According to Lengerich (2018), a confounder is an extraneous variable that partially accounts for the observed effect of a risk factor on the status of disease status (Lengerich, 2018). In evaluating the conditions needed for confounding to occur, there are three conditions. These three conditions that must be present include the confounding factor being associated with both the risk factor of interest and the outcome, the confounder not being an intermediary step in the causal pathway from the exposure of interest to the outcome of interest and finally, the confounding factor is distributed unequally among the groups being compared.In epidemiology, the ability to understand confounding is critical in determining what inferences can be drawn from the findings of a study and examples of this can be seen in the “Multicausality: Confounding – Assignment,” by Schoenbach. Based on the “Multicausality: Confounding – Assignment,” by Schoenbach, there are two significant insights that can be learned about confounding. In evaluating this assignment, the first insight you can see is that in a cohort study, it is possible to have many confounders that may lead to disease. An example of this can be seen in question 1 in which focuses on the association between reserpine, hypertension, obesity and breast cancer. Although in this question, reserpine, hypertension, and obesity are three confounders in this question, it is also important to state that these confounders risk factors for heart disease.Secondly, another significant insight that can be learned about confounding is that confounders can also be surrogates/markers for other causes of diseases. Based on the “Multicausality: Confounding – Assignment,” by Schoenbach, this can be seen through question 2 in which the levels of copper smelters (low SO2 and High SO2) and levels forced expiratory volume (low FEV1) are confounders for the development of chronic obstructive pulmonary disease (COPD). Overall, when looking at the “Multicausality: Confounding – Assignment,” by Schoenbach, it is important to state that the two examples stated in this paper all meet the three conditions that must be present in order for confounding to occur.ReferencesLengerich, E. (. ). (2018). 3.5 – bias, confounding and effect modification | STAT 507. Penn State Eberly college of science (). State College, PA: The Pennsylvania State University. Retrieved from https://newonlinecourses.science.psu.edu/stat507/node/34/
