite for similar food products in humans. Odors may thus signal essential information about a foods' composition such as taste or even macronutrient content and may stimulate specific physiological responses in anticipation of food intake. Several studies have shown that sensory food cues could stimulate saliva secretion. However, potential differences between food odors in their effect on saliva secretion, or the effects of olfactory stimulation on changes in saliva composition remain to be elucidated. To gain more insight, we conducted two studies to determine the influence of various odors, representing different taste qualities (study 1) and macronutrients (study 2), on salivary biomarkers. In study 1, 36 participants were randomly exposed to no-odor, non-food, and odors signaling sweet, savory, and sour taste. In study 2, 60 participants were randomly exposed to no-odor, non-food, and odors signaling carbohydrates, protein, fat, and low-calorie food. For each condition, whole-mouth saliva was collected and saliva secretion rate determined. Furthermore, we determined mouth-watering perception (subjective salivation), visco-elasticity (study 1 only), mucin concentration, α-amylase and lingual lipase activity (study 2 only). For both studies, linear mixed model analyses showed that saliva secretion rate significantly increased by food odor exposure compared to no-odor and non-food conditions. However, no changes in salivary composition were observed. These findings indicate that food odors play a crucial role in anticipatory saliva responses and can thereby affect subsequent eating behavior.

Severity of olfactory deficits is reflected in functional brain networks-An fMRI study.

Even though deficits in olfactory function affect a considerable part of the population, the neuronal basis of olfactory deficits remains scarcely investigated. To achieve a better understanding of how smell loss affects neural activation patterns and functional networks, we set out to investigate patients with olfactory dysfunction using functional magnetic resonance imaging (fMRI) and olfactory stimulation. We used patients' scores on a standardized olfactory test as continuous measure of olfactory function. 48 patients (mean olfactory threshold discrimination identification (TDI) score = 16.33, SD = 6.4, range 6 - 28.5) were investigated. Overall, patients showed piriform cortex activation during odor stimulation compared to pure sniffing. Group independent component analysis indicated that the recruitment of three networks during odor stimulation was correlated with olfactory function: a sensory processing network (including regions such as insula, thalamus and piriform cortex), a cerebellar network and an occipital network. Interestingly, recruitment of these networks during pure sniffing was related to olfactory function as well. Our results support previous findings that sniffing alone can activate olfactory regions. Extending this, we found that the severity of olfactory deficits is related to the extent to which neural networks are recruited both during olfactory stimulation and pure sniffing. This indicates that olfactory deficits are not only reflected in changes in specific olfactory areas but also in the recruitment of occipital and cerebellar networks. These findings pave the way for future investigations on whether characteristics of these networks might be of use for the prediction of disease prognosis or of treatment success.

Men and Women Differ in Gastric Fluid Retention and Neural Activation after Consumption of Carbonated Beverages.

Background: The most commonly consumed carbonated beverages are soda and beer. Carbon dioxide increases gastric volume, which can lead to epigastric discomfort. Women are more susceptible to this; however, correlations with neural activity and gastric distention are unknown. Objective: This study sought to determine the subjective, gastric, and neural correlates of epigastric discomfort in men and women. Methods: Thirty-four healthy, normal-weight adults [17 women; mean ± SD body mass index (BMI; kg/m2): 22.3 ± 1.9; 17 men; BMI: 22.8 ± 1.8] participated in a randomized crossover study with 2 treatments: ingestion of 500 mL beer or soda. Before and after consumption, gastric content and brain activity were measured with magnetic resonance imaging (MRI). Participants rated fullness, bloating, hunger, and nausea at baseline and at t = 0, 10, 20, and 30 min together with gastric MRI. Brain activity [cerebral blood flow (CBF)] was measured at baseline and at t = 5 and 35 min. Liquid, gas, and total gastric volume (TGV) were segmented from gastric MRI. Ratings and gastric content areas under the curve (AUCs) were tested with a mixed model with sex and drink as factors. Results: For subjective ratings, only nausea in the beer condition scored significantly greater for women (9.4-point increase; P = 0.045). Liquid stomach content was significantly greater for women (2525 mL × min increase; P = 0.019). In both men and women, the strongest correlation for bloating was with TGV (r = 0.45, P < 0.01) and for nausea was with the liquid fraction AUC (r = 0.45, P < 0.01). CBF changes did not differ between the drinks. Men showed greater CBF than women in the left precentral and postcentral gyri at t = 5 min. Conclusions: There are differences between sexes when it comes to appetite ratings, gastric fluid retention, and neural activation. Discomfort in women may be related to fluid rather than gas in the stomach, because they retain more fluid than men. Differences between men and women should be considered when studying digestion. This study was registered with the Dutch Trial Registry as NTR5418 (http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5418).

