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Causal models and causal modelling in obesity: foundations, methods and evidence

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Yu, Xiaoxin 
Dawid, Philip 
Smith, George Davey 
French, Stephen J. 


Discussing causes in science, if we are to do so in a way that is sensible, begins at the root. All too often, we jump to discussing specific postulated causes but do not first consider what we mean by, for example, causes of obesity or how we discern whether something is a cause. In this paper, we address what we mean by a cause, discuss what might and might not constitute a reasonable causal model in the abstract, speculate about what the causal structure of obesity might be like overall and the types of things we should be looking for, and finally, delve into methods for evaluating postulated causes and estimating causal effects. We offer the view that different meanings of the concept of causal factors in obesity research are regularly being conflated, leading to confusion, unclear thinking and sometimes nonsense. We emphasize the idea of different kinds of studies for evaluating various aspects of causal effects and discuss experimental methods, assumptions and evaluations. We use analogies from other areas of research to express the plausibility that only inelegant solutions will be truly informative. Finally, we offer comments on some specific postulated causal factors. This article is part of a discussion meeting issue ‘Causes of obesity: theories, conjectures and evidence (Part II)’.


Peer reviewed: True

Publication status: Published


causal Inference, causal model, randomization, assignment mechanism, causation, counterfactual

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Philosophical Transactions of the Royal Society B

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The Royal Society