The aim was to investigate the associations of glycemic index (GI), glycemic load (GL), carbohydrate and fiber intakes with hyperglycemia in type 2 diabetic patients.
In a cross-sectional study of 640 type 2 diabetic patients aged 28–75 years, usual dietary intakes were assessed by validated food frequency questionnaire. We used published international and Iranian tables of GI based on the white bread. Multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CI).
High-GL diet was associated with higher risk of hyperglycemia in type 2 diabetic patients after controlling for potential confounders. In multivariable model, OR (95% CI) for the highest vs the lowest quartile of GL was 2.58 (1.08–6.15) for elevated fasting serum glucose (FSG) (>130 mg/dl) (Ptrend=0.02) and was 3.05 (1.33–7.03) for elevated HbA1c (>8.6%) (Ptrend=0.008). After additional adjusting for dietary fiber and protein intakes, the relation of GL with elevated FSG and HbA1c was stable. GI was not significantly associated with either elevated FSG or HbA1c. In multivariable model, OR (95% CI) for the highest vs lowest quartile of the substitution of dietary carbohydrate for fat intake was 2.32 (1.37–3.92) for elevated HbA1c (Ptrend=0.001). Higher intake of dietary fiber was associated with lower risk of elevated FSG (highest vs lowest quartile: OR, 0.53; 95% CI: 0.28–0.99; Ptrend=0.04), but not with lower risk of elevated HbA1c.
GL and carbohydrate intake were positively associated with the risk of hyperglycemia in type 2 diabetic patients; but the benefit in pursuing a low-GI diet without considering carbohydrate and energy intakes in these patients should be further investigated.
Diabetes is a chronic metabolic disease associated with long-term complications resulting from chronic hyperglycemia.1 Nutrition therapy is an integral part of diabetes care, and carbohydrate intake has the greatest impact on improving glycemic control.2 On the basis of American Diabetes Association’s (ADA) recommendations,3 there is no ideal percentage of energy from carbohydrate and other macronutrients for all diabetic patients. ADA proposes diabetic patients to monitor total carbohydrate intake via carbohydrate counting, exchanges or estimation.2 Foods containing equal amounts of carbohydrate induce a different effect on the postprandial blood glucose.4, 5 The glycemic index (GI), which quantifies the postprandial blood glucose and insulin responses to carbohydrate composition of diet,6 may have beneficial effects in addition to carbohydrate counting. On the other hand, the concept of glycemic load (GL), which represents both the quality and quantity of carbohydrate intake,7 has been developed to better represent overall glycemic effects of a particular food item.8 The effectiveness of low GI and GL diets in glycemic control has been examined in epidemiological, clinical trials and meta-analysis.9, 10, 11, 12, 13, 14 However, in some studies, diets with low GI or GL had no benefits in the management of diabetes.13, 14 On the basis of the current evidence, the ADA states that combined with carbohydrate counting, the use of GI and GL may provide a modest additional benefit in achieving blood glucose goals.3 On the other hand, the concept of the GI is considered as an important issue in the guidelines suggested by the European Association for the Study of Diabetes that recommends the substitution of low-GI foods with high-GI foods.15 Therefore, the aim of this study was to examine the potential association between dietary GI, GL, carbohydrate and fiber intakes, and the risk of hyperglycemia in men and women with type 2 diabetes.
Materials and methods
We conducted a cross-sectional study of 751 patients with type 2 diabetes who were randomly recruited via phone call from registered patients with diabetes at three major diabetes clinics located in Tehran: the Charity Foundation for Special Diseases, the Institute of Endocrinology and Metabolism, and the Iran Diabetes Association. Eligible participants were 25 years old and above with physician-diagnosed type 2 diabetes at least 1 year before data collection. We did not measure islet cell autoantibodies. Therefore, anyone with diabetes diagnosed before the age of 25 and taking only insulin therapy was considered to be having type 1 diabetes and was excluded from our sample.
Data on medical history, smoking addiction and medication were obtained from personal interview. We excluded those who did not meet the following criteria: taking insulin, altering medication regimen or dietary intake during 3 months before the study and having abnormal hepatic tests (n=30). We also excluded patients who did not live in Tehran (n=4), did not complete the food frequency questionnaire (FFQ) (n=48), those (n=11) who reported a total daily energy intake outside the range of 800–4200 kcal and those (n=18) who had missing data for confounding variables. After these exclusions, 640 type 2 diabetic patients aged 28–75 years remained.
