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Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods

The recent popularization of low-glycemic foods has expanded interest in glycemic index (GI) not only among diabetic patients but also healthy people. The purpose of this study is to validate the estimated glycemic load model (eGL) developed in 2018. This study measured the glycemic load (GL) of 24...

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Autores principales: Lee, Miran, Kang, Haejin, Chung, Sang-Jin, Nam, Kisun, Park, Yoo Kyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127965/
https://www.ncbi.nlm.nih.gov/pubmed/35619953
http://dx.doi.org/10.3389/fnut.2022.892403
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author Lee, Miran
Kang, Haejin
Chung, Sang-Jin
Nam, Kisun
Park, Yoo Kyoung
author_facet Lee, Miran
Kang, Haejin
Chung, Sang-Jin
Nam, Kisun
Park, Yoo Kyoung
author_sort Lee, Miran
collection PubMed
description The recent popularization of low-glycemic foods has expanded interest in glycemic index (GI) not only among diabetic patients but also healthy people. The purpose of this study is to validate the estimated glycemic load model (eGL) developed in 2018. This study measured the glycemic load (GL) of 24 fast foods in the market in 20 subjects. Then, the transportability of the model was assessed, followed by an assessment of model calibration and discrimination based on model performance. The transportability assessment showed that the subjects at the time of model development are different from the subjects of this validation study. Therefore, the model can be described as transportable. As for the model's performance, the calibration assessment found an x(2) value of 11.607 and a p-value of 0.160, which indicates that the prediction model fits the observations. The discrimination assessment found a discrimination accuracy exceeding 0.5 (57.1%), which confirms that the performance and stability of the prediction model can be discriminated across all classifications. The correlation coefficient between GLs and eGLs measured from the 24 fast foods was statistically significant at 0.712 (p < 0.01), indicating a strong positive linear relationship. The explanatory powers of GL and eGL was high at 50.7%. The findings of this study suggest that this prediction model will greatly contribute to healthy food choices because it allows for predicting blood glucose responses solely based on the nutrient content labeled on the fast foods.
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spelling pubmed-91279652022-05-25 Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods Lee, Miran Kang, Haejin Chung, Sang-Jin Nam, Kisun Park, Yoo Kyoung Front Nutr Nutrition The recent popularization of low-glycemic foods has expanded interest in glycemic index (GI) not only among diabetic patients but also healthy people. The purpose of this study is to validate the estimated glycemic load model (eGL) developed in 2018. This study measured the glycemic load (GL) of 24 fast foods in the market in 20 subjects. Then, the transportability of the model was assessed, followed by an assessment of model calibration and discrimination based on model performance. The transportability assessment showed that the subjects at the time of model development are different from the subjects of this validation study. Therefore, the model can be described as transportable. As for the model's performance, the calibration assessment found an x(2) value of 11.607 and a p-value of 0.160, which indicates that the prediction model fits the observations. The discrimination assessment found a discrimination accuracy exceeding 0.5 (57.1%), which confirms that the performance and stability of the prediction model can be discriminated across all classifications. The correlation coefficient between GLs and eGLs measured from the 24 fast foods was statistically significant at 0.712 (p < 0.01), indicating a strong positive linear relationship. The explanatory powers of GL and eGL was high at 50.7%. The findings of this study suggest that this prediction model will greatly contribute to healthy food choices because it allows for predicting blood glucose responses solely based on the nutrient content labeled on the fast foods. Frontiers Media S.A. 2022-05-10 /pmc/articles/PMC9127965/ /pubmed/35619953 http://dx.doi.org/10.3389/fnut.2022.892403 Text en Copyright © 2022 Lee, Kang, Chung, Nam and Park. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Nutrition
Lee, Miran
Kang, Haejin
Chung, Sang-Jin
Nam, Kisun
Park, Yoo Kyoung
Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods
title Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods
title_full Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods
title_fullStr Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods
title_full_unstemmed Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods
title_short Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods
title_sort validation study of the estimated glycemic load model using commercially available fast foods
topic Nutrition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127965/
https://www.ncbi.nlm.nih.gov/pubmed/35619953
http://dx.doi.org/10.3389/fnut.2022.892403
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