Poster Presentation Australian & New Zealand Obesity Society 2015 Annual Scientific Meeting

Combining DALYs and QALYs weights in epidemiological modelling  (#256)

Ana Maria AM Mantilla Herrera 1 , Lennert LV Veerman , Jan JB Barendregt
  1. The University of Queensland, Brisbane, QLD, Australia

As the prevalence of obesity in children and adults continues to rise, the challenge to inform effective obesity interventions becomes more crucial.  Excess body weight has been strongly associated with a plethora of metabolic disturbances and obesity-related costs. These obesity-related consequences are the result of obesity itself and the conditions arising from it. 

Despite the twofold effect of high body weight, most analyses of obesity interventions only assess the impact on quality of life indirectly, through changes in the burden of specific obesity-related diseases. Following this approach, the scope and benefits of interventions under evaluation are limited to the population that suffers from the included conditions.

Modifying a proportional multi-state life table model we included both the direct and indirect effects of obesity within the same approach. Since there is no DALY weight for obesity, a measure of QALY loss due to obesity allowed to incorporate relevant aspects of health benefit to the population.  To populate the model, we used Australian epidemiological data from the 2010 Global Burden of Disease study. We quantified the relationship between obesity and quality of life based on the literature.  Outcomes from the model are measured in terms of the cost effectiveness and health-adjusted life years of obesity interventions including uncertainty analysis.

Preliminary results show that QALY weights and DALY weights can be combined into an overall disability measure while avoiding double-counting. QALY weights for obesity were translated into a disability estimate using the change in the prevalence of obesity before and after interventions.

Results will report and compare the health benefits of obesity interventions targeting different age groups. The combination of both effects of obesity under the same methodology will provide valuable insights into the further potential gain of policies and the relative size of obesity effects on Health Adjusted life Years.