- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT01619826
Enhancing Children's Cognitive and Brain Health Through Physical Activity Training (FITKids2) (FITKids2)
July 11, 2017 updated by: University of Illinois at Urbana-Champaign
Enhancing Children's Cognitive and Brain Health Through Physical Activity Training
The objective of this study is to use a randomized controlled design to determine whether cardiorespiratory fitness training improves neurocognitive function and academic performance during preadolescent development.
Study Overview
Status
Completed
Conditions
Intervention / Treatment
Detailed Description
The long term objective of this project is to develop an understanding of lifestyle factors that influence the cognitive and brain health of children while also reducing the sedentary nature of today's youth.
Previous research has found that physical activity interventions can enhance both a variety of aspects of cognition and brain structure and function of children, older adults, and individuals with neurodegenerative disorders such as Parkinson's disease and multiple sclerosis.
More specifically, in previous research with children the researchers have found that higher fit children possess larger hippocampi which in turn are related to better relational memory than their lower fit counterparts.
The researchers have also observed that higher fit children exhibit more efficient executive control as indicated by performance measures and event-related brain potentials.
While intriguing, these cross-sectional data do not enable us to establish causality between physical activity and cognition.
In the current study the researchers substantially extend this previous research by examining the influence of a 9 month randomized controlled afterschool physical activity program on cognition and brain health.
Cognition will be assessed with a battery of tasks and standardized achievement tests both before and after the 9 month intervention in the activity group and a wait list control (who will receive the intervention the following year).
Children will also participate in magnetic resonance imaging (MRI) sessions both before and after the intervention (and at comparable times for the wait list control).
In these sessions the researchers will measure both structural aspects of the brain including regional volumes of gray matter and the integrity of the white matter tracts (through diffusion tensor imaging) and functional aspects of brain function using fMRI activity recorded as the children perform a series of executive control and memory tasks.
The researchers anticipate, based on our cross-sectional studies with children and our previous longitudinal studies with older adults, that the children in the physical activity program will show both larger regional brain volumes, particularly in brain regions that subserve executive control and relational memory, and more efficient brain function, as indexed by task-related and resting state fMRI.
Furthermore, the researchers anticipate that these changes will be accompanied by improvements in memory and executive control processes.
Given recent trends identifying decreased levels of physical activity and health status in preadolescents, the understanding of the potential benefits of physical activity on cognition is of great interest.
It is imperative that factors positively influencing cognitive function of children be examined to maximize health and effective functioning of individuals as they progress through the lifespan.
Study Type
Interventional
Enrollment (Actual)
300
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
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Illinois
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Urbana, Illinois, United States, 61801
- University of Illinois at Urbana-Champaign
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Urbana, Illinois, United States, 61801
- Beckman Institute - Biomedical Imaging Center
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Urbana, Illinois, United States, 61801
- Campus Recreation Center East
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Urbana, Illinois, United States, 61801
- Department of Kinesiology and Community Health
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-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
8 years to 9 years (Child)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Description
Inclusion Criteria:
- Parental/guardian consent
- 8 - 9 years old
- Capable of performing exercise
- Absence of school-identified learning disability
- IQ >= 85
- Tanner Scales score <= 2
- ADHD Rating Scales score >= 85%
- Right hand dominant
- Absence of metal implants
- Not claustrophobic
Exclusion Criteria:
- Non-consent of guardian
- Above or below 8 - 9 years old
- Any physical disability that prohibits exercise
- School-identified learning disability
- IQ < 85
- Tanner Scales score > 2
- ADHD Rating Scale score < 85%
- Left hand dominant
- Presence of metal implants
- Claustrophobic
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Basic Science
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Treatment Group
Participants randomized to the physical activity-based afterschool intervention
|
9-month afterschool program designed to increase physical activity and aerobic fitness.
Participants in this group partake in their regular afterschool activities, without intervention from the study staff.
|
|
Placebo Comparator: Wait List Group
Participants in this group partake in their regular afterschool activities, without intervention from the study staff.
|
9-month afterschool program designed to increase physical activity and aerobic fitness.
