S10) Concepts of Causality Flashcards
What are the three aspects of Henle-Koch’s Postulates in terms of causation?
- Necessity
- Specificity
- Sufficiency
What does it mean when a cause is necessary?
Necessary – a cause always precedes the disease i.e. disease cannot occur without cause being present
What does it mean when a cause is specific?
Specific – the cause is absent in other diseases (no longer considered relevant, including in microbiology)
What does it mean when a cause is sufficient?
Sufficient – a cause alone can lead to the disease (once predisposing and precipitating factors are in place)
Complete the following table to apply Henle-Koch’s Postulates (1882) to the 21st Century
Describe the cause-effect relationship in an epidemiological context
- Disease results from the interplay of host, environment and agent
- A cause is an exposure/factor that increases the probability of disease
- Exposures do not have to be either necessary/sufficient to be important causes
Provide four examples of exposures which are neither necessary (i.e. other causes) nor always sufficient (i.e. need other factors) to cause a disease
- Alcohol consumption → liver cirrhosis
- Ionising radiation → leukaemia
- Smoking tobacco → heart disease
- Traffic speed → pedestrian injury
Associations may be present in the absence of a true cause-effect relationship.
Explain this in terms of systematic / random variation
- Confounding (“erroneous”) – known, possible, unknown
- Bias (“incorrect”) – selection bias and information bias
- Chance (“luck”) – measured by p value
Provide four possible alternative explanations for an observed association between X and Y
- Due to an unknown confounding factor
- Due to a common cause e.g. lung cancer is associated with chronic bronchitis but both are caused by tobacco smoking
- Reverse causality (you think X→Y but Y→X) e.g. bar work is associated with alcoholism amongst staff
- A true causal association (X → Y)
How does one evaluate the strength of evidence in favour of a cause-effect relationship using Bradford Hill’s criteria for causality?
- Association features – strength of association, specificity of association, consistency of association
- Exposure/outcome – temporal sequence, dose response, reversibility
- Other evidence – coherence of theory, biological plausibility, analogy
Using an example, explain strength of association in the Bradford Hill Criteria
- A causal link is more likely with strong associations
- Strong associtions are unlikely to be explained by undetected confounding/bias
- E.g. heavy smokers have 20 times risk of mortality from laryngeal cancer than non-smokers*
Using an example, explain specificity of association in the Bradford Hill Criteria
- A causal link is more likely when an outcome is associated only with a specific factor and vice-versa
- Specificity of association strengthens the case for a causal link
- E.g. Mesothelioma is associated with exposure to asbestos – no other factors are significant causes of mesothelioma*
Using an example, explain consistency of association in the Bradford Hill Criteria
- A causal link is more likely if the association is observed in different studies and different sub-groups
- Consistency of association between studies or groups is unlikely to be due to the same confounding or bias
- E.g. Many different studies demonstrated the association between smoking and ischaemic heart disease*
Using an example, explain temporal sequence in the Bradford Hill Criteria
- A causal link is more likely if exposure to the putative factor has been shown to precede the outcome
- The corollary is that a causal link cannot exist if the outcome preceded exposure to the putative factor
- E.g. British Doctors Cohort Study showed that tobacco smoking was not only associated with many diseases but preceded them*
Using an example, explain dose response in the Bradford Hill Criteria
- A causal link is more likely if different levels of exposure to the putative factor leads to different risk of acquiring the outcome
- Dose response (biological gradient) is unlikely to be due to unknown confounding or bias
- E.g. The risk of leukaemia increased in survivors of the Hiroshima and Nagasaki atomic bombs the nearer they were to the hypocentre*
Explain reversibility in the Bradford Hill Criteria
Reversibility – a causal link is very likely if removal or prevention of the putative factor leads to a reduced or non-existent risk of acquiring the outcome
Using an example, explain coherence of theory in the Bradford Hill Criteria
- A causal link is more likely if the observed association conforms with current knowledge
- Coherence with current paradigms / constructs / theories strengthens the case for a causal link
- E.g. The link between socio-economic deprivation and greater ill-health, mortality and lower life expectancy is now well established*
Explain biological plausibility in the Bradford Hill Criteria
- A causal link is more likely if a biologically plausible mechanism is likely or demonstrated
- A biologically plausible mechanism strengthens the case for a causal link
Using an example, explain analogy in the Bradford Hill Criteria
- A causal link is more likely if an analogy exists with other diseases, species or settings
- An analogy is easier to infer than a biologically plausible mechanism
- E.g. The epidemiology of Hepatitis B virus was successfully used to predict how HIV virus would spread*
What is epidemiology?
Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems
What are the two assumptions one makes in epidemiology?
- Disease does not occur at random
- Disease has causal and preventable factors that can be identified through systematic investigation
Explain how the concepts of causality have evolved over the years
- Necessary, specific, sufficient agent → disease
⇓
- Host, environment and agent → disease
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- Multi-factorial web of factors → disease
Identify the four concepts in epidemiological reasoning
- Hypothesis
- Analytical Study
- Observed Associations
- Cause-Effect Relationship
Describe the following four concepts in epidemiological reasoning:
- Hypothesis
- Analytical study
- Observed associations
- Cause-effect relationship
- Hypothesis – generated from observations and/or theories
- Analytical Study – systematic observations of comparisons
- Observed Associations – possible explanations of non-causal associations (chance, bias, confounding ± reverse causality)
- Cause-Effect Relationship – based on judgement of how the observed association fits in with evidence from other sources
