Hill’s Criteria of Causation
Hill’s Criteria of Causation
The Epidemiologist Sir Austin Bradford Hill (1897–1991) in the year 1965 outlined the minimal conditions needed to establish a causal relationship between two items as a way to understand the causal link between specific factors e.g. smoking and lung cancer, the established criteria are equally applicable to infectious and noninfectious diseases what was called Hill’s criteria of causation
Strength of association
The larger association is more likely the causal effect this is defined by the size of the association as measured by appropriate statistical tests. The stronger the association. For example, the more highly correlated hypertension is with a increased sodium diet, the close is the relation between sodium and hypertension. The incidence of disease should be higher in those who are exposed to the factor under consideration than in those who are not exposed.
: means that the association should be observed in numerous studies, preferably by different researchers using different research methodologies. We should except consistent findings observed by different persons in different places with different samples that will strength the likelihood of an effect
refers to an association between one factor and one disease, and this association is more likely to be causal. The more specific an association between a factor and an its effect is, the higher the possibility of a causal relationship.
The effect has to occur after the cause and must also be addressed when determining cause of disease.
The biological gradient
is a dose-response relationship between increased exposure to a factor and increased likelihood of disease it is logic that greater exposure should generally lead to greater incidence of the effect. For example, the longer one smokes, the more likely one is to develop lung cancer. If the association demonstrates a biological gradient between the factor (exposure) and effect (disease), the relationship is more likely to be causal.
This criterion may be the most elusive and variable of the nine. Because biological knowledge is ever expanding, lack of biological plausibility does not necessarily disprove a theoretical association.
There should be coherence between known information about the biological spectrum of the disease and the associated factor, it is necessary to evaluate claims of causality within the context of the current state of knowledge within a given field and in related fields.
Associations derived from experiments add considerable weight to evidence supporting causal associations. These experiments can be animal model studies or clinical trials; however, although animal models may be helpful, many diseases do not manifest the same way in animals and humans.
If similar associations have been shown to be causal, by analogy the association is more likely to be causal
for more related topics you can visit the Health Care Quality section
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