  Cardiovascular disease lead the cause of death world wide and several studies
have been carried out to understand and explore cardiovascular risk markers in
normoglycemic and diabetic populations. In this work, we explore the
association structure between hyperglycemic markers and cardiovascular risk
markers controlled by triglycerides, body mass index, age and gender, for the
normoglycemic population in The Mexico City Diabetes Study. Understanding the
association structure could contribute to the assessment of additional
cardiovascular risk markers in this low income urban population with a high
prevalence of classic cardiovascular risk biomarkers. The association structure
is measured by conditional Kendall's tau, defined through conditional copula
functions. The latter are in turn modeled under a fully Bayesian nonparametric
approach, which allows the complete shape of the copula function to vary for
different values of the controlled covariates.
