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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

Background/Objectives. Reward-related eating is hypothesized to underlie risk for weight gain in obesogenic environments, but its role is unknown during pregnancy and postpartum when weight change is normative, but excess weight gain and weight retention are common. This study examined associations of self-reported reward-related eating, self-regulation, and the home food environment with excessive gestational weight gain (GWG) and postpartum weight change. Subjects/Methods. Participants in the Pregnancy Eating Attributes Study observational cohort were enrolled at ≤12 weeks pregnancy and followed through one-year postpartum (458 recruited; 367 retained through delivery). Participants completed four measures of reward-related eating – Modified Yale Food Addiction Scale, Power of Food Scale, Multiple Choice Procedure, and a Reinforcing Value of Food Questionnaire; two measures of self-regulation – Barratt Impulsiveness Scale and Delay of Gratification Inventory; and a Home Food Inventory. Measured weight and skinfolds were obtained. Multinomial logistic and multiple linear regression analyses estimated associations of reward-related eating, self-regulation, and home food environment with excessive GWG, gestational fat gain, postpartum weight change, and percent of GWG retained. Results. Excessive GWG was associated with food reinforcement intensity, but not with any other measure of reward-related eating, self-regulation, or home food environment. Greater gestational fat gain was associated only with higher Multiple Choice Procedure. Postpartum weight change and percent of GWG retained were associated with greater Delay of Gratification and obesogenic home food environment, but not with any measure of reward-related eating or with impulsivity. Conclusions. Findings do not support the hypothesis that self-reported reward-related eating is associated with weight outcomes in pregnancy and postpartum but indicate a relation of Delay of Gratification with postpartum weight retention. Further research using both surveys and objective measures of reward-related eating is needed to advance our understanding of the relation of reward-related eating with weight changes during this critical period of a woman’s life.

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.

OBJECTIVES: The 2020 dietary guidelines specifically recommended a decrease in sugar intake. Reward-related, brain-based models of overeating and obesity suggest that increased intake of highly palatable foods is linked to decreased dopaminergic (striatal and prefrontal) brain functioning. This reduction acts to increase consumption of food to achieve pleasure. Here, we examined whether increased dietary intake of sugar and fat would be associated with increased activation in reward-related brain regions during anticipation of a sugar sweetened beverage (SSB), but decreased activation during SSB receipt. METHODS: Young adults (n = 100, age = 21.8 ± 2.4 y, BMI = 23.3 ± 3.5, 70% female) underwent an fMRI scan examining brain responses to receipt of a SSB, a tasteless rinse, and response cue-induced anticipation of these tastes. The Block Food Frequency Questionnaire (FFQ) was used to assess average dietary intake, % daily caloric intake from SSBs, sugar, sugar from SSBs and fat. These were correlated with whole-brain BOLD responses to SSB anticipation and receipt contrasts (e.g., SSB > rinse). Significance was corrected for multiple comparisons; pFWE rinse). CONCLUSIONS: These results directly support previous research (Burger & Stice 2012; AJCN) demonstrating that increased consumption of highly palatable foods is associated with reduced dopaminergic brain response during consumption specifically of those foods. Critically, we demonstrate these effects with SSBs which are far more widely consumed. Our results were specific to increased intake of sugar calories from SSBs and not total calories from SSBs or total sugar calories, suggesting that added sugars in these beverages have the potential to lead to altered frontostriatal brain responses. FUNDING SOURCES: NIDDK R01DK112317.

Identifying correlates of brain response to food cues and taste provides critical information on individual differences that may influence variability in eating behavior. However, a few studies examine how brain response changes over repeated exposures and the individual factors that are associated with these changes. Using functional magnetic resonance imaging, we examined how brain response to a palatable taste and proceeding cues changed over repeated exposures and how individual differences in weight, familial obesity risk, dietary restraint and reward responsiveness correlate with these changes. In healthy-weight adolescents (n = 154), caudate and posterior cingulate cortex (PCC) response increased with repeated cue presentations, and oral somatosensory cortex and insula response increased with repeated milkshake tastes. The magnitude of increase over exposures in the left PCC to cues was positively associated with body mass index percentile (r = 0.18, P = 0.026) and negatively associated with dietary restraint scores (r = −0.24, P = 0.003). Adolescents with familial obesity risk showed higher cue-evoked caudate response across time, compared to the low-risk group (r = 0.12, P = 0.035). Reward responsiveness positively correlated with right oral somatosensory cortex/insula response to milkshake over time (r = 0.19, P = 0.018). The results show that neural responses to food cues and taste change over time and that individual differences related to weight gain are correlated with these changes.

