Does Increased Egg Consumption Have Cognitive and Neural Benefits in Food Insecure, At-risk Adolescents?
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Adolescents With Food Insecurity
- Sponsor
- Texas Tech University
- Enrollment
- 18
- Locations
- 2
- Primary Endpoint
- Comparison of functional activity during Eriksen-Flanker Task
- Status
- Completed
- Last Updated
- 4 years ago
Overview
Brief Summary
Quality nutrient intake is essential for proper development and well-being of children in all aspects of health, including cognitive development. Eggs are of particular interest based on potential cognitive and neurological benefits due in part to significant concentrations of choline and lutein. While overall, choline and lutein have received considerable attention in the literature in relation to cognition and brain function, most studies involving intake in young adults have had short intervention periods ranging from 90 minutes to 3 days. Food insecurity has been associated with decreased academic performance. Given that populations with food insecurity have limited resources to direct towards nutrition, identifying how a widely available, highly versatile and largely affordable source of nutrients (i.e. eggs) may have favorable impacts on cognitive function and brain function will be valuable in informing public health recommendations in this at-risk population. As such the investigators will examine whether an increased egg consumption dietary prescription can have positive effects on functional activity (i.e. fMRI) during an Eriksen-Flanker task, anatomical changes in the brain (i.e. DTI, MRI), and cognitive abilities as measured by the Stop Signal Reaction Time task, Operation Span task, Raven's Progressive Matrices and the Boston Naming Task.
Investigators
Martin Binks
Associate Professor
Texas Tech University
Eligibility Criteria
Inclusion Criteria
- •Age: 13-19 years.
- •Household has food security status of low or very low as designated by scoring 2-6 raw score using the U.S. Household Food Security Survey Module: Six-Item Short Form.
Exclusion Criteria
- •Participants unable or unwilling to provide informed consent.
- •Participants with motor, visual or hearing impairment.
- •Participants with current severe psychiatric illnesses (e.g. psychosis, schizophrenia, bipolar disorders, depression)
- •Participants with history of psychiatric hospitalization.
- •Participants with habitual egg consumption (past 3 months) of 4 eggs per week or more
- •Unable or unwilling to consume required study meals for any reason (e.g. dietary restrictions, allergies, or aversions to any of the food items used in the study).
- •History of liver or kidney disease, cardiovascular disease, hematologic disease, metabolic disease, Epilepsy (or other seizure disorder) or malignant tumor
- •Currently taking (or have taken in the past 4 weeks) any anti-anxiolytic, anti-epileptic, or anti-depression medications
- •Currently taking (or have taken in the past 4 weeks) any proton pump inhibitor medications
- •History of any cognitive disorder, medical and/or psychological conditions and/or medications affecting cognition
Outcomes
Primary Outcomes
Comparison of functional activity during Eriksen-Flanker Task
Time Frame: Baseline (pre-intervention) and 12 weeks (post-intervention)
Changes in regional brain activation during an fMRI scan.
Comparison of grey matter anatomical change
Time Frame: Baseline (pre-intervention) and 12 weeks (post-intervention)
Grey density as measured by MRI
Comparison of white matter connectivity change
Time Frame: Baseline (pre-intervention) and 12 weeks (post-intervention)
White matter connectivity as measured by diffusion tensor imaging
Comparison of cognitive battery performance change
Time Frame: Baseline (pre-intervention) and 12 weeks (post-intervention)
Cognitive performance as measured by Boston Naming Task
Comparison of Eriksen-Flanker Task performance change
Time Frame: Baseline (pre-intervention) and 12 weeks (post-intervention)
Eriksen-Flanker task performance compared using the drift diffusion model