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Restricción o prohibición de la publicidad del alcohol para reducir el consumo de alcohol en adultos y adolescentes

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Referencias

References to studies included in this review

Engels 2009 {published data only}

Engels RC, Hermans R, van Baaren RB, Hollenstein T, Bot SM. Alcohol portrayal on television affects actual drinking behaviour. Alcohol and alcoholism (Oxford, Oxfordshire) 2009;44(3):244‐9. [PUBMED: 19237443]

Makowksy 1991 {published data only}

Makowsky CR, Whitehead PC. Advertising and alcohol sales: a legal impact study. Journal of Studies on Alcohol 1991;52(6):555‐67.

Ogborne 1980 {published data only}

Ogborne AC, Smart RG. Will restrictions on alcohol advertising reduce alcohol consumption?. British Journal of Addiction 1980;75(3):293‐6.

Smart 1976 {published data only}

Smart RG, Cutler RE. The alcohol advertising ban in British Columbia: problems and effects on beverage consumption. British Journal of Addiction 1976;71:13‐21.

References to studies excluded from this review

Ackhoff 1975 {published data only}

Ackoff RL, Emshoff JR. Advertising research at Anheuser‐Busch, Inc. (1963‐68). Slone Management Review 1975;16:1‐15.

Calfee 1994 {published data only}

Calfee JE, Scheraga C. The influence of advertising on alcohol consumption: a literature review and an econometric analysis of four European nations. International Journal of Advertising 1994;13:287‐310.

Gallet 2007 {published data only}

Gallet CA. The demand for alcohol: a meta‐analysis of elasticities. The Australian Journal of Agricultural and Resource Economics 2007;51:121‐35.

Goldfarb 2011 {published data only}

Goldfarb A, Tucker A. Advertising bans and the substitutability of online and offline advertising. Journal of Marketing Research 2011;48:207‐27.

Loi Evin 1999 {published data only}

Mauffret M, Rousseau‐Giral A‐C, Zaidman C. The law on the fight against smoking and alcoholism: evaluation report [La loi relative a la lutte contre le tabagisme et l'alcoolisme]. Premier Minister Commissariat general du Plan1999.

Midford 2010 {published data only}

Midford R, Young, D, Chikritzhs T, Playford D, Kite E, Pascal R. The effect of alcohol sales and advertising restrictions on a remote Australian community. Drugs: Education, Prevention & Policy 2010;17(1):21‐41.

Nelson 2001 {published data only}

Nelson JP Young DJ. Do advertising bans work? An international comparison. Applied Economics 2001;20(3):273‐96.

Nelson 2003 {published data only (unpublished sought but not used)}

Nelson JP. Advertising bans, monopoly, and alcohol demand: testing for substitution effects using panel data. Review of Industrial Organization June 2003;22(1):1‐25.

Nelson 2010 {published and unpublished data}

Nelson JP. Alcohol advertising bans, consumption and control policies in seventeen OECD countries, 1975‐2000. Applied Economics 2010;42:803‐23.
Nelson JP. Alcohol advertising bans, consumption, and control policies in seventeen OECD countries, 1975‐2000 (posted 7 November 2006). http://ssrn.com/abstract=942647 (accessed 7 November 2006).

Saffer 1991 {published data only}

Saffer H. Alcohol advertising bans and alcohol abuse: an international perspective. Journal of Health Economics 1991;10:65‐79.

Saffer 2002 {unpublished data only}

Saffer H. Alcohol consumption and alcohol advertising bans. Applied Economics 2002;34(11):1325‐34.

Young 1993 {published data only}

Saffer H. Alcohol advertising bans and alcohol abuse: Reply. Journal of Health Economics 1993;12:229‐34.
Young DJ. Alcohol advertising bans and alcohol abuse: comment. Journal of Health Economics 1993;12:213‐28.

Additional references

Alcohol and Public Policy Group

Alcohol and Public Policy Group. Alcohol: no ordinary commodity ‐ a summary of the second edition. Addiction 2010;105(5):769‐79.

Anderson 2009

Anderson P, Chisholm D, Fuhr DC. Effectiveness and cost‐effectiveness of policies and programmes to reduce the harm caused by alcohol. The Lancet 2009;373(9682):2234‐46. [PUBMED: 19560605]

Anderson 2009a

Anderson P, de Bruijn A, Angus K, Gordon R, Hastings G. Impact of alcohol advertising and media exposure on adolescent alcohol use: a systematic review of longitudinal studies. Alcohol and Alcoholism 2009;44(3):229‐43. [PUBMED: 19144976]

Aspara 2013

Aspara J, Tikkanen H. A methodological critique of alcohol and addiction researchers’ studies on the effect of advertising on adolescent alcohol. http://dx.doi.org/10.2139/ssrn.2205112 (accessed 14 October 2014).

Baumberg 2006

Baumberg B. The global economic burden of alcohol: a review and some suggestions. Drug and Alcohol Review 2006;25(6):537‐51. [PUBMED: 17132572]

Bland 1997

Bland JM, Kerry SM. Trials randomised in clusters. BMJ 1997;315:600.

Booth 2008

Booth A, Meier P, Stockwell T, Sutton A, Wilkinson A, Wong R, et al. Independent review of the effects of alcohol pricing and promotion: systematic reviews. School of Health and Related Research. University of Sheffield, UK.2008.