Individuals show meaningful variability in food choices. Choices are affected by individual differences in sensitivity to food reward and punishment, so understanding correlates of response to food reinforcement can help characterize food choices. Here, we examined behavioral and physiological correlates of individual differences in how individuals learn from food reward and punishment, as measured by performance on an appetitive probabilistic selection task that used sweet and bitter tastes as reinforcement. Sensitivity to food reward, sensitivity to food punishment, and overall learning performance were measured in 89 adults. Multivariate linear regressions were used to test if variables including body mass index (BMI), external eating, emotional eating, behavioral inhibition/behavioral activation scales (BIS/BAS), and perceived sensitivity to reward and punishment (SPQ/SRQ) were associated with measures of learning performance. External eating (β=-.035, p=.019), BIS (β=-.066, p=.004), and SPQ (β=.003, p=.023) were associated with overall learning performance. BMI (β=-.000, p=.012), emotional eating (β=.055, p=.006), and external eating (β=-.062, p=.004) were associated with sensitivity to food reward. No variables were associated with sensitivity to food punishment. In post hoc analyses, the interaction of sex and SPQ was associated with overall performance (β=-.005, p=.025), such that the relationship was positive in women only (β=.006, p=0.002). Results support that, controlling for key individual characteristics, BMI and susceptibility to food cues are associated with lower sensitivity to food reward, which may affect future food choices and eating behavior.

Reinforcement learning guides food decisions, yet how the brain learns from taste in humans is not fully understood. Existing research examines reinforcement learning from taste using passive condition paradigms, but response-dependent instrumental conditioning better reflects natural eating behavior. Here, we examined brain response during a taste-motivated reinforcement learning task and how measures of task-based network structure were related to behavioral outcomes. During a functional MRI scan, 85 participants completed a probabilistic selection task with feedback via sweet taste or bitter taste. Whole brain response and functional network topology measures, including identification of communities and community segregation, were examined during choice, sweet taste, and bitter taste conditions. Relative to the bitter taste, sweet taste was associated with increased whole brain response in the hippocampus, oral somatosensory cortex, and orbitofrontal cortex. Sweet taste was also related to differential community assignment of the ventromedial prefrontal cortex and ventrolateral prefrontal cortex compared to bitter taste. During choice, increasing segregation of a community containing the amygdala, hippocampus, and right fusiform gyrus was associated with increased sensitivity to punishment on the task’s posttest. Further, healthy BMI was associated with differential community structure compared to overweight and obese BMI, where high BMI reflected increased connectivity of visual regions. Together, results demonstrate that network topology of learning and memory regions during choice is related to avoid a bitter taste and that BMI is associated with increased connectivity of area involved in processing external stimuli. Network organization and topology provides unique insight into individual differences in brain response to instrumental conditioning via taste reinforcers.

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

As the prevalence of obesity in Type 1 diabetes rises, the effects of emerging therapy options should be considered in the context of both weight and glycaemic control outcomes. Artificial pancreas device systems will ‘close the loop’ between blood glucose monitoring and automated insulin delivery and may transform day-to-day dietary management for people with Type 1 diabetes in multiple ways. In the present review, we draw directly from cognitive restraint theory to consider unintended impacts that closed-loop systems may have on ingestive behaviour and food intake. We provide a brief overview of dietary restraint theory and its relation to weight status in the general population, discuss the role of restraint in traditional Type 1 diabetes treatment, and lastly, use this restraint framework to discuss the possible behavioural implications and opportunities of closed-loop systems in the treatment of Type 1 diabetes. We hypothesize that adopting closed-loop systems will lift the diligence and restriction that characterizes Type 1 diabetes today, thus requiring a transition from a restrained eating behaviour to a non-restrained eating behaviour. Furthermore, we suggest this transition be leveraged as an opportunity to teach people lifelong eating behaviour to promote healthy weight status by incorporating education and cognitive reappraisal. Our aim was to use a transdisciplinary approach to highlight critical aspects of the emerging closed-loop technologies relating to eating behaviour and weight effects and to promote discussion of strategies to optimize long-term health in Type 1 diabetes via two key outcomes: glycaemic control and weight management.

Later onset of puberty has been associated with lower body mass index (BMI) in adulthood independent of childhood BMI. However, how the relationship between time of onset of puberty and BMI in adulthood is associated with neurocognitive outcomes is largely unstudied. In the present study, women were sampled from the Human Connectome Project 1200 parcellation, timeseries and netmats1 release (PTN) release. Inclusion criteria were: four (15 minutes) resting state fMRI scans, current measured BMI, self-reported age at onset of menstruation (a proxy of age at onset of puberty) and no endocrine complications (eg, polycystic ovarian syndrome). The effect of age at onset of menstruation, measured BMI at scan date and the interaction of age at onset of menstruation by BMI on brain functional correlation was modelled using fslnets (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLNets) controlling for race and age at scan. Corrected significance was set at a family-wise error probability (pFWE) < 0.05. A final sample of n = 510 (age 29.5 years ± 3.6, BMI at scan 25.9 ± 5.6 and age at onset of menstruation 12.7 ± 1.6 were included. Age at onset of menstruation was negatively associated with BMI at scan (r = - 0.19, P < 0.001). The interaction between age at onset of menstruation and BMI at scan was associated with stronger correlation between a somatosensory and visual network (t = 3.45, pFWE = 0.026) and a visual network and cingulo-opercular task control network (t = 4.74, pFWE = 0.0002). Post-hoc analyses of behavioural/cognitive measures showed no effect of the interaction between BMI and age at onset of menstruation on behavioural/cognitive measures. However, post-hoc analyses of heritability showed adult BMI and the correlation between the visual and somatosensory networks have high heritability. In sum, we report increased correlation between visual, taste-associated and self-control brain regions in women at high BMI with later age at onset of menstruation.

