Babul (Acacia nilotica)

Purpose

– The prevalence of diabetes has increased manifold and now become a public health problem from being mild disorder. There is a need to discover more effective and safer antidiabetic agents by utilizing the rich heritage of medicinal plants. Tannins are polyphenols that are obtained from various parts of different plants belonging to multiple species and considered as potential drugs for the treatment of non-insulin-dependent diabetes mellitus. The paper aims to discuss these issues.

Design/methodology/approach

– The study was conducted in three phases: incorporation of Babul powder in biscuits: assessment of Glycemic Index (GI): suitability of Babul powder on diabetic subjects statistical analysis: area under curve (AUC) for increase in blood glucose was calculated by trapezoidal rule and means were tested for significance by paired t-test. Mean glucose levels of all subjects were calculated for each time point. p<0.05 was considered statistically significant.

Findings

– Tannins are polyphenols that are obtained from various parts of different plants belonging to multiple species. As an indigenous plant of Rajasthan, Babul contains high amount of tannin levels ranging from 18 to 27 percent in deseeded pods from ssp. indica, whereas ssp. nilotica reached up to 50 percent. Hence, Babul was selected as the source of tannin and subjected to diabetics for its suitability. The study concluded that Babul powder is effective in management of blood glucose levels even the simple sugars also and can be considered as suitable for diabetics. The active component for the purpose may be the presence of tannin in the Babul.

Research limitations/implications

– The study was conducted on limited number of subjects. A confirmation study is suggested on the diabetic population.

Originality/value

– The prevalence of diabetes is rapidly rising all over the globe at an alarming rate. Over few decades, the status of diabetes has changed from being considered as a mild disorder of the elderly to one of the major causes of morbidity and mortality affecting the youth and middle-aged people. Therefore, the present study focused on the development of tannin-based nutraceutical for incorporation in common foods and its health-promoting effect on diabetes.

Effects of consumption of main and side dishes with white rice on postprandial glucose, insulin, glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 responses in healthy Japanese men

The co-ingestion of protein, fat and fibre with carbohydrate reportedly affects postprandial glucose, insulin and incretin (glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1)) responses. However, the effects of combination dishes with carbohydrate-rich foods at typically eaten amounts remain unclear. The objective of the present study was to evaluate the effects of consuming recommended amounts of side dishes with boiled white rice in the same meal on postprandial plasma glucose, insulin and incretin hormone responses. A total of nine healthy male volunteers consumed four different meals in a random order on separate days. The test meals were as follows: S, white rice; SM, addition of protein-rich main dishes to the S meal; SMF, addition of a fat-rich food item to the SM meal; SMFV, addition of vegetables to the SMF meal. Plasma glucose, GIP and GLP-1 and serum insulin concentrations were determined during a 3 h period after consumption of these meals. Postprandial glucose responses were lower after SMFV meal consumption than after consumption of the other meals. The incremental AUC for GIP (0–180 min) were largest after consumption of the SMF and SMFV meals, followed by that after SM meal consumption, and was smallest after S meal consumption (P< 0·05). Furthermore, we found GIP concentrations to be dose dependently increased by the fat content of meals of ordinary size, despite the amount of additional fat being small. In conclusion, the combination of recommended amounts of main and vegetable side dishes with boiled white rice is beneficial for lowering postprandial glucose concentrations, with an increased incretin response, when compared with white rice alone.

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.

Effect of water content and flour particle size on gluten-free bread quality and digestibility

The impact of dough hydration level and particle size distribution of the rice flour on the gluten free bread quality and in vitro starch hydrolysis was studied. Rice flour was fractionated in fine and coarse parts and mixed with different amounts of water (70%, 90% and 110% hydration levels) and the rest of ingredients used for making gluten free bread. A larger bread specific volume was obtained when coarser fraction and great dough hydration (90-110%) were combined. The crumb texture improved when increasing dough hydration, although that effect was more pronounced when breads were obtained from a fine fraction. The estimated glycaemic index was higher in breads with higher hydration (90-110%). Slowly digestible starch (SDS) and resistant starch (RS) increased in the coarse flour breads. The coarse fraction complemented with a great dough hydration (90-110%) was the most suitable combination for developing rice bread when considering the bread volume and crumb texture. However, the lowest dough hydration limited starch gelatinization and hindered the in vitro starch digestibility.

Health Canada's evaluation of the use of glycemic index claims on food labels

The glycemic index (GI) is a system that ranks foods according to the blood glucose-increasing potential of servings of foods that provide the same amount of available carbohydrate. The GI was originally developed as a tool for carbohydrate exchange in the dietary management of glycemia in persons with diabetes, and studies have generally supported modest benefits of low-GI diets in this population. Despite inconsistent results for the utility of the GI in the nondiabetic population, there is some interest in its universal application on food labels to assist consumers in making food choices that would help them meet their dietary goals. The objective of this review was to evaluate the usefulness of including the GI values of foods as part of the information on food labels in Canada. Health Canada's assessment identified 3 areas of concern with respect to GI labeling: 1) the GI measure has poor accuracy and precision for labeling purposes; 2) as a ratio, the GI does not vary in response to the amount of food consumed and the partial replacement of available carbohydrates with unavailable carbohydrates, whereas the glycemic response does; and 3) an unintended focus on the GI for food selection could lead to food choices that are inconsistent with national dietary guidelines. Hence, Health Canada's current opinion is that the inclusion of the GI value on the label of eligible food products would be misleading and would not add value to nutrition labeling and dietary guidelines in assisting consumers to make healthier food choices.

