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BACKGROUND: Scant research has examined whether laboratory assessments of eating in the absence of hunger (EAH) relates to long-term diet quality. OBJECTIVE: This study investigates the association of EAH with diet quality during pregnancy. DESIGN: Pregnancy diet quality was assessed using 24-hour diet recalls collected in each pregnancy trimester. EAH was assessed in a counterbalanced, crossover laboratory feeding substudy in which participants completed two free access eating occasions following a standardized meal during their 2(nd) pregnancy trimester. PARTICIPANTS/SETTING: Data were collected from March 2015 to December 2016 from a subsample of participants (n=46) enrolled at ≤ 12 weeks gestation in an observational, prospective cohort study (the Pregnancy Eating Attributes Study) in North Carolina. INTERVENTION: Participants were presented with highly processed (HP) and minimally processed (MP) foods in two separate assessments. MAIN OUTCOME MEASURES: Scores for total Healthy Eating Index-2015 (HEI2015) and adherence to adequacy (HEI2015-adq) and moderation components (HEI2015-mod) were calculated from the diet recalls. Higher scores reflect better diet quality. STATISTICAL ANALYSES PERFORMED: Linear regressions estimated associations of pregnancy diet quality with EAH (energy, EAH-kcal; and percent offered, EAH-%) in each condition for all foods, and separately for sweet and savory foods. RESULTS: Lower pregnancy diet quality (all indicators) was associated with greater EAH-kcal and EAH-% of all foods and sweet foods in the HP condition. Each 100-kcal increase in EAH of HP foods was associated with a 2–3-point decrease (SE=0.7 – 0.8) in HEI2015 (P

Highly energy dense foods are often synonymous with high palatability, excess intake and weight gain. However, food preferences show individual differences. Food preferences are closely related to food intake, which can impact weight change over time. We examined whether the energy density of food images rated as appetizing and unappetizing foods related to baseline BMI and change in BMI over 3-year follow-up (n = 117; 45% Male, Baseline BMI: 21.1 ± 1.9. Participants completed hedonic visual analog scales (−100 to 100) ratings of 103 food images, and reported dietary intake at baseline, and had their height and weight directly measured over 3-year follow-up. Energy density (ED) of the food depicted in each image was calculated. For each participant, food images (kcal/g) were categorized into appetizing (32 images) and unappetizing foods (32 images) based on each individual's hedonic ratings. We observed significant interaction between energy density and hedonic value driven by an inverse relation between unappetizing food energy density and BMI change (p = 0.008). Specifically, participants who rated higher energy dense foods as unappetizing showed less weight gain ( β = −0.83; p = 0.00052). There was no significant relation between the energy density of appetizing foods and weight change (p = 0.67), suggesting that dislike of highly energy dense foods more strongly associates with lower weight gain than preference for low energy dense foods. Post-hoc analyses revealed that individuals with a higher preference for low energy density foods showed less weight gain over 3-years (β = - 0.007, p = 0.02). Results support the idea that individual hedonic ratings for foods varying in energy density is a determinant of weight change in adolescents and may represent an important intervention target for obesity prevention programs.

BACKGROUND: Children of overweight or obese parents are at a high risk of developing obesity. OBJECTIVE: This study sought to examine the underlying neural factors related to parental obesity risk and the relative impact of sugar and fat when consuming a palatable food, as well as the impact of obesity risk status on brain response to appetizing food images. DESIGN: With the use of functional MRI, the responses of 108 healthy-weight adolescents [mean ± SD body mass index (kg/m(2)): 20.9 ± 1.9; n = 53 who were at high risk by virtue of parental obesity status, n = 55 who were low risk] to food stimuli were examined. Stimuli included 4 milkshakes, which systematically varied in sugar and fat content, a calorie-free tasteless solution, and images of appetizing foods and glasses of water. RESULTS: High-risk compared with low-risk adolescents showed greater blood oxygen–dependent response to milkshakes (all variants collapsed) compared with the tasteless solution in the primary gustatory and oral somatosensory cortices (P-family-wise error rate

