AJCN Tufts Nutrition Symposium, Boston & Online Sept 2009
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American Journal of Clinical Nutrition, Vol. 87, No. 1, 114-125, January 2008
© 2008 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

The Canadian Trial of Carbohydrates in Diabetes (CCD), a 1-y controlled trial of low-glycemic-index dietary carbohydrate in type 2 diabetes: no effect on glycated hemoglobin but reduction in C-reactive protein1,2,3

Thomas MS Wolever, Alison L Gibbs, Christine Mehling, Jean-Louis Chiasson, Philip W Connelly, Robert G Josse, Lawrence A Leiter, Pierre Maheux, Remi Rabasa-Lhoret, N Wilson Rodger and Edmond A Ryan

1 From the Departments of Nutritional Sciences (TMSW, CM, RGJ, and LAL) and Statistics (ALG), University of Toronto, Toronto, Canada; the Department of Medicine, St Michael's Hospital, Toronto, Canada (TMSW, PWC, RGJ, and LAL); the Research Center Hôtel-Dieu de Montréal, University of Montréal, Montréal, Canada (J-LC and RR-L); the Department of Medicine, University of Sherbrooke, Québec, Canada (PM); the Department of Medicine, St Joseph's Health Center, University of Western Ontario, London, Canada (NWR); and the Department of Medicine, University of Alberta, Edmonton, Canada (EAR)

See corresponding perspectives on pages 1 and 3.

2 Supported by the Canadian Institutes of Health Research (CIHR-MCT-44205). Key foods were donated by Kellogg Canada Inc, Robin Hood (division of Smucker Foods of Canada Co), HJ Heinz Co, Italpasta Ltd, Uncle Ben's Rice (division of Mars Inc), Kraft Foods Inc, Dainty Foods Inc (division of MRRM Inc), the Almond Board of California, and the National Peanut Board.

3 Reprints not available. Address correspondence to TMS Wolever, Department of Nutritional Sciences, University of Toronto, Toronto, ON M5S 3E2, Canada. E-mail: thomas.wolever{at}utoronto.ca.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: The optimal source and amount of dietary carbohydrate for managing type 2 diabetes (T2DM) are unknown.

Objective: We aimed to compare the effects of altering the glycemic index or the amount of carbohydrate on glycated hemoglobin (HbA1c), plasma glucose, lipids, and C-reactive protein (CRP) in T2DM patients.

Design: Subjects with T2DM managed by diet alone (n = 162) were randomly assigned to receive high-carbohydrate, high-glycemic-index (high-GI), high-carbohydrate, low-glycemic-index (low-GI), or low-carbohydrate, high-monounsaturated-fat (low-CHO) diets for 1 y.

Results: The high-GI, low-GI, and low-CHO diets contained, respectively, 47%, 52%, and 39% of energy as carbohydrate and 31%, 27%, and 40% of energy as fat; they had GIs of 63, 55, and 59, respectively. Body weight and HbA1c did not differ significantly between diets. Fasting glucose was higher (P = 0.041), but 2-h postload glucose was lower (P = 0.010) after 12 mo of the low-GI diet. With the low-GI diet, overall mean triacylglycerol was 12% higher and HDL cholesterol 4% lower than with the low-CHO diet (P < 0.05), but the difference in the ratio of total to HDL cholesterol disappeared by 6 mo (time x diet interaction, P = 0.044). Overall mean CRP with the low-GI diet, 1.95 mg/L, was 30% less than that with the high-GI diet, 2.75 mg/L (P = 0.0078); the concentration with the low-CHO diet, 2.35 mg/L, was intermediate.

Conclusions: In subjects with T2DM managed by diet alone with optimal glycemic control, long-term HbA1c was not affected by altering the GI or the amount of dietary carbohydrate. Differences in total:HDL cholesterol among diets had disappeared by 6 mo. However, because of sustained reductions in postprandial glucose and CRP, a low-GI diet may be preferred for the dietary management of T2DM.

Key Words: Humans • randomized controlled clinical trial • diet • carbohydrate • diabetes • monounsaturated fat


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Pharmacologic treatment of type 2 diabetes (T2DM) to improve glycemic control, control hypertension, and reduce blood lipid concentrations reduces the occurrence and progression of diabetes complications (1-6). High concentrations of the inflammatory marker C-reactive protein (CRP) are associated with greater risks of cardiovascular disease (CVD) and diabetes in persons without diabetes (7) and a greater risk of CVD in persons with diabetes (8). Serum CRP can be reduced in T2DM patients with the use of statins (9, 10) or thiazolidinediones (11) and, in persons with impaired glucose tolerance, with the use of metformin or weight reduction and exercise (12). However, the ability of dietary management to influence the outcome of diabetes is not clear.

Although almost everyone would agree that diet is the cornerstone of diabetes therapy, there is marked disagreement about what kind of dietary advice is best, particularly with respect to dietary carbohydrate. Low-fat and high-carbohydrate (high-CHO) diets may help maintain body weight (13) and insulin sensitivity (14), but they may increase CVD risk by increasing blood glucose, insulin, and triacylglycerol concentrations and reducing HDL-cholesterol concentrations (15, 16). The role of the glycemic index (GI), a classification of the glycemic effect of high-carbohydrate foods, is controversial (17, 18). Resolution of these issues requires high-quality evidence. However, a Cochrane review concluded that, because of methodologic flaws, no high-quality data on the efficacy of dietary treatment in T2DM exist (19). In addition, most existing data are from short-term (4–6-wk) studies, whose results may be misleading because of physiologic adaptation. For example, the reduction in the ratio of total to HDL cholesterol (total:HDL cholesterol) induced by a low-CHO and high-monounsaturated fatty acid diet in T2DM patients may disappear by 6 mo (20).

Thus, because of the poor quality of the currently available evidence and the controversy about dietary carbohydrates in the management of T2DM, we conducted a long-term, multicenter, randomized controlled trial with the aim of comparing the effects of altering the source of carbohydrate with the effects of reducing the amount of dietary carbohydrate on the primary endpoint of glycemic control assessed by glycated hemoglobin (HbA1c) and on secondary endpoints of blood glucose, lipids, and CRP in patients with T2DM managed by diet alone.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
Men or nonpregnant women with T2DM [fasting plasma glucose ≥ 7.0 mmol/L or plasma glucose ≥11.1 mmol/L 2 h after a 75-g oral-glucose-tolerance test (OGTT) on ≥1 occasion within 2 mo of randomization] that was managed by diet alone were recruited. Subjects were 35–75 y old and had HbA1c ≤130% of the upper limit of normal and a body mass index (BMI; in kg/m2) of 24 to 40. Exclusion criteria were the use of insulin or any hypoglycemic or antihyperglycemic medication, stroke, myocardial infarction or major surgery within 6 mo of randomization, serum triacylglycerol concentrations > 10 mmol/L, any major debilitating disorder, any condition or drug likely to alter nutrient absorption, use of oral steroids, substance or alcohol abuse, allergy or intolerance to >1 of the study key foods, and expectation of being on vacation and unable to take study foods for >8 wk in a row or a total of >12 wk.

