Abstract
Background:
National programs that reduce adolescent cannabis use warrant renewed attention in light of current discussions to reform cannabis legislation, including the possibility of legalization for recreational use. This study measures the size of a decrease in a country’s prevalence of adolescent cannabis use that accompanies a decrease in its prevalence of adolescents who had ever smoked a cigarette.
Methods:
Data are from the European School Survey Project on Alcohol and Other Drugs (ESPAD), which is a collaborative effort of more than 40 European countries to surveil adolescent substance use. This study uses data from the seven survey administrations in 1995, 1999, 2003, 2007, 2011, 2015, and 2019. The main analysis is a fixed-effect regression analysis of country-level, four-year changes in adolescent lifetime cannabis use prevalence on country-level, four-year changes in adolescent lifetime cigarette use prevalence.
Results:
Decreases in the national prevalence of adolescents who had ever smoked a cigarette were accompanied by decreases half as large in national prevalence of adolescent lifetime cannabis use.
Conclusion:
For European countries considering the legalization of adult recreational cannabis use, tobacco control can offer a tool to help counter potential increases in cannabis use among adolescents.
INTRODUCTION
National programs that reduce adolescent cannabis use warrant renewed attention in light of current discussions by European policymakers to revisit and possibly reformulate their national cannabis policies (European Monitoring Centre for Drugs and Drug Addiction, 2023). Many European countries have recently legalized medical use and, in addition, six are undergoing significant policy developments and conducting pilot tests to provide information for the potential implementation of different models of cannabis legalization (European Monitoring Centre for Drugs and Drug Addiction, 2023). Governments in Czechia, Germany, Luxembourg, and Switzerland have announced plans for the regulated supply of cannabis for recreational use; in 2021 Malta passed a law permitting the limited growing of cannabis at home and in registered non-profit growing clubs, as well as its use in private homes; and the Netherlands is implementing a cannabis policy experiment of regulating the supply chain for cannabis “coffee shops” in different cities starting in 2024 (European Monitoring Centre for Drugs and Drug Addiction, 2023). With this growing momentum it seems increasingly possible that at least one European country may set up legal retail cannabis shops for adult recreational use, as has taken place in Canada and about half of the U.S. states.
One major concern about cannabis legalization is that it may increase levels of cannabis use among adolescents and children (American Academy of Child & Adolescent Psychiatry, 2017; American Academy of Pediatrics, 2004; American Society of Addiction Medicine, 2020; Haines-Saah et al., 2019; Laqueur et al., 2020). Youth may interpret legalization as a sign that cannabis use is legitimate, accepted, and safe. Adolescents who adopt such beliefs about substance use are significantly more likely to use substances in the future (Miech et al., 2023). In addition, the large and influential cannabis industry created by legalization may invest heavily in marketing and advertising to increase cannabis demand—and prevalence—across all ages (Hall et al., 2019).
Scientific analyses of legalization experiences so far in other countries have not disarmed this concern for increased use among adolescents. It is difficult to predict what will happen in Europe because no European country has yet formally legalized recreational cannabis use, and therefore it is not possible to directly observe any subsequent changes in the prevalence of cannabis use among adolescents. A meta-analysis of other governments around the world that have liberalized cannabis laws concludes that a moderate increase in adolescent cannabis prevalence may follow after legalization of recreational use, although the authors emphasize that the conclusion is tentative and more studies are needed (Melchior et al., 2019). Importantly, these authors confirm findings from other studies showing that relaxation of other laws restricting cannabis use, such as decriminalization and allowing medical cannabis use, had little effect on adolescent cannabis prevalence (Benedetti et al., 2021; Gabri et al., 2022). In all, these results suggest that legalization may have an effect on adolescent cannabis prevalence that is distinct from other, related cannabis policies that loosen cannabis restrictions to a lesser degree. This effect may not be immediate if the impact of a new, legal cannabis industry is delayed while it works out growing pains, such as establishing a regular source of cannabis supply and establishing credit with international banks that serve countries in which cannabis use remains illegal. Also, it is worth reiterating that the effect of legalization may be yet to come if the new, legal cannabis industry decides to mount a substantial marketing campaign to increase cannabis use.