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.

Glycaemic index methodology

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

Effects of two different types of fast food on postprandial metabolism in normal and overweight subjects

BACKGROUND/OBJECTIVES

The aim was to investigate the effects of a conventional and an unconventional fast-food meal on postprandial metabolism in normal and in overweight subjects.

SUBJECTS/METHODS

Twenty-five healthy normal (n = 12) and overweight (n = 13) volunteers (21-39 years) participated in this randomized, dietary cross-over study and received two test meals (matched in energy and energy giving nutrients) after an overnight fast with 1 week between test days. The conventional fast-food meal was a hamburger meal (hamburger, bacon, cola drink, calculated glycemic load = 48.7), the unconventional fast food was a salmonburger meal (fiber-rich sourdough rye bread, salad with vinegar, orange juice, glycemic load = 46.0). Blood samples were taken before and after the meal and analyzed for glucose (before 20, 40, 60 and 80 min) and insulin (before 1, 2 and 3 h).

RESULTS

Postprandial increases in glucose and insulin were 44% lower after the unconventional meal (P<0.001 and P = 0.003, respectively). The difference between meals in insulin response (that is, conventional meal higher than unconventional) correlated with body mass index (BMI) (r = 0.538, P = 0.006).

CONCLUSIONS

Unconventional fast food can have less effect on blood insulin and glucose postprandially compared with conventional fast food matched in energy and energy giving nutrients. The difference between meals in insulin response is associated with higher BMI. Thus, improvement in food quality might help to control postprandial increases in blood glucose and blood insulin.

Glycemic index predicts individual glucose responses after self-selected breakfasts in free-living, abdominally obese adults

The degree to which an individual's glycemic response to a meal is determined by the glycemic index (GI) and other components of the meal remains unclear, especially when meals are not consumed in a highly controlled research setting. To address this question, we analyzed data collected during the run-in period of a clinical trial. Free-living, nondiabetic adults (n = 57) aged 53.9 ± 9.8 y (mean ± SD) with a BMI of 33.9 ± 5.3 kg/m(2) and waist circumference of 109 ± 11 cm underwent a 75-g oral glucose tolerance test (OGTT) and, on a separate day, wore a continuous glucose-monitoring system (CGMS) for 24 h during which time they recorded all foods consumed. The protein, fat, and available carbohydrate (avCHO) content and GI of the breakfast meals were calculated from the food records and the incremental areas under the glycemic response curves (iAUC) for 2 h after breakfast (iAUC(breakfast)) were calculated from CGMS data. Values for iAUC(breakfast), avCHO, fat, fiber, and BMI were normalized by log-transformation. The ability of participant characteristics and breakfast composition to predict individual iAUC(breakfast) responses was determined using step-wise multiple linear regression. A total of 56% of the variation in iAUC(breakfast) was explained by GI (30%; P < 0.001), iAUC after the OGTT (11%; P < 0.001), avCHO (11%; P < 0.001), and waist circumference (3%; P = 0.049); the effects of fat, protein, dietary fiber, age, sex, and BMI were not significant. We concluded that, in free-living, abdominally obese adults, GI is a significant determinant of individual glycemic responses elicited by self-selected breakfast meals. In this study, GI was a more important determinant of glycemic response than carbohydrate intake.

The individual and combined effects of glycemic index and protein on glycemic response, hunger, and energy intake

Although high protein and low glycemic index (GI) foods are thought to promote satiety, little is known about the effects of GI, protein, and their interaction on hunger and energy intake several hours following a mixed meal. This study investigated the long term effects of GI, protein, and their combined effects on glucose, insulin, hunger, and energy intake in healthy, sedentary, overweight, and obese adults (BMI of 30.9 ± 3.7 kg/m(2)). Sixteen individuals participated separately in four testing sessions after an overnight fast. The majority (75%) were non-Hispanic Blacks. Each consumed one of four breakfast meals (high GI/low protein, high GI/high protein, low GI/low protein, low GI/high protein) in random order. Visual analog scales (VAS) and blood samples were taken at baseline, 15 min, and at 30 min intervals over 4 h following the meal. After 4 h, participants were given the opportunity to consume food ad libitum from a buffet style lunch. Meals containing low GI foods produced a smaller glucose (P < 0.002) and insulin (P = 0.0001) response than meals containing high GI foods. No main effects for protein or interactions between GI and protein were observed in glucose or insulin responses, respectively. The four meals had no differential effect on observed energy intake or self-reported hunger, satiety, and prospective energy intake. Low GI meals produced the smallest postprandial increases in glucose and insulin. There were no effects for GI, protein, or their interaction on appetite or energy intake 4 h after breakfast.

