Daily Protein Intake Patterns on Energy Metabolism and the Motivation to Snack

The purpose of this study is to determine if when one eats protein can change how the body uses food for energy. Researchers will also test if eating a high protein breakfast can change one's craving for snack foods.

Study Overview

• Status: Active, not recruiting
• Conditions: Obesity
• Intervention / Treatment: Other: Even protein; Other: Skewed protein

Detailed Description

The purpose of this study is to determine if consuming 30 g of high-quality protein at each meal can increase fat utilization and shift between-meal snack choices. While the benefits of high-protein diets are well known, little is known about the optimal amount of protein that should be eaten at each meal. Most Americans eat little protein at breakfast and lunch and most of their protein at the evening meal. Current guidelines for protein are based on body weight; however, recent evidence indicates that absolute amounts of protein at each meal are needed to maintain metabolically active fat-free mass. This suggests that a more even protein consumption pattern across daily meals may positively influence energy metabolism. In addition, recent evidence indicates that protein may reduce activity in the food reward areas of the brain. This suggests that protein may influence between-meal snacking by decreasing the relative reinforcing value (RRV) of highly rewarding snack foods. The RRV of a food is an empirical measure of its motivating value and energy-dense foods are highly reinforcing, especially for obese individuals. This study will be the first to investigate the role of the daily distribution of protein intake on energy metabolism and modifying snacking behavior.

• Study Type: Interventional
• Enrollment (Actual): 26
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • North Dakota
    • Grand Forks, North Dakota, United States, 58203
      • USDA Grand Forks Human Nutrition Research Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 20 years to 60 years (Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• BMI < 25 kg/m2
• BMI ≥ 30 kg/m2 but < 34.5 kg/m2
• able to understand and sign the informed consent
• able to provide own transportation to the Center
• free of any major illness/disease
• usual protein intake within the acceptable macronutrient distribution range (10 to 30%)
• constant habitual activity patterns within the last 3 months
• females of childbearing age must be on birth control for a minimum of 3 months prior to study start and have regular menstrual cycles

Exclusion Criteria:

• unable or unwilling to consume animal products
• have had more than a 10% change in body weight within the past 2 months
• are participating in a weight loss diet/exercise program
• are consuming a specialized diet
• currently or planning on becoming pregnant during the study timeline
• lactating
• have a metabolic illness/disease
• have uncontrolled hypertension
• have ever had cancer
• have an infectious disease
• suffer from alcohol or drug abuse
• use tobacco and e-cigarette products on a regular basis
• have the presence of acute illness
• taking medications known to affect energy expenditure and appetite

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Even protein; Menu to provide 90 g of protein per day in an even distribution of 30 g at each meal.	Other: Even protein; 5 day intake of even protein 3 day rotating menu.
Experimental: Skewed protein; Menu to provide 90 g of protein per day in a skewed distribution of 10 g at breakfast, 15 g at lunch and 65 g at dinner.	Other: Skewed protein; 5 day intake of skewed protein 3 day rotating menu.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Fat, carbohydrate, and protein utilization	The effect of consuming two patterns of daily protein intake on the use of fat, carbohydrate and protein for energy.	4 hours after meal consumption
Relative reinforcing value (RRV) of energy-dense snack foods	The effect of consuming a high-protein or a low-protein breakfast on the RRV of energy-dense snack foods to a healthy snack food alternative.	2 hours after breakfast consumption

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Peripheral neurotransmitter metabolites	The effect of consuming a high-protein or low-protein breakfast and an energy-dense snack food on dopamine and serotonin metabolite plasma concentrations.	2 hours
Psychoactive Effect Questionnaire	The effect of consuming a high-protein or low-protein breakfast and an energy-dense snack food on the number of positive responses on the Psychoactive Effects Questionnaire.	2 hours
Satiety visual analog scales	The effect of consuming two patterns of daily protein intake on subjective measures of satiety.	4 hours after meal consumption

Collaborators and Investigators

• Sponsor: USDA Grand Forks Human Nutrition Research Center
• Investigators: Principal Investigator: Shanon Casperson, PhD, USDA Grand Forks Human Nutrition Research Center

Publications and helpful links

Helpful Links

• Grand Forks Human Nutrition Research Center Current Nutrition Studies

Study record dates

Study Major Dates

• Study Start (Actual): June 1, 2016
• Primary Completion (Estimated): December 1, 2024
• Study Completion (Estimated): December 1, 2024

Study Registration Dates

• First Submitted: June 6, 2016
• First Submitted That Met QC Criteria: June 6, 2016
• First Posted (Estimated): June 10, 2016

Study Record Updates

• Last Update Posted (Actual): April 23, 2024
• Last Update Submitted That Met QC Criteria: April 19, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Other Study ID Numbers: GFHNRC500

Plan for Individual participant data (IPD)

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