Lecture 8: Causation in Epidemiology Flashcards
(44 cards)
What are other ways to refer exposures by?
Causes, risk factors, independent variables
What are other ways we think about outcomes?
effects, diseases, injuries, disabilities, deaths, dependent variables
Statistical association versus biological causation
For causation, we need statistical association (how much is this affection the population) and the biological mechanisms. The presence of statistical association alone does not necessarily imply a causal relationship.
Association (relationship)
Statistical dependence between two or more events, characteristics, or other variables.
Ex. as one increases/decreases, what happens to the other variable.
Causality (causation / cause-effect relationship)
relating causes to the effects they produce.
Cause
An event, condition, characteristic (or a combination of them) which plays an important role/predictable change in occurrence of the outcome.
Deterministic Causality
cause closely related to effects, as in “necessary”/”sufficient’ causes
Necessary cause
Has to be present in order to produce the outcome
Sufficient cause
inevitably initiates or produces an effect. Sufficient, is when the factor can produce the outcome by itself. Includes “component causes.”
Component Causes
Together they constitute a sufficient cause for the outcome in question
Component Causes
Together they constitute a sufficient cause for the outcome in question
Probabilistic Causality
Weak relationship, neither necessary nor sufficient.
Effect Measures/Impact Fractions
- effect measures and impact fractions are closely related to the strength of association
- The higher the effect measures and population attributable risk, the more exposure is predictive of the outcome in question
Necessary and Sufficient
- if the factor is present, the disease will always occur
- without the factor, the disease never develops
only factor A -> Disease
Necessary but Not Sufficient (Alone)
- each factor necessary but not in itself sufficient to cause the illness in itself, all are necessary to cause disease, but individually, none are sufficient to cause the disease.
- each risk factor alone cannot cause disease
- Thus multiple factors are required often in a specified temporal sequence
Sufficient but not necessary
- that factor alone can produce the outcome but it is not the only factor that produces the outcome
- that outcome can still occur if that factor is not present
Neither Sufficient Nor Necessary
- None of the risk factors are enough or alone to cause a disease
- There are multiude risk factors
Henle-Koch’s Postulates
Four postulates should be met before a causal relationship between a disease agent and disease.
1. The agent must be present in every case
2. Agent must not be found in cases of other disease
3. Once isolated, the agent must be capable of reproducing the disease in experimental animals.
4. The agent must be recovered from the experimental disease produced.
Bradford Hill’s Considerations for Causality
- Strength of association
- Consistency
- Specificity
- Temporality
- Dose-response relationship
- biological plausibility and coherence
- Experiment-randomized controlled trials
Strength of Association
- The larger an association between exposure and disease, more likely to be causal
- Percival Pott’s study: scrotal cancer is 200 times more likely to those exposed to chimney soots
Consistency
- multiple epidemiologic studies using various locations, populations, and methods to show consistent association
- over 100s studies that show smoking and lung cancer are associated
Specificity of Outcome
- more likely to be causal when they are specific
- the exposure causes only one disease
- asbestos causes lung cancer
Temporarilty
- Exposure must precede the onset of disease
- is low serum cholesterol a cause of colon cancer or is the early phase of colon cancer cause low cholesterol
Dose-response relationship
- increase the dose/exposure, increases the response
- those with alcohol addiction die faster than those who consume less or abstain
