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ORIGINAL RESEARCH article
Front. Nutr.
Sec. Nutrition Methodology
Volume 12 - 2025 | doi: 10.3389/fnut.2025.1552367
This article is part of the Research Topic Databases and Nutrition, volume III View all 6 articles
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Food composition databases (FCDBs) are essential resources for characterizing, documenting, and advancing scientific understanding of food quality across the entire spectrum of edible biodiversity. This knowledge supports a wide range of applications with societal impact spanning the global food system. To maximize the utility of food composition data, FCDBs must adhere to criteria such as validated analytical methods, high-resolution metadata, and FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable). However, complexity and variability in food data pose significant challenges to meeting these standards. In this study, we conducted an integrative review of 35 data attributes across 101 FCDBs from 110 countries. The data attributes were categorized into three groups: general database information, foods and components, and FAIRness. Our findings reveal evaluated databases show substantial variability in scope and content, with the number of foods and components ranging from few to thousands. FCDBs with the highest numbers of food samples (≥1,102) and components (≥244) tend to rely on secondary data sourced from scientific articles or other FCDBs. In contrast, databases with fewer food samples and components predominantly feature primary analytical data generated in-house. Notably, only one-third of FCDBs reported data on more than 100 food components. FCDBs were infrequently updated, with web-based interfaces being updated more frequently than static tables. When assessed for FAIR compliance, all FCDBs met the criteria for Findability. However, aggregated scores for Accessibility, Interoperability, and Reusability for the reviewed FCDBs were 30%, 69%, and 43%, respectively. These scores reflect limitations in inadequate metadata, lack of scientific naming, and unclear data reuse notices. Notably, these results are associated with country economic classification, as databases from high-income countries showed greater inclusion of primary data, web-based interfaces, more regular updates, and strong adherence to FAIR principles. Our integrative review presents the current state of FCDBs highlighting emerging opportunities and recommendations. By fostering a deeper understanding of food composition, diverse stakeholders across food systems will be better equipped to address societal challenges, leveraging data-driven solutions to support human and planetary health.
Keywords: Food composition database, Food composition data management, Food composition data, food quality, metadata, Food components, FAIR Data, Nutritional database
Received: 27 Dec 2024; Accepted: 21 Feb 2025.
Copyright: © 2025 Brinkley, Gallo-Franco, Vázquez-Manjarrez, Chaura, Quartey, Toulabi, Odenkirk, Jermendi, Laporte, Lutterodt, Annan, Barboza, Amare, Srichamnong, Jaramillo-Botero, Kennedy, Bertoldo, Prenni, Rajasekharan, De La Parra and Ahmed. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Selena Ahmed, The Periodic Table of Food Initiative, American Heart Association, Dallas, United States
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