![[Feedback]](/icons/banner/feedbackACT.gif){kind=icon}
![[For Subscribers]](/icons/banner/subscriberACT.gif){kind=icon}
![[Archive]](/icons/banner/archiveACT.gif){kind=icon}
![[Search]](/icons/banner/searchACT.gif){kind=icon}
![[Contents]](/icons/banner/tocACT.gif){kind=icon}
|
|
|
|
|
||
Department of Medicine, Children’s Hospital, Boston, MA 02115
1To whom correspondence should be addressed. E-mail: david.ludwig{at}tch.harvard.edu.
See related article: J. Nutr. 133: 2728-2732, 2003.
Diet can be categorized according to a great number of biological and physicochemical properties. A key challenge in the formulation of nutritional recommendations is to identify which of these properties have the greatest relevance to health promotion and disease prevention. An article in the current issue of The Journal of Nutrition addresses this issue in relation to dietary carbohydrate (1).
With the recent recognition of the physiological importance of postprandial hyperglycemia, renewed attention has been focused on carbohydrate, the only nutrient that directly alters blood glucose concentration. For individuals with diabetes, postprandial blood glucose may influence metabolic control and risk for complications more strongly than does fasting blood glucose (2). For individuals without diabetes, even moderate elevations in postprandial blood glucose can place metabolic and oxidative stress on the pancreatic B-cell and the cardiovascular system, potentially increasing risk for type 2 diabetes and heart disease (3,4). Therefore, it is of particular interest to quantify the effects of dietary carbohydrate on the glycemic response to food.
Throughout much of the last century, carbohydrate was classified as complex or simple in the belief that saccharide chain length determines the rates of digestion and absorption (5). However, many starchy foods raise blood glucose as much as or more than comparable amounts of table sugar, leading David Jenkins and colleagues at the University of Toronto to propose the concept of glycemic index (GI) in 1981 (6). GI refers to the effect of standard amounts of individual foods (containing 50 g of available carbohydrate) on blood glucose compared with that of a control food. Most of the foods at the base of the USDA’s Food Guide Pyramid (bread, breakfast cereals and rice) and potato products are rapidly hydrolyzed into glucose in the human digestive tract and therefore have a high GI, whereas nonstarchy vegetables, fruits, legumes and nuts generally have a low GI (7). Because foods and meals differ in carbohydrate content, Walter Willett and colleagues at Harvard defined the glycemic load (GL) in 1997 as the arithmetic product of GI and carbohydrate amount (8).
To date, 15 epidemiological studies have examined the relationship between GL and chronic diseases (8–22). GL is associated with several cardiovascular disease risk factors, including low HDL cholesterol (12,14), high triglycerides (14) and elevated C-reactive protein (15). GL appears to be an independent risk factor for myocardial infarction (10), type 2 diabetes (8,9) and cancer (11,13,16,17,19,20) in many but not all analyses (18,21,22). Several recent reviews have explored the physiological mechanisms that might link GL to disease processes (23–26).
Though endorsed by many official health agencies around the world, the principles underlying GL have not been recognized by any governmental or professional entity in the United States. The American Diabetes Association, in a recent review of existing evidence, concluded that glycemic responses to foods may differ, but that "the total amount of carbohydrate in meals and snacks is more important than the source or type" (27). Another concern is that GL, a mathematical concept, has not been physiologically validated as a reliable measure of glycemic response.
To address this controversy, Jennie Brand-Miller at the University of Sydney and colleagues conducted two feeding studies involving healthy young adults (1). In the first study, subjects were given 10 different foods, each calculated to have a GL equal to a serving of white bread, but among which GI and carbohydrate amounts varied threefold. For 9 of these foods, the measured area under the glucose-over-time curve was not different from that for white bread. In the second study, subjects consumed 8 foods, again with different GI and carbohydrate amounts. Each food was consumed in portion sizes calculated to have the GL of 1, 2, 3, 4 or 6 servings of white bread. Incremental increases in GL produced step-wise increases in measured area under the glucose and insulin curves. These results demonstrate that calculated GL can predict the glycemic response to individual foods across a wide range of portion sizes, and call into question the conventional strategy of "carbohydrate counting" for controlling blood glucose levels. GL would seem to be a much better predictor than carbohydrate amount alone, because similar glycemic responses were observed among foods differing in available carbohydrate by more than twofold. This finding is consistent with Wolever and Bolognesi (28) who fed subjects 5 mixed meals of varying macronutrient composition and concluded that both GI and carbohydrate amount are necessary to explain most of the observed variability in glycemic response.
