Description of the condition
Alcohol is estimated to be the third leading risk factor for global disability-adjusted life years (DALYs) for all ages and sexes (Lim 2012). This estimate has increased by 28% from 1990 to 2010. For people aged 15 to 49 years, alcohol is the leading risk factor for DALYs worldwide. Over 2.3 million deaths (95% uncertainty index 2,153,733 to 2,512,207) are attributed to alcohol use linked to injury (intentional, unintentional and transport), cardiovascular disease, cirrhosis, cancer, mental and behavioural disorders, HIV/AIDS and tuberculosis, and neurological disorders (Lim 2012). Alcohol affects not only the health of the drinking individual, but in pregnant women the neurotoxic effects of alcohol may cause a range of congenital defects including foetal alcohol spectrum disorders and foetal death, stillbirth, and infant and child mortality (Burd 2012).
In addition to its effects on mortality and morbidity, alcohol has significant adverse social and economic effects. A 2006 review of studies estimating the global economic burden of alcohol found that alcohol accounts for 1.3% to 3.3% of total health costs, 6.4% to 14.4% of total public order and safety costs, 0.3 to 1.4 per thousand USD of gross domestic product (GDP) for criminal damage costs, 1.0 to 1.7 per thousand USD of GDP for drink-driving costs, and 2.7 to 10.9 per thousand USD of GDP for workplace costs (absenteeism, unemployment and premature mortality) (Baumberg 2006). The authors caution readers to consider the methodological differences between studies and inherent design limitations, but their findings are supported by a 2009 analysis conducted in partnership with the World Health Organization. The aggregate analysis of reviews of published work found that costs associated with alcohol amounted to 1% of GDP in high-income and middle-income countries, with social harm the greater proportion of these costs, in addition to health costs (Rehm 2009). In a 2010 United Kingdom multi-criteria decision analysis to assess the relative harms of 20 drugs, harms both to the user and others were greatest for alcohol compared with all other drugs, including heroin and cocaine. Harms assessed included crime, family adversity and decline in social cohesion within communities (Nutt 2010).
In an overview of systematic reviews and quantitative meta-analysis, Rehm and colleagues evaluated the evidence for a causal impact of average volume of alcohol consumption and pattern of drinking on diseases and injury and quantified those relationships identified as causal (Rehm 2010). Their findings indicate that alcohol is causally related to many chronic and acute disease outcomes as well as to injury. They report that there is evidence that both the average volume and the specific drinking pattern are causally related to ischaemic heart disease, foetal alcohol syndrome and both intentional and unintentional injury. They postulate that episodes of heavy drinking are likely to influence additional disease outcomes but that epidemiological research to date has had a limited focus on drinking patterns. Due to an absence of research, they were unable to conclude whether the quality of alcohol is a significant factor in disease outcomes.
Description of the intervention
One of the main aims of commercial advertising is to encourage the consumer to use and purchase promoted products. In their extensive 2009 review of the effectiveness and cost-effectiveness of alcohol policies and programmes, Anderson, Chisholm and Fuhr report that alcohol is increasingly marketed using sophisticated advertising in mainstream media, through linking alcohol brands to sports and cultural activities, through sponsorships and product placements, and through direct marketing such as the Internet, podcasting and mobile telephones (Anderson 2009). Alcohol marketing campaigns have recently targeted social networking sites such as Facebook and Twitter, which are disproportionately used by young people (Hastings 2013). In a systematic review of 13 longitudinal studies of 38,000 young people, Anderson et al found that longitudinal studies consistently suggest that there is an association between exposure to media and commercial communications and alcohol and adolescents starting to drink alcohol, and with increased drinking amongst baseline drinkers (Anderson 2009a). In another systematic review of seven cohort studies of young people, Smith and Foxcroft suggest that while there is an association between exposure to alcohol advertising or promotional activity and subsequent alcohol consumption in young people, the modest effect sizes may be limited by the potential influence of residual or unmeasured confounding in the included studies (Smith 2009). Snyder et al in their longitudinal investigation found empirical evidence suggesting direct measurable effects on both drink initiation and consumption levels due to exposure to advertising (Snyder 2006).
