S L Cooper1, F E Pelly1, J B Lowe1. 1. School of Health and Sport Sciences, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Maroochydore, Queensland, Australia.
Abstract
BACKGROUND/ OBJECTIVES: Nutrient profiling models classify the healthiness of foods based on their nutritional composition and provide the science that underlies nutrition signposting schemes. The two objectives were to examine the construct validity of the Health Star Rating (HSR) system by determining its diagnostic accuracy and to detect the optimal HSR cutoff points to define healthiness in packaged dairy foods. We hypothesised that ultra-processed dairy, defined by NOVA, would have less stars (less healthy) and non-ultra-processed dairy would have more stars (more healthy). SUBJECTS/ METHODS: The diagnostic accuracy of the HSR system used for 621 dairy foods for sale in an Australian regional supermarket was investigated. The healthiness of packaged dairy was measured using the NOVA food classification system. RESULTS: The dairy beverages model was found to discriminate between healthy and less healthy dairy beverages as classified by NOVA (AUC: 0.653; 95% CI: 0.556-0.750; P=0.005). A receiver operating characteristic curve analysis for dairy beverages demonstrated that the optimal cutoff point corresponded to a rating of four stars. There was no discrimination power when using the HSR for predicting the health value of yoghurt and other dairy, or cheeses. CONCLUSIONS: At the optimal cutoff point of four stars the HSR has a high sensitivity but a low specificity to correctly classify healthy packaged dairy beverages, as defined by NOVA. We provide evidence to support the construct validity of the HSR model for dairy beverages, but not for the models used for yoghurts and other dairy products, or cheeses.
BACKGROUND/ OBJECTIVES: Nutrient profiling models classify the healthiness of foods based on their nutritional composition and provide the science that underlies nutrition signposting schemes. The two objectives were to examine the construct validity of the Health Star Rating (HSR) system by determining its diagnostic accuracy and to detect the optimal HSR cutoff points to define healthiness in packaged dairy foods. We hypothesised that ultra-processed dairy, defined by NOVA, would have less stars (less healthy) and non-ultra-processed dairy would have more stars (more healthy). SUBJECTS/ METHODS: The diagnostic accuracy of the HSR system used for 621 dairy foods for sale in an Australian regional supermarket was investigated. The healthiness of packaged dairy was measured using the NOVA food classification system. RESULTS: The dairy beverages model was found to discriminate between healthy and less healthy dairy beverages as classified by NOVA (AUC: 0.653; 95% CI: 0.556-0.750; P=0.005). A receiver operating characteristic curve analysis for dairy beverages demonstrated that the optimal cutoff point corresponded to a rating of four stars. There was no discrimination power when using the HSR for predicting the health value of yoghurt and other dairy, or cheeses. CONCLUSIONS: At the optimal cutoff point of four stars the HSR has a high sensitivity but a low specificity to correctly classify healthy packaged dairy beverages, as defined by NOVA. We provide evidence to support the construct validity of the HSR model for dairy beverages, but not for the models used for yoghurts and other dairy products, or cheeses.
Authors: Carlos Augusto Monteiro; Geoffrey Cannon; Jean-Claude Moubarac; Ana Paula Bortoletto Martins; Carla Adriano Martins; Josefa Garzillo; Daniela Silva Canella; Larissa Galastri Baraldi; Maluh Barciotte; Maria Laura da Costa Louzada; Renata Bertazzi Levy; Rafael Moreira Claro; Patrícia Constante Jaime Journal: Public Health Nutr Date: 2015-07-24 Impact factor: 4.022
Authors: Christina A Roberto; Marie A Bragg; Marlene B Schwartz; Marissa J Seamans; Aviva Musicus; Nicole Novak; Kelly D Brownell Journal: Am J Prev Med Date: 2012-08 Impact factor: 5.043
Authors: Maria Laura da Costa Louzada; Ana Paula Bortoletto Martins; Daniela Silva Canella; Larissa Galastri Baraldi; Renata Bertazzi Levy; Rafael Moreira Claro; Jean-Claude Moubarac; Geoffrey Cannon; Carlos Augusto Monteiro Journal: Rev Saude Publica Date: 2015-07-10 Impact factor: 2.106