Lecture 14. Flashcards
Is Knowledge of the complete pathway of a dis-ease a prerequisite for introducing preventive measures?
No.
Must All Bradford Hill criteria be fulfilled to determine causality?
No. They act as a guide
what are the benefits of the population health framework?
Provide the maximum benefit for the largest number of
people, at the same time reducing inequities in the distribution
of health and wellbeing
An important role of epidemiology is to
seek the cause of “dis-ease”
Epidemiology does not determine the cause of a disease in a given individual
Instead, it determines the relationship or association between a given exposure and dis-ease outcome in populations
does a preventative action need to be taken after a cause has been identified?
No. Can be taken before the cause is identified( eg cholera & scurvy)
James Lind’s experiment is
an example of early RCT
attempted to find the cure for scurvy amongst sailors( citrus fruit)
Can causality be proven in human studies?
Often no, because of ethical reasons. ( especially when trying to prove if something causes a bad outcome(disease death) and it is known to be harmful. )
Bradford Hill Framework
Aid to determining a causal relationship
- Temporality
- Strength of association
- Consistency of association
- Biological gradient (dose-response)
- Biological plausibility of association
- Specificity of association
- Reversibility
Bradford Hill Framework
- Temporality
- Strength of association
- Consistency of association
- Biological gradient (dose-response)
- Biological plausibility of association
- Specificity of association
- Reversibility
Temporality
- First the cause then the disease
- Essential to establish a causal relation
Strength of association
- The stronger an association, the more likely to be causal in absence of known
biases (selection, information, and confounding)
Consistency of association
- Replication of the findings by different
investigators, at different times, in
different places, with different methods
Multiple studies have
shown similar results
Biological gradient (dose-response)
- Incremental change in disease rates in
conjunction with corresponding changes in exposure
Biological plausibility of association
- Does the association make sense biologically?
Chemicals in tobacco that are known
to promote cancers (carcinogens)
Specificity of association
A cause leads to a single effect or an effect
has a single cause
However, health issues have multiple, interacting causes and many outcomes share causes
Reversibility
The demonstration that under controlled conditions changing the exposure causes a change in the outcome
sufficient cause
• The whole pie
• A minimum set of conditions without any one
of which the disease would not occur
• Not usually a single factor, often several
• A disease may have several sufficient causes
(several pies can produce the same disease)
Component cause
• Each factor or slice is a component cause
• A factor that contributes towards dis-ease
causation, but is not sufficient to cause dis-ease on
it’s own
• Component causes “interact” to produce disease
Necessary cause
- A factor (or component cause) that must be present if a specific dis-ease is to occur.
- A component cause will be a necessary cause for some diseases
The problems with the causal pie model:
- Fails to capture dose-response relations as a continuum
- Assumes that all causes are deterministic
- A causes B means that whenever A occurs, B occurs
Probabilistic concept of causation
• A cause increases the probability (or chance) that its effect will occur
e.g., smoking increases the probability of lung cancer
• Does not exclude necessary and sufficient causes
• Probability of an effect/outcome occurring
• A sufficient cause raises the probability to 1
• A necessary cause raises that probability from 0
• Each component cause contributes toward the probability
from 0 to 1.
• Fits well with public health goals of epidemiology (considers
environmental factors, group-level effects)
Counterfactual definition of causation
• States that the presence or absence of the cause
“makes a difference” in the outcome (or probability of the outcome)
• Whereas the necessary, sufficient, component, and probabilistic definitions clarify what kind of difference it makes
• Is consistent with both deterministic and probabilistic phenomena
what is population health important?
- Targets factors that could avoid premature mortality
- Most effective at improving health of populations rather than individuals
