Background: \- Studies show that many factors affect children's eating behavior and health. These include sleep, mood, thinking skills, and genetics. Studying children over time may identify children at higher risk for eating-related health concerns. Objective: \- To understand how genes and environment influence eating behavior and health over time. Eligibility: \- Children ages 8-17 in good general health. Design: * Screening visit 1: Medical history, physical exam, body measurements, and questions. * 14 days: Participants will wear a wrist monitor and answer smartphone prompts about eating and mood. They may give a stool sample. * Screening visit 2: * Body measurements. * Saliva, urine, and blood samples. * Heart tests. * Meals provided (after fasting overnight). * Questionnaires and interview. * Behavior, thinking, and exercise tests. * X-ray of left wrist and full body.\<TAB\> * Some parents may have medical history, physical exam, and questions at screening visits. They may answer questions at the yearly visits. * Participants will have up to 6 yearly visits. They will give a urine sample and body measurements, and repeat the X-rays. They will have questions and behavior and thinking tasks. They may give stool samples. Visits will range from 3 to 8 hours. * Participants may choose to participate in other studies: * Stress and Hormones, 1 visit: While resting, participants will give saliva samples and have their heart monitored. Then they will do math. They will repeat the resting part, then do a computer task. * Brain Imaging, 2 visits: Twice, participants will perform tasks with a magnetic cone on their head then answer questions. Once, they will have an MRI, lying still in a scanner with a coil on their head. Before the first visit, participants will collect at-home saliva samples once a day for three days. During both visits, participants will perform tasks and answer questions that gauge their thinking skills and mood. * Experiment 3 (sleep/fatigue): Participants will complete 2 additional visits. During these visits, participants will complete a task on the computer for 2 hours, or watch a movie for two hours. After completion of the task/movie, they will answer questions and be provided with food. Participants will be compensated for the time and inconvenience involved with completing study procedures.
This study aims to disentangle the varying disinhibited eating patterns, or eating behavior endophenotypes, that lead to excessive weight gain and obesity-related comorbidities in youth. Extensive baseline evaluations, including three separate experimental paradigms, and annual follow-up assessments will assist with identifying biopsychosocial mechanisms that appear to increase risk for, and maintain, these eating behaviors and lead to weight gain. Illumination of early risk factors for specific eating behavior endophenotypes and their associated health outcomes will inform the development of targeted interventions for pediatric obesity. Participants for the current study will include 500 healthy obese and non-obese boys and girls (8 to 17yo at baseline) and their parents/caregivers. Youth will first complete two visits in order to ensure study eligibility and to evaluate self-regulatory, motivational, and neurocognitive factors that appear to be salient to the development and maintenance of disinhibited eating behavior, including: psychological distress, sleep behavior, food reinforcement, reward sensitivity, executive functioning, attention bias, and a range of related genetic and physiological factors. Eating behavior will be observed in the laboratory using several validated paradigms. For two weeks, participants will monitor their sleep using wrist actigraphy, as well as record their mood, eating behavior, and eating cognitions using smart phones (via ecological momentary assessment methods). Youth will then be invited to complete up to three separate experimental paradigms designed to further elucidate cognitive, emotional, and physiological processes associated with disinhibited eating behavior. All participants will then complete annual evaluations of weight and adiposity for a total of six years, with more extensive evaluations of self-regulatory, motivational and neurocognitive functioning every three years. Studying children and adolescents longitudinally will allow for examination of the independent and shared risk factors for pediatric disinhibited eating and excess weight. Data from these evaluations will not only be used to test specific hypotheses, but will also be hypothesis-generating in that they will inform the development of additional empirical questions and subsequent experiments. Thus, the current protocol will offer the flexibility to examine potentially critical contributions to weight gain in children as they continue their biopsychosocial development.
Study Type
OBSERVATIONAL
Enrollment
1,500
National Institutes of Health Clinical Center
Bethesda, Maryland, United States
RECRUITINGDifferences in eating behavior of pediatric participants
Multiple outcome measures
Time frame: up to 6 years of follow-up
Experiment 2 (Hormone and Brain Development Study): oscillatory power activity in hypothesized brain regions-of-interest and food intake in the laboratory
Explore whether gonadal hormone concentrations moderate the association between activation in ROIs and LOC-eating in the laboratory. Hyp 3a: The associations among activation in ROIs and LOC-eating severity will be stronger among girls with higher concentrations of estradiol. Hyp 3a: The associations among activation in ROIs and total energy intake will be stronger among girls with higher concentrations of estradiol. Hyp 3c: The associations among activation in ROIs and LOC-eating severity will be stronger among boys with lower concentrations of testosterone. Hyp 3d: The associations among activation in ROIs and total energy intake will be stronger among boys with lower concentrations of testosterone.
