Do societal wealth, family affluence and genderaccount for trends in adolescent cannabis use?A 30 country cross-national study
Tom F. M. ter Bogt1, Margreet de Looze1, Michal Molcho2, Emmanuelle Godeau3,4,Anne Hublet5, Anna Kokkevi6, Emmanuel Kuntsche7,8, Saoirse Nic Gabhainn2,Iva Pejnovic Franelic9, Bruce Simons-Morton10, Sharon Sznitman11, Alessio Vieno12,Wilma Vollebergh1 & William Pickett13,14
Interdisciplinary Social Sciences, Utrecht University, Utrecht, the Netherlands,1 Health Promotion, National University of Ireland, Galway, Ireland,2 UMR 1027,Inserm, Université deToulouse, Toulouse, France,3 Service médical du rectorat deToulouse, Toulouse, France,4 Department of Public Health, Gent University, Gent,Belgium,5 University Mental Health Research Institute, Athens, Greece,6 Sucht Schweiz Research Institute, Lausanne, Switzerland,7 Behavioural Science Institute,Radboud University, Nijmegen, The Netherlands,8 Croatian National Institute of Public Health, Zagreb, Croatia,9 Prevention Research Branch, Division ofEpidemiology, Statistics and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA,10
School of Public Health, University of Haifa, Haifa, Israel,11 Dipartimento di Psicologia dello Sviluppo e della Socializzazione, Universita degli Studi di Padova,Padova, Italia,12 Department of Public Health Sciences, Queen’s University, Kingston, Canada13 and Department of Emergency Medicine, Queen’s University,Kingston, Canada14
ABSTRACT
Aims To examine cross-national changes in frequent adolescent cannabis use (40+ times consumed over life-time atage 15) over time and relate these trends to societal wealth, family affluence and gender. Design Data from three cycles(2002, 2006, 2010) of the Health Behaviour in School-aged Children (HBSC) Study were used for cross-sectional andtrend analyses of adolescent cannabis use. Setting Representative surveys in 30 European and North Americancountries. Participants A total of 160 606 15-year-old students. Measurements Respondents’ life-time cannabisuse, demographics, family affluence (FAS) and frequency of peer contacts were measured individually. Indicators ofwealth (gross domestic product per capita, GDP) and perceived availability of cannabis were obtained from nationalpublic data bases. Findings The frequency of life-time cannabis use decreased over time among adolescents in Europeand North America, particularly in western European countries and the United States (relative risk (RR) = 0.86:confidence interval (CI) 0.79–0.93). This trend was not observed consistently in rapidly developing countries ineastern, central and southern Europe. Over time (2002–10), cannabis use became: (i) less characteristic of high GDPcountries in contrast to lower GDP countries (RR = 0.74: CI 0.57–0.95); (ii) less characteristic of youth from high FASfamilies in contrast to youth from low FAS families (RR = 0.83: CI 0.72–0.96); and (iii) characterized by an increasinggender gap, i.e. consumption was higher among males (RR 1.26: CI 1.04–1.53). Perceived availability of cannabisand peer contacts remained strong predictors of frequent cannabis use. Conclusions Among 30 European andNorth American countries, cannabis use appears to have ‘trickled down’ over time, with developing countries takingon the former (heavier) use pattern of richer countries, and less affluent youth taking on the former (heavier) usepattern of more affluent youth. Cannabis use continues to be more common among adolescent males than females.
Keywords Adolescence, cannabis use, family affluence, gender, societal wealth.
Correspondence to: Tom ter Bogt, Interdisciplinary Social Sciences, PO Box 80140, 3508TC Utrecht, the Netherlands. E-mail: [email protected] 25 January 2013; initial review completed 2 April 2013; final version accepted 27 September 2013
INTRODUCTION
Cannabis use has been conceptualized as typical of afflu-ent youth in wealthy societies [1], and generally youngmales have always been more prone to use the drug thanfemales [2,3]. However, gender patterns of consump-
tion and the relationship between societal and familyaffluence and cannabis use may be changing.
The Health Behavior in School-Aged Children (HBSC)study, with data collection most recently in 2002, 2006and 2010, provides a unique opportunity to study trendsin cannabis use in a large number (n = 30) of European
and North American countries. We investigated the con-sistency over time of gender, societal wealth and familyaffluence (FAS) as social determinants of cannabis use.