BACKGROUND The eating in the absence of hunger (EAH) experimental paradigm measures intake of highly palatable, highly processed foods when sated. However, no studies have examined EAH in pregnant women. OBJECTIVE The objectives were to investigate whether EAH in pregnant women differs by level of food processing and to examine relationships of EAH with hedonic hunger, addictive-like eating, and impulsivity. DESIGN EAH was assessed in a counterbalanced crossover feeding substudy in which participants completed two free-access eating occasions following a standardized meal during their second pregnancy trimester. Hedonic hunger (Power of Food Scale), addictive-like eating (modified Yale Food Addiction Scale), and impulsivity (Barratt Impulsiveness Scale-15) were assessed by self-report during early pregnancy. PARTICIPANTS AND SETTING Data were collected from March 2015 through September 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 and minimally processed foods in two separate assessments. MAIN OUTCOME MEASURES Energy intake (EAH-kcal) and percent consumed (EAH-%) (calculated as 100 × [amount consumed (g) / amount served (g)]) was measured overall and separately for sweet and savory foods. STATISTICAL ANALYSES PERFORMED Linear mixed models estimated the effect of condition on EAH. Hedonic hunger, addictive-like eating, impulsivity and their interaction were examined separately. RESULTS EAH-% was similar across conditions (16.3% ± 1.1% highly processed vs 17.9% ± 1.2% minimally processed; P = 0.76), resulting in 338.5 ± 34.2 kcal greater energy intake in the highly processed vs minimally processed condition (P < 0.001). Hedonic hunger was not significantly associated with EAH; reward-related eating was positively associated with EAH-kcal and EAH-% of savory foods, and Barratt Impulsivity was positively associated with EAH-kcal and EAH-% overall, and with EAH-% of sweet foods (P < 0.05). There was little evidence of an interaction of Barratt Impulsivity with hedonic hunger or reward-related eating. CONCLUSIONS EAH in pregnant women occurs for both highly processed and minimally processed foods and correlates positively with self-reported addictive-like eating, but not hedonic hunger. Impulsivity did not modify associations of addictive-like eating with EAH in this sample.

IntroductionIndividuals with type 1 diabetes (T1D) present with diverse body weight status and degrees of glycemic control, which may warrant different treatment approaches. We sought to identify subgroups sharing phenotypes based on both weight and glycemia and compare characteristics across subgroups.Research design and methodsParticipants with T1D in the SEARCH study cohort (n=1817, 6.0–30.4 years) were seen at a follow-up visit >5 years after diagnosis. Hierarchical agglomerative clustering was used to group participants based on five measures summarizing the joint distribution of body mass index z-score (BMIz) and hemoglobin A1c (HbA1c) which were estimated by reinforcement learning tree predictions from 28 covariates. Interpretation of cluster weight status and glycemic control was based on mean BMIz and HbA1c, respectively.ResultsThe sample was 49.5% female and 55.5% non-Hispanic white (NHW); mean±SD age=17.6±4.5 years, T1D duration=7.8±1.9 years, BMIz=0.61±0.94, and HbA1c=76±21 mmol/mol (9.1±1.9)%. Six weight-glycemia clusters were identified, including four normal weight, one overweight, and one subgroup with obesity. No cluster had a mean HbA1c ConclusionsThere are distinct subgroups of youth and young adults with T1D that share weight-glycemia phenotypes. Subgroups may benefit from tailored interventions addressing differences in clinical care, health behaviors, and underlying health inequity.

Objective Type 2 diabetes (T2D) is associated with aberrant neural functioning; however, the point at which brain function alterations occur in the progression of T2D is unknown. Here, we tested for differences in functional connectivity in adults with prediabetes and healthy individuals. We hypothesized that prediabetes, defined by glycated hemoglobin (HbA1c) 5.7-6.4% would be associated with disruptions in default mode network (DMN) connectivity. Methods Fourteen brain networks were tested in 88 adults (prediabetes: n = 44; HbA1c = 5.8±0.2%; healthy: n = 44; HbA1c = 4.7±0.2%) matched for sex, age, and BMI. Results We did not find differences in DMN connectivity between groups. Individuals with prediabetes showed stronger connectivity between the ventral attention network and (1) a visual network (pFWE = 0.0001); (2) a somatosensory network (pFWE = 0.0027). Individuals with healthy HbA1c showed stronger connectivity of the ventral attention network and (1) cingulo-opercular network (pFWE = 0.002); (2) a thalamic-striatal-visual network (pFWE = 0.001). Conclusions Relative to individuals with prediabetes, those with a healthy HbA1c showed stronger connectivity between brain networks underlying self-control and attention to stimuli. In contrast, those with prediabetes demonstrated stronger connectivity between brain networks associated with sensory and attention to stimuli. While T2D reported contribute to decreased DMN connectivity, prediabetes is characterized by a shift in functional connectivity from a self-control network towards increasing connectivity in sensory network.

