CAUSATION IN EPIDEMIOLOGY

SOYEBO O.A.

OUTLINE

• INTRODUCTION.• CONCEPT OF CAUSE• SINGLE AND MULTIPLE CAUSES.• FACTORS IN CAUSATION.• INTERACTION. • GUIDELINES FOR CAUSATION.• CONCLUSION.

INTRODUCTION

• A major goal of epidemiology is to assist in the prevention and control of disease and in the promotion of health by discovering the causes of disease and the ways in which they can be modified.

CONCEPT OF CAUSE

• An understanding of the causes of disease is important in the health field not only for prevention but also in diagnosis and the application of treatment.• A cause of a disease is an event, condition, characteristic,

or combination of these factors which plays an important role in producing the disease.• A cause could be sufficient or necessary

SUFFICIENT CAUSE

• A cause is termed sufficient when it inevitably/certainly produces or initiates a disease.

• It is not usually a single factor, but often comprises several components. e.g. cigarette smoking is one component of the sufficient cause in lung cancer.

• In general, it is not necessary to identify all the components of a sufficient cause before effective prevention can take place, since the removal of one component may interfere with the action of the others and thus prevent the disease.

NECESSARY CAUSE

• A cause is termed necessary if a disease cannot develop in its absence.• Each sufficient cause has a necessary cause as a

component.

SINGLE AND MULTIPLE CAUSES

• Pasteur’s work on microorganisms led to the formulation, first by Henle and then by Koch, of the following rules for determining whether a specific living organism causes a particular disease:

it must be present in every disease case.

Must be able to be Isolated and grown in pure culture.

Cause specific disease when inoculated in susceptible animal.

it must be recovered from the animal and identified.

• A given disease can be caused by more than one causal mechanism, and every causal mechanism involves the joint action of a multitude of component causes.

LIMITATION

• Anthrax was the first disease demonstrated to meet these rules which have proved useful with some other infectious disease but for most disease (both infectious and non-infectious) , Koch’s rules for determining causation are inadequate.

The causative organism may disappear when the disease develops.Certain micro-organisms cannot (at the present time) be grown in pure

culture.Not all organisms exposed to an infectious agent will acquire the infection.

FACTORS IN CAUSATION

• Four types of factor play a part the causation of disease. All may be necessary but will rarely be sufficient to cause a disease.

• PREDISPOSING FACTORS: create a state of susceptibility to a disease agent. e.g. age, sex, previous illness. These may have no direct bearing on the cause of the disease but they aid other risk factors e.g. salivary gland diseases for caries development.

• ENABLING FACTORS: environmental conditions which favor the development of disease. E.g. low income, poor housing, poor nutrition, inadequate medical facility.

• PRECIPITATING FACTORS: specific or noxious agent, exposure to which can be associated with the onset of a disease. E.g. pollens in asthmatic attack.

• REINFORCING FACTORS: factors which aggravates an already established disease or state. e.g. repeated exposure and unduly hard work.

• The term Risk factors are those factors that have a direct link to the cause of the disease but are not sufficient to cause the disease i.e. they heighten the chance of contacting a disease condition but themselves not enough. e.g. Refined sugar, time, bacteria for caries

INTERACTION

• The effect of two or more causes acting together is often greater than would be expected on the basis of individual effects.

• Two or more causes acting together to amplify (greater than additive) the intensity of the effect produced.

• E.g. risk of cancer in smokers exposed to asbestos is greater than the summation of effect of each of the factors.

ESTABLISHING THE CAUSE OF A DISEASE

• Causal inference is the term used for the process of determining whether observed associations are likely to be causal; the use of guidelines and the making of judgments are involved.• Before an association is assessed for the possibility that it

is causal, other ,explanations such as chance, bias and confounding have to be excluded.

COULD IT BE DUE TO SELECTION OR MEASUREMENT

BIAS?

COULD IT BE DUE TO

CONFOUNDING?

COULD IT BE A RESULT OF CHANCE?

COULD IT BE CAUSAL?

APPLY GUIDELINES AND MAKE

JUDGEMENTS

OBSERVED ASSOCIATION

GUIDELINES FOR CAUSATION

• Bradford Hill (1965) suggested that the following aspects of an association be considered in attempting to distinguish causal from non-causal associations:

Temporal relation

Plausibility

Consistency

Strength

Dose response relationship

Reversibility

Judging the evidence

TEMPORAL RELATIONSHIP

• refers to the necessity for a cause to precede an effect in time.• This is usually self-evident, although difficulties may arise in

case-control and cross sectional studies when measurements of the possible cause and effect are made at the same time and the effect may in fact alter the exposure.

• E.g. use of seat belt

PLAUSIBILITY

• An association is plausible and more likely causal if consistent with other knowledge.• Problem with plausibility: it is too often not based on logic

or data, but only on prior beliefs. Lack of which may be a simple reflection of medical knowledge.

CONSISTENCY

• Refers to the repeated observation of an association in different populations under different circumstances obtained from different studies. • Lack of consistency, however, does not rule out a causal

association, because different exposure levels and other conditions may reduce the impact of the causal factor in other causes.

STRENGTH

• Hill’s argument is that strong association between possible cause and effect are more likely to be causal than weak associations .

• The fact that an association is weak does not rule out a causal connection. example would be passive smoking and lung cancer.

DOSE-RESPONSE RELATIONSHIP

• A dose-response relationship occurs when changes in the level of a possible cause are associated with changes in the prevalence or incidence of the effect

REVERSIBILITY

• when the removal of a possible cause results in a reduced disease risk, the likelihood of the association being causal is strengthened.• Cessation of smoking reduces the risk of developing lung

cancer

JUDGING THE EVIDENCE

• There’s no completely reliable means of establishing a causal relationship and sometimes evidence can be conflicting. To make a causal inference, all available evidence must be considered.

• Correct Temporal relationship is very essential before other criteria are considered (plausibility, consistency and dose-response relationship). The likelihood of a causal association is heightened when many different types of evidence lead to the same conclusion

CONCLUSION

• The knowledge of causation is an integral part of epidemiology as it enables us to make the proper diagnosis, formulate the correct treatment plan and take necessary measures in the prevention of a certain disease.