are alcohol policies associated with alcohol consumption in low- and middle-income countries?

Are alcohol policies associated with alcoholconsumption in low- and middle-income countries?*

Won Kim Cook, Jason Bond & Thomas K. GreenfieldAlcohol Research Group, Public Health Institute, Emeryville, CA, USA

ABSTRACT

Aims To examine the associations between alcohol control policies in four regulatory domains with alcoholconsumption in low- and middle-income countries (LAMICs), controlling for country-level living standardsand drinking patterns. Design Cross-sectional analyses of individual-level alcohol consumption survey data andcountry-level alcohol policies using multi-level modeling. Setting Data from 15 LAMICs collected in the Gender,Alcohol, and Culture: an International Study (GENACIS) data set. Participants Individuals aged 18–65 years.Measurements Alcohol policy data compiled by the World Health Organization; individual-level current drinkingstatus, usual quantity and frequency of drinking, binge drinking frequency and total drinking volume; gross domesticproduct based on purchasing power parity (GDP-PPP) per capita; detrimental drinking pattern scale; and age andgender as individual-level covariates. Findings Alcohol policies regulating the physical availability of alcohol, par-ticularly those concerning business hours or involving a licensing system for off-premises alcohol retail sales, as well asminimum legal drinking age, were the most consistent predictors of alcohol consumption. Aggregate relative alcoholprice levels were associated inversely with all drinking variables (P < 0.05) except drinking volume. Greater restrictionson alcohol advertising, particularly beer advertising, were associated inversely with alcohol consumption (P < 0.05).Policies that set legal blood alcohol concentration (BAC) limits for drivers and random breath testing to enforce BAClimits were not associated significantly with alcohol consumption. Conclusions Alcohol policies that regulate thephysical availability of alcohol are associated with lower alcohol consumption in low- and middle-income countries.

Keywords Alcohol, alcohol advertising, alcohol availability, alcohol control policy, low- and middle-income coun-tries, minimal legal drinking age.

Correspondence to: Won Kim Cook, Alcohol Research Group, Public Health Institute, 6475 Christie Avenue, Suite 400, Emeryville, CA 94608-1010, USA.E-mail: [email protected] 18 April 2013; initial review completed 19 July 2013; final version accepted 25 March 2014

INTRODUCTION

Although high-income countries (HICs) tend to havehigher levels of alcohol consumption than low- andmiddle-income countries (LAMICs)—due mainly to amuch higher proportion of abstainers in middle- andespecially in low-income countries [1]—the relativeharm associated with the given amount of alcohol con-sumed is much greater in LAMICs [2]. Alcohol is oftenconsumed in more harmful patterns in developing coun-tries [3] and is likely to interact with malnutrition, unsafehousing and other aspects of lower living standards,increasing risks of mortality and morbidity [4]. Withrising incomes and consumer purchasing power in

LAMICs, along with more intensive marketing of brandedalcohol beverages, alcohol consumption has increased inLAMICs [5]. Alcohol use is already the single largestbehavioral risk factor for disease and disability in middle-income countries [6], and alcohol-related harms mayincrease further in LAMICs with increased consumption.Concerted policy and community efforts are needed toreduce alcohol-related harms in these parts of the world.

Alcohol policies are generally designed to reducedrinking and risky drinking situations by reducing theaffordability of alcohol (e.g. through higher retail pricesand taxes); regulating the physical availability of alcohol(e.g. through restrictions on alcohol sales and alcoholoutlet densities); restricting alcohol advertising; and

*An earlier draft of this paper was presented at the GENACIS Satellite Meeting of the First Annual Epidemiology and Policy ThematicMeeting of the Kettil Bruun Society and Epidemiological Study of Alcohol Kampala, Uganda, 15–18 November 2010.

