Forner Frank, Volkhardt Ina, Meier Toni, Christen Olaf, Stangl Gabriele I
Martin-Luther-University Halle-Wittenberg, Institute for Agricultural and Nutritional Sciences, Halle, Germany.
NutriCARD Competence Cluster for Nutrition and Cardiovascular Health, Halle-Jena Leipzig, Leipzig, Germany.
BMC Nutr. 2021 Nov 18;7(1):74. doi: 10.1186/s40795-021-00483-7.
Our objective was to develop a nutrient-based index for evaluating and improving menus in public catering. The nutriRECIPE-Index comprises 24 nutrients and nutrient groups. In developing the index, the following steps were included: setting the goals of the index, nutrient selection, target metrics and scaling, weighting, proof of concept and validation of the index. Furthermore, a unique database was created to integrate bioactive plant compounds in the assessment. An assessment of standard recipes and supposedly healthy recipes should show a significant difference in the results of the nutriRECIPE-Index. Finally, the nutriRECIPE-Index should generate similar or more specific results than existing indices such as the Nutri-Score and the Healthy Meal Index.
A whole meal cycle (comprising 6 weeks, 106 recipes and including different menu lines, partially with different side dishes) at a university canteen was analysed with the Federal Food Code (BLS) and the nutriRECIPE-Index. The Healthy Meal Index (comprising 3 nutritionally relevant items) and the Nutri-Score algorithm (comprising 7 items) were used to validate the nutrient composition and the results of the nutriRECIPE-Index.
The resulting scores of the recipes and menu lines showed substantial differences, wherein the meals of a health-promoting menu line usually received higher scores than the standard recipes. A correlation between the nutriRECIPE-Index and the Healthy Meal Index (0.604) and the Nutri-Score (0.591) was observed. The nutriRECIPE-Index was better at identifying the worst menus and could better separate mediocre menus from good menus.
The nutriRECIPE-Index is a useful and comprehensive tool for evaluating the nutritional value of recipes and is the first to consider bioactive plant compounds. Further adjustments to different target populations, settings, and cultural backgrounds are possible.
我们的目标是开发一种基于营养的指标,用于评估和改进公共餐饮中的菜单。营养食谱指数包含24种营养素和营养素组。在开发该指数时,包括以下步骤:设定指数目标、营养素选择、目标指标与缩放、加权、概念验证和指数验证。此外,还创建了一个独特的数据库,以便在评估中纳入生物活性植物化合物。对标准食谱和所谓的健康食谱进行评估,营养食谱指数的结果应显示出显著差异。最后,营养食谱指数应产生与现有指数(如营养评分和健康膳食指数)相似或更具体的结果。
使用联邦食品法典(BLS)和营养食谱指数对大学食堂的一个完整用餐周期(包括6周、106份食谱,涵盖不同菜单系列,部分配有不同配菜)进行分析。使用健康膳食指数(包括3个营养相关项目)和营养评分算法(包括7个项目)来验证营养食谱指数的营养成分和结果。
食谱和菜单系列的最终得分显示出显著差异,其中促进健康的菜单系列的餐食得分通常高于标准食谱。观察到营养食谱指数与健康膳食指数(0.604)和营养评分(0.591)之间存在相关性。营养食谱指数在识别最差菜单方面表现更好,并且能够更好地将中等菜单与优质菜单区分开来。
营养食谱指数是评估食谱营养价值的有用且全面的工具,并且是首个考虑生物活性植物化合物的指数。可以针对不同目标人群、环境和文化背景进行进一步调整。