Despite major investment in both research and policy, many pressing contemporary public health challenges remain. To date, the evidence underpinning responses to these challenges has largely been generated by tools and methods that were developed to answer questions about the effectiveness of clinical interventions, and as such are grounded in linear models of cause and effect. Identification, implementation, and evaluation of effective responses to major public health challenges require a wider set of approaches 1,2 and a focus on complex systems. 3,4 A complex systems model of public health conceptualises poor health and health inequalities as outcomes of a multitude of interdependent elements within a connected whole. These elements affect each other in sometimes subtle ways, with changes potentially reverberating throughout the system. 5 A complex systems approach uses a broad spectrum of methods to design, implement, and evaluate interventions for changing these systems to improve public health.Complex systems are defined by several properties, including emergence, feedback, and adaptation. 3 Emergence describes the properties of a complex system that cannot be directly predicted from the elements within it and are more than just the sum of its parts. For example, the changing distribution of obesity across the population can be conceptualised as an emergent property of the food, employment, transport, economic, and other systems that shape the energy intake and expenditure of individuals. Feedback describes the situation in which a change reinforces or balances further change. For example, if a smoking ban in public places reduces the visibility and convenience of smoking, and this makes it less appealing, fewer young people might then start smoking, further reducing its visibility, and so on in a reinforcing loop. Adaptation refers to adjustments in behaviour in response to interventions, such as a tobacco company lowering the price of cigarettes in response to a public smoking ban.Rhetoric urging complex systems approaches to public health is only rarely operationalised in ways that generate relevant evidence or effective policies. 1,6 Public health problems that emerge as a property of a complex system cannot necessarily be solved with a simple, single intervention, but the interacting factors within the system can potentially be reshaped to generate a more desirable set of outcomes. 7,8 Achievement of meaningful impacts on complex multicausal problems, like obesity, requires more than single interventions, such as traffic light food labelling or exercise on prescription, many of which require high levels of individual agency, have low reach and impact, and tend to widen health inequalities. 9-11 Shifts within multiple elements across the many systems that influence obesity are required, some of which might only have small effects on individuals but can drive large changes when aggregated at population level. 12 Although randomised controlled trials of individual-level interventions are relatively strai...
Background To make effective progress towards a global reduction in obesity prevalence, there needs to be a focus on broader structural factors, beyond individual-level drivers of diet and physical activity. This article describes the use of a systems framework to develop obesity prevention policies with adolescents. The aim of this research was to use the group model building (GMB) method to identify young people’s perceptions of the drivers of adolescent obesity in five European countries, as part of the EU-funded Co-Create project. Methods We used GMB with four groups of 16–18-year-old in schools in each of the five European countries (The Netherlands, Norway, Poland, Portugal and the UK) to create causal loop diagrams (CLDs) representing their perceptions of the drivers of adolescent obesity. The maps were then merged into one, using a new protocol. Results Two hundred and fifty-seven participants, aged 16–18 years, engaged in 20 separate system mapping groups, each of which generated 1 CLD. The findings were largely congruent between the countries. Three feedback loops in the merged diagram particularly stand out: commercial drivers of unhealthy diets; mental health and unhealthy diets; social media use, body image and motivation to exercise. Conclusions GMB provides a novel way of eliciting from young people the system-based drivers of obesity that are relevant to them. Mental health issues, social media use and commercial practices were considered by the young people to be key drivers of adolescent obesity, subjects that have thus far had little or no coverage in research and policy.
ObjectivesMost non-communicable diseases are preventable and largely driven by the consumption of harmful products, such as tobacco, alcohol, gambling and ultra-processed food and drink products, collectively termed unhealthy commodities. This paper explores the links between unhealthy commodity industries (UCIs), analyses the extent of alignment across their corporate political strategies, and proposes a cohesive systems approach to research across UCIs.MethodsWe held an expert consultation on analysing the involvement of UCIs in public health policy, conducted an analysis of business links across UCIs, and employed taxonomies of corporate political activity to collate, compare and illustrate strategies employed by the alcohol, ultra-processed food and drink products, tobacco and gambling industries.ResultsThere are clear commonalities across UCIs’ strategies in shaping evidence, employing narratives and framing techniques, constituency building and policy substitution. There is also consistent evidence of business links between UCIs, as well as complex relationships with government agencies, often allowing UCIs to engage in policy-making forums. This knowledge indicates that the role of all UCIs in public health policy would benefit from a common approach to analysis. This enables the development of a theoretical framework for understanding how UCIs influence the policy process. It highlights the need for a deeper and broader understanding of conflicts of interests and how to avoid them; and a broader conception of what constitutes strong evidence generated by a wider range of research types.ConclusionUCIs employ shared strategies to shape public health policy, protecting business interests, and thereby contributing to the perpetuation of non-communicable diseases. A cohesive systems approach to research across UCIs is required to deepen shared understanding of this complex and interconnected area and also to inform a more effective and coherent response.
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