BACKGROUND/OBJECTIVE To identify and characterize subgroups of adolescents with type 1 diabetes (T1D) and elevated hemoglobin A1c (HbA1c) who share patterns in their continuous glucose monitoring (CGM) data as "dysglycemia phenotypes." METHODS Data were analyzed from the Flexible Lifestyles Empowering Change randomized trial. Adolescents with T1D (13-16 years, duration >1 year) and HbA1c 8% to 13% (64-119 mmol/mol) wore blinded CGM at baseline for 7 days. Participants were clustered based on eight CGM metrics measuring hypoglycemia, hyperglycemia, and glycemic variability. Clusters were characterized by their baseline features and 18 months changes in HbA1c using adjusted mixed effects models. For comparison, participants were stratified by baseline HbA1c (≤/>9.0% [75 mmol/mol]). RESULTS The study sample included 234 adolescents (49.8% female, baseline age 14.8 ± 1.1 years, baseline T1D duration 6.4 ± 3.7 years, baseline HbA1c 9.6% ± 1.2%, [81 ± 13 mmol/mol]). Three Dysglycemia Clusters were identified with significant differences across all CGM metrics (P

ContextSubclinical and clinical complications emerge early in type 1 diabetes (T1D) and may be associated with obesity and hyperglycemia.ObjectiveTest how longitudinal “weight-glycemia” phenotypes increase susceptibility to different patterns of early/subclinical complications among youth with T1D.DesignSEARCH for Diabetes in Youth observational study.SettingPopulation-based cohort.ParticipantsYouth with T1D (n = 570) diagnosed 2002 to 2006 or 2008.Main Outcome MeasuresParticipants were clustered based on longitudinal body mass index z score and HbA1c from a baseline visit and 5+ year follow-up visit (mean diabetes duration: 1.4 ± 0.4 years and 8.2 ± 1.9 years, respectively). Logistic regression modeling tested cluster associations with seven early/subclinical diabetes complications at follow-up, adjusting for sex, race/ethnicity, age, and duration.ResultsFour longitudinal weight-glycemia clusters were identified: The Referent Cluster (n = 195, 34.3%), the Hyperglycemia Only Cluster (n = 53, 9.3%), the Elevated Weight Only Cluster (n = 206, 36.1%), and the Elevated Weight With Increasing Hyperglycemia (EWH) Cluster (n = 115, 20.2%). Compared with the Referent Cluster, the Hyperglycemia Only Cluster had elevated odds of dyslipidemia [adjusted odds ratio (aOR) 2.22, 95% CI: 1.15 to 4.29], retinopathy (aOR 9.98, 95% CI: 2.49 to 40.0), and diabetic kidney disease (DKD) (aOR 4.16, 95% CI: 1.37 to 12.62). The EWH Cluster had elevated odds of hypertension (aOR 2.18, 95% CI: 1.19 to 4.00), dyslipidemia (aOR 2.36, 95% CI: 1.41 to 3.95), arterial stiffness (aOR 2.46, 95% CI: 1.09 to 5.53), retinopathy (aOR 5.11, 95% CI: 1.34 to 19.46), and DKD (aOR 3.43, 95% CI: 1.29 to 9.11).ConclusionsWeight-glycemia phenotypes show different patterns of complications, particularly markers of subclinical macrovascular disease, even in the first decade of T1D.

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.

Multiple theories identify neural vulnerability factors that may increase risk for overeating and weight gain. Early cross-sectional neuroimaging studies were unable to determine whether aberrant neural responsivity was a risk factor for or a consequence of overeating. More recent obesity risk, prospective, repeated-measures, and experimental neuroimaging studies with humans have advanced knowledge of etiologic processes and neural plasticity resulting from overeating. Herein, we review evidence from these more rigorous human neuroimaging studies, in conjunction with behavioral measures reflecting neural function, as well as experiments with animals that investigated neural vulnerability theories for overeating. Findings provide support for the reward surfeit theory that posits that individuals at risk for obesity initially show hyper-responsivity of reward circuitry to high-calorie food tastes, which theoretically drives elevated intake of such foods. However, findings provide little support for the reward deficit theory that postulates that individuals at risk for obesity show an initial hypo-responsivity of reward circuitry that motives overeating. Further, results provide support for the incentive sensitization and dynamic vulnerability theories that propose that overconsumption of high-calorie foods results in increased reward and attention region responsivity to cues that are associated with hedonic reward from intake of these high-calorie foods via conditioning, as well as a simultaneous decrease in reward region responsivity to high-calorie food tastes. However, there is little evidence that this induced reduction in reward region response to high-calorie food tastes drives an escalation in overeating. Finally, results provide support for the theory that an initial deficit in inhibitory control and a bias for immediate reward contribute to overconsumption of high-calorie foods. Findings imply that interventions that reduce reward and attention region responsivity to food cues and increase inhibitory control should reduce overeating and excessive weight gain, an intervention theory that is receiving support in randomized trials.

