Is glycaemic index (GI) a valid measure of carbohydrate quality?

The acute effects of variations in the flour composition of crackers on the glycemic index and glycemic responses in healthy adults

BACKGROUND/OBJECTIVES

This study assessed the glycemic index (GI) and glycemic load (GL) of three crackers formulated with different flours: a control cracker (CC) made with conventional flour, one with 30% whole wheat flour substitution (WWC), and another with 30% sunflower seed flour substitution (SFC). This study aimed to explore the impact of these substitutions, which vary in protein and fiber content, on the glycemic responses compared to a reference glucose drink.

SUBJECTS/METHODS

In a randomized controlled, crossover design, 11 healthy participants (mean age 23.5 ± 1 years; 7 women; BMI 23 ± 1 kg/m2), consumed cracker meals (CC, WWC, and SFC) each providing 50 g of available carbohydrates, and a 50 g glucose reference in separate sessions.

RESULTS

The SFC crackers provided low GI and GL values (GI: 53 on the glucose scale, GL: 6 per serving), whereas the WWC and CC crackers provided high GI (GI: 77 and 90 on the glucose scale, respectively) and medium GL values (11 and 12 per serving, respectively). Compared with the glucose reference and CC crackers, only SFC induced lower postprandial glucose concentrations, lower glucose excursions, and lower peak glucose values. All crackers were rated as enjoyable and associated with increased satiety.

CONCLUSIONS

SFC moderated postprandial glycemic responses compared to CC and the reference (D-glucose), but not WWC. These effects may be attributed to the soluble fibers and protein content of the SFC. These findings suggest potential benefits for body weight management and glycemic control, warranting further investigation of the role of flour substitutions in healthy snack options.

CLINICAL TRIAL REGISTRATION

This trial has been registered at Clinicaltrials.gov (NCT05702372).

Minimal Effective Dose of Beans Required to Elicit a Significantly Lower Glycemic Response Than Commonly Consumed Starchy Foods: Predictions Based on In Vitro Digestion and Carbohydrate Analysis

Beans elicit lower glycemic responses (GRs) than other starchy foods, but the minimum effective dose (MED) to reduce GR is unknown. We sought to determine the MED of beans compared to common starchy foods. Overnight-fasted healthy volunteers consumed ¼c (phase 1, n = 24) or ½c (phase 2, n = 18) of black, cranberry, great northern, kidney, navy and pinto beans and corn, rice, pasta and potato (controls), with blood glucose measured before and for 2 h after eating. GRs (incremental areas under the curves, iAUCs) after beans were consumed were compared to those of controls by ANOVA followed by Dunnett's test. To qualify for MED, beans had to elicit an effective reduction in GR, defined as a statistically significant reduction in iAUC of ≥20% (i.e., a relative glycemic response, RGR, ≤80). Outcomes from in vitro digestion were compared with in vivo RGR. Both doses of all six beans effectively reduced GR versus all four starchy controls, except for ¼c and ½c cranberry and pinto vs. corn, ¼c great northern and navy vs. corn and ¼c navy and pinto vs. potato. MED criteria were met for 18 comparisons of the ¼c servings, with four of the remaining six met by the ½c servings. The overall mean ± SEM RGR vs. controls was similar for the ¼c and ½c servings: 53 ± 4% and 56 ± 3%, respectively. By multiple regression analysis, RGR = 23.3 × RDS + 8.3 × SDS - 20.1 × RS + 39.5 × AS - 108.2 (rapidly digested starch, p < 0.001; slowly digested starch, p = 0.054; resistant starch, p = 0.18; available sugars, p = 0.005; model r = 0.98, p = 0.001). RGR correlated with in vitro glucose release (r = 0.92, p < 0.001). The MED of beans is ¼ cup. For n = 30 comparisons (n = 24 beans vs. controls, n = 6 controls vs. each other), an effective reduction in GR was predicted from in vitro carbohydrate analysis with 86% sensitivity and 100% specificity.

The Glycemic Index of Indica and Japonica Subspecies Parboiled Rice Grown in Italy and the Effect on Glycemic Index of Different Parboiling Processes

Rice is generally considered a high-glycemic index (GI) food, but numerous studies show that parboiling reduces the GI. There are no studies on GI of Indica and Japonica subspecies parboiled rice grown in Italy. The aim of this study was (1) to evaluate GI in different varieties of parboiled rice (ribe, white and brown long B, basmati, black, red, roma, and arborio); (2) to evaluate GI of same variety of rice subjected to different rice parboiling processes (parboiled ribe and parboiled long B with two different methods: flora and conventional method); (3) to evaluate GI of two by-products of parboiled rice: white and brown rice cake. Participants were 10 healthy individuals (20-30 years old, body mass index 18.5-25 kg/m²). Proximate composition and GI were determined by using standard methods. All parboiled rice assessed is low-GI (brown long B 48.1 ± 6.4 by flora method, ribe 52.0 ± 1.8 GI by flora method, black rice 52.3 ± 7.6 by flora method, long B 52.4 ± 3.9 by flora method, long B 53.4 ± 5.1 by conventional method, ribe 54.4 ± 4.3 GI by conventional method, Roma 54.4 ± 7.9 GI by flora method, and arborio 54.4 ± 7.9 GI by flora method), except red rice that is of medium-GI (56.1 ± 7.0 GI), and both classic and brown cakes that are high-GI (respectively, 83.3 ± 8.9 GI and 102.2 ± 5.5 GI). Parboiled rice is low-GI and so is favorable for the dietary management of metabolic disorders and celiac disease. Clinicaltrials.gov (NCT05333081).

The importance of molecular weight in determining the minimum dose of oat β-glucan required to reduce the glycaemic response in healthy subjects without diabetes: a systematic review and meta-regression analysis

To determine the minimum amount of oat β-glucan (OBG) required to reduce glycaemic responses (MinDose), we conducted a systematic review and meta-regression analysis of acute, crossover, single-meal feeding trials that examined the effects of adding OBG or oat bran to a carbohydrate-containing test-meal versus a control test-meal containing an equivalent amount of available-carbohydrate (avCHO) from the same or similar source. Medline, Embase, and Cochrane Library were searched up to 18 August 2021. The primary outcome was glucose incremental-area-under-the-curve (iAUC). Secondary outcomes included insulin iAUC, and glucose and insulin incremental peak-rise (iPeak). Two independent reviewers extracted data. Results were expressed as ratio-of-means (RoM) with 95% confidence intervals (CIs). Linear associations were assessed by random effects meta-regression. MinDose was defined as the dose at which the upper 95% CI of the regression line cut the line of no effect (i.e., RoM = 1). Fifty-nine comparisons (n = 340) were included; 57 in healthy subjects without diabetes and two in subjects with diabetes; 24 high-MW (>1000 kg/mol), 22 medium-MW (300-1,000 kg/mol), and 13 low-MW (<300 kg/mol). In healthy subjects without diabetes the associations between OBG dose and glucose iAUC and iPeak were linear (non-linear p value >0.05). MinDoses for glucose iAUC for high-MW, medium-MW and low-MW OBG, respectively, were estimated to be 0.2 g, 2.2 g and 3.2 g per 30 g avCHO; MinDoses for glucose iPeak were less than those for iAUC. Insufficient data were available to assess MinDose for insulin, however, there was no evidence of a disproportionate increase in insulin. More high-quality trials are needed to establish MinDose in individuals with diabetes.

