Glycemic load comes of age.

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 1 To whom correspondence should be addressed. E-mail: david.ludwig@tch.harvard. edu.