Economic evaluations of obesity interventions are critical to informing policymakers and clinical practitioners about best-value prevention and treatment interventions. However, existing studies often fail to measure appropriate outcomes over sufficient time periods and to adequately address the complexity of data, environments and outcomes. An international, multidisciplinary workshop in Ireland (May 2023) addressed these issues through scientific presentations on obesity modelling, group discussions and interactive small-group exercises. Nineteen presenters and participants co-created a list of research needs, priorities and strategies for the long-term study of obesity and its complications. To support availability of relevant outcome and cost data for health economic analyses, participants highlighted a need to define standards for data collection, data sharing, modelling, and integrating a systems perspective. For example, regarding data collection, careful consideration must be given to selecting valid and relevant health-related outcomes for determining future health risk. Although these issues have been previously highlighted, they remain critical barriers to comprehensive economic obesity studies. To identify best-value obesity interventions, researchers should prioritise strategies to overcome these barriers. This includes early engagement with multidisciplinary stakeholders to integrate diverse perspectives. Developing infrastructure to support international collaborations between researchers, policymakers and patient representatives was also recommended. Additionally, establishing best-practice guidelines could help researchers navigate the complexities of obesity data, environments and outcomes, particularly in data-scarce research environments. The creation of a core outcomes set for obesity would standardise measures for economic evaluations, thereby facilitating more robust cross-country comparisons of intervention effects and improving the evidence base and overall quality of future obesity research.
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