The gender gap in cannabis use
Determinants of cannabis use have been theorized toinvolve complex interactions between biological, genetic,personality, attitudinal, family, peer and community vari-ables [4]. Existing empirical research on adolescent can-nabis use suggests that gender, as an expression of a set ofbiogenetic and social factors, is a key predictor. Acrossgeographical areas and time, adolescent males reporthigher prevalence of cannabis use compared to femalesand a greater tendency to abuse and develop dependenceon cannabis [5]. However, trends in use by gender are ofparticular interest as the gender composition of cannabisusers may have changed.
During the last five decades, teenage female smokingand drinking have increased [6,7]. Two cultural trendsworked in the same direction. First, the growing societalwealth in western countries promoted a unique youthcultural domain, involving special products, styles andrecreational activities such as dancing and partying.These fostered the consumption of smoking, drinkingand other (il)licit substances. Parker, Aldrige & Measam[8] have noted that consumption of alcohol, tobacco andillicit drugs among youth in affluent countries such as theUnited Kingdom is so prevalent that it has become ‘nor-malized’. Secondly, the emancipation of women enablednew opportunities for work and leisure, allowing womento explore public spaces such as pubs, bars and clubs [9].Recent research shows that drinking prevalence is higheramong adolescent males, but the gap between boys andgirls is declining [10]. In some European countries,females now smoke more than males [11], and femalecannabis use has generally followed similar trends to thatreported for males [12]. While gender is a crucial factor insubstance use, trends in the potential closing of thegender gap that have occurred with regard to smokingand drinking have never been studied with regard to can-nabis use in a cross-national context.
Wealth and cannabis use
The effect on adolescent cannabis use of characteri-stics of the wider social context is also understudied,although economic factors such as affordability andavailability are established determinants of tobacco anddrug use [13]. In a recent cross-national study, Ter Bogtet al. showed that societal wealth is related to higherrates of cannabis use [1]. The authors speculatedthat, historically, cannabis use might spread from richerto poorer countries. Furthermore, the aforementionedstudy of Parker et al. [8] found evidence that cannabis
use has become less characteristic of youth with a riskyhealth profile, but is ever more typical of well-adjusted,relatively healthy young people who include drug use asa recreational activity in their leisure time. It can behypothesized that cannabis normalization has not onlyappeared in the United Kingdom, but that across Europecannabis, in addition to tobacco and alcohol, is now per-ceived by young people as a substance that is part of therange of drugs typical for night-life. Speculatively, youngpeople from poorer countries may have adapted theirbehaviour to cannabis use patterns of their peers inwealthier countries (trickling-down effect 1; betweencountries). Across Europe, over the last two decades, a(relative) increase in cannabis use indeed emerged in thecentral and eastern European regions where market-orientated economies developed rapidly. The 2007 Euro-pean School Survey Project on Alcohol and other Drugs(ESPAD) study indicated significant increases in cannabisuse (1995–2007) in Bulgaria, Croatia the Czech Repub-lic, Estonia, Hungary, Lithuania, Poland, Slovak Republicand Slovenia (but not in Latvia, Romania, Ukraine),hinting at the importance of increased social wealth as apotential determinant [12].
Furthermore, Ter Bogt et al. [1] also speculated thatwithin countries, wealth and availability foster the emer-gence of a drug-using community of young people thatplays a crucial role in the socialization of younger, poten-tial cannabis users. Hence, leisure opportunities for arising middle class may foster drug use and culturalacceptance of use, which is adopted later among youthfrom a lower socio-economic status (SES) or family afflu-ence status (FAS), once they have the money and oppor-tunity to buy drugs (trickling-down effect 2; withincountries, between classes) [1]. In some countries thistendency may have levelled off, as the ‘trickling-down’has occurred at such a rate that cannabis use is now morecharacteristic of lower than higher SES youth [13].Again, trends in cannabis use and their reliance on soci-etal wealth or family affluence have never been studied ina broad cross-national context.
The present study
Broad social trends hint at a changing gender composi-tion of cannabis use, with greater parity in use betweenmales and females. Furthermore, societal and familywealth may influence cannabis use among adolescents,with ‘trickling-down’ effects from more affluent to poorernations and groups. Our study therefore sought to:1 describe cannabis use trends over the reporting periods
of 2002, 2006 and 2010 in 30 European and NorthAmerican countries;
2 examine how gender, societal wealth and familyaffluence relate to cannabis use;
3 test whether the gender gap in cannabis use is closing;and
4 evaluate possible trickle-down effects from higher toless affluent countries and from higher FAS youth toless affluent youth, respectively.
As noted above, in countries and social contexts wherecannabis is readily available, adolescent cannabis use ishigher [1,14]. Furthermore, the social context of adoles-cents is an important, if not the most important factor, incannabis initiation and use [14]. Therefore, we modelledperceived availability and peer contacts as covariates.
