{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T17:12:02Z","timestamp":1788541922138,"version":"build-2803163510"},"reference-count":52,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:00:00Z","timestamp":1788480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background\/Objectives: This study characterized compositional variation among 996 foods and beverages retained from the Universidad San Francisco de Quito Food Chemical Composition Table after record-level quality control. Methods: Nineteen nutritional variables were evaluated using descriptive statistics, heteroscedastic one-way analysis of variance, rank correlations, principal component analysis, and hierarchical clustering. Missingness was substantial and non-random across food groups; 427 records contained all 19 variables and were used for multivariate analyses. Results: Welch tests with Holm correction identified food-group differences for all variables, although the magnitude of group separation ranged from small for vitamin A (\u03b72 = 0.029, 95% CI 0.016\u20130.061) to large for carbohydrates (\u03b72 = 0.590, 95% CI 0.555\u20130.632) and energy (\u03b72 = 0.588, 95% CI 0.530\u20130.654). Spearman analysis showed strong expected compositional associations between total fat and monounsaturated fatty acids (\u03c1 = 0.956) and between total fat and saturated fatty acids (\u03c1 = 0.937), together with non-arithmetic associations involving protein, phosphorus, zinc, cholesterol, and vitamin B12. Parallel analysis retained four principal components, which explained 61.4% of total variance; the first two accounted for 40.2% and primarily represented energy-lipid-mineral covariation and lipid composition. Ward clustering in the full 19-dimensional standardized space supported a three-cluster solution (silhouette = 0.482; median subsampling adjusted Rand index = 0.845), comprising a broad mixed profile, a fiber- and mineral-dense profile, and an oil-dominant profile. Conclusions: These results describe compositional patterns within the USFQ database and provide a reproducible basis for database harmonization, nutrient profiling, and hypothesis generation. They do not estimate dietary intake, food availability, nutritional adequacy, or health outcomes in the Ecuadorian population.<\/jats:p>","DOI":"10.3390\/nu18172910","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T16:07:32Z","timestamp":1788538052000},"page":"2910","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Nutritional Variation Among Foods Included in an Ecuadorian Food Composition Database Using Multivariate Analysis"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9920-5919","authenticated-orcid":false,"given":"Orlando","family":"Meneses Quelal","sequence":"first","affiliation":[{"name":"Facultad de Industrias Agropecuarias y Ciencias Ambientales, Carrera de Alimentos, Universidad Polit\u00e9cnica Estatal del Carchi (UPEC), Tulc\u00e1n 040101, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1159\/000503355","article-title":"The Importance of Food Composition Data for Estimating Micronutrient Intake: What Do We Know Now and into the Future?","volume":"93","author":"Grande","year":"2020","journal-title":"Nestle Nutr. Inst. Workshop Ser."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"108962","DOI":"10.1016\/j.jfca.2026.108962","article-title":"Quantifying Nutrients and Beyond: Analytical Approaches for Food Composition Tables and Databases","volume":"151","author":"Mukunzi","year":"2026","journal-title":"J. Food Compos. Anal."},{"key":"ref_3","unstructured":"Rittenschober, D., Stadlmayr, B., Charrondiere, U.R., and Persijn, D. (2012). FAO\/INFOODS Food Composition Database for Biodiversity Version 2.0\u2014BioFoodComp2.0, FAO."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1016\/j.jfca.2006.04.006","article-title":"LATINFOODS: Food Composition Activities in Latin America (2004\u20132006)","volume":"20","author":"Menezes","year":"2007","journal-title":"J. Food Compos. Anal."