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

BACKGROUND AND AIMS: The positive and negative health effects of dietary carbohydrates are of interest to both researchers and consumers. METHODS: International experts on carbohydrate research held a scientific summit in Stresa, Italy, in June 2013 to discuss controversies surrounding the utility of the glycemic index (GI), glycemic load (GL) and glycemic response (GR). RESULTS: The outcome was a scientific consensus statement which recognized the importance of postprandial glycemia in overall health, and the GI as a valid and reproducible method of classifying carbohydrate foods for this purpose. There was consensus that diets low in GI and GL were relevant to the prevention and management of diabetes and coronary heart disease, and probably obesity. Moderate to weak associations were observed for selected cancers. The group affirmed that diets low in GI and GL should always be considered in the context of diets otherwise understood as healthy, complementing additional ways of characterizing carbohydrate foods, such as fiber and whole grain content. Diets of low GI and GL were considered particularly important in individuals with insulin resistance. CONCLUSIONS: Given the high prevalence of diabetes and pre-diabetes worldwide and the consistency of the scientific evidence reviewed, the expert panel confirmed an urgent need to communicate information on GI and GL to the general public and health professionals, through channels such as national dietary guidelines, food composition tables and food labels.

Evidence for greater production of colonic short-chain fatty acids in overweight than lean humans.

BACKGROUND: Short-chain fatty acids (SCFA) are produced by colonic microbiota from dietary carbohydrates and proteins that reach the colon. It has been suggested that SCFA may promote obesity via increased colonic energy availability. Recent studies suggest obese humans have higher faecal SCFA than lean, but it is unclear whether this difference is due to increased SCFA production or reduced absorption. OBJECTIVES: To compare rectal SCFA absorption, dietary intake and faecal microbial profile in lean (LN) versus overweight and obese (OWO) individuals. DESIGN: Eleven LN and eleven OWO individuals completed a 3-day diet record, provided a fresh faecal sample and had SCFA absorption measured using the rectal dialysis bag method. The procedures were repeated after 2 weeks. RESULTS: Age-adjusted faecal SCFA concentration was significantly higher in OWO than LN individuals (81.3±7.4 vs 64.1±10.4 mmol kg(-1), P=0.023). SCFA absorption (24.4±0.8% vs 24.7±1.2%, respectively, P=0.787) and dietary intakes were similar between the groups, except for a higher fat intake in OWO individuals. However, fat intake did not correlate with SCFAs or bacterial abundance. OWO individuals had higher relative Firmicutes abundance (83.1±4.1 vs 69.5±5.8%, respectively, P=0.008) and a higher Firmicutes:Bacteriodetes ratio (P=0.023) than LN individuals. There was a positive correlation between Firmicutes and faecal SCFA within the whole group (r=0.507, P=0.044), with a stronger correlation after adjusting for available carbohydrate (r=0.615, P=0.005). CONCLUSIONS: The higher faecal SCFA in OWO individuals is not because of differences in SCFA absorption or diet. Our results are consistent with the hypothesis that OWO individuals produce more colonic SCFA than LN individuals because of differences in colonic microbiota. However, further studies are needed to prove this.

Altering source or amount of dietary carbohydrate has acute and chronic effects on postprandial glucose and triglycerides in type 2 diabetes: Canadian trial of Carbohydrates in Diabetes (CCD).

