The prevention, treatment and management of disease are closely linked to how the causes of a particular disease are explained. For multi-factorial conditions, the causal explanations are inevitably complex and competing models may exist to explain the same condition. Selecting one particular causal explanation over another will carry practical and ethical consequences that are acutely relevant for health policy. In this paper our focus is two-fold; the different models of causal explanation that are put forward within current scientific literature for (...) the high and rising prevalence of the common complex conditions of coronary artery disease and type 2 diabetes mellitus ; and how these explanations are taken up within national health policy guidelines. We examine the causal explanations for these two conditions through a systematic database search of current scientific literature. By identifying different causal explanations we propose a three-tier taxonomy of the most prominent models of explanations: evolutionary, lifecourse, and lifestyle and environment. We elaborate this taxonomy with a micro-level thematic analysis to illustrate how some explanations are semantically and rhetorically foregrounded over others. We then investigate the uptake of the scientific causal explanations in health policy documents with regard to the prevention and management recommendations of current National Service Frameworks for CAD and T2D. Our findings indicate a lack of congruence between the complexity and frequent overlap of causal explanations evident in the scientific literature and the predominant focus on lifestyle recommendations found in the mainstream health policy documents. (shrink)

What kind of a thing are chronic diseases? Are they objects, bundles of signs and symptoms, properties, processes, or fictions? Rather than using concept analysis—the standard approach to disease in the philosophy of medicine—to answer this metaphysical question, I use a bottom-up, inductive approach. I argue that chronic diseases are bodily states or properties—often dispositional, but sometimes categorical. I also investigate the nature of related pathological entities: pathogenesis, etiology, and signs and symptoms. Finally, I defend my view against alternate accounts (...) of the nature of disease. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...) explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)