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Objective: The prevalence of gestational diabetes mellitus (GDM) is rising. There is little evidence to demonstrate the effectiveness of one dietary therapy over another. We aimed to investigate the effect of a low-glycemic index (LGI) versus a conventional high-fiber diet on pregnancy outcomes, neonatal anthropometry, and maternal metabolic profile in GDM.Research Design and Methods: Ninety-nine women (age 26-42 years; mean ± SD prepregnancy BMI 24 ± 5 kg/m²) diagnosed with GDM at 20-32 weeks' gestation were randomized to follow either an LGI (n = 50; target glycemic index [GI] ~50) or a high-fiber moderate-GI diet (HF) (n = 49; target GI ~60). Dietary intake was assessed by 3-day food records. Pregnancy outcomes were collected from medical records.Results: The LGI group achieved a modestly lower GI than the HF group (mean ± SEM 47 ± 1 vs. 53 ± 1; P < 0.001). At birth, there was no significant difference in birth weight (LGI 3.3 ± 0.1 kg vs. HF 3.3 ± 0.1 kg; P = 0.619), birth weight centile (LGI 52.5 ± 4.3 vs. HF 52.2 ± 4.0; P = 0.969), prevalence of macrosomia (LGI 2.1% vs. HF 6.7%; P = 0.157), insulin treatment (LGI 53% vs. HF 65%; P = 0.251), or adverse pregnancy outcomes.Conclusions: In intensively monitored women with GDM, an LGI diet and a conventional HF diet produce similar pregnancy outcomes. [ABSTRACT FROM AUTHOR]

Objective: Although carbohydrate counting is routine practice in type 1 diabetes, hyperglycemic episodes are common. A food insulin index (FII) has been developed and validated for predicting the normal insulin demand generated by mixed meals in healthy adults. We sought to compare a novel algorithm on the basis of the FII for estimating mealtime insulin dose with carbohydrate counting in adults with type 1 diabetes.Research Design and Methods: A total of 28 patients using insulin pump therapy consumed two different breakfast meals of equal energy, glycemic index, fiber, and calculated insulin demand (both FII = 60) but approximately twofold difference in carbohydrate content, in random order on three consecutive mornings. On one occasion, a carbohydrate-counting algorithm was applied to meal A (75 g carbohydrate) for determining bolus insulin dose. On the other two occasions, carbohydrate counting (about half the insulin dose as meal A) and the FII algorithm (same dose as meal A) were applied to meal B (41 g carbohydrate). A real-time continuous glucose monitor was used to assess 3-h postprandial glycemia.Results: Compared with carbohydrate counting, the FII algorithm significantly decreased glucose incremental area under the curve over 3 h (-52%, P = 0.013) and peak glucose excursion (-41%, P = 0.01) and improved the percentage of time within the normal blood glucose range (4-10 mmol/L) (31%, P = 0.001). There was no significant difference in the occurrence of hypoglycemia.Conclusions: An insulin algorithm based on physiological insulin demand evoked by foods in healthy subjects may be a useful tool for estimating mealtime insulin dose in patients with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Objective: A low-glycemic index diet is effective as a treatment for individuals with diabetes and has been shown to improve pregnancy outcomes when used from the first trimester. A low-glycemic index diet is commonly advised as treatment for women with gestational diabetes mellitus (GDM). However, the efficacy of this advice and associated pregnancy outcomes have not been systematically examined. The purpose of this study was to determine whether prescribing a low-glycemic index diet for women with GDM could reduce the number of women requiring insulin without compromise of pregnancy outcomes.Research Design and Methods: All women with GDM seen over a 12-month period were considered for inclusion in the study. Women (n = 63) were randomly assigned to receive either a low-glycemic index diet or a conventional high-fiber (and higher glycemic index) diet.Results: Of the 31 women randomly assigned to a low-glycemic index diet, 9 (29%) required insulin. Of the women randomly assigned to a higher-glycemic index diet, a significantly higher proportion, 19 of 32 (59%), met the criteria to commence insulin treatment (P = 0.023). However, 9 of these 19 women were able to avoid insulin use by changing to a low-glycemic index diet. Key obstetric and fetal outcomes were not significantly different.Conclusions: Using a low-glycemic index diet for women with GDM effectively halved the number needing to use insulin, with no compromise of obstetric or fetal outcomes. [ABSTRACT FROM AUTHOR]

BACKGROUND: The glycemic index (GI) characterizes foods by using the incremental area under the glycemic response curve relative to a similar amount of oral glucose. Its ability to differentiate between curves of different shapes, the peak response, and other aspects of the glycemic response is debatable. OBJECTIVE: The objective was to explore the association between a food's GI and the shape of the curve in healthy individuals. DESIGN: A large database of 1,126 foods tested by standardized GI methodology in 8-12 healthy subjects was analyzed systematically. Each food's absolute and incremental blood glucose concentrations were compared at individual time points with the GI. The average curve was generated for low-GI (< or = 55), medium-GI (56-69), and high-GI (> or = 70) foods within major food categories. RESULTS: The GI of individual foods was found to correlate strongly with the incremental and actual peak (Spearman's correlations of r = 0.76 and r = 0.73, respectively), incremental and actual glucose concentration at 60 min (r = 0.70 and r = 0.66, respectively), and maximum amplitude of glucose excursion (r = 0.68) (all P < 0.001). In contrast, there was only a weak correlation between the food's GI and the 120-min glucose concentration (incremental r = 0.20, P < 0.001; absolute r = 0.16, P < 0.001). Within food groups, the mean GI, 30- and 60-min glucose concentrations, and maximum amplitude of glucose excursion varied significantly for foods classified as having a low, medium, or high GI (P < 0.001). CONCLUSIONS: The GI provides a good summary of postprandial glycemia. It predicts the peak (or near peak) response, the maximum glucose fluctuation, and other attributes of the response curve. Copyright © 2009 American Society for Nutrition [ABSTRACT FROM AUTHOR]

Objective: To assess the ability of a food-frequency questionnaire (FFQ) to rank Australians according to their intake of total carbohydrate, sugar, starch, fibre, glycaemic index (GI) and glycaemic load (GL).Design: Cross-sectional sample from a population cohort.Setting: Two postcode areas west of Sydney, Australia.Subjects: From 1992 to 1994, a total of 2868 older Australians provided dietary data using a 145-item Willett-derived FFQ. A representative sub-sample of 78 subjects completed three 4-day weighed food records (WFRs). Pearson and Spearman correlations, Bland-Altman plots and weighted kappa values were calculated.Results: Compared with the WFR, the FFQ provided higher mean estimates of all nutrients except starch and GI. All Pearson and/or Spearman correlations were greater than 0.5, except for GL. For GI, sugar, starch and fibre, the regression lines from the Bland-Altman analysis indicated a non-significant linear trend (P = 0.07, P = 0.36, P = 0.28 and P = 0.10, respectively). For GL and total carbohydrate, however, there was a significant linear trend (P = 0.006 and P < 0.0001, respectively), indicating that as the GL and carbohydrate intake of individuals increased, so did the magnitude of the error between the FFQ and WFR. Weighted kappa values all indicated moderate to good agreement, with the exception of GL which was only fair. The proportions of subjects correctly classified within one quintile for all of the nutrients were over 50% and gross misclassification was low (<10%).Conclusion: This FFQ was able to rank individuals according to their intakes of total carbohydrate, sugar, starch, fibre and GI, but not as well for GL. [ABSTRACT FROM AUTHOR]