Written informed consent was obtained from all participants. The research protocol was approved by the Ethics Committee of National Nutrition and Food Technology Research Institute.
We collected 20 ml blood samples from each participant between 0800 and 1000 hours, before taking any oral hypoglycemic agent(s) and after 12–14-h overnight fasting. Aliquots of serum and red pack cells were transferred to polystyrene tubes that were immediately stored at −70 °C until analysis. Fasting serum glucose (FSG) concentration was measured by the glucose oxidase method. HbA1c was measured by a chromatography method using the commercial kit (Globe Diagnostics, Rome, Italy).
The dietary intake of patients was assessed by interview using a 1-year validated 168-item semi-quantitative FFQ.16 It consisted of a list of foods with standard serving sizes according to Iranian meal patterns, and was designed to obtain information on usual food intake during the previous year. The reported frequency for each food item was then converted to a daily intake. Information on frequency of intake and portion size was converted to the number of grams of each food item consumed on average per day. To determine the total dietary carbohydrate, protein, fat, fiber and energy compositions of Iranian foods, we used the United States Department of Agriculture database17 and Iranian food composition tables. The validity and reproducibility of dietary GI and GL were similar to those of nutrients commonly studied in epidemiologic studies with the use of FFQs.18 Of the 168 food and beverage items included in the FFQ, 30 items (17.8%) contain no available carbohydrate. The calculation of dietary GL and GI was thus based on the remaining 138 items with GI values ranging from 10 to 123. We used published international5 and Iranian tables of GI.19 We calculated GL values by multiplying the available carbohydrate content of each food by its GI value and then multiplied the resultant value with the amount of consumption (divided by 100) and then summed the values from all food items.8 Each unit of dietary GL represents the equivalent of 1 g of carbohydrate from white bread. The overall GI for each participant was estimated by dividing the dietary GL by the total amount of carbohydrates consumed.8, 20 The calculated values of dietary GI, GL and total dietary carbohydrate, protein, fat and fiber were adjusted for total energy intake using the residual method.21
Height was measured to the nearest 0.1 cm and weight to the nearest 0.1 kg. Body mass index (BMI) was calculated as weight/height2 (kg/m2).
Data on physical activity were obtained using modified international physical activity questionnaire (publicly available at http://www.ipaq.ki.se/ipaq.htm) and expressed as metabolic equivalent h/day (MET-h/day).
The data were expressed as mean±s.d. or percentages. We divided GI and GL into quartiles and participants were categorized on the basis of GI and GL quartiles. Variables were compared across quartile categories of GI and GL by one-way analysis of variance with Tukey’s post hoc comparisons for quantitative variables and χ2-tests for qualitative variables. Logistic regression models were used to estimate odds ratio (OR) and 95% confidence intervals (CI) for each category using the lowest quartile of intake as the reference category, while controlling for potential confounding variables. FSG <130 mg/dl is recommended as a target of glycemic control by ADA2 and the expected HbA1c levels for normal glucose values are 6–8.6% by the commercial HbA1c kit.22 Therefore, we defined hyperglycemia with cutoff values of 130 mg/dl for FSG and 8.6% for HbA1c. All models were adjusted for age, sex and energy intake. Multivariable models included additional terms for duration of diabetes, smoking, physical activity, BMI, vitamin/mineral supplementation, total hypoglycemic medication, blood pressure-lowering drug and lipid-lowering drug. In additional analyses, we further adjusted for dietary protein and fiber intakes (multivariable model 2). Multivariable model 1 for total carbohydrate intake was fit without adjusting for protein and fat intake to simulate the substitution of carbohydrate for the average mixture of protein and fat in the study population and with the adjustment for protein (multivariable model 2) to simulate the substitution of carbohydrate with total fat intake.23 To examine whether the associations between GL and elevated FSG or HbA1c were modified by other measures of diabetes risk factors, a cross-product term for the level of each factor and intake of GL expressed as a continuous variable was included in the multivariable model. P-values for tests for interactions were obtained from a likelihood ratio test with 1 degree of freedom. IBM SPSS 21 was used for all analyses. All P-values were two-sided.
