A whey protein supplement decreases post-prandial glycemia

<p>Abstract</p> <p>Background</p> <p>Incidence of diabetes, obesity and insulin resistance are associated with high glycemic load diets. Identifying food components that decrease post-prandial glycemia may be beneficial for developing low glycemic foods and supplements. This study explores the glycemic impact of adding escalating doses of a glycemic index lowering peptide fraction (GILP) from whey to a glucose drink.</p> <p>Methods</p> <p>Ten healthy subjects (3M, 7F, 44.4 ± 9.3 years, BMI 33.6 ± 4.8 kg/m²) participated in an acute randomised controlled study. Zero, 5, 10 and 20 g of protein from GILP were added to a 50 g glucose drink. The control (0 g of GILP) meal was repeated 2 times. Capillary blood samples were taken fasting (0 min) and at 15, 30, 45, 60, 90 and 120 minutes after the start of the meal and analyzed for blood glucose concentration.</p> <p>Results</p> <p>Increasing doses of GILP decreased the incremental areas under the curve in a dose dependant manner (Pearson's r = 0.48, p = 0.002). The incremental areas (iAUC) under the glucose curve for the 0, 5, 10, and 20 g of protein from GILP were 231 ± 23, 212 ± 23, 196 ± 23, and 138 ± 13 mmol.min/L respectively. The iAUC of the 20 g GILP was significantly different from control, 5 g GILP and 10 g GILP (p < 0.001). Average reduction in the glucose iAUC was 4.6 ± 1.4 mmol.min/L per gram of ingested GILP.</p> <p>Conclusion</p> <p>Addition of GILP to a oral glucose bolus reduces blood glucose iAUC in a dose dependent manner and averages 4.6 ± 1.4 mmol.min/L per gram of GILP. These data are consistent with previous research on the effect of protein on the glycemic response of a meal.</p

Alcohol consumption and acute myocardial infarction: A benefit of alcohol consumed with meals?

Background: The apparent favorable effect of alcohol on the risk of acute myocardial infarction (MI) may be related to its hypoinsulinemic effect when consumed with meals. We studied how the timing of alcohol consumption in relation to meals might affect the risk of MI in a population with relatively high regular alcohol consumption. Methods: We conducted a case-control study between 1995 and 1999 in Milan, Italy. Cases were 507 subjects with a first episode of nonfatal acute MI, and controls were 478 patients admitted to hospitals for other acute diseases. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by multiple logistic regression models. Results: Compared with nondrinkers, an inverse trend in risk was observed when alcohol was consumed during meals only (for greater than or equal to3 drinks per day: OR=0.50; 95% CI=0.30-0.82). In contrast, no consistent trend in risk was found for subjects drinking outside of meals (for greater than or equal to3 drinks per day: 0.98; 0.49-1.96). The pattern of risk was similar when we considered people who drank only wine. Conclusions: Alcohol drinking during meals was inversely related with risk of acute MI, whereas alcohol drinking outside meals only was unrelated to risk

Dietary glycemic index and glycemic load, and breast cancer risk: A case-control study

Background: Certain types of carbohydrates increase glucose and insulin levels to a greater extent than others. In turn, insulin may raise levels of insulin-like growth factors, which may influence breast cancer risk. We analyzed the effect of type and amount of carbohydrates on breast cancer risk, using the glycemic index and the glycemic load measures in a large case-control study conducted in Italy. Patients and methods: Cases were 2569 women with incident, histologically-confirmed breast cancer interviewed between 1991 and 1994. Controls were 2588 women admitted to the same hospital network for a variety of acute, non-neoplastic conditions. Average daily glycemic index and glycemic load were calculated from a validated 78-item food frequency questionnaire. Results: Direct associations with breast cancer risk emerged for glycemic index (odds ratio, OR for highest vs. lowest quintile = 1.4; P for trend <0.01) and glycemic load (OR = 1.3; P < 0.01). High glycemic index foods, such as white bread, increased the risk of breast cancer (OR = 1.3) while the intake of pasta, a medium glycemic index food, seemed to have no influence (OR = 1.0). Findings were consistent across different strata of menopausal status, alcohol intake, and physical activity level. Conclusions: This study supports the hypothesis of moderate, direct associations between glycemic index or glycemic load and breast cancer risk and, consequently, a possible role of hyperinsulinemia/insulin resistance in breast cancer development. RI Jenkins, David/A-1992-2009; Parpinel, Maria/B-1605-201

Dietary glycemic index and glycemic load and breast cancer risk: a case-control study

