
==== Front
PLoS Med
PLoS Med
plos
PLOS Medicine
1549-1277
1549-1676
Public Library of Science San Francisco, CA USA

10.1371/journal.pmed.1004442
PMEDICINE-D-24-00685
Research Article
Biology and Life Sciences
Nutrition
Diet
Beverages
Alcoholic Beverages
Beer
Medicine and Health Sciences
Nutrition
Diet
Beverages
Alcoholic Beverages
Beer
Biology and Life Sciences
Nutrition
Diet
Beverages
Alcoholic Beverages
Wine
Medicine and Health Sciences
Nutrition
Diet
Beverages
Alcoholic Beverages
Wine
Biology and Life Sciences
Nutrition
Diet
Alcohol Consumption
Medicine and Health Sciences
Nutrition
Diet
Alcohol Consumption
Biology and Life Sciences
Psychology
Addiction
Addicts
Alcoholics
Social Sciences
Psychology
Addiction
Addicts
Alcoholics
People and places
Geographical locations
Europe
European Union
United Kingdom
England
Social Sciences
Sociology
Communications
Marketing
People and Places
Geographical Locations
Oceania
Australia
People and places
Geographical locations
North America
United States
Impact on beer sales of removing the pint serving size: An A-B-A reversal trial in pubs, bars, and restaurants in England
Removing pints and beer sales
https://orcid.org/0000-0003-3147-5079
Mantzari Eleni Conceptualization Investigation Methodology Supervision Validation Writing – original draft Writing – review & editing 1 2
https://orcid.org/0000-0002-0492-3924
Hollands Gareth J. Conceptualization Methodology Writing – review & editing 3
https://orcid.org/0000-0001-9594-348X
Law Martin Formal analysis 4 5
https://orcid.org/0000-0001-5774-5036
Couturier Dominique-Laurent Formal analysis 4 5
https://orcid.org/0000-0003-3025-1129
Marteau Theresa M. Conceptualization Methodology Writing – review & editing 1 *
1 Behaviour and Health Research Unit, University of Cambridge, Cambridge, United Kingdom
2 Department of Health Services Research and Management, City, University of London, London, United Kingdom
3 EPPI Centre, UCL Social Research Institute, University College London, London, United Kingdom
4 MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
5 Papworth Trials Unit Collaboration, Royal Papworth Hospital NHS Foundation Trust, Cambridge, United Kingdom
The authors have declared that no competing interests exist.

* E-mail: tm388@cam.ac.uk
17 9 2024
9 2024
21 9 e10044421 3 2024
15 7 2024
© 2024 Mantzari et al
2024
Mantzari et al
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Background

Smaller serving sizes could contribute towards reducing alcohol consumption across populations and thereby decrease the risk of 7 cancers and other diseases. To our knowledge, the current study is the first to assess the impact on beer, lager, and cider sales (hereafter, for ease, referred to just as “beer sales”) of removing the largest draught serving size (1 imperial pint) from the options available in licensed premises under real-word conditions.

Methods and findings

The study was conducted between February and May 2023, in 13 licensed premises in England. It used an A-B-A reversal design, set over 3 consecutive 4-weekly periods with “A” representing the nonintervention periods during which standard serving sizes were served, and “B” representing the intervention period when the largest serving size of draught beer (1 imperial pint (568 ml)) was removed from existing ranges so that the largest size available was two-thirds of a pint. Where two-third pints were not served, the intervention included introducing this serving size in conjunction with removing the pint serving size. The primary outcome was the mean daily volume of all beer sold, including draught, bottles, and cans (in ml), extracted from electronic sales data. Secondary outcomes were mean daily volume of wine sold (ml) and daily revenue (£). Thirteen premises completed the study, 12 of which did so per protocol and were included in the primary analysis. After adjusting for prespecified covariates, the intervention resulted in a mean daily change of −2,769 ml (95% CI [−4,188, −1,578] p < 0.001) or −9.7% (95% CI [−13.5%, −6.1%] in beer sold. The daily volume of wine sold increased during the intervention period by 232 ml (95% CI [13, 487], p = 0.035) or 7.2% (95% CI [0.4%, 14.5%]). Daily revenues decreased by 5.0% (95% CI [9.6%, −0.3%], p = 0.038).

Conclusions

Removing the largest serving size (the imperial pint) for draught beer reduced the volume of beer sold. Given the potential of this intervention to reduce alcohol consumption, it merits consideration in alcohol control policies.

Trial registration

ISRCTN.com ISRCTN18365249.

Eleni Mantzari and colleagues investigate whether reducing the size of beer servings sold by the glass in licensed premises could reduce alcohol sales.

Author summary

Why was the study done?

Removing the largest serving size of wine by the glass (usually 250 ml) reduces the volume of wine sold in licensed premises.

It is unknown whether removing the largest serving size of other alcohol drinks, such as beer, has a similar effect.

What did the researchers do and find?

We asked 13 licensed premises in England to remove the offer of their largest serving size of draught beer (1 imperial pint, 568 ml) from available options for 4 weeks. We compared the total volume of beer sold during the intervention period to that sold during the nonintervention periods.

Removing the largest serving size for draught beer (the imperial pint) reduced the daily mean volume of beer sold by 9.7%.

What do these findings mean?

This intervention merits consideration for inclusion in alcohol control policies.

The findings are limited due to a lack of assessment of all alcoholic drinks sold in participating licensed premises, which would have allowed for consideration of whether people may have fully compensated for their reduced beer consumption by drinking other alcoholic drinks.

http://dx.doi.org/10.13039/100010269 Wellcome Trust 206853/Z/17/Z https://orcid.org/0000-0003-3025-1129
Marteau Theresa M. The work of this report was funded in whole by Wellcome [PI: TMM: ref 206853/Z/17/Z (Collaborative Award in Science: Behaviour Change by Design: Generating and Implementing Evidence to Improve Health for All)]. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data AvailabilityAll data are available from the Open Science Framework here: https://osf.io/afweh.
Data Availability

All data are available from the Open Science Framework here: https://osf.io/afweh.
==== Body
pmcBackground

Alcohol consumption contributes to premature mortality and preventable morbidity, causing millions of deaths annually worldwide and ranking fifth among 20 risk factors for the global burden of disease [1,2]. Reducing alcohol consumption across populations is therefore a global public health priority [3].

Aspects of physical and economic environments influence alcohol consumption across populations. These include the marketing [4–7], labelling [8–10], availability [11–15], and affordability of alcohol products [16,17]. Most implemented interventions to date have sought to reduce the affordability of alcohol and to control their marketing and licensing [18,19]. Another promising intervention includes reducing the size of servings and packages of products that can harm heath, including alcoholic drinks. People consume less food and nonalcoholic drinks when presented with smaller portions, packages, or tableware [20–22], while the package and container size of alcoholic drinks can influence alcohol consumption. Smaller wine glasses in restaurants decrease the volume of wine sold and accordingly consumed [23]. Smaller wine glasses might also reduce the amount of wine drunk at home [24]. Drinking wine at home from smaller bottles, compared with standard 75 cl bottles, may also reduce consumption when the bottles are 50 cl [25], but the impact of 37.5 cl bottles is less certain [24].

Interventions that target the sizes of servings to reduce alcohol consumption fall into 2 groups [26]:

removing the largest serving size(s) from existing options;

adding a smaller size to existing options, which could be larger or smaller than the existing smallest serving size (s).

Either of these interventions could be implemented alone or in combination. For example, if targeting draught beer in licensed premised in the United Kingdom, implementing the first would involve removing the pint (568 ml), without altering any other serving size options. Alternatively, this intervention could be combined with the second option, so that a smaller serving size not normally offered, such as two-thirds of a pint, is added to the range. Similarly, this second option could be implemented alone, for example, by adding the two-third pint serving size to the existing range of options without removing the larger serving size.

The limited evidence to date suggests that the second option—adding a smaller size to existing options—does not impact alcohol consumption. This is supported by findings from a recent study, conducted in real-world settings, in which adding a serving size of draught beer of two-thirds of a pint that was between the largest (1 imperial pint) and the smallest size (half a pint) across 13 licensed premises had no discernible effect on the volume of beer sold [27]. In contrast, removing the largest serving size from existing options (option i) alone or in combination with the second option (adding a smaller serving size) has shown potential for reducing alcohol consumption.

Two studies, one conducted in a laboratory and one in a seminaturalistic context of a pub, found reductions in alcohol consumed on a single occasion when larger servings were removed and replaced by smaller sizes [28]. In the only study assessing this in a real-world setting in licensed premises, removing the largest serving size of wine by the glass (most often 250 ml) for 4 weeks decreased wine sales—a proxy for consumption—by 7.6% [29]. It is unknown whether removing the largest serving size of other alcohol drinks, such as beers, would have similar effects. We are also unaware of any studies that have assessed the impact of adding a size smaller than the existing smallest serving size on alcohol consumption.