Time frame: During palatable (vs non-palatable) food cues attention bias paradigm
Experiment 2 (Hormone and Brain Development Study): oscillatory power activity in hypothesized brain regions-of-interest and food intake in the laboratory
Investigate if model-based decision making mediates the link between activation in ROIs while attending to images of food and LOC-eating in the laboratory. Hyp 2a: Model-based decision making (DM) will mediate the association between activation in all ROIs and severity of LOC-eating. Hyp 2a: Model-based DM will mediate the association between activation in all ROIs and total energy intake.
Time frame: During palatable (vs non-palatable) food cues attention bias paradigm
Experiment 2 (Hormone and Brain Development Study): oscillatory power activity in hypothesized brain regions-of-interest
Examine if activation in neural regions of interest (ROIs; striatum, prefrontal cortex, and hippocampus) while attending to food images is linked to decision making (DM) during a decision-making task. Hyp 1a: Striatum activation will be related to model-free learning. Hyp 1b: Activation in all ROIs will be linked to model-based learning.
Time frame: During palatable (vs non-palatable) food cues attention bias paradigm
Experiment 2 (Hormone and Brain Development Study): oscillatory power activity in hypothesized brain regions-of-interest
Differences in neural activity in youth with- and without Loss of Control Eating. In the model examining the initial attention capture period of the palatable food attention bias paradigm, condition will be coded as high-palatable food, low-palatable food, and neutral non-food trials. In the model examining the sustained attention deployment period of the palatable food attention bias paradigm, the conditions will be coded as high palatable-congruent and -incongruent trials, as well as low palatable-congruent and -incongruent trials.
Time frame: During palatable (vs non-palatable) food cues attention bias paradigm
Experiment 2 (Hormone and Brain Development Study): oscillatory power activity in hypothesized brain regions-of-interest
Differences in neural activity in youth with- and without Loss of Control Eating. In the model examining the initial attention capture period, condition will be coded as angry, happy, and neutral trials. In the model examining the sustained attention deployment period, the conditions will be coded as angry-congruent and -incongruent trials, as well as happy-congruent and -incongruent trials.
Time frame: During social threat attention bias paradigm
Experiment 3 (Sleep/fatigue): fatigue and task resistance
Difference in self-report of fatigue and resistance during the computer task and movie. According to a prior power calculations, the sample size (40 participants) was expected to have 80% power to detect a significant difference between the cognitive fatigue and non-fatigue conditions based on effect sizes from previous studies of adults (Cohen s d=0.8-2.5) \[Faber, Maurits, \& Lorist, 2012; Van der Linden \& Eling, 2006\].Faber LG, Maurits NM, Lorist MM. Mental fatigue affects visual selective attention. PLoS One 2012;7:e48073. doi: 10.1371/journal.pone.0048073Van der Linden D, Eling P. Mental fatigue disturbs local processing more than global processing. Psychol Res 2006;70:395-402.
Time frame: Immediately before and after completion of the computer task and movie (approximately 2hours)
Experiment 3 (Sleep/fatigue): behavioral performance
Reaction time and proportion of correct responses during the fatigue task.
Time frame: During the computer task (~2hours).
Experiment 3 (Sleep/fatigue): energy intake.
Difference in total energy intake (kcals) during the laboratory meals following the computer task and movie.A priori power computations were based on the effect size from a previous laboratory study evaluating energy intake differences between adults randomized to a high or low cognitive reduction condition \[Ward and Mann, 2000\]. To detect a difference in energy intake, using a randomized crossover design with power of 0.9 and a 2-sided significance level of =.05, 88 participants were required.Ward A, Mann T. Don't mind if i do: Disinhibited eating under cognitive load. J Pers Soc Psychol 2000;78:753-63. doi: 10.1037//0022-3514.78.4.753
Time frame: Immediately following completion of the computer task and movie.
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