Association between dietary glycemic index, glycemic load, and body mass index in the Inter99 study: Is underreporting a problem?

Steno Diabetes Center, Gentofte, Denmark.
American Journal of Clinical Nutrition (Impact Factor: 6.77). 10/2006; 84(3):641-5.
Source: PubMed


The few studies examining the potential associations between glycemic index (GI), glycemic load (GL), and body mass index (BMI) have provided no clear pictures. Underreporting of energy intake may be one explanation for this.
We examined the associations between GI, GL, and BMI by focusing on the confounding factor of total energy intake and the effect of exclusion of low energy reporters (LERs).
This was a cross-sectional study of 6334 subjects aged 30-60 y. Dietary intake was estimated from a food-frequency questionnaire. GI and GL were estimated by using white bread as the reference food. Underreporting of energy intake was assessed as reported energy intake divided by basal metabolic rate (EI/BMR); LERs were defined as those having an EI/BMR < 1.14. Univariate and multiple linear regression models were used to test for associations between GI, GL, and BMI. The confounders were sex, age, smoking, physical activity, alcohol intake, and energy intake. All analyses were conducted on 1) the entire population and 2) a subsample excluding LERs.
In the univariate analyses of the entire population, GL was inversely associated with BMI. No association was observed for GI. After full adjustment (including energy intake), both GI and GL were positively associated with BMI. When LERs were excluded, GL was positively associated with BMI in all analyses, and GI was positively associated with BMI in the multiple analyses.
We showed a positive association between GI, GL, and BMI. Energy adjustment and the exclusion of LERs significantly affected the results of the analysis; thus, we stress the importance of energy adjustment.

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    • "For calculating glycemic load, the amount of GI is multiplied by carbohydrate amount in gram.[13] Several studies have been conducted on the relationship of these two indices with obesity in adults and have reported a direct, neutral or reverse relationship, and their results were controversial.[141516171819] DASH diet is one of the investigated topics that appear to have a low level of GI due to having high fruit, vegetable and whole grain ingredients.[20] "
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    ABSTRACT: Several evidences have been reported so far in terms of the relationship between obesity and glycemic index and glycemic load in children. However, the number of review studies that have dealt with recent findings is quite low. The purpose of present study is to review the existing evidences in this regard. FIRST OF ALL, THE PHRASES: "Glycaemic index", "Glycaemic load", "Glycemic index" OR "Glycemic load" accompanied by one of the words: "Adolescent", "Young", "Youth" "Children" OR "Child" were searched in texts of articles existing in ISI and PUBMED databases which were obtained out of 1001 articles. Among these, some articles, which reviewed the relationship of obesity with glycemic index and glycemic load, were selected. Finally, 20 articles were studied in current review study. The majority of cross-sectional studies have found children's obesity directly linked with glycemic index and glycemic load; however, cohort studies found controversial results. Also, the intervention studies indicate the negative effect of glycemic index and glycemic load on obesity in children. Published evidences reported inconsistent results. It seems that existing studies are not sufficient and more studies are needed in this regard.
    Full-text · Article · Jan 2014
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    • "This study was conducted on both genders with an age range of 7 to 13 years, with different pubertal status. Although a few studies have reported an inverse association between GI and tight intramuscular fat, as an obesity indicator [11], more evidence indicates that there may be a positive relationship between GI and obesity among adults [12,13]. Clinical trials have illustrated inconsistent results. "
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    ABSTRACT: Although several studies have assessed the influence of the glycemic index on body weight and blood pressure among adults, limited evidence exists for the pediatric age population. In the current study, we compared the effects of low glycemic index (LGI) diet to the healthy nutritional recommendation (HNR)-based diet on obesity and blood pressure among adolescent girls in pubertal ages. This 10-week parallel randomized clinical trial comprised of 50 overweight or obese and sexually mature girls less than 18 years of age years, who were randomly assigned to LGI or HNR-based diet. Macronutrient distribution was equivalently prescribed in both groups. Blood pressure, weight and waist circumference were measured at baseline and after intervention. Of the 50 participants, 41 subjects (include 82%) completed the study. The GI of the diet in the LGI group was 42.67 ± 0.067. A within-group analysis illustrated that in comparison to the baseline values, the body weight and body mass index (not waist circumference and blood pressure) decreased significantly after the intervention in both groups (P = 0.0001). The percent changes of the body weight status, waist circumference and blood pressure were compared between the two groups and the findings did not show any difference between the LGI diet consumers and those in the HNR group. In comparison to the HNR, LGI diet could not change the weight and blood pressure following a 10-week intervention. Further longitudinal studies with a long-term follow up should be conducted in this regard.
    Full-text · Article · Oct 2013 · Nutrition research and practice
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    • "However, the bias introduced by underreporting and the measurement error tends to be non-differential with respect to the outcomes, which tends to attenuate the association. Moreover, because total energy adjustments have been reported to potentially reduce the bias caused by underreporting [46-48], we have adjusted for the total energy intake in all the models. Also, a validation study showed a good agreement between the DHQ and the dietary records for GI and GL [32]. "
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    ABSTRACT: Dietary glycemic index or load is thought to play an important role in glucose metabolism. However, few studies have investigated the relation between glycemic index (GI) or load (GL) and glycemia in Asian populations. In this cross-sectional analysis of a randomized controlled trial, the Saku Control Obesity Program, we examined the relation between the baseline GI or GL and glycemia (HbA1c and fasting plasma glucose [FPG] levels), insulin resistance (HOMA-IR), β-cell function (HOMA-β), and other metabolic risk factors (lipid levels, diastolic and systolic blood pressure, and adiposity measures). The participants were 227 obese Japanese women and men. We used multiple linear regression models and logistic regression models to adjust for potential confounding factors such as age, sex, visceral fat area, total energy intake, and physical activity levels. After adjustments for potential confounding factors, GI was not associated with HbA1c, but GL was positively associated with HbA1c. For increasing quartiles of GI, the adjusted mean HbA1c were 6.3%, 6.7%, 6.4%, and 6.4% (P for trend = 0.991). For increasing quartiles of GL, the adjusted mean HbA1c were 6.2%, 6.2%, 6.6%, and 6.5% (P for trend = 0.044). In addition, among participants with HbA1c ≥ 7.0%, 20 out of 28 (71%) had a high GL (≥ median); the adjusted odds ratio for HbA1c ≥ 7.0% among participants with higher GL was 3.1 (95% confidence interval [CI] = 1.2 to 8.1) compared to the participants with a lower GL (<median). Further, among 16 participants with FPG ≥ 150 mg/dL, 13 participants (81.3%) had a higher GL; the adjusted odds ratio for FPG ≥ 150 mg/dL among participants with a higher GL was 8.5 (95% confidence interval = 1.7 to 43.4) compared to those with a lower GL. In contrast, GI and GL were not associated with metabolic risk factors other than glycemia. Our findings suggest that participants with poor glycemic control tend to have a higher GL in an obese Japanese population.
    Full-text · Article · Sep 2012 · Nutrition & Metabolism
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