Using food network analysis to understand meal patterns in pregnant women with high and low diet quality.

BACKGROUND: Little is known about how meal-specific food intake contributes to overall diet quality during pregnancy, which is related to numerous maternal and child health outcomes. Food networks are probabilistic graphs using partial correlations to identify relationships among food groups in dietary intake data, and can be analyzed at the meal level. This study investigated food networks across meals in pregnant women and explored differences by overall diet quality classification. METHODS: Women were asked to complete three 24-h dietary recalls throughout pregnancy (n = 365) within a prospective cohort study in the US. Pregnancy diet quality was evaluated using the Healthy Eating Index-2015 (HEI, range 0-100), calculated across pregnancy. Networks from 40 food groups were derived for women in the highest and lowest HEI tertiles at each participant-labeled meal (i.e., breakfast, lunch, dinner, snacks) using Gaussian graphical models. Network composition was qualitatively compared across meals and between HEI tertiles. RESULTS: In both HEI tertiles, breakfast food combinations comprised ready-to-eat cereals with milk, quick breads with sweets (e.g., pancakes with syrup), and bread with cheese and meat. Vegetables were consumed at breakfast among women in the high HEI tertile only. Combinations at lunch and dinner were more varied, including vegetables with oils (e.g., salads) in the high tertile and sugary foods with nuts, fruits, and milk in the low tertile at lunch; and cooked grains with fats (e.g., pasta with oil) in the high tertile and potatoes with vegetables and meat in the low tertile at dinner. Fried potatoes, sugar-sweetened beverages, and sandwiches were consumed together at all main meals in the low tertile only. Foods were consumed individually at snacks in both tertiles; the most commonly consumed food were fruits in the high HEI tertile and cakes & cookies in the low tertile. CONCLUSIONS: In this cohort of pregnant women, food network analysis indicated that food combinations differed by meal and between HEI tertiles. Meal-specific patterns that differed between diet quality tertiles suggest potential targets to improve food choices at meals; the impact of meal-based dietary modifications on intake of correlated foods and on overall diet quality should be investigated in simulations and intervention studies. TRIAL REGISTRATION: PEAS was registered with number NCT02217462 in Clinicaltrials.gov on August 13, 2014.

Alterations in ventral attention network connectivity in individuals with prediabetes.

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 (p FWE = 0.0001); (2) a somatosensory network (p FWE = 0.0027). Individuals with healthy HbA1c showed stronger connectivity of the ventral attention network and (1) cingulo-opercular network (p FWE = 0.002); (2) a thalamic-striatal-visual network (p FWE = 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.

Estimating individualized treatment regimes from crossover designs.

The field of precision medicine aims to tailor treatment based on patient-specific factors in a reproducible way. To this end, estimating an optimal individualized treatment regime (ITR) that recommends treatment decisions based on patient characteristics to maximize the mean of a prespecified outcome is of particular interest. Several methods have been proposed for estimating an optimal ITR from clinical trial data in the parallel group setting where each subject is randomized to a single intervention. However, little work has been done in the area of estimating the optimal ITR from crossover study designs. Such designs naturally lend themselves to precision medicine since they allow for observing the response to multiple treatments for each patient. In this paper, we introduce a method for estimating the optimal ITR using data from a 2 × 2 crossover study with or without carryover effects. The proposed method is similar to policy search methods such as outcome weighted learning; however, we take advantage of the crossover design by using the difference in responses under each treatment as the observed reward. We establish Fisher and global consistency, present numerical experiments, and analyze data from a feeding trial to demonstrate the improved performance of the proposed method compared to standard methods for a parallel study design.

Individual differences in appeal of energy dense foods predicts lower body mass change during adolescence.

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 (ß= -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 (ß = - 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.

Body mass variability is represented by distinct functional connectivity patterns.