Written informed consent was obtained from all subjects. The procedures followed were in accordance with the ethical standards of each institution involved, and approval was obtained from the relevant ethics review committee on human subjects. The trial was registered on the Current Controlled Trials register (ISRCTN Reg. no. ISRCTN81151522. Internet: http://www.controlled-trials.com/ISRCTN81151522).

Baseline period
After eligibility was determined, subjects were instructed how to record all foods and drinks consumed during 2 typical weekdays and 1 weekend day (3-d food record). After the food record had been completed, subjects underwent a baseline 75-g OGTT, and the food record was reviewed by a registered dietitian who provided dietary advice with the aim of a diet containing {approx}55% of energy as carbohydrate, {approx}15% of energy as protein, and {approx}30% of energy as fat and with ≤10% saturated fatty acids (SFAs), ≤10% polyunsaturated fatty acids, and the remainder as monounsaturated fatty acids (MUFAs) (21). Two weeks later, the baseline (high-GI) breakfast test meal profile was performed, and subjects were randomly assigned to receive one of the following diets for 1 y: 1) high-CHO and high-GI (the high-GI diet), 2) high-CHO and low-GI (the low-GI diet), or 3) low-CHO and high-MUFA (the low-CHO diet).

Randomization and concealment
Subjects, stratified by center, were randomly assigned to 1 of the 3 diets with the use of blocks of various sizes to enhance allocation concealment (22, 23). Treatment assignments were sealed in sequentially numbered opaque envelopes kept by a person not involved with the study, and they were assigned to subjects in order on the day they attended for the baseline metabolic profile. Randomization (generated by computer with the random seed chosen from a table of random numbers) and the preparation of the sealed envelopes were done by one of us (ALG).

Dietary intervention
The dietary intervention called for in the study protocol was for subjects to consume specific key foods, which, by themselves, would result in the desired changes in nutrient intake. Subjects in each diet group could choose from 16–21 key foods (Table 1Go), which were provided free of charge. Choices could vary throughout the study period, and intake was recorded daily in key-food diaries. For the high- and low-GI diets, the key foods were starchy carbohydrates whose GI we had determined (24-29). The amount prescribed was such that their carbohydrates provided 20–25% of the energy requirement estimated by using the tables of the Lipid Research Clinics (30) to which 300 kcal/d was added for exercise (31) and from which 500 kcal/d was subtracted if the subject wished to lose weight. We expected this intervention to result in a GI difference of {approx}10 between the high-GI and low-GI diets (32). For the low-CHO diet, key foods consisted of olive or canola oils or spreads, nuts, and other foods low in SFAs and high in MUFAs and known to be associated with reduced risks of diabetes and CVD (33-35) or known to reduce blood lipids (16, 36, 37). These foods replaced carbohydrate foods normally consumed and were prescribed in amounts sufficient to raise total fat intake by {approx}10%.


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  		TABLE 1. Intakes of key foods used as the dietary interventions

 
Subjects received individualized advice from a registered dietitian at each visit. General advice on following a heart-healthy diet was provided to all subjects. Each subject had an individualized education session with the dietitian about the dietary intervention he or she was to follow on the day of the first metabolic profile (the day of randomization). This session lasted for 30–60 min, during which time the previously collected food records were reviewed and the study protocol explained. For subjects randomly assigned to the high-GI diet, the advice focused on following a healthy low-fat diet and avoiding low-GI foods. Subjects randomly assigned to the low-GI diet were given low-fat diet advice along with suggestions about to how to exchange high-GI foods for low-GI foods. Subjects randomly assigned to the low-CHO diet were given advice about how to reduce SFA intake and how to exchange carbohydrate-rich foods for the study key foods high in MUFAs. All subjects were given a list of the key foods for their respective study diet, and the list indicated the number of servings they were to consume each day. Subjects were advised on how to incorporate the key foods into their diet in exchange for others so as to avoid weight gain.

Subjects were seen 2 and 4 wk after randomization and then every 4 wk for weighing, review of key-food diaries, and pick-up of supplies of key foods. During each 30-min visit, dietitians provided individualized dietary advice and discussed any challenges that subjects encountered in following the study protocol and their solutions. Three-day food records were recorded twice during the run-in period and at 1, 3, 6, 9, and 12 mo after randomization.

Fasting blood samples and oral-glucose-tolerance tests
Blood samples were obtained after 10–14-h overnight fasts at baseline and at 1, 3, 6, 9, and 12 mo after randomization. Subjects underwent 75-g OGTTs at baseline and 3, 6, and 12 mo after randomization with blood samples for plasma glucose and insulin taken fasting and at 30, 60, and 120 min after the subjects started to consume the glucose.

Breakfast profile test
Subjects underwent breakfast profile tests at baseline and 2 wk after the final OGTT (subjects continued to consume their study diets between the final OGTT and the final breakfast profile). At baseline all subjects received a breakfast meal of normal foods reflective of the high-GI diet. At the end of the study, half of the subjects were randomly assigned to receive a breakfast meal that reflected the composition of the diet they had been consuming during the study (ie, high-GI, low-GI, or low-CHO diet); the other half of the subjects received the same breakfast as at baseline. We report here the results of the breakfast profiles for the subjects whose test meals at the end of the study reflected the diet they consumed during the study (ie, all subjects following the high-GI diet and 50% of the subjects following the low-GI or low-CHO diet). Breakfast-profile tests were performed after 10–12-h overnight fasts; fasting blood samples were taken, and additional blood samples were taken at hourly intervals for 4 h after the subjects started to consume the breakfast test meal.

Treatment failure
If HbA1c was >140% of the upper limit of normal (ie, 5.8%) regardless of the fasting plasma glucose (FPG) concentration, or if FPG was >10.0 mmol/L and HbA1c was >130% of the upper limit of normal on 2 consecutive occasions, subjects were considered to have failed the treatment, and they were withdrawn from the study and treated with an oral agent or insulin of the physician's choice.

Concomitant medications
Doses of lipid-lowering drugs were adjusted during the run-in period for optimum control, and then they were kept constant unless a change was required for clinical reasons. Subjects whose dose of statin medication changed during the study (n = 15) were excluded from the analysis of blood lipids, lipoproteins, and CRP.