Participants in this group partake in their regular afterschool activities, without intervention from the study staff.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
NeuroCognitive Assessment
Time Frame: Change from baseline, 36 - 40 weeks
|
Normed computerized test battery for cognitive testing
|
Change from baseline, 36 - 40 weeks
|
|
Structural Magnetic Resonance Imaging
Time Frame: Change from baseline, 36 - 40 weeks
|
Measures of brain structure
|
Change from baseline, 36 - 40 weeks
|
|
Functional Magnetic Resonance Imaging
Time Frame: Change from baseline, 36 - 40 weeks
|
Measures of brain function
|
Change from baseline, 36 - 40 weeks
|
|
Academic Achievement
Time Frame: Change from baseline, 36 - 40 weeks
|
Scholastic achievement tests of reading comprehension and arithmetic
|
Change from baseline, 36 - 40 weeks
|
|
Eye Tracking
Time Frame: Change from baseline, 36 - 40 weeks
|
Measures of visual gaze
|
Change from baseline, 36 - 40 weeks
|
|
Task Performance
Time Frame: Change from baseline, 36 - 40 weeks
|
Measures of responses speed and accuracy
|
Change from baseline, 36 - 40 weeks
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Event-related Brain Potentials
Time Frame: Change from baseline, 36 - 40 weeks
|
Measures of the neuroelectric system that occur in response to, or in preparation for, a discrete event
|
Change from baseline, 36 - 40 weeks
|
|
DXA Body Mass Assessment
Time Frame: Change from baseline, 36 - 40 weeks
|
Measures of bone density, total body composition, and fat content
|
Change from baseline, 36 - 40 weeks
|
|
Diet and Brain Function
Time Frame: Change from baseline, 36-40 weeks
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Measure of correlation between diet and brain function
|
Change from baseline, 36-40 weeks
|
|
Adiposity
Time Frame: Change from baseline, 36 - 40 weeks
|
Measure of change in adiposity
|
Change from baseline, 36 - 40 weeks
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Collaborators
Investigators
- Principal Investigator: Arthur F Kramer, PhD, University of Illinois at Urbana-Champaign
- Principal Investigator: Charles Hillman, PhD, University of Illinois at Urbana-Champaign
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Liu R, Hannon BA, Robinson KN, Raine LB, Hammond BR, Renzi-Hammond LM, Cohen NJ, Kramer AF, Hillman CH, Teran-Garcia M, Khan NA. Single Nucleotide Polymorphisms in CD36 Are Associated with Macular Pigment among Children. J Nutr. 2021 Sep 4;151(9):2533-2540. doi: 10.1093/jn/nxab153.
- Chojnacki MR, Holscher HD, Balbinot AR, Raine LB, Biggan JR, Walk AM, Kramer AF, Cohen NJ, Hillman CH, Khan NA. Relations between mode of birth delivery and timing of developmental milestones and adiposity in preadolescence: A retrospective study. Early Hum Dev. 2019 Feb;129:52-59. doi: 10.1016/j.earlhumdev.2018.12.021. Epub 2019 Jan 12.
- Chojnacki MR, Raine LB, Drollette ES, Scudder MR, Kramer AF, Hillman CH, Khan NA. The Negative Influence of Adiposity Extends to Intraindividual Variability in Cognitive Control Among Preadolescent Children. Obesity (Silver Spring). 2018 Feb;26(2):405-411. doi: 10.1002/oby.22053. Epub 2017 Dec 27.
- Raine LB, Khan NA, Drollette ES, Pontifex MB, Kramer AF, Hillman CH. Obesity, Visceral Adipose Tissue, and Cognitive Function in Childhood. J Pediatr. 2017 Aug;187:134-140.e3. doi: 10.1016/j.jpeds.2017.05.023. Epub 2017 Jun 13.
- Barnett SM, Khan NA, Walk AM, Raine LB, Moulton C, Cohen NJ, Kramer AF, Hammond BR Jr, Renzi-Hammond L, Hillman CH. Macular pigment optical density is positively associated with academic performance among preadolescent children. Nutr Neurosci. 2018 Nov;21(9):632-640. doi: 10.1080/1028415X.2017.1329976. Epub 2017 May 23.
- Hassevoort KM, Khazoum SE, Walker JA, Barnett SM, Raine LB, Hammond BR, Renzi-Hammond LM, Kramer AF, Khan NA, Hillman CH, Cohen NJ. Macular Carotenoids, Aerobic Fitness, and Central Adiposity Are Associated Differentially with Hippocampal-Dependent Relational Memory in Preadolescent Children. J Pediatr. 2017 Apr;183:108-114.e1. doi: 10.1016/j.jpeds.2017.01.016. Epub 2017 Feb 8.
- Baym CL, Khan NA, Monti JM, Raine LB, Drollette ES, Moore RD, Scudder MR, Kramer AF, Hillman CH, Cohen NJ. Dietary lipids are differentially associated with hippocampal-dependent relational memory in prepubescent children. Am J Clin Nutr. 2014 May;99(5):1026-32. doi: 10.3945/ajcn.113.079624. Epub 2014 Feb 12.
Helpful Links
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start
April 1, 2012
Primary Completion (Actual)
May 1, 2017
Study Completion (Actual)
May 1, 2017
Study Registration Dates
First Submitted
June 12, 2012
First Submitted That Met QC Criteria
June 12, 2012
First Posted (Estimate)
June 14, 2012
Study Record Updates
Last Update Posted (Actual)
July 14, 2017
Last Update Submitted That Met QC Criteria
July 11, 2017
Last Verified
July 1, 2017
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- HD069381
- R01HD069381-01A1 (U.S. NIH Grant/Contract)
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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