The median index across quartile of GL ranged from 108.2 to 246.6 and across quartile of GI ranged from 50.6 to 66.7. The main contributors of GL were bread (31.3%), rice (23.4%), fruits (21.3%) and sweets (9.8%). Clinical characteristics and nutrient intakes data relating to the 640 type 2 diabetes patients studied based on GL and GI quartiles are shown in Table 1. The participants with a higher GL were more likely to be younger, to be male, to have higher intakes of energy, carbohydrate, fat, protein and fiber, and to be smokers than subjects with lower GL. The participants with higher GL also had lower duration of diabetes. In comparison with the subjects in the lowest quartile of the GI, those in the higher quartiles were more likely to be younger, to be male, to be smokers and to consume more energy, carbohydrate and fat (Table 1).
From 640 type 2 diabetes patients, 440 of them had FSG >130 mg/dl and 378 of them had HbA1c >8.6%. The ORs of elevated FSG (>130 mg/dl) and HbA1c (>8.6%) according to quartile categories of GL, GI, total carbohydrate and fiber intakes are shown in Table 2. After making adjustment for demographic, anthropometric, medication and lifestyle factors, higher GL was associated with elevated FSG risk (the highest vs the lowest quartile: OR=2.58, 95% CI: 1.08, 6.15; Ptrend=0.02) and elevated HbA1c risk (the highest vs the lowest quartile: OR=3.05, 95% CI: 1.33, 7.03, Ptrend=0.008) (multivariable model 1, Table 2). To explore whether the association of hyperglycemia with the GL is independent of the dietary intakes of fiber and protein, we additionally adjusted for dietary fiber and protein intakes (multivariable model 2). The odds of having elevated FSG for the highest quartile vs the lowest quartile of GL were increased by 200% and OR (95% CI) for elevated HbA1c for the highest quartile vs the lowest quartile was 3.94 (1.66–9.31, Ptrend=0.002). The GI was not significantly related to either elevated FSG or elevated HbA1c. Substitution of carbohydrate for average intake of protein or fat (multivariable model 1) was not significantly associated with increased risk of elevated FSG, but increased the risk of elevated HbA1c by 127% in the highest vs the lowest quartile of carbohydrate intake. Because total energy intake, and percent of energy from carbohydrate and protein intakes were included simultaneously in the analysis, the OR for carbohydrate can be interpreted as the effect of substituting carbohydrate with an equivalent reduction in the percent of energy from total fat. Substitution of carbohydrate for fat intake was significantly associated with higher risk of hyperglycemia measured by HbA1c (multivariable model 2). Higher dietary fiber intake was related with lower risk of elevated FSG (highest vs lowest quartile: OR, 0.53; 95% CI: 0.28, 0.99; Ptrend=0.04). However, higher dietary fiber intake was not associated with lower risk of elevated HbA1c.
We also examined whether the associations between GL and elevated FSG and HbA1c differed by levels of hyperglycemia risk factors including age, BMI, duration of diabetes and sex. We have not found any significant interaction.
In this cross-sectional study, we examined the association of quality and quantity of dietary carbohydrate intake with risk of hyperglycemia in type 2 diabetic patients and found that dietary GL in people with type 2 diabetes was positively associated with risk of hyperglycemia after the adjustment for demographic, anthropometric, lifestyle, medication and dietary factors. These associations were independent of dietary fiber and protein intakes. However, no statistically significant association was observed for GI in relation to either FSG or HbA1c; either after adjustment for potential confounders or after further adjustment for dietary factors. In addition, we found that quantity of carbohydrate intake was positively associated with the risk of hyperglycemia measured by HbA1c. Higher intake of fiber was also associated with lower FSG, but not HbA1c.
