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Causation (Causation Criteria (Biological Gradient: This relationship…
Causation
Causation
- It’s possible to demonstrate that two variables are associated or correlated.
- This stringent process needs to be followed to provide evidence that a particular exposure causes or results in a certain health outcome
The goal of the disease detective is to determine whether a relationship between some exposure(s) and health outcome(s) is causal or otherwise.
Pathway
Indirect: The risk factor causes the disease but only with the influence of another factor or factors.
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Probabilistic Causation
- a probabilistic cause may be neither necessary nor sufficient for disease
- a cause increases the probability (or chance) that its effect will occur, by a specified amount
- The definition also does not exclude necessary and sufficient causes; a sufficient cause is one that raises the probability of its effect occurring to 1, and a necessary cause raises that probability from 0
- uses ‘statistics’ and probabilities
Causation Criteria
- Biological Gradient: This relationship occurs when changes in the level of a possible cause are associated with changes in the prevalence or incidence of the effect.
- Temporal Relationship: The cause must precede the effect, that is, the exposure must occur prior to the onset of the health outcome.
- Biological Plausibility/Analogy: Plausibility: The findings are consistent with current knowledge of both the distribution and underlying biological mechanisms of the disease.
- Specificity: A factor leads to a single effect (rather than multiple effects).
- Coherence: That a cause and effect association does not conflict with what is known of the natural history and biology of the disease
- Consistency: When the findings have been replicated by studies in different place, circumstances, times, etc.
- Experimental Evidence: The association is confirmed through controlled experiments.
- Strength of Association: The stronger the association, the more likely it is to be causal (in comparison to weak association).
Cause Model
- Necessary Cause: any component cause that is required to cause disease
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- Component Cause: a factor that contributes towards disease causation
Cause
- Sufficient but Not Necessary: The factor might cause the disease, but another factor might also cause the disease, having both factors is not required.
- Necessary but Not Sufficient: The risk factor is necessary but another factor(s) is/are also needed.
- Necessary and Sufficient: The risk factor is necessary and always causes the disease.
- Neither Sufficient nor Necessary
Counterfactuals
- ‘If I had been exposed to x instead of y, I would be less likely to have the outcome’
- It states that the presence or absence of the cause “makes a difference”
A counterfactual statement draws a contrast between one outcome given certain conditions and another outcome given alternative conditions
- The necessary and sufficient, sufficient-component, and probabilistic definitions clarify what kind of difference it makes