Glycemic Responses of Milk and Plant-Based Drinks: Food Matrix Effects

The consumption of food items containing digestible carbohydrates in food products leads to postprandial increases in blood glucose levels and glycemic responses. The extent to which these occur depends on many factors, including concentration and type of carbohydrate, but also other physicochemical properties of the food matrix, which determine the rate of uptake of monosaccharides into the bloodstream, including product structure and factors affecting gastric emptying. For milk, control of postprandial glycemic responses appears to be multifaceted, including a controlled rate of gastric emptying, a rate of glucose and galactose uptake into the bloodstream controlled by enzymatic hydrolysis, as well as stimulated insulin secretion to enhance uptake of blood glucose from the bloodstream. Altogether, this allows milk to deliver comparatively high levels of carbohydrate with limited glycemic responses. For plant-based drinks positioned as milk alternatives, however, compositional differences (including carbohydrate type and concentration) as well as matrix factors limiting control over gastric emptying and insulin secretion can, in some cases, lead to much stronger glycemic responses, which are undesirable in relation to non-communicable diseases, such as type-2 diabetes. This review discusses glycemic responses to milk and plant-based drinks from this perspective, focusing on mechanistic insights and food matrix effects.

Penurunan Indeks Glikemik Nasi Putih dengan Penambahan Ekstrak Serai dan Daun Salam

Diabetes mellitus (DM) is one of the non-communicable diseases that could be prevented by consumption of foods capable of maintaining blood glucose at a safe level. Phenolic compounds are  components in food that affect blood glucose levels. Lemongrass and bay leaf are Indonesian spices commonly used for cooking and contain phenolic compounds that have potential as antidiabetic compounds. The aim of this study was to evaluate the effect of adding lemongrass and bay leaves water extracts on the GI value of cooked white rice. Lemongrass and bay leaves containing phenolic compounds were extracted with water and added to white rice during the cooking process or sprayed on cooked rice. The glycemic index of the tested food measured using the ISO 26642 method showed that the addition of lemongrass extract and a combination of lemongrass and bay leaf extract with total phenolic content (TPC) of 570 mg GAE/100 g and 565 mg GAE/100 g, respectively, on cooked white rice IR 64 resulted in the GI reduction in the cooked rice by 23 and 27%, respectively. These reduction was higher than those resulted from the addition of lemon grass or the combination of lemon grass and bay leaf extract during the cooking process, i.e. 9 and 13%, respectively.

Relations between in vitro starch digestibility of commercial baked products and their macronutrients

BACKGROUND

Baked products such as biscuits and breads are the staple foods for a large population, with the starch digestion rate having a crucial effect on human health. Currently, there is a lack of information on general starch digestibility in commercial baked products and its correlation with macronutrient content.

RESULTS

The present study investigated the starch digestibility of 35 commercial baked products, ranging from low to high moisture contents. Biscuits generally had a slower starch digestion rate than mini-breads, whereas breads including whole wheat bread had the fastest digestion rate. Additionally, starch digestibility was negatively correlated with the calorie (R²  = 0.71) and fat content (R²  = 0.56) in per serving size, possibly because of the formation of amylose-lipid complex.

CONCLUSION

The present study provides a database for the in vitro starch digestibility of a large number of food items, which gives general indications on the performance of starch components of commercial products in the human gastrointestinal tract. © 2022 Society of Chemical Industry.

Perspective: The Glycemic Index Falls Short as a Carbohydrate Food Quality Indicator to Improve Diet Quality

This perspective examines the utility of the glycemic index (GI) as a carbohydrate quality indicator to improve Dietary Guidelines for Americans (DGA) adherence and diet quality. Achieving affordable, high-quality dietary patterns can address multiple nutrition and health priorities. Carbohydrate-containing foods make important energy, macronutrient, micronutrient, phytochemical, and bioactive contributions to dietary patterns, thus improving carbohydrate food quality may improve diet quality. Following DGA guidance helps meet nutrient needs, achieve good health, and reduce risk for diet-related non-communicable diseases in healthy people, yet adherence by Americans is low. A simple indicator that identifies high-quality carbohydrate foods and improves food choice may improve DGA adherence, but there is no consensus on a definition. The GI is a measure of the ability of the available carbohydrate in a food to increase blood glucose. The GI is well established in research literature and popular resources, and some have called for including the GI on food labels and in food-based dietary guidelines. The GI has increased understanding about physiological responses to carbohydrate-containing foods, yet its role in food-based dietary guidance and diet quality is unresolved. A one-dimensional indicator like the GI runs the risk of being interpreted to mean foods are "good" or "bad," and it does not characterize the multiple contributions of carbohydrate-containing foods to diet quality, including nutrient density, a core concept in the DGA. New ways to define and communicate carbohydrate food quality shown to help improve adherence to high-quality dietary patterns such as described in the DGA would benefit public health.

Assessing Long-Term Impact of Dietary Interventions on Occurrence of Symptoms Consistent with Hypoglycemia in Patients without Diabetes: A One-Year Follow-Up Study

Background: A well-balanced nutritional diet pattern has a significant role in the management of diet-related disorders. Currently, there are no specific dietary guidelines to refer to when advising non-diabetic patients with symptoms attributed to hypoglycemia in the postprandial period or patients with confirmed reactive hypoglycemia (RH). The aim of this study was to investigate the impact of the dietary interventions, and their sustained outcome, on the severity of hypoglycemic-like symptoms occurring in non-diabetic patients. Methods: The study group included forty non-diabetic individuals with symptoms consistent with RH. At the baseline, each patient underwent RH diagnosis and complex dietary evaluation. Over a period of six months, each patient had four appointments with a dietitian. Two sessions were focused on a dietary education about low glycemic index diet (LGID) and Mediterranean diet (MD). The said diets were to be followed for a period of three months, with two additional dietary check-ups. Once dietary supervision was completed, patients had no imposed dietary patterns. The final follow-up appointment took place twelve months later and that is when each patient underwent a detailed assessment of their current dietary habits and evaluation of the frequency of symptoms consistent with hypoglycemia. Results: There was a statistically significant reduction in the severity in eight out of the ten analyzed hypoglycemic-like symptoms after the dietary interventions. The most significant change was observed in the following symptoms: hunger (η2 = 0.66), impaired concentration (η2 = 0.61), hand tremor (η2 = 0.55), and fatigue (η2 = 0.51). The outcomes were comparable for both recommended diets, the LGID and the MD. The reduction in hypoglycemic-like symptoms continued after the twelve-month period. The individualized dietary counselling significantly improved the patients’ eating habits in comparison to those present prior to intervention in terms of healthy diet index (F(2,78) = 27.30, p < 0.001, η2 = 0.41, 90%CI [0.26; 0.51]) and unhealthy diet index (F(2,78) = 433.39, p < 0.001, η2 = 0.91, 90%CI [0.89; 0.93]). Conclusions: Healthy modifications in dietary habits may improve patient’s well-being and reduce the severity of their postprandial symptoms attributed to hypoglycemia. Therefore, dietary intervention focused on appropriate nutritional management combined with follow-up consultations may be a beneficial step towards comprehensive treatment of non-diabetic patients who present with hypoglycemic-like symptoms in the postprandial period.

Dietary glycemic load and its association with glucose metabolism and lipid profile in young adults

BACKGROUND AND AIM

To evaluate the association of Glycemic Load (GL) with glucose metabolism and blood lipids among young adults.

METHODS AND RESULTS

This study included 1538 participants (51% females), evaluated at 21 years of age as part of the EPITeen cohort. The GL of each individual was obtained from the assessment of their dietary intake by using a 86-item semi-quantitative food frequency questionnaire. The evaluation included anthropometric measurements and a fasting blood sample was used to measure glucose, insulin, triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Insulin resistance was calculated based on the homeostasis model method (HOMA-IR). The association between the GL and the biochemical parameters was evaluated by linear regression models using β and 95% confidence intervals (95% CI), stratified by sex and adjusted for body mass index (BMI), energy and fiber intake, and self-perceived social class. No association was found between GL and the glucose metabolism parameters after adjustment. Regarding blood lipids, a positive association was found with LDL-C (β = 1.507, 95% CI 0.454; 2.561 for females; β = 0.216, 95% CI -0.587; 1.020 for males) and a negative association with HDL-C (β = -0.647, 95% CI -1.112; -0.181 for females; β = -0.131, 95% CI -0.422; 0.160 for males).