We hypothesize that tobacco control offers a tool to help address this concern by reducing the pool of adolescents at risk for cannabis use. Cigarette smoking and cannabis use overlap substantially. Practically all cannabis users have smoked a cigarette (90%, estimated by Agrawal et al., 2012), and a substantial portion of cigarette smokers have used cannabis (up to 47%, as estimated by Agrawal et al., 2012). If cigarette smoking is a risk factor for future cannabis use, reducing the number of adolescents who smoke cigarettes may also reduce the number who will go on to use cannabis.
This hypothesis focuses on population-level reductions of cigarette smokers and, in essence, tests the cumulative net impact of individual-level processes theorized to link cigarette and cannabis use (Agrawal et al., 2012). Cannabis levels will fall with declining numbers of cigarette users to the extent that adolescents who never use cigarettes (a) are less likely to become known as drug users and join drug-using peer networks (Kosterman et al., 2000), (b) avoid exposure to nicotine-related processes that can biologically “prime” the adolescent brain’s reward system for substance use (Kandel & Kandel, 2014; Volkow & Li, 2005), (c) are socially and biologically unaccustomed to smoking/inhaling and are therefore less likely to initiate cannabis use (Agrawal et al., 2012), and (d) have been exposed to tobacco-control media campaigns and educational curricula that reduce their substance use in general (Tremblay et al., 2020). Any or all of these individual-level processes may be at work to reduce cannabis use in countries with declining levels of cigarette smoking.
The competing hypotheses are that adolescent cannabis levels will not change, will increase, or are confounded by changes in alcohol prevalence. Cannabis prevalence may remain steady as cigarette prevalence declines if most adolescent cannabis use stems from an independent, individual-level propensity for cannabis use, which can be either genetic or environmental in nature (Kendler et al., 2007; Young et al., 2006). It is also possible that cannabis use could increase if adolescents who would have otherwise smoked cigarettes choose to substitute cannabis use instead (Amos et al., 2004). Finally, falling cannabis use among adolescents may be driven primarily by declines in alcohol use—or both by declines in alcohol and declines in cigarette use—and may not track specifically with changes in cigarette use per se.
A unique European data set offers an unprecedented opportunity to examine whether, and by how much, changes in adolescent cigarette use move with changes in adolescent cannabis use. While smoking declines have taken place in Europe, ESPAD conducted a quadrennial, national survey of substance use, including cannabis and cigarettes, for dozens of European countries. A focus on changes within countries over time is important because each country serves as its own control. Consequently, results using this approach are free from the influence of country-level factors that are constant over time and may influence both adolescent cannabis use and adolescent cigarette use. These factors include country-level economic wealth, basic public health infrastructure, and long-standing cultural attitudes toward substance use. Note that in this research design these factors, and indeed all time-invariant country-level characteristics, are controlled even though they are not measured.
In sum, to our knowledge this study is the first to document the magnitude of change in adolescent cannabis prevalence that accompanies changes in adolescent cigarette prevalence. Europe provides a unique scientific opportunity to examine this research question because of its substantial variation in adolescent cannabis and cigarette use across dozens of European countries over more than two decades, all of which has been tracked by the ESPAD project.
METHODS
Data are from the European School Survey Project on Alcohol and Other Drugs (ESPAD), which is a collaborative effort of more than 40 European countries to surveil adolescent substance use. Every four years since 1995 it has administered standardized, in-school, self-reported, cross-sectional surveys on substance use to respondents turning age 16 in the survey year. All students in the school are eligible to be surveyed. This study uses data from the seven survey administrations in 1995, 1999, 2003, 2007, 2011, 2015, and 2019. Response rates vary by year and by country and have been high, with an average school participation rate of 82% and a student participation rate of 86% in 2019 (ESPAD Group, 2021). This project consisted solely of secondary data analysis and did not involve human subjects.