Burd 2012

Burd L, Blair J, Dropps K. Prenatal alcohol exposure, blood alcohol concentrations and alcohol elimination rates for the mother, fetus and newborn. Journal of Perinatology 2012;32(9):652‐9. [PUBMED: 22595965]

Casswell 2012

Casswell S, Meier P, MacKintosh AM, Brown A, Hastings G, Thamarangsi T, et al. The International Alcohol Control (IAC) study‐evaluating the impact of alcohol policies. Alcoholism, Clinical, and Experimental Research 2012;36(8):1462‐7.

Divine 1992

Divine GW, Brown JT, Frazer LM. The unit analysis error in studies about physicians' patient care behavior. Journal of General Internal Medicine 1992;7:623‐9.

Doran 2010

Doran CM, Hall WD, Shakeshaft AP, Vos T, Cobiac LJ. Alcohol policy reform in Australia: what can we learn from the evidence?. Medical Journal of Australia 2010;192:468‐70.

EPOC 2008

Cochrane Effective Practice and Organization of Care Group (EPOC). http://epoc.cochrane.org/sites/epoc.cochrane.org/files/uploads/14%20Suggested%20risk%20of%20bias%20criteria%20for%20EPOC%20reviews%202013%2008%2012_0.pdf (Accessed 14 October 2014).

Gallet 2011

Gallet CA, Andres AR. International evidence on the determinants of alcohol advertising restrictions. Applied Economics Letters 2011;18:1359‐62.

Guyatt 2011

Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, et al. GRADE guidelines: 1. Introduction‐GRADE evidence profiles and summary of findings tables. Journal of Clinical Epidemiology 2011;64(4):383‐94. [PUBMED: 21195583]

Hastings 2010

Hastings G, Brooks O, Stead M, Angus K, Anker T, Farrell T. Failure of self‐regulation of UK alcohol advertising. BMJ 2010;340:http://dx.doi.org/10.1136/bmj.b5650.

Hastings 2013

Hastings G, Sheron N. Alcohol marketing: grooming the next generation: children are more exposed than adults and need much stronger protection. BMJ 2013;346:f1227. [PUBMED: 23449659]

Higgins 2002

Higgins JP, Thompson SG. Quantifying heterogeneity in a meta‐analysis. Statistics in Medicine 2002;21(11):1539‐58.

Higgins 2011

Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. Available from www.cochrane‐handbook.org.

Lim 2012

Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair‐Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990‐2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet 2012;380:2224‐60.

Newcastle‐Ottawa

Wells GA, Shea B, O'Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle‐Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta‐analyses. www.ohri.ca/programs/clinical_epidemiology/oxford.htm (accessed 7 October 2014).

Nutt 2010

Nutt DJ, King LA, Phillips LD. Drug harms in the UK: a multicriteria decision analysis. The Lancet 2010;376(9752):1558‐65. [PUBMED: 21036393]

Pinsky 2010

Pinsky I, El Jundi SAJR, Sanches M, Zaleski MB, Lalanjeira RR, Caetano R. Exposure of adolescents and young adults to alcohol advertising in Brazil. Journal of Public Affairs 2010;10:50‐8.

Rehm 2009

Rehm J, Mathers C, Popova S, Thavorncharoensap M, Teerawattananon Y, Patra J. Global burden of disease and injury and economic cost attributable to alcohol use and alcohol‐use disorders. The Lancet 2009;373(9682):2223‐33. [PUBMED: 19560604]

Rehm 2010

Rehm J, Baliunas D, Borges GL, Graham K, Irving H, Kehoe T, et al. The relation between different dimensions of alcohol consumption and burden of disease: an overview. Addiction 2010;105(5):817‐43. [PUBMED: 20331573]

RevMan 2012 [Computer program]

The Nordic Cochrane Centre, The Cochrane Collaboration. Review Manager (RevMan). Version 5.2. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2012.

Smart 1988

Smart R. Does alcohol advertising affect overall consumption? A review of empirical studies. Journal of Studies on Alcohol 1988;49(4):314‐323.

Smith 2009

Smith LA, Foxcroft DR. The effect of alcohol advertising, marketing and portrayal on drinking behaviour in young people: systematic review of prospective cohort studies. BMC Public Health 2009;9:51. [PUBMED: 19200352]

Snyder 2006

Snyder LB, Milici FF, Slater M, Sun H, Strizhakova Y. Effects of alcohol advertising exposure on drinking among youth. Archives of Pediatrics & Adolescent Medicine 2006;160:18‐24.

Stockwell 1999

Stockwell CS, Donath T, Cooper‐Stanbury S, Chikritzhs M, Catalano P, Mateo C. Under‐reporting of alcohol consumption in household surveys: a comparison of quantity–frequency, graduated–frequency and recent recall. Addiction 1999;8:1024‐33.

WHO 2010

World Health Organization. Global strategy to reduce the harmful use of alcohol. www.who.int/substance_abuse/msbalcstragegy.pdf. Geneva, Switzerland: WHO, 2010 (accessed 7 October 2013).

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Engels 2009

Methods

STUDY TYPE:

  • Randomised controlled trial

COUNTRY:

  • Netherlands

SETTING:

  • Radboud University Nijmegen campus in a bar laboratory equipped as a relaxing room with a comfortable couch and a big screen television. Ashtray, nuts and chips were provided and a refrigerator was stocked with soft‐alcoholic drinks (beer and wine) and soft drinks

DURATION OF RECRUITMENT:

  • Not reported

DURATION OF TRIAL:

  • Not reported. The intervention took 1.5 hours

FOLLOW UP:

  • Not applicable as the outcomes were measured during the intervention process

  • A questionnaire was conducted with participants on completion of the intervention

Participants

INCLUSION CRITERIA:

  • Males aged 18 to 29 years

  • Each male was invited to attend with a male friend so the units of analysis was at the pair level

EXCLUSION CRITERIA:

  • Not explicitly reported

Number of participants randomised: 80 in 40 pairs, each pair randomised to one of four exposure groups (20 participants in each group)

Baseline data:

  • No numeric data reported according to group allocation

  • Mean age was 21.45 years with a SD 2.1

  • There were reported differences in weekly drinking between allocated groups: previous week’s alcohol consumption was higher in the Alcohol Movie/Alcohol Commercial (AM/AC) group than in the Non‐alcohol Movie/Non‐alcohol Commercial (NM/NC) group (mean 31.2 drinks, SD 17.1 versus mean 17.8 drinks, SD 11.7; t(38) = 2.9; p value < 0.01)

Interventions

Three discrete interventions and one control group were provided.

