Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, Canada; School of Nutrition, Université Laval, Québec, QC, Canada.
Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, Canada.
Adv Nutr. 2023 Nov;14(6):1499-1522. doi: 10.1016/j.advnut.2023.08.013. Epub 2023 Aug 31.
Nutrient profiling (NP) models are useful for characterizing the healthfulness of foods and for underpinning various nutrition-related public health strategies. Recently, there has been a rapid increase in the number of NP models developed by different organizations worldwide. A systematic review (SR) summarizing the key characteristics of NP models with applications in government-led nutrition policies was carried out in 2016 and published by Labonté et al. [4]. Given the continuous proliferation of NP models, the current study aimed to update this SR. Systematic searches were performed in databases of both the peer-reviewed (n = 7) and grey (n = 1) literature to identify publications related to NP published between May 2016 and September 2020. The full text of relevant publications was assessed independently by 2 reviewers to build a list of potential models. Each model was classified as "already identified in the original SR" or as "newly identified." The eligibility of the "newly identified" models, and of some models excluded from the previous SR because their details were not known at that time, were then assessed independently by 2 reviewers based on pre-established criteria. A total of 151 potential NP models were assessed for eligibility, of which 93 were "newly identified," 28 were originally excluded from the previous SR, and 30 were identified from additional online searches during the eligibility assessment stage. Twenty-six models met the inclusion criteria. Their most frequent applications were food labeling (n = 17) and regulation of food marketing to children (n = 7). They all included nutrients to limit, with sodium, saturated fat, and total sugars being the most frequently considered. Content or face validity testing was conducted for 11 (42%) of the included models. As NP models are increasingly used worldwide to support public health strategies, having an up-to-date resource listing them and detailing their characteristics is crucial. PROSPERO #CRD42021259041.
营养成分谱（NP）模型可用于描述食品的健康程度，并为各种与营养相关的公共卫生策略提供依据。最近，世界范围内不同组织开发的 NP 模型数量迅速增加。2016 年，Labonté 等人[4]进行了一项系统评价（SR），总结了应用于政府主导的营养政策的 NP 模型的主要特征，并已发表。鉴于 NP 模型的不断增多，本研究旨在更新该 SR。在同行评审数据库（n=7）和灰色文献数据库（n=1）中进行了系统检索，以确定 2016 年 5 月至 2020 年 9 月期间发表的与 NP 相关的出版物。由 2 位评审员独立评估相关出版物的全文，以建立潜在模型清单。将每个模型分为“原始 SR 中已识别”或“新识别”。然后，由 2 位评审员根据预先确定的标准，独立评估“新识别”模型以及由于当时不了解其详细信息而在前一次 SR 中排除的一些模型的资格。共有 151 个潜在 NP 模型进行了资格评估，其中 93 个是“新识别”，28 个是原始 SR 中排除的，30 个是在资格评估阶段通过额外在线搜索识别的。符合纳入标准的模型有 26 个。它们最常被应用于食品标签（n=17）和对儿童食品营销的监管（n=7）。它们都包含限制营养素，最常考虑的是钠、饱和脂肪和总糖。26 个模型中有 11 个（42%）进行了内容或表面有效性测试。由于 NP 模型在全球范围内越来越多地用于支持公共卫生策略，因此拥有一个最新的资源清单并详细说明其特征至关重要。PROSPERO #CRD42021259041。