CONCLUSIONS

Our results suggest that, in healthy young subjects, a high GL diet may have a negative impact on lipid profile.

Dietary glycemic index and glycemic load in association with sleep duration: YaHS-TAMYZ and Shahedieh observational studies

BACKGROUND & AIMS

Current data on the association between dietary glycemic index (GI) and glycemic load (GL) and sleep duration are limited and controversial. The present cross-sectional study aimed to investigate the relationship between dietary GI and GL with sleep duration in a large number of adults living in central Iran.

METHODS

Baseline data from two Iranian cohorts were pooled for the current analysis: the YaHS-TAMYZ (n = 9962) and Shahedieh (n = 9977) studies. Demographic data as well as dietary intakes, sleep duration, and possible confounders, were collected by interview. Anthropometric measurements were also conducted by trained interviewers. Participants were categorized based on sleep duration [short (<6 h), normal (6-8 h), and long (>8 h)]. Multivariable logistic regression was used to determine the relationship between dietary GI/GL and the likelihood of short and long sleep duration.

RESULTS

In total, 10,451 participants aged 20-70 years were included in the analyses. After controlling for all possible confounders, no significant association was observed between dietary GI and short or long sleep duration (P > 0.05). Individuals in the highest quartile of dietary GL had a higher chance for long sleep duration compared to participants in the lowest quartile (OR = 1.41; 95% CI: 1.14, 1.74, P_trend = 0.001). No significant association was observed between dietary GL and short sleep duration.

CONCLUSION

Dietary GL is positively associated with the likelihood of long sleep duration. Future prospective studies are required to confirm the current findings.

Associations of quantity and quality of carbohydrate sources with subjective appetite sensations during 3-year weight-loss maintenance: Results from the PREVIEW intervention study

BACKGROUND & AIMS

The association of quantity and quality of carbohydrate sources with appetite during long-term weight-loss maintenance (WLM) after intentional weight loss (WL) is unclear. We aimed to investigate longitudinal associations of quantity and quality of carbohydrate sources with changes in subjective appetite sensations during WLM.

METHODS

This secondary analysis evaluated longitudinal data from the 3-year WLM phase of the PREVIEW study, a 2 × 2 factorial (diet-physical activity arms), multi-center, randomized trial. 1279 individuals with overweight or obesity and prediabetes (25-70 years; BMI≥25 kg m^-2) were included. Individuals were merged into 1 group to assess longitudinal associations of yearly changes in appetite sensations. Quantity and quality of carbohydrate sources including total carbohydrate, glycemic index (GI), glycemic load (GL), and total dietary fiber were assessed via 4-day food diaries at 4 timepoints (26, 52, 104, and 156 weeks) during WLM. Visual analog scales were used to assess appetite sensations in the previous week.

RESULTS

During WLM, participants consumed on average 160.6 (25th, 75th percentiles 131.1, 195.8) g·day^-1 of total carbohydrate, with GI 53.8 (48.7, 58.8) and GL 85.3 (67.2, 108.9) g day^-1, and 22.3 (17.6, 27.3) g·day^-1 of dietary fiber. In the available-case analysis, multivariable-adjusted linear mixed models with repeated measures showed that each 30-g increment in total carbohydrate was associated with increases in hunger (1.36 mm year^-1, 95% CI 0.77, 1.95, P < 0.001), desire to eat (1.10 mm year^-1, 0.59, 1.60, P < 0.001), desire to eat something sweet (0.99 mm year^-1, 0.30, 1.68, P = 0.005), and weight regain (0.20%·year^-1, 0.03, 0.36, P = 0.022). Increasing GI was associated with weight regain, but not associated with increases in appetite sensations. Each 20-unit increment in GL was associated with increases in hunger (0.92 mm year^-1, 0.33, 1.51, P = 0.002), desire to eat (1.12 mm year^-1, 0.62, 1.62, P < 0.001), desire to eat something sweet (1.13 mm year^-1, 0.44, 1.81, P < 0.001), and weight regain (0.35%·year^-1, 0.18, 0.52, P < 0.001). Surprisingly, dietary fiber was also associated with increases in desire to eat, after adjustment for carbohydrate or GL.

CONCLUSIONS

In participants with moderate carbohydrate and dietary fiber intake, and low to moderate GI, we found that higher total carbohydrate, GL, and total fiber, but not GI, were associated with increases in subjective desire to eat or hunger over 3 years. This study was registered as ClinicalTrials.gov, NCT01777893.

The carbohydrate-insulin model: a physiological perspective on the obesity pandemic

According to a commonly held view, the obesity pandemic is caused by overconsumption of modern, highly palatable, energy-dense processed foods, exacerbated by a sedentary lifestyle. However, obesity rates remain at historic highs, despite a persistent focus on eating less and moving more, as guided by the energy balance model (EBM). This public health failure may arise from a fundamental limitation of the EBM itself. Conceptualizing obesity as a disorder of energy balance restates a principle of physics without considering the biological mechanisms that promote weight gain. An alternative paradigm, the carbohydrate-insulin model (CIM), proposes a reversal of causal direction. According to the CIM, increasing fat deposition in the body-resulting from the hormonal responses to a high-glycemic-load diet-drives positive energy balance. The CIM provides a conceptual framework with testable hypotheses for how various modifiable factors influence energy balance and fat storage. Rigorous research is needed to compare the validity of these 2 models, which have substantially different implications for obesity management, and to generate new models that best encompass the evidence.

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.

Glycemic index, but not glycemic load, is associated with an increased risk of metabolic syndrome: Meta-analysis of observational studies

BACKGROUND

Diets with high glycemic index (GI) or high glycemic load (GL) have been linked to important risk factors associated with the development of metabolic syndrome (MetS), such as dyslipidemia, higher blood glucose, and insulin concentrations. However, the role of GI and GL in relation to Mets is still understudied and controversial. This review, therefore, assessed whether high GI or GL contribute to development of Mets.

METHODS

A systematic search of four bibliographic databases was conducted (MEDLINE/PubMed, EMBASE, Web of Sciences, and Scopus) from inception to January 2020 for observational studies assessing GI/GL in relation to MetS. Risk estimates were pooled using random-effect models for the highest versus lowest intake categories, and assessed for heterogeneity using subgroup analysis. The dose-response nature of the relationship was also investigated. Sensitivity analysis and Egger test were used to check the robustness of findings and the possibility of publication bias, respectively.

RESULTS

Data from 12 publications (one cohort study and eleven cross-sectional studies) with a total sample size of 36,295 subjects are included. The pooled effect sizes from the nine studies indicated high versus low dietary GI was associated with increased risk of MetS (OR = 1.05, 95% CI: 1.01 to 1.09) (I²  = 58.1, P = .004). This finding was supported by all subgroup analyses except where studies used 24-h recalls for dietary assessment. Additionally, a linear dose-response investigation revealed that each 5-point increment in GI was associated with 2% increase in the risk of MetS (OR = 1.02, 95% CI: 1.01 to 1.02); non-linear pattern was insignificant, however (p-nonlinearity = 0.63). Moreover, pooled effect sizes from ten studies suggested that no association was found between the GL and MetS with results remaining consistent in all subgroup analyses.

CONCLUSION

A diet with lower GI may protect against MetS. Nutrition policy and clinical practices should encourage a diet with low GI. Future studies should include both GI and GL and different criteria of MetS to provide a better comparison.