Two study limitations should be noted. First, applicability of these findings to populations at greatest risk for diseases associated with insulin resistance (the obese, the elderly, certain racial/ethnic groups and individuals with diabetes) is not known. Second, these experiments involved individual foods; the ability of GL to predict blood glucose response to mixed meals remains to be determined. However, on both points, a study by Wolever and Mehling provides reassurance (29). They randomly assigned subjects with impaired glucose tolerance to a high carbohydrate/high GI control diet or to one of two experimental diets in which GL was reduced by decreasing either total carbohydrate or GI. After 4 mo, mean plasma glucose concentrations over 8 h were lowered by the same amount (0.35 mmol/L) on the low carbohydrate and low GI diets compared with controls.
The ultimate relevance of GL depends upon whether this dietary factor independently predicts disease risk in well-controlled epidemiological studies, and whether incorporation of GL principles into interventional studies produces significant improvements in clinical endpoints. Regarding the first point, as discussed above, a growing number of studies have found associations between GL and important health outcomes that are independent of, and stronger than, those for carbohydrate amount. Regarding the second point, no large scale long-term interventional studies have yet examined GL as a primary aim. However, recent reports of greater weight loss, improved cardiovascular disease risk factors and increased insulin sensitivity on very low carbohydrate (thus, low GL) diets compared with low fat diets may be relevant (30). Such diets might promote satiety and facilitate a negative energy balance by reducing postprandial glucose and insulin responses, as previously discussed with respect to GI and GL (23,25). Nevertheless, in the longest of these studies, substantial weight regain occurred on the very low carbohydrate diet at 1 y, suggesting that subjects eventually have difficulty following such severely restrictive prescriptions. Alternatively, one might lower GL in a much less restrictive fashion with moderate reductions in total carbohydrate and GI; a 30% decrease in both would produce a 51% reduction in GL (1 - 0.7 x 0.7). Along these lines, we recently conducted a pilot study with 16 obese adolescents who were randomly assigned to an ad libitum reduced GL or an energy-restricted reduced fat diet (31). Subjects in both groups made the intended dietary changes in response to outpatient counseling, but only those on the reduced GL diet lost a significant amount of weight after 12 mo. Of particular interest, no weight regain occurred in the reduced GL group between 6 and 12 mo. Thus, low GI/GL diets may constitute an optimal compromise between low fat diets on one hand, and very low carbohydrate diets on the other.
Finally, it is worth noting that two modifications of the Food Guide Pyramid could produce significant reductions in GL and also advance other nutritional goals: moving highly processed grain products and potatoes closer to the apex; and placing nonstarchy vegetables, legumes and fruit at the base.
Manuscript received 27 June 2003. Revision accepted 2 July 2003.
 |
LITERATURE CITED |
|---|
 TOP LITERATURE CITED |
|---|
1. Brand-Miller, J. C., Thomas, M., Swan, V., Ahmad, Z. I., Petocz, P. & Colagiuri, S. (2003) Physiological validation of the concept of glycemic load in lean young adults. J. Nutr. 133:2728-2732.
2. Hanefeld, M. & Temelkova-Kurktschiev, T. (2002) Control of post-prandial hyperglycemia–an essential part of good diabetes treatment and prevention of cardiovascular complications. Nutr. Metab. Cardiovasc. Dis. 12:98-107.[Medline]
3. Coutinho, M., Gerstein, H. C., Wang, Y. & Yusuf, S. (1999) The relationship between glucose and incident cardiovascular events. A metaregression analysis of published data from 20 studies of 95,783 individuals followed for 12.4 years. Diabetes Care 22:233-240.
4. Lefebvre, P. J. & Scheen, A. J. (1998) The postprandial state and risk of cardiovascular disease. Diabet. Med. 15:S63-S68.
5. Allen, F. M. (1920) Experimental studies on diabetes: production and control of diabetes in the dog: effects of carbohydrate diets. J. Exp. Med. 31:381-402.[Abstract]
6. Jenkins, D. J., Wolever, T. M., Taylor, R. H., Barker, H., Fielden, H., Baldwin, J. M., Bowling, A. C., Newman, H. C., Jenkins, A. L. & Goff, D. V. (1981) Glycemic index of foods: a physiological basis for carbohydrate exchange. Am. J. Clin. Nutr. 34:362-366.