Repeated exposure to highly palatable foods and elevated weight promote: 1) insensitivity to punishment in striatal regions and, 2) increased willingness to work for food. We hypothesized that BMI would be positively associated with negative prediction error BOLD response in the occipital cortex. Additionally, we postulated that food reinforcement value would be negatively associated with negative prediction error BOLD response in the orbital frontal cortex and amygdala. Postpartum women ( n = 47; BMI = 25.5 ± 5.1) were ‘trained’ to associate specific cues paired to either a highly palatable milkshake or a sub-palatable milkshake. We then violated these cue-taste pairings in 40% of the trials by showing a palatable cue followed by the sub-palatable taste (negative prediction error). Contrary to our hypotheses, during negative prediction error (mismatched cue-taste) versus matched palatable cue-taste, women showed increased BOLD response in the central operculum (pFWE = 0.002; k = 1680; MNI: -57, −7,14) and postcentral gyrus (pFWE = 0.006, k = 1219; MNI: 62, −8,18). When comparing the matched sub-palatable cue-taste to the negative prediction error trials, BOLD response increased in the postcentral gyrus ( r = −0.60, pFWE = 0.008), putamen ( r = −0.55, pFWE = 0.02), and insula ( r = −0.50, pFWE = 0.01). Similarly, viewing the palatable cue vs sub-palatable cue was related to BOLD response in the putamen (pFWE = 0.025, k = 53; MNI: -20, 6, −8) and the insula (pFWE = 0.04, k = 19, MNI:38, −12, −6). Neither BMI at 6-month postpartum nor food reinforcement value was related to BOLD response. The insula and putamen appear to encode for visual food cue processing, and the gustatory and somatosensory cortices appear to encode negative prediction errors. Differential response in the somatosensory cortex to the matched cue-taste pairs to negative prediction error may indicate that a palatable cue may dull aversive qualities in the stimulus.

The brain must integrate both external and internal feeding signals in an effort to maintain homeostasis and respond to the external food environment. Examination of the brain’s intrinsic connectivity, through resting state functional MRI (rsMRI), provides insight into how the brain integrates such signals. While this method has been used to identify differential connectivity associated with metabolic diseases (type 2 diabetes, obesity), fewer studies have tested differences in rsMRI following short-term manipulations, such as intake of a meal. Here, we studied the effect of a high-sugar meal using a within-subject design to test blood glucose and rsfMRI following: 1) an overnight fast and 2) a high-sugar breakfast (720 total kcals, 86g sugar) in 27 individuals (mean BMI 26.8). Independent component analysis resulted in 10 validated brain networks that were used to test within-network functional connectivity differences as a function of food intake. Fed vs. fasted resulted in an increase in blood glucose (p Disclosure G.E. Shearrer: None. J.R. Sadler: None. K. Burger: None.

Clinical-community collaboration is a promising strategy for pediatric obesity treatment, but current research is limited. This study examined the effect of a family-based treatment program embedded in a primary care clinic on retention and changes in child weight status at 1 year.Children (2-16 years, BMI ≥85th percentile, 87.0% Hispanic) and their parents were recruited from a single pediatric clinic for Healthy Hawks Primary Plus (HHP+). Children were referred by physicians and enrolled by a bilingual clinic-based recruitment coordinator. Participants received 12 weekly 2-hour sessions focused on lifestyle modification and health behavior change and then received bimonthly follow-up visits with their clinic-based physician through 1-year follow-up. Child body mass index (BMI) percentage of the 95th percentile (%BMIHHP+ participants had significantly better retention at 1 year (73.9%, p ≤ 0.001) compared to the standard treatment program (38.3%). In HHP+, physician visit attendance was significantly correlated with retention at 1 year (r = 0.69, p ≤ 0.001), and HHP+ completers had significant reductions in %BMIClinical-community partnerships might be a promising strategy to improve retention and reduce child weight status in populations currently underrepresented in obesity treatment.

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.

Energy balance and appetite regulation are a complex process that integrates signals from homeostatic, hedonic, and environmental sources directing eating behavior. In addition to integrating homeostatic signals from the endocrine axis, the brain also drives eating behavior base on learned consummatory habits, sensory cues regarding the energy content and palatability of food, self-regulation, and the environment in which individuals live. This chapter will focus on how different internal and external factors influence central control of appetite, energy intake, and weight status, as well as how eating patterns may alter the brain’s response to food stimuli.

Understanding weight-related differences in functional connectivity provides key insight into neurocognitive factors implicated in obesity. Here, we sampled three groups from human connectome project data: 1) 47 pairs of BMI-discordant twins (n=94; average BMI-discordancy 6.7 ± 3.1 kg/m(2)), 2) 47 pairs of gender and BMI matched BMI-discordant, unrelated individuals, and 3) 47 pairs of BMI-similar twins to test for body mass dependent differences in between network functional connectivity. Across BMI discordant samples, three networks appeared to be highly sensitive to weight status; specifically, a network compromised of gustatory processing regions, a visual processing network, and the default mode network (DMN). Further, individuals with a lower BMI relative to their twin had stronger connectivity between striatal/thalamic and prefrontal networks (pFWE = 0.04) in the BMI-discordant twin sample. We also observed that individuals with a higher BMI than their twin had stronger connectivity between cerebellar and insular networks (pFWE = 0.04). Connectivity patterns observed in the BMI-discordant twin sample were not seen in a BMI-similar sample, providing evidence that the results are specific to BMI discordance. Beyond the involvement of gustatory and visual networks and the DMN, little overlap in results were seen between the two BMI-discordant samples. In concordance with previous research, we hypothesize that stronger cortical-striatal-thalamic connectivity associated with lower body mass in twins may facilitate increased regulation of hedonically motivated behaviors. In twins with higher body mass, increased cerebellar-insula connectivity may be associated with compromised satiation signaling, an interpretation dovetailing prior research. The lack of overlapping results between the two BMI discordant samples may be a function of the higher study design sensitivity in the BMI-discordant twin sample, relative to the more generalizable results in the unrelated sample. These findings demonstrate that distinct connectivity patterns can represent weight variability, adding to mounting evidence that implicates atypical brain functioning with the accumulation and/or maintenance of elevated weight.