Dose-Dependent Associations of Dietary Glycemic Index, Glycemic Load, and Fiber With 3-Year Weight Loss Maintenance and Glycemic Status in a High-Risk Population: A Secondary Analysis of the Diabetes Prevention Study PREVIEW

OBJECTIVE

To examine longitudinal and dose-dependent associations of dietary glycemic index (GI), glycemic load (GL), and fiber with body weight and glycemic status during 3-year weight loss maintenance (WLM) in adults at high risk of type 2 diabetes.

RESEARCH DESIGN AND METHODS

In this secondary analysis we used pooled data from the PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) randomized controlled trial, which was designed to test the effects of four diet and physical activity interventions. A total of 1,279 participants with overweight or obesity (age 25-70 years and BMI ≥25 kg ⋅ m-2) and prediabetes at baseline were included. We used multiadjusted linear mixed models with repeated measurements to assess longitudinal and dose-dependent associations by merging the participants into one group and dividing them into GI, GL, and fiber tertiles, respectively.

RESULTS

In the available-case analysis, each 10-unit increment in GI was associated with a greater regain of weight (0.46 kg ⋅ year-1; 95% CI 0.23, 0.68; P < 0.001) and increase in HbA1c. Each 20-unit increment in GL was associated with a greater regain of weight (0.49 kg ⋅ year-1; 0.24, 0.75; P < 0.001) and increase in HbA1c. The associations of GI and GL with HbA1c were independent of weight change. Compared with those in the lowest tertiles, participants in the highest GI and GL tertiles had significantly greater weight regain and increases in HbA1c. Fiber was inversely associated with increases in waist circumference, but the associations with weight regain and glycemic status did not remain robust in different analyses.

CONCLUSIONS

Dietary GI and GL were positively associated with weight regain and deteriorating glycemic status. Stronger evidence on the role of fiber is needed.

A Practical Perspective for a Conservative Estimate of Blood Glucose Level during Restaurant Dining and Supermarket Shopping

Foods today are so diverse and enjoyable, making healthy choices difficult. In this perspective, an in vitro-in silico approach for obtaining a conservative estimate of the postprandial blood glucose concentration, which is a realistic estimate nevertheless, after intake of a certain portion of meals is proposed. The rationales and feasibilities of the approach are described and discussed to an extent. The key idea is to first measure the maximum amount of glucose released in an in vitro test under standardized conditions from a specified serving size of a meal or dish or a packaged product sold in a supermarket. The value can then be translated by a literate consumer to the highest estimate of blood glucose rise prior to purchasing or eating through an established in silico blood glucose prediction model in the medical field. The strategy proposed here would help health conscious (diabetics included) and other life quality conscious individuals to make quantitative decisions on consuming the portions of different foods of desire. This strategy may be more effective in reality compared to the conventional GI (Glycemic Index) and GL (Glycemic Load) concepts.

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.

The importance of glycemic index on post-prandial glycaemia in the context of mixed meals: A randomized controlled trial on pasta and rice

BACKGROUND AND AIMS

Post-prandial glycemic response (PPGR) depends on the intrinsic characteristic of the carbohydrate-rich foods as well as on the amount and type of other nutrients. This study aimed to explore whether the addition of condiments can affect the difference in PPGR between a low and a medium-high Glycemic Index (GI) food.

METHODS AND RESULTS

Spaghetti (S) and rice ® were consumed plain and after adding tomato sauce and extra virgin olive oil (TEVOO), or pesto sauce (P). The GI of R (63 ± 3) was statistically higher than that of S (44 ± 7) (p = 0.003). The Incremental Area Under the Curve (IAUC) for R was significantly greater than S (124.2 ± 12.1 and 82.1 ± 12.9 mmol∗min/L respectively) (p = 0.016) for blood glucose but not for insulin (1192.6 ± 183.6 and 905.2 ± 208.9 mU∗min/L, respectively) (p = 0.076). There were no significant differences after the addition of either TEVOO or P. The postprandial peaks of blood glucose and insulin for R (6.7 ± 0.3 mmol/L and 36.4 ± 4.9 mU/L, respectively) were significantly higher compared to S (6.0 ± 0.2 mmol/L and 26.7 ± 3.6 mU/L, respectively) (p = 0.033 and p = 0.025). The postprandial peak for insulin remained significantly higher with P (36.8 ± 3.7 and 28.6 ± 2.9 mU/L for R + P and S + P, p = 0.045) but not with EVOO (p = 0.963). Postprandial peaks for blood glucose were not significantly different with condiment.

CONCLUSIONS

The differences in PPGR were significant between spaghetti and rice consumed plain, they reduced or disappeared with fat adding, depending on the type of condiment used. REGISTRATION NUMBER: (www.clinicaltrial.gov):NCT03104712.

Glycemic indices of dates "Ramadan Symbolic Food" in patients with type 2 diabetes using continuous glucose monitoring system

AIM

The high consumption of dates during Ramadan raises the question about its glycemic index (GI) and its effect on the glycemic control in patients with type 2 diabetes (T2DM). We aimed to determine the GI of varieties of meals containing dates in healthy subjects compared to patients with T2DM and the effect of dates on the postprandial glucose excursions using continuous glucose monitoring system (CGMS).

METHOD AND RESULTS

Twenty patients with T2DM and twenty healthy subjects matched for age, sex and body weight participated. Testing was applied on separate days (on 3 occasions) with 50 g of glucose and 50 g equivalent of available carbohydrates from 9 date meals. The GI was calculated as ratios of the incremental areas under the response curves for dates in comparison to glucose. Minimed-530 g-diabetes-system-with-enlite was used for continuous glucose monitoring. There was no significant difference between the mean GI of dates between both study groups. However, there was a significant difference according to the time of peak blood glucose among varieties of meals containing dates in T2DM.

CONCLUSION

Studied varieties of dates have low GI. CGMS valued beyond GI calculation to study the postprandial glucose excursions among patients with T2DM.

Optimization of Extrusion and Ultrasound-Assisted Extraction of Phenolic Compounds from Jizi439 Black Wheat Bran

Jizi439, a newly developed black wheat breeding line, was reported to effectively regulate blood glucose, which may potentially be associated with its intrinsic high level of phenolic compounds (PCs). To maximize the PCs yield and thereby enhance their antioxidant activity, orthogonal experiments were designed in sequence for extrusion of Jizi439 black wheat bran (BWB) powder and followed by the extraction of PCs assisted with ultrasound technique. White wheat bran was used as a control. The optimum condition for extrusion was 110 °C, 25% feed water content, 140 rpm screw speed; meanwhile, 50 °C, 40 min, 35 kHz ultrasonic frequency, 300 W ultrasonic power for ultrasound-assisted extraction (UAE). Total phenolic content (TPC) as determined by Folin–Ciocalteu method was 2856.3 ± 57.7 μg gallic acid equivalents (GAE) per gram of dry weight (DW) of phenolic extract; meanwhile, antioxidant activity (AA) in terms of DPPH radical scavenging ratio was 85.5% ± 1.1% under optimized conditions, which were both significantly higher than the control. Phenolic acids except for gallic acid, as well as flavonoids, including luteolin and apigenin were increased by extrusion and ultrasound, as suggested by HPLC results. In conclusion, our study would provide a valuable reference for processing Jizi439 BWB before making or commercially utilize it into health-related food products.

Glycemic Index (GI) Values for Major Sources of Dietary Carbohydrates in Iran

BACKGROUND

The glycemic index (GI) values of staple foods are not available in a standardized method in Iran.

OBJECTIVES

The aim of this study was to measure the GI values of the major carbohydrate sources in a typical Iranian diet.

METHODS

Using the international standard method, the GI values were determined for four wheat flatbreads, barley and rye bread, white and brown rice, as well as white and brown rice mixed with lentils. Twelve healthy adults were given 50 g anhydrous glucose three times (as the reference carbohydrate) and the test foods once each throughout the study. Using finger-prick blood samples, capillary blood glucose was measured using a reliable glucometer. The GI was calculated using the trapezoidal method.

