Clinical trial NCT05456516: Study of Brain, Reward, and Kids' Eating
Official title: Neurocognitive and Behavioral Factors That Promote Resiliency to Pediatric Obesity
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Obesity, Childhood
Eating Behavior
Keywords: reinforcement learning
fNIRS
food-cue reactivity
Lead sponsor: Penn State University
Sponsor class: OTHER
Collaborators: name: National Center for Advancing Translational Sciences (NCATS)
First posted: 2022-07-13
Enrollment: 76
Sex: ALL
Minimum age (years): 8
Maximum age (years): 10
Standard ages: CHILD
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Primary purpose: PREVENTION

Brief summary: Children from rural communities are at greater risk for obesity than children from more urban communities. However, some children are resilient to obesity despite greater exposure to obesogenic influences in rural communities (e.g., fewer community-level physical activity or healthy eating resources). Identifying factors that promote this resiliency could inform obesity prevention. Eating habits are learned through reinforcement (e.g., hedonic, familial environment), the process through which environmental food cues become valued and influence behavior. Therefore, understanding individual differences in reinforcement learning is essential to uncovering the causes of obesity. Preclinical models have identified two reinforcement learning phenotypes that may have translational importance for understanding excess consumption in humans: 1) goal-tracking-environmental cues have predictive value; and 2) sign-tracking-environmental cues have predictive and hedonic value (i.e., incentive salience). Sign-tracking is associated with poorer attentional control, greater impulsivity, and lower prefrontal cortex (PFC) engagement in response to reward cues. This parallels neurocognitive deficits observed in pediatric obesity (i.e., worse impulsivity, lower PFC food cue reactivity). The proposed research aims to determine if reinforcement learning phenotype (i.e., sign- and goal-tracking) is 1) associated with adiposity due to its influence on neural food cue reactivity, 2) associated with reward-driven overconsumption and meal intake due to its influence on eating behaviors; and 3) associated with changes in adiposity over 1 year. The investigators hypothesize that goal-tracking will promote resiliency to obesity due to: 1) reduced attribution of incentive salience and greater PFC engagement to food cues; and 2) reduced reward-driven overconsumption. Finally, the investigators hypothesize reinforcement learning phenotype will be associated due to its influence on eating behaviors associated with overconsumption (e.g., larger bites, faster bite rat and eating sped). To test this hypothesis, the investigators will enroll 76, 8-10-year-old children, half with healthy weight and half with obesity based on Centers for Disease Control definitions. Methods will include computer tasks to assess reinforcement learning, dual x-ray absorptiometry to assess adiposity, and neural food cue reactivity from functional near-infrared spectroscopy (fNIRS).


Eligibility criteria: Child Inclusion Criteria:

* In order to be enrolled, children must be of good health based on parental self-report.
* Have no neurodevelopmental disorder (e.g., attention deficit hyperactivity disorder - ADHD) or learning disabilities (e.g., dyslexia).
* Have no allergies to the foods or ingredients used in the study.
* Not be taking any medications known to influence body weight, taste, food intake, behavior, or blood flow.
* Be 8-10 years-old at enrollment.
* speaks English.

Parent Inclusion Criteria:

* The parent who has the most knowledge of the child's eating behavior, sleep and behavior must be available to attend the visits with their child. This would be decided among the parents.

Exclusion Criteria:

* They are not within the age requirements (\< than 8 years old or \> than 10 years-old at baseline).
* If they are taking cold or allergy medication, or other medications known to influence cognitive function, taste, appetite, or blood flow.
* don't speak English.
* are colorblind.
* has a learning disability, ADHD, language delays, autism or other neurological or psychological conditions.
* has a pre-existing medical condition such as type I or type II diabetes, rheumatoid arthritis, Cushing's syndrome, Down's syndrome, severe lactose intolerance, Prader-Willi syndrome, HIV, cancer, renal failure, or cerebral palsy.
* is allergic to foods or ingredients used in the study.

Parent Exclusion Criteria:

