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

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ClinicalTrials.gov Identifier: NCT03024983
Recruitment Status : Completed
First Posted : January 19, 2017
Last Update Posted : January 19, 2017
Sponsor:
Information provided by (Responsible Party):
Francesca Scazzina Ph.D., University of Parma

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 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).

Condition or disease Intervention/treatment Phase
Dietary Modification Other: Glucose Other: Semolina soup Other: Bread Other: Penne (fresh) Other: Penne (dry) Other: Spaghetti (dry) Not Applicable

Detailed 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.

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Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 18 participants
Allocation: Randomized
Intervention Model: Crossover Assignment
Masking: None (Open Label)
Primary Purpose: Basic Science
Official Title: Pasta and Other Durum Wheat-based Products: Effects on Post-prandial Glucose Metabolism
Study Start Date : September 2015
Actual Primary Completion Date : June 2016
Actual Study Completion Date : July 2016

Arm Intervention/treatment
Active Comparator: Control
Glucose monohydrate (isoglucidic portion -50 g of available carbohydrates-)
Other: Glucose
Glucose monohydrate (55 g) dissolved with 500 mL of water

Experimental: Semolina
Semolina soup (isoglucidic portion -50 g of available carbohydrates-)
Other: Semolina soup
Semolina soup (322 g) eaten with 500 mL of water

Experimental: Bread
Bread (isoglucidic portion -50 g of available carbohydrates-)
Other: Bread
Bread (122 g) eaten with 500 mL of water

Experimental: Short pasta (fresh)
Fresh penne (isoglucidic portion -50 g of available carbohydrates-)
Other: Penne (fresh)
Cooked penne (132 g) eaten with 500 mL of water

Experimental: Short pasta (dry)
Short pasta (dry) (isoglucidic portion -50 g of available carbohydrates-)
Other: Penne (dry)
Cooked penne (142 g) eaten with 500 mL of water

Experimental: Long pasta (dry)
Long pasta (dry) (isoglucidic portion -50 g of available carbohydrates-)
Other: Spaghetti (dry)
Cooked spaghetti (142 g) eaten with 500 mL of water




Primary Outcome Measures :
  1. incremental area under the curve for plasma glucose [ Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes) ]

Secondary Outcome Measures :
  1. post-prandial insulin plasma concentration [ Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes) ]
  2. post-prandial c-peptide plasma concentration [ Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes) ]
  3. post-prandial GLP-1 plasma concentration [ Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes) ]
  4. post-prandial GIP plasma concentration [ Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes) ]
  5. post-prandial glucagon plasma concentration [ Time Frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes) ]


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Ages Eligible for Study:   18 Years to 60 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Criteria

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03024983


Locations
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Italy
Department of Food Science, University of Parma
Parma, Italy, 43125
Sponsors and Collaborators
University of Parma
Investigators
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Principal Investigator: Francesca Scazzina, Professor Department of Food Science, University of Parma
Study Director: Furio Brighenti, Professor Department of Food Science, University of Parma
Publications:
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

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Responsible Party: Francesca Scazzina Ph.D., Assistant Professor, University of Parma
ClinicalTrials.gov Identifier: NCT03024983    
Other Study ID Numbers: DWP1
First Posted: January 19, 2017    Key Record Dates
Last Update Posted: January 19, 2017
Last Verified: January 2017
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No