BACKGROUND: Growth in normal and malignant tissues has been linked to hyperinsulinemia and insulin-like growth factors (IGFs). We hypothesized that IGF and IGF-binding protein (IGFBP) responses may be acutely affected by differences in the glycemic index (GI) of foods. OBJECTIVE: We compared the postprandial responses of IGFs and IGFBP to 2 foods of similar macronutrient composition but with greatly different GIs-pearled barley (GI: 25) and instant mashed potato (GI: 85). DESIGN: Ten young lean subjects consumed 50-g carbohydrate portions of the 2 foods or water (extended fast) in random order after an overnight fast. Capillary blood was collected at regular intervals over 4 h for measurement of blood glucose, insulin, and components of the IGF system. RESULTS: Serum IGFBP-1 declined markedly after both meals, but the mean (+/-SEM) change at 4 h was significantly (P < 0.01) more prolonged after the low-GI meal (-55 +/- 20 ng/mL) than after the high-GI meal (-13 +/- 15 ng/mL). Conversely, the change in serum IGFBP-3 concentration at 4 h was significantly (P < 0.05) higher after the low-GI meal (251 +/- 102 ng/mL) than after the high-GI meal (-110 +/- 96 ng/mL); the same pattern was observed at 2 h. Changes in IGFBP-2, free IGF-1, and total IGF-1 responses were minimal and did not differ significantly from those during the 4-h fast. CONCLUSION: Acute changes in IGFBP-3 after low-GI and high-GI foods may provide a biologic mechanism linking cell multiplication with greater consumption of high-GI carbohydrates. Copyright © 2005 American Society for Clinical Nutrition [ABSTRACT FROM AUTHOR]

For at least 40-50000 years, plants played an important but supplementary role in the animal-dominated diet of Australian Aboriginal (AA) hunter-gatherers. New knowledge of the nutrient composition and the special physiological effects of their foods provides another perspective in the current debate on the composition of the 'prudent' diet and the diet on which humans evolved. In the present paper we have calculated the average nutrient composition of over 800 Aboriginal plant foods (in total and by food group) and highlighted the differences between these and modern cultivated foods. The data enable us to calculate the absolute contribution of plant foods to total food and nutrient intake of traditional living AA. If plants provided 20-40% of the energy in the diet (the most likely range), then plants would have contributed 22-44 g protein, 18-36 g fat, 101-202 g carbohydrate, 40-80 g fibre and 90-180 mg vitamin C in a 12 500 kJ (3000 kcal) diet. Since all the carbohydrate came from plant foods, the traditional AA diet would have been relatively low in carbohydrate (especially starch) but high in dietary fibre in comparison with current recommendations. Over half the carbohydrate could have been in the form of sugars derived from fruit and honey. The low glycaemic index of their carbohydrate foods, however, would generate a relatively low demand for insulin secretion and this characteristic may have protected AA from a genetic predisposition to insulin resistance and its consequences (non-insulin-dependent diabetes mellitus, coronary heart disease, obesity). The dietary pattern and active lifestyle of recent hunter-gatherers such as AA may be a reference standard for modern human nutrition and a model for defence against diseases of affluence. [ABSTRACT FROM AUTHOR]

Recent reports have suggested that the problem of childhood and adolescent obesity has been exaggerated in Australia, and that community-wide obesity prevention initiatives are not warranted; we argue that this is not an accurate reflection of the situation. Available data indicate that obesity affects 6%-8% of Australian schoolchildren, and that the proportion has continued to increase in recent years. Childhood and adolescent obesity is associated with a wide range of immediate health concerns, as well as increasing the risk of disease in adulthood. Some weight-related health problems are also found in overweight children. A range of strategies, including whole-of-community obesity prevention programs, will be required to tackle this problem. Concerns about disordered eating in children and adolescents should not preclude appropriate action on childhood obesity. [ABSTRACT FROM AUTHOR]

BACKGROUND: Many laboratories offer glycemic index (GI) services. OBJECTIVE: We assessed the performance of the method used to measure GI. DESIGN: The GI of cheese-puffs and fruit-leather (centrally provided) was measured in 28 laboratories (n=311 subjects) by using the FAO/WHO method. The laboratories reported the results of their calculations and sent the raw data for recalculation centrally. RESULTS: Values for the incremental area under the curve (AUC) reported by 54% of the laboratories differed from central calculations. Because of this and other differences in data analysis, 19% of reported food GI values differed by >5 units from those calculated centrally. GI values in individual subjects were unrelated to age, sex, ethnicity, body mass index, or AUC but were negatively related to within-individual variation (P=0.033) expressed as the CV of the AUC for repeated reference food tests (refCV). The between-laboratory GI values (mean+/-SD) for cheese-puffs and fruit-leather were 74.3+/-10.5 and 33.2+/-7.2, respectively. The mean laboratory GI was related to refCV (P=0.003) and the type of restrictions on alcohol consumption before the test (P=0.006, r2=0.509 for model). The within-laboratory SD of GI was related to refCV (P<0.001), the glucose analysis method (P=0.010), whether glucose measures were duplicated (P=0.008), and restrictions on dinner the night before (P=0.013, r2=0.810 for model). CONCLUSIONS: The between-laboratory SD of the GI values is approximately 9. Standardized data analysis and low within-subject variation (refCV<30%) are required for accuracy. The results suggest that common misconceptions exist about which factors do and do not need to be controlled to improve precision. Controlled studies and cost-benefit analyses are needed to optimize GI methodology. The trial was registered at clinicaltrials.gov as NCT00260858. Copyright © 2008 American Society for Nutrition [ABSTRACT FROM AUTHOR]

Although weight loss can be achieved by any means of energy restriction, current dietary guidelines have not prevented weight regain or population-level increases in obesity and overweight. Many high-carbohydrate, low-fat diets may be counterproductive to weight control because they markedly increase postprandial hyperglycemia and hyperinsulinemia. Many high-carbohydrate foods common to Western diets produce a high glycemic response [high-glycemic-index (GI) foods], promoting postprandial carbohydrate oxidation at the expense of fat oxidation, thus altering fuel partitioning in a way that may be conducive to body fat gain. In contrast, diets based on low-fat foods that produce a low glycemic response (low-GI foods) may enhance weight control because they promote satiety, minimize postprandial insulin secretion, and maintain insulin sensitivity. This hypothesis is supported by several intervention studies in humans in which energy-restricted diets based on low-GI foods produced greater weight loss than did equivalent diets based on high-GI foods. Long-term studies in animal models have also shown that diets based on high-GI starches promote weight gain, visceral adiposity, and higher concentrations of lipogenic enzymes than do isoenergetic, macronutrientcontrolled, low-GI-starch diets. In a study of healthy pregnant women, a high-GI diet was associated with greater weight at term than was a nutrient-balanced, low-GI diet. In a study of diet and complications of type 1 diabetes, the GI of the overall diet was an independent predictor of waist circumference in men. These findings provide the scientific rationale to justify randomized, controlled, multicenter intervention studies comparing the effects of conventional and low-GI diets on weight control. Copyright © 2002 American Society for Clinical Nutrition [ABSTRACT FROM AUTHOR]

