|Matthan, Nirupa - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|Ausman, Lynne - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|Meng, Huicui - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|Tighiouart, Hocine - Tufts - New England Medical Center|
|Lichtenstein, Alice - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
Submitted to: American Journal of Clinical Nutrition
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/25/2016
Publication Date: 9/14/2016
Citation: Matthan, N., Ausman, L., Meng, H., Tighiouart, H., Lichtenstein, A.H. 2016. Estimating the reliability of glycemic index values and potential sources of methodological and biological variability. American Journal of Clinical Nutrition. 104(4):1004-1013. doi: 10.3945/ajcn.116.137208.
Interpretive Summary: The glycemic index (GI) is a system of assigning a number to carbohydrate containing foods according to how much each food increases blood glucose (sugar) levels. Low GI foods have a value <55, medium GI foods have a value between 56 and 69, while high GI foods have a value >70. This concept was originally developed as a food selection guide for diabetic individuals to improve control of their blood glucose levels by encouraging them to select low rather than high GI foods. The assumption is that low GI foods will minimally raise blood sugar and that will lead to better metabolic health. Use of GI has gone beyond the original intent and is now being endorsed for use as a labeling tool to guide food choices to reduce chronic disease risk in the general population;however, there has been reluctance to universally adopt this system. One of the major concerns cited is that GI values, even for the same food, are not reproducible within an individual and among individuals. This was also documented in our study, We tested 63 individuals and found that the test food, white bread had a mean GI value of 62, which would put it in the medium category. However, the range of individual GI values was large, so wwhite bread would be classified as having a low value for 22 individuals (GI: 35 55), medium for 23 individuals (GI: 57 67) and high for 18 individuals (GI: 70 103). This high variability suggests that it is unlikely to be a good approach to guide individual food choices. In an attempt to reduce the variability, we increased sample size, replication of the reference and test food, and length of blood sampling, as well as calculation method. None reduced the variability. We also determined the effect of biological factors such as age, sex, body composition, lipid profile, glucose, insulin, hemoglobinA1c (HbA1c, marker of long term blood glucose control), and found that the insulin index and HbA1c values explained 15% and 16% of the variability in the mean GI value for white bread, respectively. These data indicate that glycemic control, even in healthy individuals, significantly contributes to the variability in GI value estimates, which limits its clinical and public health applicability.
Technical Abstract: Background: The utility of glycemic index (GI) values for chronic disease risk management remains controversial. While absolute GI value determinations for individual foods have been shown to vary significantly in individuals with diabetes, there is a dearth of data on the reliability of GI value determinations and potential sources of variability among healthy adults. Objective: To examine the intra and inter individual variability in glycemic response to a single food challenge, and methodological and biological factors that potentially mediate the response. Design: GI value for white bread was determined using standardized methodology in 63 volunteers free from chronic disease and recruited to differ by sex, age (18 to 85 y) and BMI (20 to 35 kg/m2). Volunteers randomly underwent 3 sets of food challenges involving glucose (reference) and white bread (test food), both providing 50g available carbohydrate. Blood glucose and insulin were monitored for 5 hours post ingestion and GI values calculated using different area under the curve (AUC) methods. Biochemical variables were measured using standard assays and body composition by dual energy X ray absorptiometry. Results: The mean (+/- SD) GI value for white bread was 62 +/- 15 calculated using the recommended method. Average intra- and inter- individual coefficient of variations (CVs) were 20% and 25%, respectively. Increasing sample size, replication of the reference and test food, and length of blood sampling, as well as AUC calculation method did not improve the CVs. Among the biological factors assessed insulin index and HbA1c values explained 15% and 16% of the variability in the mean GI value for white bread, respectively. Conclusions: These data indicate there was substantial variability in individual responses to GI value determinations, suggesting that it is unlikely to be good approach to guide food choices. Additionally, glycemic status, even in healthy individuals, significantly contributes to the variability in GI value estimates.