Clinical trial NCT05698875: The Breakfast Rise, Education and Knowledge Study
Official title: The Breakfast Rise, Education and Knowledge Study in Children and Young People Who Have Type 1 Diabetes (T1D): The BREAK Study
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: type1diabetes
Lead sponsor: University of Stirling
Sponsor class: OTHER
First posted: 2023-01-26
Enrollment: 48
Sex: ALL
Minimum age (years): 5
Maximum age (years): 17
Standard ages: CHILD
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Participants will be asked to test each of the three test meals and control meal (usual breakfast) on two occasions. The meals will be consumed in an individual randomised order with the randomisation achieved using a Latin square randomisation. The tool used for this will be http://www.jerrydallal.com/random/randomize.htm. Randomisation will be done in a block of four.
Primary purpose: BASIC_SCIENCE

Brief summary: The study proposes to recruit 90 children and young people who have type 1 diabetes (T1D) and who regularly use Dexcom continuous glucose monitoring (CGM). The participants will be recruited from National Health Service (NHS) sites in the United Kingdom (UK) via their managing dietitian. The dietitian will be asked to provide baseline information about the participants which will include demographic data and information on clinical data, treatment and anthropometrics. Participants will be asked to provide access to Dexcom CGM data throughout the period of recording. Participants will be asked to test three breakfast meals (high glycaemic load, high glycaemic with 10g added protein and medium glycaemic load) plus a control meal (usual breakfast), repeating each meal twice in a randomized order using a Latin square randomisation. The dietitian will be asked to optimise the participants insulin doses prior to commencing test meals. Participants will be asked to complete a questionnaire for each of the postprandial test and control meal periods. This will include questions about their diabetes management, food and fluid intake in addition to questions on activities all of which took place during the three-hour postprandial period. The glycaemic response to the test and control meals will be analysed using the CGM data and the results statistically described using univariate, bivariate and multivariate analysis.

Detailed description: This is a quantitative study. Dexcom CGM data will be collected for the period of recording. Participants will be asked to test three breakfast meals on two occasions and submit a postprandial questionnaire after each test meal to confirm it has been tested. The postprandial period will be three hours following the end of the breakfast test meal. The test meal recipes will be provided by the chief investigator. The dietary composition of the meals has been analysed using the a dietary analysis programme. The glycaemic index and load of the meals is estimated from this programme which uses available date from the international tables of glycaemic index and glycaemic loads (Atkinson et al. 2008; 2021). Most foods were based on average composition across different brands. For the added fibre bread used in test meal 3, an average of three known brands was used calculated by the chief investigator. The meals will be taken in the home environment with the food provided by the families. The participants will be asked to take the test meal on a day when their CGM reading is between 4-10mmol/l and when there has been no nocturnal hypoglycaemia on the night before the planned test. The participants will act as their own control. They will be asked to complete a postprandial questionnaire for control meals as well. The control meals will be there usual breakfast of choice. The study duration, commencing with the recruitment of the first participant and ending when data has been fully described, is anticipated to be two years.

Recruitment Paediatric diabetes dietitians, working across the UK, will be enrolled to help recruit participants and become principal investigators (PI) for their site.

Sample size The sample size power calculation is 64. This is based on using ANOVA repeated measures, within factors with four groups and measurements (3 test meals and control) with small effect size (0.15), P value 0.05 and power 0.80 and correlation among repeated measure of 0.5. The drop rate of clinical trials is often over 40%. Therefore, the aim is to recruit 90 participants to allow for this dropout rate and meet the sample size of 64. It may be possible to recruit this number of participants. There are approximately 29,000 children and young people living in the UK with T1D (Juvenile Diabetes Research Federation (JDRF), 2018). In the first phase of this study, 12 NHS sites were enrolled, and 96 children and young people were recruited to the study.

Methodology Baseline data

In order to make comparisons between relevant variables and glucose levels, the following baseline data will be collected from the dietitians and sent to the chief investigator, along with the artificial identifier on the Excel spreadsheet as discussed earlier at the stage of recruitment of participants:

* Parent's email address
* Sex, date of birth and recent weight and height (for calculation of BMI and BMI centile) and date of when this was taken
* Date of diagnosis of T1D
* Last four HbA1c
* Total daily insulin dose (TDD)
* Insulin: carbohydrate ratios (ICR) and Insulin Sensitivity Factor (ISF)
* Current insulin regimen - including the type of insulin prescribed and if applicable type of insulin pump i.e. open or closed loop system.

