The impact of the addition of toppings/fillings on the glycaemic response to commonly consumed carbohydrate foods

Culinary strategies to manage glycemic response in people with type 2 diabetes: A narrative review

Diet plays a critical role in the management of many chronic diseases. It is well known that individuals with type 2 diabetes (T2D) need to pay close attention to foods rich in carbohydrates to better manage their blood sugar. Usually, individuals are told to increase their dietary fiber intake which is associated with better glycemic control and limit their overall carbohydrate consumption. However, there are many other cooking strategies available to reduce the glycemic response to meals rich in carbohydrates and with a high glycemic index, such as adding fats, proteins, or vinegar, modifying the cooking or preparation processes, and even the selection and storage of foods consumed. The aim of the present narrative review is to summarize some of these existing strategies applied to the cooking process and their ability to modulate glycemic response to meals in individuals with T2D.

Glycemic Index Values of Pasta Products: An Overview

Durum wheat pasta is considered a low-glycemic index (GI) food. In recent years, the interest in developing enriched pasta has increased. Since both the formulation and processing technologies may affect the GI, this study aimed to investigate the GI values of pasta products (pp) reported in the literature until 2020. GI values of pp analyzed following the ISO guidelines were included in this survey. A total of 95 pp were identified and, according to their formulation, classified into 10 categories (n, mean GI): category n 1: 100% refined wheat (35, 55); category n 2: 100% whole wheat (6, 52); category n 3: other cereal-based products (8, 52); category n 4: containing egg (5, 52); category n 5: gluten free (11, 60); category n 6: containing legumes (9, 46); category n 7: noodles and vermicelli (9, 56); category n 8: containing vegetable or algae (6, 51); category n 9: containing other ingredients (5, 37); category n 10: stuffed (1, 58). Overall, pasta is confirmed to be a medium–low-GI food, even if a high variability among or within each category emerged. The formulation of enriched pp able to elicit a controlled glycemic response could represent a strategy to improve the nutritional value of pasta.

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.

Special Low Protein Foods in the UK: An Examination of Their Macronutrient Composition in Comparison to Regular Foods

Special low protein foods (SLPFs) are essential in a low phenylalanine diet for treating phenylketonuria (PKU). With little known about their nutritional composition, all SLPFs on UK prescription were studied (n = 146) and compared to equivalent protein-containing foods (n = 190). SLPF nutritional analysis was obtained from suppliers/manufacturers. Comparable information about regular protein-containing foods was obtained from online UK supermarkets. Similar foods were grouped together, with mean nutritional values calculated for each subgroup (n = 40) and percentage differences determined between SLPFs and regular food subgroups. All SLPF subgroups contained 43-100% less protein than regular foods. Sixty-three percent (n = 25/40) of SLPF subgroups contained less total fat with palm oil (25%, n = 36/146) and hydrogenated vegetable oil (23%, n = 33/146) key fat sources. Sixty-eight percent (n = 27/40) of SLPF subgroups contained more carbohydrate, with 72% (n = 105/146) containing added sugar. Key SLPF starch sources were maize/corn (72%; n = 105/146). Seventy-seven percent (n = 113/146) of SLPFs versus 18% (n = 34/190) of regular foods contained added fibre, predominantly hydrocolloids. Nine percent of SLPFs contained phenylalanine > 25 mg/100 g and sources of phenylalanine/protein in their ingredient lists. Stricter nutritional composition regulations for SLPFs are required, identifying maximum upper limits for macronutrients and phenylalanine, and fat and carbohydrate sources that are associated with healthy outcomes.