Prior to the interventions, all participant pairs were told that they would see a movie clip interrupted by two commercial breaks and to act like they were relaxing at home. Free drinks were available in the refrigerator, nuts and chips were offered and smoking was allowed. Taxi fare was provided for men who drank three or more bottles of wine or beer and all participants received nine euros for their participation

INTERVENTION AM/AC (20 participants):

  • Alcohol movie with alcohol commercials

    • Each pair watched a 1 hour movie clip from 'American Pie 2' ‐ a comedy containing strong sexual content and nudity, and crude humour and drinking content (characters drank alcohol 18 times and alcoholic beverages were portrayed an additional 23 times)

    • After 14 and 33 minutes, the movie clip was interrupted with a commercial break for 3.5 minutes for neutral content (cars or a video camera) and alcohol content

INTERVENTION Alcohol Movie/Neutral Commercial (AM/NC) (20 participants):

  • Alcohol movie with neutral commercials

    • Each pair watched a 1 hour movie clip from 'American Pie 2' (as above)

    • After 14 and 33 minutes, the movie clip was interrupted with a commercial break for 3.5 minutes for neutral content (cars or a video camera) only

INTERVENTION Neutral Movie/Alcohol Commercial (NM/AC) (20 participants):

  • Non‐alcoholic movie with alcohol commercials

    • Each pair watched a 1 hour movie clip from '40 days and 40 nights' ‐ a comedy containing strong sexual content and nudity and limited drinking content (characters drank alcohol 3 times and alcoholic beverages were portrayed an additional 15 times)

    • After 14 and 33 minutes, the movie clip was interrupted with a commercial break for 3.5 minutes for neutral content (cars or a video camera) and alcohol content

CONTROL NM/NC (20 participants):

  • Non‐alcoholic movie with neutral commercials

    • Each pair watched a 1 hour movie clip from '40 days and 40 nights' (as above)

    • After 14 and 33 minutes, the movie clip was interrupted with a commercial break for 3.5 minutes for neutral content (cars or a video camera) only

The commercials were selected to be similar in terms of number, length and diversity of the presented products

Outcomes

The outcomes were not clearly reported as primary or secondary.

OUTCOMES:

  • Alcohol consumption:

    • Observed number of drinks consumed in the 1 hour movie session. Bottles of beer contained 200 mL; bottles of wine contained 250 mL. To assess the total amount of alcohol consumed, the counted number of bottles of wine consumed was multiplied by 1.6, to attain an outcome relating to the amount of alcohol in one bottle of beer

    • Self‐reported number of drinks drunk during a typical 1 hour television viewing (via questionnaire)

    • Self‐reported frequency of drinking

    • Self‐reported incidence of drunkenness in past 12 months

  • Appreciation of the movie: nine question 5‐point rating scale

Notes

ETHICS:

The local ethics committee approved the laboratory protocols

INFORMED CONSENT:

This is unlikely as the article states that none of the participants guessed the real aim of the study indicating that this was withheld from them. Participants provided written permission to be video and audio recorded and to allow the footage to be used afterwards

FUNDING:

The lead author was funded by a fellowship of the Netherlands Organisation for Scientific Research. Funding for the study was received from The Netherlands Organisation for Scientific Research and a private organisation called STAP, an organisation against alcohol misuse and its consequences. The report states that both organisations were not involved in the development of design, collection of the data, writing the paper or decision to submit the paper for publication

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

The method of generating the sequence is not reported. The article states that men who were in the group allocated to watch movies with a high alcohol content reported higher rates of drinking in the week prior to the study indicating randomisation was not successful

Allocation concealment (selection bias)

Unclear risk

Not reported

Was knowledge of the allocated interventions adequately prevented during the study

High risk

The research staff were aware of the allocated groups. Participants were aware of the content they were watching but were unaware whether they were in an intervention or control group

Were incomplete outcome data adequately addressed

Low risk

All participants completed the trial and outcomes were available for all 80 participants

Was the study free from selective outcome reporting bias

Low risk

The trial was not registered on a trial database but results were reported for all outcomes identified in the methods section of the paper

Was the intervention unlikely to affect data collection (ITS)

Low risk

Not applicable to RCT

Was the intervention independent of other changes (ITS)

Low risk

Not applicable to RCT

Was the shape of the intervention effect pre‐specified (ITS)

Low risk

Not applicable to RCT

Was the study free from other risks of bias

Low risk

There is no indication of other bias

Makowksy 1991

Methods

STUDY TYPE:

  • Interrupted Time Series

COUNTRY:

  • Canada

SETTING:

  • Provinces of Saskatchewan and New Brunswick

DURATION OF STUDY PERIOD:

  • 1 April 1981 to 31 March 1987

ANALYSIS TYPE:

Reported as time series analysis using the methods of Box and Jenkins (1970). Auto‐regressive, integrated moving average (ARIMA) models were used

Participants

Adult population 15 years and older purchasing alcohol

Interventions

INTERVENTION:

Type:

  • Total ban on beer, wine and spirits advertising (the report describes the ban as partial as advertising from other media originating from outside the province (e.g. cable television), was not possible to ban; for the purposes of this review, the ban is considered total within the province)

Media:

  • Radio (beer, wine, spirits)

  • Television (beer, wine, spirits)

  • Newspapers and magazines (beer, wine and spirits)

Duration of intervention:

  • 1 April 1981 to 3 October 1983

  • The ban had been in effect for 58 years prior to being lifted in October 1983. The intervention period includes the final two years of the ban period, i.e. 1981 to 1983.

