Causation and models of disease in epidemiology
Introduction
Two conceptual questions currently face epidemiology, both relating to causation. First, how should it handle certain diseases, which appear to be etiologically more complex than the infections and deficiencies by which epidemiology made its name? In particular, chronic non-communicable diseases (CNCDs) account for a larger proportion of deaths, at least in the industrialised world, than they did in 1900 (Rockett, 1999, p. 8), and attract more epidemiological attention. Yet they often do not seem susceptible to definition in terms of any one causative agent: their etiology is typically complex.
Second, how should epidemiology respond to newly identified causes of disease? Epidemiology has moved beyond obvious environmental causes of illness (such as prolonged extreme cold) and uncovered increasingly complex and sometimes surprising environmental causes of disease. And in place of the old notion of a ‘constitution’, the discipline has had to grapple with a newly discovered category of cause: genetics. The increased depth and complexity of our knowledge of both genetic and environmental determinants of health places pressure on aspects of the conceptual framework of epidemiology: in particular, on the way it thinks about disease causation.
Devising a conceptual framework for thinking about disease causation has proved astonishingly difficult. On the one hand, the early history of epidemiology appears to attest to the power of insisting that every disease has one cause that is necessary and, in limited circumstances, sufficient for the disease. I call this way of thinking about disease etiology the monocausal model of disease. This model suits infectious diseases such as TB and cholera well, along with parasitic infestations and diseases of deficiency. On the other hand, the monocausal model is a terrible fit for CNCDs such as lung cancer or diabetes. It is theoretically possible that a condition like diabetes has a single necessary and, in some circumstances, sufficient cause, which we have not yet discovered. But surely, it is also a theoretical possibility that there is no cause for diabetes satisfying that description. And even if there is, it is not clear how insisting that there must be such a cause helps us achieve public health or clinical goals, if we don’t know what it is. The causes that we are able to identify are causal risk factors: neither necessary nor sufficient. These are all we have to work with. Accordingly, a view of disease as multifactorial now dominates epidemiology. But this is not an entirely happy situation, because it fails to mark what looks like a real etiological difference between diseases like cholera and conditions like lung cancer. The monocausal model has had some striking successes in the history of epidemiology, and these successes are left unexplained by the mere assertion that disease causation is multifactorial. Unless we can explain the successes of the monocausal model in terms of modern multifactorial thinking, there is a risk of throwing the baby out with the bathwater.
In this paper I want to address the tension that arises between monocausal and multifactorial models of disease. Both are, to some extent, rational reconstructions of positions that are implicit in the epidemiological literature. There have been very few (if any) attempts to lay out these two ways of thinking about disease causation, in a fully explicit and philosophically rigorous manner. Accordingly there is a danger of attacking straw men. It should be understood that these models of disease, as I state them, are attempts to make explicit ways of thinking that are implicit: so I refrain from attributing the result of this exercise as an opinion of any historical or contemporary figure. Nevertheless, I do think—and will argue—that these ways of thinking are present in various extant efforts to conceptualise disease causation. Once I have assessed the strengths and weaknesses of these two models of disease, I will propose a ‘contrastive’ model, which attempts to preserve the strengths of the monocausal model within a multifactorial framework.
Section snippets
The monocausal model
Perhaps the closest medicine has come to an explicit statement of the monocausal model of disease is Koch’s postulates. However, contrary to the impression sometimes conveyed, even these postulates have no authoritative statement. Koch’s own work does not define the postulates authoritatively (see Evans, 1993, Ch. 2, for several versions and discussion). Moreover, the postulates are shot through with practical concerns; they do not constitute a philosophical model of disease. This reflects the
Problems for the monocausal model
Even if successes can be claimed for it, the monocausal model as I have sketched it suffers from a number of objections. Starting with the most obvious, the monocausal model provides no justification for its restriction on the number of causes by which a disease may be defined. Why should there not be states of ill health where two, or a hundred and one, kinds of cause are used for classification? To take a simple example, swine influenza as it occurs naturally is caused by the synergistic
Multifactorial approaches
Until the latter part of the nineteenth century, medical text books contained lengthy lists of causes for any given condition. Effort was sometimes made to distinguish immediate causes from remote, or to make some other distinction of this sort; but it was nevertheless standard to find a great many different causes listed in the etiology of a single condition, and also to find a number of repeat offenders among the causes of a great many different diseases (Carter, 2003, Ch. 1). Various kinds
A contrastive model
In Section 3 I listed some problems for the monocausal model of disease, and in Section 4 I argued that a multifactorial approach is also unsatisfactory if it consists in merely rejecting the monocausal model of disease. Accordingly, in this section I shall tentatively propose a more positive multifactorial approach.
The most obvious shortcoming of the monocausal model of disease concerned its restriction of the number of causes (of a certain sort) that a disease may have. Often it seems helpful
Objections
The most obvious shortcoming of the contrastive model I have proposed is that it leaves a crucial component unspecified: it does not tell us anything about the contrast class, and especially about the notion of health. This is one reason that the proposed conditions are necessary but not jointly sufficient. Perhaps it is an exaggeration to call this a model of disease until this gap has been plugged. But my proposal is no worse that the monocausal or multifactorial models in this respect, since
Acknowledgements
I am especially grateful to Ron Zimmern, who first drew my attention to this area. I would also like to thank Sorin Bangu, Richard Barnett, Jonathan Birch, Adam Bostanci, Kevin Brosnan, Vanessa Heggie, Hai Hong, Stephen John, Luis Nacul, Sridhar Venkatapuram, Caroline Wright, Caitlin Wylie, two anonymous referees, and audiences at the Brocher Foundation conference on the Science and Politics of Neglected Disease Research, and in the Department of History and Philosophy of Science at Cambridge,
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