US EPA

3240734 

Journal Article 

Causation in epidemiology 

Parascandola, M; Weed, DL 

2001 

Yes 

Journal of Epidemiology and Community Health
ISSN: 0143-005X
EISSN: 1470-2738 

55 

12 

905-912 

WOS:000172346700017 

Causation is an essential concept in epidemiology, yet
there is no single, clearly articulated definition for the discipline. From a systematic review
of the literature, five categories can be delineated: production, necessary and sufficient,
sufficient-component, counterfactual, and probabilistic. Strengths and weaknesses of these
categories are examined in terms of proposed characteristics of a useful scientific definition of
causation: it must be specific enough to distinguish causation from mere correlation, but not so
narrow as to eliminate apparent causal phenomena from consideration. Two categories-production
and counterfactual-are present in any definition of causation but are not themselves sufficient
as definitions. The necessary and sufficient cause definition assumes that all causes are
deterministic. The sufficient-component cause definition attempts to explain probabilistic
phenomena via unknown component causes. Thus, on both of these views, heavy smoking can be cited
as a cause of lung cancer only when the existence of unknown deterministic variables is assumed.
The probabilistic definition, however, avoids these assumptions and appears to best fit the
characteristics of a useful definition of causation. It is also concluded that the probabilistic
definition is consistent with scientific and public health goals of epidemiology. In debates in
the literature over these goals, proponents of epidemiology as pure science tend to favour a
narrower deterministic notion of causation models while proponents of epidemiology as public
health tend to favour a probabilistic view. The authors argue that a single definition of
causation for the discipline should be and is consistent with both of these aims. It is concluded
that a counterfactually-based probabilistic definition is more amenable to the quantitative tools
of epidemiology, is consistent with both deterministic and probabilistic phenomena, and serves
equally well for the acquisition and the application of scientific knowledge.