Table 1 lists the 43 countries in the analysis pool and the years they contributed data. Included are surveys from all countries with at least two consecutive four-year surveys that had questions on lifetime use of cigarettes, lifetime use of cannabis, and lifetime use of alcohol. The analysis focuses on the country-level means of these variables, using data from 613,192 surveys collected in 210 four-year country periods from 43 countries with at least two consecutive surveys with questions on ever cigarette smoking, ever cannabis use, and ever alcohol use..
Table 1:
Survey Years in Analyses, by Country
| Country | 1995 | 1999 | 2003 | 2007 | 2011 | 2015 | 2019 |
|---|---|---|---|---|---|---|---|
| Albania | -- | -- | -- | -- | yes | yes | -- |
| Austria | -- | -- | yes | yes | -- | yes | yes |
| Bulgaria | -- | -- | yes | yes | yes | yes | yes |
| Croatia | -- | yes | yes | yes | yes | yes | yes |
| Cyprus | -- | -- | yes | yes | yes | yes | yes |
| Czechia | yes | yes | yes | yes | yes | yes | yes |
| Denmark | -- | yes | yes | yes | yes | yes | yes |
| Estonia | -- | -- | yes | yes | yes | yes | yes |
| Faroes | yes | yes | yes | -- | yes | yes | yes |
| Finland | yes | yes | yes | yes | yes | yes | yes |
| France | -- | -- | -- | yes | yes | yes | yes |
| Georgia | -- | -- | -- | -- | -- | yes | yes |
| Greece | -- | yes | yes | yes | yes | yes | yes |
| Hungary | yes | yes | yes | yes | yes | yes | yes |
| Iceland | yes | yes | yes | yes | yes | yes | yes |
| Ireland | -- | -- | -- | yes | yes | yes | yes |
| Italy | -- | yes | yes | yes | yes | yes | yes |
| Latvia | -- | yes | yes | yes | yes | yes | yes |
| Liechtenstein | -- | -- | -- | -- | yes | yes | -- |
| Lithuania | -- | -- | yes | yes | yes | yes | yes |
| Malta | -- | yes | yes | yes | yes | yes | yes |
| Monaco | -- | -- | -- | yes | yes | yes | yes |
| Moldova | -- | -- | -- | yes | yes | yes | -- |
| Montenegro | -- | -- | -- | yes | yes | yes | yes |
| Netherlands | -- | yes | yes | yes | yes | yes | yes |
| Belgium (Flanders) | -- | -- | yes | yes | yes | yes | -- |
| Norway | yes | yes | yes | yes | yes | yes | yes |
| Poland | yes | yes | yes | yes | yes | yes | yes |
| Portugal | yes | yes | yes | yes | yes | yes | yes |
| Romania | -- | yes | yes | yes | yes | yes | yes |
| Serbia | -- | -- | -- | yes | yes | -- | -- |
| Bosnia and Herzegovina (FBiH) | -- | -- | -- | yes | yes | -- | -- |
| Bosnia and Herzegovina (RS) | -- | -- | -- | yes | yes | -- | -- |
| Slovakia | yes | yes | yes | yes | yes | yes | yes |
| Slovenia | yes | yes | yes | yes | yes | yes | yes |
| Sweden | yes | yes | yes | yes | yes | yes | yes |
| Switzerland | -- | -- | yes | yes | -- | -- | -- |
| Ukraine | yes | yes | yes | yes | yes | yes | yes |
| North Macedonia | -- | -- | -- | -- | -- | yes | yes |
| United Kingdom | yes | yes | yes | yes | yes | -- | -- |
| Isle of Man | -- | -- | yes | yes | -- | -- | -- |
| Germany (Bavaria) | -- | -- | yes | yes | yes | yes | yes |
| Russian Fed. (Moscow) | -- | yes | yes | yes | yes | -- | -- |
Note: Analysis based on a total of 210 country-year periods and consists of 43 countries with at least two consecutive surveys with questions on ever cigarette smoking, ever cannabis use, and ever alcohol use. The analysis pool is the 165 country-years above that are preceded by a survey in the previous four-year period (necessary to compute change since last survey).
