Potential benefits of minimum unit pricing for alcohol versus a ban on below cost selling in England 2014

AbstractObjective To evaluate the potential impact of two alcohol control policies under consideration in England: banning below cost selling of alcohol and minimum unit pricing.Interventions Policy to ban below cost selling, which means that the selling price to consumers could not be lower than tax payable on the product, compared with policies of minimum unit pricing at 0.40 (0.57; $0.75), 45p, and 50p per http://www.cheapjerseys11.com/ unit (7.9 g/10 mL) of pure alcohol.Main outcome measures Changes in mean consumption in terms of units of alcohol, drinkers’ expenditure, and reductions in deaths, illnesses, admissions to hospital, and quality adjusted life years.Results The proportion of the market affected is a key driver of impact, with just 0.7% of all units estimated to be sold below the duty plus value added tax threshold implied by a ban on below cost selling, compared with 23.2% of units for a 45p minimum unit price. Below cost selling is estimated to reduce harmful drinkers’ mean annual consumption by just 0.08%, around 3 units per year, compared with 3.7% or 137 units per year for a 45p minimum unit price (an approximately 45 times greater effect). The ban on below cost selling has a small effect on population health saving an estimated 14 deaths and 500 admissions to hospital per annum. In contrast, a 45p minimum unit price is estimated to save 624 deaths and 23700 hospital admissions. Most of the harm reductions (for example, 89% of estimated deaths saved per annum) are estimated to occur in the 5.3% of people who are harmful drinkers.Conclusions The ban on below cost selling, implemented in the England in May 2014, is estimated to have small effects on consumption and health harm. The previously announced policy of a minimum unit price, if set at expected levels between 40p and 50p per unit, is estimated to have an approximately 40 50 times greater effect.IntroductionThe UK government has been considering different policy options to regulate the price of alcohol in England and Wales. Increasing the price of alcohol has been shown to be effective in reducing both consumption levels1 and harms.2 Recent Canadian research shows that minimum pricing policies reduce total alcohol consumption, shift consumption away from high strength beverages, and reduce alcohol related admissions to hospital.3 4 In 2010, the UK government proposed a «ban on below cost selling,» which would target drinks that are currently sold so cheaply that their price is below the cost of production and retail.5 In principle this would affect alcohol wherever sold, but in practice such cheap drinks are sold in supermarkets and other shops (the «off trade») rather than in pubs, clubs, bars, and restaurants (the «on trade»). In the absence of detailed, commercially sensitive information on production and retail costs, the government developed a simplified policy, which proposed that the selling price to consumers could not be lower than the tax payable on the product. In the United Kingdom, tax on alcohol has two components: the alcohol beverage specific duty, for example, 28.22 (35.57; $46.10) per litre of pure alcohol for spirits as of March 2014, and a sales value added tax (VAT), which is currently an additional 20% on top of the price of the product. Thus the selling price for a product under a ban on below cost selling (BBCS) policy would not be allowed to be lower than PriceBBCS=duty+duty20%. Because the alcohol duty rates vary for different drinks, a ban on below cost selling would target those drinks that currently have higher duty rates (for example, spirits) and have less effect on drinks with lower duty rates (for example, cider). In 2012 the UK government announced an alternative policy for its alcohol strategy a minimum unit price for alcohol6 and levels discussed ranged between 40p and 50p per unit. In 2013 the government then withdrew this commitment and returned to its previous ban on below cost selling policy, which it subsequently introduced in May 2014.7 Under a minimum unit price policy, the minimum selling price increases in proportion to the alcohol units contained in the drink (1 unit=7.9 g/10 mL of pure ethanol). Thus a minimum unit price measure would target those drinks that are high in alcohol content and sold relatively cheaply; drinks that are favoured more by those drinking at harmful levels.8 For eight example purchases, table 1 shows that a ban on below cost selling thresholds would differ considerably compared with, for example, a 45p minimum unit price level, and that since the duty on cider is low and does not increase in line with alcohol content, the ban on below cost selling threshold falls as low as 6p per unit for high strength cider.Table 1 Example prices for different product categories under a ban on below cost selling compared with minimum unit pricingView this table:View popupView inlineThe potential effects