Lecture 12 - Establishing causality in population health Flashcards
Why is establishing causal relationships important
Provide support for evidence-based practice
What did James Lind’s experiment teach us
The experiment showed us how sometimes preventive action can be taken before the cause of a disease is identified
Why can’t causality be proved in human experimental studies
For practical and ethical reasons
3
Most epidemiological studies…
- non-experimental
- conducted in ‘noisy’ environments in free-living populations
- determine relationship/association between a given exposure to a cause/s and dis-ease outcomes in populations
Epidemiological studies can identify a _____ _______ between a potential ____ and an _____.
Statistical association, exposure, outcome
What do we need when looking for links between exposure and outcome
- Need sufficient studies done in diverse settings and adequately limiting random errors, non-random erros, and confounding
What are the seven aspects of the Bradford Hill Framework (1965)
- Temporality
- Strength of association
- Reversibility
- Biological gradient
- Biological plausability of association
- consistency of association
- specifity of association
What is temporality
- First the cause, the the disease
- essential to establish a causal relationship
What is strength of association
The stronger the association, the more likely to be casual in absence of known biases (selection, information, and confounding)
What is reversibility
The demonstration that under controlled conditions, changing the exposure causes a change in the outcome
What is biological gradient
- incremental change in disease rates in conjunction with corresponding changes in exposure
What is biological plausability of association
- does the association make sense biologically
- e.g the chemicals in tobacco are know to promote cancers
What is consistency of association
Replication of the findings by different investigators, at different times, in different places, with different methods.
(multiple studies show similar results)
What is specifity of association
- a cause leads to a single effect
- an effect has a single cause
Why is specifity of association the weakest criteria
Many diseases share causes, and diseases have multiple causes. What the criteria states is never the case.
What are the three elements that are a part of the epidemiological triad
Host (persons in a population), environment (physical, social, policy) and agent (biological, nutritional, physical, chemical)
What is a cause of a disease (Rothman’s causal pie model)
An event, condition, characteristic (or combination of these factors) which play an essential role in producing the disease.
What does the causal pie recognise
Multi-causality
What is a sufficient cause
- The whole pie
- A minimum set of conditions without any one of which the disease would not occur
- A disease may have several sufficient causes
What is a component cause
- Each factor or slice
- A factor that contributes towards dis-ease causation, but is not sufficient to cause dis-ease on its own
- Component causes ‘interact’ to produce disease
What is a necessary cause and how is it linked to component cause
- A factor (or component cause) that must be present for a specific disease to occur
- A component cause will be a necessary cause for some diseases
What would blocking/removing any component cause do
Result in prevention of some cases of disease
Do we need to identify every component cause to prevent some cases of disease
No
Is it possible to intervene at any number of points in the pie
Yes
Is the knowledge of the complete pathway a pre-requisite for introducing preventitive measures
No
What are the weaknesses of the causal pie model
- fails to capture the dose-response relations as a continuum
- assumes that all causes are deterministic (A causes B, B happens when A occurs)
What is the probabilistic concept of causation
- A cause increases the probability (or chance) that its effect will occur
- does not exclude necessary and sufficient causes
A sufficient cause raises the probability to what
1
Probability of an effect/outcome happening
- A sufficient cause raises probability to 1
- A necessary cause raiss that probability from 0
- each component cause contibutes towards the probability from 0 to 1
A necessary cause raises that probabilty of