Resilience to the Effects of Advertising in Children

NCT05073185 | Recruiting

• 2 other identifiers: Project REACHR01DK126050
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 1

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.

Conditions

Obesity, Childhood

Keywords

Obesity; food-cue reactivity; functional magnetic resonance imaging; eating behaviors; food marketing; food advertisement

Outcome Measures

Primary Outcomes (15)

• fMRI blood oxygen level dependent (BOLD) response to food commercials

  Whole-brain response to food commercials, followed by images of high and low energy density foods in a fMRI scan

  baseline

• fMRI blood oxygen level dependent (BOLD) response to toy commercials

  Whole-brain response to toy commercials, followed by images of high and low energy density foods in a fMRI scan

  baseline

• Food intake in grams after no commercial viewing

  Intake in grams from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  baseline

• Food intake in kcals after no commercial viewing

  Intake in kcals from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  baseline

• Food intake in grams after viewing food commercials

  Intake in grams from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  baseline

• Food intake in kcals after viewing food commercials

  Intake in kcals from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  baseline

• Food intake in grams after food commercial viewing

  Intake in grams from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  1 year

• Food intake in kcals after food commercial viewing

  Intake in kcals from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  1 year

• Food intake in grams after viewing toy commercials

  Intake in grams from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  baseline

• Food intake in kcals after viewing toy commercials

  Intake in kcals from an eating in the absence of hunger paradigm consumed following advertisement exposure when children are not hungry (i.e., non-homeostatic intake)

  baseline

• Video recording of meal and EAH snack buffet

  A digital recording of the Child eating the Test Meal and the EAH snack buffet will be saved. We have developed a behavior coding technique to count specific behaviors while the child eats. We will also be transcribing the audio.

  baseline

• Video recording of meal and EAH snack buffet

  A digital recording of the Child eating the Test Meal and the EAH snack buffet will be saved. We have developed a behavior coding technique to count specific behaviors while the child eats. We will also be transcribing the audio.

  1 year

• Change from baseline DXA analysis for total body fat mass of child at 1 year

  Examine change in children's fat mass index = total fat mass(kg) / height (m2)

  baseline

• fMRI Region of Interest (ROI) response to toy commercials and subsequent views of high and low energy density food pictures.

  We will examine the strength of the neural connections between reward/somatosensory and cognitive control regions.

  baseline

• fMRI Region of Interest (ROI) response to food commercials and subsequent views of high and low energy density food pictures.

  We will examine the strength of the neural connections between reward/somatosensory and cognitive control regions.

  baseline

Secondary Outcomes (7)

• Change in Android fat mass as measured by DXA analysis

  Baseline and 1 year

• Change in Gynoid fat mass as measured by DXA analysis

  Baseline and 1 year

• Child screen time

  Baseline and 1 year

• Child's brand awareness

  Baseline and 1 year

• Change in scores from the NIH Toolbox: Child Cognitive battery-Flanker test

  Baseline and 1 year

Other Outcomes (54)

• Height of child and one parent

  Baseline

• Weight of child and one parent

  Baseline

• Height of child and one parent

  1 year

Study Arms (1)

Children with healthy weight status

100 child-parent dyads (200 total) will be followed for 1 year to determine the behavioral and neural impact of food and toy advertising exposure. Children will be 7-9 years old, with body mass index \< 85th % for age and sex, and either with a mother who has BMI of 30 kg/m-sq or over or a BMI of 25 kg/m-sq or less.

Eligibility Criteria

• Age: 7 Years - 9 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)
• Sampling Method: Non-Probability Sample

Study Population

Parents and children meeting the eligibility criteria living within 40 miles of University Park, Pa.

You may qualify if:

• 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.
• 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.

You may not qualify if:

• 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.
• 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.

Sponsors & Collaborators

• Penn State University: lead
• University of Kansas Medical Center: collaborator
• University of Missouri, Kansas City: collaborator
• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): collaborator

Study Sites (1)

The Pennsylvania State University

University Park, Pennsylvania, 16802, United States

RECRUITING

Related Publications (6)

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

MeSH Terms

Conditions

Pediatric Obesity; Obesity; Feeding Behavior

Condition Hierarchy (Ancestors)

Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Behavior, Animal; Behavior

Study Officials

• Kathleen L Keller, Ph.D.

  Penn State University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Kyle M Hallisky, B.S.

CONTACT

814-865-5169; kmh6587@psu.edu

Terri L Cravener, MS

CONTACT

814-863-9841; eil@psu.edu

Study Design

• Study Type: observational
• Observational Model: CASE CROSSOVER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: August 4, 2021
• First Posted: October 11, 2021
• Study Start: May 1, 2022
• Primary Completion: July 1, 2025
• Study Completion (Estimated): July 1, 2026
• Last Updated: May 14, 2024

Record last verified: 2024-05

Locations

US (1)