of a minimum unit price in England were previously examined in 2009 10.8 9 The Sheffield Alcohol Policy Model (version 2.0) used consumption survey data from the general lifestyle survey 2006 as the baseline year. The model also included levels of purchasing and prices paid from the expenditure and food surveys 2001 06 and commercially available population level distributions for prices paid for various alcohol beverage types from the commercial market research companies CGA Strategy and AC Nielsen for 2008. Baseline levels of the harms associated with alcohol were taken from 2005 for admissions to hospital and mortality in 47 diseases.10 The model estimated changes in consumption and the levels of harms over a 10 year period after the introduction of the policy, examining 54 subgroups of the population based on age, sex, and three levels of consumption (moderate, hazardous, and harmful). The research report and subsequent publications examined the potential impact of a minimum unit price threshold, ranging from 20p to 70p per unit.8 The findings contributed substantially to the debate surrounding pricing regulation and future policy options.11 12 Several areas were identified for further development of both the version 2.0 model and the evidence used within it. In particular, further evidence and analyses on the price elasticities for alcohol (which are used to quantify the relation between price changes and consumption changes) were a priority. The original work used cross sectional analysis of five years of data from the expenditure and food survey to estimate price elasticities for the main analysis, and also tested how sensitive the results were to alternative estimates taken from the research literature. The previous model combined beers and ciders, which would be better separated given their different duty rates and consumption patterns.We defined moderate drinking as alcohol intake up to 21 units per week for males and 14 units per week for females, and non drinkers were included in this group; hazardous drinking as alcohol intake between 21 and 50 units per week for males and between 14 and 35 units for females; and harmful drinking as alcohol intake of more than 50 units per week for males and over 35 units for females.In this study we have developed a new version of the Sheffield Alcohol Policy Model (version 2.5) in which we have updated data on baseline consumption and prices; developed new estimates on price elasticity accounting for the longitudinal aspects of the expenditure and food survey data (now renamed as the living costs and food survey), separated cider from beers; and incorporated greater subgroup functionality including the ability to define socioeconomic subgroups.13 The Sheffield Alcohol Policy Model (version 2.5) is used to address the current research question: What would be the differential potential impact of a ban on below cost selling versus a minimum unit price policy of 40p, 45p, or 50p if the policies were to be implemented in 2014 15? In particular, what are the estimated potential effects on alcohol consumption, consumer spending, tax and duty revenues, and health harms, including deaths, admissions to hospital, quality of life, and costs to the National Health Service of these outcomes?MethodsOverview of the modelThe aim of Sheffield Alcohol Policy Model (version 2.5) is to appraise a wide variety of policy options, including minimum unit pricing through analysis of selected costs and benefits. This involves modelling a linked series of policy outcomes for 96 population subgroups defined by sex, age, annual income, and consumption level. The outcomes are: the effect of the policy on the distribution of prices for different types of alcohol; the effect of changes in price on alcohol consumption; the effect of changes in alcohol consumption on revenue for retailers, the exchequer, and consumer spending on alcohol; and the effect of changes in alcohol consumption on levels of alcohol related admissions to hospital and deaths and quality adjusted life years lost. The model also appraises effects on crime and workplace outcomes (not reported here). The methods used are set out below (see supplementary technical appendix for full details).Baseline dataThe modelling begins with individual level baseline data from the general lifestyle survey 2009 on mean weekly and peak day consumption (a proxy for individuals’ scale of binge drinking) of alcohol for 11385 people in England. It considers 96 subgroups split by age, sex, mean consumption level (moderate, hazardous, and harmful), and income (low and higher income). (We define low income as those below the relative poverty line, defined as 60% of median equivalised household income and higher income as people above the relative poverty line.) Data on prices paid and quantity purchased by each subgroup for 10 different beverage types (off trade and on trade beer, cider, wine, spirits, and ready to drinks «alcopops») are available from the living costs and food