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 ±â€¯3.1 kg/m2), 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 comprised of gustatory processing regions, a visual processing network, and the default mode network (DMN). Further, in the BMI-discordant twin sample, twins with lower BMI had stronger connectivity between striatal/thalamic and prefrontal networks (pFWE = 0.04). 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 findings, 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 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.

The impact of sugar sweetened beverage intake on hunger and satiety in minority adolescents.

Limited research has examined the effects of habitual SSB consumption on hunger/fullness ratings and gut hormones. This study hypothesized that high versus low intakes of habitual SSBs would result in greater hunger, decreased fullness, and a blunted gut hormone response, however the high versus low fiber group would exhibit decreased hunger and increased fullness. This was a randomized crossover feeding trial with 47 African American and Hispanic adolescents. The experiment included three 24-hour recalls to assess habitual dietary intake. During the test meal phase, subjects were served breakfast and lunch. During the ad libitum meal phase, subjects were fed an ad libitum dinner. During the test meal phase, blood was drawn every 30 minutes for 3 hours. During the ad libitum meal phase, hunger and fullness visual analogue scales were completed. For this analysis, subjects were grouped into the following habitual SSB categories: low SSB (≤1 SSB serv/day), medium SSB (>1 - <2 serv/day), and high SSB (≥2 serv/day). Fiber categories were created based on quartiles of intake. Mixed modeling was used to explore how SSB and fiber categories predicted ghrelin/PYY values and hunger/fullness ratings across time within and between test meals. The following a priori covariates included: sex, ethnicity, age, and obesity status. The low SSB group had higher fullness ratings over the ad libitum meal compared to the high SSB group (ß =-0.49, CI=(-0.89, -0.08), p=0.02) and higher ghrelin concentrations than the medium and high SSB group over the test meal phase (ß =-1.86, CI=(-2.81, -0.92), p<0.01). Habitual SSB intake appears to play a key role in moderating fullness responses possibly via ghrelin.

Brain-based etiology of weight regulation.

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.

The Interaction of Glycemia with Anxiety and Depression Is Related to Altered Cerebellar and Cerebral Functional Correlations.

Depression, type 2 diabetes (T2D), and obesity are comorbid, and prevention and treatment of all three diseases are needed. We hypothesized an inverse relationship between the connectivity of the cingulo-opercular task control network with the somatosensory mouth network and the interaction between HbA1c and depression. Three-hundred and twenty-five participants (BMI: 26.11 ± 0.29; Achenbach adult self-report (ASR) DSM depressive problems T-score (depression): 54.60 ± 6.77; Age: 28.26 ± 3.90 y; adult self-report anxiety and depression scale (anxiety and depression): 54.69 ± 7.27; HbA1c: 5.26 ± 0.29; 68% white) were sampled from the Human Connectome Project 1200 subjects PTN release. Inclusion criteria were: four (15 min) resting state fMRI scans; BMI; hemoglobin A1c (HbA1c); and complete adult self-report data. The following models were run to assess the connectivity between 15 independent fMRI components: the interaction of depression with HbA1c; anxiety and depression with HbA1c; depression with BMI; and anxiety and depression with BMI. All models were corrected for a reported number of depressive symptoms, head motion in the scanner, age, and race. Functional connectivity was modeled in FSLNets. Corrected significance was set at pFWE < 0.05. The interaction HbA1c and anxiety and depression was positively related to the connectivity of the cerebellum with the visual network (t = 3.76, pFWE = 0.008), frontoparietal network (t = 3.45, pFWE = 0.02), and somatosensory mouth network (t = 4.29, pFWE = 0.0004). Although our hypotheses were not supported, similar increases in cerebellar connectivity are seen in patients with T2D and overall suggest that the increased cerebellar connectivity may be compensatory for an increasingly poor glycemic control.

Correlates of neural adaptation to food cues and taste: the role of obesity risk factors.

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.

Longitudinal Associations Between Taste Sensitivity, Taste Liking, Dietary Intake and BMI in Adolescents.

