The use of glycaemic index tables to predict glycaemic index of composite breakfast meals

A collectanea of food insulinaemic index: 2023

BACKGROUND AND AIMS

To systematically update and publish the lnsulinaemic Index (II) value compilation of food/beverages.

METHODS

A literature search identified around 400 scholarly articles published between inception and December 2023. II values were pooled according to the selection criteria of at least 10 healthy, non-diabetic subjects with normal BMI. In addition, the II reported should have been derived from incremental area under the curve (iAUC) calculation of the insulin concentration over time. The reference food used from the pooled articles were either glucose or bread.

RESULTS

The II of 629 food/beverage items were found from 80 distinct articles. This is almost a five-fold increase in the number of entries from a previous compilation in 2011. Furthermore, these articles originated from 32 different countries, and were cleaved into 25 food categories. The II values ranged from 1 to 209. The highest overall recorded II was for a soy milk-based infant formula while the lowest was for both acacia fibre and gin. Upon clustering to single food, the infant formula retained the highest II while both acacia fibre and gin maintained the lowest recording. As for mixed meal, a potato dish served with a beverage recorded the highest II while a type of taco served with a sweetener, vegetable and fruit had the lowest II. Our minimum and maximum II data values replace the entries reported by previous compilations.

CONCLUSION

Acknowledging some limitations, these data would facilitate clinical usage of II for various applications in research, clinical nutrition, clinical medicine, diabetology and precision medicine. Future studies concerning II should investigate standardisation of reference food, including glucose and the test food portion. Although this collectanea adds up new food/beverages II values, priority should be given to populate this database.

Glycemic Load, Dietary Fiber, Added Sugar, and Spontaneous Abortion in Two Preconception Cohorts

BACKGROUND

Spontaneous abortion (SAB)-pregnancy loss before the 20th week of gestation-has adverse psychological and physical sequelae. Some medical conditions known to affect insulin sensitivity, including polycystic ovary syndrome and diabetes, can affect the risk of SAB. No prior studies have examined glycemic load and incidence of SAB in populations without conditions known to affect insulin sensitivity.

OBJECTIVES

We prospectively evaluated the association between preconception glycemic load and intake of carbohydrates, dietary fiber, and added sugar and risk of SAB.

METHODS

During 2013-2020, we recruited pregnancy planners from Denmark (SnartForaeldre.dk; SF) and the United States and Canada (Pregnancy Study Online; PRESTO). Participants completed a baseline questionnaire and a cohort-specific FFQ evaluated for validity. We estimated preconception glycemic load and intake of carbohydrates, dietary fiber, and added sugar from individual foods and mixed recipes. We included 2238 SF and 4246 PRESTO participants who reported a pregnancy during the course of the study. SAB data were derived from questionnaires and population registries. We used Cox proportional hazards regression to estimate HRs and 95% CIs.

RESULTS

In the study population, 15% of SF participants and 22% of PRESTO participants experienced SAB. Across both cohorts, there was no appreciable association between glycemic load, carbohydrate quality, dietary fiber, or added sugar intake and SAB. Compared with daily mean glycemic load <110, the HR for women with daily mean glycemic load ≥130 was 0.76 (95% CI: 0.52, 1.10) in SF and 1.01 (95% CI: 0.86, 1.19) in PRESTO.

CONCLUSIONS

Diets with high glycemic load, carbohydrates, and added sugars were not consistently associated with risk of SAB in parallel analyses of 2 preconception cohort studies of women in North America and Denmark.

International tables of glycemic index and glycemic load values 2021: a systematic review

BACKGROUND

Reliable tables of glycemic indexes (GIs) and glycemic loads (GLs) are critical to research examining the relationship between glycemic qualities of carbohydrate in foods, diets, and health. In the 12 years since the last edition of the tables, a large amount of new data has become available.

OBJECTIVES

To systematically review and tabulate published and unpublished sources of reliable GI values, including an assessment of the reliability of the data.

METHODS

This edition of the tables lists over 4000 items, a 61% increase in the number of entries compared to the 2008 edition. The data have been separated into 2 lists. The first represents more precise values derived using the methodology recommended by the International Standards Organization (∼2100 items). The second list contains values determined using less robust methods, including using limited numbers of healthy subjects or with a large SEM (∼1900 food items).

RESULTS

Dairy products, legumes, pasta, and fruits were usually low-GI foods (≤55 on the 100-point glucose scale) and had consistent values around the world. Cereals and cereal products, however, including whole-grain or whole-meal versions, showed wide variation in GI values, presumably arising from variations in manufacturing methods. Breads, breakfast cereals, rice, savory snack products, and regional foods were available in high-, medium-, and low-GI versions. Most varieties of potato were high-GI foods, but specific low-GI varieties have now been identified.

CONCLUSIONS

The availability of new data on the GIs of foods will facilitate wider research and application of the twin concepts of GI and GL. Although the 2021 edition of the tables improves the quality and quantity of GI data available for research and clinical practice, GI testing of regional foods remains a priority. This systematic review was registered in PROSPERO as #171204.

Effect of Wholegrain Flour Particle Size in Bread on Glycaemic and Insulinaemic Response among People with Risk Factors for Type 2 Diabetes: A Randomised Crossover Trial

Wholegrain flour produced by roller-milling is predominantly comprised of fine particles, while stoneground flour tends to have a comparatively smaller proportion of fine particles. Differences in flour particle size distribution can affect postprandial glycaemia in people with type 2 diabetes and postprandial insulinaemia in people with and without type 2 diabetes. No prior studies have investigated the effect of wholegrain flour particle size distribution on glycaemic or insulinaemic response among people with impaired glucose tolerance or risk factors for type 2 diabetes. In a randomised crossover study, we tested the 180-min acute glycaemic and insulinaemic responses to three wholegrain breads differing in flour particle size and milling method: (1) fine roller-milled flour, (2) fine stoneground flour, and (3) coarse stoneground flour. Participants (n = 23) were males and females with risk factors for type 2 diabetes (age 55-75 y, BMI >28 kg/m², completing less than 150 min moderate to vigorous intensity activity per week). Each test meal provided 50 g available carbohydrate, and test foods were matched for energy and macronutrients. There was no significant difference in blood glucose iAUC (incremental area under the curve) between the coarse stoneground flour bread and the fine stoneground flour bread (mean difference -20.8 (95% CI: -51.5, 10.0) mmol·min/L) and between the coarse stoneground flour bread and the fine roller-milled flour bread (mean difference -23.3 (95% CI: -57.6, 11.0) mmol·min/L). The mean difference in insulin iAUC for fine stoneground flour bread compared with the fine roller-milled flour bread was -6.9% (95% CI: -20.5%, 9.2%) and compared with the coarse stoneground flour bread was 9.9% (95% CI: -2.6%, 23.9%). There was no evidence of an effect of flour particle size on postprandial glycaemia and insulinaemia among older people with risk factors for type 2 diabetes, most of whom were normoglycaemic.

