Cannabis Grow

Education efforts about the adverse impact marijuana use can have on depression are needed, with a focus on subgroups at risk for poor outcome. Together, our results warrant replication and indicate a need for providers to ask depressed patients about their marijuana use, to inform those using marijuana of its potential risks and determine treatment needs. Patients were participants in a randomized controlled trial of alcohol and drug use among psychiatry outpatients and had PHQ-9 depression of ≥ 5, limiting generalizability. Patients were using substances other than marijuana, limiting our ability to draw firm conclusions, although all models adjusted for non-marijuana use. Models were unadjusted for patient’s premorbid functioning/marijuana use, which could have impacted the results. Substance use variables were dichotomized due to low frequency, reducing statistical power, our ability to determine quantity/frequency, and our understanding of patterns over time. We do not know how patients used marijuana , whether problems were associated with use, or the primary reason/condition for medical use. Longitudinal analyses are limited to a 6-month follow-up, suggesting further research will be needed over longer periods of time. Marijuana is the most widely used controlled substance in the world . In 2016, 192.2 million people used marijuana . Regular marijuana use, particularly initiated in adolescence, is associated with a range of adverse consequences,grow benches including poor cognitive and educational outcomes, low self-reported life satisfaction , downward socioeconomic mobility , psychiatric illness , marijuana-involved injury , and substance use disorders .

Perceived risk and perceived availability of marijuana have historically been important drivers of adolescent marijuana use, and often targets of interventions to prevent or reduce adolescents’ use . However, these relationships may be changing. Most extant research on the changing associations between adolescent perceived risk, availability, and use of marijuana has been conducted in the United States , where 28 states and the District of Columbia have legalized medical marijuana since 2000, and 10 states and DC have legalized recreational marijuana since 2012 . In this context, more adolescents now perceive no/low risk of marijuana use, but the prevalence of marijuana use has not increased simultaneously . Research on changes in the individual-level association between no/low perceived risk and use has been mixed. Some have found that the association weakened in recent years , while others have reported that it strengthened or remained stable . Additionally, perceived easy availability of marijuana has largely declined among US adolescents . Evidence suggests that the association between perceived availability and use of marijuana has remained strong and stable over time . Understanding these relationships is particularly important in light of recent liberalization of marijuana access, as perceived risk and availability are two key mechanisms through which legalization could impact use. In this study, we focus on the Southern Cone context for two reasons. First the Southern Cone has recently experienced changes in marijuana regulation, which could impact perceived risk and availability. Second, trends in adolescent marijuana use and perceived availability are different from those in the US, which could suggest distinct relationships between perceived risk and availability and use of marijuana. In 2013, Uruguay enacted a law providing the government full regulation over the largescale production and sale of recreational marijuana.

Adults in Uruguay can purchase marijuana at pharmacies, grow marijuana at home, or acquire it through a cannabis club . In Argentina, possession of marijuana for personal use continues to be illegal ; however, a 2009 court judgment marked the beginning of a paradigm shift in the criminalization of marijuana since it raised a contradiction between Law 23,737 and Article 19 of the Constitution, which protects individuals’ freedom from state regulation . In 2017, Argentina approved access to medical marijuana under specific circumstances . In Chile, marijuana is decriminalized, a limited set of cannabis-based pharmaceutical products are available for medical use, and a new bill allowing other sources of access and formulations is under debate . Since the early 2000’s, past-month adolescent marijuana use has increased in Uruguay , Chile , and Argentina . These trends are distinct from the US where marijuana use has remained stable , and from other South American countries where past-year use is less than 5% . Although perceived risk of marijuana use has decreased in both the Southern Cone and the US, perceived availability has increased in the Southern Cone, but decreased in the US . We know of no study that has assessed the individual-level relationships between adolescent perceived risk, availability, and use of marijuana in the context of the Southern Cone. Such research may inform the priority and scope of context-specific public health interventions to prevent adolescent marijuana use and help identify the drivers of use during these historical shifts. As more regions debate or enact policies to decriminalize or legalize marijuana use, the impetus for cross-country comparisons increases. In this study, we used survey data from adolescents in Argentina, Chile, and Uruguay to 1) estimate associations between perceived availability and perceived risk of marijuana use and past-month marijuana use, and 2) describe how these associations changed over time.

Individual-level data from adolescents enrolled in secondary education in Uruguay, Chile, and Argentina were obtained from the National Surveys on Drug Use Among Secondary School Students . These cross sectional surveys, carried out every 2–3 years, collect information on substance use and related risk factors. The sampling design and survey instruments are similar to the Monitoring the Future Surveys and were implemented comparably across countries. Surveys were self-report and administered confidentially in students’ classrooms. The sample included 8th, 10th, and 12th graders in schools classified as public, private, and other in mostly urban areas. Net secondary school enrollment was 80–90% in Chile and Argentina over the last decade and increased from 67.6–82.8% from 2007 to 2016 in Uruguay . The sample was selected via clustered, multistage random sampling from areas with 10,000+ and 30,000+ inhabitants in Uruguay and Chile, respectively, and schools with at least 20 students in the grades under study in Argentina. In Uruguay and Argentina, strata were types of school within urban areas of geographical regions in each country; primary sampling units were schools followed by classrooms. In Chile,grow racks with lights strata were school type by grade within mostly urban areas and primary sampling units were classrooms. Individual-level survey weights were used. Recent school cooperation rates ranged from 76–86%. This study was determined not human subjects research by the University of California, Davis Institutional Review Board. We restricted the sample in two ways. First, we removed adolescents with poor quality data [i.e. those who responded “yes” to any past-month use of five or more illicit substances , lifetime users of a fictional drug, and those with more than four inconsistencies in reporting age of initiation of use, past month, past year, and lifetime use of marijuana] based on criteria used in Uruguay before data entry. To maintain comparability, we removed observations in Chile and Argentina based on the same criteria. Second, we restricted the sample to the years our variables of interest were collected. Analyses were done in Stata 15.1 and SAS 9.4 and conducted separately per country. We used the svy suite in Stata for descriptive analyses and weighted time-varying effect modeling in the SAS macro %Weighted TVEM to estimate odds ratios for past-month marijuana that vary smoothly over time, accounting for the complex survey design . This method, made available in 2017 with the %Weighted TVEM macro, uses unpenalized B-splines to estimate coefficients and point-wise 95% confidence intervals as continuous functions over time, thus relaxing parametric assumptions about how the relationships between perceived risk, availability and marijuana use vary over time, and allowing for non-linearity . TVEM has been used to assess historical trends in the US in associations between adolescent marijuana use and related attitudes .

TVEM models were run on each imputed data set, and then estimates and standard errors were combined with the PROC MIANALYZE procedure in SAS. For each country and analytic sample, we present bivariate TVEM results. Graphs are shown with consistent x-axes , but different y-axes per country to aid interpretation. Because of the small sample sizes given the relatively low prevalence of marijuana use, our ability to adjust for covariates was limited. When possible, we adjusted for grade and gender, alcohol use, and tobacco use. Additionally, in Chile, the only country with enough observations and overlapping years of data to run TVEM models, we also included risk and availability simultaneously. For this analysis, we used a separate imputation model that included both variables in the same process. All covariates were time-varying. Finally, to better understand trends in the relationships between perceptions and use, we examined how the prevalence of marijuana use changed over time within each level of perceived risk and availability.Across countries and years, approximately 5–10% of adolescents reported past-month marijuana use, with greater prevalence in Chile followed by Uruguay . Marijuana use generally increased over time , and there was a notable increase in use among Chilean adolescents from 2009–2013 . On average, approximately 7–25% of adolescents perceived no/low risk of regular marijuana use, with greater prevalence in Chile followed by Uruguay . The proportion of adolescents who perceived marijuana to pose no/low risk increased over the study period despite year-to-year fluctuations . In Chile, there was a large increase in the proportion of adolescents who perceived no/low risk from 2011–2013, in addition to greater overall change and yearly variation, compared to Argentina and Uruguay, where the prevalence increased to a lesser degree with less variation . On average, one-third to one-half of adolescents perceived marijuana to be easily available, with greater prevalence in Uruguay followed by Chile . Trends varied over time . In Argentina, perceived availability increased from 2005 to 2009–2011 and then decreased or plateaued until 2014 . In Chile, perceived availability of marijuana generally declined from 2001 to 2009–2011 and increased thereafter . In Uruguay, perceived availability increased from 2005 to 2007–2009, plateaued or declined slightly until 2011, then increased until 2016 . Consistent with prior studies from South America and the US, our results indicate that the less risk an individual attributes to marijuana use, the more likely he/she is to use marijuana . However, in the Southern Cone countries, the overall magnitude of this association weakened, although it strengthened again most recently in Argentina. This suggests that risk perceptions became a weaker correlate of adolescent marijuana use over time. There are several implications of these results. First, given the overall increase in the proportion of adolescents who perceive marijuana use to pose no/low risk of harm, marijuana use would have likely increased to a greater degree in the Southern Cone had the risk/use relationship not weakened. Second, factors other than risk perceptions, such as marijuana availability, may have played a greater role in the increase in adolescent marijuana use observed during our study period. This highlights the need to consider changes in multiple individual and environmental determinants of marijuana use. Third, there may be a cross-national weakening of the risk/use relationship. We found this trend in all Southern Cone countries, and some have identified the weakening of this relationship in the US as well . This would suggest that risk perceptions may be, at least in part, shaped by broader societal norms that extend beyond local or national context. Increases in global information sharing via internet use, social media, and international news coverage may contribute to this trend . Consistent with extant research in Europe and the US , we found that adolescents who perceive marijuana to be easily available are more likely to use marijuana. However, the stability of this association varied over time and between countries. In Chile, the availability/use association weakened, and became increasingly similar to the risk/use association, both in magnitude and trajectory, when risk and availability were modeled together. In contrast, the relationship between availability and use strengthened in Argentina and Uruguay, becoming stronger at times than the relationship between perceived risk and use in both countries. However, because we were not able to model both variables together in Argentina and Uruguay due to finite sample limitations, it is unclear how the associations relate to one another. Variation in the relationship between perceived availability and use of marijuana over time and between countries may be explained by several factors.

Furthermore, the number of dispensaries the cities in LA County have so far allowed may not have reached the threshold where their number has had an effect on the marijuana use behaviors of the adolescents who live/attend school there, but as licensing for recreational outlets proceeds the number of dispensaries in many LA County cities is increasing or is planned to increase. For example, the City of Los Angeles Department of Cannabis Regulation estimates that an additional 200 licenses for retail storefronts will be able to be given out under current regulations. When added to the 170 existing medical marijuana dispensaries currently permitted by the City there will be close to 400 licensed dispensaries operating in the City of Los Angeles. Continued research on the impact to youth and other vulnerable populations as increasing numbers of recreational marijuana use outlets are licensed in LA County cities is crucial to determine their effects compared to medical marijuana outlets. It will also be important to monitor cities’ progress in reducing the number of unlicensed dispensaries and how this may impact adolescent marijuana use and other health and safety outcomes. Although it may have raised as many questions as it has answered, it has also hopefully resulted in some useful findings about the impact of local policy implementation on adolescent marijuana use. The most important implication for policy and practice identified here is the importance of local enforcement. The example of the City of Los Angeles was first to tolerate dispensaries under state law,bud drying rack but the lack of enforcement from the state combined with what was a very underdeveloped regulatory structure instead resulted in the presence of dispensaries having unwanted impacts on youth and public health. In Los Angeles it took many attempts and a voter mandate from a ballot measure to develop and implement an adequate regulatory approach with Proposition D.