Run-in period At recruitment the dietitians will be asked to arrange a review of the participants insulin regimen including the insulin to carbohydrate ratio's (ICR), insulin sensitivity factor (ISF) and basal background insulin doses/rates. The dietitian will be asked to inform the chief investigator when this has taken place. Participants will be asked to commence the test meals following this.

Glucose measurement Data on interstitial glucose will be collected via Dexcom CGM. The Dexcom CGM data will be accessed by an NHS Highland research 'Clarity Clinic' with Dexcom CLARITY® Clinic Portal (Dexcom In, San Diego, California (CA), USA). The chief investigator is administrator of this clinic. Once the managing dietitian has obtained each participant's consent, the participant's parent's email address will be sent to the chief investigator along with the baseline information/data as described above. The chief investigator, as administrator of the Clarity Clinic account, will then invite the participant, via email, to be added to the clinic. Once the invite has been accepted, it will stand for the period of the recording i.e. until all the test meals and questionnaires have been completed. Once the participant has submitted their last questionnaire, they will be removed from the Dexcom CLARITY® Clinic Portal.

Following the provision of CGM data and review of the insulin regimen by the diabetes team, participants will be randomised to test each of the three test meals on two separate occasions with a control meal (usual breakfast meal) for each test meal. Randomisation will be achieved using a Latin square randomisation. The tool used for this will be http://www.jerrydallal.com/random/randomize.htm. Randomisation will be done in a block of four.

The test meals are based on foods children and young people enjoy eating. There are three meals. Test meal one includes a high glycaemic index cereal meal with milk and has a high glycaemic load (\> 20), test meal two is the same cereal meal with a high glycaemic load (\>20) with addition of 10g protein and test meal three has a medium glycaemic load (10-20). For test meals one and two there are three portion size options to meet age appropriate requirements and appetites. The participants will be able to choose from two different cereals for test meal 1 and a choice of protein sources for test meal 2. They will be asked to keep to the same choice of cereal and protein source for the repeat meal. They will be asked to consume at least 75% of the meal to ensure the threshold of the glycaemic load is met. The instructions and details of the test meals are presented in Appendix 11. The control meals will be the participant's usual breakfast of choice.

Participants will be asked to follow their usual insulin regimen as advised by their diabetes team i.e. their usual insulin dose and dose timing. For both test and control meals participants will be asked to avoid any further food intake during three-hour postprandial period other than carbohydrate adjustments required to treat any hypoglycaemia. Participants will also be asked to avoid drinks except water or carbohydrate free juices. They will also be asked to avoid physical activity of more than 30 minutes in duration. To minimise disruption to their normal daily activities, they will be advised to test the meal on a day when there is no planned physical activity i.e. a school day with no morning physical education. The CGM data will be collected throughout this time as discussed above.

Postprandial Questionnaire The participants will be asked to complete a postprandial questionnaire using 'online survey'. This includes questions about the meal and the three-hour postprandial period. The questionnaire is presented in Appendix 10. They will be asked to wait a minimum of three hours before answering and submitting the questionnaire. They will be encouraged to complete it on the same day as the test or control meal.

Data analysis This will be a mix of univariate, bivariate and multivariate analysis as this is best suited to describing, summarising and visualising these data. Outputs will include the distribution of glucose levels post-breakfast to determine the spread and dispersion of the data.

Eligibility criteria: Inclusion Criteria:

* Children and young people aged between 5-17 years
* Diagnosis of type 1 diabetes for a minimum of one year
* On multiple daily injections (MDI) together with carbohydrate counting or Continuous Subcutaneous Insulin Infusion (CSII) using either open or closed loop systems.
* Use Dexcom continuous glucose monitoring (CGM) on a regular basis
* Have a Dexcom Clarity account and use the Clarity App
* Regularly eats a breakfast meal before midday
* Access to internet and email

Exclusion Criteria:

* Prescribed anti-hyperglycaemia agents i.e. Glucophage (Metformin) and or antidepressants.
* Any other medical conditions that may impact on the digestion and or absorption of nutrients, including coeliac disease and gastroparesis.
* Vegans
* Allergic or intolerant to the test meals
* Experiencing difficulties with food including diagnosed eating disorders
* Currently actively taking part in another research study