Perspective: Defining Carbohydrate Quality for Human Health and Environmental Sustainability

Plant foods are universally promoted for their links to improved human health, yet carbohydrate-containing foods are often maligned based on isolated, reductionist methods that fail to assess carbohydrate foods as a matrix of nutrients and food components. Currently accepted positive carbohydrate quality indices include plant food, whole-grain content, and dietary fiber, while negative health outcomes are linked to high intakes of added sugar and high glycemic index. More recently, negative health aspects have been linked to ultra-processed foods, which are often high in carbohydrates. Yet, carbohydrate staples such as grains and dairy products are both enriched and fortified, resulting in these carbohydrate foods containing important nutrients of concern such as dietary fiber, potassium, vitamin D, and calcium. This Perspective analyzes carbohydrate metrics used in dietary guidance and labeling and finds limitations in accepted indices included in standardized quality carbohydrate definitions and also proposes additional indices to benefit both human and environmental health. As nutrition recommendations shift away from a single-nutrient focus to a more holistic dietary pattern approach that is flexible and adaptable for each individual, it is necessary to determine the quality components that make up these patterns. This review concludes that current approaches that demonize staple carbohydrate foods do little to promote the recommended patterns of foods known to improve health status and reduce disease risk.

Determining the glycaemic responses of foods: conventional and emerging approaches

A low-glycaemic diet is crucial for those with diabetes and cardiovascular diseases. Information on the glycaemic index (GI) of different ingredients can help in designing novel food products for such target groups. This is because of the intricate dependency of material source, composition, food structure and processing conditions, among other factors, on the glycaemic responses. Different approaches have been used to predict the GI of foods, and certain discrepancies exist because of factors such as inter-individual variation among human subjects. Besides other aspects, it is important to understand the mechanism of food digestion because an approach to predict GI must essentially mimic the complex processes in the human gastrointestinal tract. The focus of this work is to review the advances in various approaches for predicting the glycaemic responses to foods. This has been carried out by detailing conventional approaches, their merits and limitations, and the need to focus on emerging approaches. Given that no single approach can be generalised to all applications, the review emphasises the scope of deriving insights for improvements in methodologies. Reviewing the conventional and emerging approaches for the determination of GI in foods, this detailed work is intended to serve as a state-of-the-art resource for nutritionists who work on developing low-GI foods.

Associations between Dietary Glycemic Index and Glycemic Load Values and Cardiometabolic Risk Factors in Adults: Findings from the China Health and Nutrition Survey

Studies investigating the associations between dietary glycemic index (GI) and glycemic load (GL) values and cardiometabolic risk factors (CMRF) among Chinese populations are strikingly limited. To assess the associations between dietary GI and GL values and CMRF, including dyslipidemia, hyperglycemia, and hyperuricemia in Chinese adults, we extracted data of 7886 apparently healthy adults from the 2009 wave of the China Health and Nutrition Survey. Dietary GI and GL values were calculated using data collected from three consecutive 24 h dietary recalls. Fasting lipid, glucose, and uric acid concentrations were measured and CMRF were defined on the basis of established criteria. There were no significant associations between dietary GI values and CMRF, and analyzing the data by age, sex, body mass index (BMI), and region did not alter these results. Dietary GL values were positively associated with prevalence of hyperuricemia in all participants (Q4 compared with Q1: odds ratio (OR) = 1.46; 95% CI: 1.14, 1.87; p-trend = 0.0030) and prevalence of hypercholesterolemia in participants ≥ 60 years old (Q5 compared with Q1: OR = 1.72; 95% CI: 1.11, 2.68; p-trend < 0.0010). Higher dietary GL but not GI values were associated with increased prevalence of hyperuricemia in apparently healthy Chinese adults and hypercholesterolemia in older Chinese adults. Further studies are required to confirm the public health implication of these findings.

The MEDGICarb-Study: Design of a multi-center randomized controlled trial to determine the differential health-promoting effects of low- and high-glycemic index Mediterranean-style eating patterns

Adults with central adiposity and other features of the metabolic syndrome have a markedly elevated risk of developing type 2 diabetes (T2D) and cardiovascular disease (CVD). A Mediterranean-style healthy eating pattern (MED-HEP) and consumption of foods with a lower glycemic index (GI) are potential dietary approaches to curb the T2D and CVD epidemic. However, experimental evidence of the effectiveness of MED-HEP and of the contribution of GI towards improving indices of glucose homeostasis, especially among non-diabetic people, are lacking. Therefore, we developed the MedGI-Carb trial, a multi-center (Italy, Sweden, and United States) intervention in adults with at least two components of the metabolic syndrome (elevated waist circumference + one other component) that aims to improve markers of glucose homeostasis through dietary modification. All participants were randomized to consume an isocaloric high- or low-GI MED-HEP for 12 weeks. We hypothesized that indexes of insulinemia (primary outcome: postprandial insulin and glucose after standardized breakfast and lunch; secondary outcomes: fasting plasma glucose and insulin, HbA_1c, 24-h continuous glucose monitoring) would be improved more with the low-GI versus the high-GI MED-HEP. Additionally, we hypothesized that consumption of a MED-HEP would improve other markers of cardiometabolic health and well-being (fasting blood pressure, fasting lipid profile, sleep quality, satiety, global metabolic alterations in the plasma metabolome, changes in the gut microbiota, subjective health and well-being), with no difference between groups. Collectively, the design of MEDGI-Carb allows several different research questions to be explored. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03410719.

The Impact of Dietary Glycemic Index and Glycemic Load on Postprandial Lipid Kinetics, Dyslipidemia and Cardiovascular Risk

Many recent studies have acknowledged postprandial hypetriglyceridemia as a distinct risk factor for cardiovascular disease. This dysmetabolic state is the result of the hepatic overproduction of very low-density lipoproteins (VLDLs) and intestinal secretion of chylomicrons (CMs), which leads to highly atherogenic particles and endothelial inflammation. Postprandial lipid metabolism does not only depend on consumed fat but also on the other classes of nutrients that a meal contains. Various mechanisms through which carbohydrates exacerbate lipidemia have been identified, especially for fructose, which stimulates de novo lipogenesis. Glycemic index and glycemic load, despite their intrinsic limitations, have been used as markers of the postprandial glucose and insulin response, and their association with metabolic health and cardiovascular events has been extensively studied with contradictory results. This review aims to discuss the importance and pathogenesis of postprandial hypertriglyceridemia and its association with cardiovascular disease. Then, we describe the mechanisms through which carbohydrates influence lipidemia and, through a brief presentation of the available clinical studies on glycemic index/glycemic load, we discuss the association of these indices with atherogenic dyslipidemia and address possible concerns and implications for everyday practice.

Glycemic load, dietary fiber, and added sugar and fecundability in 2 preconception cohorts

BACKGROUND

Glycemic load (GL) reflects the quantity and quality of carbohydrates in the diet; dietary fiber and added sugar are components of GL. Few epidemiologic studies have assessed the association between these dietary factors and fecundability.

OBJECTIVE

We prospectively evaluated the associations of GL, total carbohydrates, dietary fiber, and added sugar with fecundability.

METHODS

Snart Foraeldre (SF) and Pregnancy Study Online (PRESTO) are parallel web-based prospective preconception cohorts of couples attempting to conceive in Denmark and North America. At baseline, female participants completed a web-based questionnaire on demographic and lifestyle factors and a validated FFQ. We calculated GL, total carbohydrate intake, total dietary fiber, carbohydrate-to-fiber ratio, and added sugar based on reported frequencies for individual foods, standard recipes for mixed foods, and average serving sizes. The analysis included 2709 SF participants and 4268 PRESTO participants. We used proportional probabilities regression models to estimate fecundability ratios (FR) and 95% CIs.

