Anthropometric indicators of cardiovascular risk and physical fitness in the school population
DOI:
https://doi.org/10.47197/retos.v73.117825Keywords:
Physical activity , physical fitness, anthropometric indicators, logistic regression, cardiovascular riskAbstract
Introduction: Cardiovascular risk is an increasing concern in global public health. Anthropometric indicators, along with levels of physical activity and physical fitness, are key elements in predicting such risk.
Objective: To evaluate the association between anthropometric indicators and physical fitness levels in order to forecast cardiovascular risk in a school-aged population.
Methodology: A quantitative, correlational, and predictive study was conducted. Data from 414 individuals were analyzed using R software (version 4.x). Descriptive statistics and correlational analysis were applied, and binary logistic regression was used to estimate cardiovascular risk. Anthropometric measurements (weight, height, circumferences, and skinfolds) were used to calculate body mass index, waist-to-hip ratio, waist-to-height ratio, and body fat percentage. Physical activity was assessed using the PAQ-A questionnaire, and physical fitness was evaluated through the Alpha Fitness battery.
Results: 54.35% of the students were classified as inactive, and 71% presented unhealthy physical fitness levels. These factors were significantly correlated with cardiovascular risk, which showed a prevalence of 54.4%. The binary logistic regression model achieved an average AUC of 0.826 ± 0.045, demonstrating high discriminatory power, stability, and reliability.
Conclusions: Compared to international studies, this model stands out for its diagnostic accuracy, establishing itself as an effective tool for detecting cardiovascular risk in school settings.
The findings are consistent with the scientific literature available in Colombia, Latin America, Mexico, the United States, Europe, Africa, and Asia, supporting the validity of the proposed model.
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