Continuous glucose monitoring to assess the ecologic validity of dietary glycemic index and glycemic load

BACKGROUND

The circumstances under which the glycemic index (GI) and glycemic load (GL) are derived do not reflect real-world eating behavior. Thus, the ecologic validity of these constructs is incompletely known.

OBJECTIVE

This study examined the relation of dietary intake to glycemic response when foods are consumed under free-living conditions.

DESIGN

Participants were 26 overweight or obese adults with type 2 diabetes who participated in a randomized trial of lifestyle modification. The current study includes baseline data, before initiation of the intervention. Participants wore a continuous glucose monitor and simultaneously kept a food diary for 3 d. The dietary variables included GI, GL, and intakes of energy, fat, protein, carbohydrate, sugars, and fiber. The glycemic response variables included AUC, mean and SD of continuous glucose monitoring (CGM) values, percentage of CGM values in euglycemic and hyperglycemic ranges, and mean amplitude of glycemic excursions. Relations between daily dietary intake and glycemic outcomes were examined.

RESULTS

Data were available from 41 d of monitoring. Partial correlations, controlled for energy intake, indicated that GI or GL was significantly associated with each glycemic response outcome. In multivariate analyses, dietary GI accounted for 10% to 18% of the variance in each glycemic variable, independent of energy and carbohydrate intakes (P < 0.01).

CONCLUSIONS

The data support the ecologic validity of the GI and GL constructs in free-living obese adults with type 2 diabetes. GI was the strongest and most consistent independent predictor of glycemic stability and variability.

Glycemic index and glycemic load used in combination to characterize metabolic responses of mixed meals in healthy lean young adults

BACKGROUND

Glycemic index (GI) and glycemic load (GL) have been independently assessed with regard to their metabolic effects and their associations with disease risk. Because a low-GI high-carbohydrate and a high-GI low-carbohydrate food/meal can produce the same GL, we propose that these 2 concepts should be used in conjunction to characterize the carbohydrate quality of mixed meals.

OBJECTIVE

The aim of this study was to measure postprandial glucose, insulin, and cortisol responses of meals differing in both GI and GL over a period of 3 hours (every 15 minutes for the first hour, and every 30 minutes subsequently), and to investigate the validity of methods of calculating GI and GL by measuring the cumulative incremental area under the curve (iAUC) for glucose and insulin (0-2 hours and 2-3 hours postprandially).

METHODS

A total of 10 healthy lean young adults (5 males, 5 females) participated. Breakfast meals were designed to differ in terms of GI and GL based on a 2 × 2 grid with a single elaboration: low-GI high-GL (M1); high-GI high-GL (M2a) of similar GL to M1; high-GI high-GL (M2b) of similar macronutrient composition to M1 (the elaboration); low-GI low-GL (M3); and high-GI low-GL (M4). The 5 breakfast meals were administered in a double-blind randomized crossover design. Repeated measures analysis of variance was performed to investigate differences in metabolic response between low- versus high-GI and between low- versus high-GL breakfast meals (and GI × GL interactions), with GI and GL used as within-subject factors.

RESULTS

High-GL meals increased glucose iAUC and insulin iAUC in both immediate (0-2 hours) (p < 0.01, p < 0.001, respectively) and middle postabsorptive periods (2-3 hours) (p = 0.04, p = 0.02, respectively) compared with low-GL meals. GI meals were not associated with glucose iAUC 0 to 2 hours (p = 0.37) and 2 to 3 hours (p = 0.81) postprandially. GI meals were not associated with insulin iAUC 0 to 2 hours postprandially (p = 0.81); in contrast, high-GI meals increased insulin iAUC 2 to 3 hours postprandially (p = 0.03) compared with low-GI meals. No significant differences were noted in cortisol responses, GI × GL interactions, or effect modification by gender.

CONCLUSIONS

These findings highlight the need for further investigation of meals/diets differing in both GI and GL to characterize metabolic responses and potential health effects.

Glycemic and insulinemic responses to carbohydrate rich whole foods

Glycemic and insulinemic responses to food may depend on several intrinsic factors such as the type of sugar, molecular arrangement, size of starch granules, co-components in the whole food like moisture, fat, protein, fiber, as well as external factors like processing technique and total amount consumed. The postprandial glycemic response to equivalent quantities of test food and standard food is compared using Glycemic Index food (GI food). The incremental area under the curve for blood glucose and insulin at fasting, 30, 60, 90 and 120 min after consumption of different doses (50 and 100 g) of carbohydrate rich foods like rice and chapatti were compared with standard food, white bread. The GI food value for 50 g of chapatti and rice was 44 and 11 respectively. The Insulinemic Index food (II food) values, calculated similarly, for 50 g portion of chapatti and rice were 39 and 6 respectively. Glycemic and insulinemic response showed a dose dependent increase from 50 to 100 g. Both glycemic and insulinemic impact of chapatti were found to be significantly higher than that of rice (p < 0.05). The GI food and II food values will facilitate qualitative and quantitative judgment about the selection of specific foods for effective metabolic control.