The Differential Role of Smell and Taste For Eating Behavior.

Food choice and food intake are guided by both sensory and metabolic processes. The senses of taste and smell play a key role in the sensory effects on choice and intake. This article provides a comprehensive overview of, and will argue for, the differential role of smell and taste for eating behavior by focusing on appetite, choice, intake, and satiation. The sense of smell mainly plays a priming role in eating behavior. It has been demonstrated that (orthonasal) odor exposure induces appetite specifically for the cued food. However, the influence of odors on food choice and intake is less clear, and may also depend on awareness or intensity of the odors, or personality traits of the participants. Taste on the other hand, has a clear role as a (macro)nutrient sensing system, during consumption. Together with texture, taste is responsible for eating rate, and thus in determining the oral exposure duration of food in the mouth, thereby contributing to satiation. Results from these experimental studies should be taken to real-life situations, to assess longer-term effects on energy intake. With this knowledge, it will be possible to steer people's eating behavior, as well as food product development, toward a less obesogenic society.

Effectiveness of Taste Lessons with and without additional experiential learning activities on children's willingness to taste vegetables.

This study assessed the effectiveness of the Dutch school programme Taste Lessons with and without additional experiential learning activities on children's willingness to taste unfamiliar vegetables. Thirty-three primary schools (877 children in grades 6-7 with a mean age of 10.3 years) participated in Taste Lessons Vegetable Menu (TLVM, lessons and extra activities), Taste Lessons (TL, lessons), or a control group. A baseline and follow-up measurement was used to assess for each child: number of four familiar and four unfamiliar vegetables tasted, quantity tasted, choice of vegetable of which to eat more, and number of vegetables willing to taste again later. Furthermore, children filled out a questionnaire on daily vegetable intake and food neophobia. Multilevel and Cox regression analyses were conducted to compare changes in the outcome measures between the three study groups. No significant intervention effects were found on willingness to taste unfamiliar vegetables. Neither were effects found on familiar vegetables, except for number of familiar vegetables tasted (p < 0.05). Furthermore, no significant intervention effects were found on daily vegetable consumption and food neophobia. These results indicate that more intensive school-based nutrition education activities are needed to increase children's willingness to taste unfamiliar vegetables and increase their vegetable intake.

Effectiveness of Taste Lessons with and without additional experiential learning activities on children's psychosocial determinants of vegetables consumption.

Experiential learning methods seem to be promising to enhance healthy eating behaviour in children. Therefore, this study compared the effectiveness of the Dutch programme Taste Lessons with and without additional experiential learning activities on children's psychosocial determinants of vegetable consumption. In a quasi-experimental design, 800 children aged 8-11 years old from 34 elementary schools participated in a Taste Lessons (TL: 5 lessons) group, a Taste Lessons Vegetable Menu (TLVM: TL with 3 added experiential learning activities) group, and a control group. During a baseline and follow-up measurement, children completed a questionnaire on psychosocial determinants towards vegetables consumption. Multilevel regression analyses were conducted to compare changes in the determinants between the TLVM group and the TL group, and between the two intervention groups and the control group. The TLVM group showed a significantly higher increase in knowledge (p < 0.001), attitude and subjective norm of the teacher (both p < 0.05), whereas the TL group only showed a significantly higher increase in knowledge (p < 0.001) compared to the control group. Increases in knowledge (p < 0.10), subjective norm (p < 0.10) and cooking self-efficacy (p < 0.05) were higher in the TLVM group than in the TL group. Therefore, more and stronger effects were found in children who participated in the additional hands-on activities.

