OBJECTIVE—To systematically tabulate published and unpublished sources of reliable glycemic index (GI) values. RESEARCH DESIGN AND METHODS—A literature search identified 205 articles published between 1981 and 2007. Unpublished data were also included where the data quality could be verified. The data were separated into two lists: the first representing more precise data derived from testing healthy subjects and the second primarily from individuals with impaired glucose metabolism. RESULTS—The tables, which are available in the online-only appendix, list the GI of over 2,480 individual food items. Dairy products, legumes, and fruits were found to have a low GI. Breads, breakfast cereals, and rice, including whole grain, were available in both high and low GI versions. The correlation coefficient for 20 staple foods tested in both healthy and diabetic subjects was r = 0.94 (P < 0.001). CONCLUSIONS—These tables improve the quality and quantity of GI data available for research and clinical practice.

Reliable tables of glycemic indexes (GIs) and glycemic loads (GLs) are critical to research examining the relationship between glycemic qualities of carbohydrate in foods, diets, and health. In the 12 years since the last edition of the tables, a large amount of new data has become available. To systematically review and tabulate published and unpublished sources of reliable GI values, including an assessment of the reliability of the data. This edition of the tables lists over 4000 items, a 61% increase in the number of entries compared to the 2008 edition. The data have been separated into 2 lists. The first represents more precise values derived using the methodology recommended by the International Standards Organization (∼2100 items). The second list contains values determined using less robust methods, including using limited numbers of healthy subjects or with a large SEM (∼1900 food items). Dairy products, legumes, pasta, and fruits were usually low-GI foods (≤55 on the 100-point glucose scale) and had consistent values around the world. Cereals and cereal products, however, including whole-grain or whole-meal versions, showed wide variation in GI values, presumably arising from variations in manufacturing methods. Breads, breakfast cereals, rice, savory snack products, and regional foods were available in high-, medium-, and low-GI versions. Most varieties of potato were high-GI foods, but specific low-GI varieties have now been identified. The availability of new data on the GIs of foods will facilitate wider research and application of the twin concepts of GI and GL. Although the 2021 edition of the tables improves the quality and quantity of GI data available for research and clinical practice, GI testing of regional foods remains a priority. This systematic review was registered in PROSPERO as #171204.

Despite the popularity of low-glycemic index (GI) and high-protein diets, to our knowledge no randomized, controlled trials have systematically compared their relative effects on weight loss and cardiovascular risk. A total of 129 overweight or obese young adults (body mass index, > or =25 [calculated as weight in kilograms divided by the square of height in meters]) were assigned to 1 of 4 reduced-fat, high-fiber diets for 12 weeks. Diets 1 and 2 were high carbohydrate (55% of total energy intake), with high and low GIs, respectively; diets 3 and 4 were high protein (25% of total energy intake), with high and low GIs, respectively. The glycemic load was highest in diet 1 and lowest in diet 4. Changes in weight, body composition, and blood chemistry profile were studied. While all groups lost a similar mean +/- SE percentage of weight (diet 1, -4.2% +/- 0.6%; diet 2, -5.5% +/- 0.5%; diet 3, -6.2% +/- 0.4%; and diet 4, -4.8% +/- 0.7%; P = .09), the proportion of subjects in each group who lost 5% or more of body weight varied significantly by diet (diet 1, 31%; diet 2, 56%; diet 3, 66%; and diet 4, 33%; P = .01). Women on diets 2 and 3 lost approximately 80% more fat mass (-4.5 +/- 0.5 [mean +/- SE] kg and -4.6 +/- 0.5 kg) than those on diet 1 (-2.5 +/- 0.5 kg; P = .007). Mean +/- SE low-density-lipoprotein cholesterol levels declined significantly in the diet 2 group (-6.6 +/- 3.9 mg/dL [-0.17 +/- 0.10 mmol/L]) but increased in the diet 3 group (+10.0 +/- 3.9 mg/dL [+0.26 +/- 0.10 mmol/L]; P = .02). Goals for energy distribution were not achieved exactly: both carbohydrate groups ate less fat, and the diet 2 group ate more fiber. Both high-protein and low-GI regimens increase body fat loss, but cardiovascular risk reduction is optimized by a high-carbohydrate, low-GI diet.

Background: The glycemic index (GI) characterizes foods by using the incremental area under the glycemic response curve relative to a similar amount of oral glucose. Its ability to differentiate between curves of different shapes, the peak response, and other aspects of the glycemic response is debatable.

Background: Women with polycystic ovarian syndrome (PCOS) are intrinsically insulin resistant and have a high risk of cardiovascular disease and type 2 diabetes. Weight loss improves risk factors, but the optimal diet composition is unknown. Low–glycemic index (low-GI) diets are recommended without evidence of their clinical effectiveness.

Background: Many laboratories offer glycemic index (GI) services. Objective: We assessed the performance of the method used to measure GI. Design: The GI of cheese-puffs and fruit-leather (centrally provided) was measured in 28 laboratories (n = 311 subjects) by using the FAO/WHO method. The laboratories reported the results of their calculations and sent the raw data for recalculation centrally. Results: Values for the incremental area under the curve (AUC) reported by 54% of the laboratories differed from central calculations. Because of this and other differences in data analysis, 19% of reported food GI values differed by >5 units from those calculated centrally. GI values in individual subjects were unrelated to age, sex, ethnicity, body mass index, or AUC but were negatively related to within-individual variation (P = 0.033) expressed as the CV of the AUC for repeated reference food tests (refCV). The between-laboratory GI values (mean ± SD) for cheese-puffs and fruit-leather were 74.3 ± 10.5 and 33.2 ± 7.2, respectively. The mean laboratory GI was related to refCV (P = 0.003) and the type of restrictions on alcohol consumption before the test (P = 0.006, r² = 0.509 for model). The within-laboratory SD of GI was related to refCV (P < 0.001), the glucose analysis method (P = 0.010), whether glucose measures were duplicated (P = 0.008), and restrictions on dinner the night before (P = 0.013, r² = 0.810 for model). Conclusions: The between-laboratory SD of the GI values is ≈9. Standardized data analysis and low within-subject variation (refCV < 30%) are required for accuracy. The results suggest that common misconceptions exist about which factors do and do not need to be controlled to improve precision. Controlled studies and cost-benefit analyses are needed to optimize GI methodology. The trial was registered at clinicaltrials.gov as NCT00260858.