METHODS
Study population and procedures
Health Behavior in School-Aged Children Study (HBSC),school-based anonymous surveys were conducted in2002, 2006 and 2010 according to the HBSC researchprotocols. Samples were representative geographically,with variations in sampling criteria permitted to fitcountry-level circumstances. Some countries over-sampled subpopulations (e.g. by geography, ethnicity),and therefore survey weights were applied. Statistical cri-teria specified that samples submitted for internationalcomparisons were sufficient to provide confidence inter-vals of ±3% for prevalence with sample design effects ofno more than 1.2 times greater than would be obtainedfrom a simple random sample.
Each participating country obtained approval toconduct the survey from the ethics review board orequivalent regulatory body associated with their respec-tive institutions/countries. Participation was voluntaryand informed consent was sought from school adminis-trators, parents and children according to local humansubject requirements. At the student-participant level,response rates among countries varied by survey cycleand country; for example, in 2010 response rates at theindividual level ranged from 44 to 92% [15,16]. All pro-tocols can be retrieved at: http://www.hbsc.org/methods/index.html [17]. Illicit drug use questions in HBSC wereadministered to 15-year-olds only.
Cannabis use
The HBSC cannabis use items have been used since 1994in all participating countries. In 2002, 2006 and 2010students reported the frequency with which they hadused cannabis in their life-time on a scale from 1 to 7,with 1 = never and 7 = 40 or more times. Students in thelast category were characterized as frequent life-timeusers and compared with those who reported never orless frequent life-time use. This study regards 15-year-oldstudents for whom cannabis use is a new type of behav-iour. For example, the 2010 HBSC data show that the
prevalence of life-time use (17% of the sample) is close tothat of last year use (13%), indicating that most of thecannabis-consuming students have started using canna-bis only recently. Therefore, young people who have usedthe drug 40 times or more can be qualified as relativelyheavy users.
Time
Trends in frequent life-time cannabis use were expressedin terms of changes in prevalence per 4-year survey cycle.
Individual-level predictors
Gender (males versus females) and family affluence (FAS;the validated HBSC measure of family SES) [16] wereincluded as individual predictors. FAS regards the mate-rial conditions of participant’s household (car, ownbedroom, holiday frequency, number of computers).Responses were summed on a 0–9-point scale, withscores between 0 and 3 indicating low affluence, 4–5indicating medium affluence and 6–9 indicating highaffluence.
Two measures described involvement with peers: (i)frequency of peer contacts in the evenings, assessed bythe question: ‘How many evenings per week do youusually spend out with your friends?’ (0–7 evenings perweek); and (ii) frequency of peer contact through elec-tronic communication, assessed by question: ‘How oftendo you talk to your friends(s) on the phone or send themtext messages or have contact through the internet?’(1 = rarely or never, to 5 = every day).
Country-level predictors
As indicators of societal wealth, estimates of GDP percapita (2011) were available by survey cycle and countryfrom the World Bank. This measure represents the sum ofgross value added by all resident producers in theeconomy plus any product taxes and minus any subsidiesnot included in the value of the products, divided by themid-year population [18].
Generalized perceived availability of cannabis wastaken from the ESPAD. Estimates were obtained foreach country using the ESPAD survey cycle that imme-diately preceded each HBSC survey cycle. For eachcountry and time-frame, the percentage of ESPADstudents indicating that cannabis availability was ‘easy’or ‘fairly easy’ to obtain was estimated using meanresponses of participants.
Statistical analysis
Data analyses were conducted with SAS version 9.3 (SASInstitute, Cary, NC, USA, 2012). Descriptive analyseswere conducted to characterize the international sample
by survey cycle and basic demographics. Prevalencevalues of frequent life-time cannabis use were thenestimated by survey cycle, country and gender.
Trends analysis
We evaluated trends in frequent life-time cannabis usewithin each country using a Poisson regression analysisthat modelled frequent use (yes versus no) as the depend-ent variable and gender and time (year of survey cycle) asthe independent variables. Models accounted for the clus-tered nature of the sampling scheme, with studentsnested within schools in 26 out of 30 countries. In fourcountries (Germany, Greenland, Slovakia and Switzer-land) that had incomplete school identifiers in the earlycycles, clustering by school in these countries was con-ducted by down-weighting their respective samples usinga conservative design effect of 1.2 [15]. Coefficients andstandard errors from the adjusted models were used togenerate estimates of relative risk (RR) and associated95% confidence intervals (CI) for each 4-year surveycycle.
