Clinical trial NCT05073185: Resilience to the Effects of Advertising in Children
Official title: Characterizing Resilience to Food-cue Induced Overeating in Children
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Obesity, Childhood
Keywords: Obesity
food-cue reactivity
functional magnetic resonance imaging
eating behaviors
food marketing
food advertisement
Lead sponsor: Penn State University
Sponsor class: OTHER
Collaborators: name: University of Kansas Medical Center
name: University of Missouri, Kansas City
name: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
First posted: 2021-10-11
Enrollment: 200
Sex: ALL
Minimum age (years): 7
Maximum age (years): 9
Standard ages: CHILD
Accepts healthy volunteers: yes
Observational model: CASE_CROSSOVER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Parents and children meeting the eligibility criteria living within 40 miles of University Park, Pa.

Brief summary: Strong empirical evidence shows food marketing promotes excess energy intake and obesity. Yet, not all children are susceptible to its effects and this variability is poorly understood. Identifying sources of this variability is a public health priority not only because it may elucidate characteristics of children who are most susceptible, but also because it may highlight novel sources of resiliency to overconsumption. The proposed research will use state-of-the art, data-driven approaches to identify neural, cognitive and behavioral phenotypes associated with resiliency to food-cue (i.e. food advertisement) induced overeating and determine whether these phenotypes protect children from weight gain during the critical pre-adolescent period.

Detailed description: The investigator's central hypothesis is that children who are resistant to food-cue induced overeating will exhibit a distinct cluster of neural, behavioral, and cognitive traits that protect them from weight gain, even in the context of high-familial obesity risk. Identifying these traits is critical to the development of successful, individually tailored obesity prevention programs. This hypothesis is informed by compelling preliminary research showing that children who are less susceptible to food-cue induced eating in the laboratory show decreased neural activation in somatosensory (i.e., post-central gyrus) and reward (i.e., striatum) regions and increased activation in cognitive control regions (i.e., dorsolateral prefrontal cortex-dlPFC) following food commercial exposure.

These results provide a strong foundation for characterizing neural responses that are associated with resiliency to food-cue induced eating, but highlight major gaps in the literature that must be addressed to advance the field. This proposal will make three novel contributions to the understanding of the etiology of obesity. Using a prospective, family-risk design, the investigators will follow 100, 7-9 year-old children who have healthy weight but vary by risk for obesity (based on maternal weight status) for 1 year to characterize neural and behavioral responses to food commercials and identify common neural networks associated with resiliency to food-cue induced overconsumption. Second, the investigators will use sophisticated behavioral coding to characterize children's eating following food commercial exposure at both homeostatic (i.e., meal consumed when hungry) and non-homeostatic (i.e., eating in the absence of hunger - EAH snack buffet) events and relate individual differences in eating behavior to neural phenotypes. Finally, the investigators will follow children over 1 year to determine whether the neural and behavioral responses at baseline are protective against adiposity gains, during a critical period where children are cognizant of the purpose of advertising, but cannot fully defend against its effects.

Baseline data will be collected over 4 weekly initial visits, followed by a 5th visit one year later.

Eligibility criteria: Child Inclusion Criteria:

1. In order to be enrolled, children must be of good health based on parental self-report.
2. Have no learning disabilities (e.g., ADHD).
3. Have no allergies to the foods or ingredients used in the study.
4. Not be claustrophobic.
5. Not be taking any medications known to influence body weight, taste, food intake, behavior, or blood flow.
6. Be 7-9 years-old at enrollment.
7. The child must speak English.

Parent Inclusion Criteria:

1. The parent who has the most knowledge of the child's eating behavior, media access, sleep and behavior must be available to attend the visits with their child. This would be decided among the parents.
2. The biological mother must have a body mass index either between 18.5 - 25 kg/m2 (low-risk group) or greater than or equal to 30 kg/m2 (high-risk group). One parent can report on both parents' BW and height.

Exclusion Criteria:

Children would be excluded if:

1. They are not within the age requirements (\< than 7 years old or \> than 9 years-old at baseline).
2. If they are taking cold or allergy medication, or other medications known to influence cognitive function, taste, appetite, or blood flow.
3. If they don't speak English.
4. If they are colorblind
5. If they report being claustrophobic.
6. if they have a learning disability, ADD/ADHD, language delays, autism or other neurological or psychological conditions.
7. if they have a pre-existing medical condition such as type I or type II diabetes, rheumatoid arthritis, Cushing's syndrome, Down's syndrome, food allergies, severe lactose intolerance, Prader-Willi syndrome, HIV, cancer, renal failure, or cerebral palsy.
8. if they are allergic to foods or ingredients used in the study.
9. if they have tattoos, permanent makeup, dental ware, pacemakers, or metal implants that would preclude safe completion of the MRI.
10. if the child has had an X-ray in the month prior to Visits 1 and 6. If so, they will be scheduled at a later date.