RESULTS

The GI values of the following types of bread were: Barley 66, Lavash 72, Taftoon 79, Sangak 82, rye 84, and Barbari 99. The GI values for brown and white rice were 65 and 71, respectively. The mixture of brown rice with lentils had a GI value of 55, and the mixture of white rice with lentils had a GI of 79.

CONCLUSIONS

The most common types of bread and white rice consumed in Iran have high GI values. There is potential to reduce the overall GI values in the Iranian diet by encouraging the consumption of barley bread and brown rice.

Destigmatizing Carbohydrate with Food Labeling: The Use of Non-Mandatory Labelling to Highlight Quality Carbohydrate Foods

Dietary carbohydrates are components of healthy foods, but many carbohydrate foods have recently been stigmatized as primary causes of diet-related risk factors for chronic disease. There is an opportunity to enhance efforts within the food landscape to encourage the consumption of higher quality carbohydrate foods. The use of labelling is one strategy that permits consumers to identify healthy carbohydrate foods at the point-of-purchase. This review discusses the regulatory frameworks and examples of associated non-mandatory food labelling claims that are currently employed to highlight healthy carbohydrate foods to consumers. The existing labelling frameworks discussed here align with established measures of carbohydrate quality, such as 1. dietary fibre nutrient content claims and associated dietary fibre-based health claims; 2. the presence of whole carbohydrate foods and ingredients that are intact or reconstituted, such as whole grains; and 3. low glycemic index and glycemic response claims. Standards from Codex Alimentarius, and regulations from Australia and New Zealand, Canada, Europe, and the United States will be used to illustrate the means by which food labelling can be used by consumers to identify quality carbohydrate foods.

The Role of Glycemic Index and Glycemic Load in the Development of Real-Time Postprandial Glycemic Response Prediction Models for Patients With Gestational Diabetes

The incorporation of glycemic index (GI) and glycemic load (GL) is a promising way to improve the accuracy of postprandial glycemic response (PPGR) prediction for personalized treatment of gestational diabetes (GDM). Our aim was to assess the prediction accuracy for PPGR prediction models with and without GI data in women with GDM and healthy pregnant women. The GI values were sourced from University of Sydney’s database and assigned to a food database used in the mobile app DiaCompanion. Weekly continuous glucose monitoring (CGM) data for 124 pregnant women (90 GDM and 34 control) were analyzed together with records of 1489 food intakes. Pearson correlation (R) was used to quantify the accuracy of predicted PPGRs from the model relative to those obtained from CGM. The final model for incremental area under glucose curve (iAUC120) prediction chosen by stepwise multiple linear regression had an R of 0.705 when GI/GL was included among input variables and an R of 0.700 when GI/GL was not included. In linear regression with coefficients acquired using regularization methods, which was tested on the data of new patients, R was 0.584 for both models (with and without inclusion of GI/GL). In conclusion, the incorporation of GI and GL only slightly improved the accuracy of PPGR prediction models when used in remote monitoring.

Reducing the glycemic impact of carbohydrates on foods and meals: Strategies for the food industry and consumers with special focus on Asia

Type 2 diabetes is increasingly prevalent in Asia, which can be attributed to a carbohydrate-rich diet, consisting of foods in the form of grains, for example, rice, or a food product made from flours or isolated starch, for example, noodles. Carbohydrates become a health issue when they are digested and absorbed rapidly (high glycemic index), and more so when they are consumed in large quantities (high glycemic load). The principal strategies of glycemic control should thus aim to reduce the amount of carbohydrate available for digestion, reduce the rate of digestion of the food, reduce the rate of glucose absorption, and increase the rate of glucose removal from blood. From a food perspective, the composition and structure of the food can be modified to reduce the amount of carbohydrates or alter starch digestibility and glucose absorption rates via using different food ingredients and processing methods. From a human perspective, eating behavior and food choices surrounding a meal can also affect glycemic response. This review therefore identifies actionable strategies and opportunities across foods and meals that can be considered by food manufacturers or consumers. They are (a) using alternative ingredients, (b) adding functional ingredients, and (c) changing processing methods and parameters for foods, and optimizing (a) eating behavior, (b) preloading or co-ingestion of other macronutrients, and (c) meal sequence and history. The effectiveness of a strategy would depend on consumer acceptance, compatibility of the strategy with an existing food product, and whether it is economically or technologically feasible. A combination of two or more strategies is recommended for greater effectiveness and flexibility.

Glycemic Index and Insulinemic Index of Foods: An Interlaboratory Study Using the ISO 2010 Method

An official method for determining food glycemic index (GI) was published by the Organization for International Standardization (ISO) in 2010, but its performance has not been assessed. Therefore, we aimed to determine the intra- and inter-laboratory variation of food GI values measured using the 2010 ISO method. Three laboratories (Australia, Canada and France) determined the GI and insulinemic-index (II) of six foods in groups of 13–15 participants using the 2010 ISO method and intra- and inter-laboratory Standard Deviations (SDs) were calculated. Overall mean food GIs varied from 47 to 86 (p < 0.0001) with no significant difference among labs (p = 0.57) and no food × laboratory interaction (p = 0.20). Within-laboratory SD was similar among foods (range, 17.8–22.5; p = 0.49) but varied among laboratories (range 17.5–23.1; p = 0.047). Between-laboratory SD of mean food GI values ranged from 1.6 to 6.7 (mean, 5.1). Mean glucose and insulin responses varied among foods (p < 0.001) with insulin (p = 0.0037), but not glucose (p = 0.054), varying significantly among labs. Mean II varied among foods (p < 0.001) but not among labs (p = 0.94). In conclusion, we found that using the 2010 ISO method, the mean between-laboratory SD of GI was 5.1. This suggests that the ISO method is sufficiently precise to distinguish a mean GI = 55 from a mean GI ≥ 70 with 97–99% probability.

Critical and emerging topics in dietary carbohydrates and health

Multiple factors may affect the metabolic fate of carbohydrates. Today, well-standardised and accepted methods may allow for the definitions of the changes in the glucose and insulin curves following the ingestion of either carbohydrate-based and other foods. More debate is still raised on the clinical meaning of these classifications when used at a population level, while emphasis is raised on the approach to carbohydrate metabolism on an individual basis. Within these ranges of applications, other compounds, such as plant polyphenols, may favourably add synergic effects through the modulation of carbohydrate digestion and glucose metabolic steps, resulting in lowering postprandial glucose and insulin levels. Finally, a growing knowledge suggests that the balance of dietary fructose and individual physical activity represent the key point to address the compound towards either positive, energy sparing effects, or a degenerative metabolic burden. The carbohydrate quality within a whole dietary and lifestyle pattern may therefore challenge the individual balance towards health or disease.

At a high dose even partially degraded beta-glucan with decreased solubility significantly reduced the glycaemic response to bread

Cereal beta-glucan can reduce post-prandial glycaemic responses, which makes it an interesting ingredient to improve the health impact of bread, a staple food with a high glycaemic index (GI). Here we compare the ability of different wheat-based breads prepared with oat bran concentrate and barley flour and a Norwegian type of soft wrap (lompe) for their ability to reduce glycaemic responses in healthy adults. Both breads with the highest beta-glucan content (3.8 g per serving) significantly reduced peak blood glucose rise (PBGR), incremental area under the blood glucose curve (iAUC) and GI compared to wheat control regardless of beta-glucan Mw and solubility. At a medium dose of 1.7 g per serving breads with beta-glucan of high MW and solubility significantly lowered iAUC, but not GI or PBGR compared to white bread. In contrast to previous studies, no significant correlation between viscosity after in vitro digestion and any of the glycaemia variables was found. However, the amount of soluble beta-glucan per serving was inversely correlated with GI. Lompe had a similar medium GI (63) than the high dose beta-glucan breads (56 and 64). However, while "lompe" had significantly lower amounts of rapidly digestible starch, no differences in in vitro starch digestion were found between the different breads. Instead, increased local viscosity at the intestinal border (e.g. soluble beta-glucan interacting with the mucus layer), dilution of nutrients (higher water content and serving size) and/or reduced gastric emptying are proposed as potential explanations for the lower glycaemic responses to high dose beta-glucan breads.