Then it took time and the dedication of staff and financial resources in enforcement to make it successful. The decline in rates of marijuana use after Proposition D was enacted show that it is possible to take an out of control marijuana market in hand and that doing so can have a preventative impact on youth use. However, the experience of the City of Los Angeles also indicates that a complete ban on dispensaries is not necessary to curb undesirable outcomes. Instead it suggests that a robust local regulatory structure may allow for adult access to marijuana while reversing trends of marijuana use among adolescents and, by extension, health harms. Cities that allow dispensaries are forced to balance the tax and potentially other economic gains that can come from hosting marijuana businesses with the potential costs of enforcing marijuana regulations and the potential harms that dispensaries could cause. Many cities may have not been willing to take on the challenge, which could be one reason why most of the cities in LA County have enacted bans on dispensaries. However, preventing youth use is also a frequently mentioned reason for banning dispensaries, if not always the primary reason . The results of this study suggest that allowing dispensaries to operate in a city may not bring about significant harm to youth as long as dispensaries are located far enough away from schools. This information should guide the cities of LA County in choosing an approach to dispensary regulation. If a city feels it has the resources to vigorously enforce a dispensary ordinance and the capacity to host dispensaries far from sensitive areas, it may make economic sense to allow a small number of marijuana outlets serve their adult residents. Furthermore, continuing to ban dispensaries does not obviate the need for enforcement, which means that cities with dispensary bans must spend resources on marijuana control without the benefit of marijuana taxes. Finally, an important finding from a forthcoming impact evaluation on medical and recreational marijuana outlets in LA County found than the numbers of unlicensed outlets has been decreasing in cities where dispensaries are allowed, while they have held steady in cities and unincorporated areas where they are banned .

Licensing a small number of dispensaries may offer cities more local control over marijuana if allowing a few marijuana outlets cuts down on the number of unlicensed outlets a city must identify and close down. It my hope that by using evidence-based policy we can create an environment where the young people of LA County will use marijuana less and later. With this research my aim was to determine the effectiveness of a common approach to dispensary regulation, dispensary bans, on preventing adolescent marijuana use. It also aimed to build on our understanding of how city policies like dispensary bans can be effective, whether it is by their association with a lower number of dispensaries in a city, with increasing perceptions of the risk of marijuana use among young people, with a greater distance between schools and dispensaries, or with a lower number of dispensaries located near schools. Although this analysis shows that enacting and enforcing strict controls on marijuana outlets can have a preventative impact on a city’s students, dispensary bans were not found to have an independent association with lower rates of marijuana use in cross sectional analyses. Given that minors ostensibly cannot access marijuana directly from storefront dispensaries, it may not be surprising that city ordinances that allow storefront dispensaries should have little substantive effect on adolescents’ marijuana use. I hypothesized that dispensary bans would make access to marijuana less convenient for adults on a city level, which in turn could impact availability for youth, but there are many alternate sources for marijuana available to adults other than a dispensary in their city. There was also substantial variation in enforcement among the cities in LA County that have enacted dispensary bans, where some do not seem to have the resources or political will to enforce them. In the absence of rigorous enforcement to prevent unlicensed outlets, city bans on storefront marijuana outlets are evidently more symbolic than effective. Although the number of dispensaries in a city was not significantly associated with student marijuana use, future research should monitor adolescent marijuana use rates as the number of dispensaries in cities increases with additional adult use/non-medical outlets. There may be a threshold effect for the ratio of dispensaries per resident that a city can host without a concomitant increase in adolescent marijuana use, but this threshold is unknown to date.

Furthermore, increased density of outlets can have other undesirable effects such as marijuana abuse and dependence among adults . The multivariate analyses presented here also found little evidence for an effect of dispensary bans on young people’s attitudes toward the risk of marijuana use. Instead these attitudes seem to be driven by other factors that were not measured in this study. Therefore,grow solutions greenhouse it appears that cities may be better served worrying about their capacity to enact tight regulations on dispensaries and to enforce them than being concerned whether enacting an ordinance allowing dispensaries will send a message to young people that marijuana use is safe and acceptable and thus encourage use. The most potent effects on student marijuana use were related to the proximity of unlicensed outlets. The negative association between dispensary bans and student marijuana use, was significantly dependent on dispensary bans being associated with a greater distance to the nearest dispensary in the County compared to city dispensary policies that allowed dispensaries. The continuous distance to the nearest dispensary had a powerful association with students’ marijuana use within LA County, at one mile, and at short distances such as 2,000 feet. These local effects prove the primary importance of keeping unlicensed outlets much farther away from schools than current regulations in any city in LA County require. Future policy efforts should place greater importance on preventing the localized effects of unlicensed outlets and explore different approaches, such as clustering dispensaries in industrial zones or other areas far from the business and residential neighborhoods where schools are found. Together these findings support a rigorous but nuanced approach to regulating marijuana outlets. It is evident that enforcement was key in preventing marijuana use among the youth in this study. Whether a city allowed dispensaries or not, the presence of unlicensed dispensaries seemed to drive associations with youth marijuana use, indicating that the quality of enforcement is more important than the kind a policy a city chooses. Future research should focus on minimizing the localized effects of unlicensed dispensaries and undertake to better understand why unlicensed outlets have such a disparate impact on youth marijuana compared to licensed outlets. Marijuana is the most frequently used illicit drug in America, with an estimated 18.9 million people aged 12 years or older identifying as current users in 2012. The prevalence of marijuana use has increased since 2002, and this trend can be expected to continue as states enact policies to permit medicinal or recreational use. Despite the growing movement to legalise marijuana, however, little is known about its effect on metabolic health.

Research on the association between marijuana use and various metabolic indices suggests a paradox in which greater marijuana use is associated with increased caloric consumption, but with decreases in the levels of various metabolic risk indices, including BMI, waist circumference , fasting insulin and HOMA-IR. A recent meta-analysis of eight studies suggested that current cannabis smoking is associated with 30% lower odds of diabetes. However, previous studies have been limited to cross-sectional analyses and might have lacked proper adjustment for confounding. A prospective assessment of health outcomes in relation to prior marijuana use would limit the potential bias that might result from individuals’ decisions to alter marijuana exposure based on their own health status. The purpose of this study was multifaceted. First, we aimed to assess the association between self-reported marijuana use and prediabetes and diabetes mellitus using cross-sectional and prospective analyses, considering both status and quantity used. Second, we aimed to examine the role of BMI and WC as potential confounding or mediating factors of these associations. Finally, given the varying diabetes risk profiles by race and sex, we sought to evaluate the heterogeneity of effects in the associations by race and sex.The Coronary Artery Risk Development in Young Adults study is a longitudinal observational study intended to investigate the development of coronary artery disease risk factors in four healthy metropolitan populations of black and white adults aged 18–30 years at recruitment. Participants were contacted by telephone annually and invited to participate in follow-up examinations at 2, 5, 7, 10, 15, 20 and 25 years after enrolment. Demographic information was obtained, BP and chemistries were measured, and anthropometry and structured questionnaires on manifold health characteristics were conducted, following standardised protocols that were harmonised over time. The institutional review board at each study site granted approval, and informed consent was obtained from the 5,115 participants at enrolment in 1985–1986 and at each follow-up examination. Details of the study design have been published previously. Individuals were asked to present in a fasting state on the morning of their clinical examination and to forgo tobacco use and strenuous physical activity . Appointments were generally scheduled to begin between 08:00 hours and 12:00 hours. At each clinical examination, individuals were asked to update their sociodemographic information and were questioned about their medical and family history and individual lifestyle characteristics, including educational attainment, tobacco use , regular alcohol consumption, and moderate and strenuous physical activity. A valid and reliable metric for leisure-time physical activity was developed by CARDIA researchers, as previously described. Venous blood was drawn and serum separation was performed, following which aliquots were stored at −70°C and shipped on dry ice to a central laboratory. Serum glucose was measured using the hexokinase method, and per cent HbA1c was assessed using Tosoh G7 HPLC and standardised across examinations. The 2 h serum glucose levels were measured from a standard 2 h OGTT at Y10, Y20 and Y25. Procedures for collection, storage and determination of plasma lipids and C-reactive protein have been previously described.

Proximity to dispensaries in neighborhoods has been shown to have a positive association with more frequent marijuana use among adults , but the effect of proximity to marijuana outlets to schools on adolescent marijuana use is unknown. Research Question #4 was: “Is the effect of dispensary bans on student marijuana use dependent on the distance of the nearest dispensary from a student’s high school? The hypotheses associated with RQ4 propose that H4.1) dispensary bans are associated with longer distances between dispensaries and schools; H4.2) the proximity of dispensaries is positively associated with students’ likelihood of using marijuana; and H4.3) the relationship between city dispensary bans and high school students’ marijuana use is mediated by dispensary bans effectiveness at keeping dispensaries a greater minimum distance from schools than city policies that allow dispensaries. Table 7.12 presents the results of the mediation analysis assessing the mediating effect of the distance to the nearest dispensary within LA County on lifetime marijuana use. As reported earlier, the relationship between dispensary bans and lifetime marijuana use was negative and non-significant . Whether a city had a dispensary ban was regressed on the distance in miles from the participant’s school to the nearest unlicensed dispensary using an HLM model controlling for the covariates and with a random intercept for city. The association between dispensary bans and the distance between the students’ high school and the nearest unlicensed dispensary was positive and statistically significant ,plant racks which supports H4.1 for lifetime marijuana use, i.e., my theory that dispensary bans would be associated with a greater average distance from schools than in cities that allow dispensaries.

The distance in miles from the school to the nearest unlicensed dispensary was then regressed on the lifetime marijuana use, which revealed a statistically significant negative association between distance and reports of lifetime use, meaning that students in schools located further from unlicensed dispensaries were less like likely to report lifetime marijuana use , confirming H4.2., that shorter distances between the participants’ schools and the nearest dispensary were associated with higher prevalence of lifetime marijuana use. Finally, the regression analysis of dispensary bans and lifetime marijuana use was repeated including the distance in miles from the school to the nearest unlicensed dispensary. Adding the distance measure increased the effect of dispensary bans and in the expected direction, i.e., it was hypothesized that dispensary bans would be negatively associated with marijuana use and adding the variable quantifying the distance to the nearest dispensary into the regression strengthened the negative association between dispensary bans and lifetime marijuana use, but the overall relationship still fell just short of statistical significance . This result indicates that indirect mediation was occurring, where the effectiveness of dispensary bans was partially dependent on how far away they keep unlicensed dispensaries from high schools compared to city policies that allow dispensaries. The above steps were repeated for the recent marijuana use outcome, with similar results. The focal relationship between dispensary bans was negative and not statistically significant, as reported earlier. Path a, the association between dispensary bans and the distance to the nearest dispensary was the same as described above for recent use. Path b, the effect of the distance between the nearest unlicensed dispensary and recent marijuana use was negative and statistically significant , indicating the further away unlicensed dispensaries were located from the participants’ schools, the less likely they were to report recent marijuana use .

