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Glycaemic Index and Substrate Metabolism (GI)

U

University of Vienna

Status

Completed

Conditions

Substrate Metabolism During Exercise

Treatments

Other: High Glycaemic Index
Other: Low Glycaemic Index
Other: Training intervention
Other: LCHF

Study type

Interventional

Funder types

Other

Identifiers

NCT05241730
2105/2021

Details and patient eligibility

About

Substrate metabolism during exercise can be influenced by various nutritional regimes. The effectiveness of the different nutritional regimes, which differ in their carbohydrate content, will be investigated not only by functional tests but also the measurement of the mechanistic processes in the muscle will be explored.

Magnetic resonance (MR), better known as magnetic resonance imaging (MRI), has been widely used in clinical practice as a non-invasive imaging technique. Importantly, in addition to producing anatomical images, an MR scanner also offers the possibility to measure the concentrations of a number of metabolic products. This is done through a technique known as magnetic resonance spectroscopy (MRS).

This research project asks the following questions:

  • Can a diet containing carbohydrates with a low glycemic index achieve the same adaptations in basic endurance/fat metabolism as a high fat, low carbohydrate (ketogenic) diet?
  • Does a high-fat, low-carbohydrate diet, compared with a high-carbohydrate diet, prevent improvements in performance in the submaximal and maximal range?
  • What is the effect of diets with different carbohydrate content and variable glycemic index on endurance performance in a half marathon and a time trial?
  • How do the diets with different carbohydrate content and variable glycaemic index affect the energy and glycogen stores in the muscles?

In active recreational athletes, the objectives are: (1) to investigate the effects of different diets with variable carbohydrate content and glycaemic index on substrate metabolism, (2) to determine the effects of the different diets on energy stores using multinuclear dynamic magnetic resonance spectroscopy, and (3) to measure the effects of the different diets on endurance performance.

Enrollment

65 patients

Sex

Male

Ages

18 to 40 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Male gender
  • Age between 18 and 40 years
  • Recreational active in leisure time (2-3x/week physical activity)
  • Motivation for performance testing and structured training plan
  • Interest in different diets
  • no acute or chronic illnesses

Exclusion criteria

  • Contraindications to physical exercise according to ACSM (American College of Sports Medicine) guidelines
  • Age <18 or >40 years
  • Taking medication that could influence the measurements or that is prohibited in training and/or competition according to the WADA (World Anti-Doping Agency) Code
  • Competitive athlete with own training plan
  • Experience with intervention diets

MRI-specific exclusion criteria:

  • Claustrophobia
  • Cardiac pacemaker
  • cochlear implant
  • subcutaneous injection system
  • Stents, metal implants, braces, piercings, tattoos
  • Body weight of more than 180 kg or BMI of more than 37 kg/m2

Trial design

Primary purpose

Basic Science

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

65 participants in 3 patient groups

Low GI
Experimental group
Description:
The subjects eat 55-60 E-% carbohydrates with ≥ 65 % from low glycaemic index carbohydrates per day, the other E-% are fats and proteins.
Treatment:
Other: Low Glycaemic Index
Other: Training intervention
High GI
Active Comparator group
Description:
The subjects eat 55-60 E-% carbohydrates with ≥ 65 % from high glycaemic index carbohydrates per day, the other E-% are fats and proteins.
Treatment:
Other: Training intervention
Other: High Glycaemic Index
Low Carb High Fat
Experimental group
Description:
The subjects eat ≥ 65 E-% fats and a maximum of 50 g carbohydrates per day.
Treatment:
Other: Training intervention
Other: LCHF

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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