Literature DB >> 2760355

The glycemic index: variation between subjects and predictive difference.

T M Wolever1, A Csima, D J Jenkins, G S Wong, R G Josse.   

Abstract

It is not known whether the variability of the glycemic index (GI) in different subjects is due to within- or between-individual variation. In addition, it is not known how large a difference in GI between different meals is clinically important for individuals with diabetes. Therefore, insulin-dependent (IDDM) and non-insulin-dependent (NIDDM) diabetic subjects tested four foods, with each food taken by each subject on two separate occasions. For each food, most of the variation of absolute glycemic responses was due to differences between the subjects. However, when the results were expressed as the GI, there were no significant differences between the subjects, and most of the variation was due to within-individual variation. Using the within-individual variance, we estimated the so-called "predictive difference" of GI values. Its reliability was assessed by consideration of published data from eight studies where different mixed meals were taken by the same group of subjects. There were 37 cases where the difference between the GI of any two meals was greater than the predictive difference. Of these 37 pairs of meals, the GI correctly ranked the glycemic responses in 36 (97%). We conclude that GI values for the same food do not vary significantly between different individuals. For a subject with NIDDM a difference in GI of 34 will predict the ranking of glycemic responses of two meals with 95% probability. The corresponding value for a subject with IDDM is 50.

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Year:  1989        PMID: 2760355     DOI: 10.1080/07315724.1989.10720298

Source DB:  PubMed          Journal:  J Am Coll Nutr        ISSN: 0731-5724            Impact factor:   3.169


  5 in total

1.  Automated computation of glycemic index for foodstuffs using continuous glucose monitoring.

Authors:  Rudolf Chlup; Pavel Seckar; Jana Zapletalová; Katerina Langová; Pavla Kudlová; Karolina Chlupová; Josef Bartek; Daniela Jelenová
Journal:  J Diabetes Sci Technol       Date:  2008-01

2.  Reply to TMS Wolever et al.

Authors:  Nirupa R Matthan; Alice H Lichtenstein
Journal:  Am J Clin Nutr       Date:  2017-03       Impact factor: 7.045

3.  Estimating the reliability of glycemic index values and potential sources of methodological and biological variability.

Authors:  Nirupa R Matthan; Lynne M Ausman; Huicui Meng; Hocine Tighiouart; Alice H Lichtenstein
Journal:  Am J Clin Nutr       Date:  2016-09-07       Impact factor: 7.045

4.  Lowering the glycemic index of white bread using a white bean extract.

Authors:  Jay K Udani; Betsy B Singh; Marilyn L Barrett; Harry G Preuss
Journal:  Nutr J       Date:  2009-10-28       Impact factor: 3.271

5.  The Role of Glycemic Index and Glycemic Load in the Development of Real-Time Postprandial Glycemic Response Prediction Models for Patients With Gestational Diabetes.

Authors:  Evgenii Pustozerov; Aleksandra Tkachuk; Elena Vasukova; Aleksandra Dronova; Ekaterina Shilova; Anna Anopova; Faina Piven; Tatiana Pervunina; Elena Vasilieva; Elena Grineva; Polina Popova
Journal:  Nutrients       Date:  2020-01-23       Impact factor: 5.717

  5 in total

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