Path c’, the relationship between dispensary bans and recent marijuana use was strengthened substantially and in the expected direction but fell short of statistical significance, which indicated partial mediation. Hypothesis 4.3 was therefore partially supported. In Table 7.14 I present the results of a sensitivity analysis conducted a series of multilevel logistic regression models on increments of one mile, continuing to increments of a quarter mile for recent marijuana use, where the distance to the nearest MMD was not statistically significant at one mile. For each measure of marijuana use I started with a distance of over five miles and worked inward in increments of one mile, until I reached the point at which the distance to the nearest MMD had a statistically significant association with student marijuana use. For lifetime marijuana use, this occurred at a distance of one mile. For recent marijuana use, the distance from the school to the nearest MMD was not statistically significant at one mile, so I continued using smaller distances in quarter mile increments until I reached the point where the distance between the school and the nearest unauthorized MMD became statistically significant, which occurred at a distance of between ½ mile and ¾ mile of the nearest unauthorized MMD and the participant’s school. This analysis also revealed that the distance from the school to the nearest MMD became significantly negatively associated with student marijuana use at longer distances. The association of distance becomes protective against lifetime marijuana use at a distance of over 5 miles from the participants’ school and for recent marijuana use this occurs between 3 and 4 miles. As the distance used was the distance from school to only the nearest MMD from the participant’s school, these distances were not cumulative.

The ranges of distances were treated as bands, where if the nearest dispensary was located within a certain range of distance from the participants’ school distance from their school the value for that range of distance was coded as ‘1’ and all other rangers of distance were coded as ‘0’. For the distances within one mile I chose increments of a quarter mile because it is hard to visualize distance by feet at longer distances. I created variables using the distance to the nearest MMD from each student’s school to indicate whether the nearest MMD to the student was located within 1 mile , between three quarters of a mile and one mile, and between three quarters of mile and a half mile . There were too few MMDs located within a half mile from schools to produce statistically significant and reliable results without including all of them instead of only the nearest , so I stopped at a distance of a half mile from the school. Students that did not have MMDs located within any of these distances had a zero value for each of these variables. As these were binary variables I present odds ratios in Table 7.14. The sensitivity analysis indicates that there was no “safe distance” within a mile that unauthorized MMDs could be located near schools without having an association with significantly higher rates of lifetime marijuana use among students. The distance between the school and the nearest unauthorized MMD was significantly associated with greater prevalence of recent marijuana use at a distance of a ½ mile to a ¾ mile. The association between the distance between participants’ schools and the nearest unlicensed dispensaries was remarkably consistent for lifetime marijuana use with the exception of a non-statistically-significant result for distance between ½ and ¾ mile and lifetime use. Overall, there is a clear relationship with the distance between participants’ schools and the nearest unlicensed MMD,plant growing trays where shorter distances were associated with significantly greater odds of marijuana use. The association with distance to the nearest unlicensed dispensary then decreased in size and lost statistical significance at longer distances until eventually becoming associated with lower odds of marijuana use as distances increased. The distances at which this research showed statistically significant associations with student marijuana use are much further away from schools than the state requirement of 600 feet, but it is important to note the same associations did not apply for licensed dispensaries. In contrast to the associations with distance from schools found for unlicensed dispensaries, there was not a consistent association with the distance that licensed dispensaries were located from participants’ schools and their odds of reporting lifetime or recent marijuana use . It is therefore possible that smaller distances such as 600 feet are sufficient to prevent licensed outlets from being associated with greater prevalence of marijuana use among students, as licensed marijuana outlets seem to have less of an effect on student use than unlicensed outlets. As presented in Table 7.15, the associations between the distance from the participants’ schools to the nearest unlicensed MMDs were largely inconsistent or were not statistically significant.

For lifetime marijuana use the associations were consistently negative for distances below a mile, meaning that shorter distances to licensed MMDs were associated with lower odds of lifetime marijuana use among students, but these associations were not statistically significant below a mile and were inconsistent at distances greater than a mile. The inconsistent results for distances greater than a mile may indicate confounding effects from city borders, indicating that measurements of distance to authorized outlets greater than mile should be interpreted with caution and may be of limited utility in studies of the effects of distances between schools and dispensaries on high school students’ marijuana use behavior. Similarly, the association between the distance from participants’ schools to the nearest licensed MMDs and recent marijuana use was significant and protective at one mile, but was not statistically significant below one mile and inconsistent with any discernable pattern at distances greater than one mile. Rather than concluding that the presence of licensed MMDs is protective against marijuana use among high school students at distances of one mile, I think it is safer to conclude that there is not a clear relationship between the distance to licensed MMDs and student marijuana use and that any future studies of the effect of this distance should be bound by city borders to avoid any confounding effects of authorized dispensaries being found only within cities that allow them, while unlicensed dispensaries were found both in cities that allowed MMDs and cities with bans. That there was not a clear pattern of association with the distance from schools to the nearest licensed MMD when the association was clear for unlicensed dispensaries is surprising. This finding has important implications for marijuana regulation at a city level, as it suggests that any associations between the proximity of MMDs to areas young people frequent and their marijuana use behavior may be driven by unlicensed outlets. It also reflects a need for further study of why the effects of unlicensed and licensed MMDs should be so noticeably different. It is evident from the results presented above that the continuous distance between schools and unlicensed dispensaries is a mediator of effectiveness for dispensary bans, while there appears to be little association between student marijuana use and the distance to the nearest licensed dispensary. Although I found in Chapter 5 that dispensary bans were not effective on their own, they were associated with a longer distance between participants’ schools and the nearest unlicensed dispensary, which was in turn strongly correlated with a lower prevalence of student marijuana use. It is therefore important to consider what is actually driving adolescent marijuana use and how best to prevent it using city policy. This research suggests that it may need not necessarily be a ban. Although dispensary bans were associated with longer distances to the nearest unlicensed marijuana outlet, strict enforcement of distance requirements and closing down unauthorized outlets while allowing some dispensaries to operate far from sensitive areas could possibly achieve the same aim. The cities in LA County that allow dispensaries have use local ordinances that specify the conditions under which dispensaries can operate in the city. All six of the cities that allowed dispensaries in September of 2016 required them to be at least 500 feet from schools. Current State regulations require a minimum distance of 600 feet, but at the time of data collection, the distances dispensaries were required to be kept from schools in these six cities ranged between 500 – 1,000 feet . Distances specified in dispensary ordinances may be based on somewhat arbitrary criteria, as no empirical research has established what a “safe” distance is. I suspected the presence and number of dispensaries within a larger radius could still be influential and therefore tested the mediating role of the number of dispensaries located 2,000 feet of the study participants’ schools.

The independent variable was whether or not a city had a dispensary ban and was determined by the city policy that was in effect when the count of dispensaries per city was obtained in September 2016. The research question was broken up into three testable hypotheses: H2.1) there is a direct relationship between city dispensary bans and the number of dispensaries in a city, where city dispensary bans are associated with lower numbers of dispensaries; H2.2) fewer dispensaries in a city is associated with less availability of marijuana to high school students ; H2.3) the effect of city dispensary bans on adolescent marijuana use is dependent on them having a suppressing effect on the number of dispensaries operating in a city. To test the hypotheses associated with Research Question 3, I used a variable that indicated whether students perceived great risk from frequent marijuana use as the mediating variable and controlled for factors known to influence marijuana use among adolescents, such as gender, race/ethnicity, and social/economic status. As with Research Question 2, the independent variable was whether the city had a dispensary ban and was determined by the city policy that was in effect when the count of dispensaries per city was obtained in September 2016. The outcome variable was self-reported student marijuana use . Research Question 3 was broken up into three testable hypotheses: H3.1) there is a direct relationship between city dispensary bans and students’ perceptions of the risk of frequent marijuana use, so that dispensary bans are positively associated with perceived risk; H3.2) there is a direct inverse relationship between students’ perception of the risk of frequent marijuana use and their likelihood of using marijuana,plant benches so that students who perceive great risk from frequent marijuana use are less likely to use marijuana; and H3.3) the relationship between city dispensary bans and student marijuana use is dependent on dispensary bans being associated with greater perceptions of the risk of frequent marijuana use among students and an inverse relationship between perceptions of risk and student marijuana use.

To assess the mediating effect of perceived risk on student marijuana use and test hypothesis H3.1 I calculated the association between city dispensary bans and whether students perceived great risk from frequent marijuana use. If the coefficient was significant and positive, then H3.2 was supported. The second step was to test H3.3 by establishing whether there was a significant positive association between the moderating variable and the outcome variable . This model contained both the focal independent variable and the moderator . Finally, using the same regression model, I assessed the net direct effect of the focal independent variable on the outcome variable while accounting for the indirect effect of the moderator . I hypothesized that students’ perceptions of risk mediated the effect of city policy to some degree, and that the direct effect of the focal relationship coefficient would therefore decrease in magnitude when I controlled for students’ perceptions of risk. To test whether the mediation effect of students’ perceptions of risk was statistically significant from zero, I used a Sobel Test. Because perceived risk was measured at the individual level, I used the single level of the model to test the mediated relationship. To test the hypotheses associated with Research Question 4, I used a continuous measure of the distance in miles between the school and the closest dispensary in LA County as the mediating variable and controlled for factors known to influence marijuana use among adolescents, such as gender, race/ethnicity, and social/economic status. As with Research Questions 2 – 3, the independent variable was whether or not a city had a dispensary ban and was determined by the city policy that was in effect when the count of dispensaries per city was obtained in September 2016. The outcome variable was self-reported student marijuana use .

Research Question 4 was similarly broken up into three testable hypotheses: H4.1) there is a direct relationship between city dispensary bans and the proximity of dispensaries to the students’ high school, so that dispensary bans are associated with longer distances from dispensaries; H4.2) there is a direct relationship between the proximity of dispensaries and students’ likelihood of using marijuana, so that the lesser the distance between the school and the closest dispensary, the greater a student’s likelihood to use marijuana; and H4.3) the relationship between city dispensary bans and high school students’ marijuana use is mediated to some degree by dispensary bans being associated with a longer distance between dispensaries and schools. To assess the mediating effect of the distance to the closest dispensary located within a mile of their high school on students’ marijuana use, I first tested hypothesis H4.1 by determining whether there was a relationship between the independent variable and the moderating variable by calculating the association between city dispensary bans and the continuous distance to the nearest dispensary within LA County. If the coefficient was significant and positive, then H4.2 was supported. The second step was to test H4.3 by establishing whether there was a significant positive association between the moderating variable and the outcome variable . This model contained both the focal independent variable and the moderator . Finally, using the same regression model, I assessed the net direct effect of the focal independent variable on the outcome variable while accounting for the indirect effect of the moderator . I hypothesized that city dispensary bans would be associated with longer distances between participants’ schools and the nearest dispensary in the County and that the association between dispensary bans and student marijuana use would be statistically significant when accounting for this factor.