In observational studies, habitual coffee consumption has been linked to a lower risk of type 2 diabetes. We hy-pothesized that the mechanism may be related to delayed effects on postprandial glycemia. The aim of this study is to investigate the glycemic and insulinemic effects of consumption of caffeinated and decaffeinated coffee, sweetened and unsweetened, tea and sucrose, 1 h prior to a high carbohydrate meal. On separate occasions in random order, lean young healthy subjects (n = 8) consumed a potato-based meal 1 hour after consumption of 250 mL of black coffee (COF), black coffee sweetened with 10 g of sucrose (COF+SUC), decaffeinated coffee (DECAF), black tea (TEA), 10 g sucrose (SUC) or hot water (CON). Fingerprick blood samples were taken at regular intervals over 2 h and the glucose and insulin responses quantified as area under the curve. Compared to CON, COF caused a 28% increase in postprandial glycemia (p = 0.022). In contrast, COF+SUC decreased glycemia compared with either COF (-38%, p<0.001) or CON (-20%, p = 0.100) but had no effect on insulin responses. DECAF, TEA and SUC had no significant effects on postprandial responses. SUC and DECAF reduced the absolute glucose concentration at the start of the meal (p<0.01). In conclusion, only sweetened coffee significantly reduces postprandial glycemia. This observation may explain the paradoxical findings of observational and clinical studies relating coffee drinking to diabetes risk. [ABSTRACT FROM AUTHOR]

Background: Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, >50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk., Objectives: This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss., Methods: We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over 8 wk. High-coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using differential lipid abundance comparisons and partial least squares discriminant analyses. Associations between lipid changes and clinical characteristics were determined by Spearman correlation and Bootstrap Forest of ensemble machine learning model. Baseline lipids, predictive of glycemic parameters changes postweight loss, were assessed using Bootstrap Forest analyses., Results: We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids, and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine increased significantly. Changes in certain lipid species (e.g., saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids, and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and homeostasis model assessment of insulin resistance., Conclusions: Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. The PREVIEW lifestyle intervention study was registered at clinicaltrials.gov as NCT01777893 (https://clinicaltrials.gov/study/NCT01777893)., Competing Interests: Conflict of interest JCB-M is the President and Director of the Glycemic Index Foundation, oversees a glycemic index testing service at The University of Sydney, and is a co-author of books about diet and diabetes. She is a member of the Scientific Advisory Boards of the Novo Foundation and Global Zoe P/L. All other authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work and report no conflicts of interest., (Copyright © 2024 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Background: Ultraprocessed foods (UPFs) comprise most calories in the United States diet. Glycemic index (GI) and glycemic load (GL) are measures of the quality and quantity of carbohydrates in food based on their effect on postprandial blood glucose. Diets high in UPFs and GI/GL are associated with chronic metabolic diseases but the relationship between them is unclear., Objectives: Our objective was to examine the GI and GL of foods assigned to NOVA food processing groups. We hypothesized that GI and GL would be lowest in minimally processed foods (MPFs) compared to processed food (PRF) and UPF (with no difference between PRF and UPF)., Methods: GI and GL values produced by healthy individuals for 1995 food items were collated from published sources. Food items were manually coded by processing levels according to NOVA classification. In addition, as the effects of processing on glycemic potential may vary between types of foods, food items were coded into 8 groups (beans, nuts, and seeds; beverages; dairy; fats and sweets; fruit; grains; fish, meat, and poultry; and vegetables). Multilevel linear modeling was used to determine significance with an α value of 0.05., Results: The effect of food processing on GI and GL was contrary to our hypothesis as means did not differ significantly across processing levels: GI-MPF: 54.1 ± 19.5, PRF: 53.2 ± 18.9, UPF: 49.3 ± 18.1 (P = 0.712); GL-MPF: 17.1 ± 10.3, PRF: 15.8 ± 12.4, UPF; 11.5 ± 7.9 (P = 0.890). Within food groups, there was no significant association between processing level and GI (P = 0.184), but GL was inversely associated with grains and vegetables (P < 0.001)., Conclusions: Across analyzed foods, GI and GL do not differ between processing levels, whereas GL was lower in ultraprocessed grains and vegetables than MPF. Any potential adverse outcomes associated with UPF are unlikely to be related to effects on glycemia. This project was preregistered at the Open Science Framework (OSF) Registries through the Center for Open Science as 10.17605/OSF.IO/PJWG9., (Copyright © 2024 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

This virtual (online) study tested the common but largely untested assumptions that food energy density, level of processing (NOVA categories), and carbohydrate-to-fat (CF) ratio are key determinants of food reward. Individual participants (224 women and men, mean age 35 y, 53% with healthy weight, 43% with overweight or obesity) were randomised to one of three, within-subjects, study arms: energy density (32 foods), or level of processing (24 foods), or CF ratio (24 foods). They rated the foods for taste pleasantness (liking), desire to eat (food reward), and sweetness, saltiness, and flavour intensity (for analysis averaged as taste intensity). Against our hypotheses, there was not a positive relationship between liking or food reward and either energy density or level of processing. As hypothesised, foods combining more equal energy amounts of carbohydrate and fat (combo foods), and foods tasting more intense, scored higher on both liking and food reward. Further results were that CF ratio, taste intensity, and food fibre content (negatively), independent of energy density, accounted for 56% and 43% of the variance in liking and food reward, respectively. We interpret the results for CF ratio and fibre in terms of food energy-to-satiety ratio (ESR), where ESR for combo foods is high, and ESR for high-fibre foods is low. We suggest that the metric of ESR should be considered when designing future studies of effects of food composition on food reward, preference, and intake., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest in relation to this research., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Kombucha is a complex probiotic beverage made from fermented tea, yet despite extensive historical, anecdotal, and in-vivo evidence for its health benefits, no controlled trials have been published on its effect on humans., Methods: We conducted a randomised placebo-controlled, cross-over study that examined the Glycemic Index (GI) and Insulin Index (II) responses after a standardised high-GI meal consumed with three different test beverages (soda water, diet lemonade soft drink and an unpasteurised kombucha) in 11 healthy adults. The study was prospectively registered with the Australian New Zealand Clinical Trials Registry (anzctr.org.au: 12620000460909). Soda water was used as the control beverage. GI or II values were calculated by expressing the 2-h blood glucose or insulin response as a percentage of the response produced by 50 g of glucose dissolved in water., Results: There was no statistically significant difference in GI or II between the standard meal consumed with soda water (GI: 86 and II: 85) or diet soft drink (GI: 84 and II: 81, ( p = 0.929 for GI and p = 0.374 for II). In contrast, when kombucha was consumed there was a clinically significant reduction in GI and II (GI: 68, p = 0.041 and II: 70, p = 0.041) compared to the meal consumed with soda water., Discussion: These results suggest live kombucha can produce reductions in acute postprandial hyperglycemia. Further studies examining the mechanisms and potential therapeutic benefits of kombucha are warranted., Competing Interests: FA and JB-M manage The University of Sydney’s glycemic index testing service and are directors of the Glycemic Index Foundation, a not-for-profit health promotion charity. FA and JB-M are authors of books in The New Glucose Revolution series (De Capo, Cambridge, MA). MC is a consultant to The Good Brew Company and co-owner of Extremely Alive Pty Ltd., which produces wellness tonics based on Good Brew Kombucha. He was involved in the design of the study, writing the manuscript and decision to publish the results. He was not involved in the collection, analyses, or interpretation of data. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Atkinson, Cohen, Lau and Brand-Miller.)