The importance of low GL or GI diets in the management of diabetes is controversial.9, 10, 11, 12, 13, 14 A growing body of evidence supports a pivotal role for dietary GI and GL in the prevention of diabetes. In a recent meta-analysis of prospective cohort studies, high-GI and/or high-GL diets have been correlated with the risk of type 2 diabetes (GI: OR=1.16, 95% CI: 1.06–1.26; GL: OR=1.20, 95% CI: 1.11–1.30).10 In Greenland's Inuit population, after adjustment for age, sex, BMI, smoking status and energy intake, GI was positively associated with fasting plasma glucose and HbA1c, although this association was dependent on educational level and physical activity and after further adjustment, only the association with fasting plasma glucose remained statistically significant. The inverse associations of GL with fasting plasma glucose and HbA1c have been also attenuated after additional adjustment for BMI, education, smoking status, physical activity and energy intake.24 In contrast, in a Dutch population, neither GI nor GL was associated with fasting glucose and HbA1c after multivariable adjustment.25
Besides epidemiologic studies, an effect of low-GI diet was also demonstrated by clinical trials. Consumption of low-GI foods instead of traditional or high-GI foods has clinically useful benefits on glycemic control in diabetic patients.11 A recent meta-analysis of randomized controlled trials conducted in diabetes reported that consuming low-GI diets significantly decreased HbA1c levels by 0.4% compared with comparison diets.26 Jenkins et al.9 identified that 6-month treatment with a low-GI diet in type 2 diabetic patients reduced HbA1c levels compared with a high-cereal fiber diet even after controlling for dietary fiber or body weight. In contrast, Ma et al.13 compared the effects of a low-GI diet with the standard ADA guidelines on the HbA1c for patients with type 2 diabetes. They found that the effects of low-GI diet on HbA1c improvement was comparable with ADA diet. Mayer-Davis et al. evaluated GI and GL in relation to average fasting glucose, 2 h plasma glucose following 75-g glucose load and glycated hemoglobin in adult participants in the insulin resistance atherosclerosis study. The results did not support the correlation between dietary GI and any measure of glycemia.14 To compare the long-term effects of diets with different GI or carbohydrate amount on HbA1c and plasma glucose, type 2 diabetic patients received high-carbohydrate and high-GI, high-carbohydrate and low-GI, or low-carbohydrate and high-monounsaturated fat diets for 1 year. Although there has been higher intake of fiber and reduction in postprandial glucose by high-carbohydrate and low-GI diet, HbA1c was not improved by reductions in the GI or carbohydrate intakes.27
For GI, we found no association with glycemic control, as assessed by FSG and HbA1c. The present finding of null association is hardly due to the range of dietary GI. In our study, median index across quartile of GI ranged from 50.6 to 66.7 and these values did not differ much from the studies that have found a significant association between dietary GI and risk of diabetes.28, 29, 30, 31 Energy intake has a positive effect on glycemic control in diabetic patients32 and high intake of dietary fiber is associated with lower fasting blood glucose and HbA1c.33 However, after further adjustment for energy or dietary fiber intake, the results did not change. The association with GL but not GI suggests that the amounts of carbohydrate and GI of foods should be considered simultaneously, as represented by GL, in recommended diet to effectively manage glycemic control in diabetic patients.
This study had some limitations. We could not infer causality because of the observational nature of our study. We assessed diet using a validated FFQ. Measurement errors may be introduced by the under- or overreporting of the amounts of food groups usually eaten per day. GIs were estimated on the basis of the international and Iranian tables of GI. Thus, the effect of varying degree of ripeness, processing and chewing on food GIs is a concern.34 Another possible source of measurement error is that we focused only on dietary fiber consumption without regarding the amount of fiber supplements. However, we would expect these to bias results toward the null. In addition, one limitation of the study is the possibility of participant’s weight change before including in the study and our study only addresses the association controlling for weight at time of measuring dietary intake and glycemic control factors. However, we did not find any interaction between GL and BMI. This study had several strengths. We measured known potential confounders and were able to control for them in our analyses.
In conclusion, our findings suggest that GL which describes quality and quantity of carbohydrate consumption, and also the total carbohydrate intake significantly influence glycemic control in type 2 diabetic patients. But benefit in pursuing a low-GI diet without considering carbohydrate and energy intakes in patients with type 2 diabetes should be further investigated.
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This work was supported by a grant from the National Nutrition and Food Technology Research Institute, Tehran, Iran.
The authors declare no conflict of interest.
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Farvid, M., Homayouni, F., Shokoohi, M. et al. Glycemic index, glycemic load and their association with glycemic control among patients with type 2 diabetes. Eur J Clin Nutr 68, 459–463 (2014). https://doi.org/10.1038/ejcn.2013.288
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