Comparative Effect of Low-Glycemic Index versus High-Glycemic Index Breakfasts on Cognitive Function: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis aims to compare the effect of High-Glycemic Index (GI) versus Low-GI breakfasts on cognitive functions, including memory and attention, of children and adolescents. We systematically searched the MEDLINE (via PubMed), EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science databases, from their inception until June 2019. Articles comparing the effect of Low-GI versus High-GI breakfasts on the cognitive function (i.e., immediate memory, delayed memory, and attention) of children and adolescents were included. The DerSimonian and Laird method was used to compute the pooled effect sizes (ESs) and their respective 95% confidence intervals (CIs). The pooled ESs were 0.13 (95% CI: −0.11, 0.37) for immediate memory and 0.07 (95% CI: −0.15, 0.28) for delayed memory. For attention, the pooled ES was −0.01 (95% CI: −0.27, 0.26). In summary, GI breakfasts do not affect cognitive domains in children and adolescents.

Glycemic Index of Slowly Digestible Carbohydrate Alone and in Powdered Drink-Mix

Consumer interest in food and beverages with carbohydrates offering steady glucose release and lower glycemic index (GI) continues to rise. Glycemic index is one of the metrics for carbohydrate quality. Slowly digestible carbohydrates (SDC) offer an ingredient solution to improve carbohydrate quality and meet consumer needs. SUSTRA^TM 2434 slowly digestible carbohydrate is a blend of tapioca flour and corn starch. The study objective was to determine the glycemic index of the SDC ingredient alone and in a powdered drink-mix. In a randomized, single-blind study, heathy adults (n = 14) consumed four test drinks, delivering 50 g available carbohydrates on separate days to measure GI. Participants either consumed dextrose in water (placebo), SDC ingredient in water, SDC drink-mix powder reconstituted in skim milk, or control drink-mix reconstituted in skim milk (without SDC). Post-prandial glucose response was measured over 4 h. SDC exhibited lower GI (0–2 h) and higher steady glucose release (beyond 2 h). SDC alone (GI = 27) and SDC in drink-mix (GI = 30.3) showed significantly lower GI (−27%) compared to dextrose (100) and the control drink-mix (41.5). SUSTRA^TM 2434 SDC is a low glycemic ingredient, suitable for product innovations with potential for low glycemic and steady glucose release claims.

Positioning the Value of Dietary Carbohydrate, Carbohydrate Quality, Glycemic Index, and GI Labelling to the Canadian Consumer for Improving Dietary Patterns

The objectives of this qualitative study was to: (1) understand Canadian consumers’ knowledge and perception of dietary carbohydrates, carbohydrate quality, and the glycemic index (GI); and (2) determine Canadian’s receptiveness to GI labelling to assist with identifying and consuming foods of higher carbohydrate quality. Focus groups were recruited in Vancouver, Toronto, and Montreal and grouped according to body mass index (BMI) (NBW, normal body weight; PO, previously obese; and OW/OB, overweight/obese) and diagnosis with prediabetes and diabetes (PO (Vancouver) and OW/OB (Montreal and Toronto). Subjects in all groups linked excess consumption of carbohydrate with weight gain. PO and OW/OB groups were conflicted between perceived negative consequences and feelings of pleasure associated with carbohydrate consumption. Subjects were largely unfamiliar with the term ‘carbohydrate quality’, but were often associated with classifying carbohydrates as ‘good’ or ‘bad’. The concept of the GI resonated well across groups after exposure to corresponding educational materials. However, NBW groups largely felt that the GI was irrelevant to their dietary choices as they did not have a history of diabetes. PO and OW/OB groups associated the GI with diabetes management. The concept of a GI labelling program to help facilitate healthier carbohydrate choices was well received across all groups, especially when the low GI was interpreted as giving permission to consume foods they enjoyed eating. Results suggest that the GI could be used as a consumer-facing labelling program in Canada and assist with de-stigmatizing carbohydrate foods by helping to facilitate the consumption of carbohydrate foods that align with healthy dietary patterns.

Effect of nutrient composition in a mixed meal on the postprandial glycemic response in healthy people: a preliminary study

BACKGROUND/OBJECTIVES

The glycemic index (GI) is a measure of the postprandial glucose response (PPGR) to food items, and glycemic load (GL) is a measure of the PPGR to the diet. For those who need to maintain a healthy diet, it is beneficial to regulate appropriate levels of blood glucose. In reality, what influences the meal GI or GL depends on the macronutrient composition and the physical chemistry reactions in vivo. Thus, we investigated whether different macronutrients in a meal significantly affect the PPGR and the validity of calculated GI and GL values for mixed meals.

SUBJECTS/METHODS

12 healthy subjects (6 male, 6 female) were recruited at a campus setting, and subjects consumed a total of 6 test meals one by one, each morning between 8:00 and 8:30 am after 12 h of fasting. PPGR was measured after each consumed meal and serial finger pricks were performed at indicated times. Test meals included 1) 68 g oral glucose, 2) 210 g rice, 3) rice plus 170 g egg white (RE), 4) rice plus 200 g bean sprouts (RS), 5) rice plus 10 g oil (RO), and 6) rice plus, egg white, bean sprouts, and oil (RESO). The incremental area under the curve (iAUC) was calculated to assess the PPGR. Mixed meal GI and GL values were calculated based on the nutrients the subjects consumed in each of the test meals.

RESULTS

The iAUC for all meals containing two macronutrients (RS, RO, or RE) were not significantly different from the rice iAUC, whereas, the RESO iAUC (2,237.5 ± 264.9) was significantly lower (P < 0.05). The RESO meal's calculated GI and GL values were different from the actual GI and GL values measured from the study subjects (P < 0.05).

CONCLUSIONS

The mixed meal containing three macronutrients (RESO) decreased the PPGR in healthy individuals, leading to significantly lower actual GI and GL values than those derived by nutrient-based calculations. Thus, consuming various macronutrient containing meals is beneficial in regulating PPGR.

Nutrition therapy within and beyond gestational diabetes

With the global rising prevalence of gestational diabetes (GDM), an adaptable, economical approach to nutrition therapy that effectively controls maternal glycemia while promoting normal fetal growth will have far-reaching implications. The conventional focus has been to rigidly limit all types of carbohydrate. While controlling glucose, this approach fosters maternal anxiety and is a primary barrier to adherence. Many mothers substitute fat for carbohydrate, which may unintentionally enhance lipolysis, promote elevated free fatty acids (FFA), and worsen maternal insulin resistance (IR). Nutrition that worsens IR may facilitate nutrient shunting across the placenta, promoting excess fetal fat accretion. Evidence suggests that liberalizing higher quality, nutrient-dense carbohydrates results in controlled fasting/postprandial glucose, lower FFA, improved insulin action, vascular benefits, and may reduce excess infant adiposity. Thus, a less carbohydrate-restricted approach may improve maternal adherence when combined with higher quality carbohydrates, lower fat, appropriate caloric intake, and ethnically acceptable foods. Such a diet can be culturally sensitive, socioeconomically attentive, minimize further weight gain in GDM, with potential relevance for pregnancies complicated by overweight/obesity. Future research is needed to better understand the effect of macronutrient composition on the placenta and gut microbiome, the benefits/risks of nonnutritive sweeteners, and whether precision-nutrition is beneficial in pregnancy.