RESEARCH REPORT

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doi:10.1111/add.12571

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reducing the harms associated with risky, harmful or haz-ardous drinking (e.g. through setting legal blood alcoholconcentration (BAC) level for drivers and requiringservers to refuse to serve drinks to intoxicated patrons,etc.) [7,8]. Much of the evidence demonstrating the effec-tiveness of these policies comes from HICs [5,7,9–21]. Anemerging literature documents the current state ofalcohol policies, public awareness and enforcementefforts in LAMICs, mainly in single countries and mainlythose concerning drinking driving [22,23]. There is apaucity of policy-relevant research on LAMICs [24].Cross-national studies of alcohol policies and alcoholconsumption are rare, in part because of the difficulty ofquantifying policies in a way that is comparable acrosscountries [25]. To our knowledge, only two such studieshave been reported to date [25,26], both of which involvemainly HICs. No such study, particularly one that coversa broad range of regulatory domains, has been reportedon LAMICs.

While HICs tend to have mature markets for industri-ally manufactured alcoholic beverages [8,26–28], morepervasive informal market activities in LAMICs [6,29–32] may undercut the effectiveness of policies to regulatealcohol prices or availability. It is important to improveunderstanding of what specific policies might be moreeffective and what might be less effective. By examiningthe associations of alcohol policies and alcohol consump-tion in LAMICs, the current study aims to help fill thegaps in the current literature and inform future policyefforts in LAMICs.

In approaching this study, we note that drinking maybe profoundly influenced by socio-economic and culturalconditions. Alcohol consumption tends to be associatedpositively with a country’s living standards, even inLAMICs [1,6]. Also, drinking is a social affair to enhancesociability or foster or express social unity, often guided bya variety of cultural and social practices [33,34]. Drink-ing cultures, set in a historical and cultural context [35],may shape individual drinking behaviors by conveyingnorms regarding acceptable levels and patterns ofalcohol use [36]. To the extent that a society’s dominantdrinking culture is at odds with the alcohol policies’ goals,they may represent the forces resistant to policy ‘effects’.Conversely, in societies where abstinence as a culturalnorm is widespread, alcohol control policies may be sup-portive of this norm (and vice versa).

Given the potential influence of living standards anddrinking cultures on alcohol consumption, it is impor-tant to account for them in evaluating the effectiveness ofalcohol policy. The research question addressed in thecurrent study, therefore, is: are alcohol policies—specifically, those that regulate physical availability ofalcohol, age eligibility for purchasing alcohol, alcoholadvertising and motor vehicle operation after consuming

alcohol, as well as those likely to result in higher relativealcohol price levels—associated with alcohol consump-tion in LAMICs after adjusting for drinking culture andliving standards? We use multi-level modeling to predictindividual-level drinking variables with alcohol policyvariables in random intercept models, controlling for rel-evant individual and country-level covariates. Suchmodels allow us to test hypotheses involving the associa-tions between alcohol policies and aggregate countrydrinking measures (recognizing that causality cannot bedetermined in these cross-sectional data).

METHODS

Data and measures

Alcohol consumption variables

Alcohol consumption data were extracted from theGender, Alcohol, and Culture: an International Study(GENACIS) data set, collected from individuals aged18–65 years in 38 countries, including 15 LAMICs.Table 1 presents a summary of the methods used tocollect GENACIS data in the 15 LAMICs included in ourstudy. Using national or state/regional sampling frames(the latter generally involving large population centers),surveys were conducted in these countries between 1998and 2005. More detailed descriptions of GENACIS datacollection methods are provided elsewhere [37–39].

Five individual-level alcohol consumption variableswere used in the present study: current drinking, usualquantity and frequency of drinking, binge drinking fre-quency and drinking volume, all in the prior 12 months.Current drinking indicates having consumed any alco-holic beverages. Usual quantity indicates the typicalnumber of drinks per drinking occasion, measured ingrams of pure alcohol consumed per drinking day. Drink-ing frequency was assessed by the number of days in thelast 12 months when alcohol was consumed, calculatedusing mid-points from nine categorical responses ofnever, once, twice, three to six times, seven to 11 times,one to three times a month, once or twice a week, three orfour times a week, and every day or nearly every day.Quantified in the same way, binge drinking frequency isdefined as the number of days when five or more drinks(containing approximately 60 g of ethanol) were con-sumed in a single day. Drinking volume was calculated bymultiplying usual drinking frequency by quantity perdrinking day to give the estimated grams of ethanol con-sumed in the past 12 months [37]. As questions on drink-ing measures differed somewhat across countries, everyeffort was made to reconcile the differences. Furtherdetails are provided in previous publications [37,38].Natural logs of all drinking variables except the dichoto-mous current drinking variable were used in our analyses

1082 Won Kim Cook et al.


because of their extremely skewed distributions with longtails at higher levels.