Background: Certain types of carbohydrates increase glucose and insulin levels to a greater extent than others. In turn, insulin may raise levels of insulin-like growth factors, which may influence breast cancer risk. We analyzed the effect of type and amount of carbohydrates on breast cancer risk, using the glycemic index and the glycemic load measures in a large case-control study conducted in Italy. Patients and methods: Cases were 2569 women with incident, histologically-confirmed breast cancer interviewed between 1991 and 1994. Controls were 2588 women admitted to the same hospital network for a variety of acute, non-neoplastic conditions. Average daily glycemic index and glycemic load were calculated from a validated 78-item food frequency questionnaire. Results: Direct associations with breast cancer risk emerged for glycemic index (odds ratio, OR for highest vs. lowest quintile = 1.4; P for trend < 0.01) and glycemic load (OR = 1.3; P < 0.01). High glycemic index foods, such as white bread, increased the risk of breast cancer (OR = 1.3) while the intake of pasta, a medium glycemic index food, seemed to have no influence (OR = 1.0). Findings were consistent across different strata of menopausal status, alcohol intake, and physical activity level. Conclusions: This study supports the hypothesis of moderate, direct associations between glycemic index or glycemic load and breast cancer risk and, consequently, a possible role of hyperinsulinemia/insulin resistance in breast cancer development

Glycemic index, glycemic load and risk of prostate cancer

Dietary carbohydrates have different glycemic and insulinemic potentials depending on type (glycemic index, GI) and amount (glycemic load, GL) of carbohydrate consumed or both. Insulin in turn has been implicated as a risk factor for several cancers, including that of the prostate. We assessed the relationship of GI and GL with prostate cancer risk in a multicenter case-control study. Cases and controls were recruited between 1991 and 2002 in the network of major teaching and general hospitals in 4 Italian areas. Cases were 1,204 men (age range 46-74 years) admitted for incident, histologically confirmed prostate cancer. Controls were 1,352 men (age range 46-74 years) admitted for acute, nonmalignant conditions unrelated to long-term modifications of diet. ORs of prostate cancer and the corresponding 95% Cls were derived using unconditional multiple logistic regression, including terms for age, study center, education, family history of prostate cancer, smoking, body mass index, physical activity, alcohol consumption, intake of energy, fiber and lycopenes. Compared to the lowest quintile of GI, the ORs were 1.23, 1.24, 1.47 and 1.57 for subsequent levels of GI. The corresponding values for GL were 0.91, 1.00, 1.20 and 1.41. No heterogeneity was found among strata of selected covariates. We found direct relations between dietary GI and GL and prostate cancer risk. Correcting for potential confounding factors did not substantially modify these associations. (C) 2004 Wiley-Liss, Inc. RI Jenkins, David/A-1992-200

Lipid, protein and carbohydrate intake in relation to body mass index: an Italian study

Objective: To analyse the association between macronutrient intake and body mass index (BMI). Design: A series of hospital-based case-control studies. Settings: Selected teaching and general hospitals in several Italian regions. Subjects: A total of 6619 subjects from the comparison groups of the case-control studies were included in the analysis. Methods: We obtained data from a validated 78-item food-frequency questionnaire submitted between 1991 and 2002. For various macronutrients, the partial regression coefficient (variation of BMI (kg m -2 ) per 100 kcal increment of energy intake) was derived from multiple linear regression models, after allowance for age, study centre, education, smoking habits, number of eating episodes and mutual adjustment for macronutrients. Results: BMI was directly associated with protein intake among women only (\u3b2 = 0.68) and with unsaturated fats in both genders (for monounsaturated fats \u3b2 = 0.27 for men and 0.26 for women; for polyunsaturated fats \u3b2 = 0.27 for men and 0.54 for women), and inversely related to carbohydrates (\u3b2 = - 0.05 for men and - 0.21 for women) and number of eating episodes in both genders (\u3b2 = - 0.42 for men and - 0.61 for women) and to saturated fats among women only (\u3b2 = - 0.57). Conclusions: These results confirm and provide convincing evidence that, after allowance for selected covariates including total energy intake, a protein-rich diet is not inversely related to BMI, and a carbohydrate-rich diet is not directly related to BMI

Dietary glycemic index, glycemic load and ovarian cancer risk: a case-control study

Background: Dietary carbohydrates vary in their ability to raise blood glucose and insulin levels, which, in turn, influence levels of sex hormones and insulin-like growth factors. We analyzed the effect of type and amount of carbohydrates on ovarian cancer risk, using the glycemic index (GI) and the glycemic load (GL) measurement in a large case-control study conducted in Italy. Materials and methods: Cases included 1031 women with incident, histologically confirmed epithelial ovarian cancer, from four Italian regions. Controls included 2411 women admitted to the same hospital networks for acute, non-neoplastic conditions. Average daily GI and GL were calculated from a validated food frequency questionnaire. Odds ratios (OR) and the corresponding 95% confidence intervals (CI) were computed using multiple logistic regression. Results: Ovarian cancer was directly associated with dietary GI (OR for highest versus lowest quartile = 1.7, 95% CI 1.3-2.1) and GL (OR = 1.7, 95% CI 1.3-2.1). The associations were observed in pre- and post-menopausal women, and they remained consistent across strata of major covariates identified. Conclusions: This study supports the hypothesis of a direct association between GI and GL and ovarian cancer risk and, consequently, of a possible role of hyperinsulinemia/insulin resistance in ovarian cancer development