Abnormalities in deep-brain morphology and orbitofrontal cortical thinning relate to reward processing and body mass in adolescent girls.

BACKGROUND: Research examining the neural correlates of obesity has recently expanded. However, limited attention has focused on identifying unique brain signatures associated with obesity, particularly in adolescents. The aim of this study was to use surface-based approaches to examine the integrity of brain structures involved in processing the pleasurable effects of food with body mass and food reward sensitivity in adolescent girls. METHODS: Structural morphology of the nucleus accumbens, amygdala, pallidum, and orbitofrontal cortex was examined in 89 adolescent girls with body mass ranging from normal to obese. High-resolution T1-weighted MPRAGE images were used to characterize deep-brain nuclei with high-dimensional diffeomorphic mapping procedures, while cortical thickness was derived from the FreeSurfer toolkit. RESULTS: Results revealed that zBMI was significantly associated with the shape of the left amygdala (ß = -1.1, p < 0.021, 95% CI = -2.02, -0.16), volume of the right and left pallidum (ß = 49.66, p < 0.010, 95% CI = 11.74, 87.58; ß = 47.87, p < 0.017, 95% CI = 8.48, 87.25), and cortical thickness of the lateral and right medial orbitofrontal cortex (ß = -0.06, p < 0.001, 95% CI = -0.09, -0.04; ß = -0.05, p = 0.004, 95% CI = -0.08, -0.02). Sensitivity to food reward significantly predicted volume of the right nucleus accumbens (ß = 0.66, p = 0.047, 95% CI = 0.01, 1). Contrast mapping for surface shape of the amygdala revealed significant outward deformation of the posterior lateral left amygdala and an inward deformation of the basolateral left amygdala in the group with overweight/obesity. CONCLUSIONS: Integrity of the left amygdala and orbitofrontal cortex varies as a function of body mass, with greater localized amygdalar volume loss, pallidum volume, and increased cortical thinning of the orbitofrontal cortex occurring as weight increases. Thus, overweight/obesity may be associated with surface-based abnormalities in brain structures associated with processing of reward value related to food. Overall, findings highlight the importance of understanding changes in reward-related brain regions and how they pertain to variability in body mass in adolescent girls.

Neural mechanisms that promote food consumption following sleep loss and social stress: an fMRI study in adolescent girls with overweight/obesity.

STUDY OBJECTIVES: Insufficient sleep and social stress are associated with weight gain and obesity development in adolescent girls. Functional magnetic resonance imaging (fMRI) research suggests that altered engagement of emotion-related neural networks may explain overeating when under stress. The purpose of this study is to explore the effects of acute sleep restriction on female adolescents' neural responding during social evaluative stress and their subsequent eating behavior. METHODS: Forty-two adolescent females (ages 15-18 years) with overweight or obesity completed a social stress induction task in which they were told they would be rated by peers based on their photograph and profile. Participants were randomly assigned to one night of sleep deprivation or 9 h of sleep the night before undergoing fMRI while receiving positive and negative evaluations from their peers. After which, subjects participated in an ad libitum buffet. RESULTS: Sleep deprived, relative to nondeprived girls had distinct patterns of neural engagement to positive and negative evaluation in anterior, mid, and posterior aspects of midline brain structures. Moreover, a sleep deprivation-by-evaluation valence-by-caloric intake interaction emerged in bilateral dorsal anterior cingulate. Among sleep deprived girls, greater engagement during negative, but not positive, feedback was associated with lower caloric intake. This was not observed for nonsleep deprived girls. CONCLUSIONS: Results suggest an interaction between acute sleep loss and social evaluation that predicts emotion-related neural activation and caloric intake in adolescents. This research helps to elucidate the relationship between sleep loss, social stress, and weight status using a novel health neuroscience model.

Maternal self-efficacy is associated with mother-child feeding practices in middle childhood.

OBJECTIVE: Maternal self-efficacy (MSE) is a well-established correlate of health outcomes in young children, though little is known about this association in older children. The purpose of this cross-sectional study was to examine how MSE relates to mother-child feeding practices in middle childhood. METHODS: A total of 306 children ages 8-12 (Mean age = 9.72, SD = 0.91, 52.9% female) and their mothers participated in this study. Mothers completed the New General Self-Efficacy Scale and the Child Feeding Questionnaire. A series of hierarchical regression models were used to examine how MSE related to maternal food restriction, maternal pressure to eat, and maternal food monitoring. RESULTS: After accounting for maternal Body Mass Index (BMI), education, and age, and child Body Mass Index Percentile (BMI%ile) and age within the first step of each regression model, MSE emerged as a significant predictor for maternal restriction of foods (p = .024) and maternal food monitoring (p = .048). MSE was not significantly related to maternal pressure to eat. CONCLUSIONS: This study is the first to establish that higher MSE is significantly related to healthier mother-child feeding practices in middle childhood, providing preliminary justification for enhancing MSE within comprehensive family interventions to support child weight-related health.

Does iPhone night shift mitigate negative effects of smartphone use on sleep outcomes in emerging adults?

OBJECTIVES: Apple's iPhone Night Shift feature purports to reduce short-wavelength light emissions and improve sleep. We aimed to investigate these claims by comparing emerging adults' sleep outcomes associated with smartphone use before bed with iPhone's Night Shift enabled to two comparison conditions (iPhone use with no Night Shift, no iPhone use). DESIGN: Participants were randomly assigned to one of three conditions specifying iPhone use during the hour preceding bedtime for seven consecutive nights: iPhone use with Night Shift enabled; iPhone use with Night Shift disabled; and no phone use. SETTING: Participants were recruited from a western undergraduate university. PARTICIPANTS: A sample of 167 emerging adults (ages 18-24; 71.3% female) with iPhones participated in the study. MEASUREMENTS: Sleep outcomes (sleep latency, duration, efficiency and wake after sleep onset) were tracked using wrist-worn accelerometers. RESULTS: There were no significant differences in sleep outcomes across the three experimental groups. Post-hoc exploratory stratified analyses revealed a significant main effect of phone condition on sleep efficiency (P = .014) and WASO (P = .013) for participants averaging more than 6.8 hours of sleep per night, with the no phone condition demonstrating the best sleep outcomes. For those averaging less than 6.8 hours of sleep, there was no effect of phone condition on sleep outcomes. CONCLUSIONS: Across our full study sample, there were no differences in sleep outcomes attributable to Night Shift. For individuals who regularly obtained adequate sleep, abstaining from screen use resulted in better quality sleep than did phone use with Night Shift enabled.