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"7914","DOI":"10.3390\/nu7095373","article-title":"Standardization of the Food Composition Database Used in the Latin American Nutrition and Health Study (ELANS)","volume":"7","author":"Kovalskys","year":"2015","journal-title":"Nutrients"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Mondal, D.D., Chakraborty, U., Bera, M., Ghosh, S., and Kar, D. (2023). An Overview of Nutritional Profiling in Foods: Bioanalytical Techniques and Useful Protocols. Front. Nutr., 10.","DOI":"10.3389\/fnut.2023.1124409"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Balakrishna, Y., Manda, S., Mwambi, H., and van Graan, A. (2022). Statistical Methods for the Analysis of Food Composition Databases: A Review. Nutrients, 14.","DOI":"10.3390\/nu14112193"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Balakrishna, Y., Manda, S., Mwambi, H., and van Graan, A. (2021). Identifying Nutrient Patterns in South African Foods to Support National Nutrition Guidelines and Policies. Nutrients, 13.","DOI":"10.3390\/nu13093194"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Theodore Armand, T.P., Nfor, K.A., Kim, J.-I., and Kim, H.-C. (2024). Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Nutrition: A Systematic Review. Nutrients, 16.","DOI":"10.3390\/nu16071073"},{"key":"ref_10","unstructured":"Ortiz, J., Astudillo, G., Donoso, S., and Ochoa, A. (2026, July 18). Tabla de Composici\u00f3n de Alimentos Cuenca\u2014Ecuador 2018. Available online: https:\/\/www.researchgate.net\/publication\/336532862."},{"key":"ref_11","first-page":"209","article-title":"Revisi\u00f3n de las Tablas de Composici\u00f3n de Alimentos Usadas para Estimar la Ingesta de Nutrientes en Ecuador","volume":"43","year":"2016","journal-title":"Rev. Chil. Nutr."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Herrera Fontana, M.E., Chisaguano Tonato, A.M., Jumbo Crisanto, J.V., Castro Morillo, N.P., and Anchundia Ortega, A.P. (2021). Tabla de Composici\u00f3n Qu\u00edmica de los Alimentos: Basada en Nutrientes de Inter\u00e9s para la Poblaci\u00f3n Ecuatoriana, Universidad San Francisco de Quito USFQ Press. Available online: http:\/\/bitacora.usfq.edu.ec.","DOI":"10.18272\/ba.v11i.3326"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Micoanski, K.S., Izquierdo-Garc\u00eda, C., Huacho-J\u00e1come, A.S., Trelis, M., and Gozalbo, M. (2025). Dietary Habits and Nutritional Status in Ecuatorian Children Aged 1\u201311 Years: A Systematic Review Highlighting the Dual Burden of Malnutrition. Nutrients, 17.","DOI":"10.3390\/nu17223608"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Romero-Benavides, J.C., Guaraca-Pino, E., Duarte-Casar, R., Rojas-Le-Fort, M., and Bailon-Moscoso, N. (2023). Chenopodium quinoa Willd. and Amaranthus hybridus L.: Ancestral Andean Food Security and Modern Anticancer and Antimicrobial Activity. Pharmaceuticals, 16.","DOI":"10.3390\/ph16121728"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s12963-017-0119-3","article-title":"The Share of Ultra-Processed Foods and the Overall Nutritional Quality of Diets in the US: Evidence from a Nationally Representative Cross-Sectional Study","volume":"15","author":"Popkin","year":"2017","journal-title":"Popul. Health Metr."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1017\/S1368980018003762","article-title":"Ultra-Processed Foods: What They Are and How to Identify Them","volume":"22","author":"Monteiro","year":"2019","journal-title":"Public Health Nutr."},{"key":"ref_17","unstructured":"Menchu, M.T., and Mendez, H. (2012). Tabla de Composici\u00f3n de Alimentos de Centroam\u00e9rica, Instituto de Nutrici\u00f3n de Centro Am\u00e9rica y Panam\u00e1 (INCAP)\/Organizaci\u00f3n Panamericana de la Salud (OPS). [2nd ed.]."},{"key":"ref_18","unstructured":"Reyes Garc\u00eda, M., G\u00f3mez-S\u00e1nchez Prieto, I., and Espinoza Barrientos, C. (2017). Tablas Peruanas de Composici\u00f3n de Alimentos."},{"key":"ref_19","unstructured":"Instituto Colombiano de Bienestar Familiar (2026, July 18). Tabla de Composici\u00f3n de Alimentos Colombianos, Available online: https:\/\/www.icbf.gov.co\/system\/files\/tcac_web.pdf."},{"key":"ref_20","unstructured":"Ministerio de Salud y Deportes (2005). Tabla Boliviana de Composici\u00f3n de Alimentos."},{"key":"ref_21","unstructured":"U.S. Department of Agriculture, Agricultural Research Service (2026, July 18). FoodData Central, Available online: https:\/\/fdc.nal.usda.gov."