Food intake and dietary glycaemic index in free-living adults with and without type 2 diabetes mellitus

A recent Cochrane review concluded that low glycaemic index (GI) diets are beneficial in glycaemic control for patients with type 2 diabetes mellitus (T2DM). There are limited UK data regarding the dietary GI in free-living adults with and without T2DM. We measured the energy and macronutrient intake and the dietary GI in a group (n = 19) of individuals with diet controlled T2DM and a group (n = 19) without diabetes, matched for age, BMI and gender. Subjects completed a three-day weighed dietary record. Patients with T2DM consumed more daily portions of wholegrains (2.3 vs. 1.1, P = 0.003), more dietary fibre (32.1 vs. 20.9 g, P < 0.001) and had a lower diet GI (53.5 vs. 57.7, P = 0.009) than subjects without T2DM. Both groups had elevated fat and salt intake and low fruit and vegetable intake, relative to current UK recommendations.

CONCLUSIONS

Patients with T2DM may already consume a lower GI diet than the general population but further efforts are needed to reduce dietary GI and achieve other nutrient targets.

Prediction of postprandial glycemia and insulinemia in lean, young, healthy adults: glycemic load compared with carbohydrate content alone

BACKGROUND

Dietary glycemic load (GL; defined as the mathematical product of the glycemic index and carbohydrate content) is increasingly used in nutritional epidemiology. Its ability to predict postprandial glycemia and insulinemia for a wide range of foods or mixed meals is unclear.

OBJECTIVE

Our objective was to assess the degree of association between calculated GL and observed glucose and insulin responses in healthy subjects consuming isoenergetic portions of single foods and mixed meals.

DESIGN

In study 1, groups of healthy subjects consumed 1000-kJ portions of 121 single foods in 10 food categories. In study 2, healthy subjects consumed 2000-kJ servings of 13 mixed meals. Foods and meals varied widely in macronutrient content, fiber, and GL. Glycemia and insulinemia were quantified as area under the curve relative to a reference food (= 100).

RESULTS

Among the single foods, GL was a more powerful predictor of postprandial glycemia and insulinemia than was the available carbohydrate content, explaining 85% and 59% of the observed variation, respectively (P < 0.001). Similarly, for mixed meals, GL was also the strongest predictor of postprandial glucose and insulin responses, explaining 58% (P = 0.003) and 46% (P = 0.01) of the variation, respectively. Carbohydrate content alone predicted the glucose and insulin responses to single foods (P < 0.001) but not to mixed meals.

CONCLUSION

These findings provide the first large-scale, systematic evidence of the physiologic validity and superiority of dietary GL over carbohydrate content alone to estimate postprandial glycemia and insulin demand in healthy individuals. This trial was registered at ANZCTR.org as ACTRN12610000484044.

Are the glycemic and insulinemic index values of carbohydrate foods similar in healthy control, hyperinsulinemic and type 2 diabetic patients?

BACKGROUND/OBJECTIVES

a criticism of glycemic index (GI) is that it does not indicate the insulin response of foods (insulinemic index, II). However, it is unknown if the GI and II values of foods are equivalent in all subjects, a necessary criterion for clinical utility. We compared GI and II values in non-diabetic subjects with fasting-serum-insulin (FSI) <40 pmol/l (healthy control) or with FSI ≥ 40 pmol/l (hyper[I]) and subjects with type 2 diabetes (T2DM), and to see whether GI and II were related to the serum-glucose concentrations, insulin sensitivity, β-cell function and hepatic insulin extraction (HIE) of the subjects.

SUBJECTS/METHODS

Serum-glucose, -insulin and -C-peptide responses after 50 g available-carbohydrate portions of glucose (tested three times by each subject), sucrose, instant mashed-potato, white-bread, polished-rice and pearled-barley were measured in healthy control (n=9), hyper[I] (n=12) and T2DM (n=10) subjects.

RESULTS

Food GI values did not differ significantly among the three subject groups, whereas II values were higher in T2DM (100±7) than healthy controls (78±5) and hyper[I] subjects (70±5) (mean±s.e.m., P=0.05). II was inversely associated with insulin sensitivity (r=-0.66, P<0.0001) and positively related to fasting- and postprandial-glucose (both r=0.68, P<0.0001) and HIE (r=0.62, P=0.0002). In contrast, GI was not related to any of the biomarkers (P>0.05).

CONCLUSION

The GI is a valid property of foods because its value is similar in healthy control, hyper [I] and T2DM subjects, and is independent of subjects' metabolic status. However, II may depend upon the glycaemic control, insulin sensitivity and HIE of the subjects.

Perceived barriers to application of glycaemic index: valid concerns or lost in translation?

