Estimation of Cardiovascular Risk Based on Body Measu8rements: A Score Ahead in Primary Care

Abstract

Introduction: Cardiovascular risk is currently considered one of the most dangerous triggers of chronic diseases, as it is the cause of thousands of deaths worldwide.

Objective: To create a logistic regression model for a desktop application that estimates cardiovascular risk using anthropometric measures and different formulas, and thus identify the prevalence of cardiovascular risk in the study population.

Methods: A descriptive, observational and cross-sectional study was carried out with 169 workers from a university in southwestern Colombia, to whom anthropometric measurements such as weight, height and waist circumference were taken, applying the protocol of the International Society for the Advancement of Kinanthropometry. In addition, a structured survey was applied to collect sociodemographic data. The data were analyzed with a Minitab statistical package, using univariate description for qualitative variables as absolute and relative frequencies, as well as mean and standard deviation for quantitative variables. The resulting desktop application was made with the JAVA platform.

Results: In a population of 93 women and 76 men, a logistic regression model was found, using the quantitative predictor variables of weight and waist circumference, significantly related to the cardiovascular risk response variable, as well as the qualitative variable of gender. Applying the model, prevalence of cardiovascular risk was found to be 53.85 % in the working population of the university institution.

Conclusions: Cardiovascular risk is a phenomenon that is gaining more and more strength, while measuring weight and waist circumference is a way for determining such risk, a fact that will facilitate the prevention and control of cardiovascular diseases in the primary care level.