Parent Exclusion Criteria:

1. if the biological mother has a body mass index \< 18.5 kg/m2
2. if the mother is between 25-30 kg/m2.
3. if the parent is unable to attend the study visits
4. if the family reports plans to move away from the area in the next year.

Primary outcomes:
measure: fMRI blood oxygen level dependent (BOLD) response to food commercials
timeFrame: baseline
measure: fMRI blood oxygen level dependent (BOLD) response to toy commercials
timeFrame: baseline
measure: Food intake in grams after no commercial viewing
timeFrame: baseline
measure: Food intake in kcals after no commercial viewing
timeFrame: baseline
measure: Food intake in grams after viewing food commercials
timeFrame: baseline
measure: Food intake in kcals after viewing food commercials
timeFrame: baseline
measure: Food intake in grams after food commercial viewing
timeFrame: 1 year
measure: Food intake in kcals after food commercial viewing
timeFrame: 1 year
measure: Food intake in grams after viewing toy commercials
timeFrame: baseline
measure: Food intake in kcals after viewing toy commercials
timeFrame: baseline
measure: Video recording of meal and EAH snack buffet
timeFrame: baseline
measure: Video recording of meal and EAH snack buffet
timeFrame: 1 year
measure: Change from baseline DXA analysis for total body fat mass of child at 1 year
timeFrame: baseline
measure: fMRI Region of Interest (ROI) response to toy commercials and subsequent views of high and low energy density food pictures.
timeFrame: baseline
measure: fMRI Region of Interest (ROI) response to food commercials and subsequent views of high and low energy density food pictures.
timeFrame: baseline
Secondary outcomes:
measure: Change in Android fat mass as measured by DXA analysis
timeFrame: Baseline and 1 year
measure: Change in Gynoid fat mass as measured by DXA analysis
timeFrame: Baseline and 1 year
measure: Child screen time
timeFrame: Baseline and 1 year
measure: Child's brand awareness
timeFrame: Baseline and 1 year
measure: Change in scores from the NIH Toolbox: Child Cognitive battery-Flanker test
timeFrame: Baseline and 1 year
measure: Change in scores from the NIH Toolbox: Child Cognitive battery-List Sorting Working memory test
timeFrame: Baseline and 1 year
measure: Change in scores from the NIH Toolbox: Child Cognitive battery-Dimensional Change Card Sort Test (DCCS)
timeFrame: Baseline and 1 year
Other outcomes:
measure: Height of child and one parent
timeFrame: Baseline
measure: Weight of child and one parent
timeFrame: Baseline
measure: Height of child and one parent
timeFrame: 1 year
measure: Weight of child and one parent
timeFrame: 1 year
measure: Taste testing to measure liking of foods
timeFrame: Baseline
measure: Taste testing to measure liking of foods
timeFrame: 1 Year
measure: IQ test results
timeFrame: Baseline
measure: IQ test results
timeFrame: 1 year
measure: Freddy Fullness survey
timeFrame: Baseline
measure: Freddy Fullness survey
timeFrame: 1 year
measure: Physical Activity Intensity
timeFrame: Baseline
measure: Sleep Quality and Sleep Quantity
timeFrame: Baseline
measure: Computer game called Stop Signal Task
timeFrame: Baseline
measure: Television and internet use and exposure assessment
timeFrame: Baseline
measure: Television and internet use and exposure assessment
timeFrame: 1 year
measure: Child pubertal development assessment
timeFrame: Baseline
measure: Child pubertal development assessment
timeFrame: 1 year
measure: Parental feeding strategies assessment
timeFrame: Baseline
measure: Child eating behavior assessment
timeFrame: Baseline
measure: Child Eating Assessment
timeFrame: 1 Year
measure: Behavioral avoidance/inhibition assessment
timeFrame: Baseline
measure: Child behavior assessment
timeFrame: Baseline
measure: Child behavior assessment
timeFrame: 1 Year
measure: Assessment of child leisure activities
