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OpenTrials
Completed

NCT Number: NCT02285907

Protein Quality on Appetite Control, Reward-driven Eating, & Subsequent Food Intake

To determine whether the consumption of a beef-rich lunch improves appetite control, satiety, and energy intake regulation while reducing food reward and food cravings compared to the consumption of a soy-rich lunch when matched for macronutrients and fiber content or when match for serving size. The mechanisms of action surrounding the differential responses of beef versus soy proteins were also explored.

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Key information

Conditions

Appetite and General Nutritional Disorders

Age range

18 year–30 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University of Missouri

Columbia, Missouri, 65211, United States

About this study

A randomized, crossover design, acute study was completed in 21 healthy adults (age 23 ±1 y; BMI: 23.8 ± 0.6 kg/m2) to compare 400 kcal lunch meals varying in protein quality. Two separate comparisons were performed. The first comparison consisted of macronutrient and fiber-matched lunches which varied in protein quality: 24 g beef protein vs. 24 g soy protein. The second comparison matched serving size only: 1 serving of beef (24 g protein with 0 g fiber) vs. 1 serving of soy (14 g protein; 5 g fiber). For each treatment, the participants completed 2 testing days per lunch treatment. During the "Appetite Assessment Days," each participant reported to the lab to consume one of the lunch meals. Pre and 7-h post-lunch appetite and cravings questionnaires were completed throughout each testing day along with plasma, hormonal responses, and plasma amino acid concentrations through repeated blood sampling. Ad libitum dinner energy intake was also measured. During the "Reward Assessment Days," the participants reported to our facility to again consume one of the lunch meals. Pre and post-lunch neural responses to food stimuli, through functional magnetic resonance imaging (fMRI), occurred followed by ad libitum consumption of a lunch dessert.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age range 18-30 y
  • Normal to Overweight (BMI: 18-29.9 kg/m2)
  • No metabolic, psychological, or neurological diseases/conditions
  • Not currently/previously on a weight loss or other special diet (in the past 6 months)
  • Not a vegetarian
  • Right-handed (necessary for the fMRI analyses)
  • Not pregnant
  • Meets the MU-Brain Imaging Center Screening Criteria
  • Have not given blood (for the American Red Cross in the past 6 months)

Exclusion criteria

  • Age >30 y and <18y
  • Under Weight or Obese (BMI: <18 kg/m2 or >29.9 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.
  • Currently/previously on a weight loss or other special diet (in the past 6 months)
  • 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
  • Does not meeting the MU-Brain Imaging Center screening criteria
  • Have given blood (for the American Red Cross) in the past 6 months or plan to give blood in the following 6 months

Treatment and study plan

Macronutrient and Fiber Matched BEEF

Other

The participants will consume the macronutrient and fiber matched BEEF lunch on a single testing day. BEEF contained 33% protein, 43% CHO, and 24% fat; the BEEF meal contained 24 g of beef protein from 96% lean ground beef (Cargill, KS). Soy fiber (Nutritional Designs, NY) was added to the BEEF meal to match total final content between meals.The participants will consume the serving size matched BEEF lunch on a single testing day. BEEF contained 33% protein, 43% CHO, and 24% fat; the BEEF meal contained 24 g of beef protein from 96% lean ground beef patty (Cargill, KS).

Macronutrient and Fiber Matched SOY

Other

The participants will consume the macronutrient and fiber matched SOY lunch on a single testing day. SOY contained 33% protein, 43% CHO, and 24% fat; the SOY meal contained 24 g of textured soy protein concentrate (Boca Foods, WI).

Serving Size Matched BEEF

Other

The participants will consume the serving size matched BEEF lunch on a single testing day. BEEF contained 33% protein, 43% CHO, and 24% fat; the BEEF meal contained 24 g of beef protein from 96% lean ground beef patty (Cargill, KS).

Serving Size Matched SOY

Other

The participants will consume the serving size matched SOY lunch on a single testing day. SOY contained 24% protein, 49% CHO, and 24% fat; the SOY meal contained 14 g of textured soy protein concentrate (Boca Foods, WI).

Primary outcomes

  1. Eating Initiation

    Time frame: 1 Day

    Eating initiation will be measured as the time lapse between consuming the intervention and requesting dinner.

  2. Subsequent Food Intake

    Time frame: 1 Day

    Ad libitum dinner and snacks were provided. Energy content and macronutrient content of these eating occasions were assessed.

  3. Net Incremental Area Under the Curve (niAUC) of Perceived Hunger and Fullness

    Time frame: - 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

    Computerized questionnaires, assessing perceived sensations of hunger and fullness were completed throughout the testing days. 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 for by computing the summation of the average change from baseline score (units of 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." For fullness, higher can be interpreted as "feeling more full." Questionnaires were asked at baseline and about every 30 minutes throughout the day for a total of 20 questionnaires.

  4. Net Incremental Area Under the Curve (niAUC) of Plasma Total Glucagon-like Peptide (GLP-1) and Total Peptide YY (PYY)

    Time frame: - 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 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 at -80°C. Plasma total glucagon-like peptide (GLP-1) 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. niAUC was calculated throughout the testing period by computing the summation of the average change from baseline score (units of pg/ml) for each time point and the subsequent time point, multiplied by the difference in time (units of min) between the two time instances for a total of 20 blood samples.

  5. Food Cue-stimulate fMRI Brain Scans

    Time frame: 3 hours

    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 protein type 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] and protein source (BEEF vs. SOY) comparisons within the macronutrient and fiber-matched condition and the serving size-matched conditions, separately. The mean percent signal change in the maximum voxel within each region that displayed significant activation after the BEEF and SOY meals was then determined. Talairach coordinates for each region are presented for each row as (x;y;z).

Secondary outcomes

  1. Plasma Amino Acids

    Time frame: - 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

    Plasma amino acid concentrations were measured from the pre and hourly postprandial time points until dinner request following the Macronutrient and Fiber Matched BEEF meal and the Serving Size Matched Beef Meal. An average amino acid concentration was then determined from the change from baseline concentration for all available time points. Plasma amino acid analyses were performed through the University of Missouri-Columbia Agricultural Experiment Station Chemical Laboratories using cation-exchange chromatography (cIEC-HPLC) coupled with post-column ninhydrin derivatization and quantitation.

Sponsors and collaborators

Lead sponsor

University of Missouri-Columbia

Other

Registry information

Official study title

The Effects of Consuming Beef vs. Soy-rich Lunch Meals, Matched for Macronutrient Content or Serving Size, on Markers of Appetite Control and Satiety

Important dates

Study start
2012
Primary completion
2013
Study completion
2014
First posted
Nov 7, 2014
Registry last updated
May 15, 2019

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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