Country-level predictors and covariates

Alcohol control policies. Information on alcohol policiesfor each country was obtained from the 2004 WorldHealth Organization (WHO) Alcohol Status Reportreflecting the status of alcohol policies as of 1 May 2002[40], approximately the middle of the survey epochrange. The only exception was India, where alcohol poli-cies are state-based; as we were able to obtain informationon alcohol policies for Karnataka state [41], where theGENACIS survey was conducted, we used this in lieu ofWHO data. Guided by two previous cross-national studies[26,28], we focus on five alcohol policy domains: physicalavailability of alcohol, age eligibility for purchasingalcohol, alcohol prices, alcohol advertising and motorvehicle operation. We did not include drinking context, asthere was no publicly available information on it prior to2008. Table 2 shows the policy measures we used. Inaddition to considering each policy variable, we also con-sidered a summary measure for each of the domains withmultiple variables.

We made concerted efforts to improve alcohol policydata to the extent possible. For example, we contactedGENACIS survey leaders to obtain policy data missing inthe WHO report, and also asked those in countries whereGENACIS data were regional whether alcohol policieswere enacted and enforced nationally or varied by state orregion. Those who replied—for example, survey leadersin Costa Rica and Nicaragua—confirmed that alcohol

policies were indeed enacted and enforced nationallyin their respective countries. As indicated above, we alsoused state-level policy data to the extent appropriate andpossible.

Living standards: gross domestic product based on purchasingpower parity (GDP-PPP) per capita. As a proxy forcountry-level living standards, we used 2004 GDP-PPPper capita [42]. GDP-PPP is converted to internationaldollars using PPP rates to compare the welfare of inhab-itants in real terms, controlling for differences in pricelevels [43].

Drinking culture: detrimental drinking pattern. Theoreticalconstructs or proxies that allow cross-national compari-son of drinking cultures are rare. We considered onesuch available measure, detrimental drinking pattern(DDP). DDP captures the prevailing drinking pattern in acountry that may affect the negative health impact of agiven amount of alcohol consumed using a scaleranging from 1, for the least risky pattern, to 4 for themost risky [3]. The DDP scale is based on WHO’s aggre-gate alcohol consumption data, population surveys andkey informant surveys conducted with experts selectedby the WHO to assess the extent to which frequent heavydrinking, drunkenness, festive drinking at communitycelebrations, drinking outside meals and drinking inpublic places are common in a particular society [44].Central to the concept of DDP is the pattern of alcoholconsumption commonly exhibited or socially accepted ina society, which may be considered normative in some

Table 1 Countries included and Gender, Alcohol, and Culture: an International Study (GENACIS) survey characteristics.

CountryCountry incomedesignationa

Surveyyear

Age range(years)

Samplesize

Samplingframe

GDP-PPPper capitab

DDPscorec

Argentina Upper-middle 2003 18–65 1000 Regional 11 456 2Belize Upper-middle 2005 18+ 3973 National 6 391 4Brazil Lower-middle 2002 17+ 712 Regional 8 258 3Costa Rica Upper-middle 2003 18+ 2526 Regional 9 206 3Czech Republic Upper-middle 2002 18–64 1273 National 16 265 2Hungary Upper-middle 2001 19–65 2243 National 15 342 3India Low 2003 16+ 2597 Regional 2 849 3Kazakhstan Lower-middle 2002 18+ 1170 Regional 7 196 4Mexico Upper-middle 1998 18–65 5711 National 9 357 4Nicaragua Low 2005 18+ 2030 Regional 2 482 4Nigeria Low 2003 18+ 2064 Regional 920 2Peru Lower-middle 2005 18–65 1531 Regional 5 170 3Sri Lanka Lower-middle 2002 18+ 1193 Regional 3 827 3Uganda Low 2003 18+ 1478 Regional 1 442 3Uruguay Upper-middle 2004 18–65 1000 National 12 108 3

a2004 World Bank country income designations as reported in World Health Organization (2011) Global Status Report on Alcohol and Health. b2004Gross domestic product based on purchasing-power-parity (GDP-PPP) per capita as reported in the International Monetary Fund World EconomicOutlook Database. cDetrimental drinking pattern (DDP) scores as reported in the World Health Organization Global Information System on Alcohol andHealth database.

