Nutritional Variation Among Foods Included in an Ecuadorian Food Composition Database Using Multivariate Analysis

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 (η2 = 0.029, 95% CI 0.016–0.061) to large for carbohydrates (η2 = 0.590, 95% CI 0.555–0.632) and energy (η2 = 0.588, 95% CI 0.530–0.654). Spearman analysis showed strong expected compositional associations between total fat and monounsaturated fatty acids (ρ = 0.956) and between total fat and saturated fatty acids (ρ = 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.

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Journal
Nutrients
Published
2026-09-04
DOI
https://doi.org/10.3390/nu18172910
Primary Topic
Nutritional Studies and Diet
Type
article
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article

Nutritional Variation Among Foods Included in an Ecuadorian Food Composition Database Using Multivariate Analysis

Orlando Meneses Quelal
Nutrients
Nutritional Studies and Diet
article

Nutritional Variation Among Foods Included in an Ecuadorian Food Composition Database Using Multivariate Analysis

Orlando Meneses Quelal
article en

Abstract

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 (η2 = 0.029, 95% CI 0.016–0.061) to large for carbohydrates (η2 = 0.590, 95% CI 0.555–0.632) and energy (η2 = 0.588, 95% CI 0.530–0.654). Spearman analysis showed strong expected compositional associations between total fat and monounsaturated fatty acids (ρ = 0.956) and between total fat and saturated fatty acids (ρ = 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.

NutrientsVol. 18(17)
Universidad Politécnica Estatal del Carchi (EC)
Zero hunger
Openalex Percentile: Top 8%
Nutritional Studies and Diet
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