Primary outcomes:
measure: Mean Glucose (mmol/l)
timeFrame: three-hour postprandial breakfast period
Secondary outcomes:
measure: Mean Glucose Excursion
timeFrame: three-hour postprandial breakfast period
measure: Mean Peak Glucose Excursion
timeFrame: three-hour postprandial breakfast period
measure: Mean Time to Peak
timeFrame: three-hour postprandial breakfast period
measure: Area Under the Glucose Curve
timeFrame: three-hour postprandial breakfast period
measure: Percentage Coefficient of Variation
timeFrame: 3 hours
measure: Time in Range
timeFrame: three-hour postprandial breakfast period
measure: Time Above Range
timeFrame: 3 hours
measure: Time in Tight Range
timeFrame: 3 hours
measure: Glucose at 30 Minutes
timeFrame: 30 minutes
measure: Glucose at 60 Minutes
timeFrame: 60 minutes
measure: Glucose at 90 Minutes
timeFrame: 90 minutes
measure: Glucose at 120 Minutes
timeFrame: 120 minutes
measure: Glucose at 150 Minutes
timeFrame: 150 minutes
measure: Glucose at 180 Minutes
timeFrame: 180 minutes
Other outcomes:
Locations:
city: Stirling
country: United Kingdom
facility: Faculty of Health Sciences and Sport
state: Stirlingshire
Study officials:
affiliation: University of Stirling
name: Julie Johnson, MNutr
role: PRINCIPAL_INVESTIGATOR
References:
citation: Atkinson FS, Foster-Powell K, Brand-Miller JC. International tables of glycemic index and glycemic load values: 2008. Diabetes Care. 2008 Dec;31(12):2281-3. doi: 10.2337/dc08-1239. Epub 2008 Oct 3.
citation: Atkinson FS, Brand-Miller JC, Foster-Powell K, Buyken AE, Goletzke J. International tables of glycemic index and glycemic load values 2021: a systematic review. Am J Clin Nutr. 2021 Nov 8;114(5):1625-1632. doi: 10.1093/ajcn/nqab233.
citation: Barnea-Goraly N, Raman M, Mazaika P, Marzelli M, Hershey T, Weinzimer SA, Aye T, Buckingham B, Mauras N, White NH, Fox LA, Tansey M, Beck RW, Ruedy KJ, Kollman C, Cheng P, Reiss AL; Diabetes Research in Children Network (DirecNet). Alterations in white matter structure in young children with type 1 diabetes. Diabetes Care. 2014 Feb;37(2):332-40. doi: 10.2337/dc13-1388. Epub 2013 Dec 6.
citation: Battelino T, Danne T, Bergenstal RM, Amiel SA, Beck R, Biester T, Bosi E, Buckingham BA, Cefalu WT, Close KL, Cobelli C, Dassau E, DeVries JH, Donaghue KC, Dovc K, Doyle FJ 3rd, Garg S, Grunberger G, Heller S, Heinemann L, Hirsch IB, Hovorka R, Jia W, Kordonouri O, Kovatchev B, Kowalski A, Laffel L, Levine B, Mayorov A, Mathieu C, Murphy HR, Nimri R, Norgaard K, Parkin CG, Renard E, Rodbard D, Saboo B, Schatz D, Stoner K, Urakami T, Weinzimer SA, Phillip M. Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range. Diabetes Care. 2019 Aug;42(8):1593-1603. doi: 10.2337/dci19-0028. Epub 2019 Jun 8.
citation: Bell KJ, Smart CE, Steil GM, Brand-Miller JC, King B, Wolpert HA. Impact of fat, protein, and glycemic index on postprandial glucose control in type 1 diabetes: implications for intensive diabetes management in the continuous glucose monitoring era. Diabetes Care. 2015 Jun;38(6):1008-15. doi: 10.2337/dc15-0100.
citation: Birnbacher R, Waldhor T, Schneider U, Schober E. Glycaemic responses to commonly ingested breakfasts in children with insulin-dependent diabetes mellitus. Eur J Pediatr. 1995 May;154(5):353-5. doi: 10.1007/BF02072101.
citation: Bluestone JA, Herold K, Eisenbarth G. Genetics, pathogenesis and clinical interventions in type 1 diabetes. Nature. 2010 Apr 29;464(7293):1293-300. doi: 10.1038/nature08933.
