Medin Anine Christine, Gulowsen Stine Rambekk, Groufh-Jacobsen Synne, Berget Ingunn, Grini Ida Synnøve, Varela Paula
Kristiansand Norway, Department of Nutrition and Public Health, Faculty of Health and Sport Sciences, University of Agder, Priority Research Centre Lifecourse Nutrition, Kristiansand, Norway.
Nofima AS, Ås, Norway.
Food Nutr Res. 2025 Jun 16;69. doi: 10.29219/fnr.v69.12217. eCollection 2025.
Ultra-processed foods (UPFs) are associated with negative health outcomes, but current classification systems, including the dominant NOVA system, are typically not suitable for identifying which factors of these foods may be harmful. New ways of defining UPFs are needed to better understand how food processing affects health.
To identify classification systems that include a category for ultra-processed or highly processed foods with a focus on comparing their definitions and provide a current evaluation of available alternatives to NOVA.
A systematic literature review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, with the search strategy developed in collaboration with a university librarian. The literature search was completed on 18 December 2023, using databases Medline, Embase (via Ovid), and Web of Science. No human participants were included.
We identified six systems - NOVA, European Prospective Investigation into Cancer and Nutrition (EPIC), International Food Policy Research Institute (IFPRI), University of North Carolina (UNC), UnProcessed Pantry Project (UP3), and Siga - that categorize highly processed food or UPFs. These systems differ in structure and detail, with NOVA, EPIC, and Siga providing specific examples of processing techniques. Regarding additives, NOVA, Siga, and UP3 include them explicitly, with Siga offering the most detailed categorization based on additives and ingredients. Siga also includes quantitative measures for nutritional quality, including cut-offs for sugar, fat, and salt, while IFPRI and UP3 address nutritional quality non-quantitatively.
When comparing NOVA's UPF category with the highly processed food or UPF categories used in the other five identified systems, we found that none specifies processing techniques clearly. Both NOVA and Siga define additives unique to their UPF categories. Siga stands out by addressing the diverse risks associated with additives and offering quantitative nutritional quality criteria, thus addressing some of the criticisms of how UPFs are commonly defined.
Siga represents a valuable, but not final, step forward in classifying UPFs and could serve as a reference in developing a new operational definition for UPFs.
超加工食品（UPFs）与不良健康结果相关，但当前的分类系统，包括占主导地位的NOVA系统，通常不适用于确定这些食品的哪些因素可能有害。需要新的定义超加工食品的方法，以更好地理解食品加工如何影响健康。
确定包括超加工或高度加工食品类别的分类系统，重点比较它们的定义，并对NOVA的现有替代方案进行当前评估。
按照系统评价和Meta分析的首选报告项目（PRISMA）指南进行系统文献综述，搜索策略与大学图书馆员合作制定。文献检索于2023年12月18日完成，使用的数据库有Medline、Embase（通过Ovid）和Web of Science。未纳入人类参与者。
我们确定了六个系统——NOVA、欧洲癌症与营养前瞻性调查（EPIC）、国际粮食政策研究所（IFPRI）、北卡罗来纳大学（UNC）、未加工食品库项目（UP3）和Siga——对高度加工食品或超加工食品进行分类。这些系统在结构和细节上有所不同，NOVA、EPIC和Siga提供了加工技术的具体示例。关于添加剂，NOVA、Siga和UP3明确包括它们，Siga基于添加剂和成分提供了最详细的分类。Siga还包括营养质量的定量测量，包括糖、脂肪和盐的临界值，而IFPRI和UP3非定量地处理营养质量。
当将NOVA的超加工食品类别与其他五个确定系统中使用的高度加工食品或超加工食品类别进行比较时，我们发现没有一个系统明确规定加工技术。NOVA和Siga都定义了其超加工食品类别特有的添加剂。Siga通过解决与添加剂相关的各种风险并提供定量营养质量标准而脱颖而出，从而解决了一些对超加工食品通常定义方式的批评。
Siga是在对超加工食品进行分类方面迈出的有价值但非最终的一步，可作为制定超加工食品新操作定义的参考。
