Abstract
The scientific and public health claim that smoking is a cause of lung cancer or cardiovascular diseases dates back to the mid-1960s. Nevertheless smoking is neither a necessary nor a sufficient condition for lung cancer. One of the main indicators for causality is that, at the population level, smoking highly increases the probability of having lung cancer. A probabilistic concept of causation was developed by some philosophers that could have given conceptual support to epidemiological causal analysis and inference. Yet, it appears that the agreement on the causal status of specific risk factors did not necessarily lead to the adoption of a probabilistic concept of causation by epidemiologists.
In this paper I propose a historical analysis of the emergence of the risk factor concept in epidemiology with the objective of highlighting how the question of causality arose. Causal inference in epidemiology has been structured by the famous Bradford Hill’s criteria that were developed in the context of the ‘smoking-lung cancer’ controversy in a pragmatic objective and spirit. Even if there were not analysis of the implicit concept of causation presupposed by these criteria, I will show that there are several interpretations of causation behind these criteria which are more or less assumed by epidemiologists. All this leads us to the question of pluralism or monism with regard to the nature of causality in epidemiology and more generally in biomedicine.
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Notes
- 1.
- 2.
The term ‘ecologic’ is used to refer to the population-level of analysis which relies on summary measures of health. Ecologic studies are to be distinguished from individual level studies.
- 3.
The incidence rate is the proportion of subjects who develop a disease within a specified time period.
- 4.
In the case-control study it is not possible to obtain a direct measure of incidence rate. But an equivalent of the relative risk can be calculated: the odds ratio.
- 5.
In this paper, Perreti-Watel denounced the extension of this ‘epidemiological paradigm’ to the study of behaviors and individual beliefs.
- 6.
- 7.
This report was the result of an analysis led by a committee of several experts appointed by the surgeon general. U.S. Department of Health Education and Welfare, Surgeon General’s Report 1964. Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service. Washington DC: Government Printing Office.
- 8.
These five criteria were the following one: consistency of the association, strength of the association, specificity of the association, temporal relationship of the association, coherence of the association.
- 9.
According to Fagot-Largeault (1989), a causal explanation in medicine is a “judgment in which intervene in various proportion historical components (an aetiologic history), some calculus components (a statistical inference), and some decisional component (a choice relying on criteria of relevance)”.
- 10.
Most of the variation between probabilistic theory of causation and most of the debates are around the content of the ceteris paribus clause. The basic idea that causes raise the probability of their effects has indeed to be qualified to resolve the problem of spurious correlations and the problem of the symmetric nature of this simple ‘probability-raising’ condition.
- 11.
- 12.
(4) temporality, (6) plausibility, (7) coherence, (8) experiment, (9) analogy.
- 13.
(1) strength, (2) consistency, (5) biological gradient, (8) experiment.
- 14.
Anitschkov submitted rabbits to a diet mainly composed of eggs. The vasculary wall or intima of these rabbits were then covered with fat atherosclerotic layers thus considered as cholesterol (Anitschkov and Chalatow 1913).
- 15.
Statins are a kind of medicine which in acting on an enzyme of the metabolism pathway of cholesterol permit the decrease of the ratio of LDL-cholesterol (the ‘bad cholesterol’) in the blood.
- 16.
Thagard explains that he does not seek here to define cause in terms of explanation or explanation in terms of cause. To him, causes, mechanisms, explanations, and explanatory coherence are intertwined notions.
- 17.
Thagard (1999) defined the ‘explanatory coherence’ as a positive constraint between hypotheses such as if one is accepted the other is too, and vice versa.
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Giroux, É. (2015). Risk Factor and Causality in Epidemiology. In: Huneman, P., Lambert, G., Silberstein, M. (eds) Classification, Disease and Evidence. History, Philosophy and Theory of the Life Sciences, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8887-8_9
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