1. Causality Inferences

2. Objectives: 1. To understand the concept of risk factors and outcome in a scientific way. 2. To understand and comprehend each and every causality inference of Hill’s criteria. 3. You students must be capable to identify risk factors and outcome in the research within the scope of causality inference.

3. Causal Criteria Hill ’ s Criteria (1965)  Strength; the higher the measure of association the stronger the relationship  Consistency; repeated observations of a factor effect give similar outcome  Specificity; the factor is a specific for the outcome (e.g. smoking and lung diseases)

4. Cont.  Temporality; proof of exposure prior to outcome (e.g. allergy preceded by exposure)  Biological Gradient ; Dose response relationship (e.g. amount of alcohol consumption and rate of car accident)  Plausibility; logically and likely to be true (e.g. the historical suspicion of the relationship between cholera and water drinking)

5. Cont.  Coherence; the ideas are going together (e.g. spotting SARS cases based on clinical condition rather than diagnostic test)  Experimental Evidence ; matching with previous animal or human studies  Analogy ; similarity using imagination (e.g. imagination links romance with fragrance)

6. Koch ’ s postulates were an example of deterministic causality. To prove that an organism causes a disease, he required that: 1. The organism must be isolated in every case of the disease (i.e. be necessary) 2. The organism must be grown in pure culture 3. The organism must always cause the disease when inoculated into an experimental animal (i.e. be sufficient) 4. The organism must then be recovered from the experimental animal and identified.

7. ASSOCIATION VS CAUSATION To decide whether exposure A causes disease B, we must first find out whether the two variables are associated, i.e. whether one is found more commonly in the presence of the other.

8. MAKING CAUSAL INFERENCES The use of causal criteria in making inferences from data.

9. WHEN TO APPLY CAUSAL CRITERIA? Causal criteria are principally designed to deal with the problem of confounding. By applying the criteria, we reduce the possibility of falsely assigning cause to the wrong exposure. Causal criteria do not work well in the case of bias.

10. Objectives: 1. To understand the concept of risk factors and outcome in a scientific way. 2. To understand and comprehend each and every causality inference of Hill’s criteria. 3. You students must be capable to identify risk factors and outcome in the research within the scope of causality inference.