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Sugar-Sweetened Beverage Demand and Tax Simulation for Federal Food Assistance Participants: A Case of Two New England States

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Abstract

Background

Excessive consumption of sugar-sweetened beverages is a major concern in the efforts to improve diet and reduce obesity in USA, particularly among low-income populations. One of the most commonly proposed strategies to reduce sugar-sweetened beverage consumption is increasing beverage prices through taxation.

Objective

The objective of this study was to evaluate whether and how price-based policies could reduce sugar-sweetened beverage consumption among participants in the federal Supplemental Nutrition Assistance Program.

Methods

Using point-of-sale data from a regional supermarket chain (58 stores), we estimated the responsiveness of demand to sugar-sweetened beverage price changes among Supplemental Nutrition Assistance Program-participating families with young children. Own-price and cross-price elasticities for non-alcoholic beverages were estimated using a Quadratic Almost Ideal Demand System model.

Results

The study found evidence that a tax-induced sugar-sweetened beverage price increase would reduce total sugar-sweetened beverage purchases among Supplemental Nutrition Assistance Program participants, who were driven by purchase shifts away from taxed sodas and sports drinks to non-taxed beverages (bottled water, juice, milk). The substitution of non-taxed caloric beverages decreases the marginal effects of the sugar-sweetened beverage tax, yet the direct tax effects are large enough to reduce the overall caloric intake, with the average net reduction in monthly calories from sugar-sweetened beverages estimated at around 8% for a half-cent per ounce tax and 16% for a one cent per ounce tax.

Conclusion

A beverage price increase in the form of an excise tax would reduce sugar-sweetened beverage consumption and increase healthier beverage purchases among low-income families.

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References

  1. Ogden CL, Carroll MD, Lawman HG, et al. Trends in obesity prevalence among children and adolescents in the United States, 1988-1994 through 2013–2014. JAMA. 2016;315(21):2292–9.

    Article  PubMed  CAS  Google Scholar 

  2. Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in obesity among adults in the United States, 2005 to 2014. JAMA. 2016;315(21):2284–91.

    Article  PubMed  CAS  Google Scholar 

  3. Kim DD, Basu A. Estimating the medical care costs of obesity in the United States: systematic review, meta-analysis, and empirical analysis. Value Health. 2016;19(5):602–13.

    Article  PubMed  Google Scholar 

  4. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff. 2009;28(5):822–31.

    Article  Google Scholar 

  5. Malik VS, Schulze MB, Hu FB. Intake of sugar-sweetened beverages and weight gain: a systematic review. Am J Clin Nutr. 2006;84(2):274–88.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Brownell KD, Farley T, Willett WC, Popkin BM, Chaloupka FJ, Thompson JW, Ludwig DS. The public health and economic benefits of taxing sugar-sweetened beverages. N Engl J Med. 2009;361(16):1599–605.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Brownell KD, Frieden TR. Ounces of prevention: the public policy case for taxes on sugared beverages. N Engl J Med. 2009;360(18):1805–8.

    Article  PubMed  CAS  Google Scholar 

  8. Andreyeva T, Chaloupka FJ, Brownell KD. Estimating the potential of taxes on sugar-sweetened beverages to reduce consumption and generate revenue. Prev Med. 2011;52(6):413–6.

    Article  PubMed  Google Scholar 

  9. Lin BH, Guthrie J. How do low-income households respond to food prices? Economic Information Bulletin No. 29(5): 1–4. Washington, DC: US Department of Agriculture, Economic Research Service; 2007.

  10. Dharmasena S, Capps O. Intended and unintended consequences of a proposed national tax on sugar-sweetened beverages to combat the US obesity problem. Health Econ. 2012;21(6):669–94.

    Article  PubMed  Google Scholar 

  11. Leftin JE, Strayer MM. Trends in Supplemental Nutrition Assistance Program participation rates: fiscal year 2002 to fiscal year 2009. Washington, DC: Mathematica Policy Research; 2011.

    Google Scholar 

  12. US Department of Agriculture, Food and Nutrition Service. Supplemental Nutrition Assistance Program: eligible food items. 2018; Washington, DC. http://www.fns.usda.gov/snap/retailers/eligible.htm. Accessed May 2018.

  13. US Department of Agriculture, Food and Nutrition Service. Monthly SNAP participation and benefits. 2018; Washington, DC. http://www.fns.usda.gov/pd/34snapmonthly.htm. Accessed May 2018.

  14. Just DR. Behavioral economics, food assistance, and obesity. Agr Resour Econ Rev. 2006;35(2):209–20.

    Article  Google Scholar 

  15. Guthrie JF, Lin BH, Ver Ploeg M, Frazao E. Can food stamps do more to improve food choices? US Department of Agriculture, Economic Research Service. Economic Information Bulletin No. 29(1). 2007. https://www.ers.usda.gov/publications/pub-details/?pubid=44191. Accessed May 2018.

  16. Ver Ploeg M, Ralston K. Food stamps and obesity: what do we know? US Department of Agriculture, Economic Research Service. Economic Information Bulletin No. 34. 2008. https://www.ers.usda.gov/publications/pub-details/?pubid=44224. Accessed May 2018.

  17. Leung CW, Villamor E. Is participation in food and income assistance programmes associated with obesity in California adults? Results from a state-wide survey. Public Health Nutr. 2011;14(4):645–52.

    Article  PubMed  Google Scholar 

  18. Andreyeva T, Luedicke J, Henderson KE, Tripp AS. Grocery store beverage choices by participants in federal food assistance and nutrition programs. Am J Prev Med. 2012;43(4):411–8.