Background: The Power of Food Scale (PFS) seeks to identify individuals who experience high appetitive drive in response to food cues, which is a construct termed “hedonic hunger.” Objective: The purpose of this study was to assess cross-sectional correlates and predictive power of PFS scores to probe the construct of hedonic hunger. Methods: Separate data from 3 studies (study 1, n = 44; study 2, n = 398; study 3, n = 100) were used to evaluate the construct of hedonic hunger. We examined the correlations between the PFS and neural responsivity during intake and anticipated intake of palatable foods, behavioral food reinforcement, perceptual hedonic ratings of food images, and change in body mass index (BMI) and binge eating over time. Results: Hedonic hunger was strongly related to bilateral brain response in regions implicated in oral somatosensory processing during cue-elicited anticipation of food intake (study 1; right postcentral gyrus: r = 0.67, P < 0.001; left postcentral gyrus: r = 0.64, P < 0.001), and was correlated with behavioral food reinforcement (study 2; r = 0.31, P = 0.03) and perceptual hedonic ratings (study 3; r = 0.24, P = 0.02). Hedonic hunger was not associated with baseline BMI (studies 1–3: P = 0.14, 0.21, and 0.37, respectively) or change in BMI over the 2-y follow-up (studies 1 and 2: P = 0.14 and 0.37, respectively) but was significantly correlated with baseline binge eating in 2 samples (study 1: r = 0.58, P = 0.001; study 2: r = 0.31, P = 0.02; and study 3: P = 0.02). Conclusions: Hedonic hunger was not predictive of weight regulation. However, individuals who report high hedonic hunger are likely to show increased neural and perceptual responses to cues of palatable foods, increased motivation to consume such foods, and a greater likelihood of current binge eating.

Ingestive behavior is a complex decision-making process involving the integration of homeostatic and hedonic systems. Human neuroimaging studies have provided considerable insight into aspects of hedonically-motivated food intake. Here, we review reports that examine brain response patterns to food stimuli (food cues and during food intake) that vary by weight status, habitual ingestive behavior, and weight change, as well as investigations that use neuroimaging techniques to predict food intake. Secondly, we discuss the application of decision-making theory stemming from computational neuroscience to better understand the basis of habit formation in the context of food intake. This framework may provide insight into the neuroadaptive processes that drive the transition from infrequent, moderate intake of energy-dense foods to habitual overconsumption.

Background: Inaccuracies in energy intake (EI) measurement hinder identification of risk factors that predict weight gain and evaluation of obesity prevention and treatment interventions. Research has used objective measures of EI to identify underreporting correlates, producing mixed results, suggesting the need to examine novel potential correlates. Objective: With the use of an objective measure of EI from doubly labeled water (DLW) this report examined multiple potential underreporting correlates. Methods: Adolescents from 2 studies (study 1, n = 91; mean age: 18.4 6 0.58 y; 100% female; study 2, n = 162; mean age: 15.2 6 1.99 y; 82 female adolescents; 80 male adolescents) completed a DLW assessment of EI, a food-frequency questionnaire, and measures of perceived pressure for thinness, thin-ideal internalization, body dissatisfaction, dieting, food-cue reactivity, eating disorder symptoms, socioeconomic status, and neural response to food; BMI (in kg/m 2 ) was measured over a 2-y follow-up. Results: Elevated BMI correlated with underreported EI in study 1 (r = 0.26, P < 0.05) and study 2 (r = 0.20, P = 0.01), as did male sex in study 2 (r = 0.24, P < 0.01); the other survey measures did not. Underreporting correlated negatively (r = 20.29; uncorr P < 0.001) with responsivity of brain regions implicated in motor control to palatable food receipt and positively (r = 0.31; uncorr P < 0.001) with responsivity of a region implicated in taste processing to cues signaling impending milkshake receipt. Underreporting did not predict future change in BMI in either study. Conclusions: Findings document marked underreporting and replicate evidence that BMI correlates positively with underreporting and extends this literature by revealing that several novel factors were unrelated to underreporting and further that neural responsivity to food correlated with underreporting, suggesting that adolescents who showed reduced responsivity in a motor control region to food receipt and elevated responsivity of gustatory regions to anticipated palatable food receipt showed greater underreporting. This trial was registered at clinicaltrials.gov as NCT00433680 and NCT02084836. JN utrdoi: 10.3945/jn.115.216366.