In the UK, the largest and most popular serving size of draught beer is the imperial pint [30]. At 568 ml, this size is larger than the typical sizes for draught beer found in most other countries. For example, in the United States of America, the largest and most popular size is 473 ml [31]. In the Netherlands and Belgium, the usual serving size is 250 ml; in France, it is 330 ml; and in Germany, it is 500 ml, depending on the region and type of beer ordered [30]. In many parts of Australia, the most common serving size is the “schooner,” i.e., 425 ml. In South Australia, this size is called “a pint” and is therefore the biggest most popular size on offer [32]. As suggested by news reports, licensed premises in Western Australia have undergone a process by which a pint-drinking culture has been replaced by a schooner-drinking one, to tackle increasing costs and adhere to government efforts to reduce alcohol consumption. We are unaware of any relevant scientific research that corroborates this [33–35].

The aim of the current study is to assess the impact on the volume of beer, lager, and cider sold of removing the largest serving size of draught beer, lager, and cider (1 imperial pint, 568 ml) so that the largest serving size available is two-thirds of a pint. We hypothesise that this intervention reduces the volume of beer, lager, and cider sold.

Methods

The study was approved by the University of Cambridge Psychology Research Ethics Committee (reference no: PRE.2022.103). The study protocol was preregistered (ISRCTN: ISRCTN18365249 (https://www.isrctn.com/ISRCTN18365249); Open Science Framework: registration: https://osf.io/369sh/, protocol https://osf.io/shckx, statistical analysis plan https://osf.io/n7pdy).

Study design

The study used an A-B-A treatment reversal design consisting of 3 consecutive 4-week periods. “A” represented the nonintervention periods during which usual serving sizes were offered, and “B” represented the intervention period during which the largest serving size (pint) of draught beer, cider, and lager—hereinafter referred to collectively as “beer” for ease—was removed from premises’ existing range so that the largest serving size available was two-thirds of a pint.

Setting and context

The study was conducted in pubs, bars, and restaurants in England, where draught beer must legally be available in at least 1 of 2 sizes [36]: pint (568 ml), which is the most popular measure [30], and half-pint (284 ml). Since 2011, one-third (189 ml) and two-third pint servings (379 ml) can also be sold, but there is no legal obligation for these to be available [30,37].

Participating premises

Thirteen licensed premises in England participated in the study. Their characteristics are shown in Table 1. The majority of these were in London (61.5%), located in more deprived areas, with 77% falling within the first and second Index of Multiple Deprivation quintiles.

10.1371/journal.pmed.1004442.t001 Table 1 Characteristics of participating licensed premises.

Premises number	Location	Index of Multiple Deprivation Quintile*	Premises type**	Baseline daily revenue
(£; mean (SD))	Offered 2/3 pint before study	
1	Hackney, London	1	Restaurant	5,831.6 (2,870.9)	No	
2	Hackney, London	1	Pub	1,101.9 (938.5)	No	
3	Haringey, London	5	Pub	1,149.6 (687.5)	No	
4	Wandsworth, London	1	Cocktail bar and Restaurant	8,223.6 (7,968.4)	Yes	
5	Brighton and Hove	1	Pub	1,530.7 (1,038.4)	No	
6	Newham, London	3	Bar and Restaurant	967.2 (441.0)	Yes	
7	Birmingham	2	Restaurant	3,681.7 (3,042.1)	Yes	
8	Lewisham, London	2	Bar and Restaurant	2,351.2 (1,072.3)	No	
9	Lewisham, London	3	Bar	993.9 (798.4)	No	
10	Hackney, London	2	Pub	1,676.0 (1,831.0)	No	
11	Brighton and Hove	1	Restaurant	1,510.5 (990.7)	No	
12	Sheffield	1	Bar	675.1 (256.3)	Yes	
13	Brighton and Hove	2	Bar	1,177.3 (676.8)	No	
*The Index of Multiple Deprivation (IMD) ranks every area in England according to deprivation levels. The IMD combines information from the 7 domains to produce an overall relative measure of deprivation; 1 = most deprived; 5 = least deprived.

**Description of premises type taken from each premises’ website.

Eligibility criteria for premises’ participation were the following:

sell a minimum of 150 pints of beer on average per week;

be willing to remove the larger serving of draught beer, i.e., a pint, and introduce a two-third pint if this serving size was not already available;

have an electronic point of sale (EPOS) till system to record daily sales of all drinks and their served sizes;

be primarily indoor, permanent establishments in a fixed location, i.e., not purposefully temporary or time-limited (e.g., pop-up) or mobile venues (e.g., vans).

Sample size calculation

A simulation-based predictive power analysis was performed based on data from a previous study assessing the impact of removing the largest serving size of wine by the glass in 21 licensed premises, using an A-B-A design with each period lasting 4 weeks [29]. This previous study found that the intervention resulted in a mean 7.6% (95% CI [−12.3%, −2.9%]) reduction in the daily volume of wine sold. The simulations suggested that 5 licensed premises would be required for the current study to detect an effect of this size on the daily volume of beer sold with a probability of 0.85 at the 0.05 significance level. Due to the model complexity [38], it was considered favourable to increase the sample size to 10 premises. To account for possible attrition, 13 premises were recruited. The sample size calculation report providing a more thorough description of the process used to define the number of premises is available as Supporting information (S2 Appendix).

Intervention

Licensed premises removed the largest serving size of draught beer (1 imperial pint) from their existing ranges so that the largest serving size available was two-thirds of a pint. Where two-third pints were not usually served, this serving size was introduced, with proportionate pricing as far as possible, i.e., with a price that was linear-by-volume between the pint and half-pint sizes. Premises were provided with the necessary two-third pint glassware by the research team. Menus and signs were updated to reflect the changes.

Within the TIPPME intervention typology for changing environments to change behaviour [39], the type of intervention used in the current study is classified as “Size,” focused on the “Product” itself (i.e., the alcoholic drink(s), as opposed to, for example, aspects of the wider environment).

Measures

Primary outcome

Daily volume (in millilitres (ml)) of all beer, lager, and cider (draught as well as bottled and canned), extracted from electronic records of sales.

Secondary outcomes

The following outcomes were extracted from electronic records of sales from each premises: Number of beers and cider sold in each serving size per day: one-third pint (189 ml) draught

half-pint (284 ml) draught

330 ml bottle

375 ml bottle

two-third pint (379 ml) draught

440 ml can

500 ml bottle

pint (568 ml) draught

568 ml can

550 ml bottle

660 ml bottle

750 ml bottle

Daily volume (in ml) of wine sold, in order to assess whether the absence of the largest serving of beer affects wine consumption, given that beers, cider, and wines make up more than 70% of alcoholic drinks sold in licensed premises in the UK [40];

Daily revenue from food and all drinks, alcoholic and nonalcoholic.

Covariates

Given that daily temperature, day of the week, season, and holidays can influence alcohol sales [41,42], the following covariates were considered:

Maximum daily local temperature;

Special events (including national events, i.e., Valentine’s Day, St Patrick’s Day, Mother’s Day, Bank Holidays—Good Friday, Easter weekend, May Day—and local events, i.e., DJ nights, quiz nights; live music events, parties; open mic/karaoke evenings, fundraiser events, local markets, marathons and half-marathons, and beer festivals);

Total revenue;

Day of the week;

Time in days from start of the study.

Procedure

Potentially eligible licensed premises were identified through a publicly available database (www.whatpub.com). Invitations to participate in the study were sent to those based in 1 of 6 geographical areas to which the research team could readily travel in order to conduct fidelity checks. Those expressing interest were sent more information about the study and then assessed for eligibility over the telephone. Eligible premises wishing to participate provided written informed consent to take part.

Premises changed their available serving sizes for draught beer on 2 occasions over a period of 12 weeks: once to remove pints and introduce two-third pints (if this serving size was not already available); and once to reintroduce pints and remove two-third pint serving sizes (if this serving size had been added during the intervention period). Till systems were updated to reflect the new serving sizes.

Premises were contacted 1 day before each reversal to remind them of the required changes. Fidelity to the protocol was checked by visits organised by the research team in the first week after each occasion on which changes were due to occur. No premises failed any fidelity checks, but given these were conducted only once following each reversal, sales data were also checked for any protocol violations.

