Abstract
Recent years have witnessed prominent calls to tax sugar-sweetened beverages (SSB) to prevent obesity in the United States. Despite efforts to evaluate this proposed policy, limited data and no framework exist for evaluating long-term, dynamic, cumulative health impacts of taxing SSBs while recycling revenue to support related interventions. Systems simulation models offer an important new lens for evaluating policy interventions, but such models have traditionally under-conceptualized key implementation science concerns, such as sustainability, revenue recycling, and bringing interventions to scale. Using a system dynamics model representing implementation dynamics, this study contributes a simulation model to inform policymakers’ understanding of how allocating revenue collected by SSB taxation across sustainable implementation strategies might maximize benefits of such taxation for childhood obesity prevention.
Similar content being viewed by others
References
Andreyeva T, Chaloupka FJ and Brownell KD (2011). Estimating the potential of taxes on sugar-sweetened beverages to reduce consumption and generate revenue. Preventive Medicine 52 (6): 413–416.
Andreyeva T, Long MW and Brownell KD (2010). The impact of food prices on consumption: A systematic review of research on price elasticity of demand for food. American Journal of Public Health 100 (2): 216–222.
Banks J (2005). Discrete-Event System Simulation. Prentice Hall: Upper Saddle River, NJ.
Bar-Yam Y (2006). Improving the effectiveness of health care and public health: A multiple complex systems analysis. American Journal of Public Health 96 (3): 459–466.
Berkey CS et al (2000). Activity, dietary intake, and weight changes in a longitudinal study of preadolescent and adolescent boys and girls. Pediatrics 105 (4): E56.
Blanck HM et al (2012). Let’s go to the park today: The role of parks in obesity prevention and improving the public’s health. Childhood Obes 8 (5): 426–431.
Blevins D, Farmer MS, Edlund C, Sullivan G and Kirchner AE (2010). Collaborative research between clinicians and researchers: A multiple case study of implementation. Implementation Science 5 (76): 1–9.
Brailsford SC, Lattimer VA, Tarnaras P and Turnbull JC (2004). Emergency and on-demand health care: Modeling a large complex system. Journal of Operational Research Society 55 (1): 34–42.
Brink LA, Nigg CR, Lampe SM, Kinston BA, Mootz AL and van Vliet W (2010). Influence of schoolyard renovations on children’s physical activity: The learning landscapes program. American Journal of Public Health 100 (9): 1672–1678.
Brownell KD et al (2009). The public health and economic benefits of taxing sugar-sweetened beverages. New England Journal of Medicine 361 (16): 1599–1606.
Brownell KD and Frieden TR (2009). Ounces of prevention: The public policy case for taxes on sugared beverages. New England Journal of Medicine 360 (18): 1805–1808.
Cavana RY and Clifford LV (2006). Demonstrating the utility of system dynamics for public policy analysis in New Zealand: The case of excise tax policy on tobacco. System Dynamics Review 22 (4): 321–348.
Cohen DA, McKenzie TL, Sehgal A, Williamson S, Golinelli D and Lurie N (2007). Contribution of public parks to physical activity. American Journal of Public Health 97 (3): 509–514.
Dangerfield BC (1999). System dynamics applications to European health care issues. Journal of Operational Research Society 50 (4): 345–353.
Davies R (1985). An assessment of models in a health system. Journal of Operational Research Society 36 (8): 679–687.
DGfA (2010). Dietary guidelines for Americans, http://www.cnpp.usda.gov/DGAs2010-PolicyDocument.htm, accessed 15 January 2013.
Fallah-Fini S, Rahmandad H, Chen H-J, Xue H and Wang Y (2013). Connecting micro dynamics and population distributions in system dynamics models. System Dynamics Review 29 (4): 197–215.
Farley TA, Meriwether RA, Baker ET, Watkins LT, Johnson CC and Webber LS (2007). Safe play spaces to promote physical activity in inner-city children: Results from a pilot study of an environmental intervention. American Journal of Public Health 97 (9): 1625–1631.
Frieden TR, Dietz W and Collins J (2010). Reducing childhood obesity through policy change: Acting now to prevent obesity. Health Affairs 29 (3): 357–363.
