The Beneficial Effects of a Protein-rich Breakfast on Appetite Control & Cognition in Overweight and Obese Adolescents

The purpose of this study is to assess whether the daily addition of a protein-rich breakfast leads to beneficial changes in appetite control, food intake regulation,and cognitive function in overweight & obese 'breakfast skipping' young women.

Study Overview

• Status: Completed
• Conditions: Obesity; Overweight
• Intervention / Treatment: Behavioral: Breakfast Skipping; Behavioral: Normal Protein Breakfast Meals; Behavioral: Protein-rich Breakfast Meals

Detailed Description

Breakfast skipping, which is a common, yet unhealthy dietary habit among young women, has been strongly associated with over-eating (especially in the evening), weight gain, and obesity. Breakfast skipping has also been shown to reduce cognitive function in this population. However, it is unclear as to whether the addition of breakfast, with specific emphasis on increased dietary protein, leads to improvements in these outcomes. This study will provide mechanistic evidence supporting the addition of a protein-rich breakfast to improve and/or re-establish appetite control, energy intake regulation, and cognitive function in overweight/obese 'breakfast skipping' young women. 22 overweight and obese 'breakfast skipping' adolescent girls will participate in the following randomized within-subject crossover-design breakfast study. The participants will randomly complete the follow breakfast patterns at home for 6 days: 1) Breakfast Skipping; 2) Consumption of Normal Protein breakfast meals(i.e., 350 kcal; 15% of the meal as protein, 65% CHO, & 20% fat); and 3) Consumption of Protein-Rich breakfast meals (i.e., 350 kcal; 40% of the meal as protein, 40% CHO, & 20% fat). On the 7th day of each pattern, the participants will report to the MU-Brain Imaging Center in the morning to complete the respective 10-h testing day. The participants will begin the testing day by either skipping breakfast or consuming their respective breakfast meal. Blood samples and assessments of perceived appetite, pleasure/reward, and cognitive function will be collected/completed at specific times throughout the day. A standardized lunch will also be provided. Prior to dinner, a brain scan will be completed using functional magnetic resonance imaging (fMRI) to identify brain activation patterns in response to food pictures. Following the fMRI, the participants will be provided with an ad libitum dinner buffet to consume of the facility. They will also be given evening snacks to consume ad libitum, at home throughout the remainder of the day. There is a 7-day washout period between each breakfast pattern. Primary outcomes include morning, mid-day, afternoon, and evening appetite, satiety, pleasure/reward, hormonal responses (plasma glucose, insulin, ghrelin, and PYY concentrations), brain activation patterns, evening energy intake, and daily energy intake.

• Study Type: Interventional
• Enrollment (Actual): 22
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Missouri
    • Columbia, Missouri, United States, 65211
      • University of Missouri

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 15 years to 20 years (ADULT, CHILD)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: Female

Description

Inclusion Criteria:

The participants must meet the following inclusion criteria:

• Female
• Age range 15-20 y
• Overweight to obese (85th -99th percentile for BMI for age; BMI: 25-39.9 kg/m2
• No metabolic, psychological, or neurological diseases/conditions
• Not currently/previously on a weight loss/other special diet
• Frequently eats lunch ( ≥ 5 eating occasions/wk)
• Consistently skips breakfast every week day (i.e., 5 week days/week)
• Right-handed (necessary for the fMRI analyses)

Exclusion Criteria:

The participants will be excluded from participation in the study if they meet the following exclusion criteria:

• Male
• Age >20 y and <15 y
• Under Weight (<5th percentile for BMI for age; BMI: <18 kg/m2)
• Normal Weight (6th-84th percentile for BMI for age; BMI: 18-24.0 kg/m2)
• Morbidly Obese (BMI: >40 kg/m2)
• Clinically diagnosed with diabetes (Type I or Type II), having an eating disorder, or having any other metabolic, psychological, or neurological diseases/conditions that would influence the study outcomes.
• Not currently/previously on a weight loss or other special diet (in the past 6 months)
• Skip lunch ( ≥ 2 eating occasions/wk)
• Consume breakfast (≥ 2 eating occasions/wk)
• Left-handed
• Claustrophobic (≥ 2 past bouts of claustrophobia when exposure to small spaces)
• Do not meet the fMRI criteria established by the MU-BIC (regarding metal implants, etc.)
• Pregnant

Study Plan

How is the study designed?