Statistical Analysis
The analytical plan consists of two parts. First, we present a scatterplot of country-level, four-year changes in the prevalence of adolescents who ever smoked a cigarette (x-axis) with the concurrent period change in the prevalence of adolescents who ever used cannabis (y-axis). Second, we present results from fixed-effect regression analysis of country-level, four-year changes in adolescent lifetime cannabis use prevalence on country-level, four-year changes in adolescent lifetime use of cigarettes. Additional fixed-effects regression analyses control for concurrent four-year country-level changes in lifetime prevalence of adolescent alcohol use. Supplemental sensitivity analyses provide a parallel set of fixed-effects regression analyses that: stratified by sex; weighted each country by its population size; and examined potential interaction among the model variables. We implement a fixed-effect regression by including an indicator variable for each country except one and for all four-year periods except one (the reference country and the reference time period). The indicator variables for country control for nation-to-nation variation in all time-invariant, national characteristics that potentially may affect country-specific mean levels and average rates of change in adolescent substance use.
RESULTS
Figure 1 is a country-level scatterplot of four-year changes in prevalence of ever smoked a cigarette with four-year changes in prevalence of lifetime cannabis use. The two tracked together with a Pearson correlation of .58. These results show that as lifetime cigarette smoking prevalence increased or decreased, so too did lifetime cannabis use prevalence.
Figure 1:
Scatterplot of Four-Year, National Changes in Prevalence Ever Smoked a Cigarette with Four-Year, National Changes in Prevalence Ever Used Cannabis among Adolescents Age 15-16, Years 1995-2019
Patterns by quadrants of the scatterplot warrant note. In practically all four-year periods when lifetime smoking increased so too did lifetime cannabis use, as indicated by the upper and lower right quadrants. This pattern holds for 94% (29 out of 31) of four-year periods when lifetime smoking prevalence increased. In the other two four-year periods lifetime cannabis prevalence was little changed, with decreases of one percentage point or less.
In four-year periods when prevalence of lifetime smoking decreased, as denoted in the upper and lower left quadrants, lifetime cannabis prevalence decreased in the majority of cases (57%; 76 out of 134 instances).
The upper left quadrant shows that decreases in lifetime smoking prevalence over a single four-year period do not guarantee an accompanying decrease in lifetime cannabis prevalence. In 58 four-year periods, a decrease in lifetime smoking prevalence was accompanied by increases in lifetime cannabis use. In these cases it is possible that a longer, sustained period of cigarette decreases may result in declines for lifetime cannabis prevalence. In 40 of these 58 four-year periods, decreases in cigarette prevalence extended into the next four-year period. And in 68% of these extensions, lifetime cannabis prevalence decreased in this second four-year period (analyses not graphed).
Table 2 presents results from fixed-effects country-level regression of four-year changes in lifetime adolescent cannabis prevalence on four-year changes in lifetime cigarette prevalence. In Model 1 the coefficient for changes in lifetime cigarette use indicates that a one percentage point change in cigarette prevalence tracked, on average, with a .49 percentage point change in cannabis use in the same direction. Specifically, if the change was a decrease in lifetime cigarette prevalence then lifetime cannabis use decreased half as much, and if lifetime cigarette prevalence increased then lifetime cannabis also increased half as much. Model 2 adds to the regression model four-year changes in lifetime adolescent alcohol use, which had a small coefficient of 0.12, was not statistically significant, and its inclusion had negligible effect on the coefficient for lifetime cigarette use (0.52 in Model 2 compared to 0.49 in Model 1).