Glycemic index of pulses and pulse-based products: a review

Pulses are a major source for plant-based proteins, with over 173 countries producing and exporting over 50 million tons annually. Pulses provide many of the essential nutrients and vitamins for a balanced and healthy diet, hence are health beneficial. Pulses have been known to lower glycemic index (GI), as they elicit lower post prandial glycemic responses, and can prevent insulin resistance, Type 2 diabetes and associated complications. This study reviews the GI values (determined by in vivo methodology) reported in 48 articles during the year 1992-2018 for various pulse type preparations consumed by humans. The GI ranges (glucose and bread as a reference respectively) for each pulse type were: broad bean (40 ± 5 to 94 ± 4, 75 to 93), chickpea (5 ± 1 to 45 ± 1, 14 ± 3 to 96 ± 21), common bean (9 ± 1 to 75 ± 8, 18 ± 2 to 99 ± 11), cowpea (6 ± 1 to 56 ± 0.2, 38 ± 19 to 66 ± 7), lentil (10 ± 3 to 66 ± 6, 37 to 87 ± 6), mung bean (11 ± 2 to 90 ± 9, 28 ± 1 to 44 ± 6), peas (9 ± 2 to 57 ± 2, 45 ± 8 to 93 ± 9), pigeon peas (7 ± 1 to 54 ± 1, 31 ± 4), and mixed pulses (35 ± 5 to 66 ± 23, 69 ± 42 to 98 ± 29). It was found that the method of preparation, processing and heat applications tended to affect the GI of pulses. In addition, removal of the hull, blending, grinding, milling and pureeing, reduced particle size, contributed to an increased surface area and exposure of starch granules to the amylolytic enzymes. This was subsequently associated with rapid digestion and absorption of pulse carbohydrates, resulting in a higher GI. High or increased heat applications to pulses were associated with extensive starch gelatinization, also leading to a higher GI. The type of reference food used (glucose or white bread) and the other nutrients present in the meal also affected the GI.

Relation between the Recipe of Yeast Dough Dishes and Their Glycaemic Indices and Loads

The aim of the study was to evaluate the glycaemic indices (GI) and glycaemic loads (GL) of four food dishes made from yeast dough (steamed dumplings served with yoghurt, apple pancakes sprinkled with sugar powder, rolls with cheese and waffles with sugar powder), based on their traditional and modified recipes. Modification of the yeast dough recipe consisted of replacing wheat flour (type 500) with whole-wheat flour (type 2000). Energy value and the composition of basic nutrients were assessed for every tested dish. The study was conducted on 50 people with an average age of 21.7 ± 1.1 years, and an average body mass index of 21.2 ± 2.0 kg/m2. The GI of the analysed food products depended on the total carbohydrate content, dietary fibre content, water content, and energy value. Modification of yeast food products by replacing wheat flour (type 500) with whole-wheat flour (type 2000) contributed to the reduction of their GI and GL values, respectively.

Postprandial glucose, insulin and incretin responses differ by test meal macronutrient ingestion sequence (PATTERN study)

BACKGROUND

Previous studies have shown that the sequential order of consuming different food components significantly impacts postprandial glucose and insulin excursions in prediabetes and type 2 diabetes, but the causative mechanisms in healthy humans remain ill-defined.

OBJECTIVE

Using a typical Asian meal comprising vegetables, protein (chicken breast), and carbohydrate (white rice), the aim of this study was to examine the effect of food intake sequence on postprandial glucose, insulin and incretin secretions in healthy adults.

DESIGN

Sixteen healthy Chinese adults participated in a randomized, controlled, crossover meal trial. Subjects consumed in random order 5 experimental isocaloric meals that differed in the food intake sequence of vegetables, protein and carbohydrate. Glucose, insulin, incretins and satiety markers were measured over 3 h.

RESULTS

There were significant food intake sequence × time interaction effects on plasma glucose, insulin, glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) concentrations (P < 0.001). In comparison with rice consumed first followed by vegetable and meat (R-VM), the overall postprandial glucose response was significantly attenuated after the food intake sequence of vegetable first, followed by meat and rice (V-MR) or meat first, followed by vegetable and rice (M-VR) or vegetable first followed by meat and rice (V-M-R) or vegetable, meat and rice consumed together (VMR). The insulin iAUC (0-60) was significant lower after V-M-R than M-VR, VMR and R-VM. V-M-R food intake sequence stimulated higher GLP-1 release than other meal sequences. However, GIP response was lower after V-MR and V-M-R than M-VR and R-MR food intake sequences.

CONCLUSIONS

Food macronutrient intake sequence can considerably influence its glycemic, insulinemic and incretin responses. V-M-R food intake sequence attenuates the glycemic response to a greater degree with accentuated GLP-1 stimulation without any increased demand for insulin. The sequence of food intake has great potential as a novel and simple behavioral strategy to modulate glycemic response in healthy adults. The trial was registered at clinicaltrials.gov as NCT03533738.

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.