Main effects analysis
We first examined bivariate correlations between predic-tors of cannabis use at the country level and reportedrates of frequent life-time use by cycle using a series ofexploratory correlation analyses. Next, taking all coun-tries together, Poisson regression analyses were con-ducted to predict frequent life-time cannabis use. Theseanalyses focused on the main effects of the various pre-dictors measured at both individual (gender, FAS, peercontacts) and country levels (GDP per capita, perceivedavailability of cannabis). Countries were included asrandom effects in these models, and random interceptsindicating baseline levels of cannabis use were alsoassumed by country. (Note: in exploratory analysesmodels that considered fixed and random slopes forincluded countries were consistent, hence models withfixed slopes, but random intercepts, were ultimately pre-sented.) Due to the missing school identifiers in the afore-mentioned countries, we down-weighted all observationsby a design effect of 1.2 in order to account for clusteringat the school sampling unit level. A hierarchical series ofmodels was developed as follows: model 1: adjusted modelfor key individual-level predictors; model 2: adjustedmodel for country-level predictors; model 3: individualplus country-level predictors considered simultaneously;and model 4: individual plus country-level predictorsconsidered with time (survey cycle). Model findings werepresented in the form of adjusted relative risks and theirassociated 95% CI. Canada and the United States wereexcluded from these analyses, as no comparable ESPADdata on perceived availability of cannabis were available.
Interactions with survey cycle
In model 5, we tested for the presence of interactions bytime (survey cycle) with several key predictors. Two-wayinteraction terms (survey cycle × each predictor) wereintroduced individually and then together into eachmodel. Final model results were again presented in termsof RR and their associated CIs adjusted for the clusterednature of the data collection.
Statistical power
Because of the large sample sizes, the overall analysis hadstrong power and could detect main effects in the formof RR of 1.02 or larger (or conversely 0.98 or lower;alpha = 0.05, two-sided, design effect of 1.2). However,power to detect such effects varied substantially at thecountry level depending upon the prevalence of cannabisuse and available sample sizes. For example, Greenland(496 boys, 556 girls) and the United Kingdom (7218boys, 7389 girls) had the smallest and largest numbers ofyoung people, respectively, that participated in the threecycles of the survey. When one compares the highestversus lowest proportions of young people reporting fre-quent life-time cannabis use by survey cycle, afteraccounting for the clustered sample design, the power todetect differences in the observed prevalence between thehighest and lowest cycles were quite modest in Greenland(42% in boys, 77% in girls) and very high (virtually 100%in both boys and girls) in the United Kingdom. Hence,modest sample sizes and an associated lack of statisticalpower in a few countries (See Table 1) may account for anabsence of trends in those same countries.
RESULTS
The sample
A sample of 15-year-old adolescents (weightedn = 160 606) from 30 countries participated in the2002, 2006 and 2010 cycles of the HBSC survey andprovided full responses to the life-time cannabis use items(Table 1). There was sufficient variability in individualand country-level predictors to permit meaningfulsubanalyses by gender and time, and to build variousregression models.
Trends in cannabis use
The prevalence of frequent life-time use of cannabisvaried widely by country, gender and survey cycle(Table 2a,b). The 10 countries with the greatest increases(2002–2010) in terms of GPD per capita were Russia,Ukraine, Slovakia, Latvia, Lithuania, Croatia, Estonia,Czech Republic and FYR Macedonia; Slovenia ranked 13and Hungary 14 out of 30 (data not shown). Frequent
cannabis consumption stabilized or rose in all these coun-tries. In high GPD western/southern European and NorthAmerican countries, frequent cannabis use generallydeclined, particularly among male adolescents (Belgium,Canada, Denmark, France, Germany, Ireland, Spain,Switzerland, United Kingdom, United States) and lessoften among female adolescents (France, Ireland, Italy,Netherlands, Portugal, United Kingdom). Boys univer-sally reported higher prevalence levels compared to girls,with notable differences in the reported prevalence levelsacross time. Increases were observed for boys in Austria,FYR Macedonia, Latvia, Lithuania and for girls in Russia.
Shown in Table 3 are the median overall percentagesof frequent users across the 30 participating countries forthe three time-points. Prevalence levels were higheramong boys compared to girls at all time-points. Overall,
the results show a significant decrease in frequent canna-bis use among both and girls between 2002 and 2010.