BACKGROUND AND AIMS: Nutrition recommendations for type 2 diabetes (T2DM) are partly guided by the postprandial responses elicited by diets varying in carbohydrate (CHO). We aimed to explore whether long-term changes in postprandial responses on low-glycemic-index (GI) or low-CHO diets were due to acute or chronic effects in T2DM. METHODS AND RESULTS: Subjects with diet-alone-treated T2DM were randomly assigned to high-CHO/high-GI (H), high-CHO/low-GI (L), or low-CHO/high-monounsaturated-fat (M) diets for 12-months. At week-0 (Baseline) postprandial responses after H-meals (55% CHO, GI = 61) were measured from 0800 h to 1600 h. After 12 mo subjects were randomly assigned to H-meals or study diet meals (L, 57% CHO, GI = 50; M, 44% CHO, GI = 61). This yielded 5 groups: H diet with H-meals (HH, n = 34); L diet with H- (LH, n = 17) or L-meals (LL, n = 16); and M diet with H- (MH, n = 18) or M meals (MM, n = 19). Postprandial glucose fluctuations were lower in LL than all other groups (p < 0.001). Changes in postprandial-triglycerides differed among groups (p < 0.001). After 12 mo in HH and MM both fasting- and postprandial-triglycerides were similar to Baseline while in MH postprandial-triglycerides were significantly higher than at Baseline (p = 0.028). In LH, triglycerides were consistently (0.18-0.34 mmol/L) higher than Baseline throughout the day, while in LL the difference from Baseline varied across the day from 0.04 to 0.36 mmol/L (p < 0.001). CONCLUSION: Low-GI and low-CHO diets have both acute and chronic effects on postprandial glucose and triglycerides in T2DM subjects. Thus, the composition of the acute test-meal and the habitual diet should be considered when interpreting the nutritional implications of different postprandial responses.

Utility of non-high-density lipoprotein cholesterol in assessing incident type 2 diabetes risk.

AIMS: Traditional lipid indices have been associated with type 2 diabetes, but limited data are available regarding non-high-density lipoprotein (non-HDL) cholesterol. In view of recent guidelines for the clinical management of dyslipidemia recommending the monitoring of non-HDL cholesterol as a secondary target after achieving the low-density lipoprotein (LDL) cholesterol goal, we aimed to assess the association of non-HDL cholesterol with incident type 2 diabetes and compare its utility as a risk predictor with traditional lipid variables in Aboriginal Canadians. METHODS: Of 606 diabetes-free participants at baseline, 540 (89.1%) returned for 10-year follow-up assessments. Baseline anthropometry, blood pressure, fasting insulin and serum lipids were measured. Fasting and 2-h postload glucose were obtained at baseline and follow-up to determine the incidence of type 2 diabetes. RESULTS: The cumulative incidence of type 2 diabetes was 17.5%. Higher non-HDL cholesterol, total-to-HDL cholesterol ratio, apolipoprotein B, triglyceride and LDL cholesterol and lower HDL cholesterol concentrations were individually associated with incident type 2 diabetes in univariate analyses (all p < 0.05). Non-HDL cholesterol was a superior determinant of incident diabetes compared with LDL cholesterol (comparing C-statistics of univariate models p = 0.01) or HDL cholesterol (p = 0.004). With multivariate adjustment including waist circumference, non-HDL cholesterol remained associated with incident diabetes [odds ratio (OR) 1.42 (95% confidence interval, CI 1.07-1.88)], while LDL cholesterol and HDL cholesterol became non-significant. CONCLUSIONS: Non-HDL cholesterol was associated with incident type 2 diabetes and was superior to LDL cholesterol as a risk predictor in this population. Further studies are required to establish the utility of non-HDL cholesterol in non-Aboriginal populations.

Sugars and fat have different effects on postprandial glucose responses in normal and type 1 diabetic subjects.

BACKGROUND AND AIMS: We aimed to determine the effects on glycemic responses and potential risk of hypoglycaemia in type 1 diabetic subjects of replacing half the starch in a meal with sugars, and of adding fat to the low-sugar and high-sugar meals. METHODS AND RESULTS: We studied overnight fasted subjects with type 1 diabetes (n = 11) and age-, BMI- and ethnicity-matched controls (n = 11) using a 2 × 2 factorial design. The low-sugar/low-fat meal was 110 g white-bread. In the high-sugar/low-fat meal half the white-bread starch replaced by sugars (jam and orange juice). The high-fat meals consisted of the low-fat meals plus 20 g fat (margarine). The significance of the main effects of sugars and fat and the sugar × fat, group × sugar and group × fat interactions were determined by ANOVA. In control and diabetic subjects, respectively, high-sugar significantly reduced time to peak rise by 13% (P = 0.004) and 32% (P = 0.004; group × sugar: P = 0.01) and increased peak rise by 14% and 10% (ns). Adding fat increased time to peak rise by 17-19% in both groups (P = 0.003), reduced peak rise by 31% in normal (P < 0.001) but increased peak rise in diabetic subjects by 3% (ns) (group × fat: P = 0.022). Blood glucose nadir and occurrence of hypoglycaemia were similar among the 4 meals. CONCLUSIONS: In type 1 diabetes, insulin adjustment to avoid hypoglycemia may be useful for meals in which the proportion of carbohydrate absorbed as glucose is <0.75, however the precise level which increases hypoglycaemic risk requires further research. The results suggest that people with type 1 diabetes should not be advised to add fat to meals to reduce glycemic responses.

