Resilience to the Effects of Advertising in Children

Official title

Characterizing Resilience to Food-cue Induced Overeating in Children

Overview

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.

Primary outcome measures

• fMRI blood oxygen level dependent (BOLD) response to food commercials [Time frame: baseline]
• fMRI blood oxygen level dependent (BOLD) response to toy commercials [Time frame: baseline]
• Food intake in grams after no commercial viewing [Time frame: baseline]
• Food intake in kcals after no commercial viewing [Time frame: baseline]
• Food intake in grams after viewing food commercials [Time frame: baseline]
• Food intake in kcals after viewing food commercials [Time frame: baseline]
• Food intake in grams after food commercial viewing [Time frame: 1 year]
• Food intake in kcals after food commercial viewing [Time frame: 1 year]
• Food intake in grams after viewing toy commercials [Time frame: baseline]
• Food intake in kcals after viewing toy commercials [Time frame: baseline]

Secondary outcome measures (7)

• Change in Android fat mass as measured by DXA analysis [Time frame: Baseline and 1 year]
• Change in Gynoid fat mass as measured by DXA analysis [Time frame: Baseline and 1 year]
• Child screen time [Time frame: Baseline and 1 year]
• Child's brand awareness [Time frame: Baseline and 1 year]
• Change in scores from the NIH Toolbox: Child Cognitive battery-Flanker test [Time frame: Baseline and 1 year]
• Change in scores from the NIH Toolbox: Child Cognitive battery-List Sorting Working memory test [Time frame: Baseline and 1 year]
• Change in scores from the NIH Toolbox: Child Cognitive battery-Dimensional Change Card Sort Test (DCCS) [Time frame: Baseline and 1 year]

Eligibility criteria

Child Inclusion Criteria:

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

Parent Inclusion Criteria:

• 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.
• 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:

• They are not within the age requirements (< than 7 years old or > than 9 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.
• If they don't speak English.
• If they are colorblind
• If they report being claustrophobic.
• if they have a learning disability, ADD/ADHD, language delays, autism or other neurological or psychological conditions.
• 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.
• if they are allergic to foods or ingredients used in the study.
• if they have tattoos, permanent makeup, dental ware, pacemakers, or metal implants that would preclude safe completion of the MRI.
• 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:

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Case-crossover

Study locations

United States · 1 center

• The Pennsylvania State University — University Park

Publications

• 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. PMID 29971684
• 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. PMID 32793062
• 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. PMID 30312738
• 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. PMID 27457416
• 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. PMID 22450261
• 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. PMID 26973134

Identifiers

NCT: NCT05073185 · Project REACH · R01DK126050

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