Taste sensitivity and liking drive food choices and ingestive behaviors from childhood to adulthood, yet their longitudinal association with dietary intake and BMI is largely understudied. Here, we examined the longitudinal relationship between sugar and fat sensitivity, sugar and fat liking, habitual dietary intake, and BMI percentiles in a sample of 105 healthy-weight adolescents (baseline: BMI %tile 57.0 ± 24.3; age 14-16 years) over a 4-year period. Taste sensitivity was assessed via a triangle fat and sweet taste discrimination test. Taste liking were rated on a visual analog scale for four milkshakes that varied in sugar and fat contents (high-fat/high-sugar (HF/HS), low-fat/high-sugar (LF/HS), high-fat/low-sugar (HF/LS), low-fat/low-sugar (LF/LS) milkshakes). A modified version of the reduced Block Food Frequency Questionnaire (BFFQ) was used to assess dietary intake. All measurements were repeated annually. Repeated measures correlations and linear mixed effects models were used to model the associations between the variables. Sugar sensitivity was negatively associated with liking for the LF/HS milkshake over the 4-year period. Low sugar sensitivity at baseline predicted increases in BMI percentile over time, but this association didn't survive a correction for multiple comparisons. Percent daily intake from fat was positively associated with liking for the HF/HS milkshake and negatively associated with liking for the LF/LS milkshake over 4 years. Together, these results demonstrate that lower sensitivity to sweet taste is linked to increased hedonic response to high-sugar foods and increased energy intake from fat seems to condition adolescents to show increased liking for high-fat/high-sugar foods.

Eating in the Absence of Hunger Is Related to Worse Diet Quality throughout Pregnancy.

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 second 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 (HEI-2015) and adherence to adequacy and moderation components 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 (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- to 3-point decrease (standard error = 0.7 to 0.8) in HEI-2015 (P < 0.01); each 10% increase in EAH of HP foods was associated with a 5- to 7-point decrease (standard error = 2.0) in HEI-2015 (P < 0.01). Greater EAH (energy and percent offered) of savory food intake in the HP condition was associated with a lower HEI-2015 adequacy component score, but was not associated with the HEI-2015 or HEI-2015 moderation component scores. EAH in the MP condition was not associated with pregnancy diet quality. CONCLUSIONS: Greater EAH of HP, especially sweet, foods was related to worse pregnancy diet quality. Consuming HP sweets after meal termination may reflect a tendency for eating beyond satiation and may be a useful intervention target for improving maternal diet quality.

Pregnant Women Consume a Similar Proportion of Highly vs Minimally Processed Foods in the Absence of Hunger, Leading to Large Differences in Energy Intake.

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.

Earlier onset of menstruation is related to increased body mass index in adulthood and altered functional correlations between visual, task control and somatosensory brain networks.

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.

Behavioral and physiological characteristics associated with learning performance on an appetitive probabilistic selection task.

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 (ß=-.035, p=.019), BIS (ß=-.066, p=.004), and SPQ (ß=.003, p=.023) were associated with overall learning performance. BMI (ß=-.000, p=.012), emotional eating (ß=.055, p=.006), and external eating (ß=-.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 (ß=-.005, p=.025), such that the relationship was positive in women only (ß=.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.

Network organization during probabilistic learning via taste outcomes.

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, normal 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 avoiding a bitter taste, and that BMI is associated with increased connectivity of area involved in processing external stimuli. Network organization and topology provide unique insight into individual differences in brain response to instrumental conditioning via taste reinforcers.

Association between regional brain volumes and BMI z-score change over one year in children.