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.foodchem.2017.03.103","article-title":"EuroFIR Guideline on Calculation of Nutrient Content of Foods for Food Business Operators","volume":"238","author":"Machackova","year":"2018","journal-title":"Food Chem."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"111368","DOI":"10.1016\/j.fct.2020.111368","article-title":"Evaluating Missing Value Imputation Methods for Food Composition Databases","volume":"141","author":"Ispirova","year":"2020","journal-title":"Food Chem. Toxicol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Little, R.J.A., and Rubin, D.B. (2020). Statistical Analysis with Missing Data, Wiley. [3rd ed.].","DOI":"10.1002\/9781119482260"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3661","DOI":"10.1080\/10408398.2020.1810624","article-title":"Dairy Intake and Bone Health Across the Lifespan: A Systematic Review and Expert Narrative","volume":"61","author":"Wallace","year":"2021","journal-title":"Crit. Rev. Food Sci. Nutr."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zhao, T., Liu, S., Zhang, R., Zhao, Z., Yu, H., Pu, L., Wang, L., and Han, L. (2022). Global Burden of Vitamin A Deficiency in 204 Countries and Territories from 1990\u20132019. Nutrients, 14.","DOI":"10.2139\/ssrn.4005132"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Perna, M., and Hewlings, S. (2022). Saturated Fatty Acid Chain Length and Risk of Cardiovascular Disease: A Systematic Review. Nutrients, 15.","DOI":"10.3390\/nu15010030"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Ajomiwe, N., Boland, M., Phongthai, S., Bagiyal, M., Singh, J., and Kaur, L. (2024). Protein Nutrition: Understanding Structure, Digestibility, and Bioavailability for Optimal Health. Foods, 13.","DOI":"10.3390\/foods13111771"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Obeid, R., Heil, S.G., Verhoeven, M.M.A., van den Heuvel, E.G.H.M., de Groot, L.C.P.G.M., and Eussen, S.J.P.M. (2019). Vitamin B12 Intake From Animal Foods, Biomarkers, and Health Aspects. Front. Nutr., 6.","DOI":"10.3389\/fnut.2019.00093"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"10319","DOI":"10.29219\/fnr.v68.10319","article-title":"Sodium\u2014A Systematic Review for Nordic Nutrition Recommendations 2023","volume":"68","author":"Jula","year":"2024","journal-title":"Food Nutr. Res."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Lakens, D. (2013). Calculating and Reporting Effect Sizes to Facilitate Cumulative Science: A Practical Primer for t-Tests and ANOVAs. Front. Psychol., 4.","DOI":"10.3389\/fpsyg.2013.00863"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1037\/1082-989X.8.4.434","article-title":"Generalized Eta and Omega Squared Statistics: Measures of Effect Size for Some Common Research Designs","volume":"8","author":"Olejnik","year":"2003","journal-title":"Psychol. Methods"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"20150202","DOI":"10.1098\/rsta.2015.0202","article-title":"Principal Component Analysis: A Review and Recent Developments","volume":"374","author":"Jolliffe","year":"2016","journal-title":"Philos. Trans. R. Soc. A"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","article-title":"Hierarchical Grouping to Optimize an Objective Function","volume":"58","author":"Ward","year":"1963","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1007\/s00357-014-9161-z","article-title":"Ward\u2019s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward\u2019s Criterion?","volume":"31","author":"Murtagh","year":"2014","journal-title":"J. Classif."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3559","DOI":"10.1007\/s00394-022-02903-1","article-title":"Effect of Different Food Groups on Energy Intake Within and Between Individuals","volume":"61","author":"Horgan","year":"2022","journal-title":"Eur. J. Nutr."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1111\/j.1753-4887.2010.00304.x","article-title":"Water, Hydration and Health","volume":"68","author":"Popkin","year":"2010","journal-title":"Nutr. Rev."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1111\/nbu.12280","article-title":"Dietary Energy Density: Applying Behavioural Science to Weight Management","volume":"42","author":"Rolls","year":"2017","journal-title":"Nutr. Bull."