Data were collected between February 2023 and May 2023. Premises were paid £3,000 (including VAT) to compensate for expected losses to revenue as well as the resources needed for them to take part in the study, including the timely provision of all requested data. Premises were additionally reimbursed for any costs associated with changes to menus and signs.

Data analysis

For the primary analysis, a heteroscedastic linear mixed model was used to predict the cube root of daily volume of beer sold as a function of the following fixed effects: (i) study period (reference nonintervention period); (ii) day of week (using contrasts of type sum); (iii) study day (per-site standardised time from start of the study); (iv) total daily revenue (per-site standardised (log) revenue); (v) standardised maximum daily temperature; and (vi) special events (dichotomous variable with 0 for normal days (reference) and to 1 for special events). The analysis excluded any days when premises were closed.

Possibly correlated random intercept and standardised (log) revenue slope for each site were used to take the within site-dependence into account. The cube root was used to linearise the relationship between response and predictors, as well as to overcome heteroscedasticity. All model checks suggested a good fit of the assumed model to the data. The residual variance was allowed to differ for site and day of week. Estimates were obtained by maximising the restricted maximum likelihood, via the function lme of the nlme package of the R Statistical Software (version 4.4.0) [43].

Data included in the final analysis were from those sites that completed the study in full per protocol.

Sensitivity analyses

To check the robustness of the primary conclusions from models when aggregating the 3 sets of 4-week conditions, 4 sets of sensitivity analyses were conducted:

Sensitivity analysis 1

Modelling the primary analysis, using a heteroscedastic linear mixed model, with study period as fixed-effects predictor without controlling for other predictors while modelling the dependence (random effects) and heteroscedasticity as in the primary analysis.

Sensitivity analysis 2

Same model as in the primary analysis, using a heteroscedastic linear mixed model, but applied to all available daily-level data, i.e., including data from sites with incomplete data and/or whose data indicated a violation of protocol for intervention implementation, e.g., sales of pints during period B.

Sensitivity analysis 3

Same model as in the primary analysis, using a heteroscedastic linear mixed model, but considering the intervention predictor as a 3-level factor (with levels A1, B, and A2), thus allowing the pre- and postintervention periods to have different average sale levels.

Sensitivity analysis 4

Use of a paired t test to compare the premises’ beer sales aggregated per intervention period, obtained by considering the mean daily sales. Like sensitivity analysis 1, this model does not control for other predictors. Furthermore, the model relies on fewer assumptions than the primary analysis, suggesting that the conclusions of the primary analysis are not dependent on its assumptions.

Analysis of secondary outcome

Three sets of secondary analyses were conducted:

Negative binomial regression analysis to estimate the number of beer drinks sold in each serving size per day according to study Period (A versus B).

A heteroscedastic linear mixed model analysis, similar to that used for the primary analysis (i.e., using the fixed and random effects) to estimate the daily volume of table wine (excluding fortified wines) sold according to study period (A versus B).

A heteroscedastic linear mixed model analysis, similar to that used for the primary analysis (i.e., using the fixed and random effects) to estimate total daily revenue according to study Period (A versus B).

Results

The flow of premises through the study is shown in Fig 1. Thirteen licensed premises were recruited from 1,740 contacted in 6 geographical areas of England, a recruitment rate of 0.75%. Site 2 violated the protocol by selling pints during the intervention period, identified by inspection of their data. All data from this premises were excluded from the primary analysis.

10.1371/journal.pmed.1004442.g001 Fig 1 Flow of premises through the study.

Primary outcome analysis: Volume of beer sales

The unadjusted mean daily volume of beer sold per 12 premises during the nonintervention periods (A1 + A2) was 43,136 ml (SD = 48,592.4) and 36,061.0 ml (SD = 43,099.8) during the intervention period (B) (Table 2). After accounting for prespecified covariates (day of the week; study day; total revenue; temperature; special events), there was a significant effect of study period (Table 3): The mean daily change in volume of beer sold was −2,769.21 ml (95% CI [−4,188.46, −1,577.75], p < 0.001) or 9.7% (95% CI [−13.5%, −6.1%]) during the intervention period (B) compared to the 2 nonintervention periods (A1 + A2). Fig 2 shows the effect of the intervention on beer sales overall and for each of the 12 premises included in the primary analysis. Detailed time series plots, showing daily beer, wine, and total sales by site, are shown in the Supporting information (S1 Appendix, Figs A1 to A13).

10.1371/journal.pmed.1004442.g002 Fig 2 Change in daily volume of beer sold (% (95% CI) with intervention.

10.1371/journal.pmed.1004442.t002 Table 2 Unadjusted mean (SD) volume (ml) of beer sold per day, overall and by serving size, and volume of wine (ml) sold of premises included in primary analysis (n = 12).

	Nonintervention periods [A1 + A2]
(both combined)	Intervention period [B]	
Overall volume of beer sold	43,476.8 (48,592.4)	36,061.0 (43,099.8)	
Volume of beer sold in 1/3 pints (189 ml)	88.3 (404.6)	78.0 (331.2)	
Volume of beer sold in 275 ml	0.99 (16.5)	2.93 (28.3)	
Volume of beer sold in 1/2 pints (284 ml)	2,127.4 (3,020.0)	2,218.4 (2,889.5)	
Volume of beer sold in 330 ml	3,212.1 (19,239.8)	2,085.7 (7,731.3)	
Volume of beer sold in 355 ml	0	2.53 (42.3)	
Volume of beer sold in 375 ml	21.0 (131.1)	10.7 (83.2)	
Volume of beer sold in 2/3 pints (378 ml)	666.3 (2,294.9)	28,714.5 (37,571.3)	
Volume of beer sold in 440 ml	1,203.6 (4,651.9)	1,320.0 (5,208.4)	
Volume of beer sold in 500 ml	1,384.0 (2,633.0)	1,485.8 (3,191.7)	
Volume of beer sold in 550 ml	17.9 (143.3)	15.6 (173.2)	
Volume of beer sold in 568 ml cans	6.17 (83.6)	40.4 (216.2)	
Volume of beer sold in pints (568 ml)	34,713 (41,338.6)	0	
Volume of beer sold in 6,600 ml	2.39 (39.7)	0	
Volume of beer sold in 750 ml	29.9 (219.3)	21.3 (124.9)	
Volume of wine sold	4,706.7 (5,255.3)	4,822.1 (4,611.6)	

10.1371/journal.pmed.1004442.t003 Table 3 Heteroscedastic linear mixed model main results, estimating the volume (ml) of beer sold per day on the transformed (cube root) scale, on the original scale and on the relative scale, covariate coefficients shown in Table A in S3 Appendix (n = 12).

Rounding is to 2 decimal places.

Scale	Intercept	Intervention	
Estimate	Estimate	Lower 95% CI	Upper 95% CI	p-value	
Transformed (cube root)	30.62	−1.01	−1.39	−0.64		
Original (ml)	29,126.66	−2,769.21	−4,188.46	−1,577.75	<0.001	
Relative (%)	100.00	−9.66	−13.52	−6.08		

Sensitivity analyses

Results and conclusions were unchanged when running the model with our 2-level intervention factor as a unique predictor. Indeed, the simplified model led to an average change in daily beer sales of −1,535.3 ml (95% CI [−2,342.6, −863.4], p < 0.001) or −13.8% (95% CI [−19.0%, −8.8%]) during the intervention period (B) compared to the nonintervention periods (A1 + A2) (Table B in S3 Appendix).

Similarly, an intention-to-treat analysis (n = 13) that included the one premises that had violated the protocol had no effect on the main results. The model fit showed that, on average, −2,912.7 ml (95% CI [−4,386.0, −1,685.3], p < 0.001) or −9.6% (95% CI [−13.2%, −6.1%]) was the change in beer sold per day during the intervention period (B) compared to the non-intervention periods (A1 + A2) (Table C in S3 Appendix).

In order to assess whether the 2 nonintervention periods were comparable, an additional analysis was conducted in which the 2 nonintervention periods were added to the model separately. The results showed that sales of beer did not significantly differ during the 2 nonintervention periods (A1 versus A2) (p = 0.374) (Table D in S3 Appendix), justifying the choice of combining data from both nonintervention periods for the primary analysis.

The analysis considering per intervention period aggregated sales data per site (obtained by estimating the average of the daily sales per site and intervention period) rather than daily-level data also concluded that beer sales were significantly lower during the intervention period (B) compared to the nonintervention periods (A1 + A2) (average change of −7,862 ml or −20%; p < 0.001) (Table E in S3 Appendix).

Analysis of secondary outcomes

Beer sales by serving size

During the nonintervention periods, the largest selling serving size in terms of volume (Table 2) and average number of drinks sold per day (Table F in S3 Appendix) was the pint (568 ml). During the intervention period, the largest selling serving size was the two-third pint (Table 2 and Table F in S3 Appendix).