Effects of sucromalt on postprandial responses in human subjects.

BACKGROUND/OBJECTIVE: To compare postprandial responses elicited by sucromalt, a nutritive sweetener produced by treating a blend of sucrose and corn syrup with an enzyme from Leuconostoc mesenteroides, with those after 42% of high-fructose corn syrup (HFCS), and to see if the reduced responses after sucromalt could be accounted for by carbohydrate malabsorption. SUBJECT AND METHODS: Three experiments were performed in separate groups of normal subjects studied after overnight fasts using double-blind, randomized, cross-over designs. HFCS was used as the control because it contained a similar amount of fructose as sucromalt. Experiment 1 (n = 10): plasma glucose and insulin were measured after 50 g sucromalt and 50 g HFCS. Experiment 2 (n = 10): metabolic profiles were measured after 80 g HFCS, 80 g sucromalt or 56 g fructose/glucose blend plus 24 g inulin. Experiment 3 (n = 20): the glycaemic indices of sucromalt and HFCS were determined. RESULTS: Mean glucose and insulin responses after sucromalt were 66 and 62%, respectively, of those after HFCS (P < 0.05). The inulin treatment, used to mimic the effects of carbohydrate malabsorption, elicited higher breath hydrogen (H2), lower glucose and insulin responses, and a significantly earlier rise in serum free fatty acids (FFA) than those of HFCS (all P < 0.05). Sucromalt elicited no rise in breath H2, and delayed falls in glucose and insulin, and a delayed rebound of FFA compared to HFCS (all P < 0.05). CONCLUSIONS: The reduced glucose and insulin responses elicited by sucromalt are not explained by malabsorption and are more likely related to differences in either rate of digestion and absorption or postabsorptive handling by body.

Acute increases in serum colonic short-chain fatty acids elicited by inulin do not increase GLP-1 or PYY responses but may reduce ghrelin in lean and overweight humans.

BACKGROUND: Colonic fermentation of dietary fibre to short-chain fatty acids (SCFA) influences appetite hormone secretion in animals, but SCFA production is excessive in obese animals. This suggests there may be resistance to the effect of SCFA on appetite hormones in obesity. OBJECTIVES: To determine the effects of inulin (IN) and resistant starch (RS) on postprandial SCFA, and gut hormone (glucagon-like peptide (GLP-1), peptide-tyrosine-tyrosine (PYY) and ghrelin) responses in healthy overweight/obese (OWO) vs lean (LN) humans. SUBJECTS/METHODS: Overnight-fasted participants (13 OWO and 12 LN) consumed 300 ml water containing 75 g glucose (GLU) as control or 75 g GLU plus 24 g IN, or 28.2 g RS using a randomised, single-blind, cross-over design. Blood for appetite hormones and SCFA was collected at intervals over 6 h. A standard lunch was served 4 h after the test drink. RESULTS: Relative to GLU, IN, but not RS, significantly increased SCFA areas under the curve (AUC) from 4-6 h (AUC4-6). Neither IN nor RS affected GLP-1 or PYY-AUC4-6. Although neither IN nor RS reduced ghrelin-AUC4-6 compared with GLU, ghrelin at 6 h after IN was significantly lower than that after GLU (P<0.05). After IN, relative to GLU, the changes in SCFA-AUC4-6 were negatively related to the changes in ghrelin-AUC4-6 (P=0.017). SCFA and hormone responses did not differ significantly between LN and OWO. CONCLUSIONS: Acute increases in colonic SCFA do not affect GLP-1 or PYY responses in LN or OWO subjects, but may reduce ghrelin. The results do not support the hypothesis that SCFA acutely stimulate PYY and GLP-1 secretion; however, a longer adaptation to increased colonic fermentation or a larger sample size may yield different results.

The acute effects of inulin and resistant starch on postprandial serum short-chain fatty acids and second-meal glycemic response in lean and overweight humans.

