Literature DB >> 34618011

Limitations of the glycaemic index and the need for nuance when determining carbohydrate quality.

Mitch Kanter1, Siddhartha Angadi2, Julie Miller-Jones3, Katherine A Beals4.   

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Year:  2022        PMID: 34618011      PMCID: PMC8953453          DOI: 10.1093/cvr/cvab312

Source DB:  PubMed          Journal:  Cardiovasc Res        ISSN: 0008-6363            Impact factor:   10.787


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In the recent review study by Riccardi et al., the study’s notable focus on the glycaemic index (GI) to inform broad dietary guidance is troubling given GI’s demonstrable limitations as a tool for predicting health risk. In 2019, Reynolds et al. observed the relationship between GI and clinical outcomes was consistently graded as low to very low. Furthermore, a recent analysis demonstrated the inconsistent link between GI and hard clinical endpoints across populations that likely have divergent risk profiles (e.g. for developed vs. developing countries)., As Riccardi et al. previously noted in an earlier publication, intervention studies on the effects of GI on cardiovascular disease outcomes are not clear, and while GI may have some utility for people with type 2 diabetes, it has not shown to be particularly useful as a standalone metric. Indeed, multiple studies have demonstrated GI’s wide intra- and inter-individual variability, suggesting it cannot be considered a reliable nor generalizable measure of glycaemic impact on health outcomes. In the most comprehensive evaluation of post-prandial glycaemic responses with controlled meals to date, Zeevi et al. observed a roughly five-fold interpersonal variability in glycaemic response to bread between the bottom and top 10% of participants. This degree of inter-individual variability would disqualify the use of any other biomarker of health or disease status. Lifestyle factors, many of which are difficult to control even in lab settings, can affect one’s glycaemic response to a food (e.g. prior exercise, stress, lack of sleep, composition of previous meal(s), etc.). There is also significant GI variability within food categories and across geographic locations as well., Variables such as food variety, growing conditions, small changes in meal preparation, and even degree of mastication can impact GI. Furthermore, GI tables are developed based on consumption of 50 g of available carbohydrate of a food. This quantity of carbohydrate is often difficult to attain in ad lib food settings. For example, when comparing rice to beets—both classified as high GI foods—the 50 g threshold for available carbohydrate is a reasonable measure for rice (there are 53 g of carbohydrate per cup and most of it is available). However, the GI for beets is 64, which has little real-world meaning as there are only 13 g of carbohydrate per cup of beets; to reach the 50 g threshold one would need to consume more than 4 cups of beets. On the basis of GI alone, the authors pointedly call out potatoes as a food to limit, yet evidence indicates that potatoes in many forms (despite its GI, which varies significantly depending on variety and cooking preparation), produce different (generally more beneficial) effects on food intake, satiety, blood glucose, and insulin responses than pasta, which has a lower GI. All of these issues speak to the impracticality of GI as a metric for carbohydrate quality in real-world settings. A recent review by the US Academy of Nutrition and Dietetics noted that the GI may be a useful tool in some contexts, but acknowledged it is ‘an imperfect system’, noting one of its major flaws is that it assesses glycaemic impact on an empty stomach and when consumed without any other foods or condiments. Lastly, the use of GI seems counter to the authors’ call for a ‘meal pattern’ vs. an individual nutrient approach, a perspective widely supported among health professionals and government agencies. Yet, GI is not a metric for assessing the healthfulness of meal patterns, but rather, analyzes carbohydrates in isolation of all other dietary factors. Recently published reviews and perspectives call into question its use as a marker of diet quality and strongly recommend departing from such reductionist assessment methods and have called for a more holistic approach to evaluating the quality of carbohydrate foods., Conflict of interest: M.K. serves a a consultant for the Alliance for Potato Research & Education (APRE). K.A.B is consultant for Potatoes USA.
  17 in total