In their 2008 independent review of the effects of alcohol pricing and promotion for the United Kingdom Department of Health, Booth and colleagues identify the methodological complexity of linking advertising to consumption (Booth 2008). Cross-sectional studies will fail to meet the causality criteria of temporality (the intervention predates the effect), and cohort studies and time series analyses may be prone to confounding unless adequately controlled. In addition, they point out that sub-populations such as problem drinkers are likely to be under-represented in general population aggregated data which are primarily used in national or state-level studies. Despite these methodological limitations, they conclude that there is evidence for an effect of alcohol advertising on underage drinkers and that exposure to television, music videos and billboards which contain alcohol advertising predict onset of youth drinking and increased drinking (Booth 2008).
How the intervention might work
Prevention strategies to reduce the quantity of alcohol consumed and the age of initiation of alcohol use include several public health interventions targeted at the general population. One such strategy is the reduction and banning of all forms of advertising of alcohol. The reduction in marketing may be voluntary and implemented by the alcohol, media or advertising industries, or mandatory and implemented by government decree.
Theoretically, a reduction or a ban of alcohol advertising may reduce consumption of alcohol across the general population and may raise the age of initiation of drinking in young people. In their 2001 international comparison of bans on broadcast advertising of alcohol in 17 Organization for Economic and Cooperation Development (OECD) countries between 1977 and 1995, Nelson and Young report that there are several theoretical models of advertising, including social learning theory which argues that advertising contributes to normalising perceptions of drinking in society (Nelson 2001). They also describe conflicting economic theories with advertising either increasing or decreasing consumption because it affects both demand and the levels of prices that sellers find optimal. They warn that partial bans of advertising using specific forms of media may drive substitution towards other advertising media (Nelson 2001).
In their review of policies and programmes, Anderson et al indicate that making alcohol less available and more expensive and placing a ban on alcohol advertising are the most cost-effective ways to reduce the harm caused by alcohol (Anderson 2009a). However, little evidence is provided to support the statement on banning alcohol advertising. The authors acknowledge that in regions where alcohol marketing relies on self regulation (rather than regulatory banning or restrictions), several studies show that these voluntary systems do not prevent marketing content directed at young people. In another study of pooled time series data from 20 countries over a 26-year period, the authors' primary conclusion is that alcohol advertising bans do decrease consumption by 5% to 8% (Saffer 2002). Similarly, a cross-sectional study in the emerging market context of Brazil found evidence of association, but not causation, between alcohol consumption and alcohol promotion (Pinsky 2010).
Why it is important to do this review
In the 2012 Global Burden of Disease report, the authors state that public policy to improve the health of populations will be more effective if policies address the major causes of disease burden. They argue that small reductions of population exposure to large risks will yield substantial health gains (Lim 2012). Reducing or banning alcohol advertising may reduce exposure to the very large risk posed by alcohol both to the individual and to the general population. To date, no systematic review has evaluated the effectiveness, possible harms and cost-effectiveness of this intervention. This Cochrane review aims to evaluate, in a systematic manner, the benefits and harms of reducing or banning alcohol advertising and the cost-effectiveness of such an intervention.
To evaluate the benefits and harms of reducing or banning advertising of alcohol, via any format including advertising in the press, television, on the Internet, using social media and product placement in films, on alcohol consumption in adults and adolescents.
Criteria for considering studies for this review
Types of studies
This question is applicable to both general population-level studies (where aggregate data from regions are collated before and after a reduction or ban on advertising) and individual-level studies (where participants may be randomised to different levels of advertising and their subsequent consumption measured).
General population level
- Randomised controlled trials (RCT)
- Controlled clinical trials (CCT)
- Prospective cohort studies
- Retrospective cohort studies if baseline exposure data were collected at time of baseline of study
- Controlled before and after (CBA) cross-sectional studies including econometric studies
- Interrupted time series (ITS) studies. We will use the definition for ITS given by the Cochrane Effective Practice and Organization of Care Review Group, viz:
- there were at least three time points before and after the intervention, irrespective of the statistical analysis used;
- the intervention occurred at a clearly defined point in time;
- the study measured provider performance or participant outcome objectively.