Background: Reliable tables of glycemic indexes (GIs) and glycemic loads (GLs) are critical to research examining the relationship between glycemic qualities of carbohydrate in foods, diets, and health. In the 12 years since the last edition of the tables, a large amount of new data has become available., Objectives: To systematically review and tabulate published and unpublished sources of reliable GI values, including an assessment of the reliability of the data., Methods: This edition of the tables lists over 4000 items, a 61% increase in the number of entries compared to the 2008 edition. The data have been separated into 2 lists. The first represents more precise values derived using the methodology recommended by the International Standards Organization (∼2100 items). The second list contains values determined using less robust methods, including using limited numbers of healthy subjects or with a large SEM (∼1900 food items)., Results: Dairy products, legumes, pasta, and fruits were usually low-GI foods (≤55 on the 100-point glucose scale) and had consistent values around the world. Cereals and cereal products, however, including whole-grain or whole-meal versions, showed wide variation in GI values, presumably arising from variations in manufacturing methods. Breads, breakfast cereals, rice, savory snack products, and regional foods were available in high-, medium-, and low-GI versions. Most varieties of potato were high-GI foods, but specific low-GI varieties have now been identified., Conclusions: The availability of new data on the GIs of foods will facilitate wider research and application of the twin concepts of GI and GL. Although the 2021 edition of the tables improves the quality and quantity of GI data available for research and clinical practice, GI testing of regional foods remains a priority. This systematic review was registered in PROSPERO as #171204., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Background: Individuals with pre-diabetes are commonly overweight and benefit from dietary and physical activity strategies aimed at decreasing body weight and hyperglycemia. Early insulin resistance can be estimated via the triglyceride glucose index {TyG = Ln [TG (mg/dl) × fasting plasma glucose (FPG) (mg/dl)/2]} and the hypertriglyceridemic-high waist phenotype (TyG-waist), based on TyG x waist circumference (WC) measurements. Both indices may be useful for implementing personalized metabolic management. In this secondary analysis of a randomized controlled trial (RCT), we aimed to determine whether the differences in baseline TyG values and TyG-waist phenotype predicted individual responses to type-2 diabetes (T2D) prevention programs. Methods: The present post-hoc analyses were conducted within the Prevention of Diabetes through Lifestyle intervention and population studies in Europe and around the world (PREVIEW) study completers ( n = 899), a multi-center RCT conducted in eight countries (NCT01777893). The study aimed to reduce the incidence of T2D in a population with pre-diabetes during a 3-year randomized intervention with two sequential phases. The first phase was a 2-month weight loss intervention to achieve ≥8% weight loss. The second phase was a 34-month weight loss maintenance intervention with two diets providing different amounts of protein and different glycemic indices, and two physical activity programs with different exercise intensities in a 2 x 2 factorial design. On investigation days, we assessed anthropometrics, glucose/lipid metabolism markers, and diet and exercise questionnaires under standardized procedures. Results: Diabetes-related markers improved during all four lifestyle interventions. Higher baseline TyG index ( p < 0.001) was associated with greater reductions in body weight, fasting glucose, and triglyceride (TG), while a high TyG-waist phenotype predicted better TG responses, particularly in those randomized to physical activity (PA) of moderate intensity. Conclusions: Two novel indices of insulin resistance (TyG and TyG-waist) may allow for a more personalized approach to avoiding progression to T2D. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT01777893 reference, identifier: NCT01777893., Competing Interests: TL was employed by company NetUnion Sarl. PS has received travel grants from the Cambridge Weight Plan, UK. JB-M is the President and Director of the Glycemic Index Foundation, oversees a glycemic index GI testing service at the University of Sydney and is a co-author of books about diet and diabetes. IM is a member of the UK Government Scientific Advisory Committee on Nutrition, Treasurer of the Federation of European Nutrition Societies, Treasurer of the World Obesity Federation, member of the Mars Scientific Advisory Council, member of the Mars Europe Nutrition Advisory Board, and Scientific Adviser to the Waltham Centre for Pet Nutrition. He is also a member of the Nestle Research Scientific Advisory Board and of the Novozymes Scientific Advisory Board. SP was the Fonterra Chair in Human Nutrition and Principle Investigator for NZ National Science Challenge High Value Nutrition during the PREVIEW intervention. TML is an advisor for the “Sense” diet program. AR has received honorariums from Novo Nordisk A/S, the International Sweeteners Association, Nordic Sugar and Unilever. JM is the President of IUNS. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Navas-Carretero, San-Cristobal, Siig Vestentoft, Brand-Miller, Jalo, Westerterp-Plantenga, Simpson, Handjieva-Darlenska, Stratton, Huttunen-Lenz, Lam, Muirhead, Poppitt, Pietiläinen, Adam, Taylor, Handjiev, McNarry, Hansen, Brodie, Silvestre, Macdonald, Boyadjieva, Mackintosh, Schlicht, Liu, Larsen, Fogelholm, Raben and Martinez.)

The glycaemic index (GI) is a food metric that ranks the acute impact of available (digestible) carbohydrates on blood glucose. At present, few countries regulate the inclusion of GI on food labels even though the information may assist consumers to manage blood glucose levels. Australia and New Zealand regulate GI claims as nutrition content claims and also recognize the GI Foundation's certified Low GI trademark as an endorsement. The GI Foundation of South Africa endorses foods with low, medium and high GI symbols. In Asia, Singapore's Healthier Choice Symbol has specific provisions for low GI claims. Low GI claims are also permitted on food labels in India. In China, there are no national regulations specific to GI; however, voluntary claims are permitted. In the USA, GI claims are not specifically regulated but are permitted, as they are deemed to fall under general food-labelling provisions. In Canada and the European Union, GI claims are not legal under current food law. Inconsistences in food regulation around the world undermine consumer and health professional confidence and call for harmonization. Global provisions for GI claims/endorsements in food standard codes would be in the best interests of people with diabetes and those at risk.

Sugary carbohydrate foods have long been associated with increased risk of dental caries formation, but the dental health impact of starchy carbohydrates, particularly those with a high glycemic index (GI), has not been well examined., Aim: To investigate the effect of different starchy foods varying in their GI, on acute changes in dental plaque pH., Methods: In a series of sub-studies in healthy adults, common starchy carbohydrate foods, including white bread, instant mashed potatoes, canned chickpeas, pasta, breakfast cereals, white rice, and an oral glucose solution were consumed in fixed 25 g available carbohydrate portions. The change in dental plaque pH was assessed postprandially over 1 h and capillary plasma glucose was measured at regular intervals over 2 h., Results: Higher GI starchy foods produced greater acute plaque pH decreases and larger overall postprandial glucose responses compared to lower GI starchy foods (white bread compared with canned chickpeas: -1.5 vs. -0.7 pH units, p = 0.001, and 99 ± 8 mmol/L min vs. 47 ± 7 mmol/L min, p = 0.026). Controlling for other food factors (food form and nutritional composition), lower GI versions of matched food pairs produced smaller plaque pH excursions compared to higher GI versions of the same food. Using linear regression analysis, the GI value of starchy carbohydrate foods explained 60% of the variation in maximum plaque pH nadir and 64% of the variation in overall acute dental plaque pH excursion ( p < 0.01)., Conclusion: The findings imply that starchy foods, in particular those with a higher GI, may play a role in increasing the risk of dental caries.

