Rising obesity rates across the United States have become not only a public health concern, but also a fiscal one. In an era with constrained healthcare resources both at the federal and state levels, reducing obesity and its negative consequences are prominent on the policy agenda. Experiences in tobacco control have greatly shaped the design and evaluation of policies aimed to change consumer behavior at the population level. Tax to discourage unhealthy food and beverages is one of many policy initiatives being discussed nationwide. While a wide range of obesity policies-many of them at the state level-highlight the potential to reduce the downstream health and economic burdens of obesity, analytical tools to estimate their magnitude are lacking. Public health researchers and legislators across the country intensely seek concrete, evidence-based tools to enumerate the value of obesity prevention policies especially at the state level. The overarching goal of this proposal is to establish the data and methods repertoire within an analytical model for estimating state-level healthcare cost savings and productivity gains from reducing obesity.
We aim to: (1) Estimate 10-year healthcare cost savings from obesity reduction by state. By linking existing state-level surveillance systems, we aim to create a tool that estimates the monetary values of obesity-attributable diseases prevented under given reductions in BMI for the whole or a segment of the population. We will also assess the monetary values of the productivity gained (in the forms of reduced absenteeism and presenteeism) in an exploratory analysis. (2) Investigate the potential downstream impact on obesity levels, healthcare costs, and productivity gain from a state-level excise tax on SSBs, a case study of a state-level tax-based policy. The proposed research capitalizes our team's collective research portfolio and the unique assembly of expertise in economics, epidemiology, and nutrition policy. The innovation of this proposed research is three- fold: (1) for the first time we will critically compare two commonly-used approaches (incidence-based and prevalence-based) to tally the economic burden of obesity;(2) we will incorporate an extensive list of state- level data to reflect importnt regional variations on population composition, dietary consumption, employment and wage, and healthcare costs;and (3) we will design a user-friendly, web-based tool to engage stakeholders and facilitate the dissemination of results and methods. Data gaps, uncertainties, and methodological challenges revealed in the proposed activities will contribute to the existing evidence base. The recent political climate indicates that more state-level legislatures will tackl obesity in the years to come, with taxation as a potential vehicle to influence behavior. The proposed research will provide evidence-based tools and anchor points for researchers to assess potential public health benefits. Going forward, the flexibility of the model constructed allows subsequent updates with new data and/or customization with local (e.g. city- level) data. It may also pave the way for designing potential natural experiments.
Rising obesity rates across the United States have become not only a public health concern for states, but also a fiscal one. The proposed research will provide an evidence-based tool to estimate the value of reducing obesity for each state from savings from healthcare costs and productivity gains, using taxes on sugary beverages as a case study. It fills many knowledge gaps and paves the way for designing potential natural experiments.
|Ward, Zachary J; Long, Michael W; Resch, Stephen C et al. (2016) Redrawing the US Obesity Landscape: Bias-Corrected Estimates of State-Specific Adult Obesity Prevalence. PLoS One 11:e0150735|
|Wang, Y Claire; Pamplin, John; Long, Michael W et al. (2015) Severe Obesity In Adults Cost State Medicaid Programs Nearly $8 Billion In 2013. Health Aff (Millwood) 34:1923-31|
|Andreyeva, Tatiana; Luedicke, Joerg; Wang, Y Claire (2014) State-level estimates of obesity-attributable costs of absenteeism. J Occup Environ Med 56:1120-7|