Pasta and Couscous Prepared With Durum Wheat Semolina: Effect on Post-prandial Glucose and Insulin Metabolism
1 other identifier
interventional
30
1 country
1
Brief Summary
Carbohydrate-based products can influence the post-prandial glycemic response differently based on their ability to be digested, absorbed and to affect rises in plasma glucose. Pasta is one of the major carbohydrate-rich foods consumed in Italy. Studies from the literature describe a lower glycemic response after the consumption of pasta compared with other wheat-based products, such as couscous. Among the factors affecting post-prandial glycemia after consumption of carbohydrate-based products, the technological process represents a central one. In fact, the different technological processes alter the food matrix which can affect the post-prandial metabolism of glucose and insulin differently. Thus, the present study aims at investigating the effect induced by the principal steps of the process of pasta production on the reduction of post-prandial glycemic and insulinemic responses compared to a similar durum wheat based product, couscous.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Mar 2017
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 28, 2017
CompletedStudy Start
First participant enrolled
March 13, 2017
CompletedFirst Posted
Study publicly available on registry
March 31, 2017
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 13, 2018
CompletedStudy Completion
Last participant's last visit for all outcomes
July 13, 2018
CompletedSeptember 12, 2018
September 1, 2018
1.3 years
February 28, 2017
September 10, 2018
Conditions
Outcome Measures
Primary Outcomes (2)
incremental area under the curve for blood glucose
postprandial IAUC of blood glucose
Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
incremental area under the curve for plasma insulin
postprandial IAUC for plasma insulin
Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary Outcomes (1)
post-prandial c-peptide plasma concentration
Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Study Arms (4)
Couscous (dry)
ACTIVE COMPARATORCooked couscous (50g available carbohydrate, 70g uncooked) eaten with 500 mL of water
Short pasta (dry)
EXPERIMENTALCooked penne (50g available carbohydrate, 71g uncooked) eaten with 500 mL of water
Long pasta (dry)
EXPERIMENTALCooked spaghetti (50g available carbohydrate, 71g uncooked) eaten with 500 mL of water
Glucose
ACTIVE COMPARATORGlucose monohydrate (55 g) dissolved with 500 mL of water
Interventions
50g available carbohydrate portion of penne (\~71g uncooked) will be cooked according to package instructions and served with 500mL water
50g available carbohydrate portion of spaghetti (\~71g uncooked) will be cooked according to package instructions and served with 500mL water
50g available carbohydrate portion of couscous (\~70g uncooked) will be cooked according to package instructions and served with 500mL water
50g available carbohydrate portion of glucose monohydrate (\~55g) will be dissolved in 500mL water
Eligibility Criteria
You may qualify if:
- healthy male and female
You may not qualify if:
- BMI\>30kg/m2
- celiac disease
- metabolic disorders (diabetes, hypertension, dislipidemia, glucidic intolerance)
- chronic drug therapies for any pathologies (including psychiatric diseases)
- intense physical activity
- dietary supplements affecting the metabolism
- anemia
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Department of Food Science, University of Parma
Parma, 43125, Italy
Related Publications (17)
Blaak EE, Antoine JM, Benton D, Bjorck I, Bozzetto L, Brouns F, Diamant M, Dye L, Hulshof T, Holst JJ, Lamport DJ, Laville M, Lawton CL, Meheust A, Nilson A, Normand S, Rivellese AA, Theis S, Torekov SS, Vinoy S. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev. 2012 Oct;13(10):923-84. doi: 10.1111/j.1467-789X.2012.01011.x. Epub 2012 Jul 11.
PMID: 22780564BACKGROUNDCollier GR, Greenberg GR, Wolever TM, Jenkins DJ. The acute effect of fat on insulin secretion. J Clin Endocrinol Metab. 1988 Feb;66(2):323-6. doi: 10.1210/jcem-66-2-323.
PMID: 3276722BACKGROUNDDong JY, Zhang L, Zhang YH, Qin LQ. Dietary glycaemic index and glycaemic load in relation to the risk of type 2 diabetes: a meta-analysis of prospective cohort studies. Br J Nutr. 2011 Dec;106(11):1649-54. doi: 10.1017/S000711451100540X. Epub 2011 Sep 29.
PMID: 22017823BACKGROUNDGannon MC, Nuttall FQ, Neil BJ, Westphal SA. The insulin and glucose responses to meals of glucose plus various proteins in type II diabetic subjects. Metabolism. 1988 Nov;37(11):1081-8. doi: 10.1016/0026-0495(88)90072-8.
PMID: 3054432BACKGROUNDJenkins DJ, Wolever TM, Jenkins AL. Starchy foods and glycemic index. Diabetes Care. 1988 Feb;11(2):149-59. doi: 10.2337/diacare.11.2.149.
