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Cardiovascular disease lead the cause of death world wide and several studieshave been carried out to understand and explore cardiovascular risk markers innormoglycemic and diabetic populations. In this work, we explore theassociation structure between hyperglycemic markers and cardiovascular riskmarkers controlled by triglycerides, body mass index, age and gender, for thenormoglycemic population in The Mexico City Diabetes Study. Understanding theassociation structure could contribute to the assessment of additionalcardiovascular risk markers in this low income urban population with a highprevalence of classic cardiovascular risk biomarkers. The association structureis measured by conditional Kendall's tau, defined through conditional copulafunctions. The latter are in turn modeled under a fully Bayesian nonparametricapproach, which allows the complete shape of the copula function to vary fordifferent values of the controlled covariates.

A Copula-based Fully Bayesian Nonparametric Evaluation of Cardiovascular Risk Markers in the Mexico City Diabetes Study