RESULTS

Compared with an average daily GL of ≤100, FRs for an average daily GL of ≥141 were 0.89 (95% CI: 0.73, 1.08) in SF and 0.87 (95% CI: 0.77, 0.98) in PRESTO participants. Compared with consuming ≤16 g/d of dietary fiber, FRs for consuming ≥25 g/d were 0.99 (95% CI: 0.81, 1.22) in SF and 1.06 (95% CI: 0.94, 1.20) in PRESTO. Compared with a carbohydrate-to-fiber ratio of ≤8, FRs for a ratio of ≥13 were 0.86 (95% CI: 0.73, 1.01) in SF and 0.87 (95% CI: 0.78, 0.98) in PRESTO. Compared with ≤27 g/d of added sugar, FRs for ≥72 g/d were 0.87 (95% CI: 0.68, 1.10) in SF and 0.86 (95% CI: 0.75, 0.99) in PRESTO participants.

CONCLUSIONS

Among women attempting to conceive in Denmark and North America, diets high in GL, carbohydrate-to-fiber ratio, and added sugar were associated with modestly reduced fecundability.

Dietary Glycemic Index and Glycemic Load Are Not Associated with the Metabolic Syndrome in Lebanese Healthy Adults: A Cross-Sectional Study

High dietary glycemic index (GI) and glycemic load (GL) were suggested to increase the risk of metabolic syndrome (MetS). This study aims to estimate dietary GI and GL in a sample of healthy Lebanese adults and examine their association with MetS and its individual abnormalities. The study uses data from a community-based survey of 501 Lebanese urban adults. Dietary intake was assessed using a food frequency questionnaire. Biochemical, anthropometric, and blood pressure measurements were obtained. Subjects with previous diagnosis of chronic disease, metabolic abnormalities, or with incomplete data or implausible energy intakes were excluded, yielding a sample of 283. Participants were grouped into quartiles of GI and GL. Multivariate logistic regression analyses were performed. Average dietary GI and GL were estimated at 59.9 ± 8 and 209.7 ± 100.3. Participants belonging to the highest GI quartile were at increased risk of having MetS (odds ratio (OR) = 2.251, 95% CI:1.120–4.525) but this association lost significance with further adjustments. Those belonging to the second quartile of GI had significantly lower odds of having hyperglycemia (OR: 0.380, 95% CI:0.174–0.833). No associations were detected between GL and MetS. The study contributes to the body of evidence discussing the relationship between GI, GL, and MetS, in a nutrition transition context.

Knowledge and Perceptions of Carbohydrates among Nutrition-Major and Nutrition-Elective Undergraduate Students in Canada

Objective: The purpose of the study was to assess knowledge and perceptions related to carbohydrates, including sugars, among Canadian nutrition-major undergraduates compared to those enrolled in elective nutrition courses (i.e., "nutrition-elective students").Methods: Cross-sectional surveys were distributed during class time at eight Canadian universities, which included 32 questions on demographics, knowledge and perceptions of carbohydrates and sugars. Descriptive analyses were performed. Differences between groups were tested by Chi-squared statistics.Results: A total of 1207 students (60% nutrition-majors) participated in the survey (January 2016-February 2017). Internet-based sources accounted for one-third of the sources where students obtained nutrition information. About 61% of internet-bases sources were "online" or "website" with no qualifiers, and about a quarter was from social media. A higher percentage of nutrition-majors correctly answered knowledge questions of carbohydrates compared with nutrition-elective students (p < 0.01); no difference was observed for sugars-related knowledge questions. The perceptions of sugars were generally negative and did not differ between groups.Conclusions: Several knowledge gaps and common perceptions on topics related to carbohydrates and sugars were identified; nutrition-major students performed better than nutrition-elective students on carbohydrate knowledge questions, but not sugars. These results highlight the importance of identifying methods to help students bridge knowledge gaps and develop skills to critically evaluate nutrition information from various resources and challenge personal biases.

Evaluation of Postprandial Glycemic Response and Physical Properties of High-Amylose Rice "Koshinokaori"

This study evaluated the postprandial glycemic response and physical properties of the high-amylose rice, Koshinokaori (KK), cooked under different conditions. Twelve healthy subjects (Japanese, 6 males, 6 females) were given cooked, white KK rice or tomato chicken rice (TCR) using KK rice. The Japanese standard rice, Koshihikari (KH), was used as reference. All meals contained the same amount (50 g) of available carbohydrate. Blood glucose levels were measured at 0 (fasting), 15, 30, 45, 60, 90, and 120 min after each meal. The results from the cooked, white KK rice showed a significant difference in blood glucose variation at 60, 90, and 120 min and the incremental area under the curve (IAUC) of blood glucose concentration for KK cooked at optimal water to rice ratio was observed. Blood glucose variation and IAUC after intake of TCR-KK rice was lower than that after TCR-KH rice intake. Addition of 5% trehalose to KK rice resulted in a smaller decrease in adhesiveness and stickiness of cooked rice after 180 min at 20ºC. The addition of 5% trehalose to KK rice also produced favorable results in the sensory evaluation. KK rice produces favourable postprandial glycemic responses and physical properties under varied cooking condition and thus, may be beneficial in the prevention of lifestyle-related diseases such as type 2 diabetes.

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.

New Insight into Diabetes Management: From Glycemic Index to Dietary Insulin Index

BACKGROUND

Despite efforts to control hyperglycemia, diabetes management is still challenging. This may be due to focusing on reducing hyperglycemia and neglecting the importance of hyperinsulinemia; while insulin resistance and resultant hyperinsulinemia preceded diabetes onset and may contribute to disease pathogenesis.

OBJECTIVE

The present narrative review attempts to provide a new insight into the management of diabetes by exploring different aspects of glycemic index and dietary insulin index.

RESULTS

The current data available on this topic is limited and heterogeneous. Conventional diet therapy for diabetes management is based on reducing postprandial glycemia through carbohydrate counting, choosing foods with low-glycemic index and low-glycemic load. Since these indicators are only reliant on the carbohydrate content of foods and do not consider the effects of protein and fat on the stimulation of insulin secretion, they cannot provide a comprehensive approach to determine the insulin requirements.

CONCLUSION

Selecting foods based on carbohydrate counting, glycemic index or glycemic load are common guides to control glycemia in diabetic patients, but neglect the insulin response, thus leading to failure in diabetes management. Therefore, paying attention to insulinemic response along with glycemic response seems to be more effective in managing diabetes.

The association between glycemic index, glycemic load, and metabolic syndrome: a systematic review and dose-response meta-analysis of observational studies

PURPOSE

The association of glycemic index (GI) and glycemic load (GL) with metabolic syndrome (MetS) is controversial. Therefore, we conducted this first systematic review and dose-response meta-analysis of observational studies to quantify these associations.

METHODS

We searched PubMed, EMBASE, Web of Science, and the Cochrane Library for relevant studies up to 1 April 2019. Summary odds ratios (OR) and 95% confidence intervals (CI) were calculated by a random-effects model. This study was registered with PROSPERO (CRD42019131788).