Starchy Carbohydrates in a Healthy Diet: The Role of the Humble Potato

Potatoes have been an affordable, staple part of the diet for many hundreds of years. Recently however, there has been a decline in consumption, perhaps influenced by erroneous reports of being an unhealthy food. This review provides an overview of the nutritional value of potatoes and examines the evidence for associations between potato consumption and non-communicable diseases. Potatoes are an important source of micronutrients, such as vitamin C, vitamin B6, potassium, folate, and iron and contribute a significant amount of fibre to the diet. However, nutrient content is affected by cooking method; boiling causes leaching of water-soluble nutrients, whereas frying can increase the resistant starch content of the cooked potato. Epidemiological studies have reported associations between potato intake and obesity, type 2 diabetes and cardiovascular disease. However, results are contradictory and confounded by lack of detail on cooking methods. Indeed, potatoes have been reported to be more satiating than other starchy carbohydrates, such as pasta and rice, which may aid weight maintenance. Future research should consider cooking methods in the study design in order to reduce confounding factors and further explore the health impact of this food.

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.

A nutritional evaluation of various typical Italian breakfast products: a comparison of macronutrient composition and glycaemic index values

Breakfast foods with lower glycaemic responses are associated with better body weight control. Glycaemic index (GI) values of some commonly consumed breakfast foods in Italy were determined and compared, along with macronutrients. Cakes/pastries were low-medium GI (44-60), with high-sugar and saturated fat and low-fibre. Generally, mueslis and breads were medium GI (62-66 and 59-76, respectively) with higher fibre and lower saturated fat and sugar. The addition of spreads to bread lowered GI (47-66) but increased sugar and saturated fat.

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.

The effects of potatoes and other carbohydrate side dishes consumed with meat on food intake, glycemia and satiety response in children

BACKGROUND

The effect of carbohydrate (CHO) foods on blood glucose (BG) is ranked by their glycemic index (GI). Boiled and mashed potatoes (BMPs) are ranked as high GI foods, whereas pasta and rice have moderate GI rankings. The objective of this study was to compare ad libitum consumption of common CHO dishes consumed with meat on meal-time food intake and post-meal satiety, BG, insulin and gut hormones in 11- to 13-year-old normal weight children.

METHODS

Two randomized crossover studies were conducted. At weekly intervals, children (experiment 1: 12 males (M), 8 females (F); experiment 2: 6M, 6 F) received in random order 1 of 5 CHO side dishes of rice, pasta, BMP, fried French fries (FFF) or baked French fries (BFF) eaten freely together with a fixed amount of lean beef (100 g). In experiment-1, food intake over 30 min and subjective appetite were measured for 120 min. In experiment-2, the same outcomes were measured along with BG, plasma insulin and gut hormones.

RESULTS

The results for boys and girls were pooled as sex was not a factor. In both experiments, children consumed 30-40% less calories at meals with BMP (P<0.0001) compared with all other treatments, which were similar. BMP increased satiety, expressed as a change in appetite per kilocalorie, more than all other treatments (P<0.0001). FFF resulted in the lowest (P<0.0001) glucose and insulin at meal end and post-meal and peptide YY (PYY) post-meal. Blood measures were similar among all other treatments.

CONCLUSIONS

The physiological functions of CHO foods consumed ad libitum at meal time on food intake, appetite, BG, insulin and gut hormone responses in children is not predicted by the GI.

Physiology of Food Intake Control in Children

The purpose of this review is to draw attention to the limited information available on food intake (FI) control in children and adolescents 7-17 y of age, which is essential for developing food policies and guidelines in this population. Although environmental factors have been the overwhelming focus of research on the causative factors of obesity, research focusing on the physiologic control of appetite in children and adolescents is a neglected area of research. To present this message, a review of FI regulation and the role of food and food components in signaling processes are followed by an examination of the role of hormones during puberty in intake regulation. To examine the interaction of environment and physiology on FI regulation, the effects of exercise, television programs, and food advertisements are discussed. In conclusion, although limited, this literature review supports a need for children and adolescents to be a greater focus of research that would lead to sound nutrition policies and actions to reduce chronic disease. A focus on the environment must be balanced with an understanding of physiologic and behavioral changes associated with this age group.

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.