During the intervention period, sales of half-pints, 440 ml and 568 ml cans increased slightly with statistical significance (Table F in S3 Appendix).

Volume of wine sold

The unadjusted mean daily volume of wine sold per premises during the nonintervention periods (A1 + A2) was 4,706.7 ml (SD = 5,255.3) and 4,822.1 ml (SD = 4,611.6) during the intervention period (B) (Table 2). After accounting for prespecified covariates (day of the week; study day; total revenue; temperature; special events), there was a significant effect of study period (Table G in S3 Appendix and Fig B in S1 Appendix): On average, 232.0 ml (95% CI [112.7, 487.5], p = 0.035) or 7.2% (95% CI [0.4%, 14.5%]) more wine was sold per day during the intervention period (B) compared to the 2 nonintervention periods (A1 + A2).

Daily revenue

The unadjusted mean daily per premises sales during the nonintervention periods (A1 + A2) was £2,336.9 (SD = 3,053.6), and £2,091.5 (SD = 2,703.8) during the intervention period (B). After accounting for prespecified covariates (day of the week; study day; total revenue; temperature; special events), there was a significant effect of study period (Table H in S3 Appendix): On average, daily revenues decreased during the intervention period (B) compared to the nonintervention periods (A1 + A2) (−£67.2; 95% CI [−£146.6, −£3.7], p = 0.038); −5.0% (95% CI [−9.6%, −0.3%]).

Discussion

Removing the largest serving size of draught beer (the imperial pint, 568 ml) from the range of options available in 12 licensed premises reduced the volume of beer sold by 9.6%. The intervention was also associated with a small absolute increase in the volume of wine sold during the intervention period, and a small decrease in daily revenues.

The intervention had the hypothesised effect of reducing the volume of beer sold. This is in keeping with recent findings showing that removing the largest serving size of wine in licensed premises reduced the volume sold by a similar amount: 7.6% (95% CI [−12.3%, −2.9%]) [29]. It is also consistent with the results of 2 studies conducted in seminaturalitic contexts—which found a reduction in alcohol consumption on a single occasion when larger servings were removed and replaced by smaller sizes [28]—and with a large body of evidence on the effect of smaller serving sizes on food consumption [44].

The results suggest that when the largest serving size of draught beer was not available, people shifted to the next available size, the two-third pint, which resulted in them drinking less. This could be explained by a tendency to consume a specific number of “units” (e.g., number of glasses or bottles), regardless of serving or package size [45]. If patrons ordered a preset number of beer servings, regardless of size, with less alcohol per serving in two-third pints, they would purchase less overall. There were also more half-pints sold during the intervention period, suggesting that some patrons might have shifted to this size in the absence of pints, but this did not appear to have happened enough to compensate for the removal of the 1 pint serving size.

Two-thirds of a pint is arguably not too small a measure to be considered a large deviation from 1 pint and thus provoke resistance, but small enough to reduce consumption. Had the largest size available been the half-pint instead, that may have been considered too small, in part because there appears to be a negative attitude in England, albeit declining, towards ordering and drinking half-pints [46]. This could therefore inadvertently have led to greater consumption than that observed in the current study [47,48]. Another reason people tend not to prefer smaller servings or packages is that these are not proportionately priced, so provide less value for money [25]. Premises in the current study were asked to price two-third pints in proportion to pint and half-pint sizes to ensure they represented the same value for money compared to other available draught serving sizes. While all premises confirmed they had done so, we were only able to verify this for the small number of premises that had drinks lists available.

In addition to the intervention having the predicted impact on lowering beer sales, it was associated with a small increase in the absolute volume of wine sales. We considered 3 possible explanations for this unexpected finding, informed by reflections from some of the participating premises. First, it is a chance finding, perhaps due to factors unrelated to the study. Second, it is a result of some beer drinkers switching to wine when pint servings are not available. This seems more plausible in premises that serve food and for people who tend to have beer before, and wine with, their meal. In the absence of their typical serving size for beer, such customers might have opted immediately for wine. This was the account given by one of the premises, which was responsible for around 50% of the increase in wine sales observed during the study. Interestingly, however, following the reintroduction of pints, wine sales in this premises were still rising, casting doubts on this explanation. Third, it is a result of premises managers responding to reduced beer sales by promoting wine sales. Two premises reported changing their wine lists during the intervention period and promoting their new lists at that time.

However, even if the increase in wine sales in the absence of the largest serving size for beer is not a chance finding, it is important to note that this effect on wine was small in absolute terms and far smaller than the effect of reduced sales of beer. Removing the largest serving size resulted in an average per premises per day of 2,769.2 ml less beer being sold, equivalent to approximately 5 pints or 13 units of alcohol, if assuming an average ABV for beer of 4.6% [49]. The volume of wine sold increased 232.0 ml per day, i.e., almost 1 large glass of wine or approximately 3 units of alcohol—assuming an average ABV for wine of 12% [49]. After accounting for the small increase in wine sales, the intervention therefore still resulted in approximately 10 fewer units of alcohol being sold per day by each premises. Given that no level of alcohol consumption is currently considered safe for health [50], such a reduction could meaningfully contribute to population health.

In terms of the study strengths, to our knowledge, this is the first study to estimate the impact on sales of removing the largest serving of size of draught beer in pubs, bars, and restaurants, under real-world conditions. The pint has been the standard and most popular serving size for beer in England for centuries [30], having been established in 1698 [51]. Indeed, “going for a pint” has become synonymous with the act of going for a drink in British culture [52]. Previous attempts to remove this “iconic” serving size for research purposes have been unsuccessful [29]. Further strengths of this study include the use of objective measures to assess the primary and secondary outcomes, i.e., electronic records of sales and the high retention rate of premises through the study.

The study, however, also has several limitations. First, it was unable to fully assess the possibility of any compensation effects. Due to the complexity of the sales reports provided by participating premises, it was not feasible to assess sales of all alcoholic drinks. Although beers, ciders, and wines are estimated to contribute more than 70% of the sales of alcoholic drinks in licensed premises in the UK [40], it was not possible to assess sales of spirits or cocktails, estimated to contribute to the remaining 30%. It is not known, therefore, whether people might have compensated for their reduced beer consumption by drinking more of these other alcoholic drinks. Given that the intervention also resulted in a decrease in daily revenue and that cocktails and spirits tend to be more expensive than beers, this seems unlikely. It is also not known whether customers compensated for the removal of pints by drinking stronger beers, i.e., those higher in percentage alcohol by volume (% ABV). We judged this unlikely given there were very small variations in the % ABV of beers sold by premises, with most options ranging from 4% to 5%. Also, beers lists did not change during the study, and none of the premises managers interviewed at the end of the study reported any changes in the drinking patterns of their customers during the intervention period relating to beer strength. Finally, it is unknown whether people compensated for their reduced beer consumption by drinking more alcohol at home, although this has not been shown to be the case in previous research, in which, like in the current study, pints were replaced by two-third pints during one drinking occasion in a seminaturalistic setting [28]. Second, caution is needed in generalising these findings. The low response rate to an invitation to participate in the study might have resulted in sampling bias, meaning that participating premises may not have been representative of typical licensed premises in England. Additionally, the majority of premises were in London, which potentially restricts the generalisability of the findings to this large metropolitan city. The remainder were also in cities and no premises were located in smaller towns or rural areas. Third, sales were used as a proxy for actual consumption; direct measurement of which at scale in these kinds of real-world settings is not feasible. Sales are, however, a valid proxy for consumption [53] and are commonly used in behavioural research [54–56]. Finally, the intervention was assessed for a 4-week period, leaving uncertainties about whether the observed effects are sustained over time.

In terms of the broader implications of this study, the sizes of servings of alcoholic drinks sold in licensed premises in England are subject to regulations, and draught beer must be legally available for sale in pints and half-pints [36]. One-third and two-thirds of a pint can also be sold, but licensed premises are not legally obliged to offer these [30,37]. The pint is by far the most popular serving size in the UK [30]. Based on the current findings, removing this serving size from the range offered in licensed premises and replacing it with two-thirds of a pint could contribute to policies for reducing alcohol consumption at the population level, thereby meriting consideration as part of alcohol control policies. Given that alcohol contributes between 5% and 10% of energy intake among those who consume it [57,58], the intervention also merits consideration as part of policies tackling obesity in adults.