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.

Background: Strategies to treat pediatric obesity are needed, especially among high-need populations. Technology is an innovative approach; however, data on technology as adjuncts to in-person treatment programs are limited. Methods: A total of 64 children [body mass index (BMI) ≥85th percentile, mean age = 9.6 ± 3.1 years, 32.8% female, 84.4% Hispanic] were recruited to participate in one of three cohorts of a family-based behavioral group (FBBG) treatment program: FBBG only, TECH1, and TECH2. Rolling, nonrandomized recruitment was used to enroll participants into three cohorts from May 2014 to February 2015. FBBG began in May 2014 and received the standard, in-person 12-week treatment only (n = 21); TECH1 began in September 2014 and received FBBG plus a digital tablet equipped with a fitness app (FITNET) (n = 20); TECH2 began in February 2015 and received FBBG and FITNET, plus five individually tailored TeleMed health-coaching sessions delivered via Skype (n = 23). Child BMI z-score (BMI-z) was assessed at baseline and postintervention. Secondary aims examined weekly FBBG attendance, feasibility/acceptability of FITNET and Skype, and the effect of technology engagement on BMI-z. Results: FBBG and TECH1 participants did not show significant reductions in BMI-z postintervention [FBBG: β = −0.05(0.04), p = 0.25; TECH1: β = −0.006(0.06), p = 0.92], but TECH2 participants did [β = −0.09(0.02), p

In the USA, Hispanics and African-Americans show elevated obesity, yet little is known about possible ethnic/racial differences in brain response during intake of palatable foods. To examine potential differences between non-Hispanic white (nHW) and racial/ethnic minority individuals, we used functional magnetic resonance imaging (fMRI) to assess brain response to intake of eucaloric milkshakes that were either high-sugar or high-fat and a calorie-free, tasteless control solution. Our sample included healthy-weight adolescents who identified as African-American and/or Hispanic (minority, n = 27) and non-Hispanic white (nHW, n = 106). Minority participants showed elevated response in the pre-/postcentral gyrus, precuneus, and left thalamus in response to the high-sugar milkshake compared to high-fat milkshake. To confirm these effects were not driven by differences in body mass or a function of unequal cell sizes, we performed the same analyses in minority participants and a randomly selected subsample of nHW participants (n = 27) that were matched on BMI percentile. Similar to the full sample, we observed an elevated ventral posterior thalamic response to high-sugar milkshake in minority participants. This effect held after controlling for self-reported sugar and fat intake. These results suggest that African-American and Hispanic groups may have elevated response to specifically high-sugar foods in regions of the brain associated with sensory processing, providing novel information regarding the possible neural underpinnings of the disproportional risk for obesity seen in African-American and Hispanic populations.

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.

Objective Although soft drinks are heavily advertised, widely consumed, and have been associated with obesity, little is understood regarding neural responsivity to soft drink intake, anticipated intake, and advertisements. Design and Methods Functional MRI was used to assess examine neural response to carbonated soft drink intake, anticipated intake and advertisement exposure as well as milkshake intake in 27 adolescents that varied on soft drink consumer status. Results Intake and anticipated intake of carbonated Coke® activated regions implicated in gustatory, oral somatosensory, and reward processing, yet high-fat/sugar milkshake intake elicited greater activation in these regions vs. Coke intake. Advertisements highlighting the Coke product vs. nonfood control advertisements, but not the Coke logo, activated gustatory and visual brain regions. Habitual Coke consumers vs. nonconsumers showed greater posterior cingulate responsivity to Coke logo ads, suggesting that the logo is a conditioned cue. Coke consumers exhibited less ventrolateral prefrontal cortex responsivity during anticipated Coke intake relative to nonconsumers. Conclusions Results indicate that soft drinks activate reward and gustatory regions, but are less potent in activating these regions than high-fat/sugar beverages, and imply that habitual soft drink intake promotes hyper-responsivity of regions encoding salience/attention toward brand specific cues and hypo-responsivity of inhibitory regions while anticipating intake.

