Lecture 6: Association & Causality Flashcards
define cause
a pre-cursor event required for the occurrence of the disease
a study may yield associations between exposure and disease, but this does not mean ……?
that the exposure is the cause of the disease
3 types of associations
artifactual associations
non-causal associations
causal associations
artifactual associations
’s may show an association but it’s actually not related at all
associations that are false/wrong
can come from bias or confounding
non-causal associations
can occur in 2 ways
- the disease causes the exposure
- disease and exposure are both related to a confounding variable
types of causal relationships
- sufficient cause
- necessary cause
- component cause
a set of minimal conditions that inevitably will produce disease 100% of the time
sufficient cause
type of cause which precedes a disease, and if present, the disease will always occur
sufficient cause
type of cause that must be present for the disease to occur, yet you may have this cause and never get the disease
necessary cause
a factor that if present, increases the probability of a particular disease. most common example?
component cause
ex. age
2 interactions in causal research
- synergism
2. parallelism
define ‘synergism’
interaction of at least 2 component-causes, such that the combined effect of the components is greater than the effect of just one cause being present
define ‘parallelism’
interaction of at least 2 component-causes, such that the measure of effect is greater if either one is present.
but they are not occurring at the same time. must have 2 variables to compare and their effects on RR separately
_______ causes work in concert to collectively become ______ causes.
multiple component causes together become sufficient causes
how can we decide if the RR’s of risk factors contain enough of a relationship to be called a cause?
use Hill’s Guidelines to create causal inferences
Hill’s criteria/Guidlines
- strength
- consistency
- temporality
- biologic gradient
- plausibility
explain the strength guideline
refers to the size of the measure of association (RR)
the greater an association value, the more convincing it is to show a causality
explain consistency guideline
the repeated observation of an association, across different studies, populations, or circumstances
multiple studies show that same result
consistency may obscure _______
the truth!
observational studies might show an association but is possible for it to be wrong after doing randomized blind studies
explain temporality guideline
reflects that the cause precedes the outcome
proximal or distant cause in time-line
a cause happens just before the outcome so you assume there is an association. but this is not always the truth
explain biological gradient guideline
the presence of a gradient of risk associated with the exposure
more of exposure = greater probability of an outcome
ex. 10 packs a day = greater chance of lung cancer than 1 cigarette a day
explain plausibility guideline
biological feasibility of the association
can the cause be explained or understood physiologically
issue with plausibility
decisions of plausibility are based upon known beliefs but our current beliefs may be wrong. we don’t know everything or understand everything that happens