7. Foster-Powell, K., Holt, S. H. & Brand-Miller, J. C. (2002) International table of glycemic index and glycemic load values: 2002. Am. J. Clin. Nutr. 76:5-56.
8. Salmeron, J., Manson, J. E., Stampfer, M. J., Colditz, G. A., Wing, A. L. & Willett, W. C. (1997) Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. J. Am. Med. Assoc. 277:472-477.[Abstract]
9. Salmeron, J., Ascherio, A., Rimm, E. B., Colditz, G. A., Spiegelman, D., Jenkins, D. J., Stampfer, M. J., Wing, A. L. & Willett, W. C. (1997) Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 20:545-550.[Abstract]
10. Liu, S., Willett, W. C., Stampfer, M. J., Hu, F. B., Franz, M., Sampson, L., Hennekens, C. H. & Manson, J. E. (2000) A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Am. J. Clin. Nutr. 71:1455-1461.
11. Augustin, L. S., Dal Maso, L., La Vecchia, C., Parpinel, M., Negri, E., Vaccarella, S., Kendall, C. W., Jenkins, D. J. & Francesch, S. (2001) Dietary glycemic index and glycemic load, and breast cancer risk: a case-control study. Ann. Oncol. 12:1533-1538.
12. Ford, E. S. & Liu, S. (2001) Glycemic index and serum high-density lipoprotein cholesterol concentration among US adults. Arch. Intern. Med. 161:572-576.
13. Franceschi, S., Dal Maso, L., Augustin, L., Negri, E., Parpinel, M., Boyle, P., Jenkins, D. J. & La Vecchia, C. (2001) Dietary glycemic load and colorectal cancer risk. Ann. Oncol. 12:173-178.
14. Liu, S., Manson, J. E., Stampfer, M. J., Holmes, M. D., Hu, F. B., Hankinson, S. E. & Willett, W. C. (2001) Dietary glycemic load assessed by food-frequency questionnaire in relation to plasma high-density-lipoprotein cholesterol and fasting plasma triacylglycerols in postmenopausal women. Am. J. Clin. Nutr. 73:560-566.
15. Liu, S., Manson, J. E., Buring, J. E., Stampfer, M. J., Willett, W. C. & Ridker, P. M. (2002) Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. Am. J. Clin. Nutr. 75:492-498.
16. Michaud, D. S., Liu, S., Giovannucci, E., Willett, W. C., Colditz, G. A. & Fuchs, C. S. (2002) Dietary sugar, glycemic load, and pancreatic cancer risk in a prospective study. J. Natl. Cancer Inst. 94:1293-1300.
17. Slattery, M. L., Curtin, K., Ma, K., Edwards, S., Schaffer, D., Anderson, K. & Samowitz, W. (2002) Diet activity, and lifestyle associations with p53 mutations in colon tumors. Cancer Epidemiol. Biomarkers Prev. 11:541-548.
18. Stevens, J., Ahn, K., Juhaeri, , Houston, D., Steffan, L. & Couper, D. (2002) Dietary fiber intake and glycemic index and incidence of diabetes in African-American and white adults: the ARIC study. Diabetes Care 25:1715-1721.
19. Augustin, L. S., Gallus, S., Bosetti, C., Levi, F., Negri, E., Franceschi, S., Dal Maso, L., Jenkins, D. J., Kendall, C. W. & La Vecchia, C. (2003) Glycemic index and glycemic load in endometrial cancer. Int. J. Cancer 105:404-407.[Medline]
20. Augustin, L. S., Polesel, J., Bosetti, C., Kendall, C. W., La Vecchia, C., Parpinel, M., Conti, E., Montella, M., Franceschi, S., Jenkins, D. J. & Dal Maso, L. (2003) Dietary glycemic index, glycemic load and ovarian cancer risk: a case-control study in Italy. Ann. Oncol. 14:78-84.
21. Jonas, C. R., McCullough, M. L., Teras, L. R., Walker-Thurmond, K. A., Thun, M. J. & Calle, E. E. (2003) Dietary glycemic index, glycemic load, and risk of incident breast cancer in postmenopausal women. Cancer Epidemiol. Biomarkers Prev. 12:573-577.
