Тhe Structure and Content of National Food Composition Databases for Population-Based Nutritional Epidemiology Studies

Introduction: National food composition databases are becoming increasingly important. They play a key role in nutritional epidemiology research and enable consumers to make informed food and dish choices by providing sciencebased information about their energy and nutritional value.

Objectives: To analyze national databases of the chemical composition of foods and dishes, to assess the completeness of information on the contents of macroand micronutrients, vitamins, minerals, and biologically active substances, to establish availability of various built-in analysis tools and the convenience of their use.

Materials and Methods: We have reviewed seven large national food composition databases for the United States, Australia, Switzerland, France, Portugal, Denmark, and the United Kingdom as of September 2025 using open sources of official information for the analysis. Database inclusion criteria were government ownership, web interface availability, and application in dietary analysis. Evaluation criteria included the number of foods and dishes, the range and completeness of the list of nutrients, the ability to download, and availability of various additional tools.

Results: We established that the most critical limitation for the majority of databases is the incomplete nutrient composition for all declared foods and dishes, which prevents an objective assessment of the dietary intake of a nutrient for which data is missing.

Conclusion: A set of criteria selected for the architecture, contents, and tools of the developed software with a user interface for processing, storing, analyzing, and verifying data on the chemical composition of food products, intended for the creation and maintenance of the Russian national food composition database, is substantiated.

1. Lordan R, Grant WB. Dietary patterns, physical activity, and lifestyle in the onset, prevention, and management of noncommunicable diseases. Nutrients. 2023;15(11):2540. doi: 10.3390/nu15112540

2. Di Cesare M, Sorić M, Bovet P, et al. The epidemiological burden of obesity in childhood: A worldwide epidemic requiring urgent action. BMC Med. 2019;17(1):212. doi: 10.1186/s12916-019-1449-8

3. Toebes B, Hesselman M, van Dijk JP, Herman J. Curbing the lifestyle disease pandemic: Making progress on an interdisciplinary research agenda for law and policy interventions. BMC Int Health Hum Rights. 2017;17(1):25. doi: 10.1186/s12914-017-0131-5

4. Delgado A, Issaoui M, Vieira MC, Saraiva de Carvalho I, Fardet A. Food composition databases: Does it matter to human health? Nutrients. 2021;13(8):2816. doi: 10.3390/nu13082816

5. Williams G, Hamilton A, Cade JE. Comparison of online food composition databases including those in nutritional assessment tools. Proc Nutr Soc. 2024;83(OCE4):E339. doi: 10.1017/S0029665124005779

6. Naaman RK, Almasaudi A, Albajri E, Naseeb M. Current use of food composition database and dietary analysis software in Saudi Arabia: A review study. J Food Compos Anal. 2023;(123(5)):105598. doi: 10.1016/j.jfca.2023.105598

7. Jansen L, Roodenburg AJ. The use of food composition data in the Choices International Programme. Food Chem. 2016;193:196-202. doi: 10.1016/j.foodchem.2015.06.082

8. Murphy SP, Charrondiere UR, Burlingame B. Thirty years of progress in harmonizing and compiling food data as a result of the establishment of INFOODS. Food Chem. 2016;193:2-5. doi: 10.1016/j.foodchem.2014.11.097

9. Scrimshaw NS. INFOODS: The international network of food data systems. Am J Clin Nutr. 1997;65(4 Suppl):1190S-1193S. doi: 10.1093/ajcn/65.4.1190S

10. Garcia V, Rona RJ, Chinn S. Effect of the choice of food composition table on nutrient estimates: A comparison between the British and American (Chilean) tables. Public Health Nutr. 2004;7(4):577-583. doi: 10.1079/phn2003555

11. Stanford J, McMahon S, Lambert K, Charlton KE, Stefoska-Needham A. Expansion of an Australian food composition database to estimate plant and animal intakes. Br J Nutr. 2023;130(11):1950-1960. doi: 10.1017/s0007114523001101

12. Zhong L, Blekkenhorst LC, Bondonno NP, et al. A food composition database for assessing nitrate intake from plant-based foods. Food Chem. 2022;394:133411. doi: 10.1016/j.foodchem.2022.133411

13. Vahid F, Hoge A, Hébert JR, Bohn T; ORISCAV working group. Association of diet quality indices with serum and metabolic biomarkers in participants of the ORIS-CAV-LUX-2 study. Eur J Nutr. 2023;62(5):2063-2085. doi: 10.1007/s00394-023-03095-y

14. Oliveira LM, Castanheira IP, Dantas MA, Porto AA, Calhau MA. Portuguese food composition database quality management system. Eur J Clin Nutr. 2010;64(Suppl 3): S53-S57. doi: 10.1038/ejcn.2010.211

15. Pakkala H, Christensen T, de Victoria IM, Presser K, Kadvan A. Harmonised information exchange between decentralised food composition database systems. Eur J Clin Nutr. 2010;64(Suppl 3):S58-S63. doi: 10.1038/ejcn.2010.212

16. Foroni F, Pergola G, Argiris G, Rumiati RI. The FoodCast research image database (FRIDa). Front Hum Neurosci. 2013;7:51. doi: 10.3389/fnhum.2013.00051

17. Shi Z, Zhu W, Lei Z, et al. Intake of added sugar from different sources and risk of all-cause mortality and cardiovascular diseases: The role of body mass index. J Nutr. 2024;154(11):3457-3464. doi: 10.1016/j.tjnut.2024.09.017

18. Lin AW, Morgan N, Ward D, et al. Comparative validity of mostly unprocessed and minimally processed food items differs among popular commercial nutrition apps compared with a research food database. J Acad Nutr Diet. 2022;122(4):825-832.e1. doi: 10.1016/j.jand.2021.10.015

19. Hinojosa-Nogueira D, Pérez-Burillo S, Navajas-Porras B, et al. Development of an unified food composition database for the European project “Stance4Health”. Nutrients. 2021;13(12):4206. doi: 10.3390/nu13124206

20. Khatibzadeh S, Saheb Kashaf M, Micha R, et al.; Global Burden of Diseases Nutrition; Chronic Diseases Expert Group (NutriCode). A global database of food and nutrient consumption. Bull World Health Organ. 2016;94(12):931-934. doi: 10.2471/BLT.15.156323

21. Durazzo A, Astley S, Kapsokefalou M, et al. Food composition data and tools online and their use in research and policy: EuroFIR AISBL contribution in 2022. Nutrients. 2022;14(22):4788. doi: 10.3390/nu14224788

22. Marconi S, Durazzo A, Camilli E, et al. Food Composition Databases: Considerations about Complex Food Matrices. Foods. 2018;7(1):2. doi: 10.3390/foods7010002

23. Bessonov VV, Bogachuk MN, Bokov DO, et al. Databases of the chemical composition of foods in the era of digital nutrition science. Voprosy Pitaniya. 2020;89(4):211-219. (In Russ.) doi: 10.24411/0042-8833-2020-10058