Background: Previous research showed that weight-reducing diets increase appetite sensations and/or circulating ghrelin concentrations for up to 36 months, with transient or enduring perturbations in circulating concentrations of the satiety hormone peptide YY. Objective: This study assessed whether a diet that is higher in protein and low in glycemic index (GI) may attenuate these changes. Methods: 136 adults with pre-diabetes and a body mass index of ≥25 kg/m 2 underwent a 2-month weight-reducing total meal replacement diet. Participants who lost ≥8% body weight were randomized to one of two 34-month weight-maintenance diets: a higher-protein and moderate-carbohydrate (CHO) diet with low GI, or a moderate-protein and higher-CHO diet with moderate GI. Both arms involved recommendations to increase physical activity. Fasting plasma concentrations of total ghrelin and total peptide YY, and appetite sensations, were measured at 0 months (pre-weight loss), at 2 months (immediately post-weight loss), and at 6, 12, 24, and 36 months. Results: There was a decrease in plasma peptide YY concentrations and an increase in ghrelin after the 2-month weight-reducing diet, and these values approached pre-weight-loss values by 6 and 24 months, respectively ( P = 0.32 and P = 0.08, respectively, vs. 0 months). However, there were no differences between the two weight-maintenance diets. Subjective appetite sensations were not affected by the weight-reducing diet nor the weight-maintenance diets. While participants regained an average of ~50% of the weight they had lost by 36 months, the changes in ghrelin and peptide YY during the weight-reducing phase did not correlate with weight regain. Conclusion: A higher-protein, low-GI diet for weight maintenance does not attenuate changes in ghrelin or peptide YY compared with a moderate-protein, moderate-GI diet. Clinical Trial Registry: ClinicalTrials.gov registry ID NCT01777893 (PREVIEW) and ID NCT02030249 (Sub-study)., Competing Interests: RS serves on the Nestlé Health Science Optifast® VLCDTM™ Advisory Board. JB-M is the President of the Glycemic Index Foundation (a non-profit food endorsement program), oversees a glycemic index testing service at the University of Sydney and is the author of books about the glycemic index, food and healthy eating. AS owns 50% of the shares in Zuman International, a company which receives royalties for books she has written about weight management and payments for presentations at industry conferences. She has also received presentation fees and travel reimbursements from Eli Lilly and Co, the Pharmacy Guild of Australia, Novo Nordisk, the Dietitians Association of Australia, Shoalhaven Family Medical Centres, the Pharmaceutical Society of Australia, and Metagenics, and served on the Nestlé Health Science Optifast VLCD advisory board from 2016 to 2018. FA is a director of the Glycemic Index Foundation (a non-profit food endorsement program), manages a glycemic index testing service at the University of Sydney, and is a co-author of books about the glycemic index. Finally, Cambridge Weight Plan©, Ltd, UK provided all meal replacement products used at all sites of the PREVIEW Study. The commercial and funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, nor in the decision to publish the results. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Buso, Seimon, McClintock, Muirhead, Atkinson, Brodie, Dodds, Zibellini, Das, Wild-Taylor, Burk, Fogelholm, Raben, Brand-Miller and Sainsbury.)

High protein diets and low glycemic index (GI) diets have been associated with improved diet quality. We compared the changes in nutrient intakes of individuals at high risk of developing type-2 diabetes over 3 y who followed either a higher protein-lower GI diet (HPLG) or a conventional moderate protein-moderate GI diet (MPMG). This post hoc analysis included 161 participants with overweight and pre-diabetes from the Australian cohort of the PREVIEW study (clinical trial registered in https://www.clinicaltrials.gov/ct2/show/NCT01777893?term=NCT01777893&draw=2&rank=1) who were randomly assigned to a HPLG diet (25% energy from protein, dietary GI ≤ 50, n = 85) or a MPMG diet (15% energy from protein, dietary GI ≥ 56, n = 76). Food records were collected at 0-mo (baseline) and at 6-, 12-, 24-, and 36-mo (dietary intervention period). Linear mixed models were used to compare the differences in total energy, macro- and micronutrients, dietary GI, glycemic load (GL) and body weight between the two diet groups at the 4 dietary intervention time points. At 3 y, 74% participants from the HPLG diet and 74% participants from the MPMG diet completed the trial. The HPLG group showed significantly higher protein intake and lower dietary GI and GL than the MPMG group (group fixed effect P < 0.001 for all three parameters). By 6-, 12-, 24-, and 36-mo there was a 3.0, 2.7, 2.2, and 1.4% point difference in protein intake and 6.2, 4.1, 4.8, and 3.9 GI unit difference between the groups. The intake of energy and saturated fat decreased (mostly in the first 6-mo), while the intake of dietary fiber increased (from mo-0 to mo-12 only) in both diets, with no significant differences between the diets. The dietary intakes of zinc (group fixed effect P = 0.05), selenium ( P = 0.01), niacin ( P = 0.01), vitamin B12 ( P = 0.01) and dietary cholesterol (group by time fixed effect P = 0.001) were higher in the HPLG group than in the MPMG group. Despite both diets being designed to be nutritionally complete, a HPLG diet was found to be more nutritious in relation to some micronutrients, but not cholesterol, than a MPMG diet., Competing Interests: FA and JB-M manage The University of Sydney's glycemic index testing service and are directors of the Glycemic Index Foundation, a not-for-profit health promotion charity. JB-M is an author of books in The New Glucose Revolution series (De Capo, Cambridge, MA). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Meroni, Muirhead, Atkinson, Fogelholm, Raben and Brand-Miller.)

Purpose: Previous studies in older Australians have reported higher alcohol intake in those with low added sugar intake, yet the relationship between energy in liquid form [alcoholic beverages vs. sugar-sweetened beverages (SSB)] and measures of obesity has not been evaluated. We aimed to assess the association between the energy derived from SSB and alcoholic beverages, and to model the association between the substitution of SSB with alcoholic beverages and waist circumference., Methods: In this cross-sectional analysis, dietary data from the Australian Health Survey 2011-12 were analyzed. Participants with implausible dietary intake were excluded by applying the Goldberg cut-off. Usual SSB intake of adults ≥ 19 years old was estimated using the Multiple Source Method and participants were classified into zero-, low- or high-SSB consumers according to their usual SSB intake. Energy from alcoholic beverages in the three SSB consumption groups was compared using multivariable general linear models. A substitution model was used to assess the association between the replacement of SSB with alcoholic beverages and waist circumference., Results: Zero-SSB consumers made up 33% of the included participants. In all age groups, zero-SSB consumers had significantly higher energy intakes from alcoholic beverages than low- and high-SSB consumers. Low- and high-SSB consumers had similar consumption of alcoholic beverages. Substituting SSB intake with alcoholic beverage intake was not associated with significant differences in waist circumference in most age groups., Conclusions: Australian adults who avoid SSB are common but consume substantially more energy in the form of alcoholic beverages. An increase in alcoholic beverage intake could be an 'unintended consequence' of strictly discouraging SSB consumption.

