An interventional study of Glucose and Semolina soup in Dietary Modification, sponsored by University of Parma. Completed at 1 site in Italy. Open to participants aged 18 Years to 60 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2017-01-19.
Sponsored by University of Parma · Not applicable, Interventional, and Basic science
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).
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.
University of Parma is the lead sponsor of 76 studies on the registry; 8 are open to participants now.
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Exclusion Criteria:
Glucose monohydrate (isoglucidic portion -50 g of available carbohydrates-)
Other: Glucose
Semolina soup (isoglucidic portion -50 g of available carbohydrates-)
Other: Semolina soup
Bread (isoglucidic portion -50 g of available carbohydrates-)
Other: Bread
Fresh penne (isoglucidic portion -50 g of available carbohydrates-)
Other: Penne (fresh)
Short pasta (dry) (isoglucidic portion -50 g of available carbohydrates-)
Other: Penne (dry)
Long pasta (dry) (isoglucidic portion -50 g of available carbohydrates-)
Other: Spaghetti (dry)
Glucose monohydrate (55 g) dissolved with 500 mL of water
Semolina soup (322 g) eaten with 500 mL of water
Bread (122 g) eaten with 500 mL of water
Cooked penne (132 g) eaten with 500 mL of water
Cooked penne (142 g) eaten with 500 mL of water
Cooked spaghetti (142 g) eaten with 500 mL of water
incremental area under the curve for plasma glucose
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
post-prandial insulin plasma concentration
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
post-prandial c-peptide plasma concentration
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
post-prandial GLP-1 plasma concentration
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
post-prandial GIP plasma concentration
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
post-prandial glucagon plasma concentration
Time frame: 2 hours (-10 and 0 -fasting-, 15, 30, 45, 60, 90, 120 minutes)
Plan to share: No
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