Table 2:
Change in Country-Level Proportion Ever Used Cannabis as a Function of Change in Country-Level Proportion Never Smoking and Never Drank Alcohol among Adolescents Age 15-16; Results from Fixed-Effects Regression Analysis
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| Coef. | 95% CI | Coef. | 95% CI | |
| Δ National Proportion Never Smoked a Cigarette since Previous Survey, Four Years Earlier | 0.49** | (0.33 to 0.65) | 0.52** | (0.35 to 0.69) |
| Δ National Proportion Never Drank Alcohol since Previous Survey, Four Years Earlier | 0.12 | (−0.32 to 0.09) | ||
| Calendar Year | ||||
| 1999 (reference) | ||||
| 2003 | −0.01 | (−0.04 to 0.01) | −0.01 | (−0.04 to 0.01) |
| 2007 | −0.02 | (−0.05 to 0.01) | −0.02 | (−0.05 to 0.01) |
| 2011 | −0.03 | (−0.05 to 0.001) | −0.03* | (−0.06 to −0.002) |
| 2015 | −0.01 | (−0.04 to 0.02) | −0.01 | (−0.05 to 0.02) |
| 2019 | −0.03 | (−0.05 to 0.003) | −0.03 | (−0.06 to 0.001) |
| Constant | 0.05 | (−0.03 to 0.13) | 0.07 | (−0.02 to 0.15) |
Note: First year of data is 1995. Analysis focuses on changes since last four-year survey, and therefore first possible year to included in the analysis pool is 1999 (to compare changes since 1995).
Note: Analysis includes a separate indicator variable for each country except one (the reference country); coefficients of these indicator variables not shown.
Tables S1 and S2 in the Appendix consider the influence of population size on the study results. These results weight each country by population size so that larger countries have larger analytical influence; this contrasts with the main analyses of the study in which each country had an equal influence. Table S1 presents the population size of each country in the analysis, and Table S2 presents results from a fixed-effects regression that weighted each country by its population size. The coefficient of 0.77 in Model 1 of Table S2 indicates that with this weighted approach a one point change in a country’s prevalence of lifetime adolescent cigarette smoking moved with an accompanying 0.77 percent change in lifetime cannabis prevalence in the same direction during that same time period. Model 2 of Table S3 shows that taking into account four-year changes in lifetime adolescent alcohol use had negligible effect on the weighted results. These sensitivity analyses show larger declines in adolescent cannabis prevalence with declines in lifetime cigarette prevalence than did the unweighted approach.
The analyses tested if survey year moderated the study results by including tests of multiplicative interaction terms for each year with the four-year changes in cigarette prevalence, for both the unweighted and weighted analyses. None of these tests were statistically significant at p<.05 for a two-tailed test adjusted for multiple testing. Additional analyses stratified the sample by females and males in both weighted and unweighted analyses, and the coefficients for four-year changes in adolescent cigarette prevalence were similar across sex and did not significantly differ.
DISCUSSION
Among adolescents, decreases in national lifetime smoking prevalence were accompanied by decreases half as large in national, adolescent lifetime cannabis use. Specifically, a 5 percentage point decrease in lifetime smoking prevalence over a four-year period—the sample average—tracked, on average, with a 2.5 percentage point decrease in lifetime cannabis use. We are not aware of other studies showing that national declines in adolescent lifetime cannabis use track with national declines in adolescent lifetime cigarette use.
Many countries had substantial declines in lifetime smoking prevalence over the 25 year study period as they put together multiple four-year declines in lifetime smoking prevalence. These sustained declines were accompanied, on average, by substantial cumulative declines in the prevalence of lifetime cannabis use. For example, in Ukraine a 19 point decrease in adolescent lifetime smoking prevalence from 1999 to 2019 (from 69% to 50%) was accompanied by an 11 point decrease in cannabis prevalence (from 19% to 8%). Likewise, in Ireland a 42 point decrease in prevalence of adolescent lifetime smoking from 1995 to 2019 (from 73% to 31%) was accompanied by a 17 point decrease in cannabis prevalence (from 36% to 19%).
These results support the proposition that tobacco control has a spillover effect of cannabis use reduction. We interpret most of the declines in adolescent smoking in Europe as the result of tobacco control policies. The multi-country World Health Organization’s Framework Convention on Tobacco Control (FCTC), which entered into force on February 27, 2005 (Gravely et al., 2017), set in place policies and programs targeted at the reduction of cigarette smoking at the population level. These included increased tobacco taxes, laws prohibiting smoking in public places, implementation of smoking cessation programs, bans on cigarette advertising, promotion, and sponsorship, as well as graphic pictorial warnings on cigarette packaging (Bertollini et al., 2016). Analysis of these policies indicates that cigarette consumption per capita in Europe as a whole was more than 50% lower than would be expected in the absence of the FCTC (Hoffman et al., 2019). These policies reduced the prevalence of cigarette smoking, and in so doing reduced a major risk factor associated with cannabis use.
