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Official websites use. Share sensitive information only on official, secure websites. HL supervised the statistical analyses, interpreted the results, and drafted and revised the manuscript. ARA performed the primary statistical analyses. AS performed additional statistical analyses and provided statistical consulting. KR provided additional statistical consulting and reviewed and commented on manuscript drafts. MC obtained project funding, conceptualized the study, contributed to the interpretation of results, and provided comments and edits to the manuscript. Corresponding Author: Dr. Hannah Laqueur, hslaqueur ucdavis. In , Uruguay became the first country in the world to legalize recreational cannabis, instituting a non-commercial state regulatory model of production and supply. This study provides the first empirical evidence on its impacts on adolescent use of cannabis and related risks. We use a generalization of the synthetic control method SCM to estimate the impact of legalization in Uruguay on adolescent past year and month cannabis use, perceived availability of cannabis and perceived risk of cannabis use. We compare biennial high school student self-reported survey data from Montevideo and regions in the interior of Uruguay post-legalization — and post initial implementation — to a synthetic counterfactual constructed using a weighted combination of 15 control regions in Chile. We find no evidence of an impact on cannabis use or the perceived risk of use. At the same time, our study period represents a period of transition: pharmacy access, by far the most popular means of access, was not available until the summer of Additional study will be important to assess the longer-term impacts of the fully implemented legalization regime on substance use outcomes. Keywords: Cannabis, legalization, drug policy, adolescent substance use, synthetic control. In December , Uruguay became the first country in the world to legalize the sale, cultivation, and distribution of recreational cannabis, putting it at the forefront of a growing list of nations and states in the U. Unlike the for-profit commercial models that have been adopted in a number of U. Given the unprecedented changes in cannabis policy that are taking place across the globe, and the growing number of jurisdictions considering some form of legalization, it is critical that we understand the impacts of different legalization models on drug use and related health and social outcomes. The present study provides the first empirical evidence on the impact of legalization in Uruguay, examining adolescent cannabis use. Although those under the age of 18 are not legally permitted to purchase or consume cannabis in Uruguay, nor, for that matter, in any other jurisdiction that has legalized, there are a number of mechanisms by which legalization may nonetheless impact adolescent substance use. Unlike cannabis reform legislation in the U. The expressed motivation of the legalization of recreational cannabis was to eliminate the illicit drug trade and its associated violence and public health related harms Cruz et al. As of November, , of an estimated population of 3. Most of the research on the relationship between cannabis legalization and adolescent cannabis use has focused on the impact of medical marijuana laws MML in the United States. Studies have shown that while adolescent use tends to be higher in states that allow medical marijuana Wall et al. More recently, studies have begun to report on the effects of the legalization of recreational cannabis in U. SCM, rather than using a single control unit or the simple average of control units to estimate a counterfactual time trend for the treated unit in the absence of the treatment, creates a weighted average of a set of controls. Weights are generated from pre-intervention data on each outcome of interest such that the weighted combination of control units mirrors the intervention unit as closely as possible during the pre-intervention period Imbens, In so doing, the synthetic control aims to provide a good approximation of how the outcome of interest of the treated unit would have developed if no treatment had taken place. The treatment effect is estimated as the difference between the actual outcomes for the treated unit post- intervention and the counterfactual outcomes from the synthetic control. We compare biennial national high school student self-reported survey data in Montevideo and regions in the interior of Uruguay post-legalization to a synthetic control counterfactual group constructed from a weighted combination of 15 regions in Chile. Chile is similar epidemiologically, socially, economically and culturally to Uruguay. Further, Chile resembles the regulatory status of Uruguay pre-legalization — both countries had decriminalized, but not legalized, cannabis. Our primary analysis considers the post-legalization period from through We also conduct secondary analyses in which we treat as a pre-intervention year and as the first year post intervention. Though the symbolic import of legalization may have had an impact on adolescent use and related risks immediately following legalization, the first substantive means of legal adult access — cannabis clubs and home registration — were not available until several months after the student survey was conducted in Student age in these grades typically ranges from 13 — We exclude improbably ages, restricting the study population to students between the ages of 12 and 21 The National Drug Observatories in each country use a common sampling scheme and instrument, modeled after the Monitoring the Future Surveys in the U. Miech, , allowing for inter-country comparisons. Surveys are carried out approximately every two years and samples are selected via a clustered, multistage stratified design. Survey data collection takes place in school classrooms under strictly confidential procedures. Surveys are self-administered, and take approximately 50 minutes. Surveys include built-in logic and consistency checks. We did not find any substantive changes in