Main effects analysis
Table 4 shows the results of our Poisson regression mod-elling for the individual-level and country-level as well astemporal predictors of frequent life-time cannabis use. Abivariate correlation analysis confirmed the potentialimportance of all of demographic and social factorsthat had been hypothesized to influence cannabis use apriori. Individual-level risk factors (model 1) for frequentuse included male gender, lower family affluence andincreased frequency of peer contact in the form of eve-nings out with friends or electronic media communica-tions. The country-level risk factor analysis (model 2)
Table 1 Available sample sizes by country (n = 30), gender and Health Behavior in School-Aged Children (HBSC) survey cycle.
showed that perceived availability is a consistent predic-tor of cannabis use compared to GDP per capita. Whenentered simultaneously into the model, perceived avail-ability turned out to be a clear risk factor for frequentcannabis use (RR = 1.40), while GDP per capita was anegative predictor (RR = 0.70). This implies that in highGDP countries where availability is generally high, feweryoung people report frequent use of cannabis than wouldbe expected based on GDP alone, and vice versa.
When the individual predictors were modelledtogether with the country-level factors, the findingsobserved in models 1 and 2 were generally replicated(model 3), while some estimates were slightly attenuated.The time variable (survey cycle) was then added to themultivariate model. A decline in frequent use was evidentwith time. Observed relations with the individual-level
predictors remained the same as before and perceivedavailability remained associated with frequent use, butthe relationships with GDP became weak and statisticallynon-significant (model 4).
Interactions with time
In model 5, we present interactions with time (surveycycle) to test whether the associations of individual-leveland country-level factors with cannabis use were similaracross survey cycles. The survey cycle year 2002 was usedas a referent group in these analyses. There was no signifi-cant interaction between survey cycle and frequent elec-tronic communications with friends; hence, this term wasdropped from the model. The remaining interaction termswere retained either because a statistically significant
Table 2a Prevalence rates of frequent (>40 times) use of cannabis in life-time and temporal trend, by country: 15-year-old males.
Country
Rate per 100 males Temporal trend (change per 4 year cycle)
interaction was identified or because they were par-ticularly relevant in terms of our a priori theories.
Interactions of survey cycle (2010 versus 2002 only),with gender FAS and GDP per capita were statistically
significant, while interactions between frequency of peercontact (evenings out with friends) or perceived availabil-ity of cannabis and survey cycle were non-significant.The models identified stronger associations between
Table 2b Prevalence rates of frequent (>40 times) use of cannabis in life-time and temporal trend, by country: 15-year-old females.
Country
Rate per 100 females Temporal trend (per 4 year cycle)
aModelled change in adjusted beta for frequent life-time frequent cannabis use, per 4-year cycle. bAge/gender-adjusted relative risks of frequent life-timecannabis use, per 4-year cycle. cModel did not converge. dEstimated using traditional sample down-weighting methods. RR: relative risk; CI: confidenceinterval; SE: standard error.
Table 3 Summary of temporal trends in frequent (>40 times) life-time cannabis use among 15-year-olds, by gender and HealthBehavior in School-Aged Children (HBSC) survey cycle.
Overall median prevalence per 100 participantsfor the 30 countries, by gender and survey cycle
Number of countries reporting significant lineartrend between 2002 and 2010 (P < 0.05)
gender and cannabis use in the later cycles, suggestingthat the effects of male gender were more pronouncedover time. This strong overall pattern was not consistentacross all countries, with some countries demonstratinga narrowing gap (e.g. Belgium, Canada, Czech Republic,Denmark, Estonia, Germany, Poland, Russia, Spain) andothers a widening gap (e.g. Austria, Finland, France,Hungary, Ireland, Italy, the Netherlands, Portugal,Ukraine, United Kingdom) in terms of changes in therelative male/female difference in cannabis use in 2010compared with 2002 (data not shown). For GDP percapita and FAS, the models identified weaker associationsbetween higher levels of societal wealth or family afflu-ence and cannabis use in 2010 compared to 2002(Table 4), indicating waning effects of GDP and FASover time.
DISCUSSION
First, this study explored cannabis use trends among15-year-old boys and girls in 30 European and NorthAmerican countries between 2002 and 2010. Overall, asignificant decline occurred. Particularly in affluentcountries in western and southern Europe and NorthAmerica (Belgium, Canada, Denmark, France, Germany,Ireland, Italy, the Netherlands, Portugal, Spain, UnitedKingdom, United States), a decrease in frequent cannabisconsumption was observed among boys and/or girls.Conversely, stabilization or even increases in cannabis usewere found particularly in the emerging market countriesthat have recently experienced a rapid increase in theirGDP. In three of the 12 former communist countriesin eastern, central and southern Europe, cannabis useincreased among boys (FYR Macedonia, Latvia, Lithu-ania), and in one it increased among girls (Russia). Inthe remaining nine countries, cannabis use stabilizedover time.