    Article  PubMed  Google Scholar 

  19. Food Research and Action Center. A review of strategies to bolster SNAP’s role in improving nutrition as well as food security. 2011. http://frac.org/wp-content/uploads/SNAPstrategies.pdf. Accessed May 2018.

  20. Andreyeva T, Tripp A, Schwartz MB. Dietary quality of Americans by Supplemental Nutrition Assistance Program participation status: a systematic review. Am J Prev Med. 2015;49(4):594–604.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Leung CW, Ding EL, Catalano PJ, Villamor E, Rimm EB, Willett WC. Dietary intake and dietary quality of low-income adults in the Supplemental Nutrition Assistance Program. Am J Clin Nutr. 2012;96(5):977–88.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Leung CW, Blumenthal SJ, Hoffnagle EE, Jensen HH, Foerster SB, Cheung LW, et al. Association of food stamp participation with dietary quality and obesity in children. Pediatrics. 2013;131(3):463–72.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Leung CW, Willett WC, Ding EL. Low-income Supplemental Nutrition Assistance Program participation is related to adiposity and metabolic risk factors. Am J Clin Nutr. 2012;95(1):17–24.

    Article  PubMed  CAS  Google Scholar 

  24. Dharmasena S, Bessler DA, Capps O. Food environment in the United States as a complex economic system. Food Policy. 2016;61:163–75.

    Article  Google Scholar 

  25. Huang KS, Lin BH. Estimation of food demand and nutrient elasticities from household survey data. Washington, DC: US Department of Agriculture, Economic Research Service; 2000.

    Google Scholar 

  26. Zhen C, Wohlgenant MK, Karns S, Kaufman P. Habit formation and demand for sugar-sweetened beverages. Am J Agric Econ. 2011;931(1):175–93.

    Article  Google Scholar 

  27. Yen ST, Lin BH, Smallwood DM, Andrews M. Demand for nonalcoholic beverages: the case of low-income households. Agribusiness. 2004;20(3):309–21.

    Article  Google Scholar 

  28. Fletcher JM, Frisvold DE, Tefft N. The effects of soft drink taxes on child and adolescent consumption and weight outcomes. J Publ Econ. 2010;94(11):967–74.

    Article  Google Scholar 

  29. Dharmasena S, Davis GC, Capps O. Partial versus general equilibrium calorie and revenue effects associated with a sugar-sweetened beverage tax. J Agric Res Econ. 2014;39(2):157–73.

    Google Scholar 

  30. Smith TA, Lin BH, Leen JY. Taxing caloric sweetened beverages potential effects on beverage consumption, calorie intake, and obesity. Economic Research Report No. 100. Washington DC: US Department of Agriculture, Economic Research Service; 2010.

  31. Banks J, Blundell R, Lewbel A. Quadratic Engel curves and consumer demand. Rev Econ Stat. 1997;79(4):527–39.

    Article  Google Scholar 

  32. Goldman SM, Uzawa H. A note on separability in demand analysis. Econometrica. 1964;32(3):387–98.

    Article  Google Scholar 

  33. Zhen C, Finkelstein EA, Nonnemaker JM, Karns SA, Todd JE. Predicting the effects of sugar-sweetened beverage taxes on food and beverage demand in a large demand system. Am J Agric Econ. 2013;96(1):1–25.

    Article  PubMed Central  Google Scholar 

  34. Hausman J. Sources of bias and solutions to bias in the consumer price index. J Econ Perspect. 2003;17(1):23–44.

    Article  Google Scholar 

  35. Abel JR, Berndt ER, White AG. Price indexes for Microsoft’ personal computer software products. Hard-to-measure goods and services: essays in honor of Zvi Griliches, vol. 67. Chicago: University of Chicago Press; 2007. p. 269–89.

    Google Scholar 

  36. Blundell R, Pashardes P, Weber G. What do we learn about consumer demand patterns from micro data? Am Econ Rev. 1993;83(3):570–97.

    Google Scholar 

  37. Gebhardt SE, Robin GT. Nutritive value of foods. Home and Garden Bulletin No. 72. Washington, DC: US Department of Agriculture, Agricultural Research Service; 2002.

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Acknowledgements

The authors thank Profs. Bruce A. McCarl and Ximing Wu at Texas A&M University who mentored and advised on this research as a dissertation chapter, which enabled substantial improvements in the analytical framework and design of this study. The authors are grateful for the constructive suggestions and detailed comments from the two anonymous reviewers. The views expressed herein are those of the authors and cannot be attributed to the affiliated organizations.

Data Availability

The proprietary scanner data from the grocery chain in this study is confidential and not available for sharing.

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Authors and Affiliations

Authors

Contributions

TA designed the concept of this study and assembled the raw microdata. TJ performed all analyses and analyzed the results. TJ wrote the main paper, and both TJ and TA discussed the results and implications and contributed to drafting the manuscript.

Corresponding author

Correspondence to Theepakorn Jithitikulchai.

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Funding

Proprietary data for this study were funded by a grant from the Economic Research Service at the US Department of Agriculture and work was supported in part by the Rudd Foundation.

Conflict of interest

Theepakorn Jithitikulchai and Tatiana Andreyeva have no conflicts of interest directly relevant to the content of this article.

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Jithitikulchai, T., Andreyeva, T. Sugar-Sweetened Beverage Demand and Tax Simulation for Federal Food Assistance Participants: A Case of Two New England States. Appl Health Econ Health Policy 16, 549–558 (2018). https://doi.org/10.1007/s40258-018-0399-1

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