Directed acyclic graphs approach in epidemiological research: an example with NHANES II data on the relationship between skin color and heart attack

Background: Statistical methods are essential in epidemiology research, but they can generate erroneous estimates when selecting variables based only on statistical criteria. The use of directed acyclic graphs (DAG) helps to understand the causal relationships between variables and to avoid biases. Objective: Compare the estimate of the effect of skin color on heart attack obtained from two data analysis techniques: a stepwise approach based on statistical criteria and a graphical approach based on causal criteria. Methods: : Population-based cross-sectional study using data from the second National Health and Nutrition Examination Survey (NHANES II). The exposure variable was skin color (black or non-black) and the outcome was heart attack (yes or no). To identify the association between the variables, multivariate logistic regressions were carried out using the stepwise technique and the DAG-based approach. In the stepwise technique, all variables potentially related to the outcome were included in the model and a forward or backward algorithm was used. In the DAG-based approach, different possible causal models were developed between the variables, identifying confounding, mediation, and collision factors. The models were created considering self-rated health as a confounding or collider variable, and the modeling results were verified. Results: : A total of 10.351 adults were evaluated, the majority female (52.1%), aged 20 to 39 years (48.5%), and with non-black skin color (90.4%). The prevalence of heart attack was 3.0%, and 45% rated their health as good, fair or poor. Using different modeling techniques, no association was found between skin color and heart attack (p>0.05), except when self-rated health, a collider variable, was included in the models. In this case, there was an inverse and biased association between the two variables, indicating a collision bias (stepwise-backward-OR: 0.48; 95%CI: 0.33-0.70; stepwise-forward-OR: 0.64; 95%CI: 0.44-0.94). Conclusion: Skin color was not associated with heart attack when controlling for appropriate confounding factors. However, when adjusting for self-rated health, a colliding variable, there was an inverse and distorted association between the two variables, indicating a collider bias. The DAG-based approach can avoid this bias by correctly identifying confounding factors and colliders.