Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
254 participants
OBSERVATIONAL
2018-01-31
2023-06-20
Brief Summary
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Detailed Description
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Second, the investigators will determine the relationship between brain response to visual portion size cues and measured food intake when portions are increased in the laboratory.
Third, the investigators will determine the relationship between brain response to large portions and other validated measures of overeating, including satiety responsiveness and the amount of calories children consumed from high calorie snacks when they are not hungry (i.e., eating in the absence of hunger).
Fourth, the investigators will conduct follow-up visits one year after baseline to determine the extent to which baseline brain and behavioral responses to portion size predict gains in adiposity assessed by anthropometrics (body weight, height, and dual-energy x-ray absorptiometry).
Secondary study endpoints include the relationship between child behavioral and brain response to food portion size and physical activity assessed by accelerometry and questionnaires, inhibitory control assessed by a stop signal test, reward-related design making assessed by a computer task, working memory assessed by an N-back task loss of control eating, child sleep, child working memory, child meal microstructure assessed by observational meal coding, parent rated eating behaviors, and parental feeding practices.
Conditions
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Study Design
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OTHER
PROSPECTIVE
Study Groups
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Low-risk of obesity
Children whose biological mother and biological father have a body mass index between 18.5 - 25 kg/m2.
No interventions assigned to this group
High-risk of obesity
Children whose biological mother has a body mass index greater than or equal to 30 kg/m2 and whose biological father have a body mass index greater than or equal to 25 kg/m2.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Child has no learning disabilities (e.g., ADHD)
* Child has no diagnosed psychological or medical conditions/devices, or metal in/on the body that may impact comfort or safety in the fMRI (e.g., anxiety, insulin pump)
* Child is not on any medications known to influence body weight, taste, food intake, behavior, or blood flow
* Child is not claustrophobic
* Child is between the ages of 7-8 years-old at enrollment
* Child's immediate family members have not been diagnosed with a psychological disorder, including depression, anxiety, schizophrenia, etc.
* Child's biological mother and biological father have a body mass index either between 18.5 - 25 kg/m2 (low-risk group) or biological mother has a body mass index greater than or equal to 30 kg/m2 and biological father has a body mass index greater than or equal to 25 kg/m2 (high-risk group)
* Child's parent participating in study must be available to attend visits with child
Exclusion Criteria
* Child has any learning disabilities (e.g., ADHD)
* Child has any psychological or medical conditions/devices that may impact comfort in the fMRI (e.g., anxiety, insulin pump)
* Child is taking any medications known to influence body weight, taste, food intake, behavior, or blood flow
* Child is claustrophobic
* Child is less than 7 or greater than 8 years-old at enrollment
* Child has any immediate family members diagnosed with a psychological disorder, including depression, anxiety, schizophrenia, etc.
* Child's biological mother or biological father's body mass index do not fit into the parameters for either group (both biological parents \< 18.5 for low-risk group or biological mother is \< 30 and biological father is \< 25 for high-risk group)
* Child's parent participating in study is not available to attend visits with child
* Child is blue/green colorblind
* Child is not fluent in the English language
7 Years
8 Years
ALL
Yes
Sponsors
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Penn State University
OTHER
Responsible Party
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Kathleen Loralee Keller
Director
Principal Investigators
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Kathleen L Keller, Ph.D.
Role: PRINCIPAL_INVESTIGATOR
Penn State University
Locations
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The Pennsylvania State University
University Park, Pennsylvania, United States
Countries
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References
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Burger KS, Stice E. Variability in reward responsivity and obesity: evidence from brain imaging studies. Curr Drug Abuse Rev. 2011 Sep;4(3):182-9. doi: 10.2174/1874473711104030182.
Bruce AS, Martin LE, Savage CR. Neural correlates of pediatric obesity. Prev Med. 2011 Jun;52 Suppl 1:S29-35. doi: 10.1016/j.ypmed.2011.01.018. Epub 2011 Feb 1.
De Silva A, Salem V, Matthews PM, Dhillo WS. The use of functional MRI to study appetite control in the CNS. Exp Diabetes Res. 2012;2012:764017. doi: 10.1155/2012/764017. Epub 2012 May 8.
French SA, Mitchell NR, Wolfson J, Harnack LJ, Jeffery RW, Gerlach AF, Blundell JE, Pentel PR. Portion size effects on weight gain in a free living setting. Obesity (Silver Spring). 2014 Jun;22(6):1400-5. doi: 10.1002/oby.20720. Epub 2014 Feb 19.
Grammer JK, Carrasco M, Gehring WJ, Morrison FJ. Age-related changes in error processing in young children: a school-based investigation. Dev Cogn Neurosci. 2014 Jul;9:93-105. doi: 10.1016/j.dcn.2014.02.001. Epub 2014 Feb 11.
Morrell, J. (1999). The Infant Sleep Questionnaire: A new tool to assess infant sleep problems for clinical and research purposes. Child Psychology and Psychiatry Review 4, 20-26.
Tetley A, Brunstrom J, Griffiths P. Individual differences in food-cue reactivity. The role of BMI and everyday portion-size selections. Appetite. 2009 Jun;52(3):614-620. doi: 10.1016/j.appet.2009.02.005. Epub 2009 Feb 25.
Tanner, J.M. (1962). Growth at adolescence.(Oxford: Blackwell Scientific Publications).
Bhat YR, Keller KL, Brick TR, Pearce AL. ByteTrack: a deep learning approach for bite count and bite rate detection using meal videos in children. Front Nutr. 2025 Oct 3;12:1610363. doi: 10.3389/fnut.2025.1610363. eCollection 2025.
Bhat YR, Rolls BJ, Wilson SJ, Rose E, Geier CF, Fuchs B, Garavan H, Keller KL. Eating in the Absence of Hunger Is a Stable Predictor of Adiposity Gains in Middle Childhood. J Nutr. 2024 Dec;154(12):3726-3739. doi: 10.1016/j.tjnut.2024.10.008. Epub 2024 Oct 10.
Keller KL, Pearce AL, Fuchs B, Rolls BJ, Wilson SJ, Geier CF, Rose E, Garavan H. PACE: a Novel Eating Behavior Phenotype to Assess Risk for Obesity in Middle Childhood. J Nutr. 2024 Jul;154(7):2176-2187. doi: 10.1016/j.tjnut.2024.05.019. Epub 2024 May 23.
Neuwald NV, Pearce AL, Cunningham PM, Koczwara L, Setzenfand MN, Rolls BJ, Keller KL. Switching between foods is reliably associated with intake across eating events in children. Appetite. 2024 Jun 1;197:107325. doi: 10.1016/j.appet.2024.107325. Epub 2024 Mar 26.
Related Links
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Dr. Kathleen Keller's current research
Dr. Barbara Rolls' current research
Dr. Stephen Wilson's current research
Other Identifiers
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RO1 Study
Identifier Type: -
Identifier Source: org_study_id
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