The state of food composition databases: data attributes and FAIR data harmonization in the era of digital innovation
| dc.contributor.author | Brinkley S. | |
| dc.contributor.author | Gallo-Franco J.J. | |
| dc.contributor.author | Vázquez-Manjarrez N. | |
| dc.contributor.author | Chaura J. | |
| dc.contributor.author | Quartey N.K.A. | |
| dc.contributor.author | Toulabi S.B. | |
| dc.contributor.author | Odenkirk M.T. | |
| dc.contributor.author | Jermendi E. | |
| dc.contributor.author | Laporte M.A. | |
| dc.contributor.author | Lutterodt H.E. | |
| dc.contributor.author | Annan R.A. | |
| dc.contributor.author | Barboza M. | |
| dc.contributor.author | Amare E. | |
| dc.contributor.author | Srichamnong W. | |
| dc.contributor.author | Jaramillo-Botero A. | |
| dc.contributor.author | Kennedy G. | |
| dc.contributor.author | Bertoldo J. | |
| dc.contributor.author | Prenni J.E. | |
| dc.contributor.author | Rajasekharan M. | |
| dc.contributor.author | de la Parra J. | |
| dc.contributor.author | Ahmed S. | |
| dc.contributor.correspondence | Brinkley S. | |
| dc.contributor.other | Mahidol University | |
| dc.date.accessioned | 2025-04-12T18:28:11Z | |
| dc.date.available | 2025-04-12T18:28:11Z | |
| dc.date.issued | 2025-01-01 | |
| dc.description.abstract | Introduction: 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. Methods: 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. Results: 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. Discussion: 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. | |
| dc.identifier.citation | Frontiers in Nutrition Vol.12 (2025) | |
| dc.identifier.doi | 10.3389/fnut.2025.1552367 | |
| dc.identifier.eissn | 2296861X | |
| dc.identifier.scopus | 2-s2.0-105001980123 | |
| dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/123456789/109501 | |
| dc.rights.holder | SCOPUS | |
| dc.subject | Nursing | |
| dc.subject | Agricultural and Biological Sciences | |
| dc.subject | Medicine | |
| dc.title | The state of food composition databases: data attributes and FAIR data harmonization in the era of digital innovation | |
| dc.type | Article | |
| mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105001980123&origin=inward | |
| oaire.citation.title | Frontiers in Nutrition | |
| oaire.citation.volume | 12 | |
| oairecerif.author.affiliation | Division of Chemistry and Chemical Engineering | |
| oairecerif.author.affiliation | Ethiopian Public Health Institute | |
| oairecerif.author.affiliation | Pontificia Universidad Javeriana, Cali | |
| oairecerif.author.affiliation | Bioversity International | |
| oairecerif.author.affiliation | Kwame Nkrumah University of Science & Technology | |
| oairecerif.author.affiliation | Centro Internacional de Agricultura Tropical | |
| oairecerif.author.affiliation | Rockefeller Foundation | |
| oairecerif.author.affiliation | University of California, Davis | |
| oairecerif.author.affiliation | Mahidol University | |
| oairecerif.author.affiliation | American Heart Association | |
| oairecerif.author.affiliation | Colorado State University | |
| oairecerif.author.affiliation | Instituto Nacional de la Nutrición Salvador Zubiran | |
| oairecerif.author.affiliation | Wageningen University & Research |
