Sattamini Isabela F, Hanley-Cook Giles T, Frongillo Edward A, Coates Jennifer
Department of Nutrition and Food Safety, WHO, Geneva, Switzerland.
Food and Nutrition Division, FAO of the United Nations, Rome, Italy.
Curr Dev Nutr. 2025 Apr 6;9(5):107439. doi: 10.1016/j.cdnut.2025.107439. eCollection 2025 May.
Valid, sensitive healthy diet metrics that are comparable across contexts are needed for global monitoring. The healthy diets monitoring initiative identified 4 field metrics as potentially fit for purpose: global diet quality score (GDQS), global dietary recommendations score, minimum dietary diversity for women (MDD-W), and Nova ultra-processed food score.
To review whether these 4 healthy diet metrics ) accurately predict food and nutrient intakes; ) accurately differentiate the average or prevalence of food and nutrient intakes; ) respond to changes over time; ) are comparable across contexts; and ) can be collected using their proposed brief assessment methods while preserving predictive accuracy.
Peer-reviewed literature was searched and extracted from PubMed, Web of Science, and Google Scholar, including preprints and grey literature from the latter. Evidence on the accuracy of the field metrics and methods was qualitatively assessed against the aforementioned objectives, considering the underlying theory of change and study design, as well as the direction and magnitudes of the observed associations or effects.
Increments in GDQS+ and MDD-W predicted higher composite metrics of nutrient adequacy. MDD-W was sensitive to changes in nutrient intakes over time. MDD-W cutoffs showed limited variability across contexts and population groups. Higher GDQS and global dietary recommendation scores and lower Nova ultra-processed food scores were associated with lower intakes of food and nutrients to moderate. The predictive accuracy of field methods for nutrient adequacy was maintained for GDQS and MDD-W. No study explicitly investigated how field metrics differentiate averages or prevalence of reference metrics across countries.
MDD-W demonstrated comparatively stronger predictive accuracy for nutrient adequacy, with a lower burden method, than GDQS+. Further research is required to determine the predictive accuracy of field-friendly metrics measuring moderation across contexts and time. Complementary metrics that can be collected simultaneously on a large scale are needed for global monitoring.
全球监测需要在不同环境下具有可比性的有效、敏感的健康饮食指标。健康饮食监测倡议确定了4个可能符合要求的实地指标：全球饮食质量得分（GDQS）、全球膳食建议得分、妇女最低膳食多样性（MDD-W）和诺瓦超加工食品得分。
评估这4个健康饮食指标是否：）准确预测食物和营养素摄入量；）准确区分食物和营养素摄入量的平均值或流行率；）随时间变化做出反应；）在不同环境下具有可比性；）可以使用其提议的简短评估方法进行收集，同时保持预测准确性。
在PubMed、科学网和谷歌学术上搜索并提取同行评审文献，包括后者的预印本和灰色文献。根据上述目标，从变化的潜在理论和研究设计以及观察到的关联或效应的方向和大小方面，对实地指标和方法准确性的证据进行定性评估。
GDQS+和MDD-W的增加预测了更高的营养素充足综合指标。MDD-W对营养素摄入量随时间的变化敏感。MDD-W的临界值在不同环境和人群组中显示出有限的变异性。较高的GDQS和全球膳食建议得分以及较低的诺瓦超加工食品得分与适量食物和营养素的较低摄入量相关。GDQS和MDD-W的实地方法对营养素充足性的预测准确性得以保持。没有研究明确调查实地指标如何区分不同国家参考指标的平均值或流行率。
与GDQS+相比，MDD-W在测量营养素充足性方面表现出相对更强的预测准确性，且方法负担更低。需要进一步研究以确定在不同环境和时间测量适度性的实地友好型指标的预测准确性。全球监测需要能够同时大规模收集的补充指标。