Laboratory procedures
Blood samples were analyzed centrally. We measured HbA1c with HPLC (Diamat HPLC; Bio-Rad Laboratories Ltd, Mississauga, Canada), plasma glucose by using a hexokinase method, insulin by using an electrochemiluminescence immunoassay (Roche Diagnostics, Mannheim, Germany), and we measured free fatty acids (FFAs) enzymatically (Wako Chemical Industries, Dallas, TX). Serum cholesterol, triacylglycerol, apolipoprotein (apo) A-I, and apo B were measured as previously described (31); HDL was measured after the precipitation of non-HDL cholesterol with the use of dextran sulfate magnesium chloride (38), and LDL cholesterol was calculated. CRP was analyzed by using nephelometry (Behring BN-100; Dade-Behring, Mississauga, Canada).

Power analysis
To allow detection of a difference of 0.36%/y in the rate of change of HbA1c between the low-CHO and low-GI diets with 80% probability and a 2-tailed P ≤ 0.05, the estimated sample size was 42/group. With an allowance for a 20% dropout rate, we planned to randomly assign 168 subjects to the 3 treatment groups.

Statistical analysis
The nutrient composition of test meals and diets was assessed by using an in-house program with a nutrient database based on the Canadian Nutrient File and with values for GI added as described previously (39). The term "carbohydrate" refers to available carbohydrate, defined as total carbohydrate minus dietary fiber. Glycemic load (GL) was calculated as the sum of GI x g for each food in the diet, where g represents grams carbohydrate. The GI of test meals and diets was calculated as GL/G, where G is the amount of carbohydrate in the entire meal or diet. GL values of the diets were adjusted for energy by using the residuals method. We calculated incremental areas under the curve (AUC), ignoring the area beneath the fasting value, as described previously (40).

Longitudinal analyses of primary and secondary outcomes were carried out by using a general linear mixed model in SAS PROC MIXED software [version 8.2 for Unix; SAS Institute, Cary, NC (41)]. The correlation structure between measurements from the same subject was unspecified and estimated from the data. Time was treated as a regression variable; nonlinearity in change over time was modeled by polynomials up to degree 3. Model covariates included the baseline value and any of age, BMI, sex, and center that correlated significantly with the response variable. Models for 2-h glucose and insulin included the fasting value as a covariate. Outcomes were modeled for time points when subjects were under treatment. Diet x time interactions represent differences in the shape of the response profile over time by diet for these time points. Main effects of diet indicate differences among the diet groups between baseline and the first measurement taken during treatment. Data on those who dropped out because of treatment failure were retained in the model up to and including the point at which they were declared to have failed treatment, so the missing values for the subjects can be considered to be missing at random. All other missing observations (eg, those missing because of missed appointments or adverse events not related the study treatments) can be considered to be missing completely at random.

Analysis of CRP, fasting insulin, and FFAs was carried out on the natural logarithm of the values to improve the symmetry and homoscedasticity of the distributions. Plots of these variables display the estimated percentage change from baseline. Data in tables are displayed in the original scale of measurement.

For the breakfast profiles, the significance of differences in plasma glucose increments and AUC from baseline values were assessed by using a paired t test. The significance of differences in glucose increments and AUC between baseline and 1 y were compared across the different diets by using one-factor analysis of variance (ANOVA) with Tukey's test used to control for multiple comparisons. Differences were considered significant if 2-tailed P values were <0.05.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
One hundred sixty-two subjects were randomly assigned to receive the high-GI (n = 52), low-GI (n = 56), or low-CHO (n = 54) diet (Figure 1Go). At baseline, 77 (48%) subjects were taking an angiotensin-converting enzyme inhibitor (n = 35), a diuretic (n = 26), a calcium channel blocker (n = 19), an angiotensin-receptor blocker (n = 17), or a β-blocker (n = 15) or an {alpha}-blocker (n = 5) (or both); 47 of the subjects were taking a single agent and 30 were taking ≥2 agents. Sixty-nine subjects (43%) were taking lipid-lowering medication; 58 were taking a statin, 4 were taking fibrate and 7 were taking both; in addition, 50 subjects (31%) were taking aspirin. The distribution of medications did not differ significantly between the diet groups. The only significant differences among diet groups at baseline were lower LDL cholesterol in subjects following the high-GI diet than in those following the low-GI diet and lower CRP in those following the low-CHO diet than in those following the high-GI diet (Table 2Go).


Figure 1
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  		FIGURE 1.. Study flowchart.

 

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  		TABLE 2. Baseline variables at the time of randomization1

 
Subjects following the high-GI, low-GI, and low-CHO diets were prescribed 9.0 ± 0.4, 7.9 ± 0.3, and 5.2 ± 0.2 servings of key foods/d, respectively. Key-food diaries were obtained from 147 (91%) subjects, and consumption was recorded for 95% of the days of the study. Subjects on the high-GI, low-GI, and low-CHO diets consumed 85 ± 3%, 81 ± 3%, and 106 ± 3%, respectively, of the amount prescribed; the energy intake from key foods with those diets was 611 ± 13, 532 ± 24, and 323 ± 14 kcal/d, representing 33.5 ± 1.6%, 30.2 ± 1.4%, and 16.1 ± 0.6%, respectively, of recorded energy intake.

The 3-d food records showed that fat intake fell from baseline with the high-GI and low-GI diets and increased with the low-CHO diet; approximately two-thirds of the increase in fat with the low-CHO diet was accounted for by MUFAs and the remainder was accounted for by polyunsaturated fat (Table 3Go). Intakes of SFAs and cholesterol fell slightly but significantly with all 3 diets. Carbohydrate intake increased from baseline with the high-GI and low-GI diets and decreased with the low-CHO diet. Fiber intake did not change with the high-GI or low-CHO diet, but it increased with the low-GI diet. Diet GI increased with the high-GI diet, fell with the low-GI diet, and did not change with the low-CHO diet; GL increased with the high-GI diet, did not change with the low-GI diet, and decreased with the low-CHO diet.


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  		TABLE 3. Daily nutrient intakes by diet group at baseline and during the study1

 
Glycemic control
HbA1c rose from {approx}6.1% at baseline to {approx}6.3% after 1 y (P < 0.0001; Figure 2Go), but there was no significant difference in HbA1c with the different diets (Table 4Go). HbA1c tended to fall initially with the low-GI diet (time x diet interaction, P = 0.084; Figure 2Go). There were significant time x diet interactions for FPG (P = 0.041) and plasma glucose 2 h after OGTT (P = 0.010; Figure 2Go). FPG fell initially with the low-GI and low-CHO diets but then rose, so that, by 12 mo, FPG was lowest with the high-GI diet. At 3 mo, 2-h post-OGTT plasma glucose concentrations were {approx}8% lower with the low-CHO diet than with the other diets; by 12 mo, however, the glucose concentration had risen steadily to a value {approx}7% greater than that with the low-GI diet (P < 0.05; Figure 2Go). There were no significant differences in fasting or 2-h post-OGTT insulin concentrations.


