Effect of volume and type of beverage consumed with a standard test meal on postprandial blood glucose responses

The Effect of Adding Protein to a Carbohydrate Meal on Postprandial Glucose and Insulin Responses: A Systematic Review and Meta-Analysis of Acute Controlled Feeding Trials

BACKGROUND

Protein influences acute postprandial glucose and insulin responses, but the effects of dose, protein type, and health status are unknown.

OBJECTIVES

We aimed to determine the acute effect of adding protein to carbohydrate on postprandial responses and identify effect modifiers.

METHODS

We searched MEDLINE, EMBASE, and Cochrane databases through 30 July, 2023 for acute, crossover trials comparing acute postprandial responses elicited by carbohydrate-containing test meals with and without added protein in adults without diabetes or with type 2 (T2DM) or type 1 (T1DM) diabetes mellitus. Group data were pooled separately using generic inverse variance with random-effects models and expressed as the ratio of means with 95% confidence interval. Risk of bias and certainty of evidence (Grading of Recommendations Assessment, Development, and Evaluation) were assessed.

RESULTS

In 154 trial comparisons of animal, dairy, and plant proteins (without diabetes, n = 22, 67, 32, respectively; T2DM, n = 14, 16, 3, respectively), each gram protein per gram available carbohydrate (g/g) reduced the glucose area under the curve (AUC) less in adults with T2DM than in those without diabetes (-10% compared with -50%, P < 0.05) but increased the insulin AUC similarly (+76% compared with +56%). In subjects without diabetes, each g/g of dairy and plant protein reduced glucose AUC by 52% and 55%, respectively, and increased the insulin AUC by 64% and 45%, respectively (all P < 0.05). Animal proteins significantly reduced the glucose AUC by 31% and increased the insulin AUC by 37% (pooled effects) but without a significant dose-response. In adults with T2DM, animal protein reduced the glucose AUC by 13% and increased the insulin AUC by 105%, with no significant dose-response. Dairy protein reduced the glucose AUC by 18% (no dose-response), but each g/g increased the insulin AUC by 34% (P < 0.05). In adults with T1DM, protein increased the glucose AUC by 40% (P < 0.05, n = 5). Data source (reported AUC compared with calculated AUC) and study methodology quality significantly modified some outcomes and contributed to high between-study heterogeneity.

CONCLUSIONS

In people without diabetes, adding dairy or plant protein to a carbohydrate-containing meal elicits physiologically significant reductions in glucose AUC and increases insulin AUC. Animal protein may slightly reduce the glucose AUC and may increase the insulin AUC. In people with T2DM, protein may not have such large and consistent effects. Further research is needed to determine if the effects of protein differ by health status and protein source. This study was registered at PROSPERO as CRD42022322090.

The association between water intake and future cardiometabolic disease outcomes in the Malmö Diet and Cancer cardiovascular cohort

The aim of this study was to explore the longitudinal association between reported baseline water intake and incidence of coronary artery disease (CAD) and type 2 diabetes in the Malmö Diet and Cancer Cohort (n = 25,369). Using cox proportional hazards models, we separately modelled the effect of plain and total (all water, including from food) water on CAD and type 2 diabetes risk, whilst adjusting for age, sex, diet collection method, season, smoking status, alcohol intake, physical activity, education level, energy intake, energy misreporting, body mass index, hypertension, lipid lowering medication, apolipoprotein A, apolipoprotein B, and dietary variables. Sensitivity analyses were run to assess validity. After adjustment, no association was found between tertiles of plain or total water intake and type 2 diabetes risk. For CAD, no association was found comparing moderate to low intake tertiles from plain or total water, however, risk of CAD increased by 12% (95% CI 1.03, 1.21) when comparing high to low intake tertiles of plain water, and by 17% (95% CI 1.07, 1.27) for high versus low tertiles of total water. Sensitivity analyses were largely in agreement. Overall, baseline water intake was not associated with future type 2 diabetes risk, whilst CAD risk was higher with higher water intakes. Our findings are discordant with prevailing literature suggesting higher water intakes should reduce cardiometabolic risk. These findings may be an artefact of limitations within the study, but future research is needed to understand if there is a causal underpinning.

