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

NCT ID: NCT03024983

Last Updated: 2017-01-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

18 participants

Study Classification

INTERVENTIONAL

Study Start Date

2015-09-30

Study Completion Date

2016-07-31

Brief Summary

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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).

Detailed Description

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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.

Conditions

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Dietary Modification

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

NONE

Study Groups

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Control

Glucose monohydrate (isoglucidic portion -50 g of available carbohydrates-)

Group Type ACTIVE_COMPARATOR

Glucose

Intervention Type OTHER

Glucose monohydrate (55 g) dissolved with 500 mL of water

Semolina

Semolina soup (isoglucidic portion -50 g of available carbohydrates-)

Group Type EXPERIMENTAL

Semolina soup

Intervention Type OTHER

Semolina soup (322 g) eaten with 500 mL of water

Bread

Bread (isoglucidic portion -50 g of available carbohydrates-)

Group Type EXPERIMENTAL

Bread

Intervention Type OTHER

Bread (122 g) eaten with 500 mL of water

Short pasta (fresh)

Fresh penne (isoglucidic portion -50 g of available carbohydrates-)

Group Type EXPERIMENTAL

Penne (fresh)

Intervention Type OTHER

Cooked penne (132 g) eaten with 500 mL of water

Short pasta (dry)

Short pasta (dry) (isoglucidic portion -50 g of available carbohydrates-)

Group Type EXPERIMENTAL

Penne (dry)

Intervention Type OTHER

Cooked penne (142 g) eaten with 500 mL of water

Long pasta (dry)

Long pasta (dry) (isoglucidic portion -50 g of available carbohydrates-)

Group Type EXPERIMENTAL

Spaghetti (dry)

Intervention Type OTHER

Cooked spaghetti (142 g) eaten with 500 mL of water

Interventions

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Glucose

Glucose monohydrate (55 g) dissolved with 500 mL of water

Intervention Type OTHER

Semolina soup

Semolina soup (322 g) eaten with 500 mL of water

Intervention Type OTHER

Bread

Bread (122 g) eaten with 500 mL of water

Intervention Type OTHER

Penne (fresh)

Cooked penne (132 g) eaten with 500 mL of water

Intervention Type OTHER

Penne (dry)

Cooked penne (142 g) eaten with 500 mL of water

Intervention Type OTHER

Spaghetti (dry)

Cooked spaghetti (142 g) eaten with 500 mL of water

Intervention Type OTHER

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Maximum Eligible Age

60 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of Parma

OTHER

Sponsor Role lead

Responsible Party

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Francesca Scazzina Ph.D.

Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Francesca Scazzina, Professor

Role: PRINCIPAL_INVESTIGATOR

Department of Food Science, University of Parma

Furio Brighenti, Professor

Role: STUDY_DIRECTOR

Department of Food Science, University of Parma

Locations

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Department of Food Science, University of Parma

Parma, Parma, Italy

Site Status

Countries

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Italy

References

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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.

Reference Type BACKGROUND
PMID: 22780564 (View on PubMed)

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. doi: 10.1210/jcem-66-2-323.

Reference Type BACKGROUND
PMID: 3276722 (View on PubMed)

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. Epub 2011 Sep 29.

Reference Type BACKGROUND
PMID: 22017823 (View on PubMed)

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. doi: 10.1016/0026-0495(88)90072-8.

Reference Type BACKGROUND
PMID: 3054432 (View on PubMed)

Jenkins 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.

Reference Type BACKGROUND
PMID: 3383733 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 6259925 (View on PubMed)

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. Epub 2013 Jan 30.

Reference Type BACKGROUND
PMID: 23364021 (View on PubMed)

Ludwig 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.

Reference Type BACKGROUND
PMID: 11988062 (View on PubMed)

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. Epub 2012 Jun 6.

Reference Type BACKGROUND
PMID: 22727193 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23962874 (View on PubMed)

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. doi: 10.1056/NEJM199001253220404.

Reference Type BACKGROUND
PMID: 2403660 (View on PubMed)

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

Reference Type BACKGROUND

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. Epub 2013 Jun 17.

Reference Type BACKGROUND
PMID: 23786819 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 20386010 (View on PubMed)

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. doi: 10.1210/jcem.86.5.7463.

Reference Type BACKGROUND
PMID: 11344187 (View on PubMed)

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. doi: 10.2337/diacare.9.4.401.

Reference Type BACKGROUND
PMID: 3743316 (View on PubMed)

Other Identifiers

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DWP1

Identifier Type: -

Identifier Source: org_study_id

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