Figure 2
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  		FIGURE 2.. Mean (±SEM) glycated hemoglobin (HbA1c), fasting glucose, and plasma glucose concentrations 2 h after a 75-g oral-glucose-tolerance test (OGTT) in subjects receiving the high-glycemic-index (•; n = 48), low-glycemic-index ({circ}; n = 55), and low-carbohydrate ({blacktriangleup}; n = 53) diets. Values are the residuals of regression models including the baseline value and other significant confounding variables, which were as follows: HbA1c, none; fasting glucose, BMI; 2-h post-OGTT glucose, fasting glucose.

 

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  		TABLE 4. Effect of dietary treatments on outcome variables1

 
Body weight and blood pressure
There was a main effect of time squared (P = 0.0005) for body weight, which fell over the first 8 wk and then rose steadily over the remainder of the trial (Table 4Go; Figure 3Go). Although the initial weight loss was mainly seen with the low-GI diet, and the late weight gain was mainly seen with the low-CHO diet, these differences were not significant (diet x time interaction, P = 0.09; main effect of diet, P = 0.062). There was no significant effect of diet, time, or diet x time interaction for systolic blood pressure, but there was a significant diet x time interaction for diastolic blood pressure (Table 4Go; Figure 3Go).


Figure 3
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  		FIGURE 3.. Mean (±SEM) body weight and diastolic blood pressure in subjects receiving the high-glycemic-index (•; n = 48), low-glycemic-index ({circ}; n = 55), and low-carbohydrate ({blacktriangleup}; n = 53) diets. Values are the residuals of regression models including the baseline value and other significant confounding variables, which were as follows: A: weight, age, BMI, and center; B: diastolic blood pressure, none. The significance of the differences among diets is given in Table 4Go.

 
Blood lipids and lipoproteins
There were no significant effects for total cholesterol or apoB (Table 4Go). With the low-GI diet, mean triacylglycerol was 12% higher, HDL was 4% lower, and the ratio of apoB to apoA was 4% higher than with the low-CHO diet (P < 0.05 for all); the high-GI diet values were intermediate. Mean apoA was 4% lower with the low-GI diet than with the high-GI diet (P < 0.05); the value with the low-CHO diet was intermediate. There was a significant diet x time interaction for total:HDL cholesterol (P = 0.044; Table 4Go); initially, the total:HDL was 6–8% lower with the low-CHO diet than with the low-GI diet, but this difference disappeared after 6 mo (Figure 4Go).


Figure 4
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  		FIGURE 4.. Mean (±SEM) fasting blood lipids and lipoproteins in subjects receiving the high-glycemic-index (•; n = 43), low-glycemic-index ({circ}; n = 48), and low-carbohydrate ({blacktriangleup}; n = 50) diets. Values are the residuals of regression models including the baseline value and other significant confounding variables (in parentheses), which were as follows: A: total cholesterol (center); B: triacylglycerol (none); C: LDL cholesterol (none); D: HDL cholesterol (center and sex); E: apolipoprotein B100 (none); F: apolipoprotein (apo) A-I (center and sex); G: ratio of total to HDL cholesterol (none); H: ratio of apolipoprotein B to apolipoprotein A (none). There was no significant effect of diet and no significant time x diet interaction for total or LDL cholesterol or apolipoprotein B.

 
C-reactive protein
There was a highly significant main effect of diet (P = 0.0078), in which mean CRP with the low-GI diet was 29% less than that with the high-GI diet (P < 0.05). The diet x time interaction was nearly significant (P = 0.064); with the low-GI diet, CRP tended to fall throughout the study, reaching a reduction from baseline of >20% by 12 mo. With the high-GI diet, CRP increased acutely by 40% and then stabilized 15–20% above baseline from 3–12 mo. With the low-CHO diet, mean CRP was between the values seen with the high-GI and low-GI diets throughout (Figure 5Go). At baseline, 57%, 43%, and 33% of subjects following the high-GI, low-GI, and low-CHO diets, respectively, had CRP ≥ 3 mg/L (NS). After 1 y, the proportion of subjects with CRP ≥ 3 mg/L had increased to 80% with the high-GI diet, decreased to 33% with the low-GI diet, and not changed (33%) with the low-CHO diet (P < 0.0001).


Figure 5
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  		FIGURE 5.. Mean (and 95% CI) serum C-reactive protein (CRP) concentrations in subjects receiving the high-glycemic-index (•; n = 43), low-glycemic-index ({circ}; n = 48), and low-carbohydrate ({blacktriangleup}; n = 50) diets. Values are the residuals of a regression model that included the baseline value and BMI (the only other significant confounding variable). The statistical analysis was performed on the natural logarithms of the CRP concentrations, which are shown here as percentage changes from baseline. Main effect of diet, P = 0.0078.

 
Breakfast profile
The GL of the low-GI and low-CHO breakfast test meals taken at the end of the study were 24% less than the GL of the respective high-GI meals taken at baseline, because of a reduction in GI with the low-GI diet and a lower carbohydrate intake with the low-CHO diet (Table 5Go). At the end of the study, the glycemic responses elicited by the high-GI and low-CHO diet breakfast meals did not differ significantly from the response elicited by the high-GI meal at baseline. However, the 1-h glucose increment elicited by the low-GI meal was not only 24% less than baseline (P = 0.04), but also significantly less than the increments seen with the other diets (P < 0.05; Figure 6Go). The mean AUC with the low-GI diet was 24% less than baseline (P = 0.008) and less than that seen with the high-GI diet (P = 0.016); the AUC with the low-CHO diet was intermediate.


