Susser's Three Characteristics to Argue that the Outcome and Exposure can only be Inferred from Epidemiological Studies

Susser's Three Characteristics to Argue that the Outcome and Exposure can only be Inferred from Epidemiological Studies

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The scientific method is built on the principle that nothing can ever be proved as definitively true. Rather, once a hypothesis is proposed, evidence can be generated in favor of the hypothesis or in favor of an alternative hypothesis. When enough evidence is gathered in one direction or the other, the original hypothesis is either accepted or debunked in favor of an alternative. As scientific work is always in flux, any previously accepted theory can always be overturned by new evidence.1, 2 Many epidemiologists accept Popper’s thesis that causality can never be truly proven; although, once enough reliable evidence has been accumulated, a causal relationship can be inferred.2
The question of what constitutes a cause is a matter of ongoing inquiry among epidemiologists. Causality is extremely complex and has been described with a number of metaphors, images and guidelines, and has been summarized simply by Susser as “something that makes a difference”.2 A primary objective in epidemiology is to make inferences identifying a causal variable for the outcome of interest. However, these inferences can only be valid if the accumulation of evidence is done within a causal framework, rather than an associational one. A critical description of the difference between associational and causal concepts insists that while an associational relationship can be defined by the distribution of observed variables, a causal relationship cannot be.3 This paper will use the lens of Susser’s three characteristics of a cause, association, time order, and direction to argue that a causal relationship between exposure and outcome can only be inferred from experimental epidemiologic studies. The basis for this argument is an examination of the counterfact...

... middle of paper ... priority whose causes may not be perfectly understood and must not ignore the accumulation of evidence that calls for action, imperfect though it may be.1

Works Cited

1. Hill AB. The Environment and Disease: Association or Causation? Proc R Soc Med. 1965;58(5):295–300.
2. Aschengrau A, Seage GR. Essentials of epidemiology in public health. Burlington, MA: Jones & Bartlett Learning; 2014.
3. Pearl J. An introduction to causal inference. Int J Biostat. 2010;6(2):Article 7. doi:10.2202/1557-4679.1203.
4. Susser ES. Psychiatric epidemiology: searching for the causes of mental disorders. Oxford; New York: Oxford University Press; 2006.
5. Thorpe L. Causality in Epidemiology. 2014.
6. Kaufman JS, Poole C. Looking back on “causal thinking in the health sciences.” Annu Rev Public Health. 2000;21:101–119. doi:10.1146/annurev.publhealth.21.1.101.

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