Competing Risk of Death and Time-Varying Covariates in Cardiovascular Epidemiologic Research: Modeling the Hazards of Coronary Heart Disease in the First National Health and Nutrition Examination Survey Epidemiologic Follow-Up Study

Authors

  • Rodrigue Pierre Institute of Public Health Florida Agricultural and Mechanical University, Tallahassee, Florida
  • C. Brown Institute of Public Health Florida Agricultural and Mechanical University, Tallahassee, Florida
  • Charlotte Baker Department of Population Health Sciences, Virginia Tech University, Tallahassee, Florida
  • Matthew Dutton College of Pharmacy and Pharmaceutical Sciences, Economic, Social, and Administrative Pharmacy Division, Florida Agricultural and Mechanical University, Tallahassee, Florida
  • Oghenekome Onokpise College of Agriculture and Food Science, Florida Agricultural and Mechanical University, Tallahassee, Florida
  • Brian Hickey Department of Health, Physical Education, and Recreation, Florida Agricultural and Mechanical University, Tallahassee, Florida

DOI:

https://doi.org/10.22158/mshp.v3n1p20

Abstract

Competing risk of death and time-varying covariates, often overlooked during statistical analyses of longitudinal studies, can alter the magnitude of estimates of the effect of covariates on the hazards of health outcomes. This study aimed to investigate whether estimates obtained when modeling the effect of risk factors on the hazards of coronary heart disease (CHD) varied significantly while accounting for the presence of competing risk of death and time-varying covariates. We used data from the First National Health and Nutrition Examination Survey Epidemiologic Follow-Up Study (n=6346) to model estimates of the effect of risk factors on the hazards of CHD using Cox proportional hazards model, Cox extension with time-varying covariates, and the Fine Gray approach. We used a chi-square test to compare coefficient estimates obtained from the three modeling techniques. We obtained a P-value > 0.05 when comparing coefficient estimates for body mass index, age, cholesterol, smoking, and diabetes after fitting the three models. Coefficient estimates obtained when modeling the effect of risk factors on the hazards of CHD did not vary significantly in the presence of competing risk of death and time-varying covariates. Researchers should consider exploring these concepts more systematically in cohort studies with cardiovascular outcomes.

Published

2018-12-26

Issue

Section

Articles