The role of potatoes and potato components in cardiometabolic health: a review

Potatoes (Solanum tuberosum) are an important food crop worldwide and contribute key nutrients to the diet, including vitamin C, potassium, and dietary fiber. Potatoes and potato components have been shown to have favorable impacts on several measures of cardiometabolic health in animals and humans, including lowering blood pressure, improving lipid profiles, and decreasing markers of inflammation. A range of glycemic index (GI) values have been reported for potatoes, and data are sparse regarding the impact of potato consumption on the postprandial glycemic response, especially when potatoes are consumed with other foods. There is a lack of clinical trial data regarding the impact of potatoes on weight management. A small number of human cohort studies have reported beneficial associations between potato consumption as part of a healthy lifestyle and cardiometabolic health. Another small number of human population studies have included potatoes as part of a dietary pattern with other calorie-dense foods and have not reported cardiometabolic benefits. The epidemiological literature should be interpreted with caution due to lack of consistency in both defining dietary patterns that include potatoes and in control for potential confounding variables. Controlled clinical trials are needed to define the impact of potatoes on cardiometabolic health.

Discovery of a low-glycaemic index potato and relationship with starch digestion in vitro

Potatoes are usually a high-glycaemic index (GI) food. Finding a low-GI potato and developing a screening method for finding low-GI cultivars are both health and agricultural priorities. The aims of the present study were to screen the commonly used and newly introduced cultivars of potatoes, in a bid to discover a low-GI potato, and to describe the relationship between in vitro starch digestibility of cooked potatoes and their in vivo glycaemic response. According to International Standard Organisation (ISO) guidelines, seven different potato cultivars were tested for their GI. In vitro enzymatic starch hydrolysis and chemical analyses, including amylose content analysis, were carried out for each potato cultivar, and correlations with the respective GI values were sought. The potato cultivars had a wide range of GI values (53–103). The Carisma cultivar was classified as low GI and the Nicola cultivar (GI = 69) as medium GI and the other five cultivars were classified as high GI according to ISO guidelines. The GI values were strongly and positively correlated with the percentage of in vitro enzymatic hydrolysis of starch in the cooked potatoes, particularly with the hydrolysis percentage at 120 min (r 0·91 and P <0·01). Amylose, dietary fibre and total starch content was not correlated with either in vitro starch digestibility or GI. The findings suggest that low-GI potato cultivars can be identified by screening using a high-throughput in vitro digestion procedure, while chemical composition, including amylose and fibre content, is not indicative.

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.

Glycemic response to carbohydrate and the effects of exercise and protein

OBJECTIVE

The purpose of this study was to investigate the effects of pre-exercise and protein coingestion on the glycemic response to carbohydrates.

METHODS

Twenty-one volunteers (13 males and 8 females) aged 22 y (± 3.8 y) participated in four trials in random order. These included: 1) glucose ingestion at rest (RG), 2) glucose and protein ingestion at rest (RGP), 3) glucose ingestion after exercise (EG), and 4) glucose and protein ingestion after exercise (EGP). Exercise consisted of 45 min of cycling at 60% of participants' age-predicted maximum heart rate. Test drinks contained 50 g glucose or 50 g glucose with 20 g whey protein. Venous blood samples were taken at baseline and subsequently every 15 min for 2 h after drink consumption. Blood plasma was subsequently analyzed for glucose and insulin.

RESULTS

Plasma glucose concentration was significantly lower in the RGP group than in the RG group at 30, 45, 60, and 75 min and in the EGP group than in the EG group at 30, 45, and 60 min (P < 0.05). Plasma insulin area under the curve was significantly higher in the RGP group than in the RG group and in than in the EGP group than in the EG group (P < 0.05). No significant effect of exercise was seen on glycemic or insulinemic responses.

CONCLUSIONS

Coingestion of protein with carbohydrate reduces glycemic response and increases insulinemic response in healthy subjects, whereas pre-exercise seems to have no effect.

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.