Secondly, we tested whether societal and individualfactors predicted differences in cannabis use. Country-level factors of GDP per capita and perceived availabilityboth related positively to cannabis use, indicating that inricher countries, in countries where cannabis is readilyavailable (which increases as social wealth increases), useis higher. A significant relation was also found for indi-vidual factors such as gender, family affluence and peercontacts, implying that males, adolescents from less afflu-ent families and adolescents with frequent peer contactsuse more cannabis.
Thirdly, we examined gender in relation to cannabisuse. We had expected to find a closing gender gap,but our results did not corroborate this assumption.Although male and female consumption patternsstarted to show more similarity in some countries (e.g.Belgium, Canada, Czech Republic, Denmark, Estonia,
Germany, Poland, Russia, Spain), in others the gapwidened (e.g. Austria, Finland, France, Hungary,Ireland, Italy, the Netherlands, Portugal, Ukraine, UnitedKingdom), and across the whole sample cannabisbecame ever more characteristic of males. An overalldecline was found for both genders, but this decline wassteeper for girls compared to boys.
A potential explanation for this rather surprisingoverall finding may be found in a substance use ‘normali-zation thesis’ proposed by Parker et al. in the late1990s [8]. These authors use the term ‘substance usenormalization’ to describe widespread alcohol and othersubstance use among well-adjusted and successful,goal-orientated, non-risk-taking young people. The nor-malization thesis suggests that high substance use preva-lence rates are associated with a shift in the recruitmentof substance users from risky, deviant segments to non-risky, well-adjusted segments of the youth population.Conversely, then, decreasing substance use rates mayhave an effect in the opposite direction. With decliningrates of cannabis use, cannabis may become a more non-mainstream drug of choice. ‘De-normalization’ of can-nabis use would not only re-install an older situation inwhich boys are more prone to cannabis use than girls butalso, because a higher proportion of this male user groupis characterized by problem behaviour, the decreasingcannabis-using scene may become unattractive for girls.As risk-taking increases social status among boys [19], itmay be easier for boys to remain part of a cannabis-usingscene than for girls. Further research should explorewhether the de-normalization of cannabis use hasaffected girls more than it did boys.
Finally, we examined whether potential trickle-downeffects may have occurred. The results indicated that GDPper capita became less important as a predictor of fre-quent cannabis use between 2002 and 2010. Familyaffluence demonstrated the same trend.
In line with our expectations, the study findings sup-ported our assumptions on the role of wealth in cannabisuse and our hypothesis of a between-countries ‘trickling-down’ effect 1. Cannabis consumption became relativelymore common in less wealthy but strongly developingcountries across Europe. Adolescents from less affluentcountries seem to have adopted consumption patternsconsistent with their peers in richer countries. Interest-ingly, the apparent effects of GDP level off in the highGDP western European countries, where cannabis useis declining, sometimes dramatically. Our results alsoprovide evidence for a relationship between family afflu-ence and cannabis use, and support the presumed‘trickling-down’ effect 2. In the 1990s, family affluencewas a positive predictor of frequent cannabis use, butnow cannabis use has emerged as a more commonbehaviour among adolescents from less affluent families,
a trend that has strengthened in the first decade ofthe new century.
Thus, both high GDP and high FAS were less stronglyrelated to frequent cannabis use in 2010 compared to2002, and an analogous situation with observed changesin smoking prevalence has become visible. Historically,tobacco use was more prevalent in countries with highersocietal wealth and among individuals with higher SES.More recently, however, poorer countries and individualswith lower SES levels have followed the pattern laid out bymore affluent countries and groups. Nowadays, tobaccouse tends to be more prevalent in poorer countries andamong poorer individuals in Europe and North America[20–22]. As the route of administration is most oftensimilar for tobacco and cannabis, i.e. cannabis is usuallysmoked with tobacco, the decline in tobacco use in richercountries and among higher SES youth may be closelyrelated to the observed decline in adolescent cannabisuse.
Both for tobacco and cannabis, the recent decrease inespecially richer countries and among higher SESgroups may be explained by the recently increasedattention for, and knowledge of, the harmful effects ofsubstance use for young people and the subsequentimplementation of prevention measures aimed atreducing substance use (e.g. European Commission,2009 [23]). According to Mackenbach & McKee [24],wealthy countries are more likely to implement suchmeasures because ‘people in more advanced industrial-ized societies have been shown to shift their prioritiesfrom basic economic and physical security towards sub-jective well-being, self-expression and quality of life’(p. 196). This implies that they ‘look more to the futureand invest in measures that will enhance future health’(p. 196). Thus, while wealth in earlier decades fosteredadolescent substance use due to increased opportunitiesfor use (i.e. because of increased availability and theexistence of a flourishing youth culture), nowadaysnational health policies in wealthy countries mayhave contributed to the observed decrease of adolescentcannabis use.