CONTROL:

Type:

  • Partial ban for spirits only (the ban on advertising for spirits continued to be applied, with the exception ofthe print media where spirits could be advertised)

Media:

  • Radio (spirits)

  • Television (spirits)

Duration of control:

  • Post‐ban after lifting of the ban in October 1983 until 31 March 1987

COMPARISON:

The consumption rates were compared to those in the province of New Brunswick where a similar ban had been in place and was not lifted during the same period

Outcomes

PRIMARY OUTCOME:

  • Per capita consumption:

    • The initial unit of measure was monthly sales data for alcohol beverages across the province. Sales data were derived from monthly reports of the Saskatchewan and New Brunswick Liquor Commissions that were sent to Statistics Canada. Total volume of sales was measured in terms of sales of absolute alcohol per litres for the population 15 years and older. Volumes of absolute alcohol were derived from the relative alcohol content using the following percentages per alcohol type:

      • Spirits: 39%

      • Wine: 10%

      • Beer: 5%

SECONDARY OUTCOMES:

  • None reported

Notes

ETHICS:

Not applicable as nationally aggregated data.

FUNDING:

Not clearly reported; study undertaken by employees of Health Services and Promotion branch of the Health and Welfare Canada

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Not a RCT

Allocation concealment (selection bias)

High risk

Not a RCT

Was knowledge of the allocated interventions adequately prevented during the study

Low risk

The outcome of monthly alcohol sales was objectively measured by routine data collection and was thus unlikely to have been influenced by knowledge of the intervention

Were incomplete outcome data adequately addressed

Low risk

There is no report of missing data as each month is accounted for. The methodology that the liquor commissions used to collect data was not reported

Was the study free from selective outcome reporting bias

Low risk

There is no indication that other outcomes would be of interest

Was the intervention unlikely to affect data collection (ITS)

Low risk

The data were collected from routine source before and after the lifting of the ban

Was the intervention independent of other changes (ITS)

Unclear risk

No report of historical or political reasons underpinning decision to lift the ban

Was the shape of the intervention effect pre‐specified (ITS)

Low risk

Yes, the lifting of the ban was predicted to increase sales of alcohol

Was the study free from other risks of bias

High risk

There is an acknowledged possibility that advertising from other provinces and countries would not have been stopped by the ban, causing a dilution effect. Seasonality may have affected results and this is addressed in the analysis

Ogborne 1980

Methods

STUDY TYPE:

  • Interrupted Time Series

COUNTRY:

  • Canada

SETTING:

  • Province of Manitoba

DURATION OF STUDY PERIOD:

  • January 1970 to January 1978

ANALYSIS TYPE:

Reported as time series analysis using the methods of Glass, Wilson and Gottman. t test values reported

Participants

Defined as adult population purchasing alcohol

Interventions

INTERVENTION:

Type:

  • Partial ban on beer advertising

Media:

  • Print

  • Electronic

Duration of intervention:

  • 1974 to 1978

CONTROL:

Type:

  • No ban

Duration of control:

  • Pre‐ban before 1974

COMPARISON:

The beer consumption rates were compared to those in the province of Alberta where no ban had been in place during the same period

Outcomes

PRIMARY OUTCOME:

  • Per capita alcohol consumption:

    • Monthly beer sales were obtained from the Brewers' Association of Canada and sales data for alcohol beverages from Statistics Canada for British Columbia and Ontario. Per capita consumption was calculated for each month by dividing the monthly sales figures by the year's estimate of the size of the provincial adult population (over 15 years of age) published by Statistics Canada

SECONDARY OUTCOMES:

  • None reported

Notes

ETHICS:

Not applicable as nationally aggregated data

FUNDING:

Conducted by the Addiction Research Foundation, Canada, and assumed to be the funding source

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Not a RCT

Allocation concealment (selection bias)

High risk

Not a RCT

Was knowledge of the allocated interventions adequately prevented during the study

Low risk

The outcome of consumption was objectively measured by routine data collection and was thus unlikely to have been influenced by knowledge of the intervention

Were incomplete outcome data adequately addressed

Low risk

There is no report of missing data as each month is accounted for

Was the study free from selective outcome reporting bias

Low risk

There is no indication that other outcomes would be of interest

Was the intervention unlikely to affect data collection (ITS)

Low risk

The data were collected from routine source before and after the ban

Was the intervention independent of other changes (ITS)

Unclear risk

No report of historical or political reasons underpinning decision to implement ban

Was the shape of the intervention effect pre‐specified (ITS)

Low risk

It was predicted that beer sales would decrease

Was the study free from other risks of bias

High risk

Seasonality was not addressed although the analysis may have adjusted for this but no details are given. Broadcast and printed media originating outside the province were not subject to regulation or control by the Manitoba Provincial Liquor Commission

Smart 1976

Methods

STUDY TYPE:

  • Interrupted Time Series

COUNTRY:

  • Canada

SETTING:

  • Provinces of British Columbia and Ontario

DURATION OF STUDY PERIOD:

  • 1962 to 1972

ANALYSIS:

Simple mean comparisons using t test on de‐trended data

Participants

Adult population purchasing alcohol

Interventions

INTERVENTION:

Type:

  • Complete ban on alcohol (beer, wine and spirits) and tobacco advertising

Media:

  • Newspaper

  • Radio

  • Television

  • Billboards

  • Notice‐boards

Duration of intervention:

  • 1 September 1971 to 31 October 1972

CONTROL:

Type:

  • No ban

Duration of control:

  • Pre‐ban before 1 September 1971

    • Variable depending on data type (monthly or yearly) and type of alcohol

    • Monthly data:

      • Beer: 1968 to 1 September 1971

      • Wine: 1968 to 1 September 1971

      • Spirits: October 1970 to 1 September 1971

  • Post‐ban after 31 October 1972

    • Variable depending on data type (monthly or yearly) and type of alcohol

    • Monthly data:

      • Beer: 31 October 1972 to August 1972 (note no monthly data for post‐ban period)

      • Wine: 31 October 1972 to 1974

      • Spirits: 31 October 1972 to December 1973

COMPARISON:

The consumption rates were compared to those in the province of Ontario where no ban had been in place during the same period

Outcomes

PRIMARY OUTCOME:

  • Per capita alcohol consumption:

    • Measured by sales data for alcohol beverages from Statistics Canada for British Columbia and Ontario. Using population estimates from the dicennial censuses (1961 to 1971) per capita consumption estimates were made for beer, wine and spirits

SECONDARY OUTCOMES:

  • None reported

Notes

ETHICS:

Not applicable as nationally aggregated data.

FUNDING:

Addiction Research Foundation, Canada and Alcoholism Foundation of British Columbia

Risk of bias

Bias

Authors' judgement

Support for judgement

Random sequence generation (selection bias)

High risk

Not a RCT

Allocation concealment (selection bias)

High risk

Not a RCT

Was knowledge of the allocated interventions adequately prevented during the study

Low risk

The outcome of consumption was objectively measured by routine data collection and was thus unlikely to have been influenced by knowledge of the intervention

Were incomplete outcome data adequately addressed

Unclear risk

Data were not available for all alcohol types across all the same periods. The author states that he was unable to obtain the data despite requests

Was the study free from selective outcome reporting bias

Low risk

There is no indication that other outcomes would be of interest

Was the intervention unlikely to affect data collection (ITS)

Low risk

The data were collected from routine sources before and after the ban

Was the intervention independent of other changes (ITS)

High risk

The ban was initiated by a unanimous political vote, but the ban was stopped after elections when there was a change in political power. There is a likelihood that other political or social changes may have coincided with the period of the ban

Was the shape of the intervention effect pre‐specified (ITS)

Low risk

An increase in consumption was predicted after the ban was removed. This was tested and the point was dated

Was the study free from other risks of bias

High risk

There is an acknowledged possibility that advertising from other states would not have been stopped by the ban, causing a dilution effect. Seasonality may have affected results and this is addressed in the analysis. Mediators of alcohol use, other than advertising, are not discussed

RCT: randomised controlled trial

SD: standard deviation

Characteristics of excluded studies [ordered by study ID]

Study

Reason for exclusion

Ackhoff 1975

This marketing study performed several interrupted time series of restrictions of advertising on beer sales within Anheuser‐Busch Inc. (the company that manufacturer BUDWEISER beer) between 1963 and 1968. No numerical data were presented in the report, only graphical representation of the stimuli‐response curve and we were therefore unable to extract useful data

Calfee 1994

This econometric analysis of four European nations (France, Germany, Netherlands, UK) evaluated the effects of advertising using two different models between years spanning 1968 to 1991. Bans were not in place in these countries. The authors also consider Sweden in the years 1970 to 1989 with a ban implemented in 1979. The data are not presented but the authors report that the results did not differ between the dataset spanning the period 1970 to 1989 compared with the period after the ban (1979 to 1989). The actual data are not presented and we could not therefore extract them

Gallet 2007

This is a meta‐regression of elasticities of alcohol demand in 132 studies. The specific intervention time point was not possible to identify for the individual studies from the aggregated data

Goldfarb 2011

This US‐based study used data from a large database of surveys collected by a media metrics agency to measure the effectiveness of 275 different online alcohol advertising campaigns between 2001 and 2008. 61,580 consumers browsing the website on which a campaign ran were either exposed to an advertisement for alcohol or a dummy advertisement for a neutral product, based on a randomised numerical algorithm placed on the advertisement server. Both exposed and not exposed (control) respondents were then recruited using an online survey invitation typically issued by a pop‐up window. Respondents were asked whether they were likely or not likely to purchase a variety of products including the alcohol product advertised. These results were then evaluated against the background advertising restrictions of the relevant state. The study reported that results show that people are 8% less likely to say that they will purchase an alcoholic beverage in states that have alcohol advertising bans compared with states that do not. For consumers exposed to online advertising, this gap narrows to 3%. We excluded this study as the outcome measured intent to purchase and not sales and consumption data