I used a Sobel Test to determine whether the mediation effect of the distance to the nearest dispensary from the school was statistically significant. To test the hypotheses associated with Research Question 5, I used the number of verified dispensaries located within 2,000 feet of the students’ high schools as the mediating variable and controlled for factors known to influence marijuana use among adolescents, such as gender, race/ethnicity,gardening rack and social/economic status. I also explored whether there were any different effects for the number of unlicensed dispensaries compared to licensed dispensaries. As with Research Questions 2 – 4, the independent variable was whether or not a city had a dispensary ban and was determined by the city policy that was in effect when the count of dispensaries per city was obtained in September 2016. The outcome variable was self-reported student marijuana use . Research Question 5 was similarly broken up into three testable hypotheses: H5.1) there is a direct relationship between city dispensary bans and the number of dispensaries located within 2,000 feet of the students’ high school, such that dispensary bans are associated with less dispensaries being located within a quarter mile of the school; H5.2) there is a direct relationship between the number of dispensaries located within 2,000 feet of the school and students’ likelihood of using marijuana, so that the number of dispensaries located within 2,000 feet is positively associated with students’ likelihood to use marijuana; and H5.3) the relationship between city dispensary bans and high school students’ marijuana use is mediated to some degree by dispensary bans being more effective at preventing dispensaries from locating near schools than city policies that allow dispensaries. To assess the mediating effect of the number of dispensaries located within 2,000 feet of their high school on students’ marijuana use, I first tested hypothesis H5.1 by determining whether there was a relationship between the independent variable and the moderating variable by calculating the association between city dispensary bans and how many dispensaries were located within 2,000 feet of each school. If the coefficient was significant and positive, then H5.2 was supported. The second step was to test H5.3 by establishing whether there was a significant positive association between the moderating variable and the outcome variable . Finally, using the same regression model, I assessed the net direct effect of the focal independent variable on the outcome variable while accounting for the indirect effect of the moderator . I hypothesized that the number of dispensaries located within 2000 of their school would mediate the effect of city policy to some degree, and that the direct effect of the focal relationship coefficient would therefore decrease in magnitude when I controlled for the number of dispensaries located within 2,000 feet the school. To test whether the mediation effect of having dispensaries located near the students’ high schools was statistically significant from zero, I used Sobel Test. The analyses presented above had several important limitations.

The trend analysis relied on a series of cross-sectional surveys, so I was not able to follow the same students over time. The students surveyed were also limited to students who participated in a school-based survey, so the findings from these analyses cannot be generalized to students who are out of school. The students surveyed were also exclusively public high school students, and may have differed in substantial ways from students attending private high schools. The results of this analysis should therefore not be generalized to students attending private high schools. The results may also not be generalizable to LA County as a whole, as only 57 cities out the 88 cities in the County had schools that participated in the CHKS survey during the 2105/2016 and 2016/2017 school years. Instead, this research should be taken as evidence of the need for representative data that can be used for further study of the effects of city dispensary policies on the neighborhood-level conditions that were shown to have a significant influence on students’ marijuana use behaviors; the distance to the nearest dispensary and the number of dispensaries located within several blocks of schools. Finally, I was unable to measure compliance with city or state laws regulating business practices among dispensary owners. I could not measure efforts to enforce dispensary bans or restrictions and did not undertake tomeasure how strict city dispensary ordinances were relative to each other. Future studies of city and county dispensary ordinances should assess these factors to determine how they may mediate or moderate the effect of dispensary ordinances on local conditions that facilitate adolescent marijuana use. Although there are compelling reasons to believe the presence of dispensaries would be correlated with adolescent marijuana use, there is equally credible evidence to suggest that dispensary bans may have little effect on students’ marijuana use. For example, a notable result from the preliminary analyses presented in Chapter 4 was that rates of marijuana use increased from baseline through the 2011/2013 time point even among cities that banned dispensaries. The proportion of students in LA County attending school in a city that allowed dispensaries more than quadrupled during the study period from 3.48% in 2005/2006 to 14.45% in 2016/2017. During the same period, the proportion of students in the County reporting lifetime marijuana use declined from 30% to 25% and recent marijuana use declined from 16% to 14% . These findings suggest that whether their city allows dispensaries may not the primary determinant of rates of marijuana use among LA County high school students. For this analysis, I used a 2-level Hierarchical Generalized Linear Model with students as the level 1 variable and city as the level 2 variable to compare the proportion of students who reported lifetime and recent marijuana use among all the LA County cities that had students participating in the CHKS survey during the 2015/2016 and 2016/2017 school years. The independent variable is whether the city the students lived in/attended school in a city that allowed or banned dispensaries as of September 2016. Covariates included gender, grade, race/ethnicity, participation in after school programs, whether the student received free or low cost meals , whether one or more of the students’ parents had a college degree, and whether they attended a non-traditional school. This analysis uses two pooled years of CHKS survey data, for a combined total of 101,521 students. Combining two school years of CHKS data was necessary because most schools administer the survey every other year and therefore, in any given year half of them are off cycle. More importantly, preliminary analyses indicated that the average number of participants from Los Angeles schools on odd years was approximately double the average from even years.

Visual cues to marijuana use such as billboard and magazine advertising for cannabis are strongly associated with adolescents’ intentions to use marijuana and eventual use . The presence of dispensaries may be analogous to advertising because many dispensaries in LA County use their exterior walls as advertising space like any other store . It is therefore possible that repeatedly seeing dispensaries located near their school will have an impact on high school students’ likelihood to use marijuana, even if they are not able to obtain it directly from these outlets. Furthermore, among people who have already used a psychoactive substance, visual reminders of that substance activate a chemical response that triggers a craving for the substance, increasing their propensity to use substances to which they are frequently exposed to reminders of . This means that among high school students who have already tried marijuana, the sight of dispensaries may trigger cravings for marijuana and thus increase their propensity to use it. Although measuring individual enforcement efforts by city or county police or code enforcement officers was beyond the scope of my analysis, enforcement is nevertheless an important construct in the conceptual model for this dissertation and the analyses that follow. In the conceptual model below, the effects of city policies banning or enacting stricter regulations on storefront dispensaries are hypothesized to be dependent on effective enforcement. For example, the impact of a city policy allowing dispensaries on adolescent substance, such as dispensary density in a city,cannabis curing is determined not just by how many dispensaries the city ordinance allows, but also on how many dispensaries are actually in operation.

Similarly, city policies that allow dispensaries often require them to be located a specific distance away from schools, but dispensaries have often been found located near schools in violation of these policies. Keeping dispensaries away from sensitive areas is therefore also dependent on effective enforcement.Key informant interviews conducted with city officials as part of the LA County Department of Public Health Cannabis Health Impact Evaluation indicate that preventing unlicensed outlets is a central goal for city dispensary ordinances. Therefore, the number of unlicensed outlets per 10,000 city residents was included as a proxy measure of the effectiveness of the city dispensary ordinance, with a higher proportion of unlicensed dispensaries per residents indicating less effective enforcement. Figure 3.2 presents the conceptual model of this dissertation. At the individual level, the focal relationship is between city dispensary bans and students’ self-reported marijuana use . The additional variables that explain and influence the focal relationship are described in the research questions and hypotheses that follow. The conceptual model also presents the backdrop of potentially confounding external influences, which include a general trend toward greater acceptance of marijuana use in American society, changes in state laws that have seen the majority of U.S. states enact laws that allow some level of access to marijuana, and changes in the Federal government’s stance on enforcement priorities concerning marijuana. Although these changes occur outside the scope of this dissertation, they are relevant from the standpoint of the Social Ecological Model and the Drug Normalization Framework and are accounted for in the study design wherever possible.

This study draws upon diverse data sources and uses several different methodological approaches to arrive at a greater understanding of the impact that the dispensary bans enacted throughout Los Angeles County over the past decade have had on high school students’ marijuana use. In the five descriptive and explanatory data analyses for this dissertation that follow, I first used primary and secondary data sources to construct an administrative data set that documented which cities in LA County have enacted medical marijuana dispensary bans. Second, I used school-based CHKS survey data to measure marijuana use among 9th and 11th grade students in each city. Third, I geocoded school addresses from the California Department of Education school directory and mapped their locations within city and county boundaries. Fourth, I linked the CHKS data set to the geographic location of the schools using the unique ID assigned to each school by the California Department of Education. Lastly, I used street addresses from commercial listings of marijuana businesses to establish the location of dispensaries in cities and near schools. These data sources and methods were required to compare long term trends in student marijuana use by whether a city bans or allows dispensaries and to test different ways that city bans may influence high school students’ marijuana use . The population of interest for this dissertation was adolescents living within LA County. The study population was 9th and 11th grade students at public high schools that participated in the CHKS survey between the 2005/2006 and 2016/2017 school years. Students’ demographic and socio-economic characteristics and their marijuana use behavior were recorded using restricted-use secondary data from a school-based survey of student health and school climate, the California Health Kids Survey. Dispensary policies for each of the 88 cities in Los Angeles were obtained from online municipal code databases and categorized by whether they allowed or banned dispensaries. City dispensary policies were linked to student behavior by the city where their high school was located, which according to California public school residency requirements is most often the city where they live .

Addresses of dispensaries were then downloaded from commercial listings of marijuana businesses and mapped to determine their location and density within cities and near schools. Each of these data sources were required to address the central question of this dissertation; whether dispensaries bans prevent adolescent marijuana use. The dependent variables,drying weed lifetime and recent marijuana use, are self-reported data from the CHKS survey. The independent variable is whether each city had a dispensary ban. I also conducted a mediation analysis using measures of marijuana density within cities and relative to schools as well as student perceptions of the health risks of marijuana use to test whether the effectiveness of MMD bans was dependent on any of these variables. The survey sample used for this dissertation was comprised of students who completed the California Healthy Kids Survey at LA County public high schools between the 2005/2006 school year and the 2016/2017 school year. The CHKS is a statewide survey that covers a range of health perceptions and behaviors and is administered annually in school districts throughout the state. The initial population was 532,200 LA County high school students who participated in the CHKS survey between 2005/2006 and 2016/2017. In Los Angeles County during the school years studied, most high schools administered the CHKS every other year to 9th and 11th grade students. However, about 10% of the surveys each year were administered to 10th and 12th grade students or students who chose categories of “don’t know” or “ungraded/other” for grade. These students were excluded to draw more precise conclusions about the behavior of students in 9th and 11th grade and for comparability with the other research published using CHKS survey data, which focuses on these grades. After excluding a handful of remaining students who attended special education schools or who were missing important data, the population available for analysis over the 12 years of the study period numbered 487,354. Criteria for exclusion from the study sample are presented below in Table 4.2. The study period spanning the 2005/2006 school year and the 2016/2017 school year was chosen for several reasons. An original motivation for this study was to learn whether rates of marijuana use among LA County high school students increased overall as the number of cities in the County that allowed dispensaries increased after medical marijuana entered the formal marketplace after SB 420 in 2004 allowed medical marijuana collectives to operate as businesses.

