Sex-specific clustering of metabolic risk factors and their association with incident cardiovascular diseases: A population-based prospective study

Abstract

Background and aimsWe identified distinct patterns of metabolic risk factors (MRF), and examined their association with subsequent cardiovascular disease (CVD) risk. MethodsThe study sample included 8113 participants (45% men) aged ≥30 years. Self-organizing map (SOM) was applied to clustering of five dichotomized MRF in men and women. MRF were included: low estimated glomerular filtration rate (eGFR), high fasting plasma glucose (FPG), high total cholesterol (TC), high systolic blood pressure (SBP) and high body mass index (BMI). The association between clusters membership and age, education, smoking status, physical activity level and family history (FH) of premature CVD was estimated using multinomial logistic regression. Cox regression was used to estimate the relation of each cluster with CVD events. ResultsSOM identified seven distinct clusters of MRF in both men and women. About 35 and 44% of men and women, respectively, had ≥3 MRF. Among men, MRF were clustered in those with older age, low physical activity, lower education and FH of premature CVD; while, among women, clustering was observed in past smoker, those with older age and positive FH of premature CVD. In the male population, a cluster with 100% high SBP and high FPG, had the highest risk for CVD events. However, among women, two clusters, each with 100% high FPG, yielded the highest and similar risk for CVD. ConclusionsSOM identified multiple patterns of MRF in the Iranian population. The results may be useful for targeting efforts to promote strategies to reduce the risk of CVD in the Iranian population.