Obesity, ChildhoodREACHNCT05073185
Resilience to the Effects of Advertising in Children
An observational study of Obesity, Childhood, run by Penn State University at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 7 to 9 yearsHealthy volunteers can take part
- Conditions the study is for
- Obesity, Childhood
- How many people
- 209 participants
- Where
- 1 siteUnited States
- Study dates
- 1 May 2022to 30 Jul 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 7 to 9 years
- All sexes
- Healthy volunteers accepted
- Child
Study population: Parents and children meeting the eligibility criteria living within 40 miles of University Park, Pa.
Who may be able to join
None listed.
Who cannot join
- 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.
Show all 16Show fewer
- 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.
Trial locations and contacts
1 site in 1 country.
United States1 site
The Pennsylvania State University
University Park, Pennsylvania, 16802
About this study
Official title: Characterizing Resilience to Food-cue Induced Overeating in Children
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.
Read the 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.
- Conditions
- Obesity, Childhood
- Keywords
- Obesity, food-cue reactivity, functional magnetic resonance imaging, eating behaviors, food marketing, food advertisement
- Medical subject headings
- Pediatric Obesity, Obesity, Feeding Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 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
Measured: 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)
Measured: 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)
Measured: 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)
Measured: 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)
Measured: 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)
Measured: 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)
Measured: 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)
Measured: 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)
Measured: 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.
Measured: 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.
Measured: 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)
Measured: 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.
Measured: 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.
Measured: baseline
Secondary outcomes (7)
Change in Android fat mass as measured by DXA analysis
Android fat mass (%) = (Android fat mass (kg) / total fat mass (kg))*100
Measured: Baseline and 1 year
Change in Gynoid fat mass as measured by DXA analysis
Gynoid fat mass (%) = (Gynoid fat mass (kg) / total fat mass (kg))*100
Measured: Baseline and 1 year
Child screen time
Child questionnaire quantifying the number of hours per day a child is exposed to different types of media.
Measured: Baseline and 1 year
Child's brand awareness
Child's brand awareness assessed by a child computerized task. Children are asked to match pictures of products and brand logos. No scaling is used.
Measured: Baseline and 1 year
Change in scores from the NIH Toolbox: Child Cognitive battery-Flanker test
The Flanker is a measure of executive function, specifically tapping inhibitory control and attention. Scoring is based on a combination of accuracy and reaction time. A 2-vector scoring method is employed that uses accuracy and reaction time, where each of these "vectors" ranges in value between 0 and 5, and the computed score, combining each vector score, ranges in value from 0-10. For any given individual, accuracy is considered first. If accuracy levels for the participant are less than or equal to 80%, the final "total" computed score is equal to the accuracy score. If accuracy levels for the participant reach more than 80%, the reaction time score and accuracy score are combined. Higher scores indicate higher levels of ability to attend to relevant stimuli and inhibit attention from irrelevant stimuli.
Measured: Baseline and 1 year
Change in scores from the NIH Toolbox: Child Cognitive battery-List Sorting Working memory test
The List Sorting Working memory test assesses working memory. The List Sorting test requires immediate recall and sequencing of different visually and orally presented stimuli (i.e., "working memory"). Pictures of different foods and animals are displayed with accompanying audio recording and written text (e.g., "elephant"), and the participant is asked to say the items back in size order from smallest to largest, first within a single dimension (either animals or foods, called 1-List) and then on two dimensions (foods, then animals, called 2-List). The test takes approximately seven minutes to administer. List Sorting is scored by summing the total number of items correctly recalled and sequenced on 1-List and 2-List, which can range from 0-26.Higher scores on each of these indicate higher levels of working memory within the normative standard being applied.
Measured: Baseline and 1 year
Change in scores from the NIH Toolbox: Child Cognitive battery-Dimensional Change Card Sort Test (DCCS)
The Dimensional Change Card Sort Test is used to measure cognitive flexibility. Two target pictures are presented that vary along two dimensions (e.g., shape and color). Scoring is based on a combination of accuracy and reaction time. A 2-vector scoring method is employed that uses accuracy and reaction time, scores ranging from 0-10. For any given individual, accuracy is considered first. If accuracy levels for the participant are less than or equal to 80%, the final "total" computed score is equal to the accuracy score. If accuracy levels for the participant reach more than 80%, the reaction time score and accuracy score are combined. Higher scores indicate higher levels of cognitive flexibility.