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: Current obesity theories suggest that the repeated intake of highly palatable high-sugar foods causes adaptions in the striatum, parietal lobe, and prefrontal and visual cortices in the brain that may serve to perpetuate consumption in a feed-forward manner. However, the data for humans are cross-sectional and observational, leaving little ability to determine the temporal precedence of repeated consumption on brain response.Objective: We tested the impact of regular sugar-sweetened beverage intake on brain and behavioral responses to beverage stimuli.Design: We performed an experiment with 20 healthy-weight individuals who were randomly assigned to consume 1 of 2 sugar-sweetened beverages daily for 21 d, underwent 2 functional MRI sessions, and completed behavioral and explicit hedonic assessments.Results: Consistent with preclinical experiments, daily beverage consumption resulted in decreases in dorsal striatal response during receipt of the consumed beverage (r = -0.46) and decreased ventromedial prefrontal response during logo-elicited anticipation (r = -0.44). This decrease in the prefrontal response correlated with increases in behavioral disinhibition toward the logo of the consumed beverage (r = 0.54; P = 0.02). Daily beverage consumption also increased precuneus response to both juice logos compared with a tasteless control (r = 0.45), suggesting a more generalized effect toward beverage cues. Last, the repeated consumption of 1 beverage resulted in an explicit hedonic devaluation of a similar nonconsumed beverage (P < 0.001).Conclusions: Analogous to previous reports, these initial results provide convergent data for a role of regular sugar-sweetened beverage intake in altering neurobehavioral responses to the regularly consumed beverage that may also extend to other beverage stimuli. Future research is required to provide evidence of replication in a larger sample and to establish whether the neurobehavioral adaptations observed herein are specific to high-sugar and/or nonnutritive-sweetened beverages or more generally related to the repeated consumption of any type of food. This trial was registered at clinicaltrials.gov as NCT02624206.

The objective of the study was to test the hypotheses that humans with genotypes putatively associated with low dopamine (DA) signaling capacity, including the TaqIA A1 allele, DRD2-141C Ins/Ins genotype, DRD4 7-repeat or longer allele, DAT1 10-repeat allele, and the Met/Met COMT genotype, and with a greater number of these genotypes per a multilocus composite, show less responsivity of reward regions that primarily rely on DA signaling. Functional magnetic resonance imaging (fMRI) paradigms were used to investigate activation in response to receipt and anticipated receipt of palatable food and monetary reward. DNA was extracted from saliva using standard methods. Participants were 160 adolescents (mean age = 15.3 years, SD = 1.07 years; mean body mass index = 20.8, SD = 1.9). The main outcome was blood oxygenation level-dependent activation in the fMRI paradigms. Data confirmed that these fMRI paradigms activated reward, attention, somatosensory, and gustatory regions. Individuals with, versus without, these five genotypes did not show less activation of DA-based reward regions, but those with the Met/Met versus the Val/Val COMT genotype showed less middle temporal gyrus activation and those with the DRD4-L versus the DRD4-S genotype showed less middle occipital gyrus activation in response to monetary reward. Critically, the multilocus composite score revealed that those with a greater number of these genotypes showed less activation in reward regions, including the putamen, caudate, and insula, in response to monetary reward. The results suggest that the multilocus genetic composite is a more sensitive index of vulnerability for low reward region responsivity than individual genotypes.

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.

Advances in neuroimaging techniques have provided insight into the role of the brain in the regulation of food intake and weight. Growing evidence demonstrate that energy dense, palatable foods elicit similar responses in reward-related brain regions that mimic those of addictive substances. Currently, various models of obesity’s relation to reward from food have been theorized. There is evidence to support a theory of hypo-responsivity of reward regions to food, where individuals consume excess amounts to overcome this reward deficit. There is also data to support a theory of hyper-responsivity of reward regions, where individuals who experience greater reward from food intake are at risk for overeating. However, these seemingly discordant theories are static in nature and do not account for the possible effects of repeated overeating on brain responsivity to food and initial vulnerability factors. Here we review data that support these theories and propose a dynamic vulnerability model of obesity that appears to offer a parsimonious theory that accommodates extant findings.

Obese humans, compared with normal-weight humans, have less striatal D2 receptors and striatal response to food intake; weaker striatal response to food predicts weight gain for individuals at genetic risk for reduced dopamine (DA) signaling, consistent with the reward-deficit theory of obesity. Yet these may not be initial vulnerability factors, as overeating reduces D2 receptor density, D2 sensitivity, reward sensitivity, and striatal response to food. Obese humans also show greater striatal, amygdalar, orbitofrontal cortex, and somatosensory region response to food images than normal-weight humans do, which predicts weight gain for those not at genetic risk for compromised dopamine signaling, consonant with the reward-surfeit theory of obesity. However, after pairings of palatable food intake and predictive cues, DA signaling increases in response to the cues, implying that eating palatable food contributes to increased responsivity. Using fMRI, we tested whether normal-weight adolescents at high- versus low-risk for obesity showed aberrant activation of reward circuitry in response to receipt and anticipated receipt of palatable food and monetary reward. High-risk youth showed greater activation in the caudate, parietal operculum, and frontal operculum in response to food intake and in the caudate, putamen, insula, thalamus, and orbitofrontal cortex in response to monetary reward. No differences emerged in response to anticipated food or monetary reward. Data indicate that youth at risk for obesity show elevated reward circuitry responsivity in general, coupled with elevated somatosensory region responsivity to food, which may lead to overeating that produces blunted dopamine signaling and elevated responsivity to food cues.

