Five Definitions Of Causation From Epidemiologic Literature

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CAUSATION
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July 3, 2014
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Causation
The concept of causation is indispensable in the discipline of epidemiology; paradoxically, not a single definition could plainly define the notion of causation. There has been five major definitions spawned to bring out meaning to this concept yet none of them can accurately bring into words the idea of causation. The five categories of defining causation include production, sufficient-component cause, necessary cause, probabilistic cause and counterfactual cause (Parascandola & Weed, 2001).These definitions are educed from a systematic review of the literature; there are various strengths and weaknesses allied with each definition. In order for a definition to be effectual it must be explicit enough so that it can differentiate causation from mere correlation, the definition should not be contracted as this could eliminate apparent causal phenomenon from deliberation (Parascandola & Weed, 2001). Both the production counterfactual concepts are inherently found in all the definitions of causations although this does not imply the two concepts are sufficient by themselves.
Five Definitions Of Causation From Epidemiologic Literature
 
Production
Under this category causation is defined as something which creates or triggers an effect. After cause there is an effect. For example, extreme cigarette smoking leads to lung cancer, in this case the cause is excessive smoking and the effect is lung cancer. Epidemiology is the science of studying the patterns, causes and effects of health and diseases in a given population cluster (Olsen, 2001). Through this science, the health practitioners are able to institute the right measures for evidence based practice. It’s therefore important for them to identify risk factors for disease and the targeted population in order to institute preventive medical care. In this case, the definition of production is utilized to help the health care establish the cause of a disease in order to combat the outcome. When healthcare officers are acquainted with the fact that excessive smoking leads to cancer this helps them to campaign at the grassroots and warn the public on the dangers of extreme cigarette smoking.
Necessary Causes
 
Under this definition the epidemiologists believe that the “cause” of a disease should be limited to highly precise essential conditions (Parascandola & Weed, 2001). This means that the actual cause should be present in order for a specific effect to occur. This concept is applicable with the germ theory of disease for instance Tetanus is caused by a bacteria known as Clostridium tetani.( Karhausen,2000) This is the specific causal agent, a minority epidemiologists believe that there is no disease with more than one cause thus every causal agent should be identified in order for a disease to be appropriately eradicated. When scientists utilize multi-causal model to explain the existence of a particular disease it simply means that they lack intrinsic knowledge on the actual causal agent of the disease (Olsen, 2001). There are some particular diseases that have been proven to have more than one cause. In this case therefore scientists cannot just state that obesity leads to high blood pressure; in order for this statement to be scientifically relevant, the scientist must be able to pin point the particular causal agent of high blood pressure.
The sufficient-component cause
This particular causation theory is an improvement of the necessary cause model. Even though the above theory asserts that the agent causing a should be specific, it does not consider the adequacy of that component. This theory asserts that in order for the cause of a disease to be valid a sufficient component cause should be enough, comprising of many other components which makes it possible for the disease to be detected (Parascandola & Weed, 2001). Since one set of components may be   adequate in order for disease to be present, this chiefly means that a single disease may actually have multiple causes.  This model differs with the necessary cause model because it requires that within a given set of situation, all causes must be essential and enough. In this case, the occurrence or non-occurrence of a disease is depended on the prevailing conditions.  
Probabilistic cause
Probabilistic causation offers a different model different from the determinism inbuilt in both necessary and causation models. Gradually, as the philosophers sought to explain the exact causal agents of diseases they spawned sophisticated theories linked to probabilistic causation to offer an explanation to apparently indeterministic processes. The devi...