Food microstructure and starch digestion

Microstructural characteristics of starch-based natural foods such as parenchyma or cotyledon cell shape, cell size and composition, and cell wall composition play a key role in influencing the starch digestibility during gastrointestinal digestion. The stability of cell wall components and the arrangement of starch granules in the cells may affect the free access of amylolytic enzymes during digestion. Commonly used food processing techniques such as thermal processing, extrusion cooking, and post-cooking refrigerated storage alter the physical state of starch (gelatinization, retrogradation, etc.) and its digestibility. Rheological characteristics (viscosity) of food affect the water availability during starch hydrolysis and, consequently, the absorption of digested carbohydrates in the gastrointestinal tract. The nonstarch ingredients and other constituents present in food matrix, such as proteins and lipids interact with starch during processing, which leads to an alteration in the overall starch digestibility and physicochemical characteristics of digesta. Starch digestibility can be controlled by critically manipulating the food microstructure, processing techniques, and food composition.

Calculating meal glycemic index by using measured and published food values compared with directly measured meal glycemic index

BACKGROUND

Glycemic index (GI) testing is normally based on individual foods, whereas GIs for meals or diets are based on a formula using a weighted sum of the constituents. The accuracy with which the formula can predict a meal or diet GI is questionable.

OBJECTIVE

Our objective was to compare the GI of meals, obtained by using the formula and by using both measured food GI and published values, with directly measured meal GIs.

DESIGN

The GIs of 7 foods were tested in 30 healthy people. The foods were combined into 3 meals, each of which provided 50 g available carbohydrate, including a staple (potato, rice, or spaghetti), vegetables, sauce, and pan-fried chicken.

RESULTS

The mean (95% CI) meal GIs determined from individual food GI values and by direct measurement were as follows: potato meal [predicted, 63 (56, 70); measured, 53 (46, 62)], rice meal [predicted, 51 (45, 56); measured, 38 (33, 45)], and spaghetti meal [predicted, 54 (49, 60); measured, 38 (33, 44)]. The predicted meal GIs were all higher than the measured GIs (P < 0.001). The extent of the overestimation depended on the particular food, ie, 12, 15, and 19 GI units (or 22%, 40%, and 50%) for the potato, rice, and spaghetti meals, respectively.

CONCLUSIONS

The formula overestimated the GI of the meals by between 22% and 50%. The use of published food values also overestimated the measured meal GIs. Investigators using the formula to calculate a meal or diet GI should be aware of limitations in the method. This trial is registered with the Australian and New Zealand Clinical Trials Registry as ACTRN12611000210976.

High-glycaemic index and -glycaemic load meals increase the availability of tryptophan in healthy volunteers

The purpose of the present study was to determine the influence of the glycaemic index (GI) and glycaemic load (GL) on the ratio of tryptophan (TRP) relative to other large neutral amino acids (LNAA). Ten healthy men (age 22·9 (sd 3·4) years; BMI 23·5 (sd 1·6) kg/m2) underwent standard GI testing, and later consumed each of a mixed-macronutrient (1915 kJ; 66·5 % carbohydrate (CHO), 17 % protein and 16·5 % fat) high-GI (MHGI), an isoenergetic, mixed-macronutrient low-GI (MLGI) and a CHO-only (3212 kJ; 90 % CHO, 8 % protein, 2 % fat) high-GI (CHGI) meal on separate days. The GI, GL and insulin index values (e.g. area under the curve) were largest after the CHGI meal (117, 200, 158), followed by the MHGI (79, 59, 82) and MLGI (51, 38, 56) meals, respectively (all values were significantly different, P < 0·05). After the MHGI and MLGI meals but not after the CHGI meal, TRP was elevated at 120 and 180 min (P < 0·05). After the CHGI, LNAA was lower compared with the MLGI (P < 0·05); also the rate of decline in LNAA was higher after CHGI compared with MHGI and MLGI (both comparisons P < 0·05). The percentage increase from baseline in TRP:LNAA after CHGI (23 %) was only marginally higher than after the MHGI meal (17 %; P = 0·38), but it was threefold and nearly significantly greater than MLGI (8 %; P = 0·05). The present study demonstrates that the postprandial rise in TRP:LNAA was increased by additional CHO ingestion and higher GI. Therefore, the meal GL appears to be an important factor influencing the postprandial TRP:LNAA concentration.

