Fig. 1A–C.

Possible scenarios of confounding are shown. One-way arrows describe a causal relationship; two-way arrows describe an association. (A) The association between exposure (E) and outcome (O) is partially confounded by the confounder (C). (B) The confounder (C) causes the outcome (O). Because exposure (E) and C are associated, looking at E and O only, there is a spurious association. An example for this is the association of coffee drinking and pancreatic cancer, which actually is the result of the associations between coffee drinking and smoking and smoking and pancreatic cancer. (C) Again, there is a spurious association between exposure (E) and outcome (O) resulting from the confounder (C). In this case, however, there is no causal relationship between C and O; C is a surrogate for the causal variables x, y, z. An example would be area of residence as a confounder, which is a surrogate for lifestyle, environmental exposure, and access to medical treatment.