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.

Energy expenditure during nutritional rehabilitation: a scoping review to investigate hypermetabolism in individuals with anorexia nervosa.

BACKGROUND: Weight gain and nutritional rehabilitation are essential first steps to achieve medical stabilization in anorexia nervosa, and frequent resistance to weight gain requires patients to consume high kilocalorie loads. Adaptive hypometabolism is common when patients begin treatment, and rebound hypermetabolism is suspected to be a significant barrier to weight gain. The aim of this review was to summarize existing data describing metabolic changes in anorexia nervosa during weight restoration. The reported findings challenge current hypotheses of weight gain resistance and highlight key areas for future research. METHODS: Using scoping review guidelines, three databases were searched for studies investigating metabolic changes in anorexia nervosa before and after renourishment. Two reviewers systematically screened the titles and abstracts of 447 articles, and full-text versions of 106 studies were assessed for eligibility. A total of 36 studies were included for review. Data regarding the study description, sample population (including age, weight, BMI, duration of treatment, and caloric intake), and metabolic variable descriptions were extracted. RESULTS: Female patients with anorexia nervosa from studies across 13 countries were included. Across the studies, average BMI increased from 13.7 kg/m2 at admission to 17.57 kg/m2. Patients presented to treatment with clinically reduced energy expenditure levels. After varying levels of nutritional rehabilitation and weight restoration, measured energy expenditure increased significantly in 76% of the studies. Energy expenditure values at the second timepoint increased to the standard range for normal weight female teenagers and adults. Despite these increases, the studies do not indicate the presence of a hypermetabolic state during renourishment. Additionally, all studies including both measured and predicted energy expenditure reported that predicted energy expenditure overestimated measured values. CONCLUSION: This study provides a detailed evaluation of the literature investigating energy expenditure and metabolic rate in patients with anorexia nervosa before and following a period of renourishment. The findings from this review identify important gaps in the current beliefs of energy expenditure in anorexia nervosa and highlight a need for further exploration of metabolic alterations during weight restoration.

Nutritional rehabilitation and weight restoration are two primary goals of anorexia nervosa treatment that pose significant physiological and psychological challenges for patients. Patients often require high caloric loads to continue an adequate weight gain trajectory, but the underlying cause of weight gain resistance remains unknown. We completed a scoping review of research into energy expenditure and metabolic rate during treatment. Our search identified 447 relevant articles from academic databases, and 106 were deemed eligible after screening. We extracted data, including sample characteristics, kilocalorie intake, energy expenditure, and treatment information, from 36 studies. When individuals arrived for treatment, their energy expenditure was lower than that of individuals without an eating disorder due to the prolonged state of nutrient deprivation. After varying amounts of time and kilocalorie intake, most studies reported significant increases in energy expenditure. However, energy expenditure after a period of renourishment did not indicate an overactive metabolism (i.e., "hypermetabolism"). Funders should consider supporting exploration of additional factors that may be functioning as barriers to weight gain during treatment, in pursuit of making treatment more efficient and long-lasting. Additionally, future research describing metabolism in anorexia nervosa should provide more consistent methodologies, robust statical testing, and comprehensive reporting of dietary intake.

Food reinforcement architecture: A framework for impulsive and compulsive overeating and food abuse.

Few reward-based theories address key drivers of susceptibility to food cues and consumption beyond fullness. Decision-making and habit formation are governed by reinforcement-based learning processes that, when overstimulated, can drive unregulated hedonically motivated overeating. Here, a model food reinforcement architecture is proposed that uses fundamental concepts in reinforcement and decision-making to identify maladaptive eating habits that can lead to obesity. This model is unique in that it identifies metabolic drivers of reward and incorporates neuroscience, computational decision-making, and psychology to map overeating and obesity. Food reinforcement architecture identifies two paths to overeating: a propensity for hedonic targeting of food cues contributing to impulsive overeating and lack of satiation that contributes to compulsive overeating. A combination of those paths will result in a conscious and subconscious drive to overeat independent of negative consequences, leading to food abuse and/or obesity. Use of this model to identify aberrant reinforcement learning processes and decision-making systems that can serve as markers of overeating risk may provide an opportunity for early intervention in obesity.

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.

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.

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.

Characterizing the weight-glycemia phenotypes of type 1 diabetes in youth and young adulthood.

INTRODUCTION: Individuals 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 METHODS: Participants 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. RESULTS: The 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 <58 mmol/mol (7.5%). Cluster 1 (34.0%) was normal weight with the lowest HbA1c and comprised 85% NHW participants with the highest socioeconomic position, insulin pump use, dietary quality, and physical activity. Subgroups with very poor glycemic control (ie, ≥108 mmol/mol (≥12.0%); cluster 4, 4.4%, and cluster 5, 7.5%) and obesity (cluster 6, 15.4%) had a lower proportion of NHW youth, lower socioeconomic position, and reported decreased pump use and poorer health behaviors (overall p<0.01). The overweight subgroup with very poor glycemic control (cluster 5) showed the highest lipids and blood pressure (p<0.01). CONCLUSIONS: There 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.

Longitudinal Phenotypes of Type 1 Diabetes in Youth Based on Weight and Glycemia and Their Association With Complications.

CONTEXT: Subclinical and clinical complications emerge early in type 1 diabetes (T1D) and may be associated with obesity and hyperglycemia. OBJECTIVE: Test how longitudinal "weight-glycemia" phenotypes increase susceptibility to different patterns of early/subclinical complications among youth with T1D. DESIGN: SEARCH for Diabetes in Youth observational study. SETTING: Population-based cohort. PARTICIPANTS: Youth with T1D (n = 570) diagnosed 2002 to 2006 or 2008. MAIN OUTCOME MEASURES: Participants 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. RESULTS: Four 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). CONCLUSIONS: Weight-glycemia phenotypes show different patterns of complications, particularly markers of subclinical macrovascular disease, even in the first decade of T1D.

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.

Identification of clinically relevant dysglycemia phenotypes based on continuous glucose monitoring data from youth with type 1 diabetes and elevated hemoglobin A1c.

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 < .001). Dysglycemia Cluster 3 (n = 40, 17.1%) showed severe hypoglycemia and glycemic variability with moderate hyperglycemia and had a lower baseline HbA1c than Clusters 1 and 2 (P < .001). This cluster showed increases in HbA1c over 18 months (p-for-interaction = 0.006). No other baseline characteristics were associated with Dysglycemia Clusters. High HbA1c was associated with lower pump use, greater insulin doses, more frequent blood glucose monitoring, lower motivation, and lower adherence to diabetes self-management (all P < .05). CONCLUSIONS: There are subgroups of adolescents with T1D for which glycemic control is challenged by different aspects of dysglycemia. Enhanced understanding of demographic, behavioral, and clinical characteristics that contribute to CGM-derived dysglycemia phenotypes may reveal strategies to improve treatment.

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.

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.