Increases in portion size lead to increases in energy intake, yet the mechanisms behind this "portion size effect" are unclear. This study tested possible mechanisms of the portion size effect, i.e., bite size and visual cues. A 2 × 2 repeated measures, within-subject design was used to test the effects of portion size (410 g vs. 820 g of a pasta dish) and visual cues (blindfolded vs. visible) on energy intake in 30 individuals (15 men, 15 women). At each meal participants were exposed to one of four experimental conditions (small portion/visible; small portion/blindfold; large portion/visible; large portion/blindfold). Participant characteristics, food intake, number of bites, meal duration, palatability measures and hunger and fullness were assessed. In response to a doubling of the portion presented, entree energy intake increased 26% (220 kcal; P < 0.001) and mean bite size increased 2.4 g/bite (P < 0.05). Overweight (OW) individuals consumed 40% (334 kcal) more of the entree in response to the large portion condition (P < 0.05), while lean individuals' intakes did not differ (P < 0.56). A 12% (122 kcal) decrease in entree intake was observed in the blindfolded condition (P < 0.01), but no portion by visual cue interaction was found; indicating that blindfolding did not significantly attenuate the portion size effect. These data suggest that the portion size effect is not impacted by removing the visual cue of food and that this effect occurs via changes in bite size in adults.

The rising prevalence of maternal overweight/obesity and excessive gestational weight gain poses a serious public health concern due to the contribution of these factors to increased risk of negative health outcomes for both mother and child. Scant intervention research has indicated moderate short-term improvement in maternal diet and gestational weight gain, with little evidence of long-term behavior change, in parallel with findings from interventions outside of pregnancy. Recent laboratory-based findings from neuroscience implicate aberrant reward processing of food at the brain level (“food reward sensitivity,” the between-individual variation in the response to food stimuli) as a contributor to eating beyond energy needs. However, scant research has examined the influence of these processes on weight change in population-based settings, and the relevance of these processes to pregnancy-related weight change has not been explored. The purpose of the Pregnancy Eating Attributes Study (PEAS) is to examine the role of food reward sensitivity in maternal diet and weight change during pregnancy and postpartum. The study examines the interplay of food reward sensitivity with behavioral control, home food environment, and related aspects of eating behavior in the context of weight-related biomedical, psychosocial, genetic and behavioral factors including physical activity, stress, sleep and depression. Women of varying baseline weight status (n = 450) are enrolled early in pregnancy and followed, along with their infants, until 1 year postpartum. Assessments occur during each trimester of pregnancy, and postpartum at approximately 2 months, 6 months, 9 months and 12 months. Maternal food reward, self-control, home food environment, eating behaviors, dietary intake, health behaviors, and anthropometrics are assessed along with maternal and infant clinical and biological data, infant anthropometrics, and feeding practices. Primary exposures of interest include food reward sensitivity, behavioral control, and home food environment. Primary outcomes include gestational weight gain, postpartum weight retention and maternal diet quality. With increasing evidence suggesting the relevance of food reward sensitivity for understanding eating behavior, PEAS aims to advance understanding of the determinants of eating behavior during pregnancy, informing future interventions for improving maternal diet and weight change, and leading to improved maternal and child health and weight trajectories. Clinicaltrials.gov, NCT02217462 . Date of registration: August 13, 2014

Children in the United States (US) are frequently exposed to advertisements for high-fat, high-sugar (HFHS) foods, which is linked to greater demand for and consumption of those foods. Restricting advertisements for HFHS foods may be a viable obesity prevention strategy-however, public support for policy change is unclear.A secondary analysis of the 2012 Annenberg National Health Communication Survey was conducted. Respondents (N = 1838) were 53.2% female, mean age 50.0 ± 16.5 years. Race/ethnic composition was 76.8% white, 7.4% black, 9.2% Hispanic, and 6.6% other. The percentage of respondents supporting and opposing the regulation was calculated and logistic regression models identified predictors of support. Potential predictors included sociodemographic variables, attitudes towards other health regulations (e.g., smoking bans in public places), and various health behaviors (e.g., fruit and vegetable intake).A total of 56.3% of respondents supported or strongly supported advertisement restrictions, while only 8.2% strongly opposed. Approximately 20% had no opinion. Greatest support was found among respondents who supported smoking bans in public settings (OR = 4.3), who supported banning trans fats in restaurants (OR = 1.7), and who were older (OR = 1.7).The US adult population appears to have an appetite for restricting HFHS advertising to children, with more than half the populace supporting such a policy in 2012. This may be an opportune time to implement and rigorously evaluate such childhood obesity prevention strategies.

Caloric intake and energy balance are highly regulated to maintain metabolic homeostasis and weight. However, hedonic-motivated food intake, in particular consumption of highly rewarding foods, may act to override hemostatic signaling and contribute to overconsumption, weight gain, and obesity. Here, we review human neuroimaging literature that has delivered valuable insight into the neural correlates of hedonic-motivated ingestive behavior, weight gain, weight loss, and metabolic status. Our primary focus is the brain regions that are thought to encode aspects of food hedonics, gustatory and somatosensory processing, and executive functioning. Further, we discuss the variability of regional brain response as a function of obesity, weight gain, behavioral and surgical weight loss, as well as in type 2 diabetes.