citation: Boland E, Monsod T, Delucia M, Brandt CA, Fernando S, Tamborlane WV. Limitations of conventional methods of self-monitoring of blood glucose: lessons learned from 3 days of continuous glucose sensing in pediatric patients with type 1 diabetes. Diabetes Care. 2001 Nov;24(11):1858-62. doi: 10.2337/diacare.24.11.1858.
citation: Bunn HF, Gabbay KH, Gallop PM. The glycosylation of hemoglobin: relevance to diabetes mellitus. Science. 1978 Apr 7;200(4337):21-7. doi: 10.1126/science.635569.
citation: Chugani HT, Phelps ME, Mazziotta JC. Positron emission tomography study of human brain functional development. Ann Neurol. 1987 Oct;22(4):487-97. doi: 10.1002/ana.410220408.
citation: Derr R, Garrett E, Stacy GA, Saudek CD. Is HbA(1c) affected by glycemic instability? Diabetes Care. 2003 Oct;26(10):2728-33. doi: 10.2337/diacare.26.10.2728.
citation: DiMeglio LA, Acerini CL, Codner E, Craig ME, Hofer SE, Pillay K, Maahs DM. ISPAD Clinical Practice Consensus Guidelines 2018: Glycemic control targets and glucose monitoring for children, adolescents, and young adults with diabetes. Pediatr Diabetes. 2018 Oct;19 Suppl 27:105-114. doi: 10.1111/pedi.12737. No abstract available.
citation: Eisenbarth GS. Type I diabetes mellitus. A chronic autoimmune disease. N Engl J Med. 1986 May 22;314(21):1360-8. doi: 10.1056/NEJM198605223142106. No abstract available.
citation: Faber EM, van Kampen PM, Clement-de Boers A, Houdijk ECAM, van der Kaay DCM. The influence of food order on postprandial glucose levels in children with type 1 diabetes. Pediatr Diabetes. 2018 Jun;19(4):809-815. doi: 10.1111/pedi.12640. Epub 2018 Mar 12.
citation: Gandrud LM, Xing D, Kollman C, Block JM, Kunselman B, Wilson DM, Buckingham BA. The Medtronic Minimed Gold continuous glucose monitoring system: an effective means to discover hypo- and hyperglycemia in children under 7 years of age. Diabetes Technol Ther. 2007 Aug;9(4):307-16. doi: 10.1089/dia.2007.0026.
citation: Gonder-Frederick LA, Zrebiec JF, Bauchowitz AU, Ritterband LM, Magee JC, Cox DJ, Clarke WL. Cognitive function is disrupted by both hypo- and hyperglycemia in school-aged children with type 1 diabetes: a field study. Diabetes Care. 2009 Jun;32(6):1001-6. doi: 10.2337/dc08-1722. Epub 2009 Mar 26.
citation: Heptulla RA, Allen HF, Gross TM, Reiter EO. Continuous glucose monitoring in children with type 1 diabetes: before and after insulin pump therapy. Pediatr Diabetes. 2004 Mar;5(1):10-5. doi: 10.1111/j.1399-543X.2004.00035.x.
citation: Kaiser N, Sasson S, Feener EP, Boukobza-Vardi N, Higashi S, Moller DE, Davidheiser S, Przybylski RJ, King GL. Differential regulation of glucose transport and transporters by glucose in vascular endothelial and smooth muscle cells. Diabetes. 1993 Jan;42(1):80-9. doi: 10.2337/diab.42.1.80.
citation: Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, Bowling AC, Newman HC, Jenkins AL, Goff DV. Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr. 1981 Mar;34(3):362-6. doi: 10.1093/ajcn/34.3.362.
citation: Koivisto VA, Stevens LK, Mattock M, Ebeling P, Muggeo M, Stephenson J, Idzior-Walus B. Cardiovascular disease and its risk factors in IDDM in Europe. EURODIAB IDDM Complications Study Group. Diabetes Care. 1996 Jul;19(7):689-97. doi: 10.2337/diacare.19.7.689.
citation: Lopez PE, Evans M, King BR, Jones TW, Bell K, McElduff P, Davis EA, Smart CE. A randomized comparison of three prandial insulin dosing algorithms for children and adolescents with Type 1 diabetes. Diabet Med. 2018 Oct;35(10):1440-1447. doi: 10.1111/dme.13703. Epub 2018 Jun 19.
