RTI International has proposed innovative methodological and applied research entitled Geospatial and Time Series Analysis of Food Prices and Obesity: Evidence from Sugar-Sweetened Beverage Prices to enhance scientific capabilities for conducting obesity policy research. This project is motivated by the research community's need for high-quality community-level measures of food prices and by the currently active debate among academic researchers, policy analysts, and lawmakers on the efficacy of large sugar- sweetened beverage (SSB) taxes. The proposed spatial economics research will determine the feasibility of constructing high-quality community-level food price measures using optical scanner data on supermarket sales and household purchase records collected by The Nielsen Company. The utility of the price measures in informing obesity policy will be validated by matching these measures with geocoded National Health Interview Survey (NHIS) data and examining the causal effect of SSB prices on body mass index (BMI). Price endogeneity will be controlled by using instrumental variables that are correlated with the costs of SSB and non-SSB supply but uncorrelated with SSB and non-SSB demand. The proposed research will directly benefit obesity policy researchers and policy makers through (1) the development of new food price microdata and (2) the enhanced understanding of the prospect of leveraging economic incentives such as junk food taxes and/or healthy food subsidies to reverse the obesity epidemic. Upon completion, the price microdata will be made available to the research community. The proposed 2-year project has two aims:
Aim 1 : Gain insights regarding the feasibility of developing high-quality community-level measures of food prices based on existing scanner data on supermarket sales and household purchases and matching these price measures with geocoded health survey data.
Aim 2 : Validate the utility of the food price microdata in an econometric model relating obesity to SSB prices and measures of the built environment. Use the results to shed light on whether large SSB taxes are likely to affect health outcomes.
We propose to construct spatial time series prices for sugar-sweetened beverages (SSBs) and non-SSBs at the community level using optical scanner data on supermarket sales and household food purchases and geographic information system (GIS) databases. The food price microdata will be merged with geocoded respondents in the National Health Interview Survey (NHIS) to examine the effect of SSB prices on body mass index (BMI). We will use the instrumental variables method to control for endogenous food prices. The new food price microdata will be made available to the research community upon completion.
|Finkelstein, Eric A; Strombotne, Kiersten L; Zhen, Chen et al. (2014) Food prices and obesity: a review. Adv Nutr 5:818-21|
|Zhen, Chen; Finkelstein, Eric A; Nonnemaker, James et al. (2014) Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System. Am J Agric Econ 96:1-25|
|Zhen, Chen; Brissette, Ian F; Ruff, Ryan R (2014) By Ounce or By Calorie: The Differential Effects of Alternative Sugar-Sweetened Beverage Tax Strategies. Am J Agric Econ 96:1070-1083|