RESULTS

We included eight high-quality (n = 5) or medium-quality (n = 3) cross-sectional studies in the final meta-analysis, comprising 6058 MetS events and 28,998 participants. The summary ORs of MetS for the highest versus lowest categories were 1.23 (95% CI 1.10-1.38, I² = 0, tau² = 0, n = 5) for dietary GI, 1.06 (95% CI 0.89-1.25, I² = 36.2%, tau² = 0.0151, n = 6) for dietary GL. The summary OR was 1.12 (95% CI 1.00-1.26, I² = 0, tau² = 0, n = 3) per 5 GI units, 0.96 (95% CI 0.83-1.10, I² = 33.4%, tau² = 0.0059, n = 2) per 20 GL units.

CONCLUSIONS

Dietary GI was positively associated with the prevalence of MetS. However, no significant association was found between dietary GL and the prevalence of MetS. Further studies with prospective design are needed to establish potential causal relationship between dietary GI and the MetS.

Association between dietary insulin index and load with obesity in adults

PURPOSE

Hyperinsulinemia is linked to the development of various chronic diseases, especially obesity given to the role of insulin responses in body fat accumulation; hence, the current study aimed to examine the association of insulinemic potential of the diet with general and abdominal obesity among a large population of Iranian adults.

METHODS

This cross-sectional study was carried out among 8691 adult participants aged 18-55 years. Dietary data were collected using a validated dish-based 106-item semi-quantitative food frequency questionnaire. Dietary insulin index (DII) was computed through considering food insulin index values published earlier. Dietary insulin load (DIL) was also calculated using a standard formula. Assessment of anthropometric measures was conducted through a self-administered questionnaire. General obesity was defined as body mass index ≥ 25 kg/m², and abdominal obesity as waist circumference ≥ 94 cm for men and ≥ 80 cm for women.

RESULTS

Mean age of study participants was 36.8 ± 8.1 years; 60.3% were women. Compared with the lowest quintile, women in the highest quintile of DIL were less likely to be abdominally obese (OR 0.73; 95% CI 0.57-0.92). Such significant association was not seen after controlling for potential confounders (OR 0.86; 95% CI 0.44-1.67). Neither in crude nor in adjusted models, we observed a significant association between DIL and general obesity among men and women. In terms of dietary insulin index, men in the top quintile of DII were more likely to be generally overweight or obese compared with those in the bottom quintile (OR 1.27; 95% CI 1.00-1.62). This association became non-significant after controlling for demographic characteristics (OR 1.14; 95% CI 0.84-1.56). Furthermore, in thefully adjusted model, women in the top quintile of DII were more likely to have general obesity compared with those in the bottom quintile (OR 1.40; 95% CI 1.07-1.84).

CONCLUSIONS

We found that adherence to a diet with a high DII was associated with greater odds of general obesity among women, but not in men. Although such information might help to draw conclusions on the practical relevance of the shown findings, further studies, specifically of prospective design, are warranted.

Predicting Glycemic Index and Glycemic Load from Macronutrients to Accelerate Development of Foods and Beverages with Lower Glucose Responses

Low glycemic index (GI) and/or low glycemic load (GL) are associated with decreased risks of type-2 diabetes and cardiovascular disease. It is therefore relevant to consider GI and GL in the early phases of the development of packaged foods and beverages. This paper proposes a model that predicts GI and GL from macronutrient composition, by quantifying both the impact of glycemic carbohydrates and the GI-lowering effects of nutrients such as proteins, fats and fibers. The precision of the model is illustrated using data on 42 breakfast cereals. The predictions of GI (r = 0.90, median residual = 2.0) and GL (r = 0.96, median residual = 0.40 g) compete well with the precision of the underlying in-vivo data (Standard Error SE = 3.5 for GI). This model can guide product development towards lowering GI and GL, before final confirmation by in vivo testing.

Comparison of Low Glycaemic Index and High Glycaemic Index Potatoes in Relation to Satiety: A Single-Blinded, Randomised Crossover Study in Humans

High glycaemic index (GI) foods have been proposed to reduce satiety and thus promote overweight and obesity. Generally, potatoes have a high GI, but they also provide many beneficial nutrients and they are a highly important food source globally. In this study, we investigated how a low GI potato affected subjective satiety as compared to a high GI potato. Twenty healthy men (aged 18–40 years; body mass index (BMI) 18–27 kg/m²) participated in this single-blinded, controlled, randomised crossover trial. On each of the two trial days, the subjects were given a 500-gram portion of either a low or high GI potato variety (Carisma^® low GI and Arizona high GI). Subjective appetite sensations were measured at baseline and at +15 min, +45 min, +75 min, +105 min, and +135 min after consumption of the test meal until an ad libitum meal was served at +150 min. No significant differences in the primary endpoint, satiety, were found between the two potato varieties (all p > 0.05). Furthermore, no significant differences were found in the secondary endpoints; hunger, fullness, and prospective food consumption, or ad libitum energy intake (all p > 0.05). In conclusion, the results of this study do not indicate that the GI of potatoes is important for satiety in normal-weight men.

Association between Dietary Glycemic Index and Knee Osteoarthritis: The Korean National Health and Nutrition Examination Survey 2010-2012

BACKGROUND

Obesity and metabolic abnormalities are important risk factors for knee osteoarthritis (KOA). Recent epidemiologic studies have found that a high glycemic index (GI) and glycemic load (GL) diet are associated with a higher risk for metabolic complications and cardiovascular mortality.

OBJECTIVE

We aimed to examine the association between dietary GI, dietary GL, and KOA among Korean adults.

DESIGN

This was a cross-sectional study that analyzed data obtained from the Korean National Health and Nutrition Examination Survey 2010-2012.

PARTICIPANTS/SETTING

A total of 9,203 participants (5,275 women) aged ≥50 years were included.

MAIN OUTCOME MEASURES

KOA was defined as the presence of radiographic features of Kellgren-Lawrence grade ≥2. Chronic knee pain was defined as the presence of knee pain for more than 30 days during the past 3 months. Dietary information was collected using a single 24-hour recall method.

STATISTICAL ANALYSES PERFORMED

The association between the quintiles of dietary GI and dietary GL and knee conditions was analyzed using a multinomial logistic regression analysis adjusting for age, physical activity, obesity, hypertension and diabetes, serum low-density lipoprotein, and total energy intake.

RESULTS

Among the women, the association between dietary GI and symptomatic KOA was: quintile 1: 1.00 (reference); quintile 2: 1.29 (95% CI 0.87 to 1.92); quintile 3: 1.59 (95% CI 1.11 to 2.28); quintile 4: 1.74 (95% CI 1.21 to 2.51); and quintile 5: 1.77 (95% CI 1.20 to 2.60) (P=0.001). Chronic knee pain without KOA was associated with dietary GI; however, this association was not linear across quintiles. There was no significant association between dietary GI and asymptomatic KOA. Among the men, no significant association was found between dietary GI and any knee conditions. There was no significant association between dietary GL and KOA in both men and women.

CONCLUSIONS

There was a significant positive association between dietary GI and symptomatic KOA in women.