Friedman RR and Brownell KD (2012). Sugar-sweetened beverage taxes: An updated policy brief. Rudd Report. Available at, http://www.kickthecan.info/files/documents/Rudd_Policy_2012Brief_Sugar_Sweetened_Beverage_Taxes.pdf, accessed 10 November 2012.
Ghaffarzadegan N, Lyneis J and Richardson GP (2011). How small system dynamics models can help the public policy process. System Dynamics Review 27 (1): 22–44.
Giles-Corti B and Donovan RJ (2002). Socioeconomic status differences in recreational physical activity levels and real and perceived access to a supportive physical environment. Preventive Medicine 35 (6): 601–611.
Glickman DR, Parker L, Sim LJ, Cook HDV and Miller EA (2012). Accelerating Progress in Obesity Prevention-Solving the Weight of the Nation. The National Academies Press: Washington DC.
Green LW (2006). Public health asks of systems science: To advance our evidence-based practice, can you help us get more practice-based evidence? American Journal of Public Health 96 (3): 406–409.
Greenleaf EA and Lehmann DR (1995). Reasons for substantial delay in consumer decision making. Journal of Consumer Research 22 (2): 186–189.
Hall KD (2010). Predicting metabolic adaptation, body weight change, and energy intake in humans. American Journal of Physiology Endocrinology and Metabolism 298 (3): E449–E466.
Hassmiller-Lich K, Ginexi EM, Osgood ND and Mabry PL (2013). A call to address complexity in prevention science research. Preventive Science 14 (3): 279–289.
Hirsch G, Homer J, Evans E and Zielinski A (2010). A system dynamics model for planning cardiovascular disease interventions. American Journal of Public Health 100 (4): 616–622.
Hirsch GB and Immediato CS (1999). Microworlds and generic structures as resources for integrating care and improving health. System Dynamics Review 15 (3): 315–330.
Hirsch GB and Miller S (1974). Evaluating HMO policies with a computer simulation model. Med Care 12 (8): 668–681.
Holt E (2011). Hungary to introduce broad range of fat taxes. Lancet 378 (9793): 755.
Homer JB and Hirsch GB (2006). System dynamics modeling for public health: Background and opportunities. American Journal of Public Health 96 (3): 452–458.
Homer JB, Hirsch GB and Milstein B (2007). Chronic illness in a complex health economy: The perils and promises of downstream and upstream reforms. System Dynamics Review 23 (2–3): 313–343.
Homer J, Hirsch GB, Minniti M and Pierson M (2004). Models for collaboration: How system dynamics helped a community organize cost-effective care for chronic illness. System Dynamics Review 20 (3): 199–222.
Homer J, Milstein B, Wile K, Pratibhu P, Farris R and Orenstein D (2008). Modeling the local dynamics of cardiovascular health: Risk factors, context, and capacity. Preventive Chronic Disease 5 (2): 1–6.
Joffe M and Mindell J (2006). Complex causal process diagrams for analyzing the health impacts of policy interventions. American Journal of Public Health 96 (3): 379–473.
Jones AP, Homer JB, Murphy DL, Essien JDK, Milstein B and Seville DA (2006). Understanding diabetes population dynamics through simulation modeling and experimentation. American Journal of Public Health 96 (3): 488–494.
Just DR, Wansink B, Mancino L and Guthrie J (2008). Behavioral Economic Concepts to Encourage Healthy Eating in School Cafeterias: Experiments and Lessons from College Students. EPP-68 USDA: Washington DC.
Katsaliaki K and Mustafee N (2011). Applications of simulation within the healthcare context. J Oper Res Soc 62 (8): 1431–1451.
Kunc M and Kazakov R (2013). Competitive dynamics in pharmaceutical markets: A case study in the chronic cardiac disease market. Journal of Operational Research Society 64 (12): 1790–1799.
Lane DC (1994). System dynamics practice: A comment on ‘a case study in community care using systems thinking’. Journal of Operational Research Society 45 (3): 361–363.
Lane DC (2000). Looking in the wrong place for healthcare improvements: A system dynamics study of an accident and emergency department. Journal of Operational Research Society 51 (5): 518–531.
