Exam 2 : lecture Association, Causal Inference & Causality Flashcards
Cause
Precursor event, condition or characteristic required for the occurrence of the disease or outcome
Associations
Relationships between an exposure/ treatment and an outcome/disease
3 types of association (relationships)
Artifacts also (AKA false) Non-causal associations (related but not caused) Causal associations ( one thing cause the other)
Artifactual association
Arise from bias or confounding
Non-causal associations
Disease may CAUSE the exposure
Or
Disease and exposure are both associated with a third factor (confounding) ex: coffee drinking & CHD
Causal associations
Exposure causes outcome
Types of causal relationships
Sufficient cause
Necessary cause
Component cause
Sufficient cause
Cause which precedes a disease, if present, disease with ALWAYS occur
Ex: genetic abnormalities
Can have risk factors (component causes)
Necessary cause
Cause which precedes a disease and has the following relationships:
-cause must be present for disease to occur; cause may also be present without disease occurring
Ex: tuberculosis
NO GAURANTEE OF OUTCOME
Component cause
Risk factors
-if present/active, increases the probability (or likelihood) of disease
Ex: High LDL—
Some patients must be _______________ or ______________ to disease before component cause induce disease (multi factorial)
Primed
Susceptible
Interactions in causal research
Synergism
Parallelism
Synergism
Work together
2 or more components cause such that the combined measure of effect is greater than the sum of the individual effects
(Need BOTH factors)
Parallelism
Either
2 or more components causes such that the measure of effect is greater if either is present
(One or the other will give you the disease)
Hill’s guidelines
Derived following US surgeon Generals 1964 report on smoking
-no hard and fast rule of evidences could be generated by to judge likelihood of causation, but the more you have, the better the causation