Prevention of obesity: is it worth it?

Abstract

BackgroundTackling of obesity is an increasingly important public health priority. It needs a broad range of responses at all levels across a complex system, but action is constrained by a very restricted evidence base of effective interventions. Pressure is growing within an increasingly financially constrained health system to show that activities provide value for money. The traditional approach to the assessment of cost-effectiveness is built from knowledge of effectiveness. Commissioners might therefore be reluctant to fund activities to tackle obesity, and the range of those that are funded is likely to be skewed towards those that are amenable to traditional assessment of effectiveness, which might not be the most appropriate set of approaches. We set out to develop an economic model that would allow commissioners and others to make objective judgments about interventions for which robust data on effectiveness are lacking. MethodsWe consulted with commissioners and identified the need for a practical guide or electronic aid for the cost-effectiveness and cost or economic effect of interventions. We reviewed the scientific literature to identify existing approaches to economic analysis of obesity interventions and draw attention to promising approaches that would be applicable to modelling in the absence of effectiveness data. We developed a draft model based on some of these more promising approaches, and are testing this model with an advisory group of commissioners and academics before finalising and disseminating our work. FindingsOur approach enables evidence-based judgments to be made about the value of plausible interventions even without published evidence of effectiveness or cost-effectiveness. When effectiveness evidence exists, it enables users to estimate the probable economic benefits and cost benefits of an intervention. In the absence of such evidence, the user can estimate how effective the intervention would need to be to be economically viable. For example, a user would enter details (eg, age, sex, weight, and height) of the target population for an intervention and the costs of the intervention. The model would calculate the amount of weight loss needed within that population for the benefits of the intervention to outweigh costs. This information would allow commissioners to make informed decisions about funding of obesity interventions and act rationally in a climate of evidential uncertainty. InterpretationThis approach is evidence-based, but also enables a more informed and creative approach to the commissioning of obesity interventions. It could even help to support the commissioning of broader systems approaches to obesity prevention that seem unlikely in the existing evidence framework. FundingNational Obesity Observatory and UK Department of Health.