BACKGROUND/OBJECTIVES: Colonic fermentation of dietary fiber to short-chain fatty acids (SCFA) may protect against obesity and diabetes, but excess production of colonic SCFA has been implicated in the promotion of obesity. We aimed to compare the effects of two fermentable fibers on postprandial SCFA and second-meal glycemic response in healthy overweight or obese (OWO) vs lean (LN) participants. SUBJECTS/METHODS: Using a randomized crossover design, 13 OWO and 12 LN overnight fasted participants were studied for 6 h on three separate days after consuming 300 ml water containing 75 g glucose (GLU) as control or with 24 g inulin (IN) or 28 g resistant starch (RS). A standard lunch was served 4 h after the test drink. RESULTS: Within the entire group, compared with control, IN significantly increased serum SCFA (P<0.001) but had no effect on free-fatty acids (FFA) or second-meal glucose and insulin responses. In contrast, RS had no significant effect on SCFA but reduced FFA rebound (P<0.001) and second-meal glucose (P=0.002) and insulin responses (P=0.024). OWO had similar postprandial serum SCFA and glucose concentrations but significantly greater insulin and FFA than LN. However, the effects of IN and RS on SCFA, glucose, insulin and FFA responses were similar in LN and OWO. CONCLUSIONS: RS has favorable second-meal effects, likely related to changes in FFA rather than SCFA concentrations. However, a longer study may be needed to demonstrate an effect of RS on SCFA. We found no evidence that acute increases in SCFA after IN reduce glycemic responses in humans, and we were unable to detect a significant difference in SCFA responses between OWO vs LN subjects.

Metabolic effects of reducing rate of glucose ingestion by single bolus versus continuous sipping.

Modifying the rate of absorption has been proposed as a therapeutic principle of specific relevance to diabetes. To demonstrate clearly the metabolic benefits that might result from reducing the rate of nutrient delivery, nine healthy volunteers took 50 g glucose in 700 ml water on two occasions: over 5-10 min (bolus) and at a constant rate over 3.5 h (sipping). Despite similar 4-h blood glucose areas, large reductions were seen in serum insulin (54 +/- 10%, P less than 0.001) and C-peptide (47 +/- 12%, P less than 0.01) areas after sipping, together with lower gastric inhibitory polypeptide and enteroglucagon levels and urinary catecholamine output. There was also prolonged suppression of plasma glucagon, growth hormone, and free-fatty acid (FFA) levels after sipping, whereas these levels rose 3-4 h after the glucose bolus. An intravenous glucose tolerance test at 4 h demonstrated a 48 +/- 10% (P less than 0.01) more rapid decline in blood glucose (Kg) after sipping than after the bolus. Furthermore, FFA and total branched-chain amino acid levels as additional markers of insulin action were lower over this period despite similar absolute levels of insulin and C-peptide. These findings indicate that prolonging the rate of glucose absorption enhances insulin economy and glucose disposal.

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.

The glycemic index: flogging a dead horse?

The glycemic index (GI) is a classification of foods based on their blood glucose-raising potential. The American Diabetes Association (ADA) has questioned the clinical utility of the GI and recommends that priority should be given to the amount rather than the source of carbohydrate. Some have interpreted this to mean that all carbohydrates have a nearly equal impact on blood sugar, and some feel that the GI is now a dead issue. Nevertheless, the reasons for questioning the clinical utility of the GI are unfounded because of the following: 1) they are based on studies of single test meals, which provide insufficient evidence on which to base dietary recommendations; 2) they are based on a faulty interpretation of the studies actually cited as evidence; 3) they take no account of better designed studies showing that the GI does apply in mixed meals; and 4) they take no account of studies showing that a low-GI diet improves overall blood glucose control in persons with diabetes. The GI is a valid and potentially useful concept, but is also deceptively complex. There are a number of unresolved problems and unanswered questions, and the appropriate place for the GI in patient education is not known. However, progress cannot be made without balance and objectivity.

Starchy foods and glycemic index.