Alcohol policies in LAMICs 1083


societies, but not in others [45]. Indicative of consumingany given volume in a more detrimental pattern [3],DDP as a proxy for country-level drinking culture mayhave a clear advantage over per capita consumptionvolume—an alternative proxy used in prior cross-national research [28], which is largely a function ofindividuals’ drinking quantities and frequencies—as it

allows us to avoid predicting individual-level drinkingvariables using country-level predictors that would be, ineffect, aggregated from individual consumption data.The DDP scale was validated using population surveydata from 13 countries, with a good correspondencebetween the orderings and country’s values on the DDPscale [46], demonstrating the validity of the DDP

Table 2 Alcohol policies in 15 low- and middle-income countries.

Domain Alcohol policies Measures Number of countries (%)

Physical availability (a) Restrictions on off-premisealcohol retail sales

0: no restriction 2 (14%)1: licensing system 12 (86%)

(b) Restrictions on density ofoff-premise alcohol retailoutlets

(m) beer outlet 0: No 11 (79%)1: Yes 3 (21%)

(n) wine outlet 0: No 11 (79%)1: Yes 3 (21%)

(o) spirits outlet 0: No 12 (80%)1: Yes 3 (20%)

Outlet densitya: sum of (m–o)(c) Restrictions on business

hours for off-premise alcoholsales

0: none 6 (40%)1: on hours or days 9 (60%)

Physical availability index Sum of (a–c) –Eligibility to

purchase alcoholMinimum legal drinking age Age as a continuous measure 12 (7%)

18 (87%)19 (7%)

Alcohol prices (d) Relative beer price level Level of average beer price as a fraction of GDP-PPP per capita0: low (0.000066699 or lower) 4 (27%)1: medium (0.0000677–0.00018) 6 (40%)2: high (0.000181 or higher) 5 (33%)

(e) Relative wine price level Level of average wine price as a proportion of PPP-GDP per capita0: low (0.000189 or lower) 6 (40%)1: medium (0.000190–0.001066) 4 (27%)2: high (0.001067 or higher) 5 (33%)

(f) Relative spirit price level Level of average spirit price as a proportion of PPP-GDP per capita0: low (0.00038 or lower) 4 (29%)1: medium (0.00039–0.00077) 5 (36%)2: high (0.00078 or higher) 5 (36%)

(g) Relative alcohol price level Using the sum of (d–f):0: low (0, 1) –1: medium (2, 3) –2: high (4–6) –

Motor vehiclesoperation

(i) Level of restriction involvinglegal BAC limit for adults

0: low (BAC higher than 0.50 mg/dl) 7 (47%)1: high (BAC of 0.50 mg/dl or lower) 8 (53%)

(h) Enforcement of RBT 0: none 4 (27%)1: rarely 2 (13%)2: sometimes 9 (60%)3: often 04: very often 0

Motor vehicles operation index Sum of (h–i)Alcohol

advertising(j) Beer advertising (range:

0–12)(k) Wine advertising (range:

0–12)(l) Spirits advertising (range:

0–12)

Sum of restrictions on advertising of each beverage type on eachof the four media, national TV, national radio, print media, andbillboards, assessed using the scale of:

0: no1: voluntary/self-regulation2: partial statutory restriction3: ban

Mean = 3.9; SD = 3.8Mean = 4.3; SD = 3.6Mean = 4.4; SD = 3.4

Alcohol advertising restrictionsindex

Sum of (j–l) –

SD = standard deviation. aEstimates for beer and wine outlet density were identical, which differed only slightly from the estimate for spirits outlet density. For brevity of reporting,we report the estimates using the summary measure of outlet density restrictions for all three beverage types. Source (with the exception of India): World Health OrganizationGlobal Status Report: Alcohol Policy (2004), Geneva, Switzerland: World Health Organization. Data for Karnataka state where GENACIS survey was administered in India are fromGururaj et al. (2011). Alcohol Related Harm: Implications for public health and policy in India, National Institute of Mental Health and Neuro Sciences. Bangalore, India.BAC = blood alcohol concentration; PPP-GDP = purchasing power parity gross domestic product; RBT = random breath testing.



scale as a summary measure of a country’s culturaldrinking pattern.