citation: Mangrola D, Cox C, Furman AS, Krishnan S, Karakas SE. SELF BLOOD GLUCOSE MONITORING UNDERESTIMATES HYPERGLYCEMIA AND HYPOGLYCEMIA AS COMPARED TO CONTINUOUS GLUCOSE MONITORING IN TYPE 1 AND TYPE 2 DIABETES. Endocr Pract. 2018 Jan;24(1):47-52. doi: 10.4158/EP-2017-0032. Epub 2017 Nov 16.
citation: Marzelli MJ, Mazaika PK, Barnea-Goraly N, Hershey T, Tsalikian E, Tamborlane W, Mauras N, White NH, Buckingham B, Beck RW, Ruedy KJ, Kollman C, Cheng P, Reiss AL; Diabetes Research in Children Network (DirecNet). Neuroanatomical correlates of dysglycemia in young children with type 1 diabetes. Diabetes. 2014 Jan;63(1):343-53. doi: 10.2337/db13-0179. Epub 2013 Oct 29.
citation: Mauras N, Mazaika P, Buckingham B, Weinzimer S, White NH, Tsalikian E, Hershey T, Cato A, Cheng P, Kollman C, Beck RW, Ruedy K, Aye T, Fox L, Arbelaez AM, Wilson D, Tansey M, Tamborlane W, Peng D, Marzelli M, Winer KK, Reiss AL; Diabetes Research in Children Network (DirecNet). Longitudinal assessment of neuroanatomical and cognitive differences in young children with type 1 diabetes: association with hyperglycemia. Diabetes. 2015 May;64(5):1770-9. doi: 10.2337/db14-1445. Epub 2014 Dec 8.
citation: Mazaika PK, Weinzimer SA, Mauras N, Buckingham B, White NH, Tsalikian E, Hershey T, Cato A, Aye T, Fox L, Wilson DM, Tansey MJ, Tamborlane W, Peng D, Raman M, Marzelli M, Reiss AL; Diabetes Research in Children Network (DirecNet). Variations in Brain Volume and Growth in Young Children With Type 1 Diabetes. Diabetes. 2016 Feb;65(2):476-85. doi: 10.2337/db15-1242. Epub 2015 Oct 28.
citation: McDonnell CM, Northam EA, Donath SM, Werther GA, Cameron FJ. Hyperglycemia and externalizing behavior in children with type 1 diabetes. Diabetes Care. 2007 Sep;30(9):2211-5. doi: 10.2337/dc07-0328. Epub 2007 Jun 11.
citation: Paterson MA, Smart CE, Lopez PE, McElduff P, Attia J, Morbey C, King BR. Influence of dietary protein on postprandial blood glucose levels in individuals with Type 1 diabetes mellitus using intensive insulin therapy. Diabet Med. 2016 May;33(5):592-8. doi: 10.1111/dme.13011. Epub 2015 Dec 6.
citation: Paterson MA, Smart CEM, Lopez PE, Howley P, McElduff P, Attia J, Morbey C, King BR. Increasing the protein quantity in a meal results in dose-dependent effects on postprandial glucose levels in individuals with Type 1 diabetes mellitus. Diabet Med. 2017 Jun;34(6):851-854. doi: 10.1111/dme.13347. Epub 2017 Mar 19.
citation: Perantie DC, Wu J, Koller JM, Lim A, Warren SL, Black KJ, Sadler M, White NH, Hershey T. Regional brain volume differences associated with hyperglycemia and severe hypoglycemia in youth with type 1 diabetes. Diabetes Care. 2007 Sep;30(9):2331-7. doi: 10.2337/dc07-0351. Epub 2007 Jun 15.
citation: Perantie DC, Lim A, Wu J, Weaver P, Warren SL, Sadler M, White NH, Hershey T. Effects of prior hypoglycemia and hyperglycemia on cognition in children with type 1 diabetes mellitus. Pediatr Diabetes. 2008 Apr;9(2):87-95. doi: 10.1111/j.1399-5448.2007.00274.x. Epub 2008 Jan 12.
citation: Perantie DC, Koller JM, Weaver PM, Lugar HM, Black KJ, White NH, Hershey T. Prospectively determined impact of type 1 diabetes on brain volume during development. Diabetes. 2011 Nov;60(11):3006-14. doi: 10.2337/db11-0589. Epub 2011 Sep 27.
citation: Piechowiak K, Dzygalo K, Szypowska A. The additional dose of insulin for high-protein mixed meal provides better glycemic control in children with type 1 diabetes on insulin pumps: randomized cross-over study. Pediatr Diabetes. 2017 Dec;18(8):861-868. doi: 10.1111/pedi.12500. Epub 2017 Jan 24.
