In epidemiology, causality refers to the relationship between which types of variables?

• A. Independent and dependent variables
• B. Exposure and outcome
• C. Confounder and mediator
• D. Risk factor and disease

Answer: (A)

In epidemiology, causality is understood through how changing a factor that can be varied (the independent variable) relates to a change in an outcome (the dependent variable). This framing captures the idea of cause and effect: if you alter the exposure, the outcome should respond in a way that reflects a causal link, and the analysis is built around the relationship between those variable roles.

An exposure and an outcome are the core elements studied, but simply describing them as such doesn’t inherently express the modeling of a causal effect—an observed association can occur without causation. Confounders and mediators are other variables that can distort or explain the link between exposure and outcome, not the primary causal pair. A risk factor and disease describe a particular association but also don’t specify the variable roles in the causal analysis.