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"20441","DOI":"10.1021\/acsomega.2c01833","article-title":"Iron Absorption: Factors, Limitations, and Improvement Methods","volume":"7","author":"Piskin","year":"2022","journal-title":"ACS Omega"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Nsabimana, S., Ismail, T., and Lazarte, C.E. (2024). Enhancing Iron and Zinc Bioavailability in Maize (Zea mays) Through Phytate Reduction: The Impact of Fermentation Alone and in Combination with Soaking and Germination. Front. Nutr., 11.","DOI":"10.3389\/fnut.2024.1478155"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Carbonaro, M., and Nucara, A. (2022). Legume Proteins and Peptides as Compounds in Nutraceuticals: A Structural Basis for Dietary Health Effects. Nutrients, 14.","DOI":"10.3390\/nu14061188"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/S0140-6736(18)31809-9","article-title":"Carbohydrate Quality and Human Health: A Series of Systematic Reviews and Meta-Analyses","volume":"393","author":"Reynolds","year":"2019","journal-title":"Lancet"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Yanni, A.E., Iakovidi, S., Vasilikopoulou, E., and Karathanos, V.T. (2024). Legumes: A Vehicle for Transition to Sustainability. Nutrients, 16.","DOI":"10.3390\/nu16010098"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"102366","DOI":"10.1016\/j.eclinm.2023.102366","article-title":"Global Heterogeneity in Folic Acid Fortification Policies and Implications for Prevention of Neural Tube Defects and Stroke: A Systematic Review","volume":"67","author":"Quinn","year":"2024","journal-title":"eClinicalMedicine"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1002\/osp4.657","article-title":"Ultra-Processed Foods: Processing Versus Formulation","volume":"9","author":"Levine","year":"2023","journal-title":"Obes. Sci. Pract."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e062809","DOI":"10.1136\/bmjopen-2022-062809","article-title":"Health and Economic Burden of Disease of Sugar-Sweetened Beverage Consumption in Four Latin American and Caribbean Countries: A Modelling Study","volume":"13","author":"Alcaraz","year":"2023","journal-title":"BMJ Open"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Ferraz de Arruda, H., Aleta, A., and Moreno, Y. (2023). Food Composition Databases in the Era of Big Data: Vegetable Oils as a Case Study. Front. Nutr., 9.","DOI":"10.3389\/fnut.2022.1052934"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2962","DOI":"10.1017\/S136898001900226X","article-title":"Local Traditional Foods Contribute to Diversity and Species Richness of Rural Women\u2019s Diet in Ecuador","volume":"22","author":"Penafiel","year":"2019","journal-title":"Public Health Nutr."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Cordero-Ahiman, O.V., Vanegas, J.L., Franco-Crespo, C., Beltr\u00e1n-Romero, P., and Quinde-Lituma, M.E. (2021). Factors That Determine the Dietary Diversity Score in Rural Households: The Case of the Paute River Basin of Azuay Province, Ecuador. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18042059"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Maluf, R.S., Burlandy, L., Cintr\u00e3o, R.P., Tribaldos, T., and Jomalinis, E. (2024). Food Systems and Access to Healthy Food in an Amazonian Context. Sustainability, 16.","DOI":"10.3390\/su16072652"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Mahal, S., Kucha, C., Kwofie, E.M., and Ngadi, M. (2024). A Systematic Review of Dietary Data Collection Methodologies for Diet Diversity Indicators. Front. Nutr., 11.","DOI":"10.3389\/fnut.2024.1195799"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Delgado, A., Issaoui, M., Vieira, M.C., Saraiva de Carvalho, I., and Fardet, A. (2021). Food Composition Databases: Does It Matter to Human Health?. Nutrients, 13.","DOI":"10.3390\/nu13082816"}],"container-title":["Nutrients"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6643\/18\/17\/2910\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T16:13:26Z","timestamp":1788538406000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6643\/18\/17\/2910"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,4]]},"references-count":52,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["nu18172910"],"URL":"https:\/\/doi.org\/10.3390\/nu18172910","relation":{},"ISSN":["2072-6643"],"issn-type":[{"value":"2072-6643","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,4]]}}}