Pasta and Other Durum Wheat-based Products: Effects on Post-prandial Glucose Metabolism

Dietary Modification Clinical Trial

Official title:

Pasta and Other Durum Wheat-based Products: Effects on Post-prandial Glucose Metabolism

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03024983
• Other study ID #: DWP1
• Status: Completed
• Phase: N/A
• First received: January 16, 2017
• Last updated: January 18, 2017
• Start date: September 2015
• Est. completion date: July 2016

Study information

• Verified date: January 2017
• Source: University of Parma
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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 bread. 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 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 response (post-prandial glucose, insulin, GLP-1, GIP plasma concentrations).

Description:

The different glycemic responses after the consumption of carbohydrate-based products are associated with different rates of digestion and absorption of the carbohydrates in the human body. Therefore, food products rich in carbohydrates can be classified based on their ability to be digested, absorbed and to affect post-prandial glycemia. Epidemiological studies suggest that following a diet including carbohydrate-based foods inducing a low and slow glycemic response is associated with reduced risk to develop some non-communicable diseases (such as type 2 diabetes (Livesey et al, 2013; Dong et al, 2011) and cardiovascular disease (Ludwig, 2002; Blaak et al, 2012)), to control inflammatory status (Ma et al, 2012; Sieri et al, 2010), which is the trigger of several pathologies, and to reduce fasting insulin (Schwingshackl & Hoffmann, 2013). Depending on the food composition, a low glycemic response is not always associated with a low plasma insulin concentration. For instance, high protein or lipid concentrations in the food matrix have been demonstrated to induce low post-prandial glycemic responses, but not a reduction in insulin secretion (Gannon et al, 1988; Gannon et al, 1993; Collier et al. 1988). Avoiding a high insulin post-prandial response after consumption of foods represents a preventive factor against the risk of overweight and hyperlipidemia (Ostlund et al, 1990), type 2 diabetes (Weyer et al, 2001), and cancer (Onitilo et al, 2014). Therefore, the evaluation of both glycemic and insulinemic post-prandial response curves is necessary in order to demonstrate the true beneficial effect of the consumption of low glycemic index foods. Among several factors which can influence the post-prandial glycemic and insulinemic responses (such as macronutrient composition and the cooking process), the technological aspects through which the foods are produced represent an important one. Several studies reported a low glycemic response after the consumption of pasta compared with bread (Jenkins et al, 1988; Jenkins et al, 1981; Wolever et al, 1986), and this is due to the technological structures characterizing the two matrices (Petitot et al, 2009). Pasta is one of the major sources of carbohydrates consumed in Italy. Therefore, the aim of the present study is to investigate the effect of pasta and other durum wheat based products on the plasma response of glucose, insulin, and other hormones related to the glucose metabolism (c-peptide, GLP-1 and GIP) in order to clearly discriminate the different biological effect induced by the technological process in the production of pasta, compared to foods beginning with the same ingredients. Moreover, the study aims to create a solid basis for future studies for evaluating the effect of pasta consumption, as the main source of carbohydrates, in a context of a balanced diet, for maintaining health.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 18
• Est. completion date: July 2016
• Est. primary completion date: June 2016
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 60 Years

Eligibility

Inclusion criteria:

• healthy male and female (age = 18 years)

Exclusion Criteria:

• 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

Related Conditions & MeSH terms

• Dietary Modification

Intervention

Other:
• Glucose
Glucose monohydrate (55 g) dissolved with 500 mL of water
• Semolina soup
Semolina soup (322 g) eaten with 500 mL of water
• Bread
Bread (122 g) eaten with 500 mL of water
• Penne (fresh)
Cooked penne (132 g) eaten with 500 mL of water
• Penne (dry)
Cooked penne (142 g) eaten with 500 mL of water
• Spaghetti (dry)
Cooked spaghetti (142 g) eaten with 500 mL of water

Locations

Country	Name	City	State
Italy	Department of Food Science, University of Parma	Parma

Sponsors (1)

Lead Sponsor	Collaborator
University of Parma

Country where clinical trial is conducted

Italy, 

References & Publications (16)

Blaak EE, Antoine JM, Benton D, Björck 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. Review. — View Citation

Collier 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. — View Citation

Dong 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. — View Citation

Gannon 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. — View Citation

Jenkins DJ, Wolever TM, Jenkins AL. Starchy foods and glycemic index. Diabetes Care. 1988 Feb;11(2):149-59. — View 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. — View Citation

Livesey 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. Review. — View Citation

Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA. 2002 May 8;287(18):2414-23. Review. — View Citation

Ma 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. Review. — View Citation

Onitilo 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. — View Citation

Ostlund 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. — View Citation

Petitot, 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

Schwingshackl 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. Review. — View Citation

Sieri 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. — View Citation

Weyer 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. — View Citation

Wolever 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. — View Citation

* Note: There are 16 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	incremental area under the curve for plasma glucose		2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary	post-prandial insulin plasma concentration		2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary	post-prandial c-peptide plasma concentration		2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary	post-prandial GLP-1 plasma concentration		2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary	post-prandial GIP plasma concentration		2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Secondary	post-prandial glucagon plasma concentration		2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)