Predicting mixed-meal measured glycaemic index in healthy subjects

PURPOSE

To determine the influence of meal composition on the glycaemic impact of different carbohydrate staples, and the accuracy of "adjusted calculated meal GI" compared with "measured mixed-meal GI".

METHODS

In a non-blind randomized crossover trial fasted healthy subjects consumed four dinner-type mixed meals of realistic serving size comprising a carbohydrate staple of either mashed potato, pasta, rice or a glucose drink, combined with fixed portions of boiled carrots, poached salmon and herb sauce. Blood samples collected between 0 and 180 min were analysed for glucose and insulin concentrations. Adjusted calculated meal GI values were determined against a 50 g reference glucose drink, and compared to corresponding measured mixed-meal GIs, supplemented with data from four previous mixed-meal postprandial glycaemic response studies.

RESULTS

The common carbohydrate staples, and the glucose drink, ingested as part of the salmon mixed meal induced a significantly lower post-prandial relative glycaemic response (RGR) and concurrent higher relative insulin response than the same amount of staple eaten alone. Adjusted calculated mixed-meal GI closely predicted measured mixed-meal GI in healthy subjects for 15 out of 17 mixed meals examined, showing the need to account for effects of fat and protein when predicting measured mixed-meal GI. Further, we showed the validity of using customarily consumed food amounts in mixed-meal postprandial RGR study design.

CONCLUSIONS

Adjusted calculated mixed-meal GI appears a useful model to predict measured mixed-meal GI in healthy subjects and with further development and validation could aid nutrition research and rational design of healthy meals for personalized nutrition and particular consumer groups.

Effect of Processing on Postprandial Glycemic Response and Consumer Acceptability of Lentil-Containing Food Items

The consumption of pulses is associated with many health benefits. This study assessed post-prandial blood glucose response (PPBG) and the acceptability of food items containing green lentils. In human trials we: (i) defined processing methods (boiling, pureeing, freezing, roasting, spray-drying) that preserve the PPBG-lowering feature of lentils; (ii) used an appropriate processing method to prepare lentil food items, and compared the PPBG and relative glycemic responses (RGR) of lentil and control foods; and (iii) conducted consumer acceptability of the lentil foods. Eight food items were formulated from either whole lentil puree (test) or instant potato (control). In separate PPBG studies, participants consumed fixed amounts of available carbohydrates from test foods, control foods, or a white bread standard. Finger prick blood samples were obtained at 0, 15, 30, 45, 60, 90, and 120 min after the first bite, analyzed for glucose, and used to calculate incremental area under the blood glucose response curve and RGR; glycemic index (GI) was measured only for processed lentils. Mean GI (± standard error of the mean) of processed lentils ranged from 25 ± 3 (boiled) to 66 ± 6 (spray-dried); the GI of spray-dried lentils was significantly (p < 0.05) higher than boiled, pureed, or roasted lentil. Overall, lentil-based food items all elicited significantly lower RGR compared to potato-based items (40 ± 3 vs. 73 ± 3%; p < 0.001). Apricot chicken, chicken pot pie, and lemony parsley soup had the highest overall acceptability corresponding to “like slightly” to “like moderately”. Processing influenced the PPBG of lentils, but food items formulated from lentil puree significantly attenuated PPBG. Formulation was associated with significant differences in sensory attributes.

The nutritional property of endosperm starch and its contribution to the health benefits of whole grain foods

Purported health benefits of whole grain foods in lowering risk of obesity, type 2 diabetes, cardiovascular disease, and cancer are supported by epidemiological studies and scientific researches. Bioactive components including dietary fibers, phytochemicals, and various micronutrients present in the bran and germ are commonly considered as the basis for such benefits. Endosperm starch, as the major constituent of whole grains providing glucose to the body, has been less investigated regarding its nutritional property and contribution to the value of whole grain foods. Nutritional quality of starch is associated with its rate of digestion and glucose absorption. In whole grain foods, starch digestion and glucose delivery may vary depending on the form in which the food is delivered, some with starch being rapidly and others slowly digested. Furthermore, there are other inherent factors in whole grain products, such as phenolic compounds and dietary fibers, that may moderate glycemic profiles. A good understanding of the nutritional properties of whole grain starch is important to the development of food processing technologies to maximize their health benefits.

Glycemic index, glycemic load, and metabolic syndrome in Mexican adolescents: a cross-sectional study from the NHNS-2012

BACKGROUND

The role of dietary glycemic index (GI) and dietary glycemic load (GL) on metabolic syndrome (MetS) in youth populations remains unclear. The aim of the present study was to evaluate the association among dietary GI, dietary GL, and MetS and its components in Mexican adolescents.

METHODS

This study was conducted within the framework of the National Health and Nutrition Survey 2012, a cross-sectional, probabilistic, population-based survey with a multistage stratified cluster sampling design. We analyzed a sample of 1346 subjects aged 12-19 years, representing 13,164,077 adolescents. Dietary habits were assessed through a validated semiquantitative food-frequency questionnaire. We assigned GI values using the International Tables of GI values. We defined MetS according to the International Diabetes Federation criteria developed for adolescents. Multiple logistic regression models were used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) to evaluate the association between categories of dietary GI and GL and the prevalence of MetS and its components.

RESULTS

We observed no associations between dietary GI or GL and MetS prevalence. Female adolescents in the highest category of dietary GI had higher odds of abnormal blood pressure (OR = 3.66; 95% CI, 1.46-9.22; P for trend = 0.012). A high dietary GL was also associated with higher odds of abnormal blood pressure in female adolescents (OR = 5.67; 95% CI, 1.84-17.46; P for trend = 0.003).

CONCLUSIONS

We found higher odds of abnormal blood pressure for female adolescents with a high dietary GI and dietary GL.

Meal frequency patterns and glycemic properties of maternal diet in relation to preterm delivery: Results from a large prospective cohort study

Background

Dietary habits are linked to high maternal glucose levels, associated with preterm delivery. The aim of this study was to examine the associations between meal frequency and glycemic properties of maternal diet in relation to preterm delivery.

Methods

This prospective cohort study included 66,000 women from the Norwegian Mother and Child Cohort Study (MoBa). Meal frequency and food intake data were obtained from a validated food frequency questionnaire during mid-pregnancy. Principal component factor analysis was used with a data-driven approach, and three meal frequency patterns were identified: “snack meal”, “main meal”, and “evening meal”. Pattern scores were ranked in quartiles. Glycemic index and glycemic load were estimated from table values. Intakes of carbohydrates, added sugar, and fiber were reported in grams per day and divided into quartiles. Gestational age was obtained from the Medical Birth Registry of Norway. Preterm delivery was defined as birth at <37 gestational weeks. A Cox regression model was used to assess associations with preterm delivery.

Results

After adjustments, the “main meal” pattern was associated with a reduced risk of preterm delivery, with hazard ratios (HRs) of 0.89 (95% confidence interval (CI): 0.80, 0.98) and 0.90 (95% CI: 0.81, 0.99) for the third and fourth quartiles, respectively, and p for trend of 0.028. This was mainly attributed to the group of women with BMI ≥25 kg/m², with HRs of 0.87 (95% CI: 0.79, 0.96) and 0.89 (95% CI: 0.80, 0.98) for the third and fourth quartiles, respectively, and p for trend of 0.010. There was no association between glycemic index, glycemic load, carbohydrates, added sugar, fiber, or the remaining meal frequency patterns and preterm delivery.

Conclusion

Regular consumption of main meals (breakfast, lunch, dinner) was associated with a lower risk of preterm delivery. Diet should be further studied as potential contributing factors for preterm delivery.