Loi Evin 1999

This French government report of 1999 details the consumption of alcohol in France before, during and after the introduction of the Loi Evin (ban on alcohol and smoking advertising) implemented in 1991. The law curtails alcohol advertising on television and in cinemas, and disallows sport sponsorship. Data are not presented in a manner which allowed us to extract them and are in the form of reporting of cross‐sectional surveys. Only annual percentages of consumption are presented as reported in different surveys. No methodology, variance or significance levels were provided. The report states that in France alcohol consumption was declining prior to the introduction of the banning law and that internal surveys have produced contradictory results. The report notes that the proportion of alcohol consumers aged 12 to 18 years had a tendency to decline in the 1980s, but then increased significantly between 1991 and 1995, from 47% in 1991 to 65% in 1995

Midford 2010

This pre‐post controlled study was conducted in an Australian community with a recognised substantial alcohol problem. Restriction of promotion or advertising of full strength beer, spirits mixers or 2 litre casks of wine was introduced simultaneously with restrictions on hours of sales of alcohol and container types for selling alcohol. The intervention was thus complex and the effects could not be disaggregated to restrictions on advertising only

Nelson 2001

This study conducted regression analyses on cross‐country panel data from seventeen OECD countries for the period 1977 to 1995. Within the aggregated data, there was no indication of a specific point in time where the restrictions were implemented within individual countries. The country‐specific data were not available from the author for further analysis

Nelson 2003

This study analysed panel data from 45 US states for the period 1982 to 1997. Within the aggregated data, there was no indication of a specific point in time where the restrictions were implemented within states. The state‐specific data were not available from the author for further analysis

Nelson 2010

This study conducted regression analyses of cross‐country panel data from seventeen OECD countries for the period 1975 to 2000. It is an update of the Nelson 2001 study. Within the aggregated data, there was no indication of a specific point in time where the restrictions were implemented within individual countries. The country‐specific data were not available from the author for further analysis

Saffer 1991

This is a pooled time series from 17 OECD countries for the period 1970 to 1983. Within the aggregated data, there was no indication of a specific point in time where the restrictions were implemented within individual countries. The country‐specific data were not available from the author for further analysis

Saffer 2002

This economic analysis evaluates a pooled time series of data from 20 OECD countries for the period from 1970 to 1995. It is an update of the earlier analysis by Saffer 1991. Within the aggregated data, there was no indication of a specific point in time where the restrictions were implemented within individual countries. The country‐specific data were not available from the author for further analysis

Young 1993

This analysis re‐examines the same dataset from Saffer 1991 evaluating 17 OECD countries from 1970 to 1983 and employs a different analysis and set of assumptions. An additional reference, Saffer 1993, offers a response to this analysis. Within the aggregated data, there was no indication of a specific point in time where the restrictions were implemented within individual countries

OECD: Organization for Economic and Cooperation Development

Data and analyses

Open in table viewer
Comparison 1. Low‐alcohol content movies versus high‐alcohol content movies

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption in number of glasses Show forest plot

1

80

Mean Difference (IV, Fixed, 95% CI)

‐0.65 [‐1.23, ‐0.07]

Analysis 1.1

Comparison 1 Low‐alcohol content movies versus high‐alcohol content movies, Outcome 1 Total alcohol consumption in number of glasses.

Comparison 1 Low‐alcohol content movies versus high‐alcohol content movies, Outcome 1 Total alcohol consumption in number of glasses.

Open in table viewer
Comparison 2. Non‐alcohol commercials versus alcohol commercials

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption in number of glasses Show forest plot

1

80

Mean Difference (IV, Fixed, 95% CI)

‐0.73 [‐1.30, ‐0.16]

Analysis 2.1

Comparison 2 Non‐alcohol commercials versus alcohol commercials, Outcome 1 Total alcohol consumption in number of glasses.

Comparison 2 Non‐alcohol commercials versus alcohol commercials, Outcome 1 Total alcohol consumption in number of glasses.

Open in table viewer
Comparison 3. High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption Show forest plot

1

Coefficient (Fixed, 95% CI)

0.74 [0.05, 1.43]

Analysis 3.1

Comparison 3 High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects, Outcome 1 Total alcohol consumption.

Comparison 3 High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects, Outcome 1 Total alcohol consumption.

Open in table viewer
Comparison 4. Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption Show forest plot

1

Coefficient (Fixed, 95% CI)

0.83 [0.14, 1.52]

Analysis 4.1

Comparison 4 Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects, Outcome 1 Total alcohol consumption.

Comparison 4 Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects, Outcome 1 Total alcohol consumption.

Open in table viewer
Comparison 5. Total advertising ban versus Partial advertising ban Abrupt permanent model

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Volume of alcohol (beer, wine and spirits) sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐11.11 [‐27.56, 5.34]

Analysis 5.1

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.

2 Volume of beer sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

14.89 [0.39, 29.39]

Analysis 5.2

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 2 Volume of beer sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 2 Volume of beer sales in kilolitres.

3 Volume of wine sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

1.15 [‐0.91, 3.21]

Analysis 5.3

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 3 Volume of wine sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 3 Volume of wine sales in kilolitres.

4 Volume of spirits sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐22.49 [‐36.83, ‐8.15]

Analysis 5.4

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 4 Volume of spirits sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 4 Volume of spirits sales in kilolitres.

Open in table viewer
Comparison 6. Total advertising ban versus Partial advertising ban Gradual permanent model

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Volume of alcohol (beer, wine and spirits) sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐11.96 [‐55.42, 31.50]

Analysis 6.1

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.

2 Volume of beer sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐0.54 [‐1.57, 0.49]

Analysis 6.2

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 2 Volume of beer sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 2 Volume of beer sales in kilolitres.

3 Volume of wine sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐0.00 [‐0.04, 0.04]

Analysis 6.3

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 3 Volume of wine sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 3 Volume of wine sales in kilolitres.

