J C Y Louie1, H Moshtaghian2, S Boylan3, V M Flood4, A M Rangan5, A W Barclay6, J C Brand-Miller7, T P Gill3. 1. 1] School of Medicine, Faculty of Science, Medicine and Health, The University of Wollongong, Wollongong, NSW, Australia [2] Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, The University of Sydney, Sydney, NSW, Australia [3] School of Molecular Bioscience, The University of Sydney, Sydney, NSW, Australia. 2. School of Medicine, Faculty of Science, Medicine and Health, The University of Wollongong, Wollongong, NSW, Australia. 3. Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, The University of Sydney, Sydney, NSW, Australia. 4. 1] Faculty of Health Sciences, The University of Sydney, Sydney, NSW, Australia [2] St Vincent Hospital, Sydney, NSW, Australia. 5. School of Molecular Bioscience, The University of Sydney, Sydney, NSW, Australia. 6. 1] School of Molecular Bioscience, The University of Sydney, Sydney, NSW, Australia [2] Australian Diabetes Council, Glebe, NSW, Australia. 7. 1] Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, The University of Sydney, Sydney, NSW, Australia [2] School of Molecular Bioscience, The University of Sydney, Sydney, NSW, Australia.
Abstract
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.
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.
Authors: Ying Bao; Rachael Stolzenberg-Solomon; Li Jiao; Debra T Silverman; Amy F Subar; Yikyung Park; Michael F Leitzmann; Albert Hollenbeck; Arthur Schatzkin; Dominique S Michaud Journal: Am J Clin Nutr Date: 2008-08 Impact factor: 7.045
Authors: V M Rodrigues; M Rayner; A C Fernandes; R C de Oliveira; R P C Proença; G M R Fiates Journal: Int J Obes (Lond) Date: 2016-09-28 Impact factor: 5.095
Authors: M I Mesana; A Hilbig; O Androutsos; M Cuenca-García; J Dallongeville; I Huybrechts; S De Henauw; K Widhalm; A Kafatos; E Nova; A Marcos; M González-Gross; D Molnar; F Gottrand; L A Moreno Journal: Eur J Nutr Date: 2016-11-29 Impact factor: 5.614
Authors: Jimmy Chun Yu Louie; Hanieh Moshtaghian; Anna M Rangan; Victoria M Flood; Timothy P Gill Journal: Eur J Nutr Date: 2015-09-16 Impact factor: 5.614