Data analysis

Because of the nested data structure of individualswithin countries, we fitted a series of multi-levelrandom intercept models that allow prediction of vari-ability in average drinking variables across countriesafter accounting for GDP-PPP per capita and DDP. Asthe predictors of interest in this study were country-levelalcohol policies, only age and gender were included asfixed-effects individual-level covariates. An example ofsuch a model predicting a continuous drinking variableis yi,c = αc + β1Ai,c + β2Gi,c + εi,c and αc = γ0 + γ1GDP-PPPc + γ2DDPc + θZc + uc where: yi,c is the value of thedrinking variable for the ith respondent in the cthcountry; Ai,c and Gi,c are their age and gender, respec-tively; Zc is the value of a given alcohol policy variable forthe cth country; and uc is a normal random variable withmean 0 and variance τ (i.e. the random intercept effect)uncorrelated with the level 1 residual ε. Model resultsreported in the tables involve the estimated country-levelparameter θ, interpreted as the change in the adjusted(for age and gender at the individual level, and for GDP-PPP and DDP at the country level) average drinking vari-able y for a country associated with an increase of 1 unitin the alcohol policy or domain composite variable Z.

Due to the relatively small number of level-2 units (i.e.countries) available for model estimation and to simplifymodel coefficient interpretation, the associations of eachpolicy variable or domain composite with each of thedependent drinking variable were estimated in separatemodels. The relatively small number of countries avail-able also precluded the inclusion of random effects forgender and age. Although such variability is probablypresent in the data and its omission may also lead tounderestimation of parameter standard errors, the studyof such variability was not a focus of the current study.All models were estimated using the mixed effectsmodeling functionality in Stata version 12.

RESULTS

Alcohol policies in LAMICs

The far-right column in Table 2 shows the distributions ofalcohol policies in LAMICs included in this study. The vastmajority (87%) of countries in our sample had a licensingsystem for alcohol retail sales and only a small minoritydid not, with none of them having a governmentmonopoly. While a majority (60%) of the countries alsohad restrictions on business hours for off-premise alcoholsales, most of the them (80%) did not have restrictions onthe density of off-premise alcohol retail outlets. All but

two countries had a minimum legal drinking age (MLDA)of 18 years. Maximum legal BAC levels for drivers were inplace in all the countries, with 53% of the countrieshaving a BAC of 0.05 mg/dl or lower and the rest havinghigher BAC levels. Approximately 40% of the countriesnever or rarely conducted random breath testing (RBT)to enforce the BAC limit, and the rest reported occasionalenforcement, with none conducting RBT often or veryoften.

Results of multi-level analyses: predictors ofalcohol consumption

Table 3 summarizes the results of our multi-level analy-ses to examine the associations of individual alcoholpolicy variables and domain composites with each drink-ing variable. Controlling for GDP-PPP per capita and DDP,variables in the physical availability domain were associ-ated significantly and inversely with most drinking vari-ables, with requiring licenses for alcohol retail sales andimposing restrictions on business hours being associatedwith all drinking variables, and density of alcohol outletswith country averages of usual drinking frequency, bingedrinking frequency and total drinking volume. MLDA wasassociated significantly and inversely with all drinkingvariables.

Although the medium level of the domain compositeof relative alcohol prices, compared to the low level, wasnot associated significantly with any drinking variables,the high level was associated inversely with all drinkingvariables but average drinking volume. As for individualalcoholic beverage types, spirit price levels were associ-ated inversely with average usual quantity, the mediumlevel of wine price with usual drinking frequency and thehigh level of wine price with binge drinking frequency,with the low level as the reference category.

More restrictive policies on alcohol advertising wereassociated inversely with some drinking outcomes.Greater restrictions on beer advertising were associatedinversely with average usual quantity and drinkingvolume, restrictions on wine advertising with usualquantity and restrictions on spirit advertising with usualquantity and total drinking volume. BAC and RBT levelswere not associated significantly with any of the drinkingvariables.

