Oral health, sugary drink consumption and the soft drink industry levy: Using spatial microsimulation to understand tooth decay

Abstract

Spatial microsimulation is a powerful tool for creating large‐scale population datasets that can be used to assess spatial phenomena in health‐related outcomes. Despite this, it remains underutilized within dental public health. This paper outlines the development of an oral health focused microsimulation model for Sheffield (UK, SimSheffield), and how this can be used to assess potential socio‐spatial impacts of a sugar tax which was introduced in the United Kingdom in 2016 and is known as the Soft Drink Industry Levy (SDIL). Exploratory analysis showed areas paying more SDIL were not those with the highest tooth decay or deprivation scores as might be hoped (in the first case) and expected from the literature (in the second).