Lane DC and Husemann E (2008). System dynamics mapping of acute patient flows. Journal of Operational Research Society 59 (2): 213–224.
Larson NI, Story MT and Nelson MC (2009). Neighborhood environments: Disparities in access to healthy foods in the U.S. American Journal of Preventive Medicine 36 (1): 74–81.
Lee RE, Cubbin C and Winkleby M (2007). Contribution of neighborhood socioeconomic status and physical activity resources to physical activity among women. Journal of Epidemiology Community Health 61 (10): 882–890.
Leischow SJ and Milstein B (2006). Systems thinking and modeling for public health practice. American Journal of Public Health 96 (3): 403–405.
Levy DT, Bauer JE and Lee H-R (2006). Simulation modeling and tobacco control: Creating more robust public health policies. American Journal of Public Health 96 (3): 494–498.
Luke DA and Stamatakis KA (2012). Systems science methods in public health: Dynamics, networks, and agents. Annual Review of Public Health 33: 357–376.
Mahamoud A, Roche B and Homer J (2013). Modeling the social determinants of health and simulating short-term and long-term intervention impacts for the city of Toronto, Canada. Social Science and Medicine 93: 247–255.
Manca DP et al (2014). Implementing and evaluating a program to facilitate chronic disease prevention and screening in primary care: A mixed methods program evaluation. Implementation Science 9 (135): 1–9.
Marcus SE, Leischow SJ, Mabry PL and Clark PI (2010). Lessons learned from the application of systems science to tobacco control at the national cancer institute. American Journal of Public Health 100 (7): 1163–1165.
McArdle WD, Katch F and Katch V (2010). Exercise Physiology: Nutrition, Energy, and Human Performance. Lippincott Williams & Wilkins: Philadelphia.
Milstein B, Homer J and Hirsch G (2010). Analyzing national health reform strategies with a dynamic simulation model. American Journal of Public Health 100 (5): 811–819.
Milstein B, Homer J, Peter Briss P, Burton D and Pechacek T (2011). Why behavioral and environmental interventions are needed to improve health at lower cost. Health Affairs 30 (5): 823–832.
NPAP: National Physical Activity Plan (2010). National physical activity plan for the United States. Available at, http://www.physicalactivityplan.org/theplan.php, accessed 25 November 2012.
Ogden CL, Kit BK, Carroll MD and Park S (2011). Consumption of Sugar Drinks in the United States, 2005–2008, CDC/NCHS, National Health and Nutritional Examination Survey, 2005–2008. NCHS Data Brief Number 71, http://www.cdc.gov/nchs/data/databriefs/db71.htm, accessed on 20 May 2013.
Osgood ND, Dyck RF and Grassmann WK (2011). The inter- and intragenerational impact of gestational diabetes on the epidemic of type 2 diabetes. American Journal of Public Health 101 (1): 173–179.
Repenning NP and Sterman JD (2001). Nobody ever gets credit for fixing problems that never happened. California Management Review 43 (4): 64–88.
Ritchie-Dunham JL and Mendéz GJF (1999). Evaluating epidemic intervention policies with systems thinking: A case study of dengue fever in Mexico. System Dynamics Review 15 (2): 119–138.
Roberts CA and Dangerfield BC (1990). Modeling the epidemiological consequences of HIV infection and AIDS: A contribution from operational research. Journal of Operational Research Society 41 (4): 273–289.
Royston G, Dost A, Townshend J and Turner H (1999). Using system dynamics to help develop and implement policies and programs in health care in England. System Dynamics Review 15 (3): 293–314.
Rudd Center (2015). Revenue calculator for sugar-sweetened beverage taxes, http://www.uconnruddcenter.org/revenue-calculator-for-sugar-sweetened-beverage-taxes?, accessed 10 May 2015.
Sallis JF, Convey TL, Prochaska JJ, McKenzie TL, Marshall SJ and Brown M (2001). The association of school environments with youth physical activity. American Journal of Public Health 91 (4): 618–620.
Sargent RG (2010). Verification and validation of simulation models. Proceedings of the 2010 Winter Simulation Conference (WSC). IEEE: Baltimore, MD, pp 166–183.