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  		TABLE 5. Composition of breakfast test meals at baseline and after 1 y1

 

Figure 6
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  		FIGURE 6.. Mean (±SEM) incremental plasma glucose responses after high-glycemic-index (GI) breakfast test meals at baseline (•) and after high-glycemic-index (high-GI; n = 31), low-GI (n = 14), and low-carbohydrate (low-CHO; n = 16) breakfast test meals after 1 y ({circ}) of following the respective study diets. Insets show the incremental areas under the curve (AUC) and glycemic load (GL) of the test meals at baseline ({blacksquare}) and at 1 y ({square}). *Significantly different (P < 0.05) from baseline (paired t test). **Differences between baseline and 1-y values with the low-GI diet were significantly different from the differences with the high-GI diet (P < 0.05) (one-factor ANOVA followed by Tukey's test). +Difference between baseline and 1-y values on the low-GI diet significantly different from that on the low-CHO diet (P < 0.05) (one-factor ANOVA followed by Tukey's test). None of the other differences was statistically significant.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
We aimed for this study to provide high-quality evidence for the long-term (1 y) effects of altering the source or amount of dietary carbohydrate in the management of T2DM. The results showed that modest reductions in carbohydrate intake or diet GI for 1 y had no significant effect on HbA1c concentrations in T2DM patients with optimal glycemic control treated by diet alone. However, significant time x treatment interactions existed for a number of endpoints, which suggests that the long-term effects of changes in dietary carbohydrate on CVD risk factors may not be reflected by the results of studies lasting <6 mo. Moreover, the low-GI diet caused a large, sustained reduction in CRP.

Our results do not agree with meta-analyses showing that low-GI diets reduce HbA1c or fructosamine in subjects with or without diabetes (18, 42, 43). The meta-analyses were based largely on studies lasting <3 mo, and it is possible that the effects of a low-GI diet on HbA1c in T2DM patients are not sustained for 1 y. This possibility is weakly supported by our finding of a nonsignificant trend toward a temporary reduction in HbA1c with the low-GI diet. However, most T2DM patients in published reports of trials of low-GI diets had HbA1c 7.5–8.5% at baseline (18). By contrast our subjects had optimal mean HbA1c at baseline, ie, 6.1%, which may be more difficult to reduce. In addition, because dietary changes had to be sustained over long period of time, the difference in diet GI here was smaller than that in many short-term studies, and that smaller difference may have contributed to our inability to detect a significant effect of the low-GI diet on HbA1c. Our results for the low-CHO diet are consistent with the results of shorter-term studies, none of which show any significant effect of a low-CHO and high-MUFA diet on HbA1c or fructosamine concentrations (16, 44, 45).

Although HbA1c did not change significantly, the different diets had distinct effects on glucose metabolism. With the high-GI diet, FPG remained stable throughout the study, whereas, with the low-GI and low-CHO diets, FPG fell initially but then rose to exceed the concentration seen with the high-GI diet by 12 mo. The rise with the low-GI diet was unexpected, given the stability of FPG in T2DM patients consuming a high-fiber, low-GI breakfast cereal for 6 mo (20) and the sustained reduction in FPG in T2DM patients treated only with diet and acarbose (46). Changes in FPG in T2DM patients reflect changes in hepatic glucose output (47), which is regulated in part by insulin and FFAs (48). We found no significant differences in plasma insulin among the diet groups, and, although mean fasting FFAs were {approx}8% higher with the low-GI than with the high-GI diet, the difference was not significant. Nevertheless, this trend is consistent with the suggestion that low-GI diets increase fat oxidation (49). The rise in FPG with the low-CHO diet could be related to the small rise in body weight; however, fasting insulin and FFAs in the subjects following the low-CHO diet were almost identical to the values in the subjects following the high-GI diet.

The initial reduction in plasma glucose 2 h after OGTT with the low-CHO diet is consistent with short-term studies suggesting that low-CHO diets improve insulin sensitivity in T2DM patients (50, 51). This change is not likely to be due to a beneficial effect of MUFAs per se, because increasing MUFAs at the expense of dietary carbohydrate results in a high fat intake, and exchanging SFAs for MUFAs does not improve insulin sensitivity if total fat intake is >37% of energy (52). Thus, the short-term effect of a low-CHO and high-MUFA diet on insulin sensitivity in T2DM may be due to reduced glucose toxicity resulting from lower postprandial glucose responses. However, the results in the present study suggest that low-CHO and high-MUFA meals do not continue to elicit low glycemic responses over the long term, which may explain why 2-h post-OGTT plasma glucose increased between 3 and 12 mo with the low-CHO diet.

The low-GI diet had the most favorable long-term effect on 2-h post-OGTT glucose. This finding is important, because there is good evidence both in subjects without diabetes (53) and in T2DM patients (54, 55) that high postprandial glucose is a better indicator of CVD risk than is fasting glucose. After 1 y of the low-GI diet, 2-h post-OGTT glucose concentrations were {approx}1 mmol/L lower than those seen with the other 2 diets—a difference that, in prospective studies, was associated with a 6–15% reduction in cardiovascular events (56, 57). Changes in 2-h post-OGTT glucose concentrations could be due to changes in insulin sensitivity or insulin secretion or both. Short-term studies show that low-GI diets improve insulin sensitivity (58) and β-cell function (32, 59, 60), and the results of the present study suggest that these effects may persist for ≥1 y. The effects of low-GI diets on insulin sensitivity and secretion may be due directly or indirectly to reduced glycemic responses. In short-term studies in T2DM patients, the difference between the glycemic effects of low-GI and high-GI breakfast meals was quantitatively predicted by the difference in meal GI (61). The results of the present study show that the reduced glycemic effect of high-CHO and low-GI meals is sustained and, even after 1 y, is exactly predicted by the difference in meal composition.

The major reason for concern about the use of high-CHO diets for diabetes patients is that these diets raise serum triacylglycerol and reduce HDL concentrations (16) and, hence, may increase CVD risk. However, this determination was based on the results of studies lasting <6 mo (16). The results of the present study suggest that the potentially deleterious effect of high-CHO diets on blood lipids is a temporary phenomenon lasting <6 mo. We cannot confidently assert this for serum triacylglycerol and HDL, because there were significant main effects of diet but no time x diet interaction. Nevertheless, the differences in triacylglycerol and HDL between low-GI and low-CHO diets from 6–12 mo were only {approx}1/3 of the differences at 3 mo. In addition, triacylglycerol and HDL may not be the most relevant markers of CVD risk. Therapy of dyslipidemia to reduce CVD risk is based on targets for LDL cholesterol and total:HDL cholesterol (62). Although we found no effect on LDL cholesterol, there was a significant time x diet interaction for total:HDL cholesterol. There was a difference of {approx}10% in total:HDL cholesterol at 3 mo, which is consistent with the results of short-term studies (44, 63), but this difference was not present at 6, 9, and 12 mo. Because the effects of high-CHO diets on triacylglycerol and HDL-cholesterol concentrations appear to be similar in subjects with (16) and without (63) diabetes, our results may apply to more than subjects with diabetes treated with diet alone. We have no data to explain long-term adaptation, but it may be due to changes in colonic fermentation (64) or insulin sensitivity secondary to changes in body composition (65). However, reduced adherence to the dietary treatments is not a likely explanation. The key-food diaries and 3-d food records show no change in compliance or dietary composition across the study. In addition, the significant or nearly significant time x diet interactions for several variables (eg, FPG, 2-h post-OGTT glucose, and CRP), in which the differences among diets increase at the end of the study, are not consistent with reduced dietary adherence.

