Issue: October 2016
September 12, 2016
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Glycemic index unreliable predictor of glucose response in healthy adults

Issue: October 2016
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The glycemic index value of a food can vary by as much as 20% within an individual and 25% among healthy adults, with differences in HbA1c and insulin index partially explaining the variability, according to findings from a randomized controlled feeding trial.

Perspective from

“These findings suggest glycemic index has limited value in predicting how foods impact blood sugar levels,” Nirupa Matthan, PhD, a scientist at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, told Endocrine Today. “Additionally, [we] found that individual blood sugar responses after consuming a fixed amount of white bread could range across all three glycemic index categories (low, medium or high). Thus, glycemic index is impractical for use in food labeling or for dietary guidance at the individual level.”

Nirupa Matthan
Nirupa Matthan

Matthan and colleagues analyzed data from 63 healthy adults without diabetes from the greater Boston area (mean age, 49 years; 33 men; mean BMI, 27.3 kg/m²). After an overnight fast, volunteers underwent three sets of food challenges — each set including either a 500 mL glucose drink or 96.25 g white bread along with 500 mL water — in random order. Both tests provided 50 g of carbohydrates. Researchers monitored serum glucose and insulin for 5 hours after ingestion; blood samples were collected at baseline and 15, 30, 45, 60, 90, 120, 150, 180, 210, 240, 270 and 300 minutes. Glycemic index values were calculated using area under the curve (AUC) methods. Participants also completed the Community Healthy Activities Model Program questionnaire during one of the sessions and underwent a body composition scan via DXA.

The mean glycemic index value for white bread was 62.4, but there was marked variability in glycemic index values among volunteers. Mean intra-individual coefficient of variation was 20%; mean inter-individual coefficient of variation was 25%, ranging from 2% to 77%.

“Interestingly, volunteers with a low [glycemic index] value for white bread had a similar [standard deviation] to volunteers with a high glycemic index value (48 ± 14 compared with 82 ± 17), which suggests that the relation between the mean [glycemic index] value and [standard deviation] is not linear,” the researchers wrote.

Increasing sample size and the replication of reference and test foods, as well as length of

blood sampling and AUC calculation method, did not improve the coefficients of variation, according to researchers. Among the biological factors assessed, insulin index and HbA1c values explained 15% and 16% of the variability in mean glycemic index value for white bread, respectively.

In a continuation of the study, Matthan and colleagues also are assessing the variability in glycemic index values that could be introduced by differences in macronutrient (carbohydrate, protein, fat) and fiber combinations and loads, as well as by “second meal” effects and the consumption of mixed meals, Matthan said.

“Rather than focusing on the glycemic index, following the basic principles of healthy eating (emphasizing whole grains, legumes, fruits and vegetables, fish, vegetable oils and limiting red meat, full-fat dairy products, and beverages high in added sugars), along with portion control and exercise, are better ways to manage and control blood sugar.” Matthan said. – by Regina Schaffer

For more information:

Nirupa Matthan, PhD, can be reached at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, 711 Washington St., Boston MA 02111; email: nirupa.matthan@tufts.edu.

D isclosure: Matthan reports no relevant financial disclosures.