Predictive Models of Atherogenic Risk in Citizens of Trujillo (Peru) Based on Associated Factors

Background/objectives: Atherogenic risk is related to lipid metabolism imbalance and the likelihood of cardiovascular disease (CVD). The purpose of this study was to determine predictive models based on physiological parameters, family history, and lifestyle for atherogenic risk, assessed by indicators such as total cholesterol (TC)/HDL, triglycerides/HDL, LDL/HDL, and non-HDL cholesterol in citizens of the city of Trujillo (Peru). Methods: A total of 267 people, recruited from September to December 2023, participated in the study. Their lipid profile, glycaemia, abdominal perimeter, and blood pressure were determined, and questionnaires were applied with questions on diet, physical activity, alcohol consumption, smoking, hours of sleep, and family history. Binary logistic regression was considered to determine prediction models for each atherogenic risk indicator. Results: High values were found for all atherogenic indicators; dietary habits were poor in 86.1%; physical activity was low in 35.2%; hours of sleep were less than 7 h in 64.4%; and alcohol and tobacco consumption were low in 8.2% and 9%, respectively. The family history of CVD corresponded to the mother, father, grandmother, and grandfather in 53.2%, 44.9%, 30.3% and 25.1%, respectively. In addition to the inclusion of BMI in the predictive models of atherogenic risk, for the case of total cholesterol/HDL, the variable grandparental history and female sex were included; for TG/HDL, low physical activity, male sex, and alcohol consumption were associated; and for LDL/HDL and non-HDL cholesterol, female sex and age were associated. Conclusion: The best prediction model for atherogenic risk is the corresponding model for TG/HDL, without ignoring the grandfather’s history of CVD and age.