Causation in epidemiology

Abstract

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 suYcient, suYcient-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 categoriesproduction and counterfactual-are present in any definition of causation but are not themselves suYcient as definitions. The necessary and suYcient cause definition assumes that all causes are deterministic. The suYcient-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. (J Epidemiol Community Health 2001;55:905-912)

Cannabis use and psychosis: the origins and implications of an association

“…Random allocation of level of exposure to a putative cause should normally ensure that potential confounding factors, both known and unknown, are evenly distributed across different exposure categories such that their confounding effects are balanced. For this reason the existence of experimental (or 'counterfactual') evidence is often seen as an important additional causal criterion (Parascandola & Weed, 2001). Epidemiological experience based on instances where apparently robust observational associations were subsequently shown to have no causal basis by experimental studies (for example in relation to intake of various vitamins and risk of chronic disease) have led to suggestions that 'observational studies propose, RCTs dispose' with regard to causal hypotheses (Davey Smith & Ebrahim, 2002).…”

“…This leads to the statistical axiom that association alone should not be taken as evidence of causation. Criteria that can help guide causal inference were proposed around 40 years ago and have been refined on several occasions since (Hill, 1965;Rothman, 1976;Susser, 1991;Parascandola & Weed, 2001). Temporal priority is an obvious prerequisite (a cause must precede an effect) and it can be established only with longitudinal data.…”

Authors' reply to Turner and colleagues

“…Absence of a valid mechanism is not usually a basis for rejecting conclusions from consistently observed findings. 3 Indeed, the protective effect of BCG against tuberculosis is not in doubt, even though a mechanism (and a correlate) of protection remain elusive after decades of investigation. 4 Nonetheless, we believe that new vaccines for tuberculosis will be found only if we undertake more research to disentangle the mechanism of action of BCG vaccines, including their effects on innate and adaptive immune responses.…”

Quelle(s) épidémiologie(s) pour la santé au travail ? Réflexions à partir des cancers professionnels

“…Pour d'autres épidémiologistes en revanche, une ouverture vers davantage de constructivisme (c'est-à-dire de prise en compte d'une historicité sociale et politique) ainsi qu'une réelle primeur à l'intervention seraient bénéfiques à la discipline. Ce nouveau paradigme serait facilité par une redéfinition des normes probantes de causalité où la notion « biologique » ou physique de causalité (Parascandola et Weed, 2001) serait abandonnée au profit d'une approche favorisant des théories sociales. En l'absence de mécanismes sociaux pour expliquer les effets sur la santé des rapports sociaux (liés aux discriminations, aux migrations, au genre, etc.…”