rates of school response or student reporting following legalization. We focus on municipalities in the largest metropolitan areas in Uruguay and Chile. The Uruguayan Observatory on Drugs reviews each student survey questionnaire prior to data entry and drops observations for students with highly inconsistent or inaccurate survey responses. The first year of data collection and availability varies by outcome. Student survey response data on past year and past month cannabis use are available from — The survey question regarding perceived risk of frequent use was first asked in and the question regarding perceived availability was first asked in , so our analyses for these outcomes begin in and , respectively. For those years where there was no overlap of data collection between Uruguay and Chile, we interpolated the data using linear interpolation. A table showing data availability and missingness is shown in Table 1 in the Supplementary Materials. Weights are from the models build using pre-intervention biennial survey data through Our primary analysis treats as the first post-intervention year. This was the first year following the passage of the law that legalized the sale, cultivation, and distribution of recreational cannabis for Uruguayan citizens and permanent residents over the age of However, cannabis clubs and home grower registration, the first means by which legal access to cannabis was available, were not in place until August and October of , and the student survey was conducted in the spring of that year. We therefore conduct a set of additional analyses in which we treat as the first post-intervention year. This generalized approach relaxes the restrictions of the standard SCM that the intercept be zero and the weights be non-negative and sum to one. Instead, the approach uses cross-validated Elastic Net regularization to calculate the optimal weight values on the control units so as to minimize the distance between the outcomes for the treated and the control units in the pre-intervention period. This more flexible approach may offer advantages in settings where the standard SCM produces poor pretreatment model fit Li, , as was the case with our data. The optimal values for the Elastic Net tuning parameters in our analyses were chosen via leave one out cross-validation. The performance of the model is then evaluated by computing the mean squared error averaged over all control units, and the values of the tuning parameters are chosen to minimize this cross-validated error. After creating weights, we compare the post-legalization prevalence rates of Uruguay, which comprises a population weighted average of Montevideo and the Interior, to its synthetic control, a weighted combination of the 15 Chilean control units. Given differences in population density, rurality, and means of cannabis access, we also estimate trends separately for Montevideo and the Interior, constructing synthetic controls for each. Complete results for these separate analyses are shown in the Supplementary Materials. SCM, including this generalized approach, precludes the use of traditional asymptotical inference techniques. We then calculate the proportion of control regions with an estimated effect as extreme or more extreme than the difference estimated for Uruguay and its synthetic control. If the post-treatment difference between the actual treated unit and its synthetic control is larger than the difference for most of the placebo units, this provides evidence that the treatment had an effect. Our primary analysis constructs the SCMs using the pre-intervention outcome data for regions in Uruguay and Chile. We conduct sensitivity analyses that incorporate covariates into the construction of the SCMs Results shown in the Supplementary Material. These covariates include the percent of the population under the age of 25, the percent male, unemployment rate, and the percentage with a high school level education or higher. Here, the LME model is first fit on the data with a random intercept for region and fixed effects for all other covariates. The synthetic control outcomes are constructed as the sum of these two parts: a weighted average of the best linear unbiased predictions BLUP for the prevalence rates in Montevideo and the Interior from the LME model, and a weighted average of the residuals from the LME with the weights determined by the Elastic Net SCM. Table 1 shows the weights applied to each Chilean donor region to form the synthetic controls using the pre-legalization data — , — , — , — The weights for the synthetic Uruguay based on pre-intervention through trends are shown in the Supplementary Materials. Figure 1 shows prevalences for Uruguay and its synthetic control for each of our outcomes, with as the first year post-treatment. Table 2 presents the average reported prevalence post-legalization — in Uruguay, for the synthetic control, and the difference between the two. The results of the placebo test are shown in parentheses. Figure 2 shows the trends in Uruguay and the synthetic control, treating as the first post-intervention year, and Table 3 presents the difference in outcomes for these models. Trends in student reported cannabis use and related risks in Uruguay and its synthetic control — Post-Legalization. The number in the parenthesis are the results of the placebo tests. We found no meaningful difference in reported cannabis use past year or past month among adolescents in schools in Uruguay as compared to cannabis use predicted in the absence of legalization by the synthetic control. The placebo tests indicated that these small differences are not statistically meaningful: for reported past year use, 11 out of 15 placebo tests had a difference as large or larger than what we see between Uruguay and the Synthetic, 13 of 15 placebo tests showed a difference as larger or larger for past month cannabis use, and 13 of 15 placebo tests showed a difference as large or larger for frequent use. The estimates are substantively the same in the secondary model — Table 3. Likewise, in the sensitivity analyses incorporating covariates, and in the models estimated