The effect of oat β-glucan on postprandial blood glucose and insulin responses: a systematic review and meta-analysis

To determine the effect of oat β‑glucan (OBG) on acute glucose and insulin responses and identify significant effect modifiers we searched the MEDLINE, EMBASE, and Cochrane databases through October 27, 2020 for acute, crossover, controlled feeding trials investigating the effect of adding OBG (concentrate or oat-bran) to carbohydrate-containing test-meals compared to comparable or different carbohydrate-matched control-meals in humans regardless of health status. The primary outcome was glucose incremental area-under-the-curve (iAUC). Secondary outcomes were insulin iAUC, and glucose and insulin incremental peak-rise (iPeak). Two reviewers extracted the data and assessed risk-of-bias and certainty-of-evidence (GRADE). Data were pooled using generic inverse-variance with random-effects model and expressed as ratio-of-means with [95% CIs]. We included 103 trial comparisons (N = 538). OBG reduced glucose iAUC and iPeak by 23% (0.77 [0.74, 0.81]) and 28% (0.72 [0.64, 0.76]) and insulin by 22% (0.78 [0.72, 0.85]) and 24% (0.76 [0.65, 0.88]), respectively. Dose, molecular-weight, and comparator were significant effect modifiers of glucose iAUC and iPeak. Significant linear dose-response relationships were observed for all outcomes. OBG molecular-weight >300 kg/mol significantly reduced glucose iAUC and iPeak, whereas molecular-weight <300 kg/mol did not. Reductions in glucose iAUC (27 vs 20%, p = 0.03) and iPeak (39 vs 25%, p < 0.01) were significantly larger with different vs comparable control-meals. Outcomes were similar in participants with and without diabetes. All outcomes had high certainty-of-evidence. In conclusion, current evidence indicates that adding OBG to carbohydrate-containing meals reduces glycaemic and insulinaemic responses. However, the magnitude of glucose reduction depends on OBG dose, molecular-weight, and the comparator.

Potential contributions of the methodology to the variability of glycaemic index of foods

Glycaemic index (GI) testing provides a useful point of comparison between carbohydrate sources. For this comparison to be meaningful, the methods used to determine GI values need to be rigorous and consistent between testing events. This requirement has led to increasing standardization of the GI methodology, with an international standard developed in joint consultation with FAO/WHO (ISO 26642:2010) currently the most up to date document. The purpose of this review is to compare the international standard to methods of published studies claiming to have performed a GI test. This analysis revealed that the international standard permits a wide range of choices for researchers when designing a GI testing plan, rather than a single standardized protocol. It has also been revealed that the literature contains significant variation, both between studies and from the international standard for critical aspects of GI testing methodology. The primary areas of variation include; what glucose specification is used, which reference food is used, how much reference food is given, what drink is given during testing, the blood sampling site chosen and what assay and equipment is used to measure blood glucose concentration. For each of these aspects we have explored some of the methodological and physiological implications of these variations. These insights suggest that whilst the international standard has assisted with framing the general parameters of GI testing, further stan-dardization to testing procedures is still required to ensure the continued relevance of the GI to clinical nutrition.

Increasing the viscosity of oat β-glucan beverages by reducing solution volume does not reduce glycaemic responses

The soluble fibre (1 → 3)(1 → 4)-β-d-glucan attenuates postprandial glycaemic responses when administered in solution. This attenuating effect is strengthened when solution viscosity is increased by increasing the β-glucan dose or molecular weight (MW). The effect of varying solution viscosity by changing solution volume, without changing the β-glucan dose or MW, on glycaemic responses was determined. A total of fifteen healthy subjects received six 50 g oral glucose beverages prepared with or without 4 g of high-MW (HMW, 580 000 g/mol) or low-MW (LMW, 145 000 g/mol) β-glucan, with a beverage volume of 250 or 600 ml. Postprandial plasma glucose concentration was measured over 2 h, and the peak blood glucose rise (PBGR) and the incremental area under the glycaemic response curve (AUC) were calculated. Subjects served as their own controls. The physico-chemical properties of the beverages were measured to examine their relationship with glycaemic response results. The HMW β-glucan beverage was more viscous and achieved greater reductions in PBGR than the glucose beverage with LMW β-glucan (P< 0·05). At the same MW, the 250 and 600 ml β-glucan beverages differed in viscosity (>9-fold difference) but not in PBGR (P>0·05). No differences in AUC were detected among the beverages (P= 0·147). The effects of β-glucan on glycaemic response were altered by changes in beverage viscosity achieved through changes in MW but not in volume. Therefore, β-glucan dose and MW are the most vital characteristics for optimising the bioactivity of β-glucan solutions with respect to glycaemic response.