The term glycaemic-index (GI) originally appeared in the literature in the early 1980s. GI categorizes carbohydrate according to glycaemic effect postprandially. Since its inception, GI has obtained and maintained interest of academics and clinicians globally. Upon review of GI literature, it becomes clear that the clinical utility of GI is a source of controversy. Can and should GI be applied clinically? There are academics and clinicians on both sides of the argument. Certainly, this controversy has been a stimulus for the evolution of GI methodology and application research, but may also negatively impact clinicians' perception of GI if misunderstood. This article reviews two assessments of GI that are often listed as barriers to application; the GI concept is (1) too complex and (2) too difficult for clients to apply. The literature reviewed does not support the majority of purported barriers, but does indicate that there is a call from clinicians for more and improved GI education tools and clinician GI education. The literature indicates that the Registered Dietitian (RD) can play a key role in GI knowledge translation; from research to application. Research is warranted to assess GI education tool and knowledge needs of clinicians and the clients they serve.

Glycaemic index values in the Finnish food composition database: an approach to standardised value documentation

BACKGROUND/OBJECTIVES

The glycaemic index (GI) is used to describe the blood glucose-raising potential of carbohydrate-containing foods. Only a few descriptions of the addition of GI values to national food composition databases (FCDBs) exist. We tested whether the value documentation framework established within the European Food Information Resource (EuroFIR) Network could be used for GI values when adding them to the Finnish FCDB.

METHODS

The list of foods requiring GI values was based on the National FINDIET 2007 Survey data and extended with foods encoded in a food-frequency questionnaire used in other nationally representative studies. The minimum quality of GI measurements was verified when gathering values from various sources, using earlier defined criteria. If a measured GI value for a food was directly available, or could be imputed or estimated, the value was added to the Finnish FCDB and documented using core standard vocabularies of EuroFIR. The GI values of composite foods were calculated using recipe calculation software.

RESULTS

A total of 2210 foods required a GI value. GI values for 1322 foods were available and added to the FCDB. The remaining 888 foods were composite foods and received a GI value through recipe calculation. The standard vocabularies describing the origin of the GI values, the methods used in their derivation and their qualitative characteristics were suitable for GI values.

CONCLUSIONS

GI values can be added to FCDBs and documented using terms similar to those used for traditional food composition data. Standardised value documentation may provide transparency for GI database compilation processes.

The evidence for medical nutrition therapy for type 1 and type 2 diabetes in adults

This article reviews the evidence and nutrition practice recommendations from the American Dietetic Association's nutrition practice guidelines for type 1 and type 2 diabetes in adults. The research literature was reviewed to answer nutrition practice questions and resulted in 29 recommendations. Here, we present the recommendations and provide a comprehensive and systematic review of the evidence associated with their development. Major nutrition therapy factors reviewed are carbohydrate (intake, sucrose, non-nutritive sweeteners, glycemic index, and fiber), protein intake, cardiovascular disease, and weight management. Contributing factors to nutrition therapy reviewed are physical activity and glucose monitoring. Based on individualized nutrition therapy client/patient goals and lifestyle changes the client/patient is willing and able to make, registered dietitians can select appropriate interventions based on key recommendations that include consistency in day-to-day carbohydrate intake, adjusting insulin doses to match carbohydrate intake, substitution of sucrose-containing foods, usual protein intake, cardioprotective nutrition interventions, weight management strategies, regular physical activity, and use of self-monitored blood glucose data. The evidence is strong that medical nutrition therapy provided by registered dietitians is an effective and essential therapy in the management of diabetes.

Methodology for adding and amending glycaemic index values to a nutrition analysis package

Since its introduction in 1981, the glycaemic index (GI) has been a useful tool for classifying the glycaemic effects of carbohydrate foods. Consumption of a low-GI diet has been associated with a reduced risk of developing CVD, diabetes mellitus and certain cancers. WISP (Tinuviel Software, Llanfechell, Anglesey, UK) is a nutrition software package used for the analysis of food intake records and 24 h recalls. Within its database, WISP contains the GI values of foods based on the International Tables 2002. The aim of the present study is to describe in detail a methodology for adding and amending GI values to the WISP database in a clinical or research setting, using data from the updated International Tables 2008.

Dietary glycemic load is a predictor of age-related hearing loss in older adults

Age-related hearing loss is a frequent disability in older adults and nutrition could play a role in the development of this condition. Carbohydrate nutrition [including dietary glycemic index (GI) and load (GL)] may be linked to hearing loss. We aimed to determine the association between carbohydrate nutrition (including mean dietary GI and GL, and the dietary intakes of carbohydrate and sugar), starch, cereal and total fiber, and age-related hearing loss. The Blue Mountains Hearing Study is a population-based survey of age-related hearing loss (1997-1999 to 2002-2004). Hearing loss was measured in 2956 participants (aged ≥50 y) and was defined as the pure-tone average of frequencies 0.5, 1.0, 2.0, and 4.0 kHz > 25 dB hearing level. Dietary data were collected in a semiquantitative FFQ. A purpose-built database based on Australian GI values was used to calculate the mean GI. A higher mean dietary GI was associated with an increased prevalence of any hearing loss, comparing quintiles 1 (lowest) and 5 (highest), [multivariable-adjusted odds ratio = 1.41 (95% CI = 1.01-1.97)]. Participants in the highest quartile of mean dietary GL intake compared with those in the lowest quartile had a 76% greater risk of developing incident hearing loss (P-trend = 0.04). Higher carbohydrate and sugar intakes were associated with incident hearing loss (P-trend = 0.03 and P-trend = 0.05, respectively). In summary, a high-GL diet was a predictor of incident hearing loss, as was higher intake of total carbohydrate. Hence, high postprandial glycemia might be a potential underlying biological mechanism in the development of age-related hearing loss.