for Montevideo and the Interior separately, we found no meaningful differences in cannabis use post or post The sole exception was some indication of a reduction in frequent cannabis use among students in the Interior in the post-implementation — period. The magnitude of the difference was as large or larger in 2 of the 15 placebo tests, offering some indication that the reduction in the Interior was greater than we would expect by chance. The analyses provide some indication that legalization may have led to an increase in student perceptions of cannabis availability. The magnitude of the difference was as large or larger in 2 of the 15 placebo tests, offering some, albeit weak, indication that the increase seen in Uruguay might be larger than the change we would expect by chance. We found the passage and early implementation of recreational cannabis legalization in Uruguay was not associated with changes in the prevalence of adolescent cannabis use or self-reported frequency of use. We did find some indication of an increase in student reports of cannabis availability in the Interior of the country. Given we did not see a rise in use, this increase, insofar as it is real, may simply represent student perceptions of the new state of affairs post legalization given the rise in availability for those other 18 years of age rather than an actual change in how easy it is in fact to obtain cannabis. Alternatively, it could suggest a real change in cannabis availability for youth that has not yet had an impact on adolescent consumption, but merits continued surveillance. Indeed, the Uruguayan student substance use survey found that 6 out of 10 adolescent cannabis users reported consuming cannabis purchased as buds, which is the form of cannabis sold in the legal market Observatorio Uruguayo de Drogas and Junta Nacional de Drogas, Our findings contrast with some studies in U. In all cases, legal access to recreational cannabis is restricted to adults, and therefore may have less direct impact on availability for adolescents and their corresponding use, at least in the short term. The U. We find no such shift among students in Uruguay. The political campaign for legalization in Uruguay explicitly described the law as one aimed at promoting public health, and this orientation might minimize the extent to which legalization reduces perceptions of the risk or stigma associated with cannabis. The absence of an effect of legalization on student cannabis use might also be explained by the post-legalization period that we are studying, a period in which the legalization regime was not yet fully implemented for the vast majority of time. The registry for home-growers began in August and for cannabis clubs in October ; pharmacy sales did not begin until July of Given pharmacies are by far the most popular source of legal cannabis to registered adults, it will be important that future work examine the impacts of the fully implemented legalization regime. The post-legalization follow-up period also represents a statistical limitation of our study. With only two to three survey collection periods post legalization, our analyses are sensitive to year-to-year shifts in the data that may not reflect long-term trends. Additionally, the surveys are conducted biennially, which means we only have at most seven pre-legalization survey periods upon which to develop the synthetic control counterfactual, and for some outcomes, we have fewer. Finally, there are some years of non-overlapping surveys between Uruguay and Chile, requiring linear interpolation. There are additional limitations inherent in the survey data that should be noted. While the substance use measures are drawn from large and representative survey samples that are comparable across multiple years and countries, and we find no evidence of reporting biases related to legalization, the measures are self-reported and there is potential in survey data for response bias. Additionally, the surveys are designed to be representative of secondary school students enrolled in schools in the most populated areas in each country. We therefore cannot generalize our findings to all populations of adolescents in the country, and, importantly, those adolescents who are not in school may be at higher risk for frequent problematic cannabis use. A final consideration is that the SCM study design assumes that passage of legalization in Uruguay did not affect substance use outcomes in the Chilean control regions. Given Uruguay only permits cannabis purchase by its own citizens, this is likely a reasonable assumption. Nonetheless, legalization may affect perceptions and social norms towards cannabis in neighboring countries. The present study provides the first effort to estimate the effect of the first non-commercial model of national cannabis legalization on cannabis use outcomes. As analysts have noted See e. It is thus critical that we study and evaluate the different models of legalization and the associated social and health impacts. Uruguay offers one prominent example of cannabis legalization without commercialization. Our study provides preliminary evidence that this type of non-commercial model of national cannabis legalization may not lead to an increase in adolescent cannabis use in the short term. At the same time, our results are preliminary and an evaluation of the longer-term impacts of the fully implemented regime is still needed. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. Int J Drug Policy. Published in final edited form as: Int J Drug Policy. Find articles by Hannah Laqueur. Find articles by Ariadne Rivera-Aguirre. Find articles by Aaron Shev. Find articles by Alvaro Castillo-Carniglia. Find articles by Kara E Rudolph. Find articles by Jessica Ramirez. Find articles by Silvia S Martins. Author Contributions HL supervised the statistical analyses, interpreted the results, and drafted and revised the manuscript. Issue date Jun. PMC Copyright notice. The publisher's version of this article is available at Int J Drug Policy. Metropolitana 0. Open in a new tab. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel.