Limitations
This study has some limitations. First, this study assumed‘trickling-down’ processes from richer to poorer countriesand from more affluent to less affluent families. Althoughour results did not bring forward evidence that contra-dicted these potential trends, we did not measure‘trickling-down’ effects directly. Our study design did notinvolve the measurement of modelling, imitation ortransmission of cannabis use behaviours from onecountry to another or from affluent to less affluent youth.Future studies should incorporate such measures as a
more direct test of such ‘trickling-down’ theories. Sec-ondly, in this study, we did not investigate several possibledeterminants of frequent cannabis use, including person-ality factors, such as sensation-seeking and disinhibitionor genetic and biological markers. Although we includedan important set of social and individual factors in ourmodels and showed that they contributed to cannabis useindependently, a more elaborate model of cannabis useshould also include additional biological, genetic and per-sonality factors, as well as their interactions. Thirdly, weonly had at our disposal life-time measures of cannabisuse, and we could therefore not discriminate betweencurrent frequent users and youth that may have experi-mented with the drug at a lower frequency across alonger period of time. However, our study populationinvolved relatively young, 15-year-old students. The2010 HBSC data show that, for the grand majority, life-time use (17% of the sample) is close to use during thepast year (13%), indicating that most of them havestarted using cannabis only recently [16]. Fourthly, itcannot be ruled out that the results could in fact be par-tially attributable to different response rates betweencountries. These were not recorded centrally for earlieryears of the survey for all countries, and it is therefore notfully possible to account for these analytically due tomissing response rate data. Analyses of the most com-plete (2010) data suggest that, if anything, higher surveyresponse rates were associated with lower use of canna-bis, although these results were not statistically signifi-cant (r = −0.36; n = 29; P = 0.06 for boys; r = −0.28;n = 29; P = 0.14 for girls).
CONCLUSION
The overall decrease in frequent cannabis use observed inour full study sample is reassuring. Frequent cannabisuse, particularly at an early age, is a risk factor for can-nabis dependence and misuse, and it may function as agateway to use of other illicit substances. Substantialdecreases in cannabis use that now occur in concert withdecreasing tobacco and alcohol use [16] may translateinto lower levels of substance abuse and hence improvedhealth among adolescents and young adults. However,we did not find a decline in the gender gap, with malesreporting higher cannabis use prevalence than girlsoverall and in most countries. Furthermore, a ‘trickling-down’ from high GDP to low GDP countries and fromadolescents from more and less affluent families mayinvolve new risks. Health and wellbeing of adolescentsfrom less affluent circumstances are less positive com-pared to their peers from richer countries and families[25]. The stabilization or even increase in cannabis use,for example, in eastern, central and southern Europe hasthe potential to impair the health of young people already
at higher risk to be unhealthy. Last, but not least, maleadolescents have always been at higher risk for excessiveuse and dependence, and now that frequent cannabis useis concentrated in this group, relatively more users mayface health problems. Future studies should thereforeclosely monitor tendencies for ‘trickling-down’ and ‘de-normalization’ effects in frequent cannabis use as funda-mental indicators of substance use and health inadolescent populations.
Declaration of interests
None.
Acknowledgements
This research was supported (in part) by grants from theCanadian Institutes of Health Research and the Heartand Stroke Foundation of Canada (MOP 97962; PCR101415, Canada), Utrecht University, the Netherlands,and the Intramural Research Program of the EuniceKennedy Shriver National Institute of Child Health andHuman Development (United States).
References
1. Ter Bogt T., Schmid H., Nic Gabhainn S., Fotiou A.,Vollebergh W. Economic and cultural correlates of cannabisuse among mid-adolescents in 31 countries. Addiction2006; 101: 241–51.
2. Johnston L. D., Bachman J. G., Schulenberg J. E. Monitoringthe Future National Results on Adolescent Drug Use: Overviewof Key Findings, 2011. Ann Arbor: Institute for SocialResearch, University of Michigan; 2012, p. 85.
3. Hibell B., Guttormsson U., Ahlström S., Balakireva O.,Bjarnason T., Kokkevi A. et al. The 2011 ESPAD Report:Substance Use among Students in 36 European Countries.Stockholm: The Swedish Council for Information onAlcohol and Other Drugs (CAN); 2012.
4. Petraitis J., Flay B. R., Miller T. Q. Reviewing theories ofadolescent substance use—organizing pieces in the puzzle.Psychol Bull 1995; 117: 67–86.