citation: Ryan RL, King BR, Anderson DG, Attia JR, Collins CE, Smart CE. Influence of and optimal insulin therapy for a low-glycemic index meal in children with type 1 diabetes receiving intensive insulin therapy. Diabetes Care. 2008 Aug;31(8):1485-90. doi: 10.2337/dc08-0331. Epub 2008 May 5.
citation: Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, Stampfer MJ, Wing AL, Willett WC. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997 Apr;20(4):545-50. doi: 10.2337/diacare.20.4.545.
citation: Smart CE, King BR, McElduff P, Collins CE. In children using intensive insulin therapy, a 20-g variation in carbohydrate amount significantly impacts on postprandial glycaemia. Diabet Med. 2012 Jul;29(7):e21-4. doi: 10.1111/j.1464-5491.2012.03595.x.
citation: Smart CE, Evans M, O'Connell SM, McElduff P, Lopez PE, Jones TW, Davis EA, King BR. Both dietary protein and fat increase postprandial glucose excursions in children with type 1 diabetes, and the effect is additive. Diabetes Care. 2013 Dec;36(12):3897-902. doi: 10.2337/dc13-1195. Epub 2013 Oct 29.
citation: Smart CE, Annan F, Higgins LA, Jelleryd E, Lopez M, Acerini CL. ISPAD Clinical Practice Consensus Guidelines 2018: Nutritional management in children and adolescents with diabetes. Pediatr Diabetes. 2018 Oct;19 Suppl 27:136-154. doi: 10.1111/pedi.12738. No abstract available.
citation: Standl E, Schnell O, Ceriello A. Postprandial hyperglycemia and glycemic variability: should we care? Diabetes Care. 2011 May;34 Suppl 2(Suppl 2):S120-7. doi: 10.2337/dc11-s206.
citation: Tansey M, Beck R, Ruedy K, Tamborlane W, Cheng P, Kollman C, Fox L, Weinzimer S, Mauras N, White NH, Tsalikian E; Diabetes Research in Children Network (DirecNet). Persistently high glucose levels in young children with type 1 diabetes. Pediatr Diabetes. 2016 Mar;17(2):93-100. doi: 10.1111/pedi.12248. Epub 2014 Dec 11.
citation: Thomas DE, Elliott EJ, Baur L. Low glycaemic index or low glycaemic load diets for overweight and obesity. Cochrane Database Syst Rev. 2007 Jul 18;2007(3):CD005105. doi: 10.1002/14651858.CD005105.pub2.
citation: Diabetes Control and Complications Trial Research Group; Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, Davis M, Rand L, Siebert C. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep 30;329(14):977-86. doi: 10.1056/NEJM199309303291401.
citation: The absence of a glycemic threshold for the development of long-term complications: the perspective of the Diabetes Control and Complications Trial. Diabetes. 1996 Oct;45(10):1289-98.
citation: Toh DWK, Koh ES, Kim JE. Lowering breakfast glycemic index and glycemic load attenuates postprandial glycemic response: A systematically searched meta-analysis of randomized controlled trials. Nutrition. 2020 Mar;71:110634. doi: 10.1016/j.nut.2019.110634. Epub 2019 Nov 1.
citation: van Loon LJ, Saris WH, Verhagen H, Wagenmakers AJ. Plasma insulin responses after ingestion of different amino acid or protein mixtures with carbohydrate. Am J Clin Nutr. 2000 Jul;72(1):96-105. doi: 10.1093/ajcn/72.1.96.
citation: Wolever TM, Nguyen PM, Chiasson JL, Hunt JA, Josse RG, Palmason C, Rodger NW, Ross SA, Ryan EA, Tan MH. Determinants of diet glycemic index calculated retrospectively from diet records of 342 individuals with non-insulin-dependent diabetes mellitus. Am J Clin Nutr. 1994 Jun;59(6):1265-9. doi: 10.1093/ajcn/59.6.1265.