Mahal Subeg, Kucha Christopher, Kwofie Ebenezer M, Ngadi Michael
Department of Bioresource Engineering, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Department of Food Science and Technology, University of Georgia, Athens, GA, United States.
Front Nutr. 2024 Mar 21;11:1195799. doi: 10.3389/fnut.2024.1195799. eCollection 2024.
The purpose of the current study was to critically assess the gaps in the existing methodologies of dietary data collection for diet diversity indicators. The study proposed the importance of smartphone application to overcome the drawbacks. The review paper identified and assessed the conventional methodologies used in diet diversity indicators including Minimum Dietary Diversity for Women (MDD-W), Minimum Dietary Diversity of Infant and Young Child Feeding Practices (IYCF-MDD), and Household Dietary Diversity Score (HDDS). The 80 research studies from 38 countries were critically assessed on the basis of their research aim, study design, target audience, dietary data collection methodology, sample size, dietary data type, dietary data collection frequency, and location point of dietary data collection. Results indicated that most studies employed interviewer-administered 24-h recall assessing the dietary diversity. The review paper concluded that smartphone application had potential to overcome the identified limitations of conventional methodologies including recall bias, social-desirability bias, interviewer training, and cost-time constraints.
本研究的目的是严格评估饮食多样性指标现有饮食数据收集方法中的差距。该研究提出了智能手机应用对于克服这些缺点的重要性。这篇综述论文识别并评估了用于饮食多样性指标的传统方法，包括妇女最低饮食多样性（MDD-W）、婴幼儿喂养实践中的最低饮食多样性（IYCF-MDD）以及家庭饮食多样性得分（HDDS）。基于来自38个国家的80项研究的研究目的、研究设计、目标受众、饮食数据收集方法、样本量、饮食数据类型、饮食数据收集频率以及饮食数据收集的地点，对这些研究进行了严格评估。结果表明，大多数研究采用了由访谈员进行的24小时回顾法来评估饮食多样性。综述论文得出结论，智能手机应用有潜力克服传统方法中已识别出的局限性，包括回忆偏差、社会期望偏差、访谈员培训以及成本-时间限制。
