Policy options for alcohol price regulation: the importance of modelling population heterogeneity.
Context and aims Internationally, the repertoire of alcohol pricing policies has expanded to include targeted taxation, inflation-linked taxation, taxation based on alcohol-by-volume (ABV), minimum pricing policies (general or targeted), bans of below-cost selling and restricting price-based promotions. Policy makers clearly need to consider how options compare in reducing harms at the population level, but are also required to demonstrate proportionality of their actions, which necessitates a detailed understanding of policy effects on different population subgroups. This paper presents selected findings from a policy appraisal for the UK government and discusses the importance of accounting for population heterogeneity in such analyses. Method We have built a causal, deterministic, epidemiological model which takes account of differential preferences by population subgroups defined by age, gender and level of drinking (moderate, hazardous, harmful). We consider purchasing preferences in terms of the types and volumes of alcoholic beverages, prices paid and the balance between bars, clubs and restaurants as opposed to supermarkets and off-licenses. Results Age, sex and level of drinking fundamentally affect beverage preferences, drinking location, prices paid, price sensitivity and tendency to substitute for other beverage types. Pricing policies vary in their impact on different product types, price points and venues, thus having distinctly different effects on subgroups. Because population subgroups also have substantially different risk profiles for harms, policies are differentially effective in reducing health, crime, work-place absence and unemployment harms. Conclusion Policy appraisals must account for population heterogeneity and complexity if resulting interventions are to be well considered, proportionate, effective and cost-effective.
School of Health and Related Research, University of Sheffield, Sheffield, UK.
Petra Sylvia
PS
Meier
Robin
R
Purshouse
Alan
A
Brennan
D000367:Age Factors; D000428:Alcohol Drinking / Q000191:economics* / Q000453:epidemiology; D000434:Alcoholic Beverages / Q000191:economics*; D003132:Commerce / Q000191:economics* / Q000331:legislation & jurisprudence; D005260:Female; D040261:Harm Reduction; D006291:Health Policy; D006801:Humans; D008297:Male; D044382:Population Groups; D012737:Sex Factors; D013660:Taxes / Q000191:economics*; D006113:United Kingdom / Q000453:epidemiology