The endpoint for the study period, the 2016/2017 school year, preceded the licensure of non-medical marijuana storefronts throughout the state of California and LA County that began in January of 2018. Ending data collection in 2017 allowed this analysis to focus on the impacts of medical marijuana dispensaries and to serve as a comparison point for non-medical marijuana sales after 2018. As noted above, the data presented in this dissertation were drawn from multiple sources. These sources are reviewed in more detail below. The data source used to measure high school students’ perceptions of the health risks of marijuana use and marijuana use behaviors is a restricted-use secondary data set obtained from a state-level survey of California middle and high school students; the California Healthy Kids Survey . I documented whether the 88 incorporated cities within Los Angeles County had ordinances that banned or allowed dispensaries by reviewing municipal code texts using online municipal code databases such as Municode.com and categorizing city dispensary policies according to whether or not they allowed dispensaries and several other criteria . The number and location of dispensaries within each city were obtained from online dispensary listing and rating services such as Weedmaps.com, which I then used to map dispensary locations using ArcMap 10.4 geographic information system mapping software . The addresses of the high schools came from the California Schools Directory, which was downloaded from the California Department of Education . The CHKS survey is the largest statewide survey of resiliency, protective factors, and risk behaviors in the United States . It administered annually and anonymously at most public schools in California to measure middle and high school students’ attitudes and behaviors related to substance use and other health behaviors. Collecting data on student substance use has been an important goal of the survey dating from its inception. The precursor to the CHKS survey was the California Student Survey of Substance Use , which began collecting data from a representative state sample of secondary students in 1985. Over time, the focus of the CSS was expanded to include questions on other health-risk behaviors, resiliency, school climate, and school safety, which then formed the bulk of the CHKS Core Module when it was developed in 1998. In 2003, the California Department of Education mandated that CHKS serve as the primary data collection tool to document change in alcohol, tobacco, and drug use among California schools , which means that all school districts that receive funding under the federal Safe and Drug Free Schools and Communities Act or state Tobacco Use Prevention Education program must administer the CHKS survey at least once every two years and report the results publicly . As a consequence, the CHKS survey is administered by the majority of California secondary schools every other year on a staggered basis that means data is available for every year at state level but may need to be aggregated into two-year ranges to capture data for all the schools in a region. In terms of psychometric properties, a 2007 evaluation of the CHKS survey’s psychometric properties indicated that the survey exhibited good internal consistency, adequate reliability, and demonstrated measurement equivalence across racial/ethnic groups, males and females, and grades . The current iteration of the CHKS survey is built around a general Core Module and five optional supplements. The analyses presented in this dissertation relied on the Core Module, which assesses demographic information, substance use, exposure to school violence, and other behaviors that contribute to physical and mental health. Most of the items used in the CHKS Core Module were derived from the biennial California Student Survey of Substance Use and the Centers for Disease Control and Prevention Youth Risk Behavior Surveillance System . The analyses presented throughout this dissertation were conducted using two combined school years. This was necessary because school districts generally administer the CHKS survey every two years, at 9th and 11th grade. Therefore, on any given single school year, half of the schools in LA county may not have administered the survey, which could have introduced bias into the analysis. Preliminary analyses indicated that across all schools in the County, the number of participants for odd to even years varied in tandem with whether a majority of LA Unified School District schools had administered the survey that year. For example, the average number of City of Los Angeles schools on odd years was double the average number on even years.

Each business included in the analyses was verified as being in active operation via phone calls, checking WeedMaps message boards for current ratings and comments, and by whether a dispensary was photographed at that location using Google Street View. Once verified as being active, the address of each storefront was geocoded using geographic information systems software to pinpoint their location within city boundaries and determine their location relative to LA County public high schools. The primary practical use of this research is to establish whether dispensary bans are effective on a city level, or if spillover effects and the many other ways young people can access marijuana render them symbolic. The theoretical relevance is gained by establishing why city dispensary ordinances may or may not be effective. The results of this dissertation will determine whether dispensary bans work by making access less convenient at a city level, by changing teens’ perceptions of risk, or by limiting the number of outlets near areas young people frequent. Research on city dispensary policies and the local impacts of dispensaries on youth use is so scarce that it is unknown if all of these mechanisms apply…or none of them. In this review of the literature I will first assess the physiological, psychological, developmental and social consequences of cannabis grow supplier among adolescents. I will then review the current prevalence of marijuana use as well as trends in attitudes and norms toward marijuana use in California over the past two decades following the legalization of medical marijuana use in 1996. I will then cover current state and local policy approaches to regulating marijuana use and conclude by reviewing gaps in the literature.

Given that the goal of this research is to assess the role of city dispensary policies in limiting exposure to marijuana among adolescents, community and societal-level approaches to marijuana use prevention are the focus of this literature review, rather than family and peer influences.Marijuana and cannabis are used as general terms to refer to the many extracts and preparations that can be made from this plant. Marijuana products vary in effects and potency by genetic strain, cultivation technique, and by how it is processed . Traditionally used by smoking the dried flowers, marijuana can also be used by heating flowers, oils, or other concentrated forms in electronic vaporizing devices, by baking extracted oils into foods, and in pills, tinctures, sprays, creams, ointments, eye drops, and suppositories . The chemical contents of marijuana include over 100 cannabinoids; chemical compounds with physiological and/or psychoactive effects. The distinct effects of most cannabinoids have yet to be studied in laboratory settings and are poorly understood . The two best-known cannabinoids are delta-9 tetrahydrocannabinol and cannabidiol . THC is the primary psychoactive ingredient in marijuana that causes intoxication and euphoria. CBD is thought to be responsible for the anti-convulsive and pain-relieving properties of marijuana but is not intoxicating. Recent research on therapeutic uses of cannabinoids has shown that they have considerable promise to treat appetite loss, nausea, chronic pain, insomnia, inflammation, and glaucoma , but marijuana products containing THC also produce potent psychoactive side effects. Favorable psychoactive effects from THC include calming, relaxing, stimulating, or uplifting feelings, but unpleasant effects like anxiety, panic attacks, and paranoia can also occur . THC products act on the central and peripheral nervous systems by binding to receptors for endogenous cannabinoids called “endocannabinoids”.

Endocannabinoids are neurotransmitters naturally produced in the human brain that bind to and activate cannabinoid receptors found in the prefrontal cortex, hippocampus, basal ganglia, thalamus, hypothalamus, and cerebellum . The psychoactive effects of marijuana are produced by displacing endocannabinoids with exogenous cannabinoids such as THC, thus altering cognitive function. Documented effects of marijuana use on cognitive function include chronic short-term memory problems, loss of balance and coordination, difficulty concentrating, changes in sensory perceptions, impaired ability to perform complex tasks, decreased alertness, and decreased reaction time . Long-term cognitive effects from marijuana use are mild compared to those described above but can last for weeks after acute effects wear off . The most enduring cognitive effects are seen in decision-making, concept formation, and planning . Cognitive effects also differ in severity depending on the quantity of regular use, how recently a person used, how old they were when they started using marijuana, and how long they have been using it . Marijuana use that occurs during adolescence has been associated with use of other drugs , poor school performance, and a higher likelihood of substance abuse or dependence in adulthood . Adolescents are more vulnerable to harmful effects from marijuana use because of the active processes of brain development that occur during this stage . For example, developing dependence on marijuana is more likely among adolescents than among adults and the effects of frequent use at this age appear to be much longer lasting. The overall likelihood of developing dependency among people who use marijuana is estimated to be 9% , but among people who begin using marijuana before age 18, the likelihood to develop dependence is almost doubled and developing symptoms of problem use is estimated to be 4 to 7 times more likely .

Among adults the cognitive effects of marijuana use generally disappear within a month, when the last traces of the fat-soluble THC molecule dissipate . In contrast, neuroimaging studies have shown that regular marijuana use in adolescence is associated with changes to areas of the brain involved in executive functions like memory, attention, learning, retention, and impulse control . Advances in brain imaging technology have made it possible to directly observe the impact of substance use on the brain ,cannabis drainage system which has resulted in a greater understanding of the mechanisms by which marijuana use interferes with normal brain development. Studies using prospective case-control and other longitudinal designs have found that cognitive effects from repeated marijuana use during adolescence persist into adulthood . Windle and colleagues recently reported results from a prospective study that followed U.S. children into adulthood where they found that substance use between the ages of 13 and 15 years old was associated with a smaller amygdala, a brain region that develops earlier in adolescence and is crucial to emotional regulation. The authors also found that substance use between the ages of 16 and 18 years old was associated with a lower volume of gray matter in the pars opercularis, a region of the brain that develops later in adolescence and is responsible for cognitive control. These very recent research findings suggest that not only does substance use during adolescence result in changes to the brain that persist into adulthood, but that initiating regular use at different times may affect different regions of the brain according to which regions are in active development at the age when the substance use is occurring. Recent research has documented that endocannabinoids are instrumental to the final processes of brain development that occur during adolescence . Receptors for endocannabinoids begin to increase in the subcortical and frontal cortical regions of the brain during childhood and peak in adulthood, which has led scientists to conclude that the endocannabinoid system is a mechanism through which greater degrees of cognitive control are achieved between childhood and adulthood . During normal neural development endocannabinoid receptors are pruned as part of the consolidation of neuronal pathways that increases efficiency in signals to and from the prefrontal cortex, which in turn increases the capacities for cognitive control and self-directed behavior . If THC molecules replace the endocannabinoids that drive these processes, it alters the way the brain consolidates neuronal pathways throughout adolescence, which may in turn result in less capacity for cognitive control and self-directed behavior in adulthood . The Dunedin Longitudinal Study, a prospective cohort study conducted in Dunedin, New Zealand, has provided the best evidence of the long-term effects of marijuana use on intelligence and life prospects. In this study, 1,037 people were followed from birth into adulthood. Their intelligence was assessed at the ages of 7, 9, 11, and 13 years of age using the Intelligence Quotient test .

