Showing papers by "Thomas M.S. Wolever published in 2009"

Physicochemical properties of β-glucan in differently processed oat foods influence glycemic response.

Abstract: To assess the effect of food processing on the capacity of oat β-glucan to attenuate postprandial glycemia, isocaloric crisp bread, granola, porridge, and pasta containing 4 g of β-glucan as well as control products with low β-glucan content were prepared. The physicochemical properties (viscosity, peak molecular weight (Mp), and concentration (C)) of β-glucan in in-vitro-digestion extracts were evaluated, and fasting and postprandial blood glucose concentrations were measured in human subjects. Porridge and granola had the highest efficacy in attenuating the peak blood glucose response (PBGR) because of their high Mp and viscosity. β-Glucan depolymerization in bread and pasta reduced β-glucan bioactivity. Pastas, known to have low glycemic responses, showed the lowest PBGR. The analyses of these products with previously reported data indicated that 73% of the bioactivity in reducing PBGR can be explained by Mp × C. Characterizing the physicochemical properties of β-glucan in bioactive foods aids function...

Metabolic syndrome and its components as predictors of incident type 2 diabetes mellitus in an Aboriginal community

Abstract: Background: Risk factors for type 2 diabetes remain poorly characterized among Aboriginal Canadians. We aimed to determine the incidence of type 2 diabetes in an Aboriginal community and to evaluate prospective associations with metabolic syndrome and its components. Methods: Of 606 participants in the Sandy Lake Health and Diabetes Project from 1993 to 1995 who were free of diabetes at baseline, 540 (89.1%) participated in 10-year follow-up assessments. Baseline anthropometry, blood pressure, fasting insulin and serum lipid levels were measured. Fasting and 2-hour postload glucose levels were obtained at follow-up to determine incident cases of type 2 diabetes. Results: The 10-year cumulative incidence of diabetes was 17.5%. High adiposity, dyslipidemia, hyperglycemia, hyperinsulinemia and hypertension at baseline were associated with an increased risk of diabetes after adjustment for age and sex (all p ≤ 0.03). Metabolic syndrome had high specificity (75%–88%) and high negative predictive value (85%–87%) to correctly detect diabetes-free individuals at follow-up. It had low sensitivity (26%–48%) and low positive predictive value (29%–32%) to detect future diabetes. Metabolic syndrome at baseline was associated with incident diabetes after adjustment for age and sex, regardless of whether the syndrome was defined using the National Cholesterol Education Program criteria (odds ratio [OR] 2.03, 95% confidence interval [CI] 1.10–3.75) or the International Diabetes Federation criteria (OR 2.14, 95% CI 1.29–3.55). The association was to the same degree as that for impaired glucose tolerance assessed using the oral glucose tolerance test (OR 2.87, 95% CI 1.52–5.40; p > 0.05 for comparison of C statistics). Interpretation: Metabolic syndrome and its components can be identified with readily available clinical measures. As such, the syndrome may be useful for identifying individuals at risk of type 2 diabetes in remote Aboriginal communities.

Simple and complex carbohydrates.

Abstract: A literature review examines and compares the gastrointestinal uptake of and subsequent glycemic response (GR) to simple and complex dietary carbohydrates. Topics addressed include: differences in digestion rates and GR between different starchy foods; physiological effects of slowly absorbed (lente) carbohydrate foods; and factors influencing starch absorption and GR (e.g., interactions, food particle size, fiber composition). The utility of the glycemic index for classifying foods according to their resultant GR also is discussed. It is concluded that due to differences in the digestive rate for different starchy foods, it is possible that diets can be manipulated to achieve desired effects in treating diabetes and hyperlipidemia.(wz)

Effect of coffee and tea on the glycaemic index of foods: no effect on mean but reduced variability.

Abstract: Coffee and tea may influence glycaemic responses but it is not clear whether they affect the glycaemic index (GI) value of foods. Therefore, to see if coffee and tea affected the mean and SEM of GI values, the GI of fruit leather (FL) and cheese puffs (CP) were determined twice in ten subjects using the FAO/WHO protocol with white bread as the reference food. In one series subjects chose to drink 250 ml of either coffee or tea with all test meals, while in the other series they drank 250 ml water. The tests for both series were conducted as a single experiment with the order of all tests being randomised. Coffee and tea increased the overall mean peak blood glucose increment compared with water by 0.25 (SEM 0.09) mmol/l (P=0.02), but did not significantly affect the incremental area under the glucose response curve. Mean GI values were not affected by coffee or tea but the SEM was reduced by about 30% (FL: 31 (SEM 4) v. 35 (SEM 7) and CP: 76 (SEM 6) v. 75 (SEM 8) for coffee or tea v. water, respectively). The error mean square term from the ANOVA of the GI values was significantly smaller for coffee or tea v. water (F(18, 18) = 2.31; P=0.04). We conclude that drinking coffee or tea with test meals does not affect the mean GI value obtained, but may reduce variability and, hence, improve precision.

Research brief Effect of blood sampling schedule on the ability to discriminate between postprandial glycemic responses

Abstract: Objective: The blood glucose responses elicited by foods are often determined using blood samplestaken at 15-min intervals. Our objective was to see whether taking blood samples at 10-min intervalsaffected the results.Methods: Overnight-fasted healthy subjects (n¼11) were studied on nine different occasions withsevendifferenttestmeals.Bloodsampleswereobtainedatfastingandat10,15,20,30,40,45,50,60,90,and120 minafterstartingtoeat.Peakrise,incrementalareaunderthecurve,andrelativeglycemicresponse were calculated using the 10- and 15-min sampling schedules.Results: With10-minintervals,peakrisewas4%greaterthanwith15-minintervals(P<0.001),butsampling interval did not significantly affect mean incremental area under the curve or relative glyce-mic response. The 10-min blood sampling schedule had a slightly greater ability to discriminatebetween foods and between subjects for peak rise and relative glycemic response.Conclusions: We conclude that the blood sampling schedule used may influence the accuracy andprecision of measurements of glycemic response; however, the difference between taking blood sam-ples at 10-min and 15-min intervals is quite small. 2009 Elsevier Inc. All rights reserved.