Evaluate a selective obesity prevention program promoting use of cognitive reappraisals to reduce reward region response and increase inhibitory region response to high-fat/high-sugar foods and reduce intake of fat and sugar to prevent blunted reward region response to intake of such foods.Young adults at risk for future weight gain by virtue of weight concerns (N=148) were randomized to this new prevention program (Minding Health), an alternative prevention program promoting participant-driven gradual reductions in caloric intake and increases in physical activity (Healthy Weight), or an obesity education video control condition, completing assessments at pre-, post-, and 6-month follow-up. A subset of Minding Health and control participants completed an fMRI scan at pre- and post-assessing neural response to images of high-fat/sugar foods and to receipt and anticipated receipt of a high-fat/sugar food.Minding Health participants showed significantly greater reductions in body fat than controls and caloric intake from fat and sugar than Healthy Weight participants. Minding Health participants also showed greater activation of an inhibitory control region and reduced activation of an attention/expectation region in response to palatable food images relative to pretest and controls. However, Healthy Weight participants showed greater reductions in BMI and eating disorder symptoms than Minding Health participants.Although the Minding Health intervention produced some of the hypothesized effects, it did not produce lasting reductions in body fat or BMI and showed limited effects on neural responsivity, implying it will be vital to increase the efficacy of this new prevention program.

Animal experiments indicate that after repeated pairings of palatable food receipt and cues that predict palatable food receipt, dopamine signaling increases in response to predictive cues, but decreases in response to food receipt. Using functional MRI and mixed effects growth curve models with 35 females (M age = 15.5 ± 0.9; M BMI = 24.5 ± 5.4) we documented an increase in BOLD response in the caudate (r = .42) during exposure to cues predicting impending milkshake receipt over repeated exposures, demonstrating a direct measure of in vivo cue-reward learning in humans. Further, we observed a simultaneous decrease in putamen (r = −.33) and ventral pallidum (r = −.45) response during milkshake receipt that occurred over repeated exposures, putatively reflecting food reward habitation. We then tested whether cue-reward learning and habituation slopes predicted future weight over 2-year follow-up. Those who exhibited the greatest escalation in ventral pallidum responsivity to cues and the greatest decrease in caudate response to milkshake receipt showed significantly larger increases in BMI (r = .39 and −.69 respectively). Interestingly, cue-reward learning propensity and food reward habituation were not correlated, implying that these factors may constitute qualitatively distinct vulnerability pathways to excess weight gain. These two individual difference factors may provide insight as to why certain people have shown obesity onset in response to the current obesogenic environment in western cultures, whereas others have not.