The Dunedin Longitudinal Study investigators found that repeated marijuana use before the age of 15 years old was associated with declines across multiple domains of cognitive functioning, even after controlling for years of education . Their research was the first to document a decline in cognitive functioning from adolescence to adulthood among adolescent-onset marijuana users compared to non-users and that cessation of marijuana use after adolescence did not fully restore neuropsychological functioning in adulthood. More recently, Cerda and colleagues used the Dunedin Longitudinal Study data to demonstrate that chronic marijuana use during adolescence and adulthood was associated with downward socioeconomic mobility and more financial difficulties, and workplace problems in early midlife, even when controlling for socioeconomic adversity, childhood psychopathology, achievement orientation, family structure, marijuana-related criminal convictions, early onset of marijuana dependence, and comorbid substance dependence. The threshold of adolescent marijuana use where loss of cognitive potential occurs or where dependence becomes a risk is unknown and likely differs by individual. Nevertheless, it is clear from the literature that earlier and more frequent marijuana use during childhood and adolescence is associated with a greater potential to disrupt normal brain development and to develop problem substance use . More randomized controlled trials and prospective cohort studies are needed to definitively characterize the impacts of marijuana use on adolescent brain development, but the current body of literature persuasively documents the importance of minimizing exposure to THC during adolescence . The 2017 National Survey on Drug Use and Health Annual Report indicates that 25% of 9th graders and 37% of 11th graders in the U.S. report lifetime marijuana use, while 13% of 9th graders and 18% of 11th graders in the U.S. report having used within the past 30 days . The Monitoring the Future study found that as of 2017, 6% of 12th graders in the U.S. report daily use of marijuana, which corresponds to about one in 16 high school seniors . Rates of recent marijuana use among adolescents in California are over three times higher than the national average; 22% of California adolescents aged 12-17 reported using marijuana in the past 30 days in 2017 , compared to 6.5% nationally . NSDUH trend data for California between 2002 and 2014 indicates that among youth aged 12-17 there has been an overall increase of 16%, but also that there was not a consistent trend of increase. Instead, marijuana decreased from the 2002-2003 study years through the 2005-2006 study years and held relatively steady before increasing again during the 2010-2011 study years . A Community Needs Assessment conducted by the LA County Department of Public Health in 2017 indicates that nearly half of LA County residents aged 12 or older have used marijuana at least once in their lifetime and that 14% had used marijuana in the past 30 days. It also found that residents were an average age of 17 years old when they first used marijuana, with a majority using marijuana for the first time before age 18. Similar to national and state reports of the perceived accessibility of marijuana, the LA County assessment found that most County residents over the age of 12 perceived it easy to access marijuana in their neighborhood. The marijuana users in the study most commonly obtained their marijuana from a friend , followed by a dispensary , family/relative , or the illicit market . More specific data is available from the YRBSS survey for the Los Angeles Unified School District and indicates a local pattern different from what has been observed at a state level . Changing attitudes to perceive marijuana use as more socially acceptable and less of a health risk have been noted among youth populations, but whether changes in these attitudes are the result of policy changes or of a general secular change in attitudes toward marijuana is often difficult to determine. Some research supports the idea that the increasingly liberal state laws governing marijuana in the U.S. stem from more positive adult attitudes toward marijuana rather than the reverse. For example, rates of marijuana use among adults is higher in states that have approved medical and recreational marijuana laws, but the higher rates of marijuana use in these states preceded enactment of the laws, suggesting that the more liberal attitudes toward marijuana use were a motivation for liberalizing marijuana laws .

Two hundred adolescents were consented into the study and completed the baseline visit. Of those, 28 denied smoking cigarettes in the past 30 days and 7 declined to answer the question about marijuana use and were thus excluded from the analysis. The resulting sample had a mean age of 16.1 years and was racially diverse, with 28% participants identifying as White, 19% African American, 19% Hispanic and 34% other. Participants averaged 3.01 CPD for a duration of 1.98 years . Fifty-one participants reported daily cigarette smoking and 111 reported non-daily smoking . Mean scores were 2.56 on the mFTQ , 4.52 on the HONC , -1.75 on the NDSS , and 10.13 on the ICD-10 . Most participants reported marijuana use in the past 30 days with 43 using weekly, and 62 reporting daily use. Frequency of marijuana use was correlated with CPD , but not with the frequency of alcohol use .In general linear models controlling for age, years of smoking, and daily versus non-daily smoking, frequency of marijuana use was significantly and positively associated with nicotine addiction . The findings were consistent across all four measures of dependence and remained significant for the mFTQ after removing the question on CPD. When examining the NDSS sub-scales, only the drive and priority sub-scales were significantly associated with marijuana frequency. Older age, more years smoking, and daily smoking were associated with greater nicotine dependence in all models. The total percent of variance predicted ranged from 25% for the HONC to 44% for the mFTQ and NDSS. Illicit drug use may co-occur across substances,cannabis growing equipment and follow-up analyses sought to examine whether the finding of an association with nicotine dependence was specific to marijuana.

Therefore, we also assessed co-use with other illicit substances. In the past 3 months, 40 participants reported ecstasy use. A small number of participants reported use of cocaine/crack , methamphetamine , mushrooms/ mescaline , heroin , Percocet/Vicodin , or LSD , preventing inclusion in analyses. Ecstasy, included as a covariate in the fully adjusted general linear models, was not a significant contributor with p-values ranging from .24-.99 and the effects for marijuana remained largely unchanged. Marijuana smoking was prevalent in this adolescent sample of tobacco smokers: 80% reported past month marijuana use and more than a third smoked marijuana daily. Notably, among adolescent tobacco smokers who also smoked marijuana, the frequency of marijuana use was associated with greater levels of nicotine addiction on all three major scales used in studies with adolescents plus the ICD-10. Moreover, models incorporating age, frequency and years of tobacco smoking with marijuana accounted for 25-44% of variance in adolescent nicotine dependence. Interestingly, CPD was only minimally associated with the frequency of marijuana use and made minimal contribution to the model since associations with the mFTQ were similar after removing the question about CPD.The finding that with the exception of drive and priority, the other sub-scales of the NDSS were not significantly associated with marijuana frequency was not surprising since most of these adolescent smokers were light and intermittent tobacco users and dimensions of dependence such as stereotypy and tolerance become more prominent as teens develop more regular and established patterns of smoking . However, despite relatively light tobacco use, the drive sub-scale, which measures the compulsion to smoke, and the priority sub-scale, which measures the preference of smoking over other reinforcers, were associated with marijuana use. It is possible that since both marijuana and tobacco share common pathways of use, smoking cues for one substance may trigger craving for the other, and thus reinforce patterns of use. As such, tobacco and marijuana may serve as reciprocal reinforcers.

Some limitations of this brief include the relatively small sample size and the lack of detailed information on the timing of the initiation of marijuana use with regard to cigarette smoking. Future studies will need to examine how the proximity of marijuana use to cigarette smoking affects the degree of nicotine addiction. For example, examining whether concomitant use impacts the level of nicotine addiction more than smoking marijuana separately from tobacco. The sample largely consisted of light smokers, which reflects adolescent smoking in the US. That we found such a strong association between marijuana use and nicotine addiction in this group of relatively light tobacco smokers is notable, and reinforces the relevance of the association. Recreational marijuana commercialization is gaining momentum in the US. Among the 11 states and Washington DC that have legalized recreational marijuana since 2012, retail markets have been opened or anticipated in 10 states, where over a quarter of the US population live. The presence of recreational marijuana dispensaries increased rapidly following the commercialization. Children are at a high risk of initiating marijuana use and developing adverse consequences related to marijuana. The rapidly evolving environment poses considerable concerns about children’s exposure to marijuana and related marketing and creates significant challenges for pediatricians preventing, treating, and educating about marijuana related harms among children. As stated in its most recent policy statement about marijuana commercialization, the American Academy of Pediatrics “strongly recommends strict enforcement of rules and regulations that limit access and marketing and advertising to youth”. The presence of RMDs in neighborhoods and point-of-sale marketing such as advertising and promotional activities in RMDs might increase the visibility and awareness of marijuana products among children, whose perceptions and behaviors may be influenced. A study in Oregon found that dispensary storefront was the most common source of advertising seen after commercialization. 

Self-reported exposure to medical marijuana advertising was found to be related to higher levels of use and intentions of future use among children in California schools. Products, packages, and advertisements that are designed to be appealing to children are particularly concerning. Tobacco and alcohol literature repeatedly suggested that children are common targets of marketing. Despite the fact that all the states with marijuana commercialization have some form of prohibitions on child-appealing products and marketing, it remains undocumented as to what extent the marijuana industry is complying. This study is the first to comprehensively assess point-of-sale marketing practices in RMDs with a focus on those relevant to children. Unlike previous marijuana research relying on individual self-reported exposure measures, we adopted the direct and objective observation approach that has been commonly used in tobacco and alcohol studies on retail outlets. We audited RMDs near a representative and large sample of schools in California, the largest legal retail market in the US where over 10 million children can be potentially influenced. We identified product and packaging characteristics, advertising and promotional activities,cannabis grow table and access restrictions in these dispensaries. Six trained field workers audited retail environments in RMDs in closest proximity to the 333 schools . We first identified dispensaries using crowd sourced online websites, including Weedmaps, Wheresweed, Leafly, and Yelp. State licensing records were not used because they could not provide a complete list of dispensaries at the time of data collection. Specifically, 1) Marijuana commercialization in California took effect in January 2018. During the study period, California was in a transition stage when annual licenses were just issued, and most were not approved. 2) The licensing policy in California was not enforced, with a large portion of dispensaries operating without licenses. 3) For licensed dispensaries, the registered and actual business name and address often mismatched. Alternatively, we utilized crowd sourced databases, which were considered as reliable, up-to date, and comprehensive sources of dispensary directories. To identify the dispensary closest to a school, field workers entered school zip code in the online searchable databases. The street addresses of all the dispensaries with the school zip code were geocoded and mapped in ArcGIS to compute their distances to the school. Field workers then called the dispensary with the shortest distance to verify its address and operational status. These procedures were repeated if a dispensary was permanently closed or not verifiable via multiple calls until an active dispensary was identified. The primary focus was RMDs. Yet, medical marijuana dispensaries that require a doctors’ recommendation or state patient ID cards coexisted in California in 2018. During call verifications, if dispensary staff indicated that a doctors’ recommendation or a patient ID was required to enter the dispensary and make purchase, the dispensary was categorized as a MMD.i Fieldworkers also verified dispensary classification during the subsequent auditing. For those verified as MMDs, we repeated the aforementioned procedures until an active RMD was identified.