22. Terry, P. D., Jain, M., Miller, A. B., Howe, G. R. & Rohan, T. E. (2003) Glycemic load, carbohydrate intake, and risk of colorectal cancer in women: a prospective cohort study. J. Natl. Cancer Inst. 95:914-916.
23. Ebbeling, C. B. & Ludwig, D. S. (2001) Treating obesity in youth: should dietary glycemic load be a consideration?. Adv. Pediatr. 48:179-212.[Medline]
24. Liu, S. & Willett, W. C. (2002) Dietary glycemic load and atherothrombotic risk. Curr. Atheroscler. Rep. 4:454-461.[Medline]
25. Ludwig, D. S. (2002) The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. J. Am. Med. Assoc. 287:2414-2423.
26. Willett, W., Manson, J. & Liu, S. (2002) Glycemic index, glycemic load, and risk of type 2 diabetes. Am. J. Clin. Nutr. 76:274S-280S.
27. Franz, M. J., Bantle, J. P., Beebe, C. A., Brunzell, J. D., Chiasson, J. L., Garg, A., Holzmeister, L. A., Hoogwerf, B., Mayer-Davis, E., Mooradian, A. D., Purnell, J. Q. & Wheeler, M. (2002) Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications. Diabetes Care 25:148-198.
28. Wolever, T. M. & Bolognesi, C. (1996) Prediction of glucose and insulin responses of normal subjects after consuming mixed meals varying in energy, protein, fat, carbohydrate and glycemic index. J. Nutr. 126:2807-2812.
29. Wolever, T. M. & Mehling, C. (2003) Long-term effect of varying the source or amount of dietary carbohydrate on postprandial plasma glucose, insulin, triacylglycerol, and free fatty acid concentrations in subjects with impaired glucose tolerance. Am. J. Clin. Nutr. 77:612-621.
30. Bonow, R. O. & Eckel, R. H. (2003) Diet, obesity, and cardiovascular risk. N. Engl. J. Med. 348:2057-2058.
31. Ebbeling, C. B., Leidig, M. M., Sinclair, K. B., Hangen, J. P. & Ludwig, D. S. (2003) A reduced-glycemic load diet in the treatment of adolescent obesity. Arch. Pediatr. Adolesc. Med. 157:773-779.
Related articles in J. Nutr.:
This article has been cited by other articles:
|
|
 |
|
  J. W.J. Beulens, L. M. de Bruijne, R. P. Stolk, P. H.M. Peeters, M. L. Bots, D. E. Grobbee, and Y. T. van der Schouw High Dietary Glycemic Load and Glycemic Index Increase Risk of Cardiovascular Disease Among Middle-Aged Women: A Population-Based Follow-Up Study J. Am. Coll. Cardiol., July 3, 2007; 50(1): 14 - 21. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. B Biddinger and D. S Ludwig The insulin-like growth factor axis: a potential link between glycemic index and cancer Am. J. Clinical Nutrition, August 1, 2005; 82(2): 277 - 278. [Full Text] [PDF]
|
|
|
|
|
|
C. B Ebbeling, M. M Leidig, K. B Sinclair, L. G Seger-Shippee, H. A Feldman, and D. S Ludwig Effects of an ad libitum low-glycemic load diet on cardiovascular disease risk factors in obese young adults Am. J. Clinical Nutrition, May 1, 2005; 81(5): 976 - 982. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. A. Pereira, J. Swain, A. B. Goldfine, N. Rifai, and D. S. Ludwig Effects of a Low-Glycemic Load Diet on Resting Energy Expenditure and Heart Disease Risk Factors During Weight Loss JAMA, November 24, 2004; 292(20): 2482 - 2490. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. S Ludwig and D. J Jenkins Carbohydrates and the postprandial state: have our cake and eat it too? Am. J. Clinical Nutrition, October 1, 2004; 80(4): 797 - 798. [Full Text] [PDF]
|
|
|
|
 |
|
 J. C. Brand-Miller, M. Thomas, V. Swan, Z. I. Ahmad, P. Petocz, and S. Colagiuri Physiological Validation of the Concept of Glycemic Load in Lean Young Adults J. Nutr., September 1, 2003; 133(9): 2728 - 2732. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