PMID: 3383733BACKGROUNDJenkins 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.
PMID: 6259925BACKGROUNDLivesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Am J Clin Nutr. 2013 Mar;97(3):584-96. doi: 10.3945/ajcn.112.041467. Epub 2013 Jan 30.
PMID: 23364021BACKGROUNDLudwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA. 2002 May 8;287(18):2414-23. doi: 10.1001/jama.287.18.2414.
PMID: 11988062BACKGROUNDMa XY, Liu JP, Song ZY. Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies. Atherosclerosis. 2012 Aug;223(2):491-6. doi: 10.1016/j.atherosclerosis.2012.05.028. Epub 2012 Jun 6.
PMID: 22727193BACKGROUNDOnitilo AA, Stankowski RV, Berg RL, Engel JM, Glurich I, Williams GM, Doi SA. Type 2 diabetes mellitus, glycemic control, and cancer risk. Eur J Cancer Prev. 2014 Mar;23(2):134-40. doi: 10.1097/CEJ.0b013e3283656394.
PMID: 23962874BACKGROUNDOstlund RE Jr, Staten M, Kohrt WM, Schultz J, Malley M. The ratio of waist-to-hip circumference, plasma insulin level, and glucose intolerance as independent predictors of the HDL2 cholesterol level in older adults. N Engl J Med. 1990 Jan 25;322(4):229-34. doi: 10.1056/NEJM199001253220404.
PMID: 2403660BACKGROUNDSchwingshackl L, Hoffmann G. Long-term effects of low glycemic index/load vs. high glycemic index/load diets on parameters of obesity and obesity-associated risks: a systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2013 Aug;23(8):699-706. doi: 10.1016/j.numecd.2013.04.008. Epub 2013 Jun 17.
PMID: 23786819BACKGROUNDSieri S, Krogh V, Berrino F, Evangelista A, Agnoli C, Brighenti F, Pellegrini N, Palli D, Masala G, Sacerdote C, Veglia F, Tumino R, Frasca G, Grioni S, Pala V, Mattiello A, Chiodini P, Panico S. Dietary glycemic load and index and risk of coronary heart disease in a large italian cohort: the EPICOR study. Arch Intern Med. 2010 Apr 12;170(7):640-7. doi: 10.1001/archinternmed.2010.15.
PMID: 20386010BACKGROUNDWeyer C, Funahashi T, Tanaka S, Hotta K, Matsuzawa Y, Pratley RE, Tataranni PA. Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia. J Clin Endocrinol Metab. 2001 May;86(5):1930-5. doi: 10.1210/jcem.86.5.7463.
PMID: 11344187BACKGROUNDWolever TM, Jenkins DJ, Kalmusky J, Giordano C, Giudici S, Jenkins AL, Thompson LU, Wong GS, Josse RG. Glycemic response to pasta: effect of surface area, degree of cooking, and protein enrichment. Diabetes Care. 1986 Jul-Aug;9(4):401-4. doi: 10.2337/diacare.9.4.401.
PMID: 3743316BACKGROUNDPetitot, M., Abecassis, J. & Micard, V. Structuring of pasta components during processing: impact on starch and protein digestibility and allergenicity. Trends Food Sci Tech. 2009;20,521-532
BACKGROUNDVanhatalo S, Dall'Asta M, Cossu M, Chiavaroli L, Francinelli V, Pede GD, Dodi R, Narvainen J, Antonini M, Goldoni M, Holopainen-Mantila U, Cas AD, Bonadonna R, Brighenti F, Poutanen K, Scazzina F. Pasta Structure Affects Mastication, Bolus Properties, and Postprandial Glucose and Insulin Metabolism in Healthy Adults. J Nutr. 2022 Apr 1;152(4):994-1005. doi: 10.1093/jn/nxab361.
PMID: 34669959DERIVED
MeSH Terms
Interventions
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Francesca Scazzina, PhD
Department of Food Science, University of Parma
- STUDY DIRECTOR
Furio Brighenti, PhD
Department of Food Science, University of Parma
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- OUTCOMES ASSESSOR
- Masking Details
- Personnel involved in randomization, in the analyses of the samples collected, and who were involved in the data processing were blinded.
- Purpose
- BASIC SCIENCE
- Intervention Model
- CROSSOVER
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Assistant Professor
Study Record Dates
First Submitted
February 28, 2017
First Posted
March 31, 2017
Study Start
March 13, 2017
Primary Completion
July 13, 2018
Study Completion
July 13, 2018
Last Updated
September 12, 2018
Record last verified: 2018-09
Data Sharing
- IPD Sharing
- Will not share