The six trained workers in teams of two audited verified RMDs.ii On average, each RMD visit took 10-15 minutes. The 103 RMDs had unique RMD-school pairs and the 60 RMDs were the closest ones to two or more schools out of the remaining 230 schools. In the main analysis, we reported observations in the unique RMDs . In the secondary analysis, we reported observations on RMDs using school as the unit of analysis . The 60 RMDs shared by two or more schools were counted multiple times or over-weighted in the secondary analysis, reflecting their potential to influence children in multiple schools. The Human Research Protections Program at the University of California San Diego deemed this research non-human-subject and required no review. We validated SMDA-CF through a pilot test on 18 RMDs in California. To calculate inter-rater reliability, two workers in a team independently audited the same dispensaries. Reliability analysis indicated moderate to high reliability for SMDA-CF as a whole . Because of the concerns about some low-reliability items, in the formal field work of auditing 163 RMDs, the two workers in a team audited dispensaries together and discussed to resolve discrepancies before submitting observations. This study demonstrated that, in the early stage of marijuana commercialization in California, point-of-sale marketing practices that are appealing to children were minimal on the exterior of the RMDs around schools. However, such practices were abundant on the interior. Marketing practices not specifically appealing to children were common on both the interior and exterior of the RMDs. Given the age limit, RMDs’ exterior marketing might be the most concerning source of exposure for children. It is reassuring that child-appealing marketing was rarely observed on the exterior of the RMDs around schools. Yet, three quarters of the RMDs had some form of child appealing marketing on the interior, which violated the California laws. Although children should have little direct access to the interior, child-appealing items may be available to children through indirect pathways and should not be overlooked. For instance, children’s social networks such as older relatives, peers, or caregivers are their important sources of drugs. A study reported that almost three quarters of underage users obtained marijuana from friends, relatives, or family members. Child-appealing products, paraphernalia, or promotional materials could then be made available to children through these adults who are eligible for marijuana purchase. Particularly, about 30% RMDs violated the California law to offer free samples, which could be taken out of the dispensaries and given away to children. These child-appealing items in RMDs could be also resold to children in illicit markets by street dealers. Research on tobacco and alcohol have suggested that children are exposed to and influenced by tobacco and alcohol products and point-of-sale marketing despite the age limit for purchase . Whether and how the marketing activities inside of RMDs impact children’s perceptions and behaviors should be examined in future research. Meanwhile, exterior retail environments not specifically relevant to children still warrant further attention. For instance, 63% RMDs had image or wording indicative of marijuana on the exterior. One third of the RMDs had generic advertisements, and some advertisements were of a relatively big size. Marijuana could be smelled outside of 25% RMDs. All of these might potentially increase perceived presence of RMDs in the neighborhoods and shape children’s social norms. Approximately half of schools had RMDs located within a 3-mile distance that is reachable to children by walking, cycling, or driving. Some RMDs were located further away, especially in suburban or rural areas. Nonetheless, children are not free from exposure to RMDs even if RMDs are located more than 3 miles away from schools. In 2009, the average travel distance from home to school among all school children was 4.4 miles; among high school students, the average distance was even longer . 

Political process theory sprang from resource mobilization in the 1970s . It provided the dominant framework for U.S. sociologists throughout the 1970s, 1980s, and into the 1990s . Essentially, political process theory emphasizes the importance of political, legal, and cultural contexts in shaping the outcomes that social movements achieve. Many of the insights and concepts of political process theory guide my analysis of the drug policy reform and medical marijuana movements in the middle chapters of this dissertation. Eventually new social movements theory, which began in Europe in the early 1980s, and the cultural turn in the social sciences would influence social movement scholarship in the U.S. The latest currents in the field have been the emotional turn and the study of global social movements . Throughout this dissertation I will be synthesizing various strains of social movement theory to analyze the development of the drug policy reform movement, the sites where it constitutes itself, the features of the medical marijuana movement within it, and the transition of medical marijuana from a social movement to a hybrid of movement and industry. In this dissertation, I explore the origin, development and growth of the medical cannabis phenomenon in California. Medical cannabis is the most significant change to drug policy since the United States formally prohibited cannabis in the 1930s. Essentially,hydro tray the medical marijuana phenomenon represents the most successful movement outcome for the wider drug policy reform movement. Movement outcomes have received relatively little attention from social movement scholars, who have focused on issues of movement emergence, recruitment, elite benefactors, and political context .

The emergence of medical cannabis at the height of the War on Drugs is quite remarkable, and leads to several research questions that guide the organization of this dissertation. The relative success of the medical marijuana movement demonstrates that drug policy reform is possible, but very difficult to achieve. The movement highlights the power that opponents of reform wield in maintaining the regime of prohibition. This section uses political process theory to first account for the factors that contributed to the initial development of medical marijuana in the Bay Area. Next it looks at how activists shape political opportunity structures in different parts of the state, and who differing structures lead to different outcomes with regard to medical marijuana dispensaries. Using a diverse set of qualitative research methods, I address this set of research questions to provide a comprehensive view of one specific type of drug policy reform. My goal is to first situate the medical cannabis movement historically, within the context of nearly a century of drug prohibition and four decades of drug policy reform. Next I seek to situate the movement for drug policy reform spatially, by observing the sites where participants in the movement are active and where the movement largely takes place. Third, I analyze the components of the political opportunity structure of the San Francisco Bay Area, and how they contribute to the nascent movement in the early 1990s. Fourth, I compare the political opportunity structures for medical cannabis in three California cities, noting how activists have influenced the structure of opportunity. Finally, I account for how the movement has changed into a hybrid and what that change entails for the future of the movement and social movement theory. Originally, my central research question was, how did the medical marijuana movement begin, grow and change, and how has the state responded? I also wanted to examine the relationship between the drug policy reform movement and medical marijuana in California.

My original point of departure was based on the episteme of dependent and independent variables. I hypothesized that the drug policy reform movement was the independent variable and that phenomenon of medical marijuana was the dependent variable. I sought to measure the influence of the drug policy reform movement on the form and character of medical marijuana. After seven years of fieldwork as a participant observer in various aspects of the medical marijuana movement, I have revised this antiquated image of variables for an approach premised on the dynamic and dialectical relationship between the phenomenon of medical marijuana and the drug policy reform movement. While the DPRM played a key role in the expansion of medical marijuana from the San Francisco Bay Area to the entire state of California in 1995 and 1996, its role was only critical during the ballot initiative process. Shortly thereafter, medical marijuana began to have a pronounced impact on the drug policy reform movement. It changed the movement’s focus, enlisted new participants and constituents , altered its priorities and most important, provided the movement with its first major success story since the mid 1970s. After the electoral success of Proposition 215, the national organization Americans for Medical Rights formed to export the ballot initiative approach to other states where it became a viable avenue for the legalization of medical marijuana. Newer organizations, including Americans for Safe Access, formed in response to emergent challenges faced by medical cannabis patients and dispensaries. I seek to move beyond other academic and journalistic treatments of medical marijuana that treat the electoral success of proposition 215 as the end point in the struggle for medical marijuana. From my field research, I’ve discovered that the provision of medical cannabis is an ongoing process.While legal change is a necessary first step in implementing drug policy reform, it takes dedicated action on the part of organizations, cannabis providers and local governments to allow for the existence of cultivation and dispensaries “on the ground.” Because of ongoing opposition to medical cannabis on the part of federal law enforcement agencies, new drug policy modalities have to be constantly defended and protected. I theorize the implementation of a new system for cannabis provision as an outcome of the drug policy reform movement.

By theorizing the provision of medical marijuana as a movement outcome, I seek to shed light on a lesser-studied aspect of social movements, how movements contribute to both institutional and cultural change. The provision of medical marijuana through collectives and storefront dispensaries is a profound departure from the regime of punitive prohibition, where the production and consumption of marijuana are relegated to the illicit market and hidden from public view. By opening up a novel system for the production and consumption of cannabis to state and public scrutiny, the medical cannabis movement has profoundly altered the cultural representation of cannabis, planting table transforming the plant from dangerous to therapeutic. While I draw extensively from political process theory to explain the shape of the medical marijuana movement’s success in changing the legal and institutional status of cannabis, the movement has also had a profound effect on the cultural status of the substance. To theorize the provision of cannabis as a movement outcome, I define medical cannabis collectives and dispensaries, as “modalities of reform.” These modalities are characterized by physical locations, and a set of practices that participants engage in to provide cannabis in a licit manner. Although lobbying, organizing, and other social movement activities may occur at such sites, the primary purpose of such modalities is the provision of cannabis. To answer this set of research questions I will draw on social movement theory and six years of qualitative fieldwork in the overlapping medical marijuana and drug policy reform movements. My study first looks at the history and discourse of drug prohibition, then the history of the drug policy reform movement and the specific sites where the movement occurs. Next, I will examine the medical marijuana movement. For analytical purposes, I have divided the movement into three distinct phases, birth, development, and fruition. The first, or birth, phase looks at how the movement originated in the San Francisco Bay Area, and the specific features of that region that contributed to its formation. This stage lasts from roughly 1990 to 1996. Next, I look at the development of the movement, how it spread outward from the Bay Area and the different approaches to medical marijuana taken by activists, providers and officials in different parts of California. This stage lasts from 1997 to 2009. Thirdly, I will examine how the medical marijuana movement has transformed into an industry.My in-depth study of drug policy reform at both the organizational and practical levels required me to branch beyond the traditional methods of quantitative sociology. I sought to get the inside story from insiders’ perspectives, to construct new categories of analysis, and to use these categories to understand the ever developing phenomenon of drug policy change. Since the data I sought was not amenable to quantitative analysis, I eschewed surveys, secondary data analysis and structured interviews. To conduct this study I employed four main types of research methods; participant observation at cannabis dispensaries, drug policy reform conferences, organization meetings, and festivals, depth interviews with activists and organization leaders, archival research of movement websites and literature, and archival research of media coverage of drug reform modalities and movement outcomes. I also analyzed state response to this movement as conveyed through official documents and news sources.

As my project progressed, I used the Internet to explore how the movement uses social networking sites to connect activists to one another and to coordinate new forms of Internet based action. My ultimate goal for this research project is to construct a coherent historical narrative of the drug policy reform and medical marijuana movements. Because I sought to create a narrative, qualitative methods were well suited to my task. At the beginning of the process, I needed to look at existing sources on my topic to discover where I needed to fill in the blanks. My use of theory and method was hybrid in form. Because of my exploratory orientation, I intended to deviate from the deductive, theory testing, orientation that guides much quantitative work in sociology Although I did not intend my study to be exclusively generative of entirely novel “grounded theory” , I also did not completely eschew existing theoretical work in the sociology of social movements and sociology of drugs. Instead I used a dialectic approach employing existing theories from the study of social movements to guide my initial research, and a grounded theory orientation to new data I found that augmented, stretched and contradicted existing theory. This qualitative approach is well suited to my purposes of constructing a narrative of drug policy reform from the viewpoints of its participants, and presenting a study that is amenable to the goals of public sociology . To map the distribution of the wider drug policy reform movement, initially I examined movement documents, literature from conferences and organization websites to discover and catalog the various organizations that comprise the movement. This aspect of my project gave me an understanding of the various concerns that motivate organizations in the movement, its organizational bases, and the number and size of organizations involved in the wider movement. Through cataloging the various organizations that comprise the movement, I was also able see the geographical distribution of movement organizations. The websites of drug policy reform organizations will also provide an understanding of the way that movement actors frame their concerns and goals, and which symbols and values they use to animate their activism. Recently, social networking websites including “Facebook” have afforded activists with new venues for networking and engaging in lobbying activities. Internet based activism has included organizing boycotts of corporations unsympathetic to drug use, petitioning government officials and Congressional representatives, and keeping members abreast of organizational campaigns. In addition to linking participants to one another and keeping them informed about movement activities, social networking sites also offer activists a platform for lobbying politicians and publicizing their efforts. I will include an examination of these websites to assess the breadth of activity in this movement. The primary research method I used to conduct my research was participant observation. As noted above, I have participated in drug policy reform for over ten years. Throughout this study I also directly participated in a particular modality of drug policy reform, working in a medical cannabis dispensary. By working as an employee in a medical cannabis dispensary, I was able to experience first hand what became a central discovery of my research, the hybrid character of the medical marijuana movement .