Effect of prior meal macronutrient composition on postprandial glycemic responses and glycemic index and glycemic load value determinations

Background: The potential impact of prior meal composition on the postprandial glycemic response and glycemic index (GI) and glycemic load (GL) value determinations remains unclear.Objective: We determined the effect of meals that varied in macronutrient composition on the glycemic response and determination of GI and GL values of a subsequent standard test food.Design: Twenty healthy participants underwent 6 test sessions within 12 wk. The subjects received each of 3 isocaloric breakfast meals (i.e., high carbohydrate, high fat, or high protein) on separate days in a random order, which was followed by a standard set of challenges (i.e., white bread and a glucose drink) that were tested on separate days in a random order 4 h thereafter. Each challenge provided 50 g available carbohydrate. Arterialized venous blood was sampled throughout the 2-h postchallenge period. GI, GL, and insulin index (II) values were calculated with the use of the incremental area under the curve (AUCi) method, and serum lipids were determined with the use of standard assays.Results: The consumption of the high-protein breakfast before the white-bread challenge attenuated the rise in the postprandial serum glucose response (P < 0.0001) and resulted in lower glucose AUCi (P < 0.0001), GI (P = 0.0096), and GL (P = 0.0101) values than did the high-carbohydrate and high-fat breakfasts. The high-protein breakfast resulted in a lower insulin AUCi (P = 0.0146) for white bread than did the high-fat breakfast and a lower II value (P = 0.0285) than did the high-carbohydrate breakfast. The 3 breakfasts resulted in similar serum lipid responses to the white-bread challenge.Conclusions: These data indicate that the macronutrient composition of the prior meal influences the glycemic response and the determination of GI and GL values for white bread. Future studies are needed to determine whether the background food macronutrient composition influences mean dietary GI and GL values that are calculated for eating patterns, which may alter the interpretation of the associations between these values and chronic disease risk. This trial was registered at clinicaltrials.gov as NCT01023646.

Low glycaemic index diets for the prevention of cardiovascular disease

BACKGROUND

The glycaemic index (GI) is a physiological measure of the ability of a carbohydrate to affect blood glucose. Interest is growing in this area for the clinical management of people at risk of, or with, established cardiovascular disease. There is a need to review the current evidence from randomised controlled trials (RCTs) in this area. This is an update of the original review published in 2008.

OBJECTIVES

To assess the effect of the dietary GI on total mortality, cardiovascular events, and cardiovascular risk factors (blood lipids, blood pressure) in healthy people or people who have established cardiovascular disease or related risk factors, using all eligible randomised controlled trials.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase and CINAHL in July 2016. We also checked reference lists of relevant articles. No language restrictions were applied.

SELECTION CRITERIA

We selected RCTs that assessed the effects of low GI diets compared to diets with a similar composition but a higher GI on cardiovascular disease and related risk factors. Minimum trial duration was 12 weeks. Participants included were healthy adults or those at increased risk of cardiovascular disease, or previously diagnosed with cardiovascular disease. Studies in people with diabetes mellitus were excluded.

DATA COLLECTION AND ANALYSIS

Two reviewers independently screened and selected studies. Two review authors independently assessed risk of bias, evaluated the overall quality of the evidence using GRADE, and extracted data following the Cochrane Handbook for Systematic Reviews of Interventions. We contacted trial authors for additional information. Analyses were checked by a second reviewer. Continuous outcomes were synthesized using mean differences and adverse events were synthesized narratively.

MAIN RESULTS

Twenty-one RCTs were included, with a total of 2538 participants randomised to low GI intervention (1288) or high GI (1250). All 21 included studies reported the effect of low GI diets on risk factors for cardiovascular disease, including blood lipids and blood pressure.Twenty RCTs (18 of which were newly included in this version of the review) included primary prevention populations (healthy individuals or those at high risk of CVD, with mean age range from 19 to 69 years) and one RCT was in those diagnosed with pre-existing CVD (a secondary prevention population, with mean age 26.9 years). Most of the studies did not have an intervention duration of longer than six months. Difference in GI intake between comparison groups varied widely from 0.6 to 42.None of the included studies reported the effect of low GI dietary intake on cardiovascular mortality and cardiovascular events such as fatal and nonfatal myocardial infarction, unstable angina, coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, and stroke. The unclear risk of bias of most of the included studies makes overall interpretation of the data difficult. Only two of the included studies (38 participants) reported on adverse effects and did not observe any harms (low-quality evidence).

AUTHORS' CONCLUSIONS

There is currently no evidence available regarding the effect of low GI diets on cardiovascular disease events. Moreover, there is currently no convincing evidence that low GI diets have a clear beneficial effect on blood lipids or blood pressure parameters.

Glycaemic index and glycaemic load values of commonly consumed foods in the United Arab Emirates

Glycaemic index (GI) and glycaemic load (GL) values of some commonly consumed foods in the United Arab Emirates were determined with an aim of adding these values to the existing international table of GI and GL values. In all, eighteen test foods categorised into breads (n 5), entrée dishes (n 3), main dishes (n 5) and sweet dishes (n 5) were tested. For each test food, at least fifteen healthy participants consumed 25 or 50 g available carbohydrate portions of a reference food (glucose), which was tested three times, and a test food after an overnight fast, was tested once, on separate occasions. Capillary blood samples were obtained by finger-prick and blood glucose was measured using clinical chemistry analyser. A fasting blood sample was obtained at baseline and before consumption of test foods. Additional blood samples were obtained at 15, 30, 45, 60, 90 and 120 min after the consumption of each test food. The GI value of each test food was calculated as the percentage of the incremental area under the blood glucose curve (IAUC) for the test food of each participant divided by the average IAUC for the reference food of the same participant. The GI values of tested foods ranged from low (55 or less) to high (70 or more). The GI values of various breads and rice-containing dishes were comparable with previously published values. This study provides GI and GL values of previously untested traditional Emirati foods which could provide a useful guide on dietary recommendations for the Emirati population.

Estimating the reliability of glycemic index values and potential sources of methodological and biological variability

BACKGROUND

The utility of glycemic index (GI) values for chronic disease risk management remains controversial. Although absolute GI value determinations for individual foods have been shown to vary significantly in individuals with diabetes, there is a dearth of data on the reliability of GI value determinations and potential sources of variability among healthy adults.

OBJECTIVE

We examined the intra- and inter-individual variability in glycemic response to a single food challenge and methodologic and biological factors that potentially mediate this response.

DESIGN

The GI value for white bread was determined by using standardized methodology in 63 volunteers free from chronic disease and recruited to differ by sex, age (18-85 y), and body mass index [BMI (in kg/m²): 20-35]. Volunteers randomly underwent 3 sets of food challenges involving glucose (reference) and white bread (test food), both providing 50 g available carbohydrates. Serum glucose and insulin were monitored for 5 h postingestion, and GI values were calculated by using different area under the curve (AUC) methods. Biochemical variables were measured by using standard assays and body composition by dual-energy X-ray absorptiometry.

RESULTS

The mean ± SD GI value for white bread was 62 ± 15 when calculated by using the recommended method. Mean intra- and interindividual CVs were 20% and 25%, respectively. Increasing sample size, replication of reference and test foods, and length of blood sampling, as well as AUC calculation method, did not improve the CVs. Among the biological factors assessed, insulin index and glycated hemoglobin values explained 15% and 16% of the variability in mean GI value for white bread, respectively.