Degree of habitual mastication seems to contribute to interindividual variations in the glycemic response to rice but not to spaghetti

Previous work by our group showed that the degree of particle breakdown of rice during mastication affects in vitro glycemic potency. The objective of this study was to confirm these in vitro findings in an in vivo model. We hypothesized that the degree of habitual mastication will influence individuals' in vivo blood glucose response (glycemic response, or GR) to carbohydrate foods. Eleven participants came in on six nonconsecutive days to the laboratory and evaluated 2 test foods (rice and spaghetti). Their GR was measured for the subsequent 120 minutes. Mastication parameters were determined using surface electrode electromyography. The particle size distribution of individuals' masticated food was also determined. The intraindividual number of chews per mouthful did not significantly differ for rice and spaghetti (29.9 and 33, respectively), although masticated particle size distribution did (P < .001). Significant correlations between the degree of breakdown during mastication and the GR were observed for rice, but none for spaghetti. Individuals' peak GR (at 45 minutes) correlated significantly with the particles size distribution of their masticated rice (P = .002), and also with the total incremental area under the curve for the GR (r = -0.72; P = .012) and the incremental area under the curve for the first 45 (r = -0.74; P = .010) and 60 minutes (r = 0.73; P = .010) postconsumption. The results suggest that individual differences in mastication may be one of the causes for interindividual differences in the GR to rice but not spaghetti.

Effect of carbohydrate digestibility on appetite and its relationship to postprandial blood glucose and insulin levels

BACKGROUND/OBJECTIVES

'Slowly digestible' carbohydrates have been claimed to reduce appetite through their effects on postprandial glucose and insulin levels, but literature is inconsistent. The inconsistencies between studies might be explained by factors other than glycemic effects per se, for example, nutritional or physical properties. We tested this possibility by examining postprandial glucose, insulin and appetite responses to drinks differing only in rate and extent of digestibility of carbohydrates. This was accomplished by comparing different glucose polymers: maltodextrin (rapidly digestible) versus medium-chain pullulan (slowly but completely digestible) versus long-chain pullulan (indigestible).

SUBJECTS/METHODS

In a randomized double-blind balanced crossover design, 35 subjects received drinks with 15 g test carbohydrate polymers. Key outcome measures were appetite scores, digestibility (in vitro test and breath hydrogen), and (in a subset) glucose and insulin levels.

RESULTS

Digestibility, glucose and insulin data confirmed the rapid, slow and nondigestible nature of the test carbohydrates. Despite its low digestibility, only long-chain pullulan reduced appetite compared with the maltodextrin control, whereas the medium-chain pullulan did not.

CONCLUSIONS

We conclude that glycemic responses per se have minimal effects on appetite, when tested in products differing in only carbohydrate digestibility rate and extent.

Urinary C-peptide excretion: a novel alternate measure of insulin sensitivity in physiological conditions

Insulin sensitivity (IS) is measured by the euglycemic-hyperinsulinemic clamp under a nonphysiological condition. Daily C-peptide urinary excretion may be a physiological index of IS, because C-peptide is co-secreted with insulin as a function of nutrient intake and IS. The amount of (2)H(2)O released from glycolytic glucose metabolism after [6,6-(2)H(2)]-glucose ingestion was recently proposed as a physiological measure of IS. We compared these IS surrogates to the gold standard (euglycemic-hyperinsulinemic clamp). Thirty (15 male/15 female) sedentary, nondiabetic participants (27.2 +/- 4.0 (s.d.) kg/m(2), 35 +/- 12 years) were admitted for 3 days to our in-patient unit. After a 10-h fast, they received 60 g of glucose and 15 g of [6,6-(2)H(2)]-glucose. Before glucose ingestion and hourly thereafter for 4 h, plasma glucose and insulin concentrations, and plasma deuterium enrichment were determined. Plasma (2)H(2)O production divided by insulin response was used as the glycolytic index. On day 2, subjects spent 23 h in a metabolic chamber (eucaloric diet, 50% carbohydrate, 30% fat). Urinary C-peptide excretion was divided by energy intake yielding the C-peptide to energy intake ratio (CPEP/EI). After leaving the chamber (day 3, 10-h fast), IS was measured by a 2-h clamp (120 mU/m(2)/min). Average IS (clamp) was 7.3 +/- 2.6 mg glucose/kg estimated metabolic body size/min (range: 3.6-13.2). These values were inversely correlated with CPEP/EI (r = -0.62; P < 0.01) and positively with the glycolytic rate (r = 0.60; P < 0.01). In nondiabetic subjects, two novel estimates of IS--daily urinary C-peptide urinary excretion and glycolytic rate during an oral glucose tolerance test --were related to IS by a clamp.