Different starchy foods produce different glycemic responses when fed individually, and there is some evidence that this also applies in the context of the mixed meal. A major reason appears to relate to the rate at which the foods are digested and the factors influencing this. A similar ranking in terms of glycemic response to specific foods is seen independent of the carbohydrate tolerance status of the groups tested. Potentially clinically useful starchy foods producing relatively flat glycemic responses have been identified. Many of these are considered ethnic or traditional and include legumes; pasta; grains such as barley, parboiled rice, and bulgur (cracked wheat); and whole-grain breads such as pumpernickel. Specific incorporation of these foods into diets has been associated with reductions in low-density lipoprotein cholesterol and triglyceride levels in hyperlipidemia and with improved blood glucose control in insulin-dependent diabetic patients. To facilitate identification of such foods, it has been suggested that the glycemic response should be indexed to a standard (e.g., white bread) to allow comparisons to be made between the glycemic index of foods tested in different groups of subjects. The scope of application of this principle is subject to further investigation. It may be used to expand the range of possibly useful starchy foods for trial in the diets of diabetic patients.

Physiological modulation of plasma free fatty acid concentrations by diet. Metabolic implications in nondiabetic subjects.

OBJECTIVE: To determine the effect of varying the amount of carbohydrate and glycemic index (GI) of breakfast test meals on plasma free fatty acid (FFA) responses of nondiabetic subjects and to see whether the glycemic response at lunch was related to the plasma FFA response to breakfast. RESEARCH DESIGN AND METHODS: We studied eight subjects over a 6-h period on four separate occasions using a randomized Latin-square design. They received isocaloric breakfast test meals that were either high (84 g) or low (41 g) in carbohydrate and had either a high (approximately 100) or a low (approximately 70) GI, followed by a standard lunch 4 h later. RESULTS: The initial fall in plasma FFAs after breakfast was similar for all four test meals, but the extent of rebound differed significantly. The mean plasma FFA concentration just before the start of lunch (4 h) was highest after the low-GI, low-carbohydrate breakfast (418 +/- 42 mumol/l), followed by high-GI, low-carbohydrate (277 +/- 48 mumol/l), high-GI, high carbohydrate (227 +/- 32 mumol/l), and low-GI, high-carbohydrate (149 +/- 23 mumol/l) (P < 0.01). The concentration of plasma FFAs at 4 h was directly related to the total area under the glycemic response curve to lunch (r = 0.691, n = 32, P < 0.0001). CONCLUSIONS: In nondiabetic subjects, the type and amount of carbohydrate eaten at breakfast influences the plasma glucose, insulin, and FFA responses to breakfast and also affects the glucose, insulin, and FFA responses to a subsequent standard lunch. The glycemic responses after lunch were closely related to the plasma FFA concentration 4 h after breakfast, which we speculate is due to the inhibitory effect of FFAs on insulin action.

Glycemic response to wheat products: reduced response to pasta but no effect of fiber.

The blood glucose response to feeding 50-g carbohydrate portions of white and wholemeal bread and white spaghetti was studied in a group of nine diabetic subjects. Blood glucose rises after white and wholemeal bread were identical, but the response after spaghetti was markedly reduced. These results emphasize that food form rather than fiber may be important in determining the glycemic response and that pasta may be a useful source of carbohydrate in the diabetic diet.

Glycemic response to pasta: effect of surface area, degree of cooking, and protein enrichment.

To see whether food form, the degree of cooking, or protein enrichment affected the glycemic response to pasta, we gave test-meal breakfasts to 13 diabetic patients. Macaroni had a significantly greater glycemic index (GI) (68 +/- 8) than spaghetti (45 +/- 6, P less than .01); the GI of star pastina was intermediate (54 +/- 6). The GI of spaghetti was not significantly affected by cooking for 5 or 15 min (45 +/- 6 and 46 +/- 5, respectively), or by protein enrichment (38 +/- 4). The GI of spaghetti was similar in 11 non-insulin-dependent and 6 insulin-dependent diabetic patients (49 +/- 7 compared with 57 +/- 8). We conclude that different types of pasta may produce different glycemic responses but that these are not necessarily related to differences in cooking or surface area.

Positive methane-producing status associated with increased serum cholesterol in subjects with impaired glucose tolerance.