The Impact of Cannabis Legalization in Uruguay on Adolescent Cannabis Use

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Drug traffickers engage in a creative game of hide and seek with coast guards and other security forces that board their ships at sea. A spate of recent seizures prove his point as traffickers have been getting more inventive with hiding places both above and below deck. InSight Crime looks at some of the most popular and creative ways narcotics have been concealed aboard ships over the years and how this continues to evolve. In some cases, drugs have been stored in the same compartment as the anchor, to which few people would have access. Otherwise, anchors have been used to facilitate the delivery of drugs once a ship has reached its point of arrival. In , Spanish authorities announced the seizure of more than a ton of cocaine from a Venezuelan flagged vessel at high sea. This was reportedly so crew members could throw illicit loads into the sea in the shortest time possible, to avoid being detected. Authorities observed how two of the crew tried to achieve this before being caught out with four other people who were onboard. As InSight Crime reported last year, scrap metal shipments have posed a sizeable problem for authorities in this respect, due to scanners being unable to pick up on smaller quantities of drugs when they are hidden among vast volumes of scrap. Equally, authorities have found it more difficult to deploy sniffer dogs to detect drugs in such cases, as the animals may get injured when performing their duties. Otherwise, illicit substances have commonly been smuggled in among foodstuffs. And at the end of , authorities in Italy discovered close to 1. Subrayado revealed how the captain himself had denounced the illicit load on discovering it. This is incredibly rare, however it has been known to occur. Following a spate of related seizures, just under 30 kilograms of cocaine were discovered in a compartment near to the funnel of a ship belonging to the navy, anchored three miles from the Lima port of Callao. Days later, another 25 kilograms of the drug were reportedly found in the hold of the same ship. Traffickers have been concealing drugs inside the vents along ship hulls, as smuggling below deck has taken off. In , InSight Crime reported that a trafficking network headed by Colombians had been sending cocaine to Europe from the Peruvian ports of Pisco and Chimbote, principally through employing divers to weld sealed packets of the drug into vents located in the hulls of ships. In September of that year, Spanish authorities seized just over 50 kilograms of cocaine concealed in the submerged part of a merchant ship, after it reached the island of Gran Canaria from Brazil, EFE reported. According to the media outlet, officials detailed how part of the illicit load had been found inside a manipulated vent below deck. And months later, in December , police in Ecuador revealed how divers had discovered over kilograms of cocaine hidden in the lower vents of a maritime vessel. According to authorities, the cocaine was seized before it could be smuggled onward to Mexico and the Dominican Republic. When drugs are concealed below deck, ship vents are perhaps one of the most popular hiding places traffickers use, even if divers are typically required to facilitate this. Staying below deck, criminal actors have used water inlets to conceal drugs and facilitate trafficking operations. While this hiding place is less common than traditional favorites, sophisticated networks have been working with divers to store packets of illicit substances inside such valves. The organization had reportedly been concealing drugs within the water inlets of a Peru-flagged merchant ship. Reports from local media suggested the diver had been reaching the vessel on a boat with an electric motor which made little noise, to avoid being detected. On dismantling the group, authorities reportedly seized 1. Divers are often employed by criminal groups to facilitate such operations. In , InSight Crime shared how ship hulls have been increasingly used to facilitate drug trafficking, particularly by smugglers taking advantage of vessels disembarking from Ecuador and Peru. Criminal groups have picked up on how attaching drug shipments to the hulls of ships makes illicit substances near imposible to detect using standard inspection procedures. However, officials have been combatting such cunning attempts. While we may be more used to seeing drugs