- Prospective cohort studies
- Retrospective cohort studies if baseline data were collected at time of baseline of study
- Controlled before and after cross-sectional studies
- Interrupted time series studies
NOTE: For both population- and individual-level ITS studies, if the study has ignored secular (trend) changes and performed a simple t-test of the pre- versus post-intervention periods without further justification, the study will not be included in the review unless re-analysis is possible.
Types of participants
Adults of any age and adolescents (defined by World Health Organization as 10 to 19 years old).
Types of interventions
A reduction or restriction or banning of advertising of alcohol and related products via any format including advertising in the press, television, radio, on the Internet, billboards, using social media and product placement in films.
Advertising will be interpreted broadly as recommended by the World Health Organization which defines marketing (with emphasis on its persuasive impact) as: "any form of commercial communication or message that is designed to increase, or has the effect of increasing, the recognition, appeal and/or consumption of particular products and services. It could comprise anything that acts to advertise or otherwise promote a product or service" (WHO 2010, page 15). Therefore a restriction of advertising may include restricting responsible drinking campaigns led by the alcohol industry and marketing of positive associations between industry and socially responsible initiatives.
We will attempt to include restrictions of all new forms of marketing, for example those facilitated by digital technologies, but acknowledge that research into the impacts of advertising restrictions is likely to lag behind new marketing technologies.
Advertising of alcohol and related products via any format including counter-advertising (defined as the promotion of healthy choices and harm reduction messages).
As for the intervention, advertising is broadly defined as per the WHO criteria reported above.
Types of outcome measures
- Reduction in alcohol consumption
In population-based studies, this may be measured via econometric data (e.g. annual sales of alcohol per capita) and in individual-based studies this may be measured by rate of drinks (number during a specified time).
- Delayed age of initiation of alcohol use
- Reduction in rate of reported risk behaviour
- Reduction in alcohol-related injury or accident
- Reduction in individual spending on alcohol
- Loss of revenue from alcohol industry
- Loss of advertising revenue
- Reduction in gross domestic product attributable to alcohol sales
- Loss of employment from alcohol industry
- Reduction in taxes received
Search methods for identification of studies
We will develop the search strategy with the assistance of the Cochrane Drugs and Alcohol Review Group Trials Search Co-ordinator. We will formulate a comprehensive and exhaustive search strategy in an attempt to identify all relevant randomised controlled trials, cohort studies and before-and-after cross-sectional studies regardless of language or publication status (published, unpublished, in press and in progress).
As we are not limiting the strategy to search for RCT or cohort studies, we will not use the RCT strategy developed by The Cochrane Collaboration and detailed in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We will use a combination of terms specific to alcohol consumption and to advertising. The search will be iterative and will use both database-specific syntax and free-text terms. See Appendix 1 for the MEDLINE search strategy.
We will search the following databases:
1. Journal databases
- Cochrane Drugs and Alcohol Group Specialised Register
- Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library, most recent)
- MEDLINE (PubMed) (1966 - to present)
- EMBASE (embase.com) (1974 - to present)
- AgEcon (ageconsearch.umn.edu/)
- Business Source Premier and EconLit (on EBSCOHOST)
If feasible we will also search the following databases:
- National Institute of Health Alcohol and Alcohol Problems database (1972 to 2003) (http://etoh.niaaa.nih.gov/)
- NHS Economic Evaluations Database (NHS EED)
- Association for Consumer Research
- Chartered Institute of Marketing
2. Conference databases
We will attempt to search the following conference proceedings where electronic database searches are available:
- Conference proceedings of the International Council of Alcohol and Addictions (ICAA)
- Conference proceedings of the Research Society of Alcoholism (RSA) (www.rsoa.org)
- Conference proceedings of the International Society for Biomedical Research in Alcoholism (www.isbra.com/)
- Conference proceedings of the Kettil Bruun Society
- Conference proceedings of the International Network on Brief Interventions for Alcohol Problems (INEBRIA)
- Conference proceedings of the International Health Economics Association
- Meeting reports of the International Center for Alcohol Policies (http://www.icap.org/)
- Meeting reports of the European Advertising Standards Alliance (http://www.easa-alliance.org/)
- Meeting reports of the The Foundation for Alcohol Research (http://www.abmrf.org/)
3. Ongoing trials
To identify ongoing RCTs we will search ClinicalTrials.gov (http://clinicaltrials.gov/) and the World Health Organization International Clinical Trials Registry Platform (http://apps.who.int/trialsearch/).
