Glycemic index, glycemic load and glycemic response: An International Scientific Consensus Summit from the International Carbohydrate Quality Consortium (ICQC).

BACKGROUND AND AIMS: The positive and negative health effects of dietary carbohydrates are of interest to both researchers and consumers. METHODS: International experts on carbohydrate research held a scientific summit in Stresa, Italy, in June 2013 to discuss controversies surrounding the utility of the glycemic index (GI), glycemic load (GL) and glycemic response (GR). RESULTS: The outcome was a scientific consensus statement which recognized the importance of postprandial glycemia in overall health, and the GI as a valid and reproducible method of classifying carbohydrate foods for this purpose. There was consensus that diets low in GI and GL were relevant to the prevention and management of diabetes and coronary heart disease, and probably obesity. Moderate to weak associations were observed for selected cancers. The group affirmed that diets low in GI and GL should always be considered in the context of diets otherwise understood as healthy, complementing additional ways of characterizing carbohydrate foods, such as fiber and whole grain content. Diets of low GI and GL were considered particularly important in individuals with insulin resistance. CONCLUSIONS: Given the high prevalence of diabetes and pre-diabetes worldwide and the consistency of the scientific evidence reviewed, the expert panel confirmed an urgent need to communicate information on GI and GL to the general public and health professionals, through channels such as national dietary guidelines, food composition tables and food labels.

Assigning glycemic index to foods in a recent Australian food composition database.

This paper describes the compilation of a special edition of the AUSNUT2011-2013 food composition database that includes glycemic index (GI) values. A 6-step, systematic methodology was used to assign GI to 5644 foods included in AUSNUT2011-2013. A total of 1752 (31%) foods were assigned a GI of 0 owing to low carbohydrate content; 363 (6%) had a direct match in 1 of the 4 data tables used; 1738 (31%) were assigned the GI of a 'closely related' food item; 1526 (27%) were assigned the weighted mean GI of ingredients; 205 (4%) were assigned the median GI of their corresponding food subgroup; 49 (<1%) were assigned a GI of 0 because they were not a significant source of carbohydrate in typical diets; and 5 (<1%) were assigned a default GI. We propose that this database should be used for all future Australian GI research until a subsequent version/update is compiled.

A systematic methodology to estimate added sugar content of foods.

BACKGROUND/OBJECTIVES: The effect of added sugar on health is a topical area of research. However, there is currently no analytical or other method to easily distinguish between added sugars and naturally occurring sugars in foods. This study aimed to develop a systematic methodology to estimate added sugar values on the basis of analytical data and ingredients of foods. SUBJECTS/METHODS: A 10-step, stepwise protocol was developed, starting with objective measures (six steps) and followed by more subjective estimation (four steps) if insufficient objective data are available. The method developed was applied to an Australian food composition database (AUSNUT2007) as an example. RESULTS: Out of the 3874 foods available in AUSNUT2007, 2977 foods (77%) were assigned an estimated value on the basis of objective measures (steps 1-6), and 897 (23%) were assigned a subjectively estimated value (steps 7-10). Repeatability analysis showed good repeatability for estimated values in this method. CONCLUSIONS: We propose that this method can be considered as a standardised approach for the estimation of added sugar content of foods to improve cross-study comparison.