Which statement best describes the concept of causality in epidemiology?

• A. Causality can be established by a single observational study.
• B. Causality is proven only when randomized trials show a strong effect.
• C. Causality requires a temporal sequence but does not need replication.
• D. Causality requires temporal sequence and plausibility, supported by consistency across studies.

Answer: (D)

Causality in epidemiology is supported when an exposure clearly comes before the outcome, there is a biologically plausible link between them, and the association is observed consistently across different studies and populations. Temporality ensures the cause precedes the effect, which is fundamental because a supposed cause cannot produce an outcome before it exists. Plausibility asks whether there’s a reasonable biological or mechanistic explanation for how the exposure could lead to the outcome. Consistency across multiple studies reduces the influence of random chance, bias, or peculiarities of a single setting, making the link more convincing.

Think of a well-established example like smoking and lung cancer: studies consistently show that smoking precedes cancer development, the carcinogenic effects of tobacco smoke provide a plausible mechanism, and findings replicate across diverse populations and study designs. While not absolute proof—since confounding and bias can still play a role—the combination of temporality, plausibility, and consistency is the strongest framework epidemiologists use to infer causality.