Modification and Validation of a Semi-Automated In vitro Method for Predicting the Glycemic Index of Starchy Foods
Year: 2017
Type: dissertation
Abstract: The glycemic index (GI) can assist with determining the effect of food on blood glucose levels. The Englyst method is commonly used in vitro method to predict the GI, but it does not use food as eaten. The aim of this study was to establish and validate a modified semi-automated Englyst method that better estimates the GI of foods as consumed. The method was successfully established through a simulated upper gastrointestinal digestion protocol and compared with in vivo GI values. Predicted GI (pGI) was calculated from starch digestion profiles. In vivo GI was moderately correlated with pGI (r (18)= 0.51; p < 0.05), but highly correlated (r (18)= 0.72; p < 0.05) with rapidly digestible starch (RDS). Both pGI and RDS can be used as predictors for in vivo GI. This novel finding and the modified method can be used together to effectively predict the GI of starchy foods.
Author: Rasem El-Fahkhri
Language: English
Subfield: Nutrition and Dietetics
Field: Nursing
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2587360627