%0 Journal Article
%T Conceptualising population health: from mechanistic thinking to complexity science
%A Saroj Jayasinghe
%J Emerging Themes in Epidemiology
%D 2011
%I BioMed Central
%R 10.1186/1742-7622-8-2
%X Population health is defined as 'the health outcomes of a group of individuals, including the distribution of such outcomes within the group' [1]. The approach in population health is to improve the health of an entire population and goes beyond the individual focus in medicine or preventive health. This paper proposes that the discourse in population health is dominated by a Newtonian mechanistic view, and there is much to gain by embracing concepts in Complexity Science.We begin with a brief description and analysis of the mechanistic model, its influence on social sciences and on the way we perceive population health. This is followed by an outline of the new paradigm influenced by Complexity Science and an exploration as to how it sheds light on our understanding of determinants of health.The mechanistic interpretation of reality can be traced to the influential work by Ren¨¦ Descartes and Sir Isaac Newton. Their explanations and theories predicted with a high degree of accuracy most physical phenomena relating to motion, optics and gravity. This paradigm has at least three principles that are especially relevant to population health: reductionism, linearity and hierarchy [2]. The reductionist approach assumes that the whole system (or the macroscopic properties) can be understood by identifying, describing and analysing all its constituent parts (i.e. its microscopic components). The often quoted example is the unlocking of a clock's mechanism by examining its constituent parts. A linear system has two features: proportionality (i.e. the output changes in proportion to the input or a straight-line relationship with the input); and superposition (i.e. the effects of the combined action of different inputs can be figured out and predicted by dissecting the input-output relationships of the individual components) [3]. The overall output is a summation of the constituent parts, and the components of a linear system literally "add up" - there are no surprises or anom
%U http://www.ete-online.com/content/8/1/2