The results suggest a possible unexpected small increase in wine sales associated with the intervention, an effect that requires replication. Given evidence that removing the largest serving size of wine by the glass from the range offered in licensed premises reduces wine sales without affecting beer sales [29], regulations might be considered that target the largest servings of both beer as well as wine. Indeed, the impact of simultaneously removing the largest serving sizes of both draught beer and wine by the glass should be assessed, whether as part of monitoring the impact of a change in regulations or in further field studies.

Interventions that involve removing or reducing serving or package sizes are generally less supported by the public than information-based interventions such as health warning labels [59–61]. Given that the pint has been the customary serving size for draught beer in England for centuries [30], significant pushback for its removal was expected both by the research team and premises managers. But premises reported receiving surprisingly few comments or complaints from customers when the largest serving size was reduced to two-thirds of a pint. Four of the 13 participating premises reported receiving some complaints, which abated as customers got used to the new serving sizes. Whether this was because customers knew that the change was time-limited or because they realised that two-thirds of a pint was sufficient remains to be explored. Indeed, regulating serving sizes in licensed premises could help shift social norms for what constitutes an appropriate serving size [62–64], both for consumption out of the home such as in pubs and bars, as well as for consumption at home where most drinking occurs [65]. This possible indirect effect of the intervention awaits study. Given that serving sizes perceived as normal do not lead to compensation effects, in contrast to when sizes are perceived as small [66], future research should also assess the possible mediating effect of social norms about serving sizes on the potential for people to compensate for reduced consumption in licensed premises by drinking more at home; although previous has shown this not to be the case.

Although customers did not voice strong objections to the removal of pints in the 13 premises that participated in this study, the low response rate to invitations to participate in the study—fewer than 1% of premises approached, lower than the 1.2% rate observed in a previous similar study for wine [29]—suggests that support for the intervention might be generally low. Expected loss of revenue increases the possibility that licensed premises would object to intervention implementation should it be considered as part of alcohol regulation policies. Although removal of pints in the present study reduced daily revenues, losses were relatively small (average change of −£67 (5% of total revenues), 95% CI [−£146.6, −£3.7]). After the study ended, none of the participating premises removed their pint servings. Without regulation, this intervention is most unlikely to be implemented. Regulation to implement it will—understandably—meet resistance from the alcohol industry, a resistance seen to minimum unit price policies [67], but a resistance that needs to be addressed for effective alcohol control policies.

In conclusion, removing the largest serving (the imperial pint) for draught beer from the range of options available in licensed premises, so that the largest size became two-thirds of a pint, reduced the volume of beer sold. Given the potential of this intervention to reduce alcohol consumption, it merits consideration in alcohol control policies.

Supporting information

S1 Appendix Addtional figures.

(DOCX)

S2 Appendix Sample size calculation report.

(PDF)

S3 Appendix Addtional figures and analyses.

(DOCX)

S1 CONSORT Checklist Checklist of information to include when reporting a randomised trial.

(DOC)

We would like to thank the premises taking part in this study for their excellent cooperation. We would also like to thank Ms. Caveny Mantzaris for her help in cleaning and checking the data as part of her interniship at the Behaviour and Health Research Unit, University of Cambirdge in May/June 2023.

Transparency declaration

The lead author (the manuscript’s guarantor) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as originally planned (and, if relevant, registered) have been explained.

10.1371/journal.pmed.1004442.r001
Decision Letter 0
Janin Katrien G. Senior Editor
© 2024 Katrien G. Janin
2024
Katrien G. Janin
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version0
4 Mar 2024

Dear Dr Marteau,

Thank you for submitting your manuscript entitled "Impact on beer sales of removing the pint serving size: an A-B-A reversal trial in pubs, bars and restaurants in England" for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff as well as by an academic editor with relevant expertise and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. We also have the following editorial request: please include the study protocol document as approved by your committee as Supporting Information.

To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by Mar 07 2024 11:59PM.

Login to Editorial Manager here: https://www.editorialmanager.com/pmedicine

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email me at kjanin@plos.org or contact the journal office at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Katrien G. Janin, PhD

Senior Editor

PLOS Medicine

10.1371/journal.pmed.1004442.r002
Decision Letter 1
Janin Katrien G. Senior Editor
© 2024 Katrien G. Janin
2024
Katrien G. Janin
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version1
10 Apr 2024

Dear Dr. Marteau,

Thank you very much for submitting your manuscript "Impact on beer sales of removing the pint serving size: an A-B-A reversal trial in pubs, bars and restaurants in England" (PMEDICINE-D-24-00685R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

After discussing the paper with the editorial team, I’m pleased to invite you to revise the paper in response to the reviewers’ comments. We plan to send the revised paper to the original reviewers, and we cannot provide any guarantees at this stage regarding publication.

When you upload your revision, please include a point-by-point response that addresses all of the reviewer and editorial points, indicating the changes made in the manuscript and either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please also be sure to check the general editorial comments at the end of this letter and include these in your point-by-point response. When you resubmit your paper, please include a clean version of the paper as the main article file and a version with changes marked as a marked-up manuscript. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper

We expect to receive your revised manuscript by May 01 2024 11:59PM. However, if this deadline is not feasible, please contact me by email, and we can discuss a suitable alternative.

Please use the following link to submit the revised manuscript: https://www.editorialmanager.com/pmedicine

Your article can be found in the "Submissions Needing Revision" folder.

Don’t hesitate to contact me directly with any questions (kjanin@plos.org). If you reply directly to this message, please be sure to ‘Reply All’ so your message comes directly to my inbox.

We look forward to receiving your revised manuscript.

Sincerely,

Katrien Janin, PhD

PLOS Medicine

plosmedicine.org

kjanin@plos.org

-----------------------------------------------------------

Requests from the editors:

Please include line numbers in your revised manuscript, ideally not starting from 1 with each new page.

Please cite the reference numbers in square brackets. Citations should precede punctuation.

Abstract: Please report your abstract according to CONSORT for abstracts, following the PLOS Medicine abstract structure (Background, Methods and Findings, Conclusions) https://www.equator-network.org/reporting-guidelines/consort-abstracts/ (see per previous study “Impact on wine sales of removing the largest serving size by the glass: An A-B-A reversal trial in 21 pubs, bars, and restaurants in England’ - https://doi.org/10.1371/journal.pmed.1004313)

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Ideally each sub-heading should contain 2-3 single sentence, concise bullet points containing the most salient points from your study. In the final bullet point of ‘What Do These Findings Mean?’, please include the main limitations of the study in non-technical language. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary.

Please complete the CONSORT checklist and ensure that all components of CONSORT are present in the manuscript. When completing the checklist, please use section and paragraph numbers, rather than page numbers.

Discussion: please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice and/or public policy implications; followed by a one-paragraph conclusion. Please remove all subheadings within your Discussion.

Financial Disclosure: The funding statement should include: specific grant numbers, initials of authors who received each award, URLs to sponsors’ websites. Also, please state whether any sponsors or funders (other than the named authors) played any role in study design, data collection and analysis, the decision to publish, or preparation of the manuscript. If they had no role in the research, include this sentence: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

Supplementary materials: Please note that supplementary materials are not checked and will be posted as supplied by the authors. Therefore, please double check. Please cite your Supporting Information as outlined here: https://journals.plos.org/plosmedicine/s/supporting-information - Please note you may use almost any description as the item name of your supporting information as long as it contains an "S" and number. For example, “S1 Appendix” and “S2 Appendix,” “S1 Table” and “S2 Table. Please ensure each supplementary material has a call out (link) from your main manuscript.

To help us extend the reach of your research, please provide any Twitter handle(s) that would be appropriate to tag, including your own, your coauthors’, your institution, funder, or lab.

-----------------------------------------------------------

Comments from the reviewers:

Reviewer #1: Thanks for the opportunity to read your manuscript. My role is statistical reviewer, so I have focused on the design, data, and analysis that are presented. I have put general comments first, followed by questions relevant to a specific section of the manuscript (with a page/paragraph reference).

This study examines the effectiveness of removing 'pint' (568 mL) serving sizes from licenced premises, replacing with a smaller size serving (2/3rds of a pint). Thirteen sites were recruited for the study. The volume of beer and cider (draught and bottled) was the primary outcome, with secondary outcomes including size-specific volume of beer/cider, daily volume of wine, and daily revenue. Data was collected over 12 week, with a 4 week baseline period, 4 weeks of intervention (pints not available), and 4 weeks of withdrawal of intervention. Data was collected through the same time-period across all sites, and fidelity to the intervention was checked at all sites.

The main analysis used an extension of liner mixed models to allow for site-specific heterogeneity in variance. The main outcome was transformed (^1/3), with parameters in the model for study period, day of week, day of study, daily revenue, temperature, and special events. Adding daily revenue as a covariate means the main outcome for the study from this analysis can be thought of as beer/cider volume proportional to overall sales. Random intercepts were included for sites, and a random slope term for overall revenue of each site.

