Longtime readers -- if there are in truth any out there -- are likely familiar with my concern that far too much discussion and analysis of disease causality, both within and without epidemiology and public health, tend to adopt the traditional scientific focus on linear causation of relatively simple systems. This is a proble, I maintain, because the myriad systems and subsystems which shape health and illness in populations are neither linear, simple, nor closed, but are rather nonlinear, complex, and open.
Hence, I have thought for some time that insights from nonlinear dynamical systems theory, or complex adaptive systems analysis, is really best-suited for understanding both disease causality and appropriate public health policies (and the ethical implications therein). Of course, I am hardly alone in this belief, and hence I was particularly pleased to see a new article published in the International Journal of Epidemiology authored by Sandro Galea, Matthew Riddle, and George A Kaplan. The article is aptly entitled Causal thinking and complex system approaches in epidemiology. Here is the Abstract:
Identifying biological and behavioural causes of diseases has been one of the central concerns of epidemiology for the past half century. This has led to the development of increasingly sophisticated conceptual and analytical approaches focused on the isolation of single causes of disease states. However, the growing recognition that (i) factors at multiple levels, including biological, behavioural and group levels may influence health and disease, and (ii) that the interrelation among these factors often includes dynamic feedback and changes over time challenges this dominant epidemiological paradigm. Using obesity as an example, we discuss how the adoption of complex systems dynamic models allows us to take into account the causes of disease at multiple levels, reciprocal relations and interrelation between causes that characterize the causation of obesity. We also discuss some of the key difficulties that the discipline faces in incorporating these methods into non-infectious disease epidemiology. We conclude with a discussion of a potential way forward.
Notwithstanding my general skepticism at obesity discourse, the article is highly recommended.
(h/t Equidad)
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