timeFrame: Baseline
measure: Assessment of child leisure activities
timeFrame: 1 Year
measure: Child sleep assessment
timeFrame: Baseline
measure: Child sleep assessment
timeFrame: 1 Year
measure: External food cue responsiveness assessment
timeFrame: Baseline
measure: Parent Alcohol Use
timeFrame: Baseline
measure: Parent Alcohol Use
timeFrame: 1 year
measure: Behavior Rating Inventory of Executive Function
timeFrame: Baseline
measure: Household Food Security Survey Module
timeFrame: Baseline
measure: Household Food Insecurity Access Scale
timeFrame: Baseline
measure: Community Childhood Hunger ID Project
timeFrame: Baseline
measure: Fulkerson Home Food Inventory
timeFrame: Baseline
measure: Demographics
timeFrame: Baseline
measure: Demographics
timeFrame: 1 Year
measure: Reinforcement Learning
timeFrame: Baseline
measure: Decision Making in Children
timeFrame: Baseline
measure: Personality Traits in Children
timeFrame: Baseline
measure: Stress in Children
timeFrame: Baseline
measure: Loss of Control Eating in Children
timeFrame: Baseline
measure: Perceived Stress Scale
timeFrame: Baseline
measure: Confusion, Hubbub and Order Scale
timeFrame: Baseline
measure: Lifestyle Behavior Checklist
timeFrame: Baseline
measure: Binge Eating Scale
timeFrame: Baseline
measure: Family Food Behavior
timeFrame: Baseline
measure: Sensitivity to Punishment and Reward
timeFrame: Baseline
measure: Parent Weight Loss Behavior
timeFrame: Baseline
measure: Three Factor Eating
timeFrame: Baseline
measure: Parental Strategies to Teach about Advertising
timeFrame: Baseline
measure: Structure and Control in Parent Feeding
timeFrame: Baseline
measure: Comprehensive Feeding Practices
timeFrame: Baseline
measure: Comprehensive Feeding Practices
timeFrame: 1 Year
Locations:
city: University Park
country: United States
facility: The Pennsylvania State University
state: Pennsylvania
Study officials:
affiliation: Penn State University
name: Kathleen L Keller, Ph.D.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Masterson TD, Stein WM, Beidler E, Bermudez M, English LK, Keller KL. Brain response to food brands correlates with increased intake from branded meals in children: an fMRI study. Brain Imaging Behav. 2019 Aug;13(4):1035-1048. doi: 10.1007/s11682-018-9919-8.
citation: Kling SMR, Pearce AL, Reynolds ML, Garavan H, Geier CF, Rolls BJ, Rose EJ, Wilson SJ, Keller KL. Development and Pilot Testing of Standardized Food Images for Studying Eating Behaviors in Children. Front Psychol. 2020 Jul 21;11:1729. doi: 10.3389/fpsyg.2020.01729. eCollection 2020.
citation: Masterson TD, Bermudez MA, Austen M, Lundquist E, Pearce AL, Bruce AS, Keller KL. Food commercials do not affect energy intake in a laboratory meal but do alter brain responses to visual food cues in children. Appetite. 2019 Jan 1;132:154-165. doi: 10.1016/j.appet.2018.10.010. Epub 2018 Oct 9.
citation: English LK, Fearnbach SN, Lasschuijt M, Schlegel A, Anderson K, Harris S, Wilson SJ, Fisher JO, Savage JS, Rolls BJ, Keller KL. Brain regions implicated in inhibitory control and appetite regulation are activated in response to food portion size and energy density in children. Int J Obes (Lond). 2016 Oct;40(10):1515-1522. doi: 10.1038/ijo.2016.126. Epub 2016 Jul 26.
citation: Keller KL, Kuilema LG, Lee N, Yoon J, Mascaro B, Combes AL, Deutsch B, Sorte K, Halford JC. The impact of food branding on children's eating behavior and obesity. Physiol Behav. 2012 Jun 6;106(3):379-86. doi: 10.1016/j.physbeh.2012.03.011. Epub 2012 Mar 16.
citation: Fearnbach SN, English LK, Lasschuijt M, Wilson SJ, Savage JS, Fisher JO, Rolls BJ, Keller KL. Brain response to images of food varying in energy density is associated with body composition in 7- to 10-year-old children: Results of an exploratory study. Physiol Behav. 2016 Aug 1;162:3-9. doi: 10.1016/j.physbeh.2016.03.007. Epub 2016 Mar 10.