Protein and fat modify the glycaemic and insulinaemic responses to a mashed potato-based meal

Potatoes, especially mashed potatoes, are known to result in high glycaemic and insulinaemic responses. However, in most meals, potatoes are accompanied by other foods. The objective of the present study was to investigate how glycaemic and insulinaemic responses to a mashed potato meal changed when a high-fat food (rapeseed oil), a high-protein food (chicken breast) and/or salad were added to the meal. Healthy subjects (n11) ingested the test meals once and the reference food (glucose solution) twice in a random order at 1-week intervals. Capillary blood samples were then drawn for 2 h, and glucose and insulin were analysed. The 2 h glycaemic responses to six mashed potato-containing meals varied more than twofold. The glycaemic index (GI) of pure mashed potato was 108, whereas combined with chicken breast, rapeseed oil and salad, it was only 54. The latter GI also differed considerably from its predicted value of 103, which was based on the individual GI of the components of the meal. The insulinaemic indices of the mashed potato-based meals varied between 94 and 148. Chicken breast in the meal increased the insulinaemic response, and rapeseed oil diminished it. However, the insulinaemic response to mashed potato with chicken breast and rapeseed oil was lower than that to mashed potato alone. In conclusion, the protein, fat and salad contents of a meal exert considerable influence on the glycaemic and insulinaemic responses to mashed potatoes. Furthermore, the estimation of the GI of a mixed meal by calculation is imprecise.

Glycemic impact as a property of foods is accurately measured by an available carbohydrate method that mimics the glycemic response

The relative glycemic impact (RGI), the weight of glucose that would induce a glycemic response equivalent to that induced by a given amount of food, is preferably expressed for reference amounts of foods customarily consumed per eating occasion. But because customarily consumed portions of different foods deliver different glycemic carbohydrate doses, methods for determining their RGI need to allow for homeostatic responses to different glycemic carbohydrate loadings. We tested the accuracy of an in vitro method for measuring the RGI of customarily consumed portions that allows for homeostasis, using 24 foods. Glucose equivalents released during simulated gastrointestinal digestion were adjusted by the glycemic potency of contributing sugars to obtain cumulative glycemic glucose equivalents (GGE) and multiplied by food portion weight. Corresponding dose-dependent blood glucose clearance was calculated and subtracted from GGE, giving net GGE compared with time curves reminiscent of blood glucose response curves. RGI values (GGE content) for the food portions were obtained by comparing incremental areas under the curves for foods with that for a white bread reference of known GGE content. The correlation between in vivo values calculated from glycemic index values for the same foods and in vitro values was: in vivo GGE = 1.0 in vitro GGE - 0.5; R2 = 0.90. Bland-Altman methods comparison analysis showed close agreement: in vivo GGE = -0.055 in vitro GGE + 1.16; R2 = 0.027. The results suggest that a modified available carbohydrate determination can economically provide valid RGI values for consumer and industry use.

Glycemic response of mashed potato containing high-viscocity hydroxypropylmethylcellulose

Potatoes generally have one of the highest glycemic index values of any food. Relatively small differences in the glycemic response (GR) of regularly consumed starch foods have shown beneficial effects on health. Lowering the GR of a potato-based meal has potentially wide-reaching health benefits. High-viscosity hydroxypropylmethylcellulose (HV-HPMC) is a modified cellulose dietary fiber extensively used in the food industry. We hypothesized that the GR of a high-glycemic index product such as mashed potato would be lower with the addition of HV-HPMC. In a nonblind, randomized, repeat-measure, crossover controlled trial, 15 healthy adults consumed portions of mashed potato with different doses (0%, 1%, 2%, and 4%) of a specially selected and optimized HV-HPMC and a reference food (glucose) on separate occasions. Five subjects were excluded from the final analysis due to noncompliance with study procedures. Capillary blood glucose was measured in fasted subjects and at 15, 30, 45, 60, 90, and 120 minutes after starting to eat. For each sample, the incremental area under the blood glucose response curve was calculated and the GR determined. There was a significant lowering effect of HV-HPMC on GR (P < .001) of mashed potato. Glycemic responses for all mashed potato samples with the HV-HPMC were significantly lower than the standard mashed potato: 1% level (P < .05), 2% level (P < .05), and 4% level (P < .05). However, there was no significant effect of the HV-HPMC dose on GR. We conclude that addition of select HV-HPMC to mashed potato blunts GR.