Sargent RG (2013). Verification and validation of simulation models. Journal of Simulation 7 (1): 12–24.
Schofield WN (1985). Predicting basal metabolic rate, new standards and review of previous work. Human Nutrition Clinical Nutrition 39 (Suppl 1): S5–41.
Skinner AC and Foster EM (2013). Systems science and childhood obesity: A systematic review and new directions. Journal of Obesity 2013: 1–10.
Sterman JD (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill: Boston.
Taylor K and Dangerfield B (2005). Modeling the feedback effects of reconfiguring health services. Journal of Operational Research Society 56 (6): 659–675.
Tengs TO, Osgood ND and Chen LL (2001). The cost-effectiveness of intensive national school-based anti-tobacco education: Results from the tobacco policy model. Preventive Medicine 33 (6): 558–570.
Tester JM (2009). The built environment: Designing communities to promote physical activity in children. Pediatrics 123 (6): 1591–1598.
Thomson JL et al (2011). A simulation study of the potential effects of healthy food and beverage substitutions on diet quality and total energy intake in lower Mississippi delta adults. Journal of Nutrition 141 (12): 2191–2197.
Tobias MI, Cavana RY and Bloomfield A (2010). Application of a system dynamics model to inform investment in smoking cessation services in New Zealand. American Journal of Public Health 100 (7): 1274–1281.
UIC (University of Illinois at Chicago) (2013). State sales tax on regular, sugar-sweetened soda: Bridging the gap program. Available at, www.bridgingthegapresearch.org, accessed 20 December 2012.
USDA (2013). Eat smart. Play hard. Healthy lifestyle! Available at, http://www.fns.usda.gov/eatsmartplayhardhealthylifestyle/WhatsNew.htm, accessed 10 December 2013.
Van Wymelbeke V, Beridot-Therond ME, de La Gueronniere V and Fantino M (2004). Influence of repeated consumption of beverages containing sucrose or intense sweeteners on food intake. European Journal of Clinical Nutrition 58 (1): 154–161.
Vickers DM and Osgood ND (2010). Current crisis or artifact of surveillance: Insights into rebound chlamydia rates from dynamic modelling. BMC Infectious Diseases 10 (70): 1–10.
Villanueva T (2011). European nations launch tax attack on unhealthy foods. Candian Medical Association Journal 183 (17): E1229–1230.
Wang Y and Lobstein T (2006). Worldwide trends in childhood obesity. International Journal of Pediatric Obesity 1 (1): 11–25.
WHO: World Health Organization (2000). Obesity: Preventing and managing the global epidemic. WHO Technical Report Series. Geneva, WHO, https://apps.who.int/nut/publications.htm, accessed 10 November 2012.
WHO: World Health Organization (2010). Global recommendations on physical activity for health. Geneva, Switzerland: World Health Organization, http://www.who.int/dietphysicalactivity/factsheet_recommendations/en/, accessed 25 November 2012.
Wolstenholme EF (1993). A case study in community care using systems thinking. Journal of Operational Research Society 44 (9): 925–934.
Yale Rudd Center (2012). A 2012 California poll of state fee on soda and soft drinks. Available at, http://www.yaleruddcenter.org/resources/upload/docs/what/policy/SSBtaxes/CA_Field_Poll_4.12.pdf, accessed 1 May 2013.
Acknowledgements
The study was supported by research grants from the Chinese National Social Science Foundation (12CGL103), the US National Institutes of Health (NIH) (research grants 1R01HD064685-01A1 and U54HD070725 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development [NICHD]). The U54 project is co-funded by the NICHD and the NIH Office of Behavioral and Social Sciences Research (OBSSR).
Author information
Authors and Affiliations
Corresponding author
Additional information
Supplementary information accompanies this article on the Journal of the Operational Research Society website (www.palgrave-journals.com/jors)
Electronic supplementary material
Rights and permissions
About this article
Cite this article
Liu, S., Osgood, N., Gao, Q. et al. Systems simulation model for assessing the sustainability and synergistic impacts of sugar-sweetened beverages tax and revenue recycling on childhood obesity prevention. J Oper Res Soc 67, 708–721 (2016). https://doi.org/10.1057/jors.2015.99
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1057/jors.2015.99