5. Fergusson D. M., Boden J. M., Horwood L. J. The develop-mental antecedents of illicit drug use: evidence from a25-year longitudinal study. Drug Alcohol Depend 2008; 96:165–77.
6. Schaap M. M., Kunst A. E., Leinsalu M., Regidor E., Espelt A.,Ekholm O. et al. Female ever-smoking, education, emanci-pation and economic development in 19 European coun-tries. Soc Sci Med 2009; 68: 1271–8.
7. Holmila M., Raitasalo K. Gender differences in drinking:why do they still exist? Addiction 2005; 100: 1763–9.
8. Parker H., Aldridge J., Measham F. Illegal Leisure: The Nor-malization of Adolescent Recreational Drug Use. London:Routledge; 1998.
9. Kuntsche E., Kuntsche S., Knibbe R., Simons-Morton B.,Farhat T., Hublet A. et al. Cultural and gender convergencein adolescent drunkenness: evidence from 23 European andNorth American countries. Arch Pediatr Adolesc Med 2010;165: 152–8. archpediatrics. 2010.191 v1.
10. Simons-Morton B. G., Farhat T., ter Bogt T. F. M., Hublet A.,Kuntsche E., Nic Gabhain S. et al. Gender specific trends inalcohol use: cross-cultural comparisons from 1998 to 2006in 24 countries and regions. Int J Public Health 2009; 54:199–208.
11. Currie C., Levin K. A., Kirby J. L. M., Currie D. B.,Van der Sluijs W., Inchley J. C. Health Behaviour in School-aged Children: World Health Organization CollaborativeCross-National Study (HBSC): findings from the 2010 HBSCsurvey in Scotland. 2012.
12. Hibell B., Guttormsson U., Ahlström S., Balakireva O.,Bjarnason T., Kokkevi A. et al. The 2007 ESPAD report.Substance use in 35 European countries. Stockholm:Swedish Council for Information on Alcohol and OtherDrugs (CAN); 2009.
13. Daniel J. Z., Hickman M., Macleod J., Wiles N.,Lingford-Hughes A., Farrell M. et al. Is socioeconomicstatus in early life associated with drug use? A systematicreview of the evidence. Drug Alcohol Rev 2009; 28: 142–53.
14. Kuntsche E. N., Delgrande Jordan M. Adolescent alcoholand cannabis use in relation to peer and school factors.Results of multilevel analyses. Drug Alcohol Depend 2006;84: 167–74.
15. Roberts C., Freeman J., Samdal O., Schnohr C. W., De LoozeM. E., Nic Gabhain S. et al. The Health Behaviour in School-Aged Children (HBSC) Study: methodological developmentsand current tensions. Int J Public Health 2009; 54: 140–50.
16. Currie C., Zanotti C., Morgan A., Currie D., De Looze M.,Roberts C. et al. Social Determinants of Health and Well-beingamong Young People. Health Behaviour in School-aged Children(HBSC) Study: International Report from the 2009/2010Survey. Copenhagen: World Health Organization RegionalOffice for Europe; 2012.
17. Health Behavior in School-Aged Children (HBSC). ProtocolsHBSC Study. 2013. Available at: http://www.hbsc.org/methods/index.html (accessed 29 August 2013). (Archivedat http://www.webcitation.org/6JEBAHr4X on 29 August2013).
18. World Bank. World Bank per capita (current US$). WorldBank national accounts data and OECD National Accountsdata files. 2012.
19. Moffitt T. E. Adolescence-limited and life-course-persistentantisocial behavior: a developmental taxonomy. Psychol Rev1993; 100: 674–701.
20. Lopez A. D., Collishaw N. E., Piha T. A descriptive model ofthe cigarette epidemic in developed countries. Tob Control1994; 3: 242–7.
21. Hublet A., De Bacquer D., Valimaa R., Godeau E., Schmid H.,Rahav G. et al. Smoking trends among adolescents from1990 to 2002 in ten European countries and Canada.BMC Public Health 2006; 6: 280.
22. Huisman M., Kunst A. E., Mackenbach J. P. Educationalinequalities in smoking among men and women aged 16years and older in 11 European countries. Tob Control 2005;14: 106–13.
23. European Commission. Report on the implementation ofthe Council Recommendation of 30 November 2009 onSmoke-free Environments (2009/C 296/02). 2009.
24. Mackenbach J. P., McKee M. A comparative analysisof health policy performance in 43 European countries.Eur J Public Health 2013; 23: 195–201.
25. Marmot M. G. Status syndrome: a challenge to medicine.JAMA 2006; 295: 1304–7.