Our most novel finding was the larger, more sustained reduction in CRP with the low-GI diet than with the high-GI diet. The 29% difference is greater than that elicited by pravastatin in T2DM patients, ie, 13% (9), and similar to the differences elicited by atorvastatin, ie, {approx}25% (10), and rosiglitazone, ie, {approx}25% (11). These findings are consistent with a prospective study showing that CRP concentrations in diabetic women were inversely related to diet GI but not to diet GL (66). Hyperglycemia induces the release of inflammatory cytokines from monocytes (67). Although differences in HbA1c cannot explain the differences in CRP that we observed, differences in glucose fluctuations may be involved. Exposing endothelial cells to fluctuating glucose concentrations, rather than to the same average but constant concentration, increased oxidative stress and apoptosis (68), and those increases, in turn, may trigger proinflammatory responses and greater release of CRP (69). Thus, the reduction in CRP that we observed may be related to the lower postprandial glucose increments seen with the low-GI diet than with the other diets. In this context, it is of interest that the treatment of T2DM patients with repaglinide induced larger reductions in postprandial glucose and serum CRP than did treatment with glyburide, despite no difference in HbA1c, and that this treatment also was associated with greater regression of carotid artery atherosclerosis (70).

We conclude that, in T2DM patients treated with diet alone who have optimal glycemic control, long-term HbA1c was not affected by altering the source or the amount of dietary carbohydrat. The deleterious effects of the high-CHO diets on total:HDL cholesterol had disappeared by 6 mo. The low-GI diet elicited sustained reductions in postprandial glucose and CRP, and, for these reasons, it may be preferred for the dietary management of T2DM.