Measured: Baseline and 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Oct 2021
- Study start1 May 2022
- Primary completion30 Jul 2026
- Study completion30 Jul 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Obesity, ChildhoodStudies of the same condition, open and under way.
- More trials run by Penn State UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case crossover
- Time perspective
- Prospective
- Enrolment
- 209 participants (actual)
Sponsor and investigators
- Lead sponsor
- Penn State University
- Sponsor type
- University, hospital or other
- Collaborators
- University of Kansas Medical Center, University of Missouri, Kansas City, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Responsible party
- Principal investigator, Kathleen Loralee Keller, Penn State University
- Investigators
- Kathleen L Keller, Ph.D., Principal investigator, Penn State University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05073185
- Sponsor's protocol ID
- Project REACH
- Other IDs
- R01DK126050
- Acronym
- REACH
- Status last verified
- Aug 2026
- First submitted
- 4 Aug 2021
- Last updated
- 26 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
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.
PubMed 29971684Kling 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.
PubMed 32793062Masterson 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.
PubMed 30312738English 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.
PubMed 27457416Keller 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.
PubMed 22450261Fearnbach 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.
PubMed 26973134
Study at a glance
From the registry record, last updated by the sponsor on 26 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Characterizing Resilience to Food-cue Induced Overeating in Children
- ClinicalTrials.gov ID
- NCT05073185
- Acronym / sponsor ID
- REACH / Project REACH
- Conditions
- Obesity, Childhood
- Keywords
- Obesity, food-cue reactivity, functional magnetic resonance imaging, eating behaviors, food marketing, food advertisement
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 209 participants (actual)
- Lead sponsor
- Penn State UniversityUniversity, hospital or other
- Collaborators
- University of Kansas Medical Center, University of Missouri, Kansas City, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Study start
- 1 May 2022 (actual)
- Primary completion
- 30 Jul 2026 (actual)
- Study completion
- 30 Jul 2026 (actual)
- First posted
- 11 Oct 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Case crossover
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 7 to 9 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child
- Study population
- Parents and children meeting the eligibility criteria living within 40 miles of University Park, Pa.
Key inclusion criteria (0 listed)
Key exclusion criteria (16 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
fMRI blood oxygen level dependent (BOLD) response to food commercials
Time frame: baseline
Whole-brain response to food commercials, followed by images of high and low energy density foods in a fMRI scan
fMRI blood oxygen level dependent (BOLD) response to toy commercials
Time frame: baseline
Whole-brain response to toy commercials, followed by images of high and low energy density foods in a fMRI scan
Food intake in grams after no commercial viewing
Time frame: baseline
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)
Food intake in kcals after no commercial viewing
Time frame: baseline
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)
Food intake in grams after viewing food commercials
Time frame: baseline
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)
Food intake in kcals after viewing food commercials
Time frame: baseline
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)
Food intake in grams after food commercial viewing
Time frame: 1 year
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)
Food intake in kcals after food commercial viewing
Time frame: 1 year
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)
Food intake in grams after viewing toy commercials
Time frame: baseline
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)
Food intake in kcals after viewing toy commercials
Time frame: baseline
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)
Video recording of meal and EAH snack buffet
Time frame: baseline
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.
Video recording of meal and EAH snack buffet
Time frame: 1 year
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.
Change from baseline DXA analysis for total body fat mass of child at 1 year
Time frame: baseline
Examine change in children's fat mass index = total fat mass(kg) / height (m2)
fMRI Region of Interest (ROI) response to toy commercials and subsequent views of high and low energy density food pictures.
Time frame: baseline
We will examine the strength of the neural connections between reward/somatosensory and cognitive control regions.
fMRI Region of Interest (ROI) response to food commercials and subsequent views of high and low energy density food pictures.
Time frame: baseline
We will examine the strength of the neural connections between reward/somatosensory and cognitive control regions.
7 secondary outcomes
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
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Aug 2026.
- Background: PubMed 29971684Masterson 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.
- Background: PubMed 32793062Kling 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.
- Background: PubMed 30312738Masterson 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.
- Background: PubMed 27457416English 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.
- Background: PubMed 22450261Keller 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.
- Background: PubMed 26973134Fearnbach 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Kathleen L Keller, Ph.D. principal investigator
Penn State University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Obesity, Childhood, run by Penn State University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 0 inclusion and 16 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
fMRI blood oxygen level dependent (BOLD) response to food commercials (time frame: baseline). The study lists 15 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05073185, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Aug 2026.