Dietary fibre is a generic term describing non-absorbed plant carbohydrates and small amounts of associated non-carbohydrate components. The main contributors of fibre to the diet are the cell walls of plant tissues, which are supramolecular polymer networks containing variable proportions of cellulose, hemicelluloses, pectic substances, and non-carbohydrate components, such as lignin. Other contributors of fibre are the intracellular storage oligosaccharides, such as fructans. A distinction needs to be made between intrinsic sources of dietary fibre and purified forms of fibre, given that the three-dimensional matrix of the plant cell wall confers benefits beyond fibre isolates. Movement through the digestive tract modifies the cell wall structure and may affect the interactions with the colonic microbes (e.g., small intestinally non-absorbed carbohydrates are broken down by bacteria to short-chain fatty acids, absorbed by colonocytes). These aspects, combined with the fibre associated components (e.g., micronutrients, polyphenols, phytosterols, and phytoestrogens), may contribute to the health outcomes seen with the consumption of dietary fibre. Therefore, where possible, processing should minimise the degradation of the plant cell wall structures to preserve some of its benefits. Food labelling should include dietary fibre values and distinguish between intrinsic and added fibre. Labelling may also help achieve the recommended intake of 14 g/1000 kcal/day.

Background: Lower carbohydrate diets have the potential to improve glycemia but may increase ketonemia in women with gestational diabetes (GDM). We hypothesized that modestly lower carbohydrate intake would not increase ketonemia., Objective: To compare blood ketone concentration, risk of ketonemia, and pregnancy outcomes in women with GDM randomly assigned to a lower carbohydrate diet or routine care., Methods: Forty-six women aged (mean ± SEM) 33.3 ± 0.6 y and prepregnancy BMI 26.8 ± 0.9 kg/m2 were randomly assigned at 28.5 ± 0.4 wk to a modestly lower carbohydrate diet (MLC, ∼135 g/d carbohydrate) or routine care (RC, ∼200 g/d) for 6 wk. Blood ketones were ascertained by finger prick test strips and 3-d food diaries were collected at baseline and end of the intervention., Results: There were no detectable differences in blood ketones between completers in the MLC group compared with the RC group (0.1 ± 0.0 compared with 0.1 ± 0.0 mmol/L, n = 33, P = 0.31, respectively), even though carbohydrate and total energy intake were significantly lower in the intervention group (carbohydrate 165 ± 7 compared with 190 ± 9 g, P = 0.04; energy 7040 ± 240 compared with 8230 ± 320 kJ, P <0.01, respectively). Only 20% of participants in the MLC group met the target intake compared with 65% in the RC group (P <0.01). There were no differences in birth weight, rate of large-for-gestational-age infants, percent fat mass, or fat-free mass between groups., Conclusions: An intervention to reduce carbohydrate intake in GDM did not raise ketones to clinical significance, possibly because the target of 135 g/d was difficult to achieve in pregnancy. Feeding studies with food provision may be needed to assess the benefits and risks of low-carbohydrate diets. This trial was registered at www.anzctr.org.au as ACTRN12616000018415., (Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.)

An official method for determining food glycemic index (GI) was published by the Organization for International Standardization (ISO) in 2010, but its performance has not been assessed. Therefore, we aimed to determine the intra- and inter-laboratory variation of food GI values measured using the 2010 ISO method. Three laboratories (Australia, Canada and France) determined the GI and insulinemic-index (II) of six foods in groups of 13-15 participants using the 2010 ISO method and intra- and inter-laboratory Standard Deviations (SDs) were calculated. Overall mean food GIs varied from 47 to 86 ( p < 0.0001) with no significant difference among labs ( p = 0.57) and no food × laboratory interaction ( p = 0.20). Within-laboratory SD was similar among foods (range, 17.8-22.5; p = 0.49) but varied among laboratories (range 17.5-23.1; p = 0.047). Between-laboratory SD of mean food GI values ranged from 1.6 to 6.7 (mean, 5.1). Mean glucose and insulin responses varied among foods ( p < 0.001) with insulin ( p = 0.0037), but not glucose ( p = 0.054), varying significantly among labs. Mean II varied among foods ( p < 0.001) but not among labs ( p = 0.94). In conclusion, we found that using the 2010 ISO method, the mean between-laboratory SD of GI was 5.1. This suggests that the ISO method is sufficiently precise to distinguish a mean GI = 55 from a mean GI ≥ 70 with 97-99% probability., Competing Interests: T.M.W. and A.L.J. are employees and part-owners of INQUIS Clinical Research; neither they nor INQUIS have any financial interest in the sponsor, or any other food company. A.M. and S.V. are employees of Mondelez International. J.C.B.-M. and F.S.A. are directors of the Glycemic Index Foundation, manage a glycemic index testing service offered by the University of Sydney and a co-authors of books about the glycemic index of foods. D.G., S.L., M.C. and B.H. are employees of Biofortis Mérieux NutriSciences. The funders assisted in the design of the study and assisted in the writing of the manuscript and the decision to publish the results. The funders had no role in the collection or statistical analysis of the data.

While dietary factors are important modifiable risk factors for type 2 diabetes (T2D), the causal role of carbohydrate quality in nutrition remains controversial. Dietary glycemic index (GI) and glycemic load (GL) have been examined in relation to the risk of T2D in multiple prospective cohort studies. Previous meta-analyses indicate significant relations but consideration of causality has been minimal. Here, the results of our recent meta-analyses of prospective cohort studies of 4 to 26-y follow-up are interpreted in the context of the nine Bradford-Hill criteria for causality, that is: (1) Strength of Association, (2) Consistency, (3) Specificity, (4) Temporality, (5) Biological Gradient, (6) Plausibility, (7) Experimental evidence, (8) Analogy, and (9) Coherence. These criteria necessitated referral to a body of literature wider than prospective cohort studies alone, especially in criteria 6 to 9. In this analysis, all nine of the Hill's criteria were met for GI and GL indicating that we can be confident of a role for GI and GL as causal factors contributing to incident T2D. In addition, neither dietary fiber nor cereal fiber nor wholegrain were found to be reliable or effective surrogate measures of GI or GL. Finally, our cost-benefit analysis suggests food and nutrition advice favors lower GI or GL and would produce significant potential cost savings in national healthcare budgets. The high confidence in causal associations for incident T2D is sufficient to consider inclusion of GI and GL in food and nutrient-based recommendations.

