Dickie Sarah, Woods Julie, Machado Priscila, Lawrence Mark
Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia.
Curr Dev Nutr. 2022 Jul 4;6(8):nzac112. doi: 10.1093/cdn/nzac112. eCollection 2022 Aug.
Policy makers are increasingly using nutrition classification schemes (NCSs) to assess a food's health potential for informing nutrition policy actions. However, there is wide variability among the NCSs implemented and no standard benchmark against which their contrasting assessments can be validated.
This study aimed to compare the agreement of nutrient-, food-, and dietary-based NCSs in their assessment of a food's health potential within the Australian food supply, and examine the conceptual underpinnings and technical characteristics that explain differences in performance.
A dataset combining food compositional data from the Mintel Global New Products Database and the Australian Food Composition Database (AUSNUT 2011-2012) (= 7322) was assembled. Products were classified by 7 prominent NCSs that were selected as representative of one or other of ) nutrient-based NCSs [the Chilean nutrient profile model (NPM), Health Star Rating (HSR), Nutri-Score, the WHO European Region's NPM (WHO-Euro NPM), and the Pan American Health Organization's (PAHO) NPM]; ) food-based NCS (NOVA), and ) dietary-based NCS [Australian Dietary Guidelines (ADGs)].
The PAHO NPM classified the lowest proportion (22%) of products as "healthy", and the HSR the highest (63%). The PAHO NPM, NOVA, WHO-Euro NPM, and the Chilean NPM classified >50% of products as "unhealthy," and the ADGs, HSR, and Nutri-Score classified <50% of products as "unhealthy." The HSR and Nutri-Score had the highest pairwise agreement (κ = 0.7809, 89.70%), and the PAHO NPM and HSR the lowest (κ = 0.1793, 53.22%). Characteristics of NCSs that more effectively identified ultraprocessed and discretionary foods were: category-specific assessment, the classification of categories as always "healthy" or "unhealthy," consideration of level of food processing, thresholds for "risk" nutrients that do not penalize whole foods; and no allowance for the substitution of ingredients.
Wide variation was observed in agreement of the assessment of a food's health potential among the NCSs analyzed due to differing conceptual underpinnings and technical characteristics.
政策制定者越来越多地使用营养分类方案(NCS)来评估食品的健康潜力,以为营养政策行动提供信息。然而,实施的NCS之间存在很大差异,且没有标准基准可用于验证其不同评估结果。
本研究旨在比较基于营养素、食物和饮食的NCS在评估澳大利亚食品供应中食品的健康潜力方面的一致性,并研究解释性能差异的概念基础和技术特征。
收集了一个数据集,该数据集结合了英敏特全球新产品数据库和澳大利亚食品成分数据库(AUSNUT 2011 - 2012)中的食品成分数据(= 7322条)。产品由7种著名的NCS进行分类,这些NCS被选为以下一种或另一种的代表:)基于营养素的NCS [智利营养素概况模型(NPM)、健康星级评级(HSR)、营养评分、世界卫生组织欧洲区域的NPM(WHO - Euro NPM)和泛美卫生组织的(PAHO)NPM];)基于食物的NCS(NOVA),以及)基于饮食的NCS [澳大利亚饮食指南(ADG)]。
PAHO NPM将最低比例(22%)的产品归类为“健康”,而HSR将最高比例(63%)的产品归类为“健康”。PAHO NPM、NOVA、WHO - Euro NPM和智利NPM将超过50%的产品归类为“不健康”,而ADG、HSR和营养评分将不到50%的产品归类为“不健康”。HSR和营养评分的两两一致性最高(κ = 0.78