Several sensitivity analyses were considered, looking at the effect of removing covariates from the main analysis, data from sites that were not adherent, allowing baseline and reversal periods to have different levels, and an analysis that directly compared total volume of beer/cider aggregated to either no-intervention or intervention. There was a reduction in the volume of beer and cider sold during the intervention period, and with a 5% decline in daily revenues and a small increase in wine sold. The treatment effect from these sensitivity analyses was close to that seen in the main analysis.

There was a low response rate - does this affect the generalisability of the findings?

P9. Is 'wine' just table wine or does it include fortified wines?

P12, Paragraph 1. In the methods it is mentioned that all sites passed the fidelity checks - this seems to contradict this paragraph.

P13, Table 3. I would consider some adjustments to this table. Most of the information presented here about covariates could be safely moved to an appendix. I would also consider presenting just the estimate, p-value, and 95% CI here. The intercept is also superfluous to the main research questions. Is it also possible to present a back-transformed treatment effect estimate (with CL) in both the table and the main results? This would be ideal for all results where the outcome was transformed before the analysis.

Supplmentary appendices. The titles/captions for the tables should have information about the type of sensitivity analysis in each case rather than just 1, 2, 3 etc.

The study has a pre-registered protocol and statistical analysis plan, these match the current manuscript.

P6, Paragraph 2. This is a comment and requires no response - I am absolutely delighted to see a mention of the strange names for beer glass sizes from South Australia. They are a complete aberration. As a frequent visitor to Adelaide I have been caught out many times by ordering a 'Schooner' (425mL in my hometown, 3/4 of a pint) and ending up with a disappointing sized glass of beer (285mL, 1/2 pint).

P10, Paragraph 5. Just to check - does 'heteroscedastic LMM" mean that a different constraint was allowed for each site in residual variance? i.e. is this similar to what is done with the 'group' option in proc mixed in SAS or with the galamm package in R?

P10, Paragraph 6. What checks of model fit were made?

What software was used for the analysis?

P10, Paragraph 7. I follow the rationale for most of these sensitivity analyses, except for #4. What was assumption being tested with aggregating the data and using a paired t-test?

P11, Paragraph 5. Did the negative binomial model just include a parameter for day of study, or did it include similar parameters to the main analysis? Was a negbin model used for every possible serving size?

Figure 2. Instead of the 'dynamite' plot presented here, I'd consider plotting as much of the data as possible, e.g. is it possible to construct a panel graph showing the time series of primary outcome across all the study in each site? I think with the type of model used, it should also be possible to estimate a 'counterfactual' estimate of beer/cider volume sold if the intervention was not implemented (similar to an interrupted time series).

Reviewer #2: The authors have presented an intervention study with a clear rationale robust methodology. I applaud the authors use of transparent research methods, having registered their work with the open science framework prior to publication. The authors are following up on their previous work, examining whether reducing the servicing size of wine reduced consumption but now looking at beer products. They find a similar result, lowering serving sizes does result in decreased consumption. The article is of high quality and answers an important question - while the similarities to their previous work are undeniable this is a strength of the article rather than a limitation - they are building on their prior work in a meaningful way. There are some points I would like to see the authors address ahead of publication:

1. First sentence appears to have a citation error (1), (2). Should be (1,2).

2. "Licensed premises in Western Australia have undergone a process by which a pint-drinking culture has been replaced by a schooner-drinking one, to tackle increasing costs and adhere to government efforts to reduce alcohol consumption (32-34)." - the references used here are two media publications and a Wikipedia article, the authors should use higher quality empirical evidence when discussing drinking trends and their causes. This point does not add anything of value to the manuscript and could be cut.

3. "A simulation-based predictive power analysis" - could the authors go into more detail here, what was the exact method used, the statistical software, packages/commands. The reader should be able to replicate this process from the information provided in the text.

4. "Thirteen licensed premises were recruited from 1740 contacted in six geographical areas of England, a recruitment rate of 0.75%." - this is incredibly low, what were the reasons that the other 1727 venues were not recruited - was this part of the recruitment strategy (e.g. contacting all venues and then recruiting the first ones that came back) or was this due to 1727 venues saying no?

5. "ABV for beer of 4.6%" - this brings up an important point, could people have ordered a stronger beer to compensate for the smaller size? In Australia, low mid and full-strength beers are available for purchase, are these available in the UK? Could this intervention move someone from a mid to full strength beer?

6. "The pint is by far the most popular serving size in the UK (or England?)" - the authors should choose whether it is the UK or England they are referring to.

Reviewer #3: This is a great, well-written paper on an important topic. I enjoyed reading it. I do have some comments which I think will improve this manuscript.

Abstract

I don't think this is the first study to assess the impact of reducing serving size of beer on sales in a licensed premises. I think that is also examined in this published paper, though admittedly it is observed sales: https://onlinelibrary.wiley.com/doi/10.1111/add.14228. Yours is the first study that I am aware of to do so using objective sales data. This study is still very important and extends the prior findings considerably, but this sentence should be toned down.

Introduction

The last couple of sentences could be a little clearer, you say that a schooner is a pint, but also that Western Australia is transitioning from pints to schooners. Think this is down to regional differences in terminology but rewording could make this clearer.

It would be helpful to mention compensation in the introduction. If people have smaller drinks in the on-trade are they more likely to go home and have more drinks because they'd only had a small one? The Kersbergen study gets at this a bit.

Theres also a theory about norms and serving size, which outlines that there is a range of serving sizes which are accepted as being one serving, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6333281/#:~:text=The%20first%20proposition%20of%20the,'not%20normal'%20in%20size whereby compensation is less likely, which I believe Dr Kersbergen has applied to alcohol consumption too. (I am not Dr Kersbergen but a big fan of her research).

What was the reasoning for only reducing one beverage type? Might it be more effective to remove all the largest servings e.g. wine, spirits.

Methods

Did you include draft cider too? You refer to draft beer throughout but seems it would make sense to include cider too? After reading the measures I think cider was included in your primary outcome, this could be clearer throughout including the title - e.g. beer and cider sales.

Why didn't you include any PPI input? I guess it's a journal requirement but feels strange to include a section if you don't actually have any PPI input, explaining why you didn't might be helpful. I also think getting some PPI input into these findings and what they actually mean in terms of practice and implementation could be a really interesting addition if you did want to incorporate some PPI.

Results

It is unclear to me why in your sensitivity analysis with intervention as a unique predictor that your mean difference is less in ml but the proportional decrease is much greater? I can't work out why the total ml would change.

Discussion

I really enjoyed your discussion, all of the things I was thinking about whilst reading the paper are unpicked and explained really nicely. (I had to go back through and delete a lot of my comments as you had done such a good job of unpicking and explaining it all!).

One additional limitation around compensation, you don't know what people drank after, did they compensate at home because they'd only had a small one?

Thanks for the opportunity to read this really interesting work - Melissa Oldham

-----------------------------------------------------------

General editorial requests:

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

Check FD, CI, DAS and ethics statement and include requests if necessary

Any attachments provided with reviews can be seen via the following link:

[LINK]

10.1371/journal.pmed.1004442.r003
Author response to Decision Letter 1
Submission Version2
17 Jun 2024

Attachment Submitted filename: Pints study_response to reviewers FINAL.docx

10.1371/journal.pmed.1004442.r004
Decision Letter 2
Janin Katrien G. Senior Editor
© 2024 Katrien G. Janin
2024
Katrien G. Janin
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version2
5 Jul 2024

Dear Dr. Marteau,

Thank you very much for re-submitting your manuscript "Impact on beer sales of removing the pint serving size: an A-B-A reversal trial in pubs, bars and restaurants in England" (PMEDICINE-D-24-00685R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by xxx reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.  

We look forward to receiving the revised manuscript by Jul 12 2024 11:59PM.   

Sincerely,

Katrien Janin, PhD

Senior Editor 

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

Thank you for your detailed response to the editors' and reviewers' comments. I have discussed the paper with my colleagues and the academic editor, and it has also been seen again by the original reviewers. The changes made to the paper were welcomed by the reviewers.

