Mainardi Fabio, Côté Richard G, Silber Nele Kristin, Plestina Roko, Ferrer Eldridge, Angeles-Agdeppa Imelda
Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé SA, Lausanne, Switzerland.
Food and Nutrition Research Institute, Department of Science and Technology, Gen. Santos Avenue, Bicutan, Taguig City, 1631, Philippines.
BMC Nutr. 2024 Oct 30;10(1):146. doi: 10.1186/s40795-024-00954-7.
The goal of the present study was to design an easily computable score, based on nutrient composition data instead of food groups, to evaluate the nutritional quality and balance of meals, adapted to the nutritional recommendations for Filipino adults.
The score was defined as a weighted average of 9 nutrient scores. Protein, total fat, saturated fat, free sugars were scored as % of energy; calcium, fiber, sodium, vitamin C, magnesium were scored based on the local dietary reference intakes. The scoring algorithm was an adaption of a score previously developed by the authors based on US data. In the present study, the score was applied to 69,923 meals reported by 31,218 adult Filipinos aged 20 to 59 in the 2018 edition of the Philippine Expanded National Nutrition Survey to evaluate its validity and compare against exemplary meals designed as part of 24 h diet plans that meet local dietary guidelines.
Meals from these exemplary menu plans, developed by local nutrition experts, scored on average 72.2 ± 13.9 (mean ± standard deviation) while those of survey participants scored 46.1 ± 12.9. Meal scores were significantly associated with the density of positive micronutrients (e.g., Vit A, Vit C) and favourable food groups (e.g. fruits, whole grains) not directly included in the algorithm.
The score, between 0 and 100, is a valid tool to assess the nutritional quality of meals consumed by the PH population, accounting for both shortfall and excess nutrients, adjusted for the energy content of the meal. If applied to consumer-facing applications, it could potentially help users to understand which meals are nutritionally balanced.
本研究的目的是设计一种易于计算的分数，该分数基于营养成分数据而非食物类别，以评估膳食的营养质量和均衡性，并使其符合菲律宾成年人的营养建议。
该分数被定义为9种营养分数的加权平均值。蛋白质、总脂肪、饱和脂肪、游离糖按能量百分比计分；钙、纤维、钠、维生素C、镁根据当地膳食参考摄入量计分。评分算法是作者先前基于美国数据开发的一种分数的改编版。在本研究中，该分数应用于2018年菲律宾扩大国家营养调查中31218名20至59岁成年菲律宾人报告的69923份膳食，以评估其有效性，并与作为符合当地膳食指南的24小时饮食计划一部分而设计的示范膳食进行比较。
由当地营养专家制定的这些示范菜单计划中的膳食平均得分为72.2±13.9（平均值±标准差），而调查参与者的膳食平均得分为46.1±12.9。膳食分数与算法中未直接包含的阳性微量营养素（如维生素A、维生素C）和有益食物类别（如水果、全谷物）的密度显著相关。
该分数在0到100之间，是评估菲律宾人群所食用膳食营养质量的有效工具，兼顾了营养素的不足和过量，并根据膳食的能量含量进行了调整。如果应用于面向消费者的应用程序，它可能有助于用户了解哪些膳食营养均衡。