Influence of Sensory Properties in Moderating Eating Behaviors and Food Intake.

Sensory properties inform likes and dislikes, but also play an important functional role in guiding food choice and intake behavior. Odors direct food choice and stimulate sensory-specific appetites and taste helps to anticipate calorie and nutrient content of food. Food textures moderate eating rate and the energy consumed to satiation and post-ingestive metabolism. We summarize how sensory cues moderate intake, and highlight opportunities to apply sensory approaches to improve dietary behavior. Salt, sweet and savory taste influence liking, but also influence energy intake to fullness, with higher taste intensity and duration linked to lower intake. Psycho-physical studies show it is relatively easy to rank taste intensities at different concentrations but more challenging to discriminate fat contents, and fat discrimination declines further when combined with high-taste intensity. Fat has low impact on sensory intensity, but makes significant contributions to energy content. Combinations of high taste and fat-content can promote passive energy over-consumption, and adding fat also increases energy intake rate (kcals/min), reducing opportunities to orally meter consumption. Consumers adapt their oral processing behaviors to a foods texture, which can influence the rate and extent of energy intake. Understanding how texture influences eating behaviors and bolus formation, affords new opportunities to impact eating rate, energy intake and metabolic response to food. Food formulation has traditionally focused on composition and sensory appeal. Future research needs to consider the role of sensory properties in moderating consumer interaction with their food environment, and how they influence calorie selection, and shape our eating behaviors and intake.

The Nutri-Score algorithm: Evaluation of its validation process.

The Nutri-Score front-of-pack label, which classifies the nutritional quality of products in one of 5 classes (A to E), is one of the main candidates for standardized front-of-pack labeling in the EU. The algorithm underpinning the Nutri-Score label is derived from the Food Standard Agency (FSA) nutrient profile model, originally a binary model developed to regulate the marketing of foods to children in the UK. This review describes the development and validation process of the Nutri-Score algorithm. While the Nutri-Score label is one of the most studied front-of-pack labels in the EU, its validity and applicability in the European context is still undetermined. For several European countries, content validity (i.e., ability to rank foods according to healthfulness) has been evaluated. Studies showed Nutri-Score's ability to classify foods across the board of the total food supply, but did not show the actual healthfulness of products within different classes. Convergent validity (i.e., ability to categorize products in a similar way as other systems such as dietary guidelines) was assessed with the French dietary guidelines; further adaptations of the Nutri-Score algorithm seem needed to ensure alignment with food-based dietary guidelines across the EU. Predictive validity (i.e., ability to predict disease risk when applied to population dietary data) could be re-assessed after adaptations are made to the algorithm. Currently, seven countries have implemented or aim to implement Nutri-Score. These countries appointed an international scientific committee to evaluate Nutri-Score, its underlying algorithm and its applicability in a European context. With this review, we hope to contribute to the scientific and political discussions with respect to nutrition labeling in the EU.

Effects of Oro-Sensory Exposure on Satiation and Underlying Neurophysiological Mechanisms-What Do We Know So Far?

The mouth is the first part of the gastrointestinal tract. During mastication sensory signals from the mouth, so-called oro-sensory exposure, elicit physiological signals that affect satiation and food intake. It has been established that a longer duration of oro-sensory exposure leads to earlier satiation. In addition, foods with more intense sweet or salty taste induce earlier satiation compared to foods that are equally palatable, but with lower taste intensity. Oro-sensory exposure to food affects satiation by direct signaling via the brainstem to higher cortical regions involved in taste and reward, including the nucleus accumbens and the insula. There is little evidence that oro-sensory exposure affects satiation indirectly through either hormone responses or gastric signals. Critical brain areas for satiation, such as the brainstem, should be studied more intensively to better understand the neurophysiological mechanisms underlying the process of satiation. Furthermore, it is essential to increase the understanding of how of highly automated eating behaviors, such as oral processing and eating rate, are formed during early childhood. A better understanding of the aforementioned mechanisms provides fundamental insight in relation to strategies to prevent overconsumption and the development of obesity in future generations.