* the parent is unable to attend the study visits

Primary outcomes:
measure: Child body mass index
timeFrame: baseline and 1 year follow-up
measure: Oxy- and deoxyhemoglobin in response to food cues
timeFrame: baseline
measure: Food intake in grams during a standard meal
timeFrame: baseline and 1-year follow-up
measure: Food intake in kcal during a standard meal
timeFrame: baseline and 1-year follow-up
measure: Video coding of standard meal
timeFrame: baseline and 1-year follow-up
measure: Food intake in grams during a snack buffet when not hungry
timeFrame: baseline
measure: Food intake in kcal during a snack buffet when not hungry
timeFrame: baseline
measure: Reward-related decision making during 2-stage reinforcement learning task
timeFrame: baseline
measure: Value modulated attentional capture
timeFrame: baseline
measure: Body Composition
timeFrame: baseline and 1-year follow-up
Secondary outcomes:
measure: Oxy- and deoxyhemoglobin in response to rating food health, taste, and wanting
timeFrame: baseline
measure: Oxy- and deoxyhemoglobin in response to food choice
timeFrame: baseline
measure: Eye-tracking during the value-modulated attentional capture task
timeFrame: baseline
measure: Eye-tracking during the food choice task (during functional near infrared spectroscopy)
timeFrame: baseline
measure: Video coding of snack buffet
timeFrame: baseline
measure: Population density
timeFrame: baseline
measure: Child Pavlovian Instrumental Transfer Task
timeFrame: 1-year follow-up
measure: Oxy- and deoxyhemoglobin in response to consumption of foods
timeFrame: 1-year follow-up
measure: Oxy- and deoxyhemoglobin in response to rating food taste and wanting after consumption
timeFrame: 1-year follow-up.
Other outcomes:
measure: Taste testing to measure liking of foods
timeFrame: baseline and 1-year follow-up
measure: Child fullness
timeFrame: baseline and 1-year follow-up
measure: Physical activity
timeFrame: baseline and 1-year follow-up
measure: Sleep Efficiency
timeFrame: baseline and 1-year follow-up
measure: Children's Anxiety Meter Scale
timeFrame: baseline and 1-year follow-up
measure: Perceived Stress Scale
timeFrame: baseline
measure: Loss of Control Eating Questionnaire
timeFrame: baseline and 1-year follow-up
measure: Demographics
timeFrame: baseline and 1-year follow-up
measure: Child pubertal development assessment
timeFrame: baseline and 1-year follow-up
measure: Child Feeding Questionnaire
timeFrame: baseline and 1-year follow-up
measure: Child Eating Behavior Questionnaire
timeFrame: baseline
measure: Children's Behavior Questionnaire
timeFrame: baseline
measure: Behavior Rating Inventory of Executive Function - 2
timeFrame: baseline
measure: Binge Eating Scale
timeFrame: baseline and 1-year follow-up
measure: Child Sleep Habits Questionnaire
timeFrame: baseline and 1-year follow-up
measure: External Food Cues Responsiveness Scale
timeFrame: baseline and 1-year follow-up
measure: Family Food Behavior Survey
timeFrame: baseline
measure: Sensitivity to Punishment and Reward Questionnaire
timeFrame: baseline
measure: Three Factor Eating Questionnaire
timeFrame: baseline
measure: Parent Weight Loss Behavior Questionnaire
timeFrame: baseline and 1-year follow-up
measure: IQ estimation
timeFrame: baseline
measure: Processing speed and flexibility
timeFrame: baseline
measure: NIH Toolbox - Flanker Test
timeFrame: baseline
measure: NIH Toolbox - List Sorting Test
timeFrame: baseline
measure: NIH Toolbox - Dimensional Card Sorting Test
timeFrame: baseline
measure: Child adiposity
timeFrame: baseline and 1-year follow-up
measure: Parent body mass index
timeFrame: baseline and 1-year follow-up
measure: Home Food Inventory
timeFrame: baseline and 1-year follow-up
measure: Food Frequency Questionnaire
timeFrame: baseline and 1-year follow-up
measure: Home Food Environment
timeFrame: baseline and 1-year follow-up
measure: Structure and Control in Parent Feeding
timeFrame: baseline
measure: Feeding to Manage Child Behavior Questionnaire
timeFrame: baseline
measure: Body Image Scale
timeFrame: 1-year follow-up
measure: Weight Concerns Scale
timeFrame: 1-year follow-up
measure: Stress in Children Questionnaire
timeFrame: baseline and 1-year follow-up
measure: Lifestyle Behavior Checklist
timeFrame: baseline
measure: Dietary metabolites (urine)
timeFrame: baseline and 1-year follow-up
Locations:
city: University Park
country: United States
facility: Chandlee Laboratory
state: Pennsylvania
Study officials:
References:
citation: Pearce AL, Adise S, Roberts NJ, White C, Geier CF, Keller KL. Individual differences in the influence of taste and health impact successful dietary self-control: A mouse tracking food choice study in children. Physiol Behav. 2020 Sep 1;223:112990. doi: 10.1016/j.physbeh.2020.112990. Epub 2020 Jun 4.
citation: Pearce AL, Cevallos MC, Romano O, Daoud E, Keller KL. Child meal microstructure and eating behaviors: A systematic review. Appetite. 2022 Jan 1;168:105752. doi: 10.1016/j.appet.2021.105752. Epub 2021 Oct 16.
citation: Fuchs BA, Roberts NJ, Adise S, Pearce AL, Geier CF, White C, Oravecz Z, Keller KL. Decision-Making Processes Related to Perseveration Are Indirectly Associated With Weight Status in Children Through Laboratory-Assessed Energy Intake. Front Psychol. 2021 Aug 18;12:652595. doi: 10.3389/fpsyg.2021.652595. eCollection 2021.
citation: Rangel A. Regulation of dietary choice by the decision-making circuitry. Nat Neurosci. 2013 Dec;16(12):1717-24. doi: 10.1038/nn.3561. Epub 2013 Nov 22.
citation: van Meer F, Charbonnier L, Smeets PA. Food Decision-Making: Effects of Weight Status and Age. Curr Diab Rep. 2016 Sep;16(9):84. doi: 10.1007/s11892-016-0773-z.
citation: Colaizzi JM, Flagel SB, Joyner MA, Gearhardt AN, Stewart JL, Paulus MP. Mapping sign-tracking and goal-tracking onto human behaviors. Neurosci Biobehav Rev. 2020 Apr;111:84-94. doi: 10.1016/j.neubiorev.2020.01.018. Epub 2020 Jan 20.