Drewnowski Adam, Gupta Shilpi, Darmon Nicole
Center for Public Health Nutrition, University of Washington, Box 353410, Seattle, WA 98195, USA.
MOISA, INRA, Univ Montpellier, CIRAD, CIHEAM-IAMM, Montpellier SupAgro, Montpellier, France.
Nutr Today. 2020 Mar-Apr;55(2):75-81. doi: 10.1097/nt.0000000000000400.
The category of "ultra-processed" foods in the NOVA food classification scheme is ostensibly based on industrial processing. We compared NOVA category assignments with the pre-existing family of Nutrient Rich Food (NRF) indices, first developed in 2005. NRF indices are composed of two subscores; the positive NRn based on protein, fiber, and n vitamins and minerals, and the negative LIM subscore based on saturated fat, added sugar, and sodium. The 378 foods that were components of the widely used Fred Hutchinson Cancer Center food frequency questionnaire were assigned to NOVA categories and scored using multiple NRF indices. Contrary to published claims, NOVA was largely based on the foods' content of saturated fat, added sugars, and sodium. There were strong similarities between NOVA categories and NRF scores that were largely driven by the foods' content of fat, sugar, and salt. Nutrient density increased NRF scores but had less impact on NOVA categories. As a result, the NOVA scheme misclassified some nutrient-rich foods. Both NOVA categories and NRF scores were strongly affected by the amounts of saturated fat, added sugars, and sodium. Ultra-processed foods and culinary ingredients received lower NRF scores. We conclude that the arbitrary NOVA classification scheme adds little to the pre-existing nutrient profiling models. The purported links between NOVA categories and health outcomes could have been obtained using pre-existing NRF nutrient density metrics.
在NOVA食品分类体系中,“超加工”食品类别表面上是基于工业加工划分的。我们将NOVA类别划分与2005年首次制定的现有营养丰富食品(NRF)指数系列进行了比较。NRF指数由两个子分数组成;基于蛋白质、纤维以及多种维生素和矿物质的正向NRn,以及基于饱和脂肪、添加糖和钠的负向LIM子分数。对广泛使用的弗雷德·哈钦森癌症中心食物频率问卷中的378种食物进行了NOVA类别划分,并使用多种NRF指数进行评分。与已发表的说法相反,NOVA在很大程度上是基于食物中饱和脂肪、添加糖和钠的含量。NOVA类别与NRF分数之间存在很强的相似性,这在很大程度上是由食物中的脂肪、糖和盐含量驱动的。营养密度提高了NRF分数,但对NOVA类别影响较小。因此,NOVA体系对一些营养丰富的食物进行了错误分类。饱和脂肪、添加糖和钠的含量对NOVA类别和NRF分数都有很大影响。超加工食品和烹饪原料的NRF分数较低。我们得出结论,随意的NOVA分类体系对现有的营养成分分析模型贡献不大。NOVA类别与健康结果之间所谓的联系,使用现有的NRF营养密度指标本就可以得出。