RO1: Brain Mechanisms of Overeating in Children
Study Details
Study Description
Brief Summary
The proposed research will follow healthy weight children who vary by family risk for obesity to identify the neurobiological and appetitive traits that are implicated in overeating and weight gain during the critical pre-adolescent period. The investigator's central hypothesis is that increased intake from large portions of energy dense foods is due in part to reduced activity in brain regions implicated in inhibitory control and decision making, combined with increased activity in reward processing pathways. To test this hypothesis, the investigators will recruit 120 healthy weight children, aged 7-8 years, at two levels of obesity risk (i.e., 60 high-risk and 60 low-risk) based on parent weight status. This will result in 240 participants: 120 children and their parents.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
In aim one, the investigators will use functional magnetic resonance imaging to characterize the brain regions which are activated in response to food portion size and compare these regions between high- and low-risk children.
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.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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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. |
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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. |
Outcome Measures
Primary Outcome Measures
- Brain Responses to Portion Size [baseline]
The investigators will use functional magnetic resonance imaging to characterize the brain regions which are activated in response to food portion size and compare these regions between high- and low-risk children.
- Food Intake Relationship to Portion Size [baseline]
The investigators will determine the relationship between brain response to visual portion size cues and measured food intake when portions are increased in laboratory meals.
- The Change in DXA analysis of child adiposity after 1 year [From baseline visit to 1 year later]
The investigators will 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). Body weight (kg) and Height (m) will be aggregated to report BMI in kg/m^2.
Secondary Outcome Measures
- Brain Response Relationships [baseline]
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).
- Inhibitory control assessed by a Stop Signal test [baseline]
An additional endpoint includes the relationship between child behavioral and brain response to food portion size and Inhibitory control assessed by a Stop Signal test.
- Reward-related design [baseline and 1 year later]
Reward-related design making assessed by a computer task.
- Working memory [baseline and 1 year later]
Working memory assessed by an N-back task.
- Meal microstructure [baseline and 1 year later]
Meal microstructure assessed by observational meal coding.
- Eating in the absence of hunger [baseline and 1 year later]
Assessing child eating in the absence of hunger by buffet meal intake.
Other Outcome Measures
- Physical Activity [baseline]
An additional endpoint include the relationship between child behavioral and brain response to food portion size and physical activity assessed by accelerometry.
- Loss of control eating [baseline]
An additional endpoint include the relationship between child behavioral and brain response to food portion size and Loss of control eating.
- Parent-described eating behaviors [baseline]
An additional endpoint includes the relationship between child behavioral and brain response to food portion size and Parent-described eating behaviors.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Child is in good health based on parental self-report
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Child has no learning disabilities (e.g., ADHD)
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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)
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Child is not on any medications known to influence body weight, taste, food intake, behavior, or blood flow
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Child is not claustrophobic
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Child is between the ages of 7-8 years-old at enrollment
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Child's immediate family members have not been diagnosed with a psychological disorder, including depression, anxiety, schizophrenia, etc.
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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)
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Child's parent participating in study must be available to attend visits with child
Exclusion Criteria:
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Child is not in good health based on parent self-report
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Child has any learning disabilities (e.g., ADHD)
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Child has any psychological or medical conditions/devices that may impact comfort in the fMRI (e.g., anxiety, insulin pump)
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Child is taking any medications known to influence body weight, taste, food intake, behavior, or blood flow
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Child is claustrophobic
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Child is less than 7 or greater than 8 years-old at enrollment
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Child has any immediate family members diagnosed with a psychological disorder, including depression, anxiety, schizophrenia, etc.
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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)
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Child's parent participating in study is not available to attend visits with child
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Child is blue/green colorblind
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Child is not fluent in the English language
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | The Pennsylvania State University | University Park | Pennsylvania | United States | 16802 |
Sponsors and Collaborators
- Penn State University
Investigators
- Principal Investigator: Kathleen L Keller, Ph.D., Penn State University
Study Documents (Full-Text)
None provided.More Information
Additional Information:
- Dr. Kathleen Keller's current research
- Dr. Barbara Rolls' current research
- Dr. Charles Grier's current research
- Dr. Stephen Wilson's current research
- Dr. Emma Rose's current research
Publications
- 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. Review.
- 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. Review.
- 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. Review.
- 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.
- Tanner, J.M. (1962). Growth at adolescence.(Oxford: Blackwell Scientific Publications).
- 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.
- RO1 Study