I only have a few minor request for you at this stage:

1) Statistical reporting:

We suggest reporting statistical information in the following format: ‘x’; (95% CI [‘y’,’ z’] p value). For p values, please report as p<0.001 and where higher as 'p=0.002'. Please add the statistical method used to your method section. We also invite you to report p values to consistently to the third decimal digit - thousandths. For example, see abstract : "After adjusting for pre-specified covariates, the intervention resulted in a mean daily change of -2769ml (95% CI -

4188 to -1578, p<0.00001) or -9.7% (95% CI -13.5% to -6.1%) in beer sold. The daily volume of wine sold increased during the intervention period by 232ml (95% CI 13 to 487, p=0.035) or 7.2% (95% CI 0.4% to 14.5%). Daily revenues decreased by 5.0% (95% CI -9.6% to -0.3%, p=0.038). " Please check and amend throughout.

2) CONSORT checklist. Thank you for supplying the CONSORT checklist (S3). Please remove the page numbers from this list, and use section headers and paragraph numbers, please remove the page numbers.

3) please double check that reference #29 is updated

------------------------------------------------------------

Comments from Reviewers:

Reviewer #1: Thanks for the revised manuscript and responses to my original review. The updated manuscript resolves my original queries - the more detailed figures in the appendix are a helpful addition

Reviewer #2: Thankyou, I am happy with the revisions and response to my comments.

Reviewer #3: The authors have responded to all my comments and I would recommend that this paper is now published.

Any attachments provided with reviews can be seen via the following link:

[LINK]

10.1371/journal.pmed.1004442.r005
Author response to Decision Letter 2
Submission Version3
12 Jul 2024

Attachment Submitted filename: Pints study_response to reviewers 2 FINAL.docx

10.1371/journal.pmed.1004442.r006
Decision Letter 3
Janin Katrien G. Senior Editor
© 2024 Katrien G. Janin
2024
Katrien G. Janin
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version3
15 Jul 2024

Dear Dr Marteau, 

On behalf of my colleagues and the Academic Editor, [AE Name], I am pleased to inform you that we have agreed to publish your manuscript "Impact on beer sales of removing the pint serving size: an A-B-A reversal trial in pubs, bars and restaurants in England" (PMEDICINE-D-24-00685R3) in PLOS Medicine.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process. 

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper. 

