Diabetes Control: Insights from Complexity Science
The development of complexity science and non-linear dynamics coincided with the emergence of diabetes as a major threat to human health during the twentieth century. Control of blood glucose levels (glycaemia) is important both to alleviate symptoms and prevent longer term complications. Much research has focussed on lifestyle manoeuvres, pharmaceutical agents and educational programmes to help achieve these outcomes. Type 1 individuals require injected insulin and need to replace the usual homeostatic feedback mechanisms with adaptive behavioural responses to glycaemic displacements. Patient-centred self-management became possible partly through self-monitoring technology, and responded to the need for flexibility as a determinant of quality of life. Initially this appeared to contradict the traditional approach in which regularity was seen as the source of stability. Flexibility is now recognised as a useful lever to promote stability where immediate, real-time decisions are required to navigate blood glucose close to physiological levels. The implications of this insight for self-management are still not fully developed but are explored in this chapter. From a dynamical perspective, successful control requires convergent patterns reflecting the system’s resilience to disruption, but the static equilibrium condition may be difficult to achieve in practice. More dynamical models involve harnessing rather than extinguishing movement to optimise flexibility and minimise variation. Future research may enable us to identify the dynamical patterns most appropriate for the individual. This is likely to require a mixed methods approach, to arrive at a more adequate dynamical understanding and definition of glycaemic stability.