   ACKNOWLEDGMENTS
 
The authors’ responsibilities were as follows—TMSW: had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis; TMSW, ALG, CM, J-LC, PWC, RGJ, LAL, PM, RR-L, NWR, and EAR: study design and concept; TMSW, CM, J-LC, PM, RR-L, NWR, and EAR: acquisition of data; TMSW and ALG: analysis and interpretation of data; TMSW: drafting of the manuscript; TMSW, ALG, CM, J-LC, PWC, RGJ, LAL, PM, RR-L, NWR, and EAR: critical revision of the manuscript; TMSW, ALG, J-LC, RGJ, LAL, PM, NWR, and EAR: obtained funding; and TMSW, ALG, CM, and PWC: administrative, technical, or material support. TMSW is president and part-owner of Glycemic Index Laboratories Inc, a contract research organization, and president and part-owner of Glycaemic Index Testing Inc, a corporation that provides services related to the measurement of the glycemic index of foods. He has received grant or research support from Cargill Inc and ILSI Europe; was a consultant for the US Potato Board; and received honoraria for consulting or speaking from the Dutch Sugar Bureau and Mars Inc. TMSW is co-author of a range of popular books on the glycemic index under the general title of The Glucose Revolution: Authoritative Guide to the Glycemic Index, published by Marlowe & Co (New York, NY) and the author of a scientific book entitled The Glycaemic Index: A Physiologic Classification of Dietary Carbohydrate, published by CABI (London, United Kingdom). None of the other authors had any personal or financial conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study Group. Lancet 1998;352:827–53.
  2. Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study Group. Lancet 1998;352:854–65.[Medline]
  3. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. UK Prospective Diabetes Study Group. BMJ 1998;317:703–13. (Published erratum appears in BMJ 1999;318:29.)[Abstract/Free Full Text]
  4. Collins R, Armitage J, Parish S, Sleigh P, Peto R; Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of cholesterol-lowering with simvastatin in 5963 people with diabetes: a randomised placebo-controlled trial. Lancet 2003;361:2005–16.[Medline]
  5. Sever PS, Poulter NR, Dahlof B, et al. Reduction in cardiovascular events with atorvastatin in 2,532 patients with type 2 diabetes: Anglo-Scandinavian Cardiac Outcomes Trial–lipid-lowering arm (ASCOT-LLA). Diabetes Care 2005;28:1151–7.[Abstract/Free Full Text]
  6. Keech A, Simes RJ, Barter P, et al; FIELD Study investigators. Effects of long-term fenofibrate therapy on cardiovascular events in 9795 people with type 2 diabetes mellitus (the FIELD study): randomised controlled trial. Lancet 2005;366:1849–61.[Medline]
  7. Haffner SM. The metabolic syndrome: inflammation, diabetes mellitus, and cardiovascular disease. Am J Cardiol 2006;97(suppl):3A–11A.[Medline]
  8. Malik S, Wong ND, Franklin S, Pio J, Fairchild C, Chen R. Cardiovascular disease in U.S. patients with metabolic syndrome, diabetes, and elevated C-reactive protein. Diabetes Care 2005;28:690–3.[Abstract/Free Full Text]
  9. Sommeijer DW, MacGillavry MR, Meijers JC, Van Zanten AP, Reitsma PH, Ten Cate H. Anti-inflammatory and anticoagulant effects of pravastatin in patients with type 2 diabetes. Diabetes Care 2004;27:468–73.[Abstract/Free Full Text]
  10. Yamada S, Yanagawa T, Sasamoto K, Araki A, Miyao M, Yamanouchi T. Atorvastatin lowers plasma low-density lipoprotein cholesterol and C-reactive protein in Japanese type 2 diabetic patients. Metabolism 2006;55:67–71.[Medline]
  11. Haffner SM, Greenberg AS, Weston WM, Chen H, Williams K, Freed MI. Effect of rosiglitazone treatment on non-traditional markers of cardiovascular disease in patients with type 2 diabetes mellitus. Circulation 2002;106:679–84.[Abstract/Free Full Text]
  12. Haffner S, Temprosa M, Crandall J, et al; Diabetes Prevention Program Research Group. Intensive lifestyle intervention or metformin on inflammation and coagulation in participants with impaired glucose tolerance. Diabetes 2005;54:1566–72.[Abstract/Free Full Text]
  13. Pascale RW, Wing RR, Butler BA, Mullen M, Bononi P. Effects of a behavioral weight loss program stressing calorie restriction versus calorie plus fat restriction in obese individuals with NIDDM or a family history of diabetes. Diabetes Care 1995;18:1241–8.[Abstract]
  14. Purnell JQ, Brunzell JD. The central role of dietary fat, not carbohydrate, in the insulin resistance syndrome. Curr Opin Lipidol 1997;8:17–22.[Medline]
  15. Garg A, Bantle JP, Henry RR, et al. Effects of varying carbohydrate content of diets in patients with non-insulin-dependent diabetes mellitus. JAMA 1994;271:1421–8.[Abstract/Free Full Text]
  16. Garg A. High-monounsaturated-fat diets for patients with diabetes mellitus: a meta-analysis. Am J Clin Nutr 1998;67(suppl):577S–82S.[Abstract]
  17. Franz MJ, Bantle JP, Beebe CA, et al. Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications. Diabetes Care 2002;25:148–98.[Free Full Text]
  18. Brand-Miller J, Hayne S, Petocz P, Colagiuri S. Low-glycemic index diets in the management of diabetes: a meta-analysis of randomized controlled trials. Diabetes Care 2003;26:2261–7.[Abstract/Free Full Text]
  19. Moore H, Summerbell C, Hooper L, et al. Dietary advice for treatment of type 2 diabetes mellitus in adults. Cochrane Database Syst Rev 2004;2:CD004097.[Medline]
  20. Tsihlias EB, Gibbs AL, McBurney MI, Wolever TMS. Comparison of high- and low-glycemic index breakfast cereals versus monounsaturated fat in the long-term dietary management of type 2 diabetes. Am J Clin Nutr 2000;72:439–49.[Abstract/Free Full Text]
  21. Wolever TMS, Barbeau M-C, Charron S, et al. Guidelines for the nutritional management of diabetes mellitus in the new millennium: a position statement from the Canadian Diabetes Association. Can J Diabetes Care 1999;23(3):56–69.
  22. Schultz KF, Grimes DA. Allocation concealment in randomised trials: defending against deciphering. Lancet 2002;359:614–8.[Medline]
  23. Schultz KF, Grimes DA. Unequal group sizes in randomized trials: guarding against guessing. Lancet 2002;359:966–70.[Medline]
  24. Jenkins DJA, Wolever TMS, Jenkins AL, et al. Low glycemic response to traditionally processed wheat and rye products: bulgur and pumpernickel bread. Am J Clin Nutr 1986;43:516–20.[Abstract/Free Full Text]
  25. Wolever TMS, Jenkins DJA, Kalmusky J, et al. Glycemic response to pasta: effect of food form, cooking and protein enrichment. Diabetes Care 1986;9:401–4.[Abstract]
  26. Wolever TMS, Jenkins DJA, Kalmusky J, et al. Comparison of regular and parboiled rices: explanation of discrepancies between reported glycemic responses to rice. Nutr Res 1986;6:349–57.
  27. Wolever TMS, Jenkins DJA, Josse RG, Wong GS, Lee R. The glycemic index: similarity of values derived in insulin-dependent and non-insulin-dependent diabetic patients. J Am Col Nutr 1987;6:295–305.[Abstract]
  28. Wolever TMS, Jenkins DJA, Thompson LU, Wong GS, Josse RG. Effect of canning on the blood glucose response to beans in patients with type 2 diabetes. Hum Nutr Clin Nutr 1987;41C:135–40.[Medline]
  29. Wolever TMS, Katzman-Relle L, Jenkins AL, Vuksan V, Josse RG, Jenkins DJA. Glycaemic index of 102 complex carbohydrate foods in patients with diabetes. Nutr Res 1994;14:651–69.
  30. The Lipid Research Clinics population studies databook, vol 2. The prevalence study—nutrient intake. Washington, DC: Government Printing Office, 1982. (NIH publication no. 82-2014.)
  31. Jenkins DJA, Wolever TMS, Rao AV, et al. Effect on serum lipids of very high fiber intakes in diets low in saturated fat and cholesterol. N Engl J Med 1993;329:21–6.[Abstract/Free Full Text]
  32. Wolever TMS, Mehling C. High-carbohydrate/low-glycaemic index dietary advice improves glucose disposition index in subjects with impaired glucose tolerance. Br J Nutr 2002;87:477–87.[Medline]