4 Volume of spirits sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐27.8 [‐59.34, 3.74]

Analysis 6.4

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 4 Volume of spirits sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 4 Volume of spirits sales in kilolitres.

Open in table viewer
Comparison 7. Alcohol ban versus no ban

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 % Change in beer consumption Show forest plot

2

Mean % change (Random, 95% CI)

1.10 [‐5.26, 7.47]

Analysis 7.1

Comparison 7 Alcohol ban versus no ban, Outcome 1 % Change in beer consumption.

Comparison 7 Alcohol ban versus no ban, Outcome 1 % Change in beer consumption.

Flow diagram of screening and eligibility of records of electronic databases: PubMed, EMBASE, The Cochrane Library (CENTRAL and UK National Health Service Economic Evaluations Database) and PsychINFO
Figuras y tablas -
Figure 1

Flow diagram of screening and eligibility of records of electronic databases: PubMed, EMBASE, The Cochrane Library (CENTRAL and UK National Health Service Economic Evaluations Database) and PsychINFO

'Risk of bias' graph: review authors' judgements about each risk of bias item presented as percentages across all included studies (N = 4).
Figuras y tablas -
Figure 2

'Risk of bias' graph: review authors' judgements about each risk of bias item presented as percentages across all included studies (N = 4).

'Risk of bias' summary: review authors' judgements about each risk of bias item for each included study (N = 4).
Figuras y tablas -
Figure 3

'Risk of bias' summary: review authors' judgements about each risk of bias item for each included study (N = 4).

Comparison 1 Low‐alcohol content movies versus high‐alcohol content movies, Outcome 1 Total alcohol consumption in number of glasses.
Figuras y tablas -
Analysis 1.1

Comparison 1 Low‐alcohol content movies versus high‐alcohol content movies, Outcome 1 Total alcohol consumption in number of glasses.

Comparison 2 Non‐alcohol commercials versus alcohol commercials, Outcome 1 Total alcohol consumption in number of glasses.
Figuras y tablas -
Analysis 2.1

Comparison 2 Non‐alcohol commercials versus alcohol commercials, Outcome 1 Total alcohol consumption in number of glasses.

Comparison 3 High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects, Outcome 1 Total alcohol consumption.
Figuras y tablas -
Analysis 3.1

Comparison 3 High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects, Outcome 1 Total alcohol consumption.

Comparison 4 Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects, Outcome 1 Total alcohol consumption.
Figuras y tablas -
Analysis 4.1

Comparison 4 Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects, Outcome 1 Total alcohol consumption.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.
Figuras y tablas -
Analysis 5.1

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 2 Volume of beer sales in kilolitres.
Figuras y tablas -
Analysis 5.2

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 2 Volume of beer sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 3 Volume of wine sales in kilolitres.
Figuras y tablas -
Analysis 5.3

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 3 Volume of wine sales in kilolitres.

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 4 Volume of spirits sales in kilolitres.
Figuras y tablas -
Analysis 5.4

Comparison 5 Total advertising ban versus Partial advertising ban Abrupt permanent model, Outcome 4 Volume of spirits sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.
Figuras y tablas -
Analysis 6.1

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 1 Volume of alcohol (beer, wine and spirits) sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 2 Volume of beer sales in kilolitres.
Figuras y tablas -
Analysis 6.2

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 2 Volume of beer sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 3 Volume of wine sales in kilolitres.
Figuras y tablas -
Analysis 6.3

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 3 Volume of wine sales in kilolitres.

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 4 Volume of spirits sales in kilolitres.
Figuras y tablas -
Analysis 6.4

Comparison 6 Total advertising ban versus Partial advertising ban Gradual permanent model, Outcome 4 Volume of spirits sales in kilolitres.

Comparison 7 Alcohol ban versus no ban, Outcome 1 % Change in beer consumption.
Figuras y tablas -
Analysis 7.1

Comparison 7 Alcohol ban versus no ban, Outcome 1 % Change in beer consumption.

Summary of findings for the main comparison. Non‐alcohol commercials compared to alcohol commercials for reduction of alcohol consumption

Non‐alcohol commercials compared to alcohol commercials for reduction of alcohol consumption

Patient or population: General population
Settings: General population
Intervention: Non‐alcohol commercials
Comparison: Alcohol commercials

Outcomes

Illustrative comparative risks* (95% CI)

Relative effect
(95% CI)

No. of participants
(studies)

Quality of the evidence
(GRADE)

Comments

Assumed risk

Corresponding risk

Alcohol commercials

Non‐alcohol commercials

Total alcohol consumption in number of glasses
Follow up: mean 1.5 hours

The mean total alcohol consumption in number of glasses in the intervention groups was
0.73 less
(1.3 to 0.16 less)

80
(1 study)

⊕⊝⊝⊝
very low1,2,3

Delayed age of initiation of alcohol use ‐ not measured

Not estimable

This outcome was not applicable in this trial

Reduction in rate of reported risk behaviour ‐ not measured

Not estimable

Reduction in alcohol‐related injuries or accidents ‐ not measured

Not estimable

Reduction in individual spending on alcohol ‐ not measured

Not estimable

Loss of revenue from alcohol industry ‐ not measured

Not estimable

This outcome was not applicable in this trial

Loss of advertising revenue ‐ not measured

Not estimable

This outcome was not applicable in this trial

*The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI).
CI: Confidence interval;

GRADE Working Group grades of evidence
High quality: Further research is very unlikely to change our confidence in the estimate of effect.
Moderate quality: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.
Low quality: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.
Very low quality: We are very uncertain about the estimate.

