This document discusses the concepts of association and causation in epidemiology. It defines correlation as a measure of association between two variables, while causation requires one variable to be a suspected cause of the other. There are three types of association - spurious, indirect, and direct. Direct association can be either a one-to-one causal relationship or multifactorial causation from multiple independent factors. Six guidelines for judging causal relationships are temporal association, consistency, specificity, strength, coherence, and biological plausibility.

1. ASSOCIATION AND CAUSATION

2. ASSOCIATION If two attributes say A and B are found to co-exit more often than an ordinary chance. It is useful to consider the concept of correlation. Correlation indicates the degree of association between two variables.

3. CAUSATION If one of these attributes say A is the suspected cause and the other say B is a disease then we have a reason to suspect that A has caused B.

4. Types Of Association 1. Spurious association 2. Indirect association 3. Direct association One-to-one causal association Multifactorial causation

5. Spurious Association This is an association which appears due to improper comparison. Observed association between a disease and suspected factor may not be real. E.g.; Neonatal mortality was observed to be more in the newborns born in a hospital than those born at home. This is likely to lead to a conclusion that home delivery is better for the health of newborn. However, this conclusion was not drawn in the study because the proportion of “high risk” deliveries was found to be higher in the hospital than in home.

6. Indirect Association It is a statistical association between a characteristic of interest and a disease due to the presence of another factor i.e. common factor (confounding variable). E.g.: Neonatal mortality (A) was found to be associated with maternal age above 30 years (B) and with birth order 4 and above (c). It was also shown that the attribute B and C were associated with each other.

7. Direct Association The association between the two attributes is not through the third attributes. When the study reveals it is not a spurious association. When the disease is present, the factor must also be present.

8. Direct Association Is Classified Into Two Types One-to-one Casual Relationship: The variables are stated to be casual related (AB) if a change in A is followed by a change in B. When the disease is present, the factor must also be present. A single factor or cause may lead to more than one outcome.

9. Direct Association Is Classified Into Two Types Multifactorial causation: Alternative causal factors each acting independently. E.g. In lung cancer more than one factor (e.g. air pollution, smoking, heredity) can produce the disease independently.

10. Six Guidelines For Judging Whether An Association Is Causal Temporal Association Consistency Of The Association Specificity Of The Association Strength Of The Association Coherence Of The Association Biologic Plausibility Of The Association

11. Temporal association The causal attribute must precede the disease or unfavorable outcome. Exposure to the factor must have occurred before the disease developed. Length of interval between exposure and disease very important If the disease develops in a period of time too soon after exposure, the causal relationship is called into question.

12. Consistency Of The Association Consistency is the occurrence of the association at some other time and place repeatedly. If a relationship is causal, the findings should be consistent with other data. If lung cancer incidence increased as cigarette use was on the decline, we would have to be able to explain how this was consistent with a causal relationship. If there is no consistency it will weaken a causal interpretation. The causal association between smoking and lung cancer due to its consistency.

13. Specificity Of The Association The weakest of the criteria (should probably be eliminated) Specific exposure is associated with only one disease. This is used by tobacco companies to argue that smoking is not causal in lung cancer. Smoking is associated with many diseases. Specificity implies a one to one relationship between the cause and effect.

14. Strength Of The Association Relationship between cause and outcome could be strong or weak. With increasing level of exposure to the risk factor an increase in incidence of the disease is found. There are statistical methods to quantify the strength of association viz; calculation of relative risk, attributable risk etc.

15. Coherence Of The Association Causal significance of an association is its unity with known facts that are thought to be related. E.g.: the rising consumption of tobacco in the form of cigarettes and the rising incidence of lung cancer are coherent.

16. Biologic Plausibility Of The Association The association must be consistent with the other knowledge (viz mechanism of action, evidence from animal experiments etc). Sometimes the lack of plausibility may simply be due to the lack of sufficient knowledge about the pathogenesis of a disease.