CONCLUSIONS

These data indicate that there is substantial variability in individual responses to GI value determinations, demonstrating that it is unlikely to be a good approach to guiding food choices. Additionally, even in healthy individuals, glycemic status significantly contributes to the variability in GI value estimates. This trial was registered at clinicaltrials.gov as NCT01023646.

Low glycemic index diet reduces body fat and attenuates inflammatory and metabolic responses in patients with type 2 diabetes

Objective

The aim of this study was to verify the effects of glycemic index (GI) on body composition, and on inflammatory and metabolic markers concentrations in patients with type 2 diabetes.

Subjects and methods

In this randomized controlled parallel trial, twenty subjects (aged 42.4 ± 5.1 years, BMI 29.2 ± 4.8 kg.m-2) were allocated to low GI (LGI) (n = 10) or high GI (HGI) (n = 10) groups. Body composition, inflammatory and metabolic markers were assessed at baseline and after 30 days of intervention. Food intake was monitored during the study using three-day food records completed on two non-consecutive weekdays and on a weekend day.

Results

Body fat reduced after the LGI intervention compared with baseline (P = 0.043) and with the HGI group (P = 0.036). Serum fructosamine concentration (P = 0.031) and TNF-α mRNA expression (P = 0.05) increased in the HGI group. Serum non-esterified fatty acids were greater in the HGI than in the LGI group (P = 0.032). IL-6 mRNA expression tended to decrease after the consumption of the LGI diet compared to baseline (P = 0.06).

Conclusion

The LGI diet reduced body fat and prevented the negative metabolic and inflammatory responses induced by the HGI diet.

Slow-release carbohydrates: growing evidence on metabolic responses and public health interest. Summary of the symposium held at the 12th European Nutrition Conference (FENS 2015)

To draw attention to the necessity of considering differences in the digestibility of carbohydrates, and more specifically of starch, a symposium was held at the 12th European Nutrition Conference (FENS), which took place in Berlin from October 20 to 23, 2015. The purpose of this session was to present the consolidated knowledge and recent advances regarding the relationship between slow-release carbohydrates, metabolic responses, and public health issues. Three main topics were presented: 1) the definition of, sources of, and recognised interest in the glycaemic response to slowly digestible starch (SDS); 2) clinical evidence regarding the physiological effects of slow-release carbohydrates from cereal foods; and 3) interest in reducing the postprandial glycaemic response to help prevent metabolic diseases. Foods with the highest SDS content induce the lowest glycaemic responses, as the starch is protected from gelatinisation during processing. In humans, high-SDS food consumption induces slower glucose release, lower postprandial insulinaemia, and stimulation of gut hormones. Moreover, postprandial hyperglycaemia is an independent risk factor for type two diabetes mellitus (T2DM) and cardiovascular disease (CVD). Therefore, given the plausible aetiologic mechanisms, we argue that postprandial glucose levels are relevant for health and disease and represent a meaningful target for intervention, for example, through dietary factors. This symposium was organised by Mondelez International R&D.

Glycemic index, glycemic load and glycemic response: An International Scientific Consensus Summit from the International Carbohydrate Quality Consortium (ICQC)

BACKGROUND AND AIMS

The positive and negative health effects of dietary carbohydrates are of interest to both researchers and consumers.

METHODS

International experts on carbohydrate research held a scientific summit in Stresa, Italy, in June 2013 to discuss controversies surrounding the utility of the glycemic index (GI), glycemic load (GL) and glycemic response (GR).

RESULTS

The outcome was a scientific consensus statement which recognized the importance of postprandial glycemia in overall health, and the GI as a valid and reproducible method of classifying carbohydrate foods for this purpose. There was consensus that diets low in GI and GL were relevant to the prevention and management of diabetes and coronary heart disease, and probably obesity. Moderate to weak associations were observed for selected cancers. The group affirmed that diets low in GI and GL should always be considered in the context of diets otherwise understood as healthy, complementing additional ways of characterizing carbohydrate foods, such as fiber and whole grain content. Diets of low GI and GL were considered particularly important in individuals with insulin resistance.

CONCLUSIONS

Given the high prevalence of diabetes and pre-diabetes worldwide and the consistency of the scientific evidence reviewed, the expert panel confirmed an urgent need to communicate information on GI and GL to the general public and health professionals, through channels such as national dietary guidelines, food composition tables and food labels.

Changes in intake of protein foods, carbohydrate amount and quality, and long-term weight change: results from 3 prospective cohorts

BACKGROUND

Dietary guidelines recommend interchanging protein foods (e.g., chicken for red meat), but they may be exchanged for carbohydrate-rich foods varying in quality [glycemic load (GL)]. Whether such exchanges occur and how they influence long-term weight gain are not established.

OBJECTIVE

Our objective was to determine how changes in intake of protein foods, GL, and their interrelationship influence long-term weight gain.

DESIGN

We investigated the association between 4-y changes in consumption of protein foods, GL, and their interaction with 4-y weight change over a 16- to 24-y follow-up, adjusted for other lifestyle changes (smoking, physical activity, television watching, sleep duration), body mass index, and all dietary factors simultaneously in 3 prospective US cohorts (Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-Up Study) comprising 120,784 men and women free of chronic disease or obesity at baseline.

RESULTS

Protein foods were not interchanged with each other (intercorrelations typically <|0.05|) but with carbohydrate (negative correlation as low as -0.39). Protein foods had different relations with long-term weight gain, with positive associations for meats, chicken with skin, and regular cheese (per increased serving/d, 0.13-1.17 kg; P = 0.02 to P < 0.001); no association for milk, legumes, peanuts, or eggs (P > 0.40 for each); and relative weight loss for yogurt, peanut butter, walnuts, other nuts, chicken without skin, low-fat cheese, and seafood (-0.14 to -0.71 kg; P = 0.01 to P < 0.001). Increases in GL were independently associated with a 0.42-kg greater weight gain per 50-unit increase (P < 0.001). Significant interactions (P-interaction < 0.05) between changes in protein foods and GL were identified; for example, increased cheese intake was associated with weight gain when GL increased, with weight stability when GL did not change, and with weight loss when exchanged for GL (i.e., decrease in GL).

CONCLUSION

Protein foods were commonly interchanged with carbohydrate, and changes in protein foods and GL interacted to influence long-term weight gain.

Postprandial glycaemic response: how is it influenced by characteristics of cereal products?

Cereal products exhibit a wide range of glycaemic indexes (GI), but the interaction of their different nutrients and starch digestibility on blood glucose response is not well known. The objective of this analysis was to evaluate how cereal product characteristics can contribute to GI and insulinaemic index and to the parameters describing glycaemic or insulinaemic responses (incremental AUC, maximum concentration and Δ_peak). Moreover, interactions between the different cereal products characteristics and glycaemic response parameters were assessed for the first time. Relationships between the cereal products characteristics and the glycaemic response were analysed by partial least square regressions, followed by modelling. A database including 190 cereal products tested by the usual GI methodology was used. The model on glycaemic responses showed that slowly digestible starch (SDS), rapidly digestible starch (RDS) and fat and fibres, and several interactions involving them, significantly explain GI by 53 % and Δ_peak of glycaemia by 60 %. Fat and fibres had important contributions to glycaemic response at low and medium SDS contents in cereal products, but this effect disappears at high SDS levels. We showed also for the first time that glycaemic response parameters are dependent on interactions between starch digestibility (interaction between SDS and RDS) and nutritional composition (interaction between fat and fibres) of the cereal products. We also demonstrated the non-linear effect of fat and fibres (significant effect of their quadratic terms). Hence, optimising both the formula and the manufacturing process of cereal products can improve glucose metabolism, which is recognised as strongly influential on human health.

