TY - JOUR
T1 - The state of food composition databases
T2 - data attributes and FAIR data harmonization in the era of digital innovation
AU - Brinkley, Sarah
AU - Gallo-Franco, Jenny J.
AU - Vázquez-Manjarrez, Natalia
AU - Chaura, Juliana
AU - Quartey, Naa K.A.
AU - Toulabi, Sahar B.
AU - Odenkirk, Melanie T.
AU - Jermendi, Eva
AU - Laporte, Marie Angélique
AU - Lutterodt, Herman E.
AU - Annan, Reginald A.
AU - Barboza, Mariana
AU - Amare, Endale
AU - Srichamnong, Warangkana
AU - Jaramillo-Botero, Andres
AU - Kennedy, Gina
AU - Bertoldo, Jaclyn
AU - Prenni, Jessica E.
AU - Rajasekharan, Maya
AU - de la Parra, John
AU - Ahmed, Selena
N1 - Publisher Copyright:
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.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - FAIR data
KW - food components
KW - food composition data
KW - food composition data management
KW - food composition database
KW - food quality
KW - metadata
KW - nutritional database
UR - http://www.scopus.com/inward/record.url?scp=105001980123&partnerID=8YFLogxK
U2 - 10.3389/fnut.2025.1552367
DO - 10.3389/fnut.2025.1552367
M3 - Article
AN - SCOPUS:105001980123
SN - 2296-861X
VL - 12
JO - Frontiers in Nutrition
JF - Frontiers in Nutrition
M1 - 1552367
ER -