Causation and causal inference

This chapter provides an introduction to causal inference theory for public health research. Causal inference can be viewed as a prediction problem, addressing the question of what the likely outcome will be under one action vs. an alternative action. To answer this question usefully requires clarity and precision in both the statement of the causal hypothesis and the techniques used to attempt an answer. This chapter reviews considerations that have been invoked in discussions of causality based on epidemiologic evidence. It then describes the potential-outcome (counterfactual) framework for cause and effect, which shows how measures of effect and association can be distinguished. The potential-outcome framework illustrates problems inherent in attempts to quantify the changes in health expected under different actions or interventions. The chapter concludes with a discussion of how research findings may be translated into policy.