PURPOSE: Associations between brain region volume and weight status have been observed in children cross-sectionally. However, it is unclear if differences in brain region volume precede weight gain. METHODS: Two high-quality structural brain images were obtained approximately one year apart in 53 children aged 9-12 years old. Children's height and weight were also measured at each scan. Structural images were processed using the FreeSurfer software-package providing volume measures for regions of interest including the entorhinal cortex, nucleus accumbens, and hippocampus. Age- and sex-adjusted BMI z-scores (BMIz) were calculated at both timepoints. The association between brain region volume and BMIz was examined cross-sectionally using linear regression and longitudinally using structural equation modeling. All models were adjusted by estimated cranial volume to account for individual variation in head size and were corrected for multiple comparisons (pFDR<0.05). RESULTS: The sample of children was primarily healthy weight at baseline (79.78%). Cross-sectionally at the one-year follow-up, a positive relationship was observed between right hippocampal volume and BMIz (ß = 0.43, 95% CI = (0.10, 0.77)). Longitudinally a negative relationship was observed between right entorhinal volume at baseline and BMIz at the one-year follow-up (ß = -0.25, 95% CI = (-0.44, -0.07)). CONCLUSION: These results suggest that measured volumes from certain regions of the brain that have been associated with BMI in adults are associated with both concurrent BMIz and BMIz change over one-year in a primarily healthy weight sample of children. As the entorhinal cortex integrates signals from both reward and control regions, this region may be particularly important to weight management during child development.

The impact of elevated body mass on brain responses during appetitive prediction error in postpartum women.

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 ±â€¯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.

Ultraprocessed Foods at Home and Children's Attentional Bias Toward Those Foods.

This study examines the association between exposure to ultraprocessed foods at home and children's attentional bias for those foods.

Adolescents at high risk of obesity show greater striatal response to increased sugar content in milkshakes.

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/m2): 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 < 0.05), replicating a previous report. Notably, high-risk adolescents showed greater caudate, gustatory, and oral somatosensory responses to the high-sugar milkshake than to the tasteless solution; however, no effect of risk status was observed in the high-fat milkshake condition. Responses to food images were not related to obesity risk status. Conclusion: Collectively, the data presented here suggest that parental weight status is associated with greater striatal, gustatory, and somatosensory responses to palatable foods-in particular, high-sugar foods-in their adolescent offspring, which theoretically contributes to an increased risk of future overeating. This trial was registered at www.clinicaltrials.gov as NCT01949636.

Decreased eating frequency linked to increased visceral adipose tissue, body fat, and BMI in Hispanic college freshmen.

BACKGROUND: To investigate the relationship between eating frequency and specific adiposity markers in a potentially high-risk and understudied population of Hispanic college freshmen. METHODS: This study included 92 Hispanic college freshmen (18-19 y). The following cross-sectional data were collected: height, weight, waist circumference, body mass index (BMI), dietary intake, body composition, physical activity, hepatic fat, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). RESULTS: Infrequent eaters ate 44% less often (2.5 ± 0.2 vs. 4.5 ± 0.8, p ≤ 0.01) and consumed 27% more calories per EO (p ≤ 0.01), while consuming 21% less kcals per day (p ≤ 0.01) compared to frequent eaters. Infrequent eaters had 8% higher BMIs (24.8 ± 4.4 vs. 22.9 ± 3.2 kg/m2) (p = 0.02), 60% higher BMI z-scores (0.5 ± 1.0 vs. 0.2 ± 1.0, p = 0.03), 21% higher VAT (298.3 ± 153.8 vs. 236.8 ± 78.2 ml, p = 0.03), 26% higher SAT (1150.1 ± 765.4 vs. 855.6 ± 494.6 ml, p = 0.03), and 8% higher total body fat (27.6 ± 10.8 vs. 25.3 ± 8.8%, p = 0.04) compared to frequent eaters while showing no significant difference in physical activity. These findings seem to be driven by females more than males. CONCLUSIONS: These findings suggest that infrequent eating is related to increased adiposity in Hispanic college freshmen, despite a decreased daily energy intake and no significant differences in physical activity. Yet, more research is needed to understand the underlying mechanisms of these findings, as well as investigate any potential causal relationship between eating frequency and adiposity in Hispanic youth.