Key result
High-risk cardiometabolic profile affects ~46% of Ecuadorian students, driven by low HDL-c and age.
Cross-Sectional (n=365)
Yes
Multivariate profiling of university students identifies distinct cardiometabolic risk clusters that vary by sex and geographical region, highlighting early metabolic vulnerability.
Cardiovascular and metabolic diseases (CMDs) are the leading causes of global mortality. While university students represent a critical demographic for early intervention, conventional univariate screenings often fail to capture the synergistic interactions between lipid abnormalities and adiposity. This study aimed to identify and characterize multidimensional cardiometabolic phenotypes in Ecuadorian university students using multivariate exploratory techniques. A cross-sectional study was conducted with 365 students from the Coastal (n = 193) and Andean (n = 172) regions of Ecuador. Lipid profiles (TC, HDL-c, LDL-c, triglycerides), body composition (body fat percentage, visceral fat via bioelectrical impedance), and blood pressure were analyzed. Data were processed using HJ-Biplot analysis for dimensional reduction and a hybrid clustering approach (Hierarchical and K-means) for population segmentation. The HJ-Biplot explained 72.3% of the total variance. The first principal component (PC1, 49.2%) was associated with morphometric size (weight, height), while the second (PC2, 23.1%) was dominated by adiposity markers (body fat and visceral fat). Three distinct clusters were identified: Cluster 0 (27.1%, predominantly female) represented a low-risk profile with the highest HDL-c (57.5 mg/dL); Cluster 1 (26.6%, majority male) exhibited an intermediate-risk profile with the highest triglycerides (117.9 mg/dL); and Cluster 2 (46.3%, almost exclusively male and Andean-dominant) presented the highest risk, characterized by the lowest HDL-c levels (41 mg/dL) and older age. In conclusion, cardiometabolic risk is heterogeneously distributed across sex and geographical regions. Multivariate profiling allows for the detection of early metabolic vulnerability that remains undetected in traditional screenings. These findings support the implementation of targeted public health strategies tailored to the specific phenotypic and regional characteristics of the university population in Ecuador.
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Valverde et al. (2026) conducted a cross-sectional in Cardiometabolic risk (n=365). Cardiometabolic risk factors was evaluated on Cardiometabolic phenotypes. Multivariate profiling identified three distinct cardiometabolic risk clusters among Ecuadorian university students, with the highest risk cluster (46.3%) characterized by low HDL-c and older age.
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