Baselines representing blood glucose clearance improve in vitro prediction of the glycaemic impact of customarily consumed food quantities

Glycaemic responses to foods reflect the balance between glucose loading into, and its clearance from, the blood. Current in vitro methods for glycaemic analysis do not take into account the key role of glucose disposal. The present study aimed to develop a food intake-sensitive method for measuring the glycaemic impact of food quantities usually consumed, as the difference between release of glucose equivalents (GGE) from food during in vitro digestion and a corresponding estimate of clearance of them from the blood. Five foods – white bread, fruit bread, muesli bar, mashed potato and chickpeas – were consumed on three occasions by twenty volunteers to provide blood glucose response (BGR) curves. GGE release during in vitro digestion of the foods was also plotted. Glucose disposal rates estimated from downward slopes of the BGR curves allowed GGE dose-dependent cumulative glucose disposal to be calculated. By subtracting cumulative glucose disposal from cumulative in vitro GGE release, accuracy in predicting the in vivo glycaemic effect from in vitro GGE values was greatly improved. GGEin vivo = 0·99GGEin vitro+0·75 (R2 0·88). Furthermore, the difference between the curves of cumulative GGE release and disposal closely mimicked in vivo incremental BGR curves. We conclude that valid measurement of the glycaemic impact of foods may be obtained in vitro, and expressed as grams of glucose equivalents per food quantity, by taking account not only of GGE release from food during in vitro digestion, but also of blood glucose clearance in response to the food quantity.

Dose-dependent effects of barley cooked with white rice on postprandial glucose and desacyl ghrelin levels

White rice is an indispensable staple food in Japan, although it is a high glycemic index food. The objective of this study was to estimate how barley cooked with white rice might affect postprandial glucose, insulin and desacyl ghrelin concentrations as well as fullness. The study was conducted in randomized crossover design with nine healthy subjects. Blood glucose, insulin, free fatty acid and desacyl ghrelin concentrations and subjective levels of fullness and hunger were measured for 240 min after intake of glucose, white rice, 30% rolled barley (30BAR), 50% rolled barley (50BAR) and 100% rolled barley (100BAR) containing 75 g of available carbohydrate. Postprandial glucose and insulin levels were suppressed by intake of 30BAR, 50BAR and 100BAR comparing with those of white rice. Area under the curves of plasma glucose and insulin concentrations was reduced by barley intake in a dose-dependent manner. Although plasma desacyl ghrelin levels decreased postprandially, the degree of reduction was suppressed by barley intake in a dose-dependent manner. Postprandial desacyl ghrelin levels can be a sensitive biomarker of carbohydrate metabolism. The combination of white rice with barley plays a beneficial role in preventing and treating type 2 diabetes, obesity and other metabolic diseases.

Perilipin polymorphism interacts with dietary carbohydrates to modulate anthropometric traits in hispanics of Caribbean origin

Perilipin (PLIN) is the major protein surrounding lipid droplets in adipocytes and regulates adipocyte metabolism by modulating the interaction between lipases and triacylglycerol stores. Associations between PLIN gene polymorphisms and obesity risk have been described, but interactions with dietary macronutrients require further attention. We examined whether dietary macronutrients (e.g. carbohydrates and fats) modulated the associations of the common PLIN 11482G > A (rs894160) single nucleotide polymorphism with obesity. We studied a population-based sample of Caribbean-origin Hispanics (n = 920, aged 45-74 y) living in the Boston area. Obesity measures (waist and hip circumference, BMI) did not differ between GG subjects and carriers of the A allele (GA and AA). In multivariate linear regression models, we found a significant interaction between complex carbohydrate intake as a continuous variable and PLIN 11482 G > A genotype for waist circumference (P = 0.002). By dichotomizing complex carbohydrate intake, we found significantly different effects across PLIN 11482G > A genotypes. When complex carbohydrate intake was <144 g/d, waist circumference was larger in PLIN 11482G > A carriers (P = 0.024). Conversely, when complex carbohydrate intake was >/=144 g/d, waist and hip circumferences were less in PLIN 11482G > A carriers (P < 0.05). These interactions were not found for simple sugars or total carbohydrates. We identified a significant gene-diet interaction associated with obesity at the PLIN locus. In subjects with higher complex carbohydrate intake, the minor allele was protective against obesity, whereas in subjects with lower carbohydrate intake, the minor allele was associated with increased obesity. These interactions may be relevant to dietary management of obesity.