Glycaemic index methodology

The glycaemic index (GI) concept was originally introduced to classify different sources of carbohydrate (CHO)-rich foods, usually having an energy content of >80 % from CHO, to their effect on post-meal glycaemia. It was assumed to apply to foods that primarily deliver available CHO, causing hyperglycaemia. Low-GI foods were classified as being digested and absorbed slowly and high-GI foods as being rapidly digested and absorbed, resulting in different glycaemic responses. Low-GI foods were found to induce benefits on certain risk factors for CVD and diabetes. Accordingly it has been proposed that GI classification of foods and drinks could be useful to help consumers make 'healthy food choices' within specific food groups. Classification of foods according to their impact on blood glucose responses requires a standardised way of measuring such responses. The present review discusses the most relevant methodological considerations and highlights specific recommendations regarding number of subjects, sex, subject status, inclusion and exclusion criteria, pre-test conditions, CHO test dose, blood sampling procedures, sampling times, test randomisation and calculation of glycaemic response area under the curve. All together, these technical recommendations will help to implement or reinforce measurement of GI in laboratories and help to ensure quality of results. Since there is current international interest in alternative ways of expressing glycaemic responses to foods, some of these methods are discussed.

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

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.

The glycaemic index values of foods containing fructose are affected by metabolic differences between subjects

BACKGROUND/OBJECTIVES

Glycaemic responses are influenced by carbohydrate absorption rate, type of monosaccharide absorbed and the presence of fat; the effect of some of these factors may be modulated by metabolic differences between subjects. We hypothesized that glycaemic index (GI) values are affected by the metabolic differences between subjects for foods containing fructose or fat, but not for starchy foods.

SUBJECTS/METHODS

The GI values of white bread (WB), fruit leather (FL) and chocolate-chip cookies (CCC) (representing starch, fructose and fat, respectively) were determined in subjects (n=77) recruited to represent all 16 possible combinations of age (< or =40, >40 years), sex (male, female), ethnicity (Caucasian, non-Caucasian) and body mass index (BMI) (< or =25, >25 kg/m2) using glucose as the reference. At screening, fasting insulin, lipids, c-reactive protein (CRP), aspartate transaminase (AST) and waist circumference (WC) were measured.

RESULTS

There were no significant main effects of age, sex, BMI or ethnicity on GI, but there were several food x subject-factor interactions. Different factors affected each food's area under the curve (AUC) and GI. The AUC after oral glucose was related to ethnicity, age and triglycerides (r 2=0.27); after WB to ethnicity, age, triglycerides, sex and CRP (r 2=0.43); after CCC to age and weight (r 2=0.18); and after FL to age and CRP (r 2=0.12). GI of WB was related to ethnicity (r 2=0.12) and of FL to AST, insulin and WC (r 2=0.23); but there were no significant correlations for CCC.

CONCLUSIONS

The GI values of foods containing fructose might be influenced by metabolic differences between -subjects, whereas the GI of starchy foods might be affected by ethnicity. However, the proportion of variation explained by subject factors is small.

Glycaemic index of selected staples commonly eaten in the Caribbean and the effects of boiling v. crushing

Integrating information about the glycaemic index (GI) of foods into the Caribbean diet is limited by the lack of data. Therefore, we determined the GI of eight staple foods eaten in the Caribbean and the effect on GI of crushing selected tubers. Groups of eight to ten healthy volunteers participated in three studies at two sites. GI was determined using a standard method with white bread and adjusted relative to glucose. The mean area under the glucose response curve elicited by white bread was similar for the different groups of subjects. In study 1, the GI of cassava (Manihot esculenta; 94 (SEM 11)) was significantly higher than those of breadfruit (Artocarpus altilis; 60 (SEM 9)), cooking ‘green’ banana (Musa spp.; 65 (SEM 11)) and sadha roti (65 (SEM 9)) (P=0·018). There was no significant difference in the GI of the foods in study 2: dasheen (Colocasia esculenta var. esculenta; 77 (SEM 10)), eddoes (Colocasia esculenta var. antiquorum; 61 (SEM 10)), Irish potato (Solanum tuberosum; 71 (SEM 8)), tannia (Xanthosoma sagittifolium; 60 (SEM 5)) and white yam (Dioscorea alata; 62 (SEM 6)), and, in study 3, crushing did not significantly affect the GI of dasheen, tannia or Irish potato. However, when the results from studies 2 and 3 were pooled, the GI of dasheen (76 (SEM 7)) was significantly greater than that of tannia (55 (SEM 5); P=0·015) with potato being intermediate (69 (SEM 6)). We conclude that dasheen and cassava are high-GI foods, whereas the other tubers studied and sadha roti are intermediate-GI foods. Given the regular usage of cassava and dasheen in Caribbean diets we speculate that these diets would tend to be high GI, although this could be reduced by foods such as sadha roti and white yam. The range of GI between the staples is sufficiently large that health benefits may be accrued by replacing high-GI staples with intermediate-GI staples in the Caribbean diet.