Jimmy Chun-Yu Louie1, Victoria Flood2, Nicole Turner3, Christopher Everingham4, Josephine Gwynn4. 1. Cluster for Public Health Nutrition, Boden Institute of Obesity, Nutrition and Exercise, The University of Sydney NSW, Australia. 2. Cluster for Public Health Nutrition, Boden Institute of Obesity, Nutrition and Exercise, The University of Sydney NSW, Australia. Electronic address: vflood@uow.edu.au. 3. Durri Aboriginal Medical Service, Kempsey NSW, Australia. 4. School of Medicine and Public Health, The University of Newcastle, Callaghan NSW, Australia.
Abstract
OBJECTIVE: To describe a standardized method to assign glycemic index (GI) values to food items, obtained from 3 x 24-h recalls among Aboriginal and Torres Strait Islander and non-Indigenous Australian children, which can be adapted for use with simple food composition databases. METHODS: Four published GI databases were used as the source of GI values. Changes were made to a previously published methodology for GI value assignment to accommodate the needs of the Many Rivers Diabetes Prevention Project. RESULTS: There were 1132 food items in the recall database. Two hundred nineteen (19.3%) food items were directly linked to the FoodWorks GI database and 545 (48.1%) items were assigned the GI value of a "closely related" food item in the four GI databases used. Among the top carbohydrate contributors, 113 (35.3%) items have a direct linkage with the FoodWorks GI database. The mean ± SEM dietary GI and glycemic load (GL) of the study population resulting from this methodology are 57.5 ± 0.3 and 143.4 ± 2.6, respectively. CONCLUSION: This simple method provides opportunities for countries without food composition database that are comprehensive for GI/GL but which contain accurate information on carbohydrates in foods to assign high-quality GI values to food items in epidemiological studies based on 24-h recalls.
OBJECTIVE: To describe a standardized method to assign glycemic index (GI) values to food items, obtained from 3 x 24-h recalls among Aboriginal and Torres Strait Islander and non-Indigenous Australian children, which can be adapted for use with simple food composition databases. METHODS: Four published GI databases were used as the source of GI values. Changes were made to a previously published methodology for GI value assignment to accommodate the needs of the Many Rivers Diabetes Prevention Project. RESULTS: There were 1132 food items in the recall database. Two hundred nineteen (19.3%) food items were directly linked to the FoodWorks GI database and 545 (48.1%) items were assigned the GI value of a "closely related" food item in the four GI databases used. Among the top carbohydrate contributors, 113 (35.3%) items have a direct linkage with the FoodWorks GI database. The mean ± SEM dietary GI and glycemic load (GL) of the study population resulting from this methodology are 57.5 ± 0.3 and 143.4 ± 2.6, respectively. CONCLUSION: This simple method provides opportunities for countries without food composition database that are comprehensive for GI/GL but which contain accurate information on carbohydrates in foods to assign high-quality GI values to food items in epidemiological studies based on 24-h recalls.
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