Minimum unit pricing for alcohol and the ‘moderate drinker of moderate means’: An analysis of household scanner data Ourega-Zoé Ejebu Lynda McKenzie Anne Ludbrook

Background In Scotland, the misuse of alcohol contributes to a wide range of problems (health, social, work). The annual costs of excessive alcohol consumption in Scotland are at least £3.6bn (Scottish Government, 2007). In 2009/10, it was estimated at £7.2bn when intangible costs were included (pain, grief, suffering). The annual cost of alcohol misuse for most deprived households was 6 times larger than the least deprived (Johnston, Ludbrook et al., 2012). Consequences of similar drinking patterns are more severe for those with lower socioeconomic status; such that the risk of alcohol-related death and hospitalisation is higher for manual than for non-manual workers (Mäkelä, Paljärvi 2008).

Addressing alcohol affordability Addressing alcohol affordability The Scottish Government wants to address alcohol affordability as part of an integrated strategy to reduce alcohol harms. International research has demonstrated the close link between affordability and consumption of alcohol. Minimum unit pricing (MUP) per unit of alcohol is the Government’s preferred policy on affordability. MUP could be particularly effective in reducing alcohol consumption by targeting low cost alcohol preferred by the heaviest drinkers. Concern that MUP might disadvantage low income moderate drinkers.

Policy context and research questions The policy context is to investigate who are the predominant purchasers of cheap off-trade alcohol in Scotland. Research questions: Do low income households purchase more low cost alcohol? How do income and purchase level affect purchasing of cheap alcohol? What factors are significantly related to purchases of cheap alcohol?

Data and Methodology Data and Methodology Data The data was obtained from the Kantar Worldpanel ( ). It covers all areas of Scotland and contains information on 3,076 Scottish households. Households used a scanner to record daily grocery purchases including daily alcohol purchases (off sales). Methodology Use of concentration curve to assess the degree of income-related inequality in the distribution of cheap alcohol. Use of regressions: Hausman-Taylor (HT), predictions from Tobit and HT respectively were used to investigate the relationship between units of cheap alcohol (dependent variable) and key regressors.

Variables Units of cheap alcohol Household income Occupation Age Household composition Purchase level: Moderate Hazardous Harmful Type of alcohol products Promotion Year of purchase Recommended Government guidelines for weekly alcohol consumption: Moderate: <14u women; <21u men Hazardous: 15-35u women ; 22-50u men Harmful:>35u women ; >50u men

Results 1 Figure 1: Concentration curve of cheap alcohol units in Scotland Source: Based on Kantar Worldpanel data

Results 2 Figure 2: Average predicted probability that households purchase cheap alcohol (<£0.50) within income groups and by purchase level Source: Based on Kantar Worldpanel data

Results 3 Figure 3: Average predicted quantity of cheap alcohol units (<£0.50) purchased (by week) within income groups and by purchase level Source: Based on Kantar Worldpanel data

Results 4 Results 4 Control variablesHausman-Taylor (HT) Units of cheap alcohol (base=high income) Low income0.730 [0.745] Intermediate income0.558 [0.660] (base=professional & managerial occupation) Intermediate occupation1.029* [0.489] Routine and manual occupation1.518*** [0.479] Promotion4.751*** [0.110] (base=moderate) Hazardous8.541*** [0.977] Harmful26.428*** [1.834] Observations178,052 ***p<0.01, **p<0.05, *p<0.1 Source: Based on Kantar Worldpanel data Table 1: HT regression of the relationship between units of cheap alcohol and key control variables

Concluding remarks Moderate drinkers and low income drinkers are less likely to be adversely affected by MUP, considering they are not the predominant consumers of cheap alcohol. Further research could benefit from data on alcohol products purchased on-trade.

Acknowledgments and Authors’ contacts details Acknowledgments: Kantar Worldpanel (Kantar) and Rowett Institute of Nutrition and Health (RINH) Thank you! Feedback are welcome. Ourega-Zoé Ejebu Lynda McKenzie Anne Ludbrook