In the absence of registries for non-RCTs, we will contact experts and researchers in the field, to identify ongoing cohort, before-after and interrupted time series studies.
Searching other resources
We will check the reference lists of all studies identified by the above methods and examine the references of any systematic reviews, meta-analyses or guidelines we identify during the search process.
We are in close contact with individual researchers working in the field and policymakers based in inter-governmental organisations including the World Health Organization (WHO), and we will contact experts in the field who may be aware of unpublished or ongoing studies (e.g. Center on Alcohol Marketing and Youth (CAMY) and the European Centre for Monitoring Alcohol Marketing (EUCAM)).
We will not conduct handsearching of specific journals other than those searched by the Cochrane Drugs and Alcohol Review Group and already included in CENTRAL.
Data collection and analysis
Selection of studies
NS and DP will read the titles, abstracts and descriptor terms of all downloaded material from the electronic searches to identify potentially eligible reports. We will obtain full-text articles for all citations identified as potentially eligible and NS and DP will independently inspect these to establish the relevance of the article according to the pre-specified criteria. Where there is any uncertainty as to the eligibility of the record, we will obtain the full article.
NS and DP will independently apply the inclusion criteria and any differences arising will be resolved by discussions with the third review author, JA. We will review studies for relevance based on study design, types of participants, exposures and outcome measures.
Data extraction and management
NS and DP will independently extract data into a standardised data extraction form. We will pilot the form on three studies to assess its completeness and usability. We will extract the following characteristics from each included study.
- Administrative details: trial or study identification number; author(s); published or unpublished; year of publication; number of studies included in paper; year in which study was conducted; details of other relevant papers cited.
- Details of the study: study design; type, duration and completeness of follow-up; country and location of study (e.g. higher-income versus lower-income country); informed consent and ethics approval.
- Details of participants: setting; numbers; relevant baseline characteristics, including age and sex.
- Details of intervention: type of intervention (e.g. restriction, full banning); media setting (e.g. press, television, Internet, social media, product placement); timing and duration of intervention; additional co-interventions.
- Details of comparison: type and media setting of advertising; timing and duration of current advertising.
- Details of outcomes: decreased alcohol consumption; delayed age of initiation of alcohol use; decreased rate of reported risk behaviour; reduction in alcohol-related injury or accident; loss of revenue from alcohol industry; loss of revenue from the advertising agency sector; reduction in gross domestic product; loss of employment from alcohol industry; decreased individual spending on alcohol.
- Details of the analysis: for RCTs, details of the type of analysis (intention-to-treat or per protocol); for cohort studies, details of the type of adjustment performed in the analysis.
Assessment of risk of bias in included studies
Assessment for RCTs, CCTs, CBA and cohort studies
For RCTs, CCTs, CBA and cohort studies, NS and DP will independently examine the components of each included study for risk of bias using a standard form.
We will perform the 'Risk of bias' assessment for RCTs, CCTs, cohort studies and CBAs in this review using the criteria recommended by the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). The recommended approach for assessing risk of bias in studies included in a Cochrane Review is a two-part tool, addressing seven specific domains, namely sequence generation and allocation concealment (selection bias), blinding of participants and providers (performance bias), blinding of outcome assessor (detection bias), incomplete outcome data (attrition bias), selective outcome reporting (reporting bias) and other sources of bias. The first part of the tool involves describing what was reported to have happened in the study. The second part of the tool involves assigning a judgement relating to the risk of bias for that entry, in terms of low, high or unclear risk. To make these judgements we will use the criteria indicated by the Handbook adapted for the addiction field.