Increased intake of carbohydrates from sources with a higher glycemic index and lower consumption of whole grains during puberty are prospectively associated with higher IL-6 concentrations in younger adulthood among healthy individuals

Chronic low-grade inflammation represents a likely intermediary in the relation between carbohydrate nutrition and both type 2 diabetes and cardiovascular disease. This study assessed the prospective association between carbohydrate quantity and quality [dietary glycemic index (GI), glycemic load (GL), and added sugar, fiber, and whole-grain intake] during puberty, a potentially critical period for later disease, and low-grade inflammation in younger adulthood. The analysis was based on 205 participants (113 girls and 92 boys) from the DONALD (Dortmund Nutritional and Anthropometric Longitudinally Designed) study with at least 2 3-d weighed dietary records during puberty (girls: 9-14 y, boys: 10-15 y) and blood samples in younger adulthood (18-36 y). Multivariable linear regression models were used to analyze the associations between carbohydrate nutrition and circulating concentrations of pro- and anti-inflammatory immune mediators [high-sensitivity C-reactive protein (hs-CRP), interleukin (IL) 6, IL-18, and adiponectin]. A higher intake of carbohydrates during puberty (P-trend = 0.005), particularly from higher-GI food sources (P-trend = 0.01), was prospectively related to higher concentrations of IL-6 in younger adulthood, independently of baseline BMI and early life, socioeconomic, and other nutritional factors. Furthermore, a higher dietary GL (P-trend = 0.002) and a lower intake of whole grains (P-trend = 0.01) were independently associated with higher IL-6 concentrations in adults. Dietary GI and added sugar and fiber intakes were not independently associated with IL-6 (P-trend ≥ 0.09). Carbohydrate nutrition during puberty was not independently related to hs-CRP, IL-18, and adiponectin concentrations (all P-trend > 0.1). During puberty, a higher intake of carbohydrates from higher-GI food sources and lower whole-grain consumption prospectively predict greater IL-6 concentrations in young adulthood. These data support the hypothesis that diet during puberty influences later inflammation and metabolic dysfunction.

24-hour glucose profiles on diets varying in protein content and glycemic index

Evidence is increasing that the postprandial state is an important factor contributing to the risk of chronic diseases. Not only mean glycemia, but also glycemic variability has been implicated in this effect. In this exploratory study, we measured 24-h glucose profiles in 25 overweight participants in a long-term diet intervention study (DIOGENES study on Diet, Obesity and Genes), which had been randomized to four different diet groups consuming diets varying in protein content and glycemic index. In addition, we compared 24-h glucose profiles in a more controlled fashion, where nine other subjects followed in random order the same four diets differing in carbohydrate content by 10 energy% and glycemic index by 20 units during three days. Meals were provided in the lab and had to be eaten at fixed times during the day. No differences in mean glucose concentration or glucose variability (SD) were found between diet groups in the DIOGENES study. In the more controlled lab study, mean 24-h glucose concentrations were also not different. Glucose variability (SD and CONGA1), however, was lower on the diet combining a lower carbohydrate content and GI compared to the diet combining a higher carbohydrate content and GI. These data suggest that diets with moderate differences in carbohydrate content and GI do not affect mean 24-h or daytime glucose concentrations, but may result in differences in the variability of the glucose level in healthy normal weight and overweight individuals.

Glycaemic responses of staple South Asian foods alone and combined with curried chicken as a mixed meal

BACKGROUND

The glycaemic responses of staples differ when eaten as mixed meals. We determined the glycaemic responses and glycaemic index (GI) values for common South Asian carbohydrate rich foods and the effect of adding curried chicken to them as mixed meals.

METHODS

The GI and glycaemic response to staples (basmati rice, pilau rice and chapatti) and mixed meals (pilau rice with chicken curry and chapatti with chicken curry) were measured in healthy volunteers. Paired comparisons in each subject were carried out for staples and their equivalent mixed meals (n = 9).

RESULTS

GI values for the mixed meals were significantly lower than the staples alone (41 and 60 for pilau rice with chicken curry and pilau rice alone, P = 0.001; 45 and 68 for chapatti with chicken curry and chapatti alone, P = 0.004). Both, pilau rice and chapatti with chicken curry had a significantly lower glycaemic response than their equivalent staples alone: incremental area under the blood glucose response curves (IAUC) 111.9 mmol min(-1 ) L(-1) for pilau rice with curry versus 162.4 mmol min(-1 ) L(-1) for pilau rice alone (P = 0.001) and IAUC 110.1 mmol min(-1 ) L(-1) for chapatti with chicken curry versus 183.6 mmol min(-1 ) L(-1) for chapatti alone (P = 0.002).

CONCLUSIONS

Adding fat and protein-containing curries as part of a mixed meal to carbohydrate rich staple foods reduced glycaemic responses, and also changed the GI category.

Glycemic index, glycemic load, carbohydrates, and type 2 diabetes: systematic review and dose-response meta-analysis of prospective studies

OBJECTIVE

Diets with high glycemic index (GI), with high glycemic load (GL), or high in all carbohydrates may predispose to higher blood glucose and insulin concentrations, glucose intolerance, and risk of type 2 diabetes. We aimed to conduct a systematic literature review and dose-response meta-analysis of evidence from prospective cohorts.

RESEARCH DESIGN AND METHODS

We searched the Cochrane Library, MEDLINE, MEDLINE in-process, Embase, CAB Abstracts, ISI Web of Science, and BIOSIS for prospective studies of GI, GL, and total carbohydrates in relation to risk of type 2 diabetes up to 17 July 2012. Data were extracted from 24 publications on 21 cohort studies. Studies using different exposure categories were combined on the same scale using linear and nonlinear dose-response trends. Summary relative risks (RRs) were estimated using random-effects meta-analysis.

RESULTS

The summary RR was 1.08 per 5 GI units (95% CI 1.02-1.15; P = 0.01), 1.03 per 20 GL units (95% CI 1.00-1.05; P = 0.02), and 0.97 per 50 g/day of carbohydrate (95% CI 0.90-1.06; P = 0.5). Dose-response trends were linear for GI and GL but more complex for total carbohydrate intake. Heterogeneity was high for all exposures (I(2) >50%), partly accounted for by different covariate adjustment and length of follow-up.

CONCLUSIONS

Included studies were observational and should be interpreted cautiously. However, our findings are consistent with protective effects of low dietary GI and GL, quantifying the range of intakes associated with lower risk. Future research could focus on the type of sugars and other carbohydrates associated with greatest risk.

