Background Reducing the provision of tobacco is important for decreasing inequalities in smoking and smoking-related harm. Various policies have been proposed to achieve this, but their impacts—particularly on equity—are often unknown. Here, using national-level data, we simulate the impacts of potential policies designed to reduce tobacco outlet density (TOD).
Methods Tobacco retailer locations (n=9030) were geocoded from Scotland’s national register, forming a baseline. Twelve policies were developed in three types: (1) regulating type of retailer selling tobacco, (2) regulating location of tobacco sales, and (3) area-based TOD caps. Density reduction was measured as mean percentage reduction in TOD across data zones and number of retailers nationally. Equity impact was measured using regression-based Relative Index of Inequality (RII) across income deprivation quintiles.
Results Policies restricting tobacco sales to a single outlet type (‘Supermarket’; ‘Liquor store’; ‘Pharmacy’) caused >80% TOD reduction and >90% reduction in the number of tobacco outlets nationally. However, RIIs indicated that two of these policies (‘Liquor store’, ‘Pharmacy’) increased socioeconomic inequalities in TOD. Equity-promoting policies included ‘Minimum spacing’ and exclusion zones around ‘Child spaces’. The only policy to remove statistically significant TOD inequalities was the one deliberately targeted to do so (‘Reduce clusters’).
Conclusions Using spatial simulations, we show that all selected policies reduced provision of tobacco retailing to varying degrees. However, the most ‘successful’ at doing so also increased inequalities. Consequently, policy-makers should consider how the methods by which tobacco retail density is reduced, and success measured, align with policy aims.
- harm reduction
- public policy
- socioeconomic status
Data availability statement
Data are available on reasonable request.
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Contributors Funding acquisition (NKS, JP, RM, GR). Conceptualisation (all authors contributed equally). Investigation (all authors contributed equally). Data curation and analysis (FMC). Methodology (FMC). Writing original draft (FMC). Review and editing (all authors contributed equally). All authors read and approved the final manuscript.
Funding This research was funded by Cancer Research UK. FMC and RM are supported by the Medical Research Council (MC_UU_12017/10) and the Chief Scientist Office (SPHSU10). FMC is supported by an MRC Skills Development Fellowship. JP and NKS are members of SPECTRUM a UK Prevention Research Partnership Consortium. UKPRP is an initiative funded by the UK Research and Innovation Councils, the Department of Health and Social Care (England) and the UK devolved administrations, and leading health research charities.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.