The domains of sequence generation and allocation concealment (avoidance of selection bias) will be addressed in the tool by a single entry for each study.
Blinding of participants, personnel and outcome assessor (avoidance of performance bias and detection bias) will be considered separately for objective outcomes (e.g. use of alcohol measured by biomarker analysis) and subjective outcomes (e.g. patient self reported use of substance).
Incomplete outcome data (avoidance of attrition bias) will be considered for all outcomes.
We will use the criteria drawn from the Newcastle-Ottawa Scale (NOS) (Newcastle-Ottawa) and the criteria developed by the Cochrane Effective Practice and Organization of Care (EPOC) Review Group (EPOC 2008) to assess the observational studies. Specifically, the NOS makes judgements in three general areas: selection of study groups, comparability of groups and ascertainment of outcomes (in the case of cohort studies). As a result, this instrument can assess the quality of non-randomised studies so that they can be used in a meta-analysis or systematic review. The 'Risk of bias' tables will be operationalised to be used both for the assessment of RCTs, CCTs, CBA and prospective observational studies according to these criteria. Please see Appendix 2 for full details.
Assessment for interrupted time series studies
We will use the criteria recommended by the Cochrane EPOC Review Group to assess the methodological quality of the CBA and ITS studies. The assessment comprises seven standard criteria specific to ITS. See Appendix 3 for full details.
Measures of treatment effect
We will conduct data analysis using Review Manager 5 (RevMan 2012).
For RCT data, we will calculate outcome measures for dichotomous data (e.g. proportion decreasing consumption) as risk ratios with 95% confidence intervals. For continuous data (e.g. mean age of initiation) we will calculate the mean difference and standard deviation where means are reported.
For cohort and other study design data, we will preferentially report on the adjusted analysis using the estimate of effect reported in the study rather than calculating estimates of effects based on the crude data. Where only crude data are presented, we will, where appropriate, calculate the crude risk ratio and 95% confidence intervals for dichotomous data and mean difference and standard deviations for continuous data where means are reported, or report on medians if data are skewed.
Unit of analysis issues
Studies may employ 'cluster-randomisation' (such as randomisation by student group or region), but analysis and pooling of clustered data poses problems. Authors often fail to account for intra-class correlation in clustered studies, leading to a 'unit of analysis' error (Divine 1992) whereby P values are spuriously low, confidence intervals unduly narrow and statistical significance overestimated. This causes type I errors (Bland 1997).
Where clustering is not accounted for in primary studies, we will present data in a table, with a (*) symbol to indicate the presence of a probable unit of analysis error. If cluster studies have been appropriately analysed taking into account intra-class correlation coefficients and relevant data documented in the report, synthesis with other studies will be possible using the generic inverse variance technique.
We do not anticipate any cross-over trials will have been conducted on this topic.
Dealing with missing data
Where data are missing, we will contact study authors and request additional data. Should this not be possible, we will state explicitly where calculations are based on assumptions regarding missing data.
Assessment of heterogeneity
For both RCT and cohort meta-analyses, we will formally test for statistical heterogeneity using the Chi² test for statistical homogeneity with a 10% level of significance as the cut-off. We will quantify the impact of any statistical heterogeneity using the I² statistic (Higgins 2002).
Where studies do not have combinable outcomes, we will provide the data in a narrative form.
Where RCTs are found to be methodologically or clinically comparable, we will pool trial results in a meta-analysis. As we anticipate the presence of statistical heterogeneity we will combine the data using the random-effects model.
For meta-analysis of RCTs, we will combine the results and calculate the risk ratio and 95% confidence intervals for dichotomous data. For continuous data, we will combine the mean differences to calculate a mean difference and standard deviation. If time-to-event data are available, we will combine the hazard ratios reported in the RCTs using the generic inverse variance function.