Changes in glucose levels and fecal excretion of lipids due to consumption of yacon flour

Purpose

As studies investigating the effects of fructan sources, such as yacon, on glucose and lipid metabolism showed different results, additional research is required to establish a clear relationship between them. Thus, this paper aims to evaluate possible effects of the consumption of the yacon pulp flour (YPF) on biological and metabolic parameters such as food consumption, weight gain, serum glucose levels and fecal lipid excretion of rats, as well as determine the role of glycemic index (GI) of the diets added of this ingredient on those parameters.

Design/methodology/approach

For this purpose, 24 male albino Wistar rats were divided into four groups, which received the following treatments for 17 days: Group 1 (G1) (Control) – American Institute of Nutrition (AIN)-M; Group 2 (G2) – AIN-M added 5 per cent YPF; Group 3 (G3) – AIN-M added 10 per cent YPF and Group 4 (G4) – AIN-M added 15 per cent YPF. Analysis of fasting and postprandial glycemia was conducted for elaboration of the glycemic curve and calculation of the GI of the diets. Lipids loss was measured by quantification of crude fat in feces after consumption of the diet.

Findings

YPF, regarding the concentration in the diets, did not elevate the fasting glucose among the groups. The postprandial glucose of the animals declined in different postprandial glucose peaks of the groups ingesting YPF in relation to the control one, especially in group treated with 15 per cent YPF, between 30 and 60 min (p <0,05), confirming the influence of the dietary fiber on the absorption of the glucose. The ingestion of YPF increased dragging of lipids to the animal feces, proportional to the amounts of YPF added to the diets. According to the regression analysis, followed by regression testing to 5 per cent, there was a significant difference between the experimental groups, being that the elevation of the percentage of YPF added to the diet caused a proportional increase in the lipid levels in the animal feces.

Originality/value

YPF could be an alimentary source of interest, mainly when the focus is on disease risk prevention such as diabetes, obesity and dyslipidemias.

Durum wheat particle size affects starch and protein digestion in vitro

PURPOSE

The term bioaccessibility refers to the proportion of a nutrient released from a complex food matrix during digestion and, therefore, becoming potentially available for absorption in the gastrointestinal tract. In the present study, we assessed the starch and protein bioaccessibility from a range of wheat endosperm products differing in particle size.

METHODS

Five porridge meals (size A, flour, mean particle size 0.11 mm, size B, small, mean particle size 0.38 mm, size C, semolina, mean particle size 1.01 mm, size D, medium, mean particle size 1.44 mm, size E, large, mean particle size 1.95 mm) with theoretically different postprandial glycaemic responses were subjected to oral processing in vitro, followed by simulated gastric and duodenal digestion.

RESULTS

A significant increase (P < 0.001) in starch degradation was observed in size A (52%) compared with size E (25%). Both sizes C and D gave less, although not significantly, digestible starch (32 and 28%, respectively). The glucose release significantly decreased as the particle size of the meal increased (92.16% detected for size A vs 47.39% for size E). In agreement with starch degradation and glucose release, size A gave the most digestible protein.

CONCLUSIONS

This data provide further evidence that, by decreasing the size of wheat endosperm, starch release and glycaemic response are enhanced. We also showed that protein bioaccessibility followed a similar trend as for starch digestion. Finally, these results support the hypothesis that different degrees of starch encapsulation elicit different blood glucose responses.

Chemical composition of unripe banana peels and pulps flours and its effects on blood glucose of rats

Purpose

Flours obtained from pulps and peels of unripe banana were evaluated regarding their chemical composition and glycemic responses in rats. Moreover, this study aims to propose a new assay to measure glycemic responses using animals.

Design/methodology/approach

Proximal composition, total dietary fiber and its insoluble and soluble fractions, mineral content and tannins were evaluated. Glycemic responses were measured using albino Wistar rats (seven animals/group).

Findings

Flours from pulp and peel of unripe banana presented high content of carbohydrates and minerals. Moreover, flour from peel was rich in insoluble fiber, whereas flour from pulp had adequate proportion of insoluble and soluble fractions. Consumption of banana flours from peel and pulp did not affect fasting blood glucose of normoglycemic rats. Flour from pulp, when consumed in concentrations of 10 and 15 per cent of the diet, significantly stimulated lower glycemic responses in the animals.

Originality/value

Results presented in this study disclose unripe banana flour as an interesting food source, which may be indicated for preventing some types of diseases, such as diabetes, obesity and dyslipidemia. Moreover, the glycemic index assay using animals promoted accurate answers, as the diets were standardized, unlike studies with humans, which do not control variations related to omission and distortion of information regarding food intake.

Contributors to dietary glycaemic index and glycaemic load in the Netherlands: the role of beer

Diets high in glycaemic index (GI) and glycaemic load (GL) have been associated with a higher diabetes risk. Beer explained a large proportion of variation in GI in a Finnish and an American study. However, few beers have been tested according to International Organization for Standardization (ISO) methodology. We tested the GI of beer and estimated its contribution to dietary GI and GL in the Netherlands. GI testing of pilsner beer (Pilsner Urquell) was conducted at The University of Sydney according to ISO international standards with glucose as the reference food. Subsequently, GI and GL values were assigned to 2556 food items in the 2011 Dutch food composition table using a six-step methodology and consulting four databases. This table was linked to dietary data from 2106 adults in the Dutch National Food Consumption Survey 2007-2010. Stepwise linear regression identified contribution to inter-individual variation in dietary GI and GL. The GI of pilsner beer was 89 (SD 5). Beer consumption contributed to 9·6 and 5·3% inter-individual variation in GI and GL, respectively. Other foods that contributed to the inter-individual variation in GI and GL included potatoes, bread, soft drinks, sugar, candy, wine, coffee and tea. The results were more pronounced in men than in women. In conclusion, beer is a high-GI food. Despite its relatively low carbohydrate content (approximately 4-5 g/100 ml), it still made a contribution to dietary GL, especially in men. Next to potatoes, bread, sugar and sugar-sweetened beverages, beer captured a considerable proportion of between-person variability in GI and GL in the Dutch diet.

Dietary carbohydrate quantity and quality in relation to obesity: A pooled analysis of three Finnish population-based studies

Background: The relationship between carbohydrate intake, dietary glycaemic index (GI) and load (GL), and obesity remains unsolved. Sugar intake and obesity represent a timely topic, but studies on sugar subcategories are scarce. We aimed to study whether total carbohydrate, sucrose, lactose, fibre, dietary GI, and GL are associated with obesity in 25–79-year-old Finns. Methods: Our pooled analysis included three cross-sectional population-based studies: the DILGOM Study ( n = 4842), the Helsinki Birth Cohort Study ( n =1979), and the Health 2000 Survey ( n = 5521). Diet was assessed by a validated food-frequency questionnaire, and anthropometric measurements were collected by standardised protocols. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression analysis. Results: In the model, which included sex, age, education, smoking, physical activity, and energy intake, the likelihood of being obese (body mass index ⩾ 30 kg/m2) appeared lower in the highest quartiles of total carbohydrate (OR 0.65; 95% CI 0.57–0.74; P for trend < 0.0001), sucrose (OR 0.53; 95% CI 0.47–0.61; P < 0.0001), and dietary GL (OR 0.64; 95% CI 0.56–0.73; P < 0.0001) compared to the lowest quartiles. In contrast, dietary GI did not associate with obesity. Fibre intake associated inversely with abdominal obesity (OR 0.80; 95% CI 0.71–0.90; P < 0.001). The inverse sucrose–obesity relationship appeared stronger in high fruit consumers compared to low fruit consumers ( P for interaction 0.02). Conclusions: Although most of the studied carbohydrate exposures were associated with a diminished likelihood of being obese, prospective studies are needed to assess temporal relations to support causal inference.