  33. Jiang R, Manson JE, Stampfer MJ, Liu S, Willett WC, Hu FB. Nut and peanut butter consumption and risk of type 2 diabetes in women. JAMA 2002;288:2554–60.[Abstract/Free Full Text]
  34. Hu FB. Plant-based foods and prevention of cardiovascular disease: an overview. Am J Clin Nutr 2003;78(suppl):544S–51S.[Abstract/Free Full Text]
  35. Kris-Etherton PM, Hecker KD, Bonanome A, et al. Bioactive compounds in foods: their role in the prevention of cardiovascular disease and cancer. Am J Med 2002;113(suppl):71S–88S.[Medline]
  36. Lopez Ledesma R, Frati Munari AC, Hernandez Dominguez BC, et al. Monounsaturated fatty acid (avocado) rich diet for mild hypercholesterolemia. Arch Med Res 1996;27:519–23.[Medline]
  37. Sabate J, Haddad E, Tanzman JS, Jambazian P, Rajaram S. Serum lipid response to the graduated enrichment of a Step I diet with almonds: a randomized feeding trial. Am J Clin Nutr 2003;77:1379–84.[Abstract/Free Full Text]
  38. Connelly PW, MacLean DR, Horlick L, et al. Plasma lipids and lipoproteins and the prevalence of risk for coronary heart disease in Canadian adults. CMAJ 1992;146:1977–87.[Abstract]
  39. Wolever TMS, Nguyen PM, Chiasson J-L, et al. Determinants of diet glycemic index calculated retrospectively from diet records of 342 individuals with non-insulin-dependent diabetes mellitus. Am J Clin Nutr 1994;59:1265–9.[Abstract/Free Full Text]
  40. Wolever TMS, Vorster HH, Björk I, et al. Determination of the glycaemic index of foods: interlaboratory study. Eur J Clin Nutr 2003;57:475–82.[Medline]
  41. Cnaan A, Laird NM, Slasor P. Using the general linear mixed model to analyze unbalanced repeated measures and longitudinal data. Stat Med 1997;16:2349–80.[Medline]
  42. Kelly S, Frost G, Whittaker V, Summerbell C. Low glycaemic index diets for coronary heart disease. Cochrane Database Syst Rev 2004;4:CD004467.
  43. Opperman AM, Venter CS, Oosthuizen W, Thompson RL, Vorster HH. Meta-analysis of the health effects of using the glycaemic index in meal-planning. Br J Nutr 2004;92:367–81.[Medline]
  44. Garg A, Bonanome A, Grundy SM, Zhang ZJ, Unger RH. Comparison of a high-carbohydrate diet with a high-monounsaturated fat diet in patients with non-insulin-dependent diabetes mellitus. N Engl J Med 1988;319:829–34.[Abstract]
  45. Campbell LV, Marmot PE, Dyer JA, Borkman M, Storlien LH. The high-monounsaturated fat diet as a practical alternative for NIDDM. Diabetes Care 1994;17:177–82.[Abstract]
  46. Chiasson J-L, Josse RG, Hunt JA, et al. The efficacy of acarbose in the treatment of patients with non-insulin-dependent diabetes mellitus. A multicenter controlled clinical trial. Ann Intern Med 1994;121:928–35.[Abstract/Free Full Text]
  47. DeFronzo RA. Lilly Lecture 1987. The triumvirate: β-cell, muscle, liver: a collusion responsible for NIDDM. Diabetes 1988;37:667–87.[Medline]
  48. Lewis GF, Zinman B, Groenewoud Y, Vranic M, Giacca A. Hepatic glucose production is regulated both by direct hepatic and extrahepatic effects of insulin in humans. Diabetes 1996;45:454–62.[Abstract]
  49. Stevenson E, Williams C, Nute M. The influence of the glycaemic index of breakfast and lunch on substrate utilization during the postprandial periods and subsequent exercise. Br J Nutr 2005;93:885–93.[Medline]
  50. Parillo M, Rivellese AA, Ciardullo AV, et al. A high-monounsaturated-fat/low-carbohydrate diet improves peripheral insulin sensitivity in non-insulin-dependant diabetic patients. Metabolism 1992;41:1373–8.[Medline]
  51. Garg A, Grundy SM, Unger RH. Comparison of effects of high and low carbohydrate diets on plasma lipoproteins and insulin sensitivity in patients with mild NIDDM. Diabetes 1992;41:1278–85.[Abstract]
  52. Vessby B, Uusitupa M, Hermansen K, et al. Substituting dietary saturated for monounsaturated fat impairs insulin sensitivity in healthy men and women: the KANWU Study. Diabetologia 2001;44:312–9.[Medline]
  53. Levitan EB, Song Y, Ford ES, Liu S. Is nondiabetic hyperglycemia a risk factor for cardiovascular disease? A meta-analysis of prospective studies. Arch Intern Med 2004;164:2147–55.[Abstract/Free Full Text]
  54. Hanefeld M, Fischer S, Julius U, et al. Risk factors for myocardial infarction and death in newly detected NIDDM: the Diabetes Intervention Study 11-year follow-up. Diabetologia 1996;39:1577–83.[Medline]
  55. Glucose tolerance and mortality: comparison of WHO and American Diabetes Association diagnostic criteria. DECODE study group. European Diabetes Epidemiology Group. Diabetes epidemiology: collaborative analysis of diagnostic criteria in Europe. Lancet 1999;354:617–21.[Medline]
  56. Coutinho M, Gerstein HC, Wang Y, Yusuf S. The relationship between glucose and incident cardiovascular events. A metaregression analysis of published data from 20 studies of 95,783 individuals followed for 12.4 years. Diabetes Care 1999;22:233–40.[Abstract/Free Full Text]
  57. Meigs JB, Nathan DM, D'Agostino RB, Wilson PWF. Fasting and postchallenge glycemia and cardiovascular disease risk. The Framingham Offspring Study. Diabetes Care 2002;25:1845–50.[Abstract/Free Full Text]
  58. Rizkalla SW, Taghrid L, Laromiguiere M, et al. Improved plasma glucose control, whole-body glucose utilization, and lipid profile on a low-glycemic index diet in type 2 diabetic men: a randomized controlled trial. Diabetes Care 2004;27:1866–72.[Abstract/Free Full Text]
  59. Juntunen KS, Laaksonen DE, Poutanen KS, Niskanen LK, Mykkänen HM. High-fiber rye bread and insulin secretion and sensitivity in healthy postmenopausal women. Am J Clin Nutr 2003;77:385–91.[Abstract/Free Full Text]
  60. Laaksonen DE, Toppinen LK, Juntunen KS, et al. Dietary carbohydrate modification enhances insulin secretion in persons with the metabolic syndrome. Am J Clin Nutr 2005;82:1218–27.[Abstract/Free Full Text]
  61. Wolever TMS, Jenkins DJA, Vuksan V, et al. Beneficial effect of a low-glycaemic index diet in type 2 diabetes. Diabet Med 1992;9:451–8.[Medline]
  62. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106:3143–421.[Free Full Text]
  63. Jeppesen J, Schaaf P, Jones C, Zhou M-Y, Chen Y-DI, Reaven GM. Effects of low-fat, high-carbohydrate diets on risk factors for ischemic heart disease in postmenopausal women. Am J Clin Nutr 1997;65:1027–33.[Abstract/Free Full Text]
  64. Wolever TMS, Schrade KB, Vogt JA, Tsihlias EB, McBurney MI. Could colonic short chain fatty acids contribute to long-term adaptation of blood lipids on a high fiber diet in subjects with type 2 diabetes? Am J Clin Nutr 2002;75:1023–30.[Abstract/Free Full Text]
  65. Bouche C, Rizkalla SW, Luo J, et al. Five-week, low-glycemic index diet decreases total fat mass and improves plasma lipid profile in moderately overweight nondiabetic men. Diabetes Care 2002;25:822–8.[Abstract/Free Full Text]
  66. Qi L, van Dam RM, Liu S, Franz M, Mantzoros C, Hu FB. Whole-grain, bran and cereal fiber intakes and markers of systemic inflammation in diabetic women. Diabetes Care 2006;29:207–11.[Abstract/Free Full Text]
  67. Devaraj S, Venugopal SK, Singh U, Jialal I. Hyperglycemia induces monocytic release of interleukin-6 via induction of protein kinase c-{alpha} and -β. Diabetes 2005;54:85–91.[Medline]
  68. Risso A, Mercuri F, Quagliaro L, Damante G, Ceriello A. Intermittent high glucose enhances apoptosis in human umbilical vein endothelial cells in culture. Am J Physiol Endocrinol Metab 2001;281:E924–30.[Abstract/Free Full Text]
  69. Leiter LA, Ceriello A, Davidson JA, et al. Postprandial glucose regulation: new data and new implications. Clin Ther 2005;27(suppl):S42–56.[Medline]
  70. Esposito K, Giugliano D, Nappo F, Marfella R. Campanian Postprandial Hyperglycemia Study Group. Regression of carotid atherosclerosis by control of postprandial hyperglycemia in type 2 diabetes mellitus. Circulation 2004;110:214–9.[Abstract/Free Full Text]
Received for publication January 3, 2007. Accepted for publication July 27, 2007.


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