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Obesity has escalated to epidemic proportions over the past 30 years resulting in increased disease burden and healthcare costs. The aim of this paper was to analyse different costing methods for obesity. Several databases have been searched to identify eligible literature estimating obesity cost. These were categorized into databases, patient-attributable fraction (PAF) and modelling studies. Studies from the United States were used to explore effects of study designs on cost outcomes. Our results show that cost outcomes are largely affected by underlying study designs, such as population size, age, cost categories (medical expenditure vs. total costs), length of the data collection and body mass index cut-offs. Three study types are likely to have an impact on reported costs, with modelling studies providing the most conservative estimates. Database studies can help to increase the overall awareness of the economic burden of obesity. PAF studies can make the obesity disease more tangible by drawing connections to diseases. Decision makers need to be aware of the different purposes and weaknesses of the studies when interpreting cost outcomes. Further research is needed to refine the existing methods and provide high-quality data accounting for the complexity of the disease.

Original publication




Journal article


Obes Rev

Publication Date





693 - 706


Cost, modelling, obesity, patient-attributable fraction, Comorbidity, Cost of Illness, Epidemics, Health Care Costs, Humans, National Health Programs, Obesity, United States