For all drinking variables, coefficients for age and male(compared to female) were significant and positive so thatalcohol consumption volume and frequencies werehigher for men and for those who were older. GDP-PPPper capita was associated significantly and positively withmost of the drinking variables. DDP was associatedinversely with current drinking rates, usual drinkingfrequency and total drinking volume in models toexamine the associations of physical availability, alcohol



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advertising and RBT with drinking outcomes. Given thatthese variables are not the substantive focus of the paper,specific results involving them are not reported here toreduce reporting complexity.

DISCUSSION

Our findings are consistent to varying degrees with pastresearch from HICs. Consistent with such research [9,15–17], we found that alcohol policies intended to reducethe physical availability of alcohol, particularly throughrestricted business hours and licensing system for alcoholsales, were associated with lower alcohol consumption inLAMICs as well. As found in recent research, MLDAwas associated inversely with alcohol consumption, sug-gesting that exposure to permissive MLDA laws couldaffect not only drinking in young adulthood but also laterin life [47]. These findings may temper previouslyexpressed concerns that policies intended to reduce theavailability of alcoholic beverages in formal markets maynot be effective in LAMICs because of the presence of largeinformal alcohol markets [29–32,48,49]. With increasedmarketing of industrially manufactured alcoholic bever-ages, along with increased purchasing power in LAMICs[5], regulating formal alcohol markets may be an impor-tant strategy to reduce alcohol consumption and relatedharms.

We found that the high level of relative aggregatealcohol prices was associated inversely with all drinkingvariables but average drinking volume. Prices of indi-vidual alcoholic beverage types were also associatedinversely with some drinking variables; for example, spiritprice levels with average usual drinking quantity. Theseassociations are mostly consistent with the evidence fromHICs that higher prices may depress consumption [11–13]. As suggested previously [50], there may be similarprice effects on alcohol demand in both developing anddeveloped countries, at least on some aspects of drinkingbehaviors.

We found no significant associations between policiesto regulate motor vehicle operation and alcohol con-sumption, which may be due, at least in part, to a varyingdegree of enforcements of such policies and a widevariety of cultural and socio-economic conditions acrossLAMICs that may influence drinking and driving, whichwe were unable to assess.

The inverse associations between restrictions onalcohol advertising, particularly beer, and drinking vari-ables suggest potential effectiveness of such policies. Asfound in tobacco research, advertising bans may be evenmore effective in LMICs than in HICs, even when theyare limited and not comprehensive [51]. In the context ofthe emerging evidence that points to the persuasivepower of alcohol marketing, possibly sufficient to turn

non-drinking adults into drinkers in LAMICs [52] and theglobal exposure of young people to alcohol marketing[53–55], our findings support regulatory attention torestrict alcohol advertising in LAMICs.

We acknowledge the following limitations to thepresent study. First, given the cross-sectional design ofthis study, causal relations between alcohol policies anddrinking variables cannot be established. Caution isurged in interpreting our findings. While the significantassociations observed may hint at the potential effective-ness of alcohol policies, it is equally possible that morerestrictive policies are enacted in countries where alcoholis consumed less due to more conservative drinkingcultures. Longitudinal research to evaluate the effective-ness of newly introduced alcohol policies in changingdrinking norms and behaviors is warranted.

Secondly, there are measurement challenges involvedin administering surveys cross-nationally, which mayhave hampered the reliability of our estimates reported inTable 3. Questions about drinking patterns were notexactly the same in all countries included in GENACIS.Some of the survey data were regional, which may not begeneralizable to entire countries. Although additionalstratification (e.g. by regions or states) was present in thedata for a subset of countries, the small number of suchstrata precluded estimation of formal random effects atthese levels. Omission of such strata may have led tounderestimates of parameter standard errors and henceaffect inferences. In these respects, this study shareslimitations similar to those of prior studies usingGENACIS data that the findings are less valuable forprecise prevalence estimates than for identifying patternsof association between societal-level predictors andalcohol consumption across countries [37].

Thirdly, WHO’s alcohol policy data were collectedthrough country self-reports with little external valida-tion, which we acknowledge as an important limitation.Also, as widely noted [5,7,22], regulations are effectivewhen backed up with enforcement. Non-significant orweak associations between a specific policy and alcoholconsumption, due possibly to weak enforcement, mayhave led to the underestimation of the effectiveness ofthe policy.

