Introduction: Simulation modeling methods are an increasingly common tool for projecting the potential health effects of policies to decrease sugar-sweetened beverage (SSB) intake. However, it remains unknown which SSB policies are understudied and how simulation modeling methods could be improved. To inform next steps, we conducted a scoping review to characterize the (1) policies considered and (2) major characteristics of SSB simulation models.
Methods: We systematically searched 7 electronic databases in 2020, updated in 2021. Two investigators independently screened articles to identify peer-reviewed research using simulation modeling to project the impact of SSB policies on health outcomes. One investigator extracted information about policies considered and key characteristics of models from the full text of included articles. Data were analyzed in 2021-22.
Results: Sixty-one articles were included. Of these, 50 simulated at least one tax policy, most often an ad valorem tax (e.g., 20% tax, n = 25) or volumetric tax (e.g., 1 cent-per-fluid-ounce tax, n = 23). Non-tax policies examined included bans on SSB purchases (n = 5), mandatory reformulation (n = 3), warning labels (n = 2), and portion size policies (n = 2). Policies were typically modeled in populations accounting for age and gender or sex attributes. Most studies focused on weight-related outcomes (n = 54), used cohort, lifetable, or microsimulation modeling methods (n = 34), conducted sensitivity or uncertainty analyses (n = 56), and included supplementary materials (n = 54). Few studies included stakeholders at any point in their process (n = 9) or provided replication code/data (n = 8).
Discussion: Most simulation modeling of SSB policies has focused on tax policies and has been limited in its exploration of heterogenous impacts across population groups. Future research would benefit from refined policy and implementation scenario specifications, thorough assessments of the equity impacts of policies using established methods, and standardized reporting to improve transparency and consistency.