The Metabolic Effects of Consuming Carbohydrate With Different Protein Types
NCT02380846 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 15
Last updated 2019-05-15
Summary
This study aims to find out how consuming different proteins with rice affect metabolism. Most meals the investigators eat predominantly consist of a carbohydrate and protein (i.e. rice, noodles, bread etc with meats or seafood). However, it is still unknown how consuming different proteins with commonly eaten carbohydrates affect metabolism. Previous studies have shown that proteins stimulate hormones such as insulin, glucagon and gut hormones. However, the extent of the response depends on protein type. The metabolic responses to carbohydrates have also been shown to be greatly affected when they are eaten with proteins. However, most of the previous studies have used glucose as the carbohydrate and it is still unknown how eating proteins with carbohydrate foods such as rice affect metabolism. Therefore, this study has been initiated to determine the metabolic effects of eating different protein types with rice. Using the most common carbohydrate eaten in Asia (rice) and four commonly eaten protein foods (egg, chicken, fish and beancurd), this study aims to observe the metabolic effects of co-ingesting proteins and carbohydrate. The resulting data will provide valuable insights into the metabolic effects of protein-carbohydrate meals and will be useful in the development of practical advice and dietary guidelines for those with chronic diseases (such as diabetes and obesity).
Conditions
Interventions
- OTHER
-
White rice
Control - white rice
- OTHER
-
Rice with chicken breast
Treatment 1 - steamed white rice with steamed chicken breast
- OTHER
-
Rice with fish
Treatment 2 - steamed white rice with steamed fish
- OTHER
-
Rice with egg white
Treatment 3 - steamed white rice with egg white
- OTHER
-
Rice with beancurd
Treatment 4 - steamed white rice with steamed beancurd
Sponsors & Collaborators
-
Singapore Institute of Food and Biotechnology Innovation
lead OTHER_GOV
Study Design
- Allocation
- RANDOMIZED
- Purpose
- OTHER
- Masking
- NONE
- Model
- CROSSOVER
Eligibility
- Min Age
- 21 Years
- Max Age
- 40 Years
- Sex
- MALE
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2013-09-30
- Primary Completion
- 2018-10-08
- Completion
- 2018-10-08
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