Glycaemic indices of three Sri Lankan wheat bread varieties and a bread-lentil meal

The glycaemic index (GI) concept ranks individual foods and mixed meals according to the blood glucose response. Low-GI foods with a slow and prolonged glycaemic response are beneficial for diabetic people, and several advantages have been suggested also for non-diabetic individuals. The recent investigations imply an increasing prevalence of diabetes mellitus in Sri Lanka. Thus, the present study was designed primarily to determine the glycaemic indices of some bread varieties in Sri Lanka as bread has become a staple diet among most of the urban people. A second objective was to observe the effects of macronutrients and physicochemical properties of starch on GI. Glycaemic responses were estimated according to FAO/WHO guidelines and both glucose and white bread were used as standards. Non-diabetic individuals aged 22-30 years (n=10) participated in the study. The test meals included white sliced bread, wholemeal bread, ordinary white bread and a mixed meal of wholemeal bread with lentil curry. The GI values (+/-standard error of the mean) of the meals were 77+/-6, 77+/-6, 80+/-4, 61+/-6, respectively (with glucose as the standard). The GI values of the bread varieties or the meal did not differ significantly (P >0.05). However, the meal can be categorized as a medium-GI food while the other bread varieties belong to the high-GI food group. A significant negative correlation was obtained with protein (P=0.042) and fat (P=0.039) contents of the food items and GI. Although the GI values of the foods are not significantly different, the inclusion of lentils caused the GI to decrease from a high-GI category to a medium-GI category. According to the present study, a ratio of 1.36 can be used to interconvert the GI values obtained with the two standards.

The influence of maternal glycaemia and dietary glycaemic index on pregnancy outcome in healthy mothers

Infant birth weight has increased in Ireland in recent years along with levels of childhood overweight and obesity. The present article reviews the current literature on maternal glycaemia and the role of the dietary glycaemic index (GI) and its impact on pregnancy outcomes. It is known that maternal weight and weight gain significantly influence infant birth weight. Fetal macrosomia (birth weight >4000 g) is associated with an increased risk of perinatal trauma to both mother and infant. Furthermore, macrosomic infants have greater risk of being obese in childhood, adolescence and adulthood compared to normal-sized infants. There is evidence that there is a direct relationship between maternal blood glucose levels during pregnancy and fetal growth and size at birth, even when maternal blood glucose levels are within their normal range. Thus, maintaining blood glucose concentrations within normal parameters during pregnancy may reduce the incidence of fetal macrosomia. Maternal diet, and particularly its carbohydrate (CHO) type and content, influences maternal blood glucose concentrations. However, different CHO foods produce different glycaemic responses. The GI was conceived by Jenkins in 1981 as a method for assessing the glycaemic responses of different CHO. Data from clinical studies in healthy pregnant women have documented that consuming a low-GI diet during pregnancy reduces peaks in postprandial glucose levels and normalises infant birth weight. Pregnancy is a physiological condition where the GI may be of particular relevance as glucose is the primary fuel for fetal growth.

Dietary fiber, magnesium, and glycemic load alter risk of type 2 diabetes in a multiethnic cohort in Hawaii

The influence of dietary fiber, magnesium (Mg), and glycemic load (GL) on diabetes was examined in the Hawaii component of the Multiethnic Cohort. The 75,512 Caucasian, Japanese American, and Native Hawaiian participants aged 45-75 y at baseline completed a FFQ. After 14 y of follow-up, 8587 incident diabetes cases were identified through self-reports and health plans. We applied Cox regression stratified for age at cohort entry and adjusted for ethnicity, BMI, physical activity, education, and total energy with further stratifications by sex and ethnicity. When comparing extreme quintiles, total fiber intake was associated with reduced diabetes risk among all men [hazard ratio (HR): 0.75; 95% CI: 0.67, 0.84; P-trend < 0.001) and women (HR: 0.95; 95% CI: 0.85, 1.06; P-trend = 0.05). High intake of grain fiber reduced diabetes risk significantly by 10% in men and women. High vegetable fiber intake lowered risk by 22% in all men but not women. Mg intake reduced risk (HR = 0.77 and 0.84 for men and women, respectively) and, due to its strong correlation with fiber (r = 0.83; P < 0.001), may explain the protective effect of fiber. The top GL quintile was associated with a significantly elevated diabetes incidence in Caucasian men and in all women except Japanese Americans. Overall, several associations were more pronounced in Caucasians than in the other groups. These findings suggest that protection against diabetes can be achieved through food choices after taking into account body weight, but, due to differences in commonly consumed foods, risk estimates may differ by ethnic group.