Published meta-analyses indicate significant but inconsistent incident type-2 diabetes(T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is nowover a decade ago that a published meta-analysis used a predefined standard to identify validstudies. Considering valid studies only, and using random effects dose-response meta-analysis(DRM) while withdrawing spurious results ( p < 0.05), we ascertained whether these relationswould support nutrition guidance, specifically for an RR > 1.20 with a lower 95% confidence limit>1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). Thecombined T2D-GI RR was 1.27 (1.15-1.40) ( p < 0.001, n = 10 studies) per 10 units GI, while that forthe T2D-GL RR was 1.26 (1.15-1.37) ( p < 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet.The corresponding global DRM using restricted cubic splines were 1.87 (1.56-2.25) ( p < 0.001, n =10) and 1.89 (1.66-2.16) ( p < 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GLwere robustly associated with incident T2D. Together with mechanistic and other data, thissupports that consideration should be given to these dietary risk factors in nutrition advice.Concerning the public health relevance at the global level, our evidence indicates that GI and GLare substantial food markers predicting the development of T2D worldwide, for persons ofEuropean ancestry and of East Asian ancestry., Competing Interests: The following authors have no competing interests: Anette Buyken, Antonio Ceriello, Salwa Rizkalla, Richard Taylor, Antonia Trichopoulou, and Walter Willett. Arne Astrup is a consultant member of advisory boards for McCain Foods Limited, Canada, Weight Watchers, USA. He is a recipient of honoraria as a speaker for a wide range of Danish and international concerns and receives royalties from popular diet and cookery books using GI/GL. Livia Augustin has received an honorarium from the Nutrition Foundation of Italy (NFI) to co-organize a GI/GL summit. Sara Baer-Sinnott is the president of Oldways, a non-profit food and nutrition organization that receives support from a wide variety of organizations. Alan Barclay is a board member and consultant to the Glycemic Index Foundation, an international not-for-profit organization which endorses healthy low GI food products by means of a certified GI symbol. He is a co-author of lay books about the glycemic index of foods and sweeteners. Inger Bjorck is a retired professor from Lund University, Sweden, where she has managed the Antidiabetic Food Centre, a non-profitable research center including the academy, the health care system, and representatives from the industry. She is an inventor and owner of intellectual property related to the use of certain proteins, specific probiotics, and probiotics to improve glycemic regulation and metabolism. Jennie Brand-Miller is President of the Glycemic Index Foundation, an international not-for-profit organization, which endorses healthy low GI food products by means of a certified GI symbol. She manages a glycemic index testing service at the University of Sydney and is the co-author of lay books about the glycemic index of foods. Furio Brighenti is affiliated to a department of the University of Parma that does glycemic index analysis as a service to third parties. Marie-Ann Ha is a senior lecturer with Anglia Ruskin University, a Director with Cibus Biscuits Ltd., a company developing a product for people with additional energy requirements and is a Director of East Anglia Food Link, a not-for-profit organization working to increase local sourcing of local products. David Jenkins David Jenkins has received research grants from Saskatchewan Pulse Growers, the Agricultural Bioproducts Innovation Program through the Pulse Research Network, the Advanced Foods and Material Network, Loblaw Companies Ltd., Unilever Canada and Netherlands, Barilla, the Almond Board of California, Agriculture and Agri-food Canada, Pulse Canada, Kellogg’s Company, Canada, Quaker Oats, Canada, Procter & Gamble Technical Centre Ltd., Bayer Consumer Care, Springfield, NJ, Pepsi/Quaker, International Nut & Dried Fruit (INC), Soy Foods Association of North America, the Coca-Cola Company (investigator initiated, unrestricted grant), Solae, Haine Celestial, the Sanitarium Company, Orafti, the International Tree Nut Council Nutrition Research and Education Foundation, the Peanut Institute, Soy Nutrition Institute (SNI), the Canola and Flax Councils of Canada, the Calorie Control Council, the Canadian Institutes of Health Research (CIHR), the Canada Foundation for Innovation (CFI), and the Ontario Research Fund (ORF). He has received in-kind supplies for trials as research support from the Almond Board of California, Walnut Council of California, American Peanut Council, Barilla, Unilever, Unico, Primo, Loblaw Companies, Quaker (Pepsico), Pristine Gourmet, Bunge Limited, Kellogg Canada, WhiteWave Foods. He has been on the speaker’s panel, served on the scientific advisory board, and/or received travel support and/or honoraria from the Almond Board of California, Canadian Agriculture Policy Institute, Loblaw Companies Ltd., the Griffin Hospital (for the development of the NuVal scoring system), the Coca-Cola Company, EPICURE, Danone, Diet Quality Photo Navigation (DQPN), Better Therapeutics (FareWell), Verywell, True Health Initiative (THI), Institute of Food Technologists (IFT), Soy Nutrition Institute (SNI), Herbalife Nutrition Institute (HNI), Saskatchewan Pulse Growers, Sanitarium Company, Orafti, the American Peanut Council, the International Tree Nut Council Nutrition Research and Education Foundation, the Peanut Institute, Herbalife International, Pacific Health Laboratories, Nutritional Fundamentals for Health (NFH), Barilla, Metagenics, Bayer Consumer Care, Unilever Canada and Netherlands, Solae, Kellogg, Quaker Oats, Procter & Gamble, Abbott Laboratories, Dean Foods, the California Strawberry Commission, Haine Celestial, PepsiCo, the Alpro Foundation, Pioneer Hi-Bred International, DuPont Nutrition and Health, Spherix Consulting and WhiteWave Foods, the Advanced Foods and Material Network, the Canola and Flax Councils of Canada, Agri-Culture and Agri-Food Canada, the Canadian Agri-Food Policy Institute, Pulse Canada, the Soy Foods Association of North America, the Nutrition Foundation of Italy (NFI), Nutra-Source Diagnostics, the McDougall Program, the Toronto Knowledge Translation Group (St. Michael’s Hospital), the Canadian College of Naturopathic Medicine, The Hospital for Sick Children, the Canadian Nutrition Society (CNS), the American Society of Nutrition (ASN), Arizona State University, Paolo Sorbini Foundation and the Institute of Nutrition, Metabolism and Diabetes. He received an honorarium from the United States Department of Agriculture to present the 2013 W.O. Atwater Memorial Lecture. He received the 2013 Award for Excellence in Research from the International Nut and Dried Fruit Council. He received funding and travel support from the Canadian Society of Endocrinology and Metabolism to produce mini cases for the Canadian Diabetes Association (CDA). He is a member of the International Carbohydrate Quality Consortium (ICQC). His wife, ALJ, is a director and partner of Glycemic Index Laboratories, Inc., and his sister, CB, received funding through a grant from the St. Michael’s Hospital Foundation to develop a cookbook for one of his studies. Cyril Kendall has received research grants, travel funding, consultant fees, honoraria, or has served on the scientific advisory board for Abbott Laboratories, Advanced Food Materials Network, Agrifoods and Agriculture Canada (AAFC), Almond Board of California, American Peanut Council, American Pistachio Growers, Barilla, California Strawberry Commission, Calorie Control Council, Canadian Institutes of Health Research (CIHR), Canola Council of Canada, The Coca Cola Company (investigator initiated, unrestricted), Danone, General Mills, Hain Celestial, International Tree Nut Council, Kellogg, Kraft, Loblaw Brands Ltd., Nutrition Foundation of Italy, Oldways Preservation Trust, Orafti, Paramount Farms, Peanut Institute, Pepsi-Co, Pulse Canada, Saskatchewan Pulse Growers, Solae, Sun-Maid, Tate & Lyle and Unilever. Carlo La Vecchia is member of the Advisory Board of the Nutrition Foundation of Italy (NFI, honorary) and received honoraria from Soremartec and MSL Italia. Geoffrey Livesey, husband of author HFL, holds shares in Independent Nutrition Logic Ltd., a consultancy. He and his wife have benefitted from research grants, travel funding, consultant fees, and honoraria from the American Association for the Advancement of Science (USA), the All Party Parliamentary Group for Diabetes (London, UK), Almond Board of California (USA), BENEO GmbH (DE), Biotechnology and Biosciences Research Council (UK), British Nutrition Foundation(UK), Calorie Control Council (USA), Cantox (CA), Colloides Naturel International (FR), Coca Cola (UK), Danisco (UK & Singapore), Diabetes Nutrition Study Group (EASD, EU), DiabetesUK (UK), Elsevier Inc. (USA), European Commission (EU), European Polyol Association (Brussels), Eureka (UK), Food and Agricultural Organization (Rome), Granules India (Ind), General Mills (USA), Health Canada (CA), Institute of Food Research (UK), International Carbohydrate Quality Consortium (CA), Institute of Medicine (Washington, DC), International Life Sciences Institute (EU & USA), Life Sciences Research Office, FASEB (USA), Nutrition Society of Australia, Knights Fitness (UK), Leatherhead Food Research (UK), LitghterLife (UK), Matsutani (JPN), Medical Research Council (UK), MSL Group (UK), Porter Novelli (UK), Sudzuker (DE), Sugar Nutrition/WSRO (UK), Tate & Lyle (UK), The Food Group (USA), Weight Watchers (UK), Wiley-Blackwell (UK). World Health Organization (Geneva). He is a member of the EASD Nutrition Guidelines Committee. Helen Livesey, wife of Geoffrey Livesey, holds shares in Independent Nutrition Logic Ltd. (UK) and has benefitted from organizations declared by him. Simin Liu received consulting fees from Stanford University, Fred Hutchinson Cancer Research Center, honoraria from General Mills Co, and is a consultant to Barilla, Palma, Italy. Andrea Poli is the President of the Nutrition Foundation of Italy (NFI) a non-profit organization partially supported by Italian and non-Italian Food Companies. Jordi Salas-Salvadó serves on the board of, and has received grant through, his institution from the International Nut and Dried Fruit Council and the Eroski Foundation. He serves on the Executive Committee of the Instituto Danone Spain and on the Scientific Committee of the Danone International Institute. He has received research support from the Instituto de Salud Carlos III, Spain; the Ministerio de Educación years Ciencia, Spain; the Departament de Salut Pública de la Generalitat de Catalunya, Catalonia, Spain; and the European Commission. Further research support has come from the California Walnut Commission, Sacramento CA, USA; the Patrimonio Comunal Olivarero, Spain; the La Morella Nuts, Spain; and Borges S.A., Spain. He reports receiving consulting fees or travel expenses from Danone; California Walnut Commission, the Eroski Foundation, the Instituto Danone–Spain, Nuts for Life, Australian Nut Industry Council, Nestlé, Abbot Laboratories, and Font Vella Lanjarón. He is on the Clinical Practice Guidelines Expert Committee of the European Association for the study of Diabetes (EASD), and has served on the Scientific Committee of the Spanish Food and Safety Agency, and the Spanish Federation of the Scientific Societies of Food, Nutrition and Dietetics. He is an Executive Board Member of the Diabetes and Nutrition Study Group (DNSG) of the EASD. Gabriele Riccardi is a member of the scientific advisory board of Barilla Center for Food and Nutrition. John L Sievenpiper received research support from the Canadian Foundation for Innovation, Ontario Research Fund, Province of Ontario Ministry of Research and Innovation and Science, Canadian Institutes of health Research (CIHR), Diabetes Canada, PSI Foundation, Banting and Best Diabetes Centre (BBDC), American Society for Nutrition (ASN), INC International Nut and Dried Fruit Council Foundation, National Dried Fruit Trade Association, The Tate and Lyle Nutritional Research Fund at the University of Toronto, The Glycemic Control and Cardiovascular Disease in Type 2 Diabetes Fund at the University of Toronto (a fund established by the Alberta Pulse Growers), and the Nutrition Trialists Fund at the University of Toronto (a fund established by an inaugural donation from the Calorie Control Council). He has received in-kind food donations to support a randomized controlled trial from the Almond Board of California, California Walnut Commission, American Peanut Council, Barilla, Unilever, Unico/Primo, Loblaw Companies, Quaker, Kellogg Canada, and WhiteWave Foods.  He has received travel support, speaker fees and/or honoraria from Diabetes Canada, Mott’s LLP, Dairy Farmers of Canada, FoodMinds LLC, International Sweeteners Association, Nestlé, Pulse Canada, Canadian Society for Endocrinology and Metabolism (CSEM), GI Foundation, Abbott, Biofortis, ASN, Northern Ontario School of Medicine, INC Nutrition Research & Education Foundation, European Food Safety Authority (EFSA), and Physicians Committee for Responsible Medicine. He has or has had ad hoc consulting arrangements with Perkins Coie LLP, Tate & Lyle, and Wirtschaftliche Vereinigung Zucker e.V. He is a member of the European Fruit Juice Association Scientific Expert Panel. He is on the Clinical Practice Guidelines Expert Committees of Diabetes Canada, European Association for the study of Diabetes (EASD), Canadian Cardiovascular Society (CCS), and Obesity Canada. He serves or has served as an unpaid scientific advisor for the Food, Nutrition, and Safety Program (FNSP) and the Technical Committee on Carbohydrates of the International Life Science Institute (ILSI) North America. He is a member of the International Carbohydrate Quality Consortium (ICQC), Executive Board Member of the Diabetes and Nutrition Study Group (DNSG) of the EASD, and Director of the Toronto 3D Knowledge Synthesis and Clinical Trials foundation. His wife is an employee of Sobeys Inc. Thomas Wolever is a part owner and receives payment as the President and Medical Director of Glycemic Index Laboratories, Inc., (GI Labs, a contract research organization) and Glycemic Index Testing, Inc., (GI Testing, which supplies services to GI Labs) Toronto, Canada. He has authored or co-authored several books on the glycemic index for which has received royalties from Phillipa Sandall Publishing Services and CABI Publishers. He has received research support, consultant fees or honoraria from or served on the scientific advisory board for Canadian Institutes of Health Research, Canadian Diabetes Association, Dairy Farmers of Canada, Agriculture Agri-Food Canada, Public Health Agency of Canada, GI Labs, GI Testing, Abbott, Proctor and Gamble, Mars Foods, McCain Foods, Bunge, Temasek Polytechnic Singapore, Northwestern University, Royal Society of London, Glycemic Index Symbol program, CreaNutrition AG, McMaster University, University of Manitoba, University of Alberta, Canadian Society for Nutritional Sciences, National Sports and Conditioning Association, Faculty of Public Health and Nutrition—Autonomous University of Nuevo Leon, Diabetes and Nutrition Study Group of the European Association for the Study of Diabetes (EASD). His wife is part owner of Glycemic Index Laboratories, Inc., and Glycemic Index Testing, Inc., and receives payment as chief financial officer of both corporations. All authors other than HFL and RT are members of the International Carbohydrate Quality Consortium.