A complex systems approach to obesity: A transdisciplinary framework for action

Obesity is a major public health challenge which continues to increase and disproportionally affects vulnerable population groups, resulting in widening health inequalities. There is consequently an urgent need for innovative approaches to identify and implement evidence-based policy and practice to prevent and treat obesity which has been accelerated by the COVID-19 pandemic.

The population levels of obesity are driven by numerous interacting political, economic, environmental, social, cultural, digital, behavioural, and biological determinants. However, causal links between determinants and how they vary between different groups of individuals are not well defined. The identification, implementation, and evaluation of effective responses to the prevention and treatment of obesity require a set of approaches that work within this complexity.

The limited efforts to date reflect a misunderstanding of the nature of the chronic and complex nature of obesity, and importantly a limited understanding of how the multifaceted nature of the problem should influence how research, policy, and practice approach it. To date, the evidence underpinning the current approach does not reflect the complexity of the condition:

Evidence is largely generated by tools and methods developed to answer questions about the effectiveness of isolated interventions, commonly grounded in linear models of cause and effect. This is the pathway between a cause, for example, exposure to fast food restaurants, and the outcome, obesity, is assumed to be linear, when it is far more complex than this.

There is a focus on individual behaviour, yet social and structural determinants of health have a far greater influence on obesity and contribute more to health inequalities. It is acknowledged that we live in an obesogenic environment, yet most approaches to addressing obesity are focused on behaviour change to support individuals adopt healthy weight behaviours, with little (or no) consideration of the environment in which they live.

Outcomes are largely measured in the short term and the effects of efforts to reduce population obesity will take many years to be realised.

Effectiveness is primarily determined by a narrow focus on weight change, which fails to capture the underlying complexity. Instead of investigating whether a single intervention is (cost-)effective in terms of fixing the problem (i.e. obesity), we need to understand how actions drive positive changes within the system.

A systems approach captures and responds to complexity through a dynamic way of working: bringing together academic, policy, practice, and community representatives to develop a ‘shared understanding of the challenge’ and to integrate action to bring about sustainable, long-term systems change. The benefit of a systems approach to addressing population levels of obesity has been outlined: in 2013, the EPODE logic model retrospectively provided insight into the system dynamics of the programme; the ‘Improving the Health of the Public by 2040’ report acknowledged that responses to major public health challenges require a wider set of approaches; in 2017, Rutter et al. called for ‘a complex systems model of evidence for public health’, which was echoed in 2019, as part of The Lancet commission on obesity. More recently, the logic model underpinning the Amsterdam Healthy Weight Approach (AHWA) was published. There are also examples of projects that have embraced system approaches in an applied setting, as well as toolkits, guidance documents, and operational frameworks. These resources demonstrate that the concept of a systems approach to obesity is not new, and importantly that systems methods do not have to replace traditional methods, but instead incorporate and enhance them. Despite this activity and rhetoric, systems approaches are rarely operationalised in ways that generate relevant evidence or effective policies.