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.
Building similarity graph...
Analyzing shared references across papers
Loading...
Kevin Gabriel Armijo Valverde
Edgar Rolando Morales Caluña
María Victoria Padilla Samaniego
International Journal of Environmental Research and Public Health
Universidad Estatal de Milagro
Building similarity graph...
Analyzing shared references across papers
Loading...
Valverde et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69d8946e6c1944d70ce056f5 — DOI: https://doi.org/10.3390/ijerph23040467