Where cohort studies are found to be methodologically or clinically comparable, we will also pool the results in a meta-analysis using the generic inverse variance function in RevMan to allow adjusted data to be used in the analysis. We will anticipate heterogeneity due to the likelihood of different analytical techniques and different adjusted variables and will combine studies using the random-effects model.
For cohort studies, we will report on the adjusted analysis using the estimate of effect reported in the study. Where the adjusted estimate of effect is reported with 95% confidence intervals (CI), we will calculate the standard error in order to enter the data into RevMan, using the following formula for ratio measures:
- lower limit = ln(lower confidence limit given for HR)
- upper limit = ln(upper confidence limit given for HR)
- intervention effect estimate = lnHR
- SE = (upper limit – lower limit)/3.92
Subgroup analysis and investigation of heterogeneity
We anticipate statistical heterogeneity due to anticipated differences between study populations and interventions. We will explore the expected heterogeneity using the following subgroups:
- Setting: resource-constrained or resource-rich settings as defined by the World Bank as middle- or low-income countries and high-income countries, respectively
- Setting: international, national, regional or community settings
- Age: adolescent, adult or mixed populations
- Type of advertising: audiovisual, print or social media
For RCTs, we will explore the effect of study quality on the results by excluding those studies where allocation concealment was unclear or inadequate from the meta-analysis and assessing the effect of this on the overall results. For cohort studies we will examine the effect of adjustments for confounding. If data are available, we will also explore the effects of funding source (industry versus non-industry) on the meta-analysis.
We will use GRADEpro 2008 to create 'Summary of findings' and evidence profile tables. The GRADEpro software was developed as part of a larger initiative led by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group. GRADE offers a system for rating quality of evidence in systematic reviews and guidelines and grading strength of recommendations in guidelines (Guyatt 2011). Use of GRADEpro within a Cochrane systematic review facilitates the process of presenting and grading evidence transparently (http://ims.cochrane.org/revman/other-resources/gradepro/about-gradepro).
In determining the level of evidence for each outcome, we will integrate both the efficacy results and the assessment of the risk of bias into a final assessment of the level of evidence and provide full details of the decision in footnotes.
The authors are grateful to Zuzana Mitrova of the Cochrane Drugs and Alcohol Review Group for her guidance and searching. We thank Tara Carney of the Alcohol and Other Drug Research Unit for assisting so ably with article retrieval and Joy Oliver of the South African Cochrane Centre for her assistance with procuring articles and administrative assistance.
We are very grateful to our two peer referees who provided invaluable feedback to improve the protocol.
Appendix 1. PubMed search strategy
Appendix 2. 'Risk of bias' criteria for RCTs, CCTs and prospective observational studies
Appendix 3. 'Risk of bias' criteria for interrupted time series
Contributions of authors
The study was commissioned by the Alcohol and Drug Abuse Research Unit and the South African Cochrane Centre of the South Medical Research Council. NS co-ordinated the author team and wrote the first draft of the protocol. DP, JA, TK, JV, MJ and CP commented and contributed to the writing of the final draft.
Declarations of interest
NS, DP, JV, TK, and MJ declare no conflicts of interest.
JA is a member of the WHO Working Group on Alcohol Taxation and Pricing. This working group is involved in drafting a technical resource on alcohol pricing and taxation policies and guidelines on how best to implement such policies.
CP is a member of the WHO Expert Panel on Drug Dependence and Alcohol Problems and a board member of the Global Alcohol Policy Alliance, a network whose mission is to reduce alcohol-related harm worldwide by promoting science-based policies independent of commercial interests.
Sources of support
- Alcohol and other Drug Research Unit, Medical Research Council, South Africa.The Unit commissioned the study in partnership with the South African Cochrane Centre and co-funded the lead author of the review.
- South African Cochrane Centre, Medical Research Council, South Africa.The Unit commissioned the study in partnership with the Alcohol and other Drug Research Unit and co-funded the lead author of the review.
- No sources of support supplied