Understanding Causation and Association

A principal objective of epidemiology is to understand whether exposures to specific agents are associated with disease or other health outcomes and, with additional available information, to decide whether such associations are causal. Although they are frequently used synonymously, the terms “association” and “causation” have distinct meanings.

Epidemiologic studies can establish statistical associations between exposure to specific agents and health effects. In the types of epidemiologic studies described earlier in this chapter, the degree of an association is often measured by relative risks, odds ratios, and SMRs. Epidemiologic studies find different degrees of association, depending on the magnitude of the relative risk, odds ratio, or SMR, and its variability and on the ability to exclude or reduce sources of error. To conclude that an association exists, it is necessary for an agent to occur together with the health outcome more frequently than expected by chance alone. Further, it is almost always necessary to find that the effect occurs consistently in several studies. Epidemiologists seldom consider one study, taken alone, sufficient to establish an association; rather, it is necessary to replicate the findings in other studies in order to draw conclusions about the association. Results from separate studies sometimes conflict with one another. It is sometimes possible to attribute discordant study results to characteristics such as the soundness of study design, the quality of execution, and the influence of different forms of error and bias. Studies that result in a statistically significant measure of association account for the role of chance in producing the observed result. When the measure of association does not show a statistically significant effect, it is important to consider the size of the sample and whether the study had the power to detect a rare but important effect.

Study designs differ in their ability to provide a valid estimate of an association (Ellwood, 1998). Randomized controlled trials are the most robust type of evidence, whereas cohort or case-control studies are more susceptible to chance, bias, and confounding. Case series and case reports carry the least weight, but may be the only information available, especially for an extremely rare event (e.g., a hypersensitivity reaction). For most of the agents reviewed in this report, the committee had to rely on case series and case reports because more robust epidemiologic studies were not available.

Determining whether a given statistical association rises to the level of causation requires inference (Hill, 1971). In order to infer a causal association, one must bring together evidence from different studies and apply well-established criteria that have been refined over more than a century (Hill, 1971; Evans, 1976; Wegman et al., 1997). The criteria for inferring a causal relationship are strength of association, dose–response relationship, consistency of association, temporal relationship, specificity of association, and biological plausibility (as discussed above). Strictly speaking, assessing causality was not within the charge of this committee, but the criteria for causality were helpful as the com-

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