Theorists posit that food reward is a powerful determinant of intake, yet little is known regarding how individuals’ hedonic ratings of a variety of foods interrelate and how hedonic ratings correspond to habitual dietary intake. Participant ratings of food appeal of 104 food images were collected while participants were in a fed state (n = 129). Self-reported frequency of intake of the food items, perceived hunger, body mass index (BMI), and dietary restraint were also assessed. Principal components analysis (PCA) was employed to analyze hedonic ratings of the foods, to identify component structures and to reduce the number of variables. The resulting component structures comprised 63 images loading on seven components including Energy-Dense Main Courses, Light Main Courses and Seafood as well as components more analogous to traditional food groups (e.g., Fruits, Grains, Desserts, Meats). However, vegetables were not represented in a unique, independent component. All components were positively correlated with reported intake of the food items (r’s = .26–.52, p < .05), except for the Light Main Course component (r = .10). BMI showed a small positive relation with aggregated food appeal ratings (r = .19; p < .05), which was largely driven by the relations between BMI and appeal ratings for Energy-Dense Main Courses (r = .24; p < .01) and Desserts (r = .27; p < .01). Dietary restraint showed a small significant negative relation to Energy-Dense Main Courses (r = −.21; p < .05), and Meats (r = −.18; p < .05). The present investigation provides novel evidence that how individuals’ hedonic ratings of foods aggregate into food components and how these component ratings relate to dietary intake. The notable absence of a vegetable component suggests that individuals’ liking for vegetables is highly variable and, from an empirical standpoint, not related to how they respond hedonically to other food categories.

Background: Obese compared with lean individuals show greater attention-, gustatory-, and reward-region responsivity to food cues but reduced reward-region responsivity during food intake. However, to our knowledge, research has not tested whether an objectively measured caloric intake is positively associated with neural responsivity independent of excess adipose tissue. Objective: We tested the hypothesis that objectively measured energy intake, which accounts for basal needs and the percentage of body fat, correlates positively with the neural response to anticipated palatable food intake but negatively with a response to food intake in healthy-weight adolescents. Design: Participants (n = 155; mean ± SD age: 15.9 ± 1.1 y) completed functional magnetic resonance imaging scans while anticipating and receiving palatable food compared with a tasteless solution, a doubly labeled water assessment of energy intake, and assessments of resting metabolic rate and body composition. Results: Energy intake correlated positively with activation in the lateral visual and anterior cingulate cortices (visual processing and attention), frontal operculum (primary gustatory cortex) when anticipating palatable food, and greater striatal activation when anticipating palatable food in a more-sensitive region of interest analysis. Energy intake was not significantly related to neural responsivity during palatable food intake. Conclusions: Results indicate that objectively measured energy intake that accounts for basal needs and adipose tissue correlates positively with activity in attentional, gustatory, and reward regions when anticipating palatable food. Although hyperresponsivity of these regions may increase risk of overeating, it is unclear whether this is an initial vulnerability factor or a result of previous overeating. This trial was registered at clinicaltrials.gov as {"type":"clinical-trial","attrs":{"text":"NCT01807572","term_id":"NCT01807572"}}NCT01807572.

Background: Weight gain leads to reduced reward-region responsivity to energy-dense food receipt, and consumption of an energydense diet compared with an isocaloric, low-energy-density diet leads to reduced dopamine receptors. Furthermore, phasic dopamine signaling to palatable food receipt decreases after repeated intake of that food, which collectively suggests that frequent intake of an energy-dense food may reduce striatal response to receipt of that food. Objective: We tested the hypothesis that frequent ice cream consumption would be associated with reduced activation in rewardrelated brain regions (eg, striatum) in response to receipt of an ice cream–based milkshake and examined the influence of adipose tissue and the specificity of this relation. Design: Healthy-weight adolescents (n = 151) underwent fMRI during receipt of a milkshake and during receipt of a tasteless solution. Percentage body fat, reported food intake, and food craving and liking were assessed. Results: Milkshake receipt robustly activated the striatal regions, yet frequent ice cream consumption was associated with a reduced response to milkshake receipt in these reward-related brain regions. Percentage body fat, total energy intake, percentage of energy from fat and sugar, and intake of other energy-dense foods were not related to the neural response to milkshake receipt. Conclusions: Our results provide novel evidence that frequent consumption of ice cream, independent of body fat, is related to a reduction in reward-region responsivity in humans, paralleling the tolerance observed in drug addiction. Data also imply that intake of a particular energy-dense food results in attenuated reward-region responsivity specifically to that food, which suggests that sensory aspects of eating and reward learning may drive the specificity. Am J Clin Nutr 2012;95:810–7.