1.  Personalized Nutrition by Prediction of Glycemic Responses.

Authors:  David Zeevi; Tal Korem; Niv Zmora; David Israeli; Daphna Rothschild; Adina Weinberger; Orly Ben-Yacov; Dar Lador; Tali Avnit-Sagi; Maya Lotan-Pompan; Jotham Suez; Jemal Ali Mahdi; Elad Matot; Gal Malka; Noa Kosower; Michal Rein; Gili Zilberman-Schapira; Lenka Dohnalová; Meirav Pevsner-Fischer; Rony Bikovsky; Zamir Halpern; Eran Elinav; Eran Segal
Journal:  Cell       Date:  2015-11-19       Impact factor: 41.582

2.  Interindividual variability and intra-individual reproducibility of glycemic index values for commercial white bread.

Authors:  Sonia Vega-López; Lynne M Ausman; John L Griffith; Alice H Lichtenstein
Journal:  Diabetes Care       Date:  2007-03-23       Impact factor: 19.112

3.  Glycemic Index, Glycemic Load, and Cardiovascular Disease and Mortality.

Authors:  Mitch Kanter; Siddhartha Angadi; Joanne Slavin
Journal:  N Engl J Med       Date:  2021-07-22       Impact factor: 91.245

4.  International tables of glycemic index and glycemic load values 2021: a systematic review.

Authors:  Fiona S Atkinson; Jennie C Brand-Miller; Kaye Foster-Powell; Anette E Buyken; Janina Goletzke
Journal:  Am J Clin Nutr       Date:  2021-07-13       Impact factor: 7.045

5.  Carbohydrate quality and human health: a series of systematic reviews and meta-analyses.

Authors:  Andrew Reynolds; Jim Mann; John Cummings; Nicola Winter; Evelyn Mete; Lisa Te Morenga
Journal:  Lancet       Date:  2019-01-10       Impact factor: 79.321

6.  Glycemic Index, Glycemic Load, and Cardiovascular Disease and Mortality.

Authors:  David J A Jenkins; Mahshid Dehghan; Andrew Mente; Shrikant I Bangdiwala; Sumathy Rangarajan; Kristie Srichaikul; Viswanathan Mohan; Alvaro Avezum; Rafael Díaz; Annika Rosengren; Fernando Lanas; Patricio Lopez-Jaramillo; Wei Li; Aytekin Oguz; Rasha Khatib; Paul Poirier; Noushin Mohammadifard; Andrea Pepe; Khalid F Alhabib; Jephat Chifamba; Afzal Hussein Yusufali; Romaina Iqbal; Karen Yeates; Khalid Yusoff; Noorhassim Ismail; Koon Teo; Sumathi Swaminathan; Xiaoyun Liu; Katarzyna Zatońska; Rita Yusuf; Salim Yusuf
Journal:  N Engl J Med       Date:  2021-02-24       Impact factor: 91.245

Review 7.  Role of glycemic index and glycemic load in the healthy state, in prediabetes, and in diabetes.

Authors:  Gabriele Riccardi; Angela A Rivellese; Rosalba Giacco
Journal:  Am J Clin Nutr       Date:  2008-01       Impact factor: 7.045

8.  The effects of potatoes and other carbohydrate side dishes consumed with meat on food intake, glycemia and satiety response in children.

Authors:  R Akilen; N Deljoomanesh; S Hunschede; C E Smith; M U Arshad; R Kubant; G H Anderson
Journal:  Nutr Diabetes       Date:  2016-02-15       Impact factor: 5.097

9.  Glycemic Index of Slowly Digestible Carbohydrate Alone and in Powdered Drink-Mix.

Authors:  Vishnupriya Gourineni; Maria L Stewart; Rob Skorge; Thomas Wolever
Journal:  Nutrients       Date:  2019-05-29       Impact factor: 5.717

10.  Perspective: Does Glycemic Index Matter for Weight Loss and Obesity Prevention? Examination of the Evidence on "Fast" Compared with "Slow" Carbs.

Authors:  Glenn A Gaesser; Julie Miller Jones; Siddhartha S Angadi
Journal:  Adv Nutr       Date:  2021-12-01       Impact factor: 8.701

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