The gap between evidence discovery and actual causal relationships

The concept of causation in epidemiology can be illuminated by situating the discussion within a more general concept of causation in biology: “a causal relationship is one that has a mechanism that by its operation makes a difference”. Mechanism and difference-making are complementary, and discovery can proceed from either direction; each type of evidence can be qualitative or quantitative. An explanation becomes fully convincing only when supported by both. In biology, causation is typically stochastic and/or multiple. Multiple causation can be analysed statistically/epidemiologically, even though it is not truly (ontologically) stochastic. This requires some degree of regularity in the outcome variable, plus sufficient variation in the exposure(s). The analysis then demonstrates co-variations between exposure(s) and outcome that regularly occur. Rose′s important distinction of “causes of incidence” and “causes of cases” should be reconceptualised in terms of epidemiological visibility, raising the possibility of epidemiological “dark matter”.

► This paper analyses causation in epidemiology within a broader concept of causation. ► The suggested concept involves both a mechanism and making a difference. ► These are complementary, and evidence on causal relationships can come from either. ► Epidemiology requires some degree of regularity in the outcome variable. ► Epidemiologic visibility depends on the amount of variation in the exposure variable.