Marijuana smoking, the predominant method of use, causes a 5-fold increase in the blood carboxyhemoglobin level and a 3-fold increment in the quantity of tar inhaled compared with tobacco . Studies on secondhand marijuana smoke have found endothelial dysfunction in rats after exposure . Given the myriad ways in which marijuana might potentiate vascular disease, we conducted a systematic review to assess the effect of regular marijuana use on cardiovascular outcomes and their associated risk factors. The protocol was registered at PROSPERO  at the start of our investigation. This review focuses on studies examining marijuana use and cardiovascular risk factors and outcomes; our protocol also includes searches and a review of hemodynamic changes associated with marijuana use that are not reported here. We searched several online databases for titles and abstracts between 1 January 1975 and 30 September 2017. We chose a 1975 start date because that was the year the Alaska Supreme Court ruled that the “Alaska constitution’s right to privacy protects an adult’s ability to use and possess a small amount of marijuana in the home for personal use” . We also conducted reference and author tracking to identify additional articles and searched Clinical-Trials.gov and the National Institutes of Health Research Portfolio for ongoing or completed studies not reported in the literature. For search terms and details, see Supplement 1 . All titles and abstracts were independently screened by 2 reviewers . We included observational studies and interventional studies that enrolled participants older than 12 years and were published in English. The exposure criterion was any form of marijuana .

The main outcomes of interest were cardiovascular risk factors and outcomes. We excluded case reports, case series, review articles, editorials,grow table and in vitro and animal studies. The same 2 investigators independently reviewed the full texts of selected articles to identify those that met our inclusion criteria. Disagreements regarding inclusion were resolved by a third reviewer . Inter rater reliability for the abstract selection process and the concurrent decision to include the article in the review was excellent . For the selection process, see Supplement 2 . Eleven studies provided data on 1 or more metabolic parameter outcomes, including hyperglycemia, dyslipidemia, and diabetes . Five cross-sectional studies examined the association between marijuana use and hyperglycemia, dyslipidemia, metabolic syndrome, or diabetes . Marijuana use was measured by self-report in all studies. Four studies were based on 3 different waves of the NHANES . Three of the 4 used multi-variable analysis to examine the association between marijuana use and metabolic parameters after adjustment for baseline characteristics. All 3 studies reported that marijuana use had different favorable associations, including a lower prevalence of diabetes , lower glucose levels , or higher high-density lipo-protein cholesterol concentrations . The fourth NHANES study used both regression models and an instrumental variable analysis to examine associations . Marijuana use was associated with a beneficial metabolic effect in the regression model evaluation; no such effect was seen in the instrumental variable analysis. The final cross-sectional study was an exploratory analysis based on a small sample of 30 persons who were heavy marijuana users and 30 control participants matched for age, sex, ethnicity, and body mass index . The authors identified no differences between groups in glucose tolerance or fasting glucose, total cholesterol, or triglyceride levels. Three prospective studies examined the association of marijuana use with risk factors .

Two were based on the CARDIA cohort study, which examined the development and determinants of clinical and sub-clinical cardiovascular disease and its risk factors . The CARDIA study began in 1985 to 1986 with 5113 black and white men and women aged 18 to 30 years. It included comprehensive in-person baseline and outcome data and several exposure assessments during a long follow-up. Questions pertaining to marijuana use lacked detail on the form used, and exposure was quantified differently in each study. The low-ROB CARDIA-based study reported no associations between marijuana use and changes in glucose, high-density lipoprotein cholesterol, or triglyceride levels among heavy users compared with nonusers during 15 years of follow-up . The moderate-ROB CARDIAbased study examined the association between marijuana use and diabetes and pre-diabetes . Marijuana use was ascertained in year 7 of the prospective cohort, and exposure was very limited: The highest category of use was a lifetime frequency of more than 100 times. Incidence of diabetes and prediabetes assessed at 4 subsequent follow-up examinations over 18 years was based on laboratory assessment . A greater risk for prediabetes was identified among participants who reported using marijuana 100 or more times during follow-up compared with nonusers. The final prospective study followed 18 000 Swedish men and women aged 18 to 84 years over 10 years but assessed marijuana exposure only once, at baseline . Measures of socioeconomic factors, diet, or other drug use at baseline were limited. No definite relationship was found between marijuana use and diabetes; CIs around the risk estimate were wide and compatible with either increased or decreased risk for diabetes with marijuana use . Two experimental studies examined the effect of cannabis-related compounds on metabolic factors . Both had small sample sizes, and neither identified a measurable effect on metabolic parameters.

The association between marijuana use and obesity was evaluated in 1 prospective study; 1 retrospective study; 1 randomized controlled trial; and 4 cross-sectional studies, 2 of which were based on NHANES . None of these studies found an association between marijuana use and BMI. Another cross-sectional study of 786 Inuit adults found that participants who used marijuana in the past year had a lower BMI than nonusers . Although this study included important baseline characteristics, such as physical activity and dietary intake, the marijuana exposure assessment that divided the population into ever- and never-users was inadequate . Another study examined the charts of 297 women referred for weight management and found that marijuana use was associated with a lower BMI . This trial was limited by lack of adjustment for baseline characteristics and biased sample selection . One prospective cohort study found no association between marijuana use and changes in BMI . In a longitudinal pre birth study in 7223 women and their offspring , the children were administered health, sociodemo-graphic, and lifestyle questionnaires at ages 14 and 21 years . Although BMI was measured at both ages,4×8 grow table with wheels a retrospective assessment of marijuana use was conducted only at age 21. Daily cannabis users were less likely to have a BMI greater than 25 kg/m2 than were never-users. This study was limited by inadequate baseline data on the children. In a small double-blind placebo-controlled randomized trial , the effect of 5 mg of dronabinol on BMI was assessed at 28 days in 13 of the 19 participants who completed follow-up . No statistically significant association was found between marijuana use and BMI. The MIOS was a case-crossover study that examined marijuana use as a potential trigger for myocardial infarction . In this multi-center trial, 3882 patients with acute myocardial infarction were interviewed, on average within 4 days of their infarction, about their history, timing, and frequency of marijuana smoking. Marijuana use in the 1 hour immediately preceding the onset of myocardial infarction symptoms was then compared with its expected frequency on the basis of self-reported use during the previous year. Of the 3882 patients, 9 and 124 reported smoking marijuana within 1 hour of the onset of myocardial infarction symptoms and in the previous year, respectively. The myocardial infarction risk in the first hour after smoking was greater than that expected among users . That individuals served as their own control helped limit confounding from other behaviors that may be associated with marijuana use. The study, however, was assessed as moderate ROB, primarily because of recall bias.Two prospective studies examined the effect of marijuana exposure on stroke and transient ischemic attack .

One study , based on CARDIA, reported that marijuana was not associated with stroke ; however, the exposure was minimal and the population was young and healthy . Another study enrolled 49 321 Swedish men conscripted into compulsory military service between the ages of 18 and 20 years. They were followed until age 59 to assess the initial occurrence of stroke. No association between cannabis use and stroke was identified, but the study was limited by potential misclassification of the exposure, given that it was not reassessed over 25 years of follow-up and adjustment for baseline characteristics was inadequate . A third study using a case–control design compared patients admitted to the hospital for stroke or transient ischemic attack with other, matched hospitalized patients. It found no association between stroke and plant-based marijuana use ; however, the study was limited because it measured use with urine toxicology screens, and although all case participants were screened, it is unclear why the control participants underwent screening. The urine drug screen may have misclassified exposure, because results may remain positive for up to 10 weeks . Two prospective cohort studies involving myocardial infarction survivors enrolled in MIOS between 1989 and 1996 examined the association between marijuana use and mortality . Marijuana use in the year before the first myocardial infarction was self-reported at baseline and was not evaluated again. Cause of death was assessed by physician review of death certificates. In the study that followed patients for a median of 3.8 years, baseline use of marijuana once weekly or more and less than once weekly was associated with an increased risk for cardiovascular mortality compared with nonuse. This study also found an association between marijuana use and an increased risk for all-cause mortality . In the other MIOS-based study, which followed patients for a median of 12.7 years, any marijuana use was associated with an increased risk for all-cause mortality compared with nonuse, although the finding was not statistically significant . Another investigation used CARDIA data to examine the association between cumulative lifetime marijuana use and cardiovascular mortality . This study measured exposure several times and had robust assessment of baseline characteristics and outcomes. It found no association between marijuana use and cardiovascular mortality . The study also included a composite outcome of cardiovascular mortality, stroke, and coronary heart disease and, again, found no association between 5 or more years of marijuana use and this combined outcome . However, median cumulative marijuana exposure in the cohort was minimal . Further, although participants were followed for 26 years, the median age at recruitment was 18 to 30 years. Because of these factors, the study probably was under-powered to assess the association between marijuana use and cardiovascular disease. Finally, a retrospective cohort study linking NHANES to the National Center for Health Statistics survey found that users were at higher risk than nonusers for “hypertension-related” mortality. However, the marijuana exposure assessment was flawed, the outcome definition unclear, and the adjustment for baseline differences inadequate . Four studies examined the association between marijuana use and various outcomes, including peripheral arterial disease , irregular heartbeat , multi-focal intracranial stenosis , and aneurysmal subarachnoid hemorrhage . All 4 studies were rated as high ROB, primarily because their marijuana exposure assessments and adjustments for baseline risk factors were inadequate.Evidence that marijuana use either increases or decreases most cardiovascular risk factors is insufficient, as is evidence regarding any association between marijuana use and adverse cardiovascular outcomes . The current available literature is limited by a preponderance of cross-sectional study designs. Although the literature includes several long-term prospective studies, they are limited by recall bias, a lack of robust longitudinal assessment of marijuana use, participants with infrequent marijuana use, and the relative youth of some of the cohorts. A MEDLINE search revealed a recent systematic review of marijuana harms that identified 2 studies on the relationship between marijuana use and cardiovascular events . We included both articles in our systematic review and assessed 1 of them differently, assigning its ROB as moderate rather than high . The strength of this study lies in the minimization of confounding.The use of a case-crossover design in the study of marijuana compares each participant to him- or herself and eliminates this problem.