Bradford Hill Criteria

Temporality requires the exposure to occur before the observed outcome, making it a necessary condition for causal interpretation. An association cannot support a causal explanation when the sequence is reversed or unclear. In practice, establishing this ordering helps researchers distinguish a possible causal pathway from relationships in which the outcome may have influenced the exposure.

These considerations examine whether an association is substantial, appears across studies or settings, and changes systematically with different levels of exposure. Stronger and more consistent patterns, or a relationship that varies with exposure level, can support causal interpretation. They remain evidence to weigh alongside bias, confounding, temporality, and other considerations rather than independent proof.

Biological plausibility asks whether a proposed relationship fits relevant scientific understanding, while coherence considers whether it agrees with existing knowledge. Experimental support provides additional evidence when changes in exposure or related conditions produce informative results. Together, these considerations connect statistical observations with broader evidence, but the criteria do not require every consideration to be satisfied.

Researchers should review the available evidence across the relevant considerations, including temporality, association patterns, plausibility, coherence, and experimental support. They then judge whether chance, bias, or confounding could better explain the finding. This structured assessment organizes evidence from observational studies without turning the criteria into a mechanical statistical test or fixed scoring system.

In a statistical context, the criteria help interpret an observed association rather than replace statistical analysis. Researchers must consider whether chance, bias, or confounding could account for the relationship, then examine how the broader evidence fits together. This is especially important for observational studies, where an association alone does not establish that the exposure caused the outcome.

They are useful when researchers must interpret evidence from observational studies and decide how strongly it supports a causal explanation. The resulting assessment can inform public health decisions and identify uncertainties that warrant further research. Because the criteria organize rather than mechanically resolve evidence, they support reasoned judgment about both current findings and remaining questions.