Literature DB >> 28124481

A novel processed food classification system applied to Australian food composition databases.

S A O'Halloran1, K E Lacy1, C A Grimes1, J Woods1, K J Campbell1, C A Nowson1.   

Abstract

BACKGROUND: The extent of food processing can affect the nutritional quality of foodstuffs. Categorising foods by the level of processing emphasises the differences in nutritional quality between foods within the same food group and is likely useful for determining dietary processed food consumption. The present study aimed to categorise foods within Australian food composition databases according to the level of food processing using a processed food classification system, as well as assess the variation in the levels of processing within food groups.
METHODS: A processed foods classification system was applied to food and beverage items contained within Australian Food and Nutrient (AUSNUT) 2007 (n = 3874) and AUSNUT 2011-13 (n = 5740). The proportion of Minimally Processed (MP), Processed Culinary Ingredients (PCI) Processed (P) and Ultra Processed (ULP) by AUSNUT food group and the overall proportion of the four processed food categories across AUSNUT 2007 and AUSNUT 2011-13 were calculated.
RESULTS: Across the food composition databases, the overall proportions of foods classified as MP, PCI, P and ULP were 27%, 3%, 26% and 44% for AUSNUT 2007 and 38%, 2%, 24% and 36% for AUSNUT 2011-13. Although there was wide variation in the classifications of food processing within the food groups, approximately one-third of foodstuffs were classified as ULP food items across both the 2007 and 2011-13 AUSNUT databases.
CONCLUSIONS: This Australian processed food classification system will allow researchers to easily quantify the contribution of processed foods within the Australian food supply to assist in assessing the nutritional quality of the dietary intake of population groups.
© 2017 The British Dietetic Association Ltd.

Keywords:  NOVA; Processed; classification; databases; foods; ultra-processed

Mesh:

Year:  2017        PMID: 28124481     DOI: 10.1111/jhn.12445

Source DB:  PubMed          Journal:  J Hum Nutr Diet        ISSN: 0952-3871            Impact factor:   3.089


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