1 Risk of bias: rated as serious. In the Engels 2009 trial, randomisation was inadequate (the groups differed on the baseline prognostic factor prior drinking levels), allocation concealment was unclear and the researchers were not blinded to group allocation so detection bias may be present.
2 Indirectness: rated as serious. The trial is specific to young men from a university setting in a high‐income country and may not be generalisable to other settings.
3 Imprecision: rated as serious: The 95% CI is wide and the sample size small.

Figuras y tablas -
Summary of findings for the main comparison. Non‐alcohol commercials compared to alcohol commercials for reduction of alcohol consumption
Summary of findings 2. Alcohol ban compared to no ban for the general population

Alcohol ban compared to no ban for the general population

Patient or population: General population
Settings: General population
Intervention: Alcohol ban
Comparison: No ban

Outcomes

Illustrative comparative risks* (95% CI)

Relative effect
(95% CI)

No. of pParticipants
(studies)

Quality of the evidence
(GRADE)

Comments

Assumed risk

Corresponding risk

No ban

Alcohol ban

Alcohol consumption: % change in beer consumption
Follow up: 1.2 to 3 years

The mean % change in beer consumption in the intervention groups was
1.1 more
(5.26 less to 7.47 more)

2 ITS studies

⊕⊝⊝⊝
very low1,2

Results for consumption of other types of alcoholic beverages and total consumption were inconsistent in the three ITS studies

Reduction in rate of reported risk behaviour ‐ not reported

See comment

See comment

Not estimable

See comment

None of the studies measured this outcome

Delayed age of initiation of alcohol use ‐ not reported

See comment

See comment

Not estimable

See comment

None of the studies measured this outcome

Reduction in alcohol‐related injuries or accidents ‐ not reported

See comment

See comment

Not estimable

See comment

None of the studies measured this outcome

Reduction in individual spending on alcohol ‐ not reported

See comment

See comment

Not estimable

See comment

None of the studies measured this outcome

Loss of revenue from alcohol industry ‐ not reported

See comment

See comment

Not estimable

See comment

None of the studies measured this outcome

Loss of advertising revenue ‐ not reported

See comment

See comment

Not estimable

See comment

None of the studies measured this outcome

*The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI).
CI: Confidence interval; ITS: interrupted time series

GRADE Working Group grades of evidence
High quality: Further research is very unlikely to change our confidence in the estimate of effect.
Moderate quality: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.
Low quality: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.
Very low quality: We are very uncertain about the estimate.

1 Risk of bias: rated as serious: the risk of a dilution effect is present in both studies (Ogborne 1980 and Smart 1976) and seasonality may not be adequately addressed in the analyses. The studies were not further downgraded for limitations in causal inference due to a lack of randomisation, as the initial GRADE rating commenced at low quality.
2 Inconsistency: rated as serious. The results from the Smart 1976 study indicate a reduction in beer consumption after implementing a ban on advertising and Ogborne 1980 shows an increase in beer consumption.

Figuras y tablas -
Summary of findings 2. Alcohol ban compared to no ban for the general population
Comparison 1. Low‐alcohol content movies versus high‐alcohol content movies

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption in number of glasses Show forest plot

1

80

Mean Difference (IV, Fixed, 95% CI)

‐0.65 [‐1.23, ‐0.07]

Figuras y tablas -
Comparison 1. Low‐alcohol content movies versus high‐alcohol content movies
Comparison 2. Non‐alcohol commercials versus alcohol commercials

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption in number of glasses Show forest plot

1

80

Mean Difference (IV, Fixed, 95% CI)

‐0.73 [‐1.30, ‐0.16]

Figuras y tablas -
Comparison 2. Non‐alcohol commercials versus alcohol commercials
Comparison 3. High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption Show forest plot

1

Coefficient (Fixed, 95% CI)

0.74 [0.05, 1.43]

Figuras y tablas -
Comparison 3. High‐alcohol content movies versus low‐alcohol content movies adjusted for clustering effects
Comparison 4. Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Total alcohol consumption Show forest plot

1

Coefficient (Fixed, 95% CI)

0.83 [0.14, 1.52]

Figuras y tablas -
Comparison 4. Alcohol commercials versus non‐alcohol commercials adjusted for clustering effects
Comparison 5. Total advertising ban versus Partial advertising ban Abrupt permanent model

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Volume of alcohol (beer, wine and spirits) sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐11.11 [‐27.56, 5.34]

2 Volume of beer sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

14.89 [0.39, 29.39]

3 Volume of wine sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

1.15 [‐0.91, 3.21]

4 Volume of spirits sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐22.49 [‐36.83, ‐8.15]

Figuras y tablas -
Comparison 5. Total advertising ban versus Partial advertising ban Abrupt permanent model
Comparison 6. Total advertising ban versus Partial advertising ban Gradual permanent model

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Volume of alcohol (beer, wine and spirits) sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐11.96 [‐55.42, 31.50]

2 Volume of beer sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐0.54 [‐1.57, 0.49]

3 Volume of wine sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐0.00 [‐0.04, 0.04]

4 Volume of spirits sales in kilolitres Show forest plot

1

Mean Difference (Fixed, 95% CI)

‐27.8 [‐59.34, 3.74]

Figuras y tablas -
Comparison 6. Total advertising ban versus Partial advertising ban Gradual permanent model
Comparison 7. Alcohol ban versus no ban

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 % Change in beer consumption Show forest plot

2

Mean % change (Random, 95% CI)

1.10 [‐5.26, 7.47]

Figuras y tablas -
Comparison 7. Alcohol ban versus no ban