In medical science, researchers mostly use the linear model to determine associations among variables, while in reality many associations are likely to be non-linear. Recent advances have shown that associations may be regarded as parts of complex, dynamic systems for which the linear model does not yield valid results. Using as an example the interdepencies between organisms in a small ecosystem, we present the work of Sugihara et al. in Science 2012, 338:496-500 who developed an alternative non-parametric method to determine the true associations among variables in a complex dynamic system. In this context, we discuss the work of Jani et al. recently published in BMC Cardiovascular Disorders, describing a non-linear, J-shaped curve between a series of cardiometabolic risk factors and depression. Although the exact meaning of these findings may not yet be clear, they represent a first step in a different way of thinking about the relationships among medical variables, namely going beyond the linear model.
|Status||Published - 28-okt.-2014|