OBJECTIVE: To determine if those who produce methane (i.e., have presence of methane in breath) have higher serum cholesterol than those who do not produce methane in subjects with impaired glucose tolerance (IGT). RESEARCH DESIGN AND METHODS: We measured breath gases and fasting serum total and high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels in 21 subjects with IGT. RESULTS: The 11 methane-producers were well matched to the 10 non-methane-producers for age, sex, and body mass index. Methane-producers had higher fasting serum total (6.5 +/- 0.3 vs. 5.5 +/- 0.2 mmol/l; P < 0.02) and low-density lipoprotein (4.3 +/- 0.3 vs. 3.4 +/- 0.2 mmol/l; P < 0.05) cholesterol concentrations with no difference in TG or HDL levels. CONCLUSIONS: The results suggest that in subjects with IGT, positive methane-producing status may be associated with increased serum cholesterol levels.

Beneficial effect of low-glycemic index diet in overweight NIDDM subjects.

OBJECTIVE: To determine whether low-glycemic index (GI) diets have clinical utility in overweight patients with non-insulin-dependent diabetes mellitus (NIDDM). RESEARCH DESIGN AND METHODS: Six patients with NIDDM were studied on both high- and low-GI diets of 6-wk duration with metabolic diets with a randomized crossover design. Both diets were of similar composition (57% carbohydrate, 23% fat, and 34 g/day dietary fiber), but the low-GI diet had a GI of 58 compared with 86 for the high-GI diet. RESULTS: Small and similar amounts of weight were lost on both diets: 2.5 kg on high-GI diet and 1.8 kg on low-GI diet. On the low-GI diet, the mean level of serum fructosamine, as an index of overall blood glucose control, was lower than on the high-GI diet by 8% (P less than 0.05), and total serum cholesterol was lower by 7% (P less than 0.01). CONCLUSIONS: In overweight patients with NIDDM, reducing diet GI improves overall blood glucose and lipid control.

The effect of acarbose on insulin sensitivity in subjects with impaired glucose tolerance.

OBJECTIVE: To study the effect of acarbose, an alpha-glucosidase inhibitor, on postprandial plasma glucose and insulin and insulin sensitivity in subjects with impaired glucose tolerance (IGT). RESEARCH DESIGN AND METHODS: Subjects with IGT were randomly treated in a double-blind fashion with placebo (n = 10) or acarbose (n = 8) at 100 mg t.i.d. for 4 months. All subjects were submitted before randomization and at the end of the study to a standardized breakfast and a 12-h daytime plasma glucose and plasma insulin profile, and insulin sensitivity was measured as steady-state plasma glucose (SSPG) using the insulin suppression test. RESULTS: While placebo had no effect on postprandial plasma glucose and plasma insulin incremental area under the curve (AUC) (3.03 +/- 0.5 vs. 3.76 +/- 0.6 mmol.h-1.l-1, P = NS; 1,488 +/- 229 vs. 1,609 +/- 253 pmol.h-1.l-1, P = NS), acarbose resulted in a significant reduction for both glucose (1.44 +/- 0.3 vs. 4.45 +/- 0.9 mmol.h-1.l-1, P = 0.002) and insulin (626.7 +/- 104.3 vs. 1,338.3 +/- 220.5 pmol.h-1.l-1, P = 0.003). The reduction in 12-h plasma glucose and insulin AUC on acarbose (11.2 +/- 2.1 mmol.h-1.l-1 and 7.5 +/- 0.7 nmol.h-1.l-1) was significantly greater than that on placebo (4.0 +/- 1.6 mmol.h-1.l-1 and 0.8 +/- 0.4 nmol.h-1.l-1) (P = 0.014 and 0.041). While SSPG was not affected by placebo (13.9 +/- 0.4 vs. 13.8 +/- 0.3 mmol/l; P = NS), it was significantly improved by acarbose (10.9 +/- 1.4 vs. 13.1 +/- 1.5 mmol/l, P < 0.004) and was also significantly different from placebo at 4 months (P < 0.02). CONCLUSIONS: It is concluded that in subjects with IGT, acarbose treatment decreases postprandial plasma glucose and insulin and improves insulin sensitivity. Acarbose may therefore be potentially useful to prevent the progression of IGT to NIDDM.

No relationship between carbohydrate intake and effect of acarbose on HbA1c or gastrointestinal symptoms in type 2 diabetic subjects consuming 30-60% of energy from carbohydrate.

