Official websites use. Share sensitive information only on official, secure websites. Address correspondence to: Bruce Y. A number of locations have been considering sugar-sweetened beverage point of purchase warning label policies to help address rising adolescent overweight and obesity prevalence. To explore the impact of such policies, in detailed agent-based models of Baltimore, Philadelphia, and San Francisco were developed, representing their populations, school locations, and food sources, using data from various sources collected between and The model simulated, over a 7-year period, the mean change in BMI and obesity prevalence in each of the cities from sugar-sweetened beverage warning label policies.
Data analysis conducted between and found that implementing sugar-sweetened beverage warning labels at all sugar-sweetened beverage retailers lowered obesity prevalence among adolescents in all three cities. Agent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence.
Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact. Given evidence that sugar-sweetened beverage SSB consumption contributes to childhood obesity, several locations are considering legislative strategies to reduce the consumption of SSBs.
With SSB warning labels currently under consideration in multiple cities, decision makers cannot wait for results from long-standing observational and intervention studies and would benefit immediately from a clear understanding of the potential measurable range of benefits resulting from such a policy.
Testing SSB warning labels on a meaningfully large scale requires considerable time, effort, and resources. Even though emerging research suggests that labels do influence behavior, the downstream impact on obesity can take years to manifest. The class of simulation modeling used here is agent-based modeling, where individuals are represented by computational agents that have autonomous decision-making abilities and complex emergent behavior.
