Overweight, Obesity
Conditions
Keywords
Protein-rich breakfast, Breakfast Skipping, Adolescents, Obesity, Increased dietary protein, Breakfast, fMRI, Ghrelin, PYY
Brief summary
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.
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.
Interventions
BEHAVIORALBreakfast Skipping
Participants will continue to skip breakfast each morning.
BEHAVIORALNormal Protein Breakfast Meals
Participants will consume normal protein breakfast meals each morning.
BEHAVIORALProtein-rich Breakfast Meals
Participants will consume protein-rich breakfast meals each morning.
Sponsors
American Egg Board
National Cattlemen's Beef Association, a contractor to the Beef Checkoff
University of Missouri-Columbia
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
QUADRUPLE (Subject, Caregiver, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
FEMALE
Age
15 Years to 20 Years
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | 5 weeks | 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. |
| Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | 5 weeks | 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). |
| Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | 5 weeks | 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 |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Daily Energy Intake | 5 weeks | Energy intake during breakfast, lunch, dinner, and evening snacks of each testing day will be measured. |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| All Study Participants 22 overweight 'breakfast skipping' adolescent girls participated in a randomized crossover-design breakfast study where they were completed, in a random order, the follow breakfast patterns at home for 6 days: 1) Breakfast Skipping; 2) Consumption of Normal Protein breakfast meals (i.e., 350 kcal; 15% protein, 65% CHO, & 20% fat); and 3) Consumption of Protein-Rich breakfast meals (i.e., 350 kcal; 40% protein, 40% CHO, & 20% fat). On the 7th day of each pattern, the participants reported to the testing facilities in the morning to complete the respective 10-h testing day. Blood samples and assessments of perceived appetite were collected/completed throughout the day following the breakfast (or no breakfast). A standardized lunch was also be provided. Prior to dinner, a brain scan was completed using functional magnetic resonance imaging (fMRI) to identify brain activation patterns in response to food pictures. There was a 7-day washout period between each breakfast pattern. | 22 |
| Total | 22 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 | FG002 | FG003 | FG004 | FG005 |
|---|---|---|---|---|---|---|---|
| Overall Study | Protocol Violation | 0 | 0 | 0 | 1 | 0 | 0 |
| Overall Study | Withdrawal by Subject | 0 | 0 | 0 | 0 | 1 | 0 |
Baseline characteristics
| Characteristic | All Study Participants |
|---|---|
| Age, Continuous | 19 Years STANDARD_DEVIATION 1 |
| Region of Enrollment United States | 22 Participants |
| Sex: Female, Male Female | 22 Participants |
| Sex: Female, Male Male | 0 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk |
|---|---|---|---|
| deaths Total, all-cause mortality | — / — | — / — | — / — |
| other Total, other adverse events | 0 / 22 | 0 / 22 | 0 / 22 |
| serious Total, serious adverse events | 0 / 22 | 0 / 22 | 0 / 22 |
Outcome results
Primary
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).
Time frame: 5 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Breakfast Skipping | Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | Ghrelin (10^3) | 41 (pg*min)/ml | Standard Error 4 |
| Breakfast Skipping | Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | Ln PYY | 0 (pg*min)/ml | Standard Error 25 |
| Normal Protein Breakfast Meals | Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | Ghrelin (10^3) | 35 (pg*min)/ml | Standard Error 3 |
| Normal Protein Breakfast Meals | Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | Ln PYY | 90 (pg*min)/ml | Standard Error 80 |
| Protein-rich Breakfast Meals | Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | Ghrelin (10^3) | 34 (pg*min)/ml | Standard Error 3 |
| Protein-rich Breakfast Meals | Area Under the Curve (AUC) of Plasma Total Ghrelin and Ln Peptide YY (PYY) | Ln PYY | 160 (pg*min)/ml | Standard Error 70 |
Primary
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.
Time frame: 5 weeks
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Breakfast Skipping | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your feeling of being full? | 21000 mm*min | Standard Error 5000 |
| Breakfast Skipping | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How much food can you eat right now? | 17000 mm*min | Standard Error 6000 |
| Breakfast Skipping | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your feeling of hunger? | 17000 mm*min | Standard Error 5000 |
| Breakfast Skipping | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your desire to eat? | 18000 mm*min | Standard Error 5000 |
| Normal Protein Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How much food can you eat right now? | 13000 mm*min | Standard Error 4000 |
| Normal Protein Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your feeling of being full? | 27000 mm*min | Standard Error 6000 |
| Normal Protein Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your desire to eat? | 13000 mm*min | Standard Error 4000 |
| Normal Protein Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your feeling of hunger? | 11000 mm*min | Standard Error 3000 |
| Protein-rich Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How much food can you eat right now? | 10000 mm*min | Standard Error 3000 |
| Protein-rich Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your desire to eat? | 12000 mm*min | Standard Error 4000 |
| Protein-rich Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your feeling of hunger? | 10000 mm*min | Standard Error 3000 |
| Protein-rich Breakfast Meals | Area Under the Curve (niAUC) of Perceived Hunger, Fullness, Desire to Eat, and Prospective Food Consumption | How strong is your feeling of being full? | 28000 mm*min | Standard Error 8000 |
Primary
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
Time frame: 5 weeks
Population: Coordinates were only determined for regions considered significant by analysis using Brain Voyager.
| Arm | Measure | Group | Value (NUMBER) |
|---|---|---|---|
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Amygdala (x) | -28 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Amygdala (y) | -5 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Amygdala (z) | -18 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Hippocampus (x) | -31 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Hippocampus (y) | -11 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Middle Frontal Gyrus (x) | -25 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Middle Frontal Gyrus (y) | -8 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Hippocampus (z) | -12 Talairach Coordinates |
| Breakfast Skipping | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Middle Frontal Gyrus (z) | 42 Talairach Coordinates |
| Normal Protein Breakfast Meals | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Hippocampus (x) | -19 Talairach Coordinates |
| Normal Protein Breakfast Meals | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Hippocampus (y) | -17 Talairach Coordinates |
| Normal Protein Breakfast Meals | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Hippocampus (z) | -18 Talairach Coordinates |
| Normal Protein Breakfast Meals | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Parahippocampus (y) | -17 Talairach Coordinates |
| Normal Protein Breakfast Meals | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Parahippocampus (z) | -30 Talairach Coordinates |
| Normal Protein Breakfast Meals | Brain Regions Displaying Differential Activation Prior to Dinner in Response to Food vs Nonfood Stimuli From Food Cue-stimulate fMRI Brain Scans | Parahippocampus (x) | -28 Talairach Coordinates |
Secondary
Daily Energy Intake
Energy intake during breakfast, lunch, dinner, and evening snacks of each testing day will be measured.
Time frame: 5 weeks
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Breakfast Skipping | Daily Energy Intake | 2002 kilocalories | Standard Error 111 |
| Normal Protein Breakfast Meals | Daily Energy Intake | 2292 kilocalories | Standard Error 115 |
| Protein-rich Breakfast Meals | Daily Energy Intake | 2123 kilocalories | Standard Error 71 |