Sincerely, 

Katrien G. Janin, PhD 

Senior Editor 

PLOS Medicine
==== Refs
References

1 Gakidou E AA , Abajobir AA , Abate KH , Abbafati C , Abbas KM , et al . Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390 (10100 ):1345–422. doi: 10.1016/S0140-6736(17)32366-8 28919119
2 World Health Organization. Alcohol 2022. https://www.who.int/news-room/fact-sheets/detail/alcohol. 20th June 2023.
3 Rehm J SK . Alcohol and mortality: global alcohol-attributable deaths from cancer, liver cirrhosis, and injury in 2010. Alcohol Res. 2014;35 (2 ):174.
4 Grenard JL , Dent CW , Stacy AW . Exposure to alcohol advertisements and teenage alcohol-related problems. Pediatrics. 2013;131 (2 ):e369–e379. doi: 10.1542/peds.2012-1480 23359585
5 Koordeman R , Anschutz DJ , Engels RC . The effect of alcohol advertising on immediate alcohol consumption in college students: an experimental study. Alcohol Clin Exp Res. 2012;36 (5 ):874–880. doi: 10.1111/j.1530-0277.2011.01655.x 22017281
6 Brown KG , Stautz K , Hollands GJ , Winpenny EM , Marteau TM . The cognitive and behavioural impact of alcohol promoting and alcohol warning advertisements: an experimental study. Alcohol Alcohol. 2016;51 (3 ):354–362. doi: 10.1093/alcalc/agv104 26391367
7 Stautz K , Brown KG , King SE , Shemilt I , Marteau TM . Immediate effects of alcohol marketing communications and media portrayals on consumption and cognition: a systematic review and meta-analysis of experimental studies. BMC Public Health. 2016;16 (1 ):1–18. doi: 10.1186/s12889-016-3116-8 26728978
8 Zhao J , Stockwell T , Vallance K , Hobin E . The effects of alcohol warning labels on population alcohol consumption: an interrupted time series analysis of alcohol sales in Yukon, Canada. J Stud Alcohol Drugs. 2020;81 (2 ):225–237. 32359054
9 Clarke N , Pechey E , Mantzari E , Mantzari E , Blackwell AK , De-loyde K , et al . Impact of health warning labels communicating the risk of cancer on alcohol selection: an online experimental study. Addiction. 2021;116 (1 ):41–52. doi: 10.1111/add.15072 32267588
10 Clarke N , Ferrar J , Pechey E , Ventsel M , Pilling M , Munafò M , et al . Impact of health warnings and calorie labels on selection and purchasing of alcoholic and non-alcoholic drinks: a randomised controlled trial. Addiction. 2023(12 ):2327–2341.37528529
11 Stockwell T , Gruenewald PJ . Controls on the physical availability of alcohol. In: Heather N , Stockwell T , editors. The essential handbook of treatment and prevention of alcohol problems: Wiley; 2004. p. 213–233.
12 Foster S , Trapp G , Hooper P , Oddy WH , Wood L , Knuiman M . Liquor landscapes: Does access to alcohol outlets influence alcohol consumption in young adults? Health Place. 2017;45 :17–23. doi: 10.1016/j.healthplace.2017.02.008 28258014
13 Freisthler B , Wernekinck U . Examining how the geographic availability of alcohol within residential neighborhoods, activity spaces, and destination nodes is related to alcohol use by parents of young children. Drug Alcohol Depend. 2022;233 :109352. doi: 10.1016/j.drugalcdep.2022.109352 35176631
14 Clarke N , Blackwell AK , Ferrar J , De-Loyde K , Pilling MA , Munafò MR , et al . Impact on alcohol selection and online purchasing of changing the proportion of available non-alcoholic versus alcoholic drinks: A randomised controlled trial. PLoS Med. 2023;20 (3 ):e1004193. doi: 10.1371/journal.pmed.1004193 36996190
15 Hughes K , Quigg Z , Eckley L , Bellis M , Jones L , Calafat A , et al . Environmental factors in drinking venues and alcohol-related harm: the evidence base for European intervention. Addiction. 2011;106 :37–46. doi: 10.1111/j.1360-0443.2010.03316.x 21324020
16 Sharma A , Sinha K , Vandenberg B . Pricing as a means of controlling alcohol consumption. Br Med Bull. 2017:1–10. doi: 10.1093/bmb/ldx020 28910991
17 Xu X , Chaloupka FJ . The effects of prices on alcohol use and its consequences. Alcohol Res Health. 2011;34 (2 ):236. 22330223
18 Berdzuli N , Ferreira-Borges C , Gual A , Rehm J . Alcohol control policy in Europe: Overview and exemplary countries. Int J Environ Res Public Health. 2020;17 (21 ):8162. doi: 10.3390/ijerph17218162 33158307
19 Guindon EG , Fatima T , Trivedi R , Abbas U , Wilson MG . Examining the Effectiveness and/or Cost- effectiveness of Policies for Reducing Alcohol Consumption. McMaster Health Forum; 2021.
20 Clarke N , Pechey E , Pechey R , Ventsel M , Mantzari E , De-Loyde K , et al . Size and shape of plates and size of wine glasses and bottles: impact on self-serving of food and alcohol. BMC Psychol. 2021;9 (1 ):1–12.33388086
21 Zlatevska N DC , Holden SS , Sizing up the Effect of Portion Size on Consumption: A Meta-Analytic Review. J Mark. 2014;78 (3 ):140–154.
22 Hetherington M. The portion size effect and overconsumption–towards downsizing solutions for children and adolescents–An update. Nutr Bull. 2019;44 (2 ):130–137.
23 Pilling M , Clarke N , Pechey R , Hollands GJ , Marteau TM . The effect of wine glass size on volume of wine sold: a mega-analysis of studies in bars and restaurants. Addiction. 2020;115 (9 ):1660–1667. doi: 10.1111/add.14998 32003493
24 Mantzari E , Ventsel M , Ferrar J , Pilling MA , Hollands GJ , Marteau DTM . Impact of wine bottle and glass sizes on wine consumption at home: a within and between households randomised controlled trial. Addiction. 2022;117 (12 ):3037–3048.35852024
25 Codling S , Mantzari E , Sexton O , Fuller G , Pechey R , Hollands GJ , et al . Impact of bottle size on in-home consumption of wine: a randomized controlled cross-over trial. Addiction. 2020;115 (12 ):2280. doi: 10.1111/add.15042 32270544
26 Mantzari E , Marteau TM . Impact of Sizes of Servings, Glasses and Bottles on Alcohol Consumption: A Narrative Review. Nutrients. 2022;14 (20 ):4244. doi: 10.3390/nu14204244 36296928
27 Mantzari E , Ventsel M , Pechey E , Lee I , Pilling M , Hollands GJ , et al . Impact on beer sales of adding a smaller serving size: a treatment reversal trial in 13 pubs, bars and restaurants. BMC Public Health. 2023;23 :1239.37365548
28 Kersbergen I , Oldham M , Jones A , Field M , Angus C , Robinson E . Reducing the standard serving size of alcoholic beverages prompts reductions in alcohol consumption. Addiction. 2018;113 (9 ):1598–1608. doi: 10.1111/add.14228 29756262
29 Mantzari E , Ventsel M , Pechey E , Lee I , Pilling M , Hollands GJ , et al . Impact on wine sales of removing the largest serving size by the glass: a treatment reversal trial in 21 pubs, bars and restaurants. PLoS Med. 2024;21 (1 ):e1004313.38236840
30 de Moor D. The ultimate beer measures table 2017. https://desdemoor.co.uk/the-ultimate-beer-measures-table/.
31 USA beer ratings. A Guide To the Most Popular Beer Sizes 2019. https://usabeerratings.com/en/blog/insights-1/a-guide-to-the-most-popular-beer-sizes-,95.htm.
32 Bui J. Schooner Standard Drinks in Australia. JBSolicitors. 2024.
33 Prestipino D. Sneaky pint-sized tricks in Perth are not smart business. WA today. 2016.
34 Emery K. Publicans call time on pints. The West Australian. 2016.
35 Squire J. Pots, Pints and Schooners. Broadsheet. 2016.
36 UK Goverment. Weights and measures: the law. https://www.gov.uk/weights-measures-and-packaging-the-law/specified-quantities. 20th September
37 BBC. Schooner set to join pint after drinks measures review 2011. https://www.bbc.com/news/uk-12113880.
38 Bolker B. GLMM FAQ 2022. http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html.
39 Hollands GJ , Bignardi G , Johnston M , Kelly MP , Ogilvie D , Petticrew M , et al . The TIPPME intervention typology for changing environments to change behaviour. Nat Hum Behav. 2017;1 (8 ).
40 Statista. On-trade drinks sales volume share UK 2022. 2022. https://www.statista.com/statistics/1254227/on-trade-drinks-sales-volume-share-uk/. 20th June 2023
41 Hirche M , Haensch J , Lockshin L . Comparing the day temperature and holiday effects on retail sales of alcoholic beverages–a time-series analysis. Int J Wine Bus Res. 2021;33 (3 ):432–455.
42 de Vocht F , Brown J , Beard E , Angus C , Brennan A , Michie S , et al . Temporal patterns of alcohol consumption and attempts to reduce alcohol intake in England. BMC Public Health. 2016;16 (1 ):1–10. doi: 10.1186/s12889-016-3542-7 26728978
43 R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2016. http://www.R-project.org/.
44 Hollands GJ , Shemilt I , Marteau TM , Jebb SA , Lewis HB , Wei Y , et al . Portion, package or tableware size for changing selection and consumption of food, alcohol and tobacco. Cochrane Database Syst Rev. 2015(9 ):CD011045. doi: 10.1002/14651858.CD011045.pub2 26368271
45 Geier AB , Rozin P , Doros G . Unit bias: A new heuristic that helps explain the effect of portion size on food intake. Psychol Sci. 2006;17 (6 ):521–525.16771803
46 Tyers A. Mine’s a pint! Why real men don’t drink by half measures. The Telegraph. 2015.
47 Benton D. Portion size: what we know and what we need to know. Crit Rev Food Sci Nutr. 2015;55 (7 ):988–1004. doi: 10.1080/10408398.2012.679980 24915353
48 Marteau TM , Hollands GJ , Shemilt I , Jebb SA . Downsizing: policy options to reduce portion sizes to help tackle obesity. BMJ. 2015;351 :h5863. doi: 10.1136/bmj.h5863 26630968
49 Public Health England. Review of typical ABV levels in beer, cider and wine purchased for the ‘in home’ market. 2018.
50 WHO. No level of alcohol consumption is safe for our health. 2023.
51 Hopsmore Craft Beer Club. 2022 [cited 2023]. https://hopsmore.co.uk/blogs/beer-blog/the-story-of-the-british-pint.
52 Cornell M. The Oxford Companion to Beer definition of bottle sizes. https://beerandbrewing.com/dictionary/yIINroTsFH/.
53 Vermote M , Versele V , Stok M , Mullie P , D’Hondt E , Deforche B , et al . The effect of a portion size intervention on French fries consumption, plate waste, satiety and compensatory caloric intake: an on-campus restaurant experiment. Nutr J. 2018;17 (1 ):43. doi: 10.1186/s12937-018-0352-z 29653580
54 Pechey R , Couturier D-L , Hollands GJ , Mantzari E , Munafò MR , Marteau TM . Does wine glass size influence sales for on-site consumption? A multiple treatment reversal design. BMC Public Health. 2016;16 (1 ):1–6. doi: 10.1186/s12889-016-3068-z 26728978
55 Reynolds JP , Ventsel M , Kosite D , Rigby Dames B , Brocklebank L , Masterton S , et al . Impact of decreasing the proportion of higher energy foods and reducing portion sizes on food purchased in worksite cafeterias: A stepped-wedge randomised controlled trial. PLoS Med. 2021;18 (9 ):e1003743. doi: 10.1371/journal.pmed.1003743 34520468
56 Clarke N , Pechey R , Pilling M , Hollands GJ , Mantzari E , Marteau TM . Wine glass size and wine sales: four replication studies in one restaurant and two bars. BMC Res Notes. 2019;12 (1 ):1–6.30602384
57 Brenes JC , Gómez G , Quesada D , Kovalskys I , Rigotti A , Cortés LY , et al . Alcohol Contribution to Total Energy Intake and Its Association with Nutritional Status and Diet Quality in Eight Latina American Countries. Int J Environ Res Public Health. 2021;18 (24 ):13130. doi: 10.3390/ijerph182413130 34948740
58 Kwok A , Dordevic AL , Paton G , Page MJ , Truby H . Effect of alcohol consumption on food energy intake: a systematic review and meta-analysis. Br J Nutr. 2019;121 (5 ):481–495. doi: 10.1017/S0007114518003677 30630543
59 Diepeveen S , Ling T , Suhrcke M , Roland M , Marteau TM . Public acceptability of government intervention to change health-related behaviours: a systematic review and narrative synthesis. BMC Public Health. 2013;13 (1 ):1–11. doi: 10.1186/1471-2458-13-756 23280303
60 Petrescu DC , Hollands GJ , Couturier DL , Ng YL , Marteau TM . Public Acceptability in the UK and USA of Nudging to Reduce Obesity: The Example of Reducing Sugar-Sweetened Beverages Consumption. PLoS ONE. 2016;11 (6 ):e0155995. doi: 10.1371/journal.pone.0155995 27276222
61 Reynolds JP , Archer S , Pilling M , Kenny M , Hollands GJ , Marteau TM . Public acceptability of nudging and taxing to reduce consumption of alcohol, tobacco, and food: A population-based survey experiment. Soc Sci Med. 2019;236 :112395. doi: 10.1016/j.socscimed.2019.112395 31326778
62 Robinson E , Kersbergen I . Portion size and later food intake: evidence on the “normalizing” effect of reducing food portion sizes. Am J Clin Nutr. 2018;107 (4 ):640–646. doi: 10.1093/ajcn/nqy013 29635503
63 Robinson E , Henderson J , Keenan GS , Kersbergen I . When a portion becomes a norm: Exposure to a smaller vs. larger portion of food affects later food intake. Food Qual Prefer. 2019;75 :113–117. doi: 10.1016/j.foodqual.2019.02.013 32226235
64 Marteau TM , Hollands GJ , Pechey R , Reynolds JP , Jebb SA . Changing the assortment of available food and drink for leaner, greener diets. BMJ. 2022;377 :e069848. doi: 10.1136/bmj-2021-069848 35418445
65 Drinkaware. Alcohol Consumption UK 2022. https://www.drinkaware.co.uk/research/alcohol-facts-and-data/alcohol-consumption-uk. 20th June 2023
66 Haynes A , Hardman CA , Makin AD , Halford JC , Jebb SA , Robinson E . Visual perceptions of portion size normality and intended food consumption: A norm range model. Food Qual Prefer. 2019;72 :77–85. doi: 10.1016/j.foodqual.2018.10.003 30828136
67 Hilton S , Wood K , Patterson C , Katikireddi SV . Implications for alcohol minimum unit pricing advocacy: what can we learn for public health from UK newsprint coverage of key claim-makers in the policy debate? Soc Sci Med. 2014;102 :157–164. doi: 10.1016/j.socscimed.2013.11.041 24565153