Design Details

• Primary Purpose: TREATMENT
• Allocation: RANDOMIZED
• Interventional Model: CROSSOVER
• Masking: QUADRUPLE

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
EXPERIMENTAL: Breakfast Skipping; Breakfast skipping serves as the baseline/control arm since the participants habitually skip breakfast (i.e., skip breakfast at least 5 times/week). Thus, during the week prior to and including the testing day, the participants will continue to skip breakfast each morning.	Behavioral: Breakfast Skipping; Participants will continue to skip breakfast each morning.; Other Names: Control
EXPERIMENTAL: Normal Protein Breakfast Meals; For 7 days, the participants will consume normal protein breakfast meals each morning. These meals will consist of cereal-based foods and will be 350 kcal, which is approximately 18% of daily energy intake for overweight and obese adolescents ages 9-18 y. The macronutrient composition of these meals will contain 15% protein (13 g of dietary protein), 65% CHO, and 20% fat.	Behavioral: Normal Protein Breakfast Meals; Participants will consume normal protein breakfast meals each morning.
EXPERIMENTAL: Protein-rich Breakfast Meals; For 7 days, the participants will consume protein-rich breakfast meals each morning. These meals will consist of home-cooked foods and will be 350 kcal, which is approximately 18% of daily energy intake for overweight and obese adolescents ages 9-18 y. The macronutrient composition of these meals will contain 40% protein (35 g of protein), 40% CHO, and 20% fat.	Behavioral: Protein-rich Breakfast Meals; Participants will consume protein-rich breakfast meals each morning.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption	Computerized questionnaires, assessing perceived sensations of hunger and fullness were completed throughout the testing days beginning at baseline and about every 30 minutes for a total of 20 questionnaires (- 15 min, +0 min,+30 min, +60 min, +90 min, +120 min, +150 min, +180 min, +210 min, +240 min, +255 min, +270 min, +285 min, +300 min, +330 min, +360 min, +390 min, +420 min, +450 min, and +480 min). The questions are worded as "how strong is your feeling of" with anchors of "not at all" to "extremely." Each reported score can be a minimum of 0 and a maximum of 100 mm. niAUC was calculated by computing the summation of the average change from baseline score (mm) for each time point and the subsequent time point, multiplied by the difference in time (min) between the two measures. For reported feelings of hunger, a higher score can be interpreted as "feeling more hungry" throughout the day. This can be applied to the three other perceived sensations.	5 weeks
Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY)	The samples were collected in test tubes containing ethylenediaminetetraacetic acid. Protease inhibitors (pefabloc SC and dipeptidyl peptidase) were added to some of the tubes to reduce protein degradation. The plasma was separated and stored in microcentrifuge tubes at -80°C for future analysis. Plasma total ghrelin and peptide YY (PYY) were measured for all time points using the Milliplex multi-analyte profiling magnetic bead-based multi-analyte, metabolic panel, 2-plex assay and Magpix Luminex technologies. AUC was calculated by computing the summation of the average change from baseline score (pg/ml) for each time point and the subsequent time point multiplied by the difference in time (min) between the two time instances for a total of 20 blood samples (- 15 min, +0 min,+30 min, +60 min, +90 min, +120 min, +150 min, +180 min, +210 min, +240 min, +255 min, +270 min, +285 min, +300 min, +330 min, +360 min, +390 min, +420 min, +450 min, and +480 min).	5 weeks
Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans	Participants viewed 3 categories of pictures including food, nonfood (animals), and blurred baseline images. The pictures from each category were presented in blocks of images. Animal pictures were used to control for visual richness and general interest (i.e., appealing but not appetizing). To determine the effects of breakfast/no breakfast on neural activity associated with food motivation, repeated measures ANOVAs were performed on the brain activation maps within the Brain Voyager software with use of stimulus [food (i.e., appetizing and appealing) vs. nonfood (i.e., animal, nonappetizing but appealing]. To identify significant activations in a priori regions, a cluster level statistical threshold was applied to correct for multiple comparisons. By using this approach, significance was set at P = 0.01, with a cluster-level false-positive rate of a = 0.05	5 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Daily Energy Intake	Energy intake during breakfast, lunch, dinner, and evening snacks of each testing day will be measured.	5 weeks

Collaborators and Investigators

• Sponsor: University of Missouri-Columbia
• Collaborators: National Cattlemen's Beef Association; American Egg Board

Publications and helpful links

General Publications

• Leidy HJ, Ortinau LC, Douglas SM, Hoertel HA. Beneficial effects of a higher-protein breakfast on the appetitive, hormonal, and neural signals controlling energy intake regulation in overweight/obese, "breakfast-skipping," late-adolescent girls. Am J Clin Nutr. 2013 Apr;97(4):677-88. doi: 10.3945/ajcn.112.053116. Epub 2013 Feb 27.

Study record dates

Study Major Dates

• Study Start: September 1, 2010
• Primary Completion (ACTUAL): May 1, 2011
• Study Completion (ACTUAL): August 1, 2011

Study Registration Dates

• First Submitted: August 27, 2010
• First Submitted That Met QC Criteria: August 30, 2010
• First Posted (ESTIMATE): August 31, 2010

Study Record Updates

• Last Update Posted (ACTUAL): April 3, 2020
• Last Update Submitted That Met QC Criteria: March 23, 2020
• Last Verified: March 1, 2020

More Information

Terms related to this study

• Keywords: Adolescents; Obesity; fMRI; PYY; Ghrelin; Breakfast; Protein-rich breakfast; Breakfast Skipping; Increased dietary protein
• Additional Relevant MeSH Terms: Body Weight; Overweight
• Other Study ID Numbers: 1173258

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO