Glycemic Index Versus Wheat Fiber on Arterial Wall Damage in Diabetes: A Randomized Controlled Trial

Refined carbohydrate foods are recommended against, internationally, as part of the strategy to reduce the risk of cardiovascular disease (CVD). Diets high in whole grains and cereal fiber are promoted widely, as are low glycemic index (GI) diets, in many jurisdictions (e.g., Australia and Canada). This advice is driven by evidence of prospective cohort studies that have noted reductions in both diabetes (1,2) and CVD (3–6). However, in no instance have clinical trials been undertaken to support current carbohydrate advice, although meta-analyses of randomized controlled trials have been undertaken that demonstrate, for example, the effect of low-GI diets in reducing CVD risk factors, including lipids, blood glucose, and C-reactive protein (CRP) (7). In the absence of trials with clinical CVD outcomes, we believed it important to determine whether low-GI diets affected outcomes that are closer to a CVD event. Arterial damage has been associated with CVD morbidity and mortality, and we have the ability to measure arterial damage and plaque formation as vessel wall volume (VWV) by MRI of the carotid arteries. We therefore studied otherwise healthy men and women with type 2 diabetes and with evidence of possible future CVD risk, assessed as carotid intima media thickness of ≥1.2 mm. We assumed that those with diabetes would be more likely to show the effects of dietary change over the 3-year study.

A detailed account of the design and methods of this trial has been published (8). Subjects were recruited by advertisements and from previous studies, and 169 participants were eligible and randomized (Supplementary Fig. 1). Recruitment took place from December 2010 to June 2013, with the last follow-up visit in July 2016. Eligible participants were men or postmenopausal women with type 2 diabetes who took antihyperglycemic agents and had a minimum intima media thickness by ultrasound of ≥1.2 mm (Supplementary Text 1).

The study was a 3-year randomized parallel study with two treatments consisting of advice to select low-GI foods versus to increase consumption of wheat-fiber, where possible using whole-grain products. After stratification by sex, HbA_1c (>7.1%), smoking, and statin use, randomization was performed using participant ID by a statistician in a separate geographic location (Supplementary Text 2). The analytical technicians, MRI technologists, and experts who assessed and measured the MRIs were also blinded. However, the dietitians and the participants could not be blinded. Participants were seen at a teaching hospital affiliated with the University of Toronto for screening, week −1, baseline, and at 3-month intervals throughout the 3-year intervention. At each center visit, participants were weighed, a fasting blood sample was taken, and blood pressure was measured. In addition, participants brought their 7-day food record covering the week prior to the visit to discuss with the dietitian and document self-reported adherence. At baseline and years 1 and 3, participants underwent MRI of their carotid arteries.

The primary outcome was change in VWV, with blood measurements, blood pressure, and anthropometric measurements as secondary outcomes.

Details of the low-GI and wheat-fiber diets have been published (8,9). These diets also conformed to the advice given in our previous 6-month trial of a low-GI diet (9). The low-GI dietary advice emphasized low-GI oat bran and psyllium breads, peas, beans, and lentils, pasta, and temperate climate fruit, while the wheat-fiber diet emphasized 100% whole-meal and whole-grain wheat breads, and 100% whole wheat cereal products and breakfast cereals (further details are given in Supplementary Tables 1 and 2).

Maximum compliance goals were calculated from the 1-day dietary records used for participant instruction to illustrate the ideal composition of the low-GI and cereal-fiber diets (Supplementary Table 2). In these illustrative diets, all cereal foods were truly whole grain and the lowest GI options were selected for carbohydrate foods. Under these ideal conditions the low-GI diet could achieve a GI of 57 (bread scale with white bread GI = 100) and the cereal fiber diet would provide 15 g/2,000 kcal diet. The St. Michael’s Hospital Research Ethics Board and the University of Toronto approved the study. Written consent was obtained from all participants (ClinicalTrials.Gov identifier: NCT01063374).

At screening, intima media thickness was assessed by two-dimensional B-mode carotid ultrasound on a Philips iU22 ultrasound system (Philips Healthcare, Andover, MA) at Sunnybrook Health Sciences Center, Toronto, Ontario, Canada.

MRI scans were performed at the Sunnybrook Health Sciences Center Medical Imaging Department’s MRI research unit, using a Philips 3-Tesla whole-body scanner (Philips Healthcare, Markham, Ontario, Canada) with a 16-channel neurovascular coil (16-NV-SENSE). The cardiovascular imaging software VesselMASS (Medis, Leiden, Netherlands) was used for image analysis. Image grading (1–5) was performed, and images of poor quality (grade <3) or missing images were excluded from analyses. Three trained independent readers identified lumen and outer wall contours for all the participants. The software automatically generated VWV. Intraclass correlation values for measurements were >0.9 (good to excellent). This process, together with reader training, took ∼9 months after study completion.

Bloods samples were analyzed every 3 months for most measures, but CRP was assessed from samples at months 6, 12, 24, and 36. HbA_1c, blood glucose, and measures of renal function (serum creatinine and urea) were measured in the hospital’s routine analytical laboratory. Estimated glomerular filtration rate (eGFR) was calculated using a standard formula (10). Serum samples stored at −70°C were analyzed for lipids. LDL-cholesterol (C) was calculated by the method of Friedewald (11), and the cardiovascular risk score was calculated using the Framingham equation (12) at month 36.

Using MRI, the primary outcome was the treatment difference in the change in VWV, where the effect size was chosen as 54 mm³ (∼5% of baseline) (Supplementary Text 4), with a SD of the change of 109.8 mm³ (13), P < 0.05, power of 80%, and a dropout rate of 25%, leading to a requirement of 80 participants for each treatment.

The primary analysis (as prespecified) (8) compared the difference in the change in VWV from baseline to year 3, adjusted for baseline VWV, using a mixed model for repeated measures that accounted for within-subject correlation of repeated measures (PROC MIXED in SAS 9.4) (Supplementary Text 5 and Supplementary Table 3). All randomized participants with postrandomization MRI data were included in the intention-to-treat analyses, acknowledging that 19 participants did not have postintervention data due to attrition or poor MRI imaging quality (n = 9 low GI and n = 10 cereal fiber). For secondary outcomes repeated-measures ANCOVA was also used for all participants except for nine without postintervention data (n = 2 low GI and n = 7 cereal fiber). Descriptive results are expressed as means and SDs (Table 1). Data for outcomes that were not normally distributed were transformed (ln) (Table 2).

Potential baseline covariates were prespecified based on their possible influence on the primary outcome (age, sex, duration of diabetes, waist circumference, lipid-lowering medications use, dichotomous HbA_1c, baseline VWV, smoking, blood pressure, history of CVD, baseline GI, saturated fat intake, dietary cholesterol, and dietary pulse and nut intake) (8). To determine the relevant covariates, we used backward and forward regression to identify those covariates that should be retained in the model (P < 0.1) (Supplementary Table 4). Nonnormally distributed residuals were assessed after ln transformation. Treatment differences in compliance measures (e.g., HbA_1c) were also assessed by unadjusted paired t test at all time points throughout the 3-year trial using ln-transformed data to correct for skewed distribution and determine whether effects were transient or maintained. As an additional perspective on compliance, we also assessed per-protocol data (i.e., those who attended all 12 postintervention study visits and undertook all three MRI tests).

A post hoc analysis was undertaken to determine whether the change in VWV on the low-GI diet met the criterion for noninferiority compared with the change on the high wheat-fiber diet using 75%, 50%, and 25% of the prespecified treatment difference (54 mm³) (14).

Of the 169 randomized participants (Supplementary Fig. 1 and Supplementary Table 5), 134 completed the study (Supplementary Table 6). No differences were seen between the completion rates on the low-GI (69 of 86) and wheat-fiber diets (65 of 83).

Adherence to the ideal low-GI and wheat-fiber diets was very low, with only 6 participants (8.3%) on the low-GI diet at 3 years achieving a dietary GI of ≤57, and on the wheat-fiber diet, 11 participants (15.9%) at 1 year, and 7 participants (10.6%) at 3 years achieving an intake ≥15 g of wheat fiber per 2,000 kcal. The mean GI at years 1 and 3 was 66.6 and 67.3, and the corresponding cereal fiber figures were 6.5 g/2,000 kcal and 5.6 g/2,000 kcal (Supplementary Table 7).

The treatment difference at 3 years in GI, assessed as the change from baseline, was significant ([ln] −0.19; 95% CI −0.22, −0.16; P = 0.001) (Supplementary Table 8). Total fiber intake increased on both treatments (Supplementary Tables 7 and 8). The treatment difference in wheat fiber after transformation for nonnormally distributed data was significant for 1 year ([ln] −0.42 g/1,000 kcal; 95% CI −0.72, −0.12; P = 0.006) and 3 years ([ln] −0.46 g/1,000 kcal; 95% CI −0.8, −0.12; P = 0.009) (Supplementary Tables 7 and 8). There were no treatment differences in changes in medication use over the 3-year trial; however, participants on the low-GI diet were somewhat more likely to decrease use of lipid-lowering medications (16% of participants) than those on the wheat-fiber diet (11%), although similar proportions of participants increased their use of these medications (19% on the low-GI diet, and 20% on the wheat-fiber diet) (Supplementary Table 9).

The changes over the 3-year period in the VWV were very small (Tables 1 and 2), with no treatment difference between low-GI and wheat-fiber diets in the primary outcome (−15 mm³; 95% CI −40, 11; P = 0.260). However, noninferiority of the low-GI diet compared with the wheat-fiber diet was demonstrated between the treatments as change in VWV at 3 years at 75% (P < 0.001), 50% (P = 0.002), and 25% (P = 0.021) of the prespecified treatment difference (Fig. 1), indicating that the low-GI diet was not inferior therapeutically to the whole wheat diet. There was also no 1-year treatment difference (4 mm³; 95% CI −21, 29; P = 0.768). In addition, over the 3 years, an increase of 23 mm³ (95% CI 4, 41) was seen on the wheat-fiber diet (P = 0.016) that was not seen on the low-GI treatment, at 8 mm³ (95% CI −10, 26; P = 0.381). The increase in VWV at 3 years in the wheat-fiber diet was only significant in the left carotid artery (Supplementary Table 10), possibly related to more direct pulse pressure from the heart. No treatment or within-treatment differences were seen in the changes in arterial lumen volume or in the outer wall volume (Supplementary Table 11).

In the intention-to-treat analysis, using all postbaseline data, the treatment difference in HbA_1c, assessed as a reduction from baseline, was greater on the low-GI diet at 3, 6, and 9 months than on the wheat-fiber diet (Supplementary Table 12A and Fig. 2). Using the attendance at all visits and for all MRI tests as an objective indicator of adherence, as the per-protocol analysis, the reduction in HbA_1c was extended from 9 to 15 months, suggesting increased effectiveness of the low-GI diet with increased adherence (Supplementary Table 12B). Body weight was significantly reduced up to 12 months in the intention-to-treat analysis and also extended to 15 months in the per-protocol analyses (Supplementary Table 13A and B and Fig. 2).

The eGFR showed no significant change at 3 years on the low-GI diet. However, there was a small decrease in eGFR on the wheat-fiber diet, resulting in a relatively higher eGFR on the low-GI diet, and hence, a treatment difference of ([ln] 0.04 mL/min/1.73 m²; 95% CI 0.01, 0.08; P = 0.017) (Table 2 and Fig. 2).

Small treatment differences were seen, with an increase in triglycerides and a reduction in HDL-C, CRP, and pulse on the low-GI diet (Table 2), but only for CRP did the treatment difference result from a significant reduction on the low-GI diet (Table 2 and Supplementary Tables 14 and 15). For triglyceride, HDL-C, and pulse, the treatment difference resulted from the change following wheat fiber consumption. There were no treatment differences in other measures or Framingham Risk Score (12) (Table 2).

There were two significant differences in baseline values between completers (n = 134) and noncompleters (n = 35) (Supplementary Table 6). Adjustment for the two significant baseline differences, VWV and triglyceride, made little difference to the results in Table 2, although the significance of the relative reduction in HDL-C was lost (Supplementary Table 16).

Baseline values were also similar between treatments (Supplementary Table 5). The exceptions were the HDL-C and the ratio of LDL-C to HDL-C values. When these measures were added as covariates to the model used to generate Table 2, only the significance for the small increase in triglyceride was lost (P = 0.082) (Supplementary Table 17).

We also assessed whether a significant difference in the change in dietary components (Supplementary Table 8) might influence the outcomes in Table 2. After controlling for significant differences, polyunsaturated fatty acids, total fiber, and dietary cholesterol, there was a marginal increase in significance in the ratio of LDL-C to HDL-C (P = 0.048) and total cholesterol to HDL-C (P = 0.047) (Supplementary Table 18). When wheat fiber was added as a covariate to the model, again, a small but significant increase in total cholesterol to HDL-C was seen, and the significance of the treatment difference for CRP was lost (P = 0.062) (Supplementary Table 19). On the other hand, as expected, after adjustment for GI, the treatment differences for pulse, creatinine, and eGFR lost significance (Supplementary Table 20).

Smoking, alcohol use, and our changes in secondary outcomes did not appear to relate to the changes in VWV. (Supplementary Table 21). Further, no change occurred in nutrient intake related to the change in VWV either at 1 year or, as the primary outcome, at 3 years (Supplementary Tables 22 and 23).

When we ran the model used for Table 2 with only the baseline adjustment, the only significant treatment difference from Table 2 was the loss of significance of the reduction in CRP on the low-GI diet compared with the wheat-fiber diet (Supplementary Table 24).

Two deaths from liver cancer and lymphoma occurred on the low-GI diet, with none on the high-fiber diet. There were six hospitalizations on the low-GI diet (brain tumor, liver cancer, pneumonia ×2, sepsis, and vertigo) and six on the wheat-fiber diet (back surgery for nerve entrapment, dementia, gallbladder surgery, pancreatitis ×2, and thyroid cancer) (Supplementary Table 25). Hypoglycemic episodes requiring medication reduction were seen in only one study participant (on the low-GI diet). HbA_1c levels >8.5% were seen in 12 participants (7 on the low-GI and 5 on the wheat-fiber diet).

No treatment differences were seen in the change in VWV between wheat-fiber and low-GI diets at 3 years. Despite the lack of a significant treatment difference between the diets, there was an increase in VWV on the wheat-fiber diet that was not seen on the low-GI diet. Furthermore, a very small reduction in renal function (eGFR) was also seen with the wheat-fiber died that was not seen on the low-GI diet. The resulting significant treatment difference in eGFR may be an indication of potential microvascular disease benefits associated with the low-GI diet (6,15). Small changes were seen in HbA_1c, blood lipids, or blood pressure; however, these changes in risk factors did not relate to changes in VWV, possibly resulting from the already low baseline levels of risk factors that limited further reductions (Supplementary Table 14).

The current trial results do not explain the strong association of GI with CVD as seen in a recent prospective cohort study (4). Factors such as adherence and duration of exposure may have reduced the effectiveness of the low-GI diet in our study. Other factors not assessed here may also have been involved, such as the effect of postprandial glycemia on markers of oxidative damage that are associated with increased CVD risk (16,17). Further, postprandial hypotension and tachycardia have been associated with all-cause mortality (18). In turn, postprandial hypotension may be prevented by acarbose treatment (19,20) that reduces the rate of carbohydrate absorption, so effectively creating a low-GI diet. These potential actions of low GI diets require further exploration. Previous studies on low-GI diets have reported reductions in serum triglyceride and CRP and increases in HDL-C (9,21–24), with no data on pulse rate. While the relevance of the small decrease in pulse rate seen in our study is uncertain, it is of interest that a slower heart rate has been associated with reduced CVD risk (25).

The study has several weaknesses. Our original estimation of an effect size of 34 mm³ for the increase in VWV over 3 years was optimistic, even though other publications have provided annual data that translate to an increase in VWV of 40 to 72 mm³/3 year (13,26). These increases are all greater than the 8 mm³ and 23 mm³ 3-year changes in VWV that we observed for the low-GI and wheat-fiber diets, respectively. It is also possible that our two current approaches to treatment were both effective in limiting our ability to see a difference or that they are most effective as preventive measures rather than for reversing established disease.

Few participants achieved the ideal goals for the low-GI and wheat-fiber diets. Nevertheless, the reduction of 12 GI units achieved at 1 and 3 years was very similar to the reduction in GI reported in previous studies (9) and similar to the extreme quintile range of 15 units seen in a recent study in which the high GI diet was significantly associated with increased CVD risk (4). However, the absolute reliability of the diet records may be called into question since the significant treatment differences in HbA_1c were lost over the duration of this 3-year trial, while significant treatment differences in GI of 12 units were seen consistently throughout the trial, based on the 7-day self-reported food records of the participants.

Provision of foods would likely have encouraged increased adherence. However, interventions that provide significant food items over a number of years are difficult to undertake and do not necessarily reflect real-world conditions. The concern that long-term adherence is a major problem for dietary trials was supported by the observation that an objective measure of adherence, HbA_1c, showed a longer-term reduction in the per-protocol group as the most adherent group compared with all study participants combined.

This problem of maintaining adequate dietary adherence in long-term trials supports the use of large cohort studies where major changes to adherence to a specific diet is not the objective, but rather continued adherence to the participant’s self-selected diet is all that is required.

Finally, the strong association in cohort studies of cereal fiber consumption, predominately wheat-fiber, with reduced cardiometabolic events (27,28), makes the selection of wheat fiber a very positive control and will increase the difficulty in seeing a more favorable effect for the low-GI diet. Therefore, a third treatment, as a true control, would have provided the possibility of a more relevant comparison. However, our participants from previous studies had requested a positive control only, especially for long-term interventions.

The study also has several strengths. At 3 years, our trial was longer than most dietary trials, at 3 months to 2 years, with notable exceptions such as Prevención con Dieta Mediterránea (PREDIMED) and Look AHEAD (Action for Health in Diabetes) at 4 to 9.6 years (29,30). Further, the use of MRI allowed assessment of VWV as an indication of atheroma burden making the outcome closer to a CVD event.

We conclude that no significant treatment difference was seen between the low-GI and wheat-fiber diets on VWV. However, cereal fiber has consistently been associated, in cohort studies, with a reduced risk of CVD. The lack of increase in vessel volume over the 3 years on the low-GI diet and its noninferiority in VWV compared with the wheat-fiber diet provide support for considering low-GI diets along with cereal fiber and whole grains as part of the dietary strategy for CVD risk reduction (27,28).

Acknowledgments. The authors thank Dr. John Dupre (University of Western Ontario, Canada) and Dr. Meredith Hawkins (Albert Einstein College of Medicine, New York, NY) for helpful advice and are indebted to the participants who made this trial possible.

Funding. This study was funded by the Canadian Institutes of Health Research (CIHR), Loblaw Companies, Canada, and Uniliver. D.J.A.J. received salary support and discretionary funding from the Canada Research Chair (CRC) endowment of the federal government of Canada and has received research grants from Agriculture and Agri-Food Canada, International Tree Nut Council Nutrition Research and Education Foundation, International Nut & Dried Fruit Council (INC), Canola and Flax Councils of Canada, Calorie Control Council, Canada Foundation for Innovation (CFI), Soy Nutrition Institute (SNI), and Ontario Research Fund (ORF). D.J.A.J. has received in-kind supplies for trials as a research support from the Almond Board of California, Walnut Council of California, the Peanut Institute, Barilla, Unilever, Unico, Primo, Loblaw Companies, Quaker (PepsiCo), Pristine Gourmet, Bunge Limited, Kellogg Canada, and WhiteWave Foods, and an honorarium from the U.S. 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 and funding and travel support from the Canadian Society of Endocrinology and Metabolism to produce mini cases for the Canadian Diabetes Association (CDA). L.C. was a Mitacs-Elevate postdoctoral fellow jointly funded by the Government of Canada and the Canadian Sugar Institute (February 2019–August 2021). R.J.d.S. has received remuneration for contract research done for the Canadian Institutes of Health Research’s Institute of Nutrition, Metabolism, and Diabetes, Health Canada, and the World Health Organization. He has held grants from the Canadian Institutes of Health Research, Canadian Foundation for Dietetic Research, and Population Health Research Institute, as a principal investigator and as co-investigator on several funded team grants from the Canadian Institutes of Health Research. C.W.C.K. has received grants or research support from Agriculture and Agri-Foods Canada (AAFC), Canadian Institutes of Health Research (CIHR), Canola Council of Canada, International Nut and Dried Fruit Council, and International Tree Nut Council Research and Education Foundation. J.L.S. was funded by a PSI Graham Farquharson Knowledge Translation Fellowship, Diabetes Canada Clinician Scientist award, CIHR INMD/CNS New Investigator Partnership Prize, and Banting & Best Diabetes Centre Sun Life Financial New Investigator Award.

The external funders and sponsors had no role in the design and conduct of the study, in the collection, analysis, and interpretation of the data, in the preparation, review, or approval of the manuscript, or in the decision to submit the manuscript for publication.

Duality of Interest. The study received funds from Loblaw Companies and Unilever. D.J.A.J. has received research grants from Saskatchewan & Alberta Pulse Growers Associations, 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, Pulse Canada, Kellogg’s Company, Canada, Quaker Oats, Canada, Procter & Gamble Technical Centre Ltd., Bayer Consumer Care, Springfield, NJ, Pepsi/Quaker, Soy Foods Association of North America, the Coca-Cola Company (investigator initiated, unrestricted grant), Solae, Haine Celestial, the Sanitarium Company, Orafti, and the Peanut Institute. He has been on the speaker’s panel, served on the scientific advisory board, and/or received travel support and/or honoraria from Nutritional Fundamentals for Health (NFH)-Nutramedica, Saint Barnabas Medical Center, The University of Chicago, 2020 China Glycemic Index (GI) International Conference, Atlantic Pain Conference, Academy of Life Long Learning, 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), Heali AI Corp, Institute of Food Technologists (IFT), Soy Nutrition Institute (SNI), Herbalife Nutrition Institute (HNI), Saskatchewan & Alberta Pulse Growers Associations, Sanitarium Company, Orafti, the International Tree Nut Council Nutrition Research and Education Foundation, the Peanut Institute, Herbalife International, Pacific Health Laboratories, 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 is a member of the International Carbohydrate Quality Consortium (ICQC). His wife, Alexandra L Jenkins, is a director and partner of INQUIS Clinical Research for the Food Industry, his 2 daughters, Wendy Jenkins and Amy Jenkins, have published a vegetarian book that promotes the use of the foods described here, The Portfolio Diet for Cardiovascular Risk Reduction (Academic Press/Elsevier 2020 ISBN:978-0-12-810510-8), and his sister, Caroline Brydson, received funding through a grant from the St. Michael’s Hospital Foundation to develop a cookbook for one of his studies. L.C. was previously employed as a casual clinical coordinator at INQUIS Clinical Research (until November 2019). R.J.d.S. has served as an external resource person to the World Health Organization’s Nutrition Guidelines Advisory Group on trans-fats, saturated fats, and polyunsaturated fats. The World Health Organization paid for his travel and accommodation to attend meetings from 2012–2017 to present and discuss this work. He has received speaker’s fees from the University of Toronto and McMaster Children’s Hospital. He has held grants from the Hamilton Health Sciences Corporation as a principal investigator. He serves as a member of the Nutrition Science Advisory Committee to Health Canada (Government of Canada), a co-opted member of the Scientific Advisory Committee on Nutrition (SACN) Subgroup on the Framework for the Evaluation of Evidence (Public Health England), and as an independent director of the Helderleigh Foundation (Canada). L.S.A.A. is a founding member of the International Carbohydrate Quality Consortium (ICQC) and has received honoraria from the Nutrition Foundation of Italy (NFI) and research grants from LILT (a nonprofit organization for the fight against cancer). No funding that she has received has been involved in the current project. S.K.N. is supported by a postdoctoral fellowship from the Canadian Institutes of Health Research (CIHR-IRSC, MFE-171207). She was previously employed as a clinical research dietitian at GI Labs, now INQUIS Clinical Research (until February 2016), and as a dietitian and study coordinator at the Diabetes Heart Research Centre (until September 2020). C.W.C.K. has received grants or research support from the Advanced Food Materials Network, Almond Board of California, Barilla, Loblaw Brands Ltd, the Peanut Institute, Pulse Canada, and Unilever. He has received in-kind research support from the Almond Board of California, Barilla, California Walnut Commission, Kellogg Canada, Loblaw Companies, Nutrartis, Quaker (PepsiCo), the Peanut Institute, Primo, Unico, Unilever, and WhiteWave Foods/Danone. He has received travel support and/or honoraria from the Barilla, California Walnut Commission, Canola Council of Canada, General Mills, International Nut and Dried Fruit Council, International Pasta Organization, Lantmannen, Loblaw Brands Ltd, Nutrition Foundation of Italy, Oldways Preservation Trust, Paramount Farms, the Peanut Institute, Pulse Canada, Sun-Maid, Tate & Lyle, Unilever, and White Wave Foods/Danone. He has served on the scientific advisory board for the International Tree Nut Council, International Pasta Organization, McCormick Science Institute, and Oldways Preservation Trust. He is a founding member of the International Carbohydrate Quality Consortium (ICQC), Executive Board Member of the Diabetes and Nutrition Study Group (DNSG) of the European Association for the Study of Diabetes (EASD), is on the Clinical Practice Guidelines Expert Committee for Nutrition Therapy of the EASD, and is a Director of the Toronto 3D Knowledge Synthesis and Clinical Trials foundation. J.L.S. has 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, American Society for Nutrition (ASN), International Nut and Dried Fruit Council (INC) Foundation, National Honey Board (U.S. Department of Agriculture [USDA] honey “Checkoff” program), Institute for the Advancement of Food and Nutrition Sciences (IAFNS; formerly ILSI North America), Pulse Canada, Quaker Oats Center of Excellence, The United Soybean Board (USDA soy “Checkoff” program), 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), The Plant Protein Fund at the University of Toronto (a fund that has received contributions from IFF), and The Nutrition Trialists Network Fund at the University of Toronto (a fund established by an inaugural donation from the Calorie Control Council). J.L.S. has received food donations to support randomized controlled trials from the Almond Board of California, California Walnut Commission, Peanut Institute, Barilla, Unilever/Upfield, Unico/Primo, Loblaw Companies, Quaker, Kellogg Canada, WhiteWave Foods/Danone, Nutrartis, and Dairy Farmers of Canada. He has received travel support, speaker fees and/or honoraria from ASN, Danone, Dairy Farmers of Canada, FoodMinds LLC, Nestlé, Abbott, General Mills, Nutrition Communications, International Food Information Council (IFIC), Calorie Control Council, International Sweeteners Association, and International Glutamate Technical Committee. J.L.S. has or has had ad hoc consulting arrangements with Perkins Coie LLP, Tate & Lyle, Phynova, and Inquis Clinical Research. He is a former member of the European Fruit Juice Association Scientific Expert Panel and former member of the Soy Nutrition Institute (SNI) Scientific Advisory Committee. 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/Canadian Association of Bariatric Physicians and Surgeons. He serves or has served as an unpaid member of the Board of Trustees and an unpaid scientific advisor for the Carbohydrates Committee of IAFNS. 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 spouse is an employee of AB InBev. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. D.J.A.J., G.E.M.-E., and A.R.M. decided to submit the manuscript for publication. S.S.-P., M.P., S.C.P., and B.B. have verified the data. All authors contributed to revisions of the manuscript. D.J.A.J. and S.C.P. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.