Examination of the Predictors of Subclinical Cardiovascular Disease in a Diverse Sample

Open Access
Colaco, Brendon
Graduate Program:
Health Policy and Administration
Master of Science
Document Type:
Master Thesis
Date of Defense:
Committee Members:
  • Rhonda Belue, Thesis Advisor
  • Elizabeth Farmer, Thesis Advisor
  • MESA
  • Subclinical Cardiovascular Disease
  • Predictors
Cardiovascular diseases are a complex set of diseases that affect the cardiovascular system and have fatal consequences if not identified and treated. There have been many studies that have examined risk factors for cardiovascular diseases over the years. In this thesis we examine a relatively new dataset–MESA dataset, which is the Multi Ethnic Study of Atherosclerosis for risk factors for sub clinical cardiovascular disease. We use maximal carotid artery stenosis as a marker of subclinical cardiovascular disease and treat this as our outcome variable and we look at both traditional and non traditional risk factors to estimate their effect on the risk for subclinical cardiovascular disease. We use traditional analytical methods including descriptive analyses, analyses of variance and regression analyses to estimate the risk. Our results indicate that while most of the traditionally studied risk factors do impact subclinical cardiovascular disease, there are also some non traditional factors that can be used to estimate risk. The added value of this theses is two fold: primarily it examines and identifies risk factors for subclinical disease thereby allowing us to target these risk factors even before clinical disease has begun and secondly it identifies risk factors with incremental value in predicting risk above and beyond those traditional risk factors previously reported in the literature.