The hypoglycemic effect of fat and protein is not attenuated by insulin resistance

BACKGROUND

The glucose-lowering effect of fat and protein is attenuated or absent in diabetic patients, which suggests that the same may occur in insulin-resistant subjects without diabetes.

OBJECTIVE

The objective was to determine whether the postprandial metabolic responses elicited by fat and protein were influenced by the insulin sensitivity of the subjects and whether fat and protein modulate glucose responses through different mechanisms.

DESIGN

Healthy nondiabetic subjects aged 18-45 y took 50 g oral glucose with 0-30-g doses of canola oil and whey protein on 11 separate mornings after fasting overnight. The subjects were classified into 3 fasting serum insulin (FSI) groups: FSI < 40 pmol/L (n = 9), 40 < or = FSI < 70 pmol/L (n = 8), and FSI > or = 70 pmol/L (n = 8). The relative glycemic response was expressed as the incremental area under the curve (AUC) after each test meal divided by the mean AUC of the glucose control in each subject.

RESULTS

Protein significantly decreased glucose (P < 0.0001) and hepatic insulin extraction (P <0.0001) and increased insulin (P < 0.0001) and glucagon-like peptide 1 (P = 0.004); however, protein had no significant effect on C-peptide (P = 0.69) or on the insulin secretion rate (P = 0.13). No significant FSI x fat (P = 0.19) or FSI x protein (P = 0.08) interaction effects on glucose AUC were observed. In addition, the changes in relative glycemic response per gram of fat (r = -0.05, P = 0.82) or protein (r = -0.08, P = 0.70) were not related to FSI.

CONCLUSIONS

The hypoglycemic effect of fat and protein was not blunted by insulin resistance. Protein increased insulin but had no effect on C-peptide or the insulin secretion rate, which suggests decreased hepatic insulin extraction or increased C-peptide clearance.

Effects of low- and high-glycemic index/glycemic load diets on coronary heart disease risk factors in overweight/obese men

Chronic insulin resistance contributes to subclinical inflammation, thrombosis/impaired fibrinolysis, and dyslipidemia. The effect of dietary carbohydrate, specifically of glycemic index (GI) and glycemic load (GL), on established and emerging coronary heart disease risk factors has not been elucidated fully. We conducted a randomized crossover feeding study of matched diets differing only in GI and GL in 24 overweight or obese but otherwise healthy men to investigate the effects on insulin sensitivity, inflammation, thrombosis/fibrinolysis, lipoproteins/lipids, and body composition. All meals for the high- and low-GI/GL diets were prepared in a metabolic kitchen. Each participant consumed both diets in random order for 4 weeks each, with a 4-week washout period in between. Each participant underwent a frequently sampled intravenous glucose tolerance test for assessment of insulin sensitivity; blood sampling for the measurement of inflammatory markers, coagulation factors, and lipoproteins/lipids; and dual-energy x-ray absorptiometry for assessment of body composition at the beginning and end of each dietary period. There were no statistically significant differences in glucose metabolism factors, inflammatory markers, or coagulation factors after 4 weeks on the high- and low-GI/GL diets. The high-GI/GL diet resulted in a slightly greater reduction in fat mass and a slightly greater increase in lean mass compared with the low-GI/GL diet. The high-GI/GL diet resulted in significant, but unexpected, reductions in total and low-density lipoprotein cholesterol, whereas high-density lipoprotein cholesterol concentration was significantly reduced on the high-GI/GL diet compared with the low-GI/GL diet. Overall, high- and low-GI/GL diets of 4 weeks' duration had no consistent effects on coronary heart disease risk factors in this group of overweight/obese men.

Effects of a fibre-enriched milk drink on insulin and glucose levels in healthy subjects

Background

The glycaemic response to foods is dependent on the quality and content of carbohydrates. Carbohydrates in the form of dietary fibre have favourable effects on insulin and glucose metabolism and may help to control energy intake. Dairy products have a relatively low carbohydrate content, and most of the carbohydrate is in the form of lactose which causes gastrointestinal symptoms in part of the population. In order to avoid these symptoms, dairy products can be replaced with lactose-free dairy products which are on the market in many parts of the world. However, the effects of lactose-free products on insulin and glucose metabolism have not been studied.

Methods

In the present study, we investigated the effects of 1) a lactose-free milk drink, 2) a novel fibre-enriched, fat- and lactose-free milk drink and 3) normal fat-free milk on serum glucose and insulin levels and satiety using a randomized block design. Following an overnight fast, 26 healthy volunteers ingested 200 ml of one of these drinks on three non-consecutive days. Insulin and glucose levels and subjective satiety ratings were measured before the ingestion of the milk product and 20, 40, 60, 120 and 180 minutes after ingestion. The responses were calculated as the area under the curve subtracted by the baseline value (AUC minus baseline).

Results

The insulin response was significantly lower for the fibre-enriched milk drink than it was for the other milk products (AUC, P = 0.007). There were no differences in the response for glucose or in the AUC for the subjective satiety ratings between the studied milk products.

Conclusion

The present results suggest that this novel milk drink could have positive effects on insulin response.