concealed in car fuel tanks, smugglers on ships have replicated this tactic. On a smaller scale, back in , authorities in the Dominican Republic seized just short of 80 packets of presumed cocaine, onboard a vessel destined for Puerto Rico, according to Diario Libre. This method is far from the most common used by maritime smugglers and its intricacy has varied from case to case. In , police in Colombia discovered 40 kilograms of cocaine inside a sealed torpedo attached to a ship destined for the Netherlands. Two years earlier, InSight Crime reported on how this method had been applied extensively by traffickers based in Colombia. In , authorities in the nation caught 14 people suspected of being in a gang dedicated to smuggling drugs in cylinders attached to ship hulls. The media outlet added that the cylinders were manufactured by a metal working expert, who also covered them with fiber glass. But torpedoes have not just been bolted to ships setting sail from Colombia. As far back as , InSight Crime reported on how Peruvian police had found just over kilograms of cocaine hidden inside a makeshift torpedo attached to the bottom of a boat in a Lima port. The torpedo method is intricate and often requires specialist involvement, from trained divers to metal workers producing the containers. However, this technique has become increasingly popular with traffickers who want to minimize the risk of being caught with illicit loads at high sea. Drugs have been frequently hidden in rooms restricted to select crew members, often implicating those with inside knowledge in such cases. Three years later, authorities reportedly found just under 90 kilograms of cocaine in the engine room of a steamship docked at the Port of Palermo in Colombia, according to El Heraldo. Media reports suggested the load was ultimately headed for Brazil. Nearly two decades ago, a Colombian naval training ship was found with over 26 kilograms of cocaine and heroin in its engine room. While this restricted room has been used to conceal smaller quantities of drugs, it is far from a popular place for smuggling to occur, particularly without some form of insider knowledge. In a particularly creative move, traffickers have been known to hide drugs under the propellors of maritime vessels. Roberto Vaquero, assistant director of field operations for border security in Puerto Rico and the U. Naval training ships have been mobile transit hubs for drugs in the past through the use of restricted spaces. Off limits storage rooms have been used to conceal illicit loads during transatlantic voyages. The media outlet suggested that very few people had access to this space. During its voyage, the ship had stopped off in Cartagena, Colombia and then in New York. Such incidences are rare and usually rely on the direct involvement of corrupt officials or armed forces themselves. Traffickers have been using nets attached to ships to their advantage, predominantly to bring drugs aboard. In June , media outlets revealed how traffickers had snuck over Subscribe to our newsletter to receive a weekly digest of the latest organized crime news and stay up-to-date on major events, trends, and criminal dynamics from across the region. Donate today to empower research and analysis about organized crime in Latin America and the Caribbean, from the ground up. Skip to content. Anchor In some cases, drugs have been stored in the same compartment as the anchor, to which few people would have access. Vents Traffickers have been concealing drugs inside the vents along ship hulls, as smuggling below deck has taken off. Water Inlets Staying below deck, criminal actors have used water inlets to conceal drugs and facilitate trafficking operations. Fuel Tank While we may be more used to seeing drugs concealed in car fuel tanks, smugglers on ships have replicated this tactic. Engine Room Drugs have been frequently hidden in rooms restricted to select crew members, often implicating those with inside knowledge in such cases. Propellor In a particularly creative move, traffickers have been known to hide drugs under the propellors of maritime vessels. Nets Traffickers have been using nets attached to ships to their advantage, predominantly to bring drugs aboard. Stay Informed With InSight Crime Subscribe to our newsletter to receive a weekly digest of the latest organized crime news and stay up-to-date on major events, trends, and criminal dynamics from across the region.

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