A strength of the study’s analysis is that it controls major, potential sources of confounding in two ways. First, the fixed-effect analysis reduces the plausibility of time-invariant, country-level characteristics as competing explanations for the study results. This method takes into account time-invariant characteristics even if they are not measured, including factors such as long-standing cultural attitudes toward drug use and public health infrastructure. Second, at the country level the analyses controlled time-varying changes in adolescent alcohol use, which had a negligible effect on the results and did not play a confounding or mediating role. These results provide evidence against the possibility that a decline in use of other important substance—not just cigarettes—will carry with it a decline in cannabis use. They also address and provide evidence against the possibility that the study results are part of broader substance use trends rather than being driven by cigarettes specifically; if usage trends for all three were being driven by some larger trend, then both cigarettes and alcohol would be expected to trend with cannabis in near-equal proportion.
Policymakers seeking to reduce or prevent adolescent cannabis use have few effective tools at their disposal, and these results suggest that tobacco control can help address this gap. Specific tobacco control policies to implement are known, numerous countries can provide multiple example roadmaps and perhaps even technical assistance for implementation, and the results of this study provide guidance on the expected size of adolescent cannabis reduction that will accrue.
The results point to the importance of future research to identify the factors that moderate the declines in adolescent cigarette use and the associated declines in adolescent cannabis use. The decreases in adolescent cannabis use that accompanied decreases in smoking prevalence were larger than average for some countries and smaller than average for others. Specification of the moderating factors at work can help countries tailor the tobacco control policies they adopt, and how they adopt them, to their national context and culture.
Additional areas for future research also include specifying which components of tobacco control policies most strongly predict declines in adolescent smoking at the national level, as well as working to identify which of the many individual-level links between cigarette smoking and cannabis use account for declines in cannabis as cigarette smoking decreases at the population level. These two lines of research can inform each other. Countries can serve as case studies to evaluate the individual-level processes at work, and this information can, in turn, inform decisions on which tobacco control policies would be expected to be most effective in different settings.
One limitation of this study is that the repeated, cross-section, observational research design is not sufficient, by itself, to establish causality between successful tobacco control and adolescent cannabis use. Using a research design that would do so, such as a randomized-controlled trial, would face substantial, ethical hurdles because it would require intentionally withholding the proven benefits of tobacco control from a population of adolescents in a control group. Instead, this study aims to add key findings to a broader frame of evidence based on observational studies that, taken as a whole, support cannabis reduction as a spillover effect of tobacco control.
CONCLUSION
As European countries revisit and reconsider cannabis legislation, tobacco control can offer a tool to help counter potential, unintended increases in cannabis use among adolescents.
Supplementary Material
Acknowledgement:
Funding for R.M. was provided by NIDA grant # R01 DA001411 (Richard Miech, Principal Investigator). The authors would like to acknowledge the members of the ESPAD Group who collected the national data (http://www.espad.org/report/acknowledgements) and the funding bodies who supported the international coordination of ESPAD and the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). Special thanks are due to the schoolchildren, teachers and national funding bodies who made this project possible. The authors also acknowledge Institute of Clinical Physiology, CNR, Pisa, Italy who compiled the common ESPAD trend database (1995–2019). There were no conditions related to the publication of the results from any of the funding agencies.
Contributor Information
Richard Miech, University of Michigan.
Steven G. Heeringa, University of Michigan
Sabrina Molinaro, Institute of Clinical Physiology, National Research Council - CNR, Via Moruzzi 1 - 56124 Pisa (IT).
Elisa Benedetti, Institute of Clinical Physiology, National Research Council - CNR, Via Moruzzi 1 - 56124 Pisa (IT).
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