Fourthly, with only 15 LAMICS countries included aslevel-2 units, the power to detect significant differences ineffect sizes was limited.

Finally, while drinking cultures and norms, both onthe societal and intimate network levels, may modify theeffectiveness of alcohol policy, the measure of country-level drinking culture we used, DDP, captured suchcultural norms only to a limited degree. We were unableto fully assess specific values, norms and behaviorsrelated to drinking, a limitation imposed by the paucity ofcomparably assessed measures across countries.



Even with these limitations, the current study hasimportant strengths. Given that prior research on alcoholpolicy in LAMICs involves mainly single countries [1,22],our study contributes to this literature by providing animportant overview of alcohol policies implemented inLAMICs, which may be useful in generating hypothesesfor future testing of more or less effective alcohol policiesin the developing world using stronger, longitudinaldesigns. Importantly, the present study is the first one, toour knowledge, that evaluates the associations of alcoholpolicies and regulatory domains with drinking variablesin LAMICs to offer clues as to what policies might work inLAMICs.

Overall, our findings suggest that some alcoholpolicies found to be effective in HICs may also work inLAMICs. Expansion of industrial production and market-ing of alcohol is driving alcohol use to rise in emergingmarkets; cost-effective and affordable interventions torestrict alcohol-related harm exist, and are in urgentneed of scaling up [56]. With few civic organizationsbeing present whose mandate is to reduce alcohol-relatedharms, there has been a lack of non-governmentalorganization engagement [53,57], while alcohol-industry funded organizations have promoted a ‘partner-ship’ role with governments to design national alcoholpolicies, as observed in some low-income countries [58].There is a need to develop public health infrastructures inthose countries to develop, enact and then enforce com-prehensive alcohol policies [5].

Declaration of interests

None.

Acknowledgements

The data used in this paper are from the project, Gender,Alcohol and Culture: An International Study (GENACIS).GENACIS is a collaborative international project affiliatedwith the Kettil Bruun Society for Social and Epidemiologi-cal Research on Alcohol and coordinated by GENACISpartners from the University of North Dakota, AarhusUniversity, the Alcohol Research Group/Public HealthInstitute, the Centre for Addiction and Mental Health, theUniversity of Melbourne and the Swiss Institute for thePrevention of Alcohol and Drug Problems. Support foraspects of the project comes from the World HealthOrganization, the Quality of Life and Management ofLiving Resources Programme of the European Commis-sion (Concerted Action QLG4-CT-2001-0196), USA.Funding for this work was provided by the National Insti-tute on Alcohol Abuse and Alcoholism (NIAAA)/National Institutes of Health (Grants R21 AA012941and R01 AA015775), the German Federal Ministryof Health, the Pan American Health Organization, and

Swiss national funds. Additional funding for preparationfor this manuscript was supported in part by NIAAACenter Grant (P50 AA005595) and Training Grant (T32AA07240). Support for individual country surveyswas provided by government agencies and other nationalsources. The study leaders and funding sources fordata sets used in this report are: Argentina: MyriamMunné PhD, World Health Organization; Belize: ClaudiaCayetano PhD, Pan American Health Organization(PAHO); Brazil: Florence Kerr-Corréa MD, PhD, Founda-tion for the Support of Sao Paulo State Research(Fundação de Amparo a Pesquisa do Estado de São Paulo,FAPESP) (grant 01/03150-6); Czech Republic: LadislavCsemy; Costa Rica: Julio Bejarano MSc, World HealthOrganization; Hungary: Zsuzsanna Elekes; India: VivekBenegal MD, World Health Organization; Kazakhstan:Bedel Sarbayev PhD, World Health Organization; Mexico:Maria-Elena Medina-Mora; Nicaragua, Jose TrinidadCaldera PhD, Pan American Health Organization(PAHO); Nigeria: Akanidomo Ibanga PhD, World HealthOrganization; Peru: Marina Piazza; Sri Lanka: SiriHettige; Uganda: Nazarius Mbona Tumwesigye; andUruguay: Raquel Magri.

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are alcohol policies associated with alcohol consumption in low- and middle-income countries?

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