consistent with the null value (that is, no association). If the computed confidence interval does not include 1.0, the association is said to be consistent with a positive (or negative) association.

Inferring Causality

Determining whether an observed statistical association is causal requires additional considerations that must be examined carefully in the context of the particular relationship under study. Causality cannot be established directly through observational epidemiological studies for the reasons outlined above. The issue of causality is a major concern in epidemiology and in 1965, following the Surgeon General’s report on the relationship between smoking and lung cancer, Sir Austin Bradford Hill, a British epidemiologist and statistician, described nine aspects that should be carefully considered when trying to come to a decision about whether an observed association might be causal (Hill, 1965). While all aspects are relevant in making inference about causality there is only one of the nine aspects that is truly necessary and that is temporality. The remaining eight aspects are neither necessary nor sufficient requirements for causation but do present a framework for consideration. While the committee was mindful of the Bradford Hill aspects when assigning the categories of association discussed later in the chapter, it did not use them as rigid criteria but rather guidelines to inform its conclusions about the association between deployment to the Gulf War and a particular health outcome. Aspects such as consistency, plausibility, and strength of association were discussed for each health outcome as the committee reached consensus on assigning a category of association but there was no requirement that all the aspects be met. The nine aspects are summarized below.

  • Strength of association. Hill argues that a strong association is an important consideration and in the absence of other explanations would be a marker of causation. However he also points out that the absence of a strong association does not preclude a causal relationship.

  • Consistency. If an association is observed in different studies, using different designs and in different settings then this would be supportive of a causal association.

  • Specificity. If the association is specific to a particular exposure-disease outcome combination and there is no association between the exposure and other outcomes then such a finding would favor a causal association.

  • Temporality. For an association to be causal it is essential that there be evidence that the exposure in question precedes the outcome of interest.

  • Biologic gradient. Evidence of a biological gradient (also called a dose-response relationship) between increasing levels of the exposure and increasing frequency of the outcome supports a causal association.

  • Plausibility. Hill suggested that if the observed association was biologically plausible this would add evidence for causality. He further noted, however, that if the observed association was new then biological plausibility might not be expected.

  • Coherence. Following from biological plausibility, Hill suggested that at least the observed association should not contradict known facts.

  • Experiment. An association would be judged more likely to be causal if evidence is based on randomized experiments.

  • Analogy. Hill’s final aspect for consideration was analogy: “In some circumstances it would be fair to judge by analogy.” By this, Hill referred to the effect already having been shown for another similar exposure.



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