survey, an annual two week purchasing diary survey of around 6500 UK households. We utilised data on prices paid for England only, for the years 2001 02 to 2009, a sample of 227933 purchasing transactions. These self reported prices paid for alcohol are known to over estimate the mean price paid,9 and we adjust them so that the distribution of actual amounts of alcohol bought at different price levels match with actual sales prices in the market using 2011 data from AC Nielsen and CGA Strategy.Process for estimating effect of price change on consumption for population subgroupsA minimum unit price or a ban on below cost selling policy is assumed to increase all product prices below the policy threshold up to exactly the threshold level, and it is further assumed to affect none of the products currently priced above the threshold. The percentage change in mean price paid in each subgroup for the 10 beverage types is used to estimate the effect of price changes on consumption. This is done in conjunction with own price elasticities (for example, percentage change in consumption of off trade beer given a 1% increase in off trade beer price), and cross price elasticities (for example, percentage change in off trade beer consumption given a 1% increase in the price of another product, for example, off trade spirits). When a change in prices is inputted as a model scenario, the percentage change in mean weekly consumption for each population subgroup is estimated for each beverage. This is then applied to the corresponding individual level consumption data in the model. Each individual’s percentage change in peak daily consumption is indirectly modelled using a linear regression, with peak daily consumption estimated as a function of mean weekly consumption, age, and sex.Estimating price elasticities for alcoholTo estimate the effect of changing prices on consumption, a new set of price elasticity models have been developed. Full details on the statistical approach and the model fit can be found elsewhere.14 Technically, we used individual level data from the living costs and food survey for 2001 to 2009 to construct a time series pseudopanel for 72 defined population groups based on sex, birth year, and socioeconomic status. Within each population group, in each year, and for each of the 10 beverage categories, we calculated the mean number of units purchased and the mean price paid. A set of 10 fixed effects regression models were then fitted to estimate the own and cross price elasticities. Covariates adjusted for in the final models were income, age, and proportions of individuals in each population group having children, and being married, unemployed, and a smoker. Table 2 shows the resulting own price and cross price elasticities. To illustrate the interpretation, the own price elasticity for off trade beer (top left cell of matrix) was 0.980, which means that a 1% increase in the price of off trade beer would be estimated to result in a 0.98% reduction in the amount purchased. Similarly, there can be switching between drinks when prices change, so for example (two cells to the right), a 1% increase in off trade beer was estimated to produce a slight increase of 0.096% in purchasing of off trade wine. To examine the effects of uncertainty, we also carried out runs of the Sheffield Alcohol Policy Model (version 2.5) using alternative definitions to generate the pseudopanel purchasing groups, and using probabilistic sensitivity analysis accounting for variable uncertainty reported in the regression coefficients.15 16Table 2 Base case estimated own price and cross price elasticities for off trade and on trade beer, cider, wine, spirits, and ready to drinks (RTDs, or «alcopops») in the United KingdomView this table:View popupView inlineNote that different subgroups in Sheffield Alcohol Policy Model (version 2.5) experience different scales of effect due to a price change because for each subgroup we accounted for data on their preferences for the 10 categories of beverage (for example, middle aged women drink more wine at home, younger men drink more beer on nights out) and data on the prices paid for each of the 10 beverages (for example, harmful drinkers spend less per unit on average). Thus, the 1010 matrix of price elasticities means that each of the 96 modelled population subgroups essentially has a different overall price elasticity and a different scale of response to a given policy (for example, drinkers who favour cheaper cider would be more affected by a minimum unit price because their beverages would experience a relatively large increase in price and also because the own price elasticity for off trade cider is relatively large at 1.268).Risk functions and modelling process for health harmsThe baseline and estimated post policy consumption data for each of the population subgroups feed into a second model component relating changes in consumption to changes in harm. We model the effects of consumption changes on mortality and disease