Effects of different protein and glycemic index diets on metabolic profiles and substrate partitioning in lean healthy males

Dietary glycemic index (GI) and protein affects postprandial insulin responses and consequently 24 h glucose metabolism and therefore substrate partitioning. This study investigated the mechanistic effects of different protein and GI diets on 24 h profiles of metabolic markers and substrate partitioning. After 3 days of diet and physical activity standardization, 10 healthy male subjects (BMI: 22.5 ± 0.6 kg/m2) stayed in a respiration chamber 4 times for 36 h each time to measure substrate partitioning. All subjects randomly received four isoenergetic diets: a normal (15En%) dairy protein and low GI (<40 units) (NDP-LGI) diet; a high (25En%) dairy protein and low GI (HDP-LGI) diet; a normal vegetable protein and low GI (NVP-LGI) diet; or a normal dairy protein and high GI (>60 units) (NDP-HGI) diet. During the day, blood was sampled at fixed time points for the measurement of metabolic markers and satiety hormones. The HDP-LGI diet increased 24 h protein oxidation and sleeping metabolic rate (SMR) compared with the NDP-LGI diet (p < 0.002). No significant differences in 24 h carbohydrate and fat oxidation (day and night) were found between all intervention diets. Net incremental area under the curve (net iAUC) of 24 h plasma glucose decreased in the HDP-LGI diet compared with the NDP-LGI diet (p < 0.01), but no effect was observed on insulin levels. No difference in appetite profiles were observed between all intervention diets. The lower 24 h glycemic profile as a result of a high dairy protein diet did not lead to changes in 24 h substrate partitioning in lean healthy subjects with a normal insulin sensitivity.

Habitually higher dietary glycemic index during puberty is prospectively related to increased risk markers of type 2 diabetes in younger adulthood

OBJECTIVE

Carbohydrate nutrition during periods of physiological insulin resistance such as puberty may affect future risk of type 2 diabetes. This study examined whether the amount or the quality (dietary glycemic index [GI], glycemic load [GL], and added sugar, fiber, and whole-grain intake) of carbohydrates during puberty is associated with risk markers of type 2 diabetes in younger adulthood.

RESEARCH DESIGN AND METHODS

The analysis was based on 226 participants (121 girls and 105 boys) from the Dortmund Nutritional and Anthropometric Longitudinally Designed Study (DONALD) with an average of five 3-day weighed dietary records (range 2-6) during puberty (girls, age 9-14 years; boys, age 10-15 years) and fasting blood samples in younger adulthood (age 18-36 years) (average duration of follow-up 12.6 years). Multivariable linear regression was used to analyze the associations between carbohydrate nutrition and homeostasis model assessment-insulin resistance (HOMA-IR) as well as the liver enzymes alanine aminotransferase (ALT) and γ-glutamyltransferase (GGT) (n = 214).

RESULTS

A higher dietary GI was prospectively related to greater values of HOMA-IR (P(trend) = 0.03), ALT (P(trend) = 0.02), and GGT (P(trend) = 0.04). After adjustment for sex, adult age, baseline BMI, and early life and socioeconomic factors as well as protein and fiber intake, predicted mean HOMA-IR values in energy-adjusted tertiles of GI were 2.37 (95% CI 2.16-2.60), 2.47 (2.26-2.71), and 2.59 (2.35-2.85). The amount of carbohydrates, GL, and added sugar, fiber, and whole-grain intake were not related to the analyzed markers.

CONCLUSIONS

Our data indicate that a habitually higher dietary GI during puberty may adversely affect risk markers of type 2 diabetes in younger adulthood.

White vegetables: glycemia and satiety

The objective of this review is to discuss the effect of white vegetable consumption on glycemia, satiety, and food intake. White vegetables is a term used to refer to vegetables that are white or near white in color and include potatoes, cauliflowers, turnips, onions, parsnips, white corn, kohlrabi, and mushrooms (technically fungi but generally considered a vegetable). They vary greatly in their contribution to the energy and nutrient content of the diet and glycemia and satiety. As with other foods, the glycemic effect of many white vegetables has been measured. The results illustrate that interpretation of the semiquantitative comparative ratings of white vegetables as derived by the glycemic index must be context dependent. As illustrated by using the potato as an example, the glycemic index of white vegetables can be misleading if not interpreted in the context of the overall contribution that the white vegetable makes to the carbohydrate and nutrient composition of the diet and their functionality in satiety and metabolic control within usual meals. It is concluded that application of the glycemic index in isolation to judge the role of white vegetables in the diet and, specifically in the case of potato as consumed in ad libitum meals, has led to premature and possibly counterproductive dietary guidance.

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

Recent criticisms of the glycaemic index (GI) focus on its validity with assertions that GI methodology is not valid, GI values are inaccurate and imprecise, GI does not predict what foods are healthy and that whole grain and fibre are better markers of carbohydrate quality than GI. None of the critics provide sound reasons for rejecting GI because some of their arguments are based on flagrant errors in understanding and interpretation while others are not supported by current data or are inconsistent with other nutritional recommendations. This paper addresses current criticisms of GI and outlines reasons why GI is valid: (1) GI methodology is accurate and precise enough for practical use; (2) GI is a property of foods; and (3) GI is biologically meaningful and relevant to virtually everyone. Current dietary guidelines recommend increased consumption of whole grains and dietary fibre but do not mention GI. However, this is illogical because the evidence that GI affects health outcomes is at least as good or better than that for whole grains and fibre. GI is a novel concept from a regulatory point of view and a number of problems need to be addressed to successfully translate GI knowledge into practice. The problems are not insurmountable but no progress can be made until bias and misunderstanding about GI can be overcome and there is better agreement about what is the actual state of knowledge on GI so that the real issues can be identified and addressed.

Methodology for adding glycemic index to the National Health and Nutrition Examination Survey nutrient database

Generating valid estimates of dietary glycemic index (GI) and glycemic load (GL) has been a challenge in nutritional epidemiology. The methodologic issues may have contributed to the wide variation of GI/GL associations with health outcomes observed in existing literature. We describe a standardized methodology for assigning GI values to items in the National Health and Nutrition Examination Survey (NHANES) nutrient database using the new International Tables to develop research-driven, systematic procedures and strategies to estimate dietary GI/GL exposures of a nationally representative population sample. Nutrient databases for NHANES 2003-2006 contain information on 3,155 unique foods derived from the US Department of Agriculture National Nutrient Database for Standard Reference versions 18 and 20. Assignment of GI values were made to a subset of 2,078 carbohydrate-containing foods using systematic food item matching procedures applied to 2008 international GI tables and online data sources. Matching protocols indicated that 45.4% of foods had identical matches with existing data sources, 31.9% had similar matches, 2.5% derived GI values calculated with the formula for combination foods, 13.6% were assigned a default GI value based on low carbohydrate content, and 6.7% of GI values were based on data extrapolation. Most GI values were derived from international sources; 36.1% were from North American product information. To confirm data assignments, dietary GI and GL intakes of the NHANES 2003-2006 adult participants were estimated from two 24-hour recalls and compared with published studies. Among the 3,689 men and 4,112 women studied, mean dietary GI was 56.2 (men 56.9, women 55.5), mean dietary GL was 138.1 (men 162.1, women 116.4); the distribution of dietary GI was approximately normal. Estimates of population GI and GL compare favorably with other published literature. This methodology of adding GI values to an existing population nutrient database utilized systematic matching protocols and the latest comprehensive data sources on food composition. The database can be applied in clinical and survey research settings where there is interest in estimating individual and population dietary exposures and relating them to health outcomes.