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/m²): 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 carbohydrate-containing 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.

Keywords: glycemic index; glycemic load; healthy participants; macronutrients and fiber; variability.

FIGURE 1

Mean ± SD glycemic response and measured and calculated meal GI and GL after the consumption of a glucose reference and WB with different amounts of additional macronutrients or fiber. Serum postprandial glucose concentrations (A1–A4), incremental glucose AUC (B1–B4), measured and calculated meal GI (C1–C4), and measured and calculated meal GL (D1–D4) after the food challenges or consumption of the glucose reference drink during the 2-h test period are presented for studies 1–4. Differences in serum postprandial glucose concentrations (A1–A4) in food challenges over the 2-h test period were determined with the use of 2-factor mixed ANOVA with the main effects of food challenges and time and the food challenges × time interaction with repeated measures. Differences in the incremental glucose AUC (B1−B4), measured and calculated meal GI (C1–C4) and measured and calculated meal GL (D1–D4) values in food challenges over the 2-h test period in each individual study were determined with the use of mixed-design ANOVA model with the participant as a random effect and the food challenge as a fixed effect. The Tukey-Kramer method was used for the post hoc analyses. Differences in calculated meal GI and GL values in study 1 were compared with the use of Friedman’s chi-square test with Dunn’s multiple-comparison test as post hoc analyses. Differences between measured and calculated meal GI and GL values within each food-challenge group were compared with the use of a paired t test or Wilcoxon’s signed rank sum test depending on the data distribution. The statistical analysis was performed only with food challenges that contained WB and did not include the glucose reference drink. Statistical analyses with measured meal GI and GL values and calculated meal GI and GL values were performed separately. Significance was accepted at P ≤ 0.05. Means denoted by different lowercase letters were significantly different from each other. ***Significantly different from calculated meal GI or GL values within the same food-challenge group, P < 0.001. Sample sizes for studies 1–4 were 20, 22, 20, and 20, respectively. CHO, carbohydrate; GI, glycemic index; GL, glycemic load; PRO, protein; WB, white bread.

FIGURE 2

Mean ± SD insulin response and insulin index after consumption of a glucose reference and WB with different amounts of additional macronutrients or fiber. Serum postprandial insulin concentrations (A1–A4), incremental insulin AUC (B1–B4), and insulin index (C1–C4) after food challenges and consumption of the glucose reference drink during the 2-h test period are presented for studies 1–4. Differences in serum postprandial insulin concentrations (A1–A4) in food challenges over the 2-h test period were determined with the use of a 2-factor mixed ANOVA with the main effects of food challenges and time and the food challenges × time interaction with repeated measures. Differences in incremental insulin AUC (B1–B4) and insulin index (C1–C4) values in food challenges over the 2-h test period in each individual study were determined with the use of a mixed-design ANOVA model with the participant as a random effect and the food challenge as a fixed effect. The Tukey-Kramer method was used for post hoc analyses. The statistical analysis was performed only with food challenges that contained WB and did not include the glucose reference drink. Significance was accepted at P ≤ 0.05. Means denoted by different lowercase letters were significantly different from each other. Sample sizes for studies 1–4 were 20, 22, 20, and 20, respectively. CHO, carbohydrate; PRO, protein; WB, white bread.

FIGURE 3

Mean ± SD postprandial serum HDL-C, LDL-C, TAG, and NEFA responses to challenges with a glucose reference and WB with different amounts of additional macronutrients or fiber. Serum HDL-C (A1–A4), LDL-C (B1–B4), TAG (C1–C4), and NEFA (D1–D4) concentrations after food challenges and consumption of the glucose reference drink during the 2-h test period are presented for studies 1–4. Differences in serum HDL-C (A1–A4), LDL-C (B1–B4), TAG (C1–C4), and NEFA (D1–D4) concentrations in food challenges over the 2-h test period were determined with the use of 2-factor mixed ANOVA with the main effects of food challenges and time and the food challenges × time interaction with repeated measures. The statistical analysis was performed only with food challenges that contained WB and did not include the glucose reference drink. Significance was accepted at P ≤ 0.05. Sample sizes for studies 1–4 were 20, 22, 20, and 20, respectively. CHO, carbohydrate; HDL-C, HDL cholesterol; LDL-C, LDL cholesterol; NEFA, nonesterified fatty acid; PRO, protein; TAG, triacylglycerol; WB, white bread.