Effect of macronutrients and fiber on postprandial glycemic responses and meal glycemic index and glycemic load value determinations

Abstract

Background: The potential confounding effect of different amounts and proportions of macronutrients across eating patterns on meal or dietary glycemic index (GI) and glycemic load (GL) value determinations has remained partially unaddressed. Objective: The study aimed to determine the effects of different amounts of macronutrients and fiber on measured meal GI and GL values. Design: Four studies were conducted during which participants [n = 20-22; women: 50%; age: 50-80 y; body mass index (in kg/m 2 ): 25-30)] received food challenges containing different amounts of the variable nutrient in a random order. Added to the standard 50 g available carbohydrate from white bread was 12.5, 25, or 50 g carbohydrate; 12.5, 25, or 50 g protein; and 5.6, 11.1, or 22.2 g fat from rice cereal, tuna, and unsalted butter, respectively, and 4.8 or 9.6 g fiber from oat cereal. Arterialized venous blood was sampled for 2 h, and measured meal GI and GL and insulin index (II) values were calculated by using the incremental area under the curve (AUC i ) method. Results: Adding carbohydrate to the standard white-bread challenge increased glucose AUC i (P , 0.0001), measured meal GI (P = 0.0066), and mean GL (P , 0.0001). Adding protein (50 g only) decreased glucose AUC i (P = 0.0026), measured meal GI (P = 0.0139), and meal GL (P = 0.0140). Adding fat or fiber had no significant effect on these variables. Adding carbohydrate (50 g), protein (50 g), and fat (11.1 g) increased the insulin AUC i or II; fiber had no effect. Conclusions: These data indicate that uncertainty in the determination of meal GI and GL values is introduced when carbohydratecontaining foods are consumed concurrently with protein (equal amount of carbohydrate challenge) but not with carbohydrate-, fat-, or fiber-containing foods. Future studies are needed to evaluate whether this uncertainty also influences the prediction of average dietary GI and GL values for eating patterns. This trial was registered at clinicaltrials.gov as NCT01023646.Am J Clin Nutr 2017;105:842-53.

Quality attributes of breads from high‐quality cassava flour improved with wet gluten

“…Since the major contributing components to the calorie contents of the various bread samples differ, varying implications on possible glycaemic indices are possible. Wheat bread in this study will likely have lower glycaemic response than cassava breads, owing to lower carbohydrate and higher protein content (Meng, Matthan, Ausman, & Lichtenstein, 2017). However, the higher fibre content of cassava breads might have a positive effect on its glycaemic response as well.…”

Effect of an alcohol-free beer enriched with isomaltulose and a resistant dextrin on insulin resistance in diabetic patients with overweight or obesity

“…Several clinical trials have documented the beneficial effect of low-glycemic index (GI) diets on glycemic control in T2DM [8]. More recently, several studies have demonstrated that the impact of carbohydrates on insulin secretion and postprandial glycemia can substantially change depending on the types of foods with which the carbohydrates are consumed [9].…”

High orange juice consumption with or in-between three meals a day differently affects energy balance in healthy subjects

“…Contrary to the finding of Meng et al 2017, in the present study the incremental glucose area under the curve did not differ and MAGE-Index was higher with WM-intervention compared to BM-intervention. Hence we may deduce that postprandial glycemia is not attenuated by a concurrent meal when sugar is consumed in a liquid form that quickly passes the stomach into the intestine 19 . This is in line with no significant differences in fructosamine levels between the interventions (Table 1 ).…”

“…Intake of sugar-containing drinks with or in-between meals may differently affect metabolic regulation, because postprandial glycemia is lowered especially by protein content of the diet, which is due to slower gastric emptying and enhanced insulin response 19 . On the other hand, intake of juice in-between main meals (e.g., snacking behavior) may prevent the drop in insulin between meals and thus may inhibit effective lipid oxidation.…”