The article by Liese et al. (1) investigated the association of glycemic index, glycemic load, and total carbohydrate and fiber intake with direct measures of insulin sensitivity, insulin secretion, and adiposity in a cohort of 979 adults with normal and impaired glucose tolerance. The authors concluded that there were no significant associations of glycemic index, glycemic load, and carbohydrate intake with any measure of insulin sensitivity or secretion.

In their study, usual dietary intake was assessed via a 114-item food frequency questionnaire (FFQ) that had been previously “validated” in a subsample of the Insulin Resistance Atherosclerosis Study (IRAS) population. Unfortunately, the validation study showed that the FFQ did not confidently predict total carbohydrate intake as assessed by repeated 24-h recall of food intake. The Pearson correlation coefficient between the two methods was only 0.37 after adjustment for energy. Furthermore, the correlation coefficients for starch and sucrose were similarly low at r = 0.33 and 0.46, respectively (2).

Is a correlation coefficient between 0.3 and 0.4 adequate for the purposes of validation? Brunner et al. (3) have suggested that a value “of about 0.5 for most nutrients and 0.8 for alcohol between methods is good evidence that the FFQ has the ability to rank individuals … according to nutrient intake.” Indeed, correlation coefficients in the order of 0.6–0.7 are more typical for energy-adjusted nutrients in FFQs (4). In the Nurses Health Study (5) and Health Professionals Follow-up Study (6), the correlation coefficient for energy-adjusted total carbohydrate was r = 0.69 (7).

Like most current FFQs, the IRAS questionnaire was not originally constructed for the purpose of measuring glycemic index, and glycemic index was not included in the original validation study. Therefore, the validity of the calculated glycemic index values is essentially unknown. However, given the relatively low correlation coefficients for quantity of total carbohydrate, starches, and sucrose, it would seem unlikely that subtle differences in the quality (i.e., glycemic index) of that carbohydrate can be accurately assessed. The authors note that correlations for carbohydrate were higher in urban non-Hispanic white subjects (<20% of the sample) and that stratification for ethnicity did not alter their conclusions. However, due to the relatively small sample size, subanalysis may not have had sufficient statistical power to detect associations.

Interestingly, observational studies that found no association between glycemic index, glycemic load, and incidence of type 2 diabetes (8,9) also had validation correlation coefficients for total carbohydrate that were <0.5. In contrast, those studies finding glycemic index, glycemic load, or both to be predictive of diabetes (5,6,10) had r values >0.6.

Given the limitations of the IRAS study in relation to its ability to accurately assess total carbohydrate intake, starches, and sucrose, we believe that the conclusions drawn from the study of Liese et al., i.e., that glycemic index and glycemic load are not related to measures of insulin sensitivity, insulin secretion, and adiposity, should be interpreted with caution.

1
Liese AD, Schulz M, Fang F, Wolever TMS, D’Agostino RB Jr, Sparks KC, Mayer-Davis EJ: Dietary glycemic index and glycemic load, carbohydrate and fiber intake, and measures of insulin sensitivity, secretion, and adiposity in the Insulin Resistance Atherosclerosis Study.
Diabetes Care
28
:
2832
–2838,
2005
2
Mayer-Davis EJ, Vitolins MZ, Carmichael SL, Hemphill S, Tsaroucha G, Rushing J, Levin S: Validity and reproducibility of a food frequency interview in a Multi-Cultural Epidemiology Study.
Ann Epidemiol
9
:
314
–324,
1999
3
Brunner E, Stallone D, Juneja M, Bingham S, Marmot M: Dietary assessment in Whitehall II: comparison of 7 d diet diary and food-frequency questionnaire and validity against biomarkers.
Br J Nutr
86
:
405
–414,
2001
4
Willett WC: Nutritional Epidemiology. 2nd ed. Oxford, U.K., Oxford University Press, 1998
5
Salmeron J, Manson JAE, Stampfer MJ, Colditz GA, Wing AL, Jenkins DJ, Wing AL, Willett WC: Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women.
JAMA
277
:
472
–477,
1997
6
Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, Stampfer MJ, Wing AL, Willett WC: Dietary fiber, glycemic load, and risk of NIDDM in men.
Diabetes Care
20
:
545
–550,
1997
7
Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willwtt WC: Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals.
Am J Epidemiol
135
:
1114
–1126,
1992
8
Meyer KA, Kushi LH, Jacobs DR Jr, Slavin J, Sellers TA, Folsom AR: Carbohydrates, dietary fiber, and incident type 2 diabetes in older women.
Am J Clin Nutr
71
:
921
–930,
2000
9
Stevens J, Ahn K, Juhaeri, Houston D, Steffan L, Couper D: Dietary fiber intake and glycemic index and incidence of diabetes in African-American and white adults: the ARIC study.
Diabetes Care
25
:
1715
–1721,
2002
10
Schulze MB, Liu S, Rimm EB, Manson JE, Willett WC, Hu FB: Glycemic index, glycemic load, and dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women.
Am J Clin Nutr
80
:
348
–356,
2004

J.C.B.-M. serves on the board of directors for Glycemic Index Limited.