OBJECTIVE: To determine the relationship between carbohydrate intake and the effect of acarbose on HbA1c in subjects with type 2 diabetes treated with acarbose alone, acarbose plus sulfonylurea, acarbose plus metformin, or acarbose plus insulin. RESEARCH DESIGN AND METHODS: We conducted a double-blind randomized placebo-controlled study in which subjects with diabetes in four treatment strata (77 on diet alone, 83 treated with metformin, 103 treated with sulfonylurea, and 91 treated with insulin) were randomized to treatment with placebo or acarbose for 12 months. Before randomization, and 3, 6, 9, and 12 months after randomization, fasting blood was obtained for HbA1c, and 3-day diet records were collected. Subjects who completed at least 6 months of acarbose therapy and provided at least three 3-day diet records were included. RESULTS: In the 114 subjects included in this analysis, carbohydrate intake varied from approximately 30-60% of energy There was no significant relationship between carbohydrate intake and change in HbA1c in any of the four treatment strata (diet: n=26, r=0.35, P=0.076; metformin: n=27, r=0.26, P=0.19; sulfonylurea: n=35, r=0.24, P=0.16; insulin: n=25, r=-0.27, P=0.19). In the 80 subjects consuming <50% of energy from carbohydrate, the fall in HbA1c (7.83 +/-0.17% at baseline to 6.72+/-0.13% on acarbose, P < 0.001) was no different from that of the 34 subjects consuming >50% of energy from carbohydrate (7.55+/-0.25% at baseline to 6.66+/-0.23% on acarbose, P < 0.001). There was no difference in carbohydrate intake between those who dropped out of the study because of gastrointestinal side effects and those who did not, and there was no relationship between severity of symptoms and the composition of the diet. CONCLUSIONS: In subjects with type 2 diabetes consuming 30-60% of energy from carbohydrate, the effect of acarbose on HbA1c and gastrointestinal symptoms was not related to carbohydrate intake. Because most people consume at least 30% of energy from carbohydrate, we conclude that no special diet is needed for acarbose to be effective in improving blood glucose control in the treatment of type 2 diabetes.

Variation of postprandial plasma glucose, palatability, and symptoms associated with a standardized mixed test meal versus 75 g oral glucose.

OBJECTIVE: To compare within-subject variability of plasma glucose measured 2 h after a glucose tolerance test (GTT) with that of plasma glucose measured 2 h after administration of a standardized test meal (diabetes screening product [DSP], Ceapro, Edmonton, Alberta, Canada) and to determine the relationship between the two sets of plasma glucose measurements. RESEARCH DESIGN AND METHODS: Plasma glucose and insulin responses of 36 overnight-fasted subjects (10 lean normal, 9 obese normal, 9 with impaired glucose tolerance [IGT], and 8 with mild diabetes) were studied on eight different mornings after they consumed 75 g oral glucose or 50 g carbohydrate from the DSP. Each test meal was repeated four times by each subject. Within-subject coefficients of variation (CVs) (CV = 100 x SD/mean) of plasma glucose concentrations 2 h after administration of the GTT and DSP were compared by repeated measures ANOVA and linear regression analysis. RESULTS: Mean plasma glucose 2 h after administration of the DSP (D) was linearly related to that 2 h after the GTT (G): G = 1.5 x D - 1.6 (r = 0.97, P < 0.0001). The CV of 2-h plasma glucose was significantly lower after administration of the DSP, 10.5 +/- 1.0%, than after the GTT, 12.7 +/- 1.18% (P = 0.025). The effect of test meal on CV differed in different groups of subjects (P = 0.018), with the largest difference found in IGT subjects, in whom the CV after DSP administration was 47% less than after the GTT (P = 0.0005). The DSP was significantly more palatable and produced fewer adverse symptoms than the GTT. CONCLUSIONS: Plasma glucose concentrations measured 2 h after DSP administration are closely related to those measured 2 h after the GTT but are more consistent than the 2-h post-GTT concentrations within the critical IGT range. This finding suggests that measurement of plasma glucose 2 h after administration of the DSP may allow more precise discrimination among normal glucose levels, IGT, and diabetes than measurement of plasma glucose 2 h after the GTT.