The consumption of sugar-sweetened beverages (SSBs) is contributing worldwide to an increased burden of non-communicable diseases (NCDs). SSB taxation can serve as an incentive for decreased SSB consumption and product reformulation, thus leading to improved population health and reduced healthcare costs. To project the potential effects of an SSB tax modelling techniques, which often require the use of assumptions, can be applied.
In an article recently published in BMC Public Health, Karl Emmert-Fees, Andreea Felea, and Michael Laxy from the Professorship of Public Health and Prevention together with colleagues from the TUM School of Management and the Deakin University now for the first time exemplifiy how uncertainty around such assumptions (structural uncertainty) can considerably impact the results of modelling studies. By applying a Markov cohort simulation model, the study compared the projected health and economic effects related to type 2 diabetes of a hypothetical SSB tax in Germany under differing assumptions. The results show that depending on whether (1) the SSB purchasing behavior in response to tax is assumed to vary with pre-tax SSB consumption levels, (2) the pre-tax SSB consumption is adjusted to reflect potential underreporting, and (3) the substitution of SSBs with other beverages is accounted for, varying tax effects can be obtained.
This new study therefore highlights the importance of transparently discussing structural uncertainty in the context of public health economic modelling studies also beyond SSB taxation.