prevalence for 47 conditions defined by the international classification of diseases, 10th revision (ICD 10) codes.10 The modelling uses epidemiological risk functions, which one can visualise as a graph, with the x axis being level of consumption of alcohol in units and the y axis being the risk of harm, for example, relative risk of mortality from oesophageal cancer (ICD10 code C15). We partitioned the diseases into four categories: chronic or acute conditions, which were attributable partially or wholly to alcohol. For partially attributable chronic conditions, we used functions relating an individual’s mean consumption to his or her health risk from the published literature.15 For partially attributable acute conditions, published literature is more limited, and we quantified functions relating highest daily consumption to risk by calibrating the slope of an assumed linear risk function to published evidence of the alcohol attributable fractions for each condition (see details8). For wholly attributable chronic and acute conditions, we similarly calibrated functions relating either mean weekly units or maximum daily consumption to absolute risk to published evidence on the absolute number of cases observed.8This process was undertaken both for annual mortality risk for each condition and for morbidity risk, where morbidity was defined as the annual rate of person specific admissions to hospital. Condition specific mortality rates for each age and sex based subgroup are taken from published analyses cheap jerseys of 2005 06 Office for National Statistics, and morbidity rates from 2005 06 hospital episodes statistics.10The modelled change in consumption for each subgroup then feeds into a change in relative or absolute risk, and the potential impact fraction method17 is used to adjust observed mortality and morbidity rates. For chronic conditions, there can be a time lag between population level changes in alcohol consumption and changes in outcome, and we chose a linear time lag function of 10 years to realisation of full effect, which is consistent with average estimates in the literature.18Framework for base case and sensitivity analysesFor all ban on below cost selling analyses, we estimated the average duty plus VAT per unit of alcohol for beer, cider, wine, spirits, and ready to drink beverages (or alcopops) in the United Kingdom based on the duty rates set by Her Majesty’s Revenue and Customs effective from 25 March 2013. We used several assumptions to estimate these thresholds because different duty rates exist for the same modelled beverage type (for example, there are currently three duty rates for beer which increase with alcohol content) and because duty rates for cider and wine are calculated based on product volume rather than on ethanol content. (For full details see supplementary technical appendix table 13.1 or table 1 in Meng et al16.)The set of policies analysed are a ban on below cost selling and minimum unit price polices with thresholds of 40p, 45p, and 50p in 2014 15 prices. We particularly focus on 45p as this was the level proposed by the UK government. The model actually uses 2011 as the baseline year because this is our most recently availably price distribution data. We adjusted for future beverage specific retail price indices using estimates provided by the Home Office (for details see supplementary technical Appendix table 5.3).The analysis reported here applies the elasticity matrix estimated in table 2. See online for the full details on methods and results of sensitivity analyses undertaken to test the robustness of our results under alternative elasticity matrices (for example, assuming no substitution effects, excluding non significant (P16ResultsThe proportion of the market that would be affected by price regulation is the key driver of the scale of estimated policy impact. Overall, just 0.7% of alcohol units are estimated to be sold below the ban on below cost selling duty plus VAT threshold. In contrast, a 45p minimum unit price would affect 23.2% of all units. For analyses across subgroups, baseline consumption and prices paid are shown in table 3. Harmful drinkers are a policy priority group, as they consume substantially (on average 58 units per week for females, 80 units for males) and spend substantially (1800 and 3400 per annum, respectively). Of the population aged 16 or more, 2.2 million (5.3%) are harmful drinkers, 7.2 million (17.3%) are hazardous drinkers, and 25.5 million (61.5%) are moderate drinkers. The proportion of alcohol affected by a minimum unit price varied across these subgroups: for example, a 45p minimum unit price would affect 12.5%, 19.5%, and 30.5% of units sold to moderate, hazardous, and harmful drinkers, respectively. In contrast, table 3 and figure1 show that the impact of a ban on below cost selling on all drinkers would be minimal, and just 1.0% of units currently consumed by harmful drinkers would be affected.

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