Hemp Growing

We used linear mixed-effects models to assess changes in continuous outcomes over time: post-bronchodilator FEV1, post-bronchodilator FVC, SGRQ total score, CAT score, and HRCT metrics. Linear mixed-effects models, specifically proportional odds models, were used to assess changes in respiratory symptoms over time. In assessing whether marijuana use among tobacco smoking participants without COPD at baseline increased the risk of subsequent development of COPD, the primary outcome was time to development of airflow obstruction, defined by a post-bronchodilator FEV1/FVC<0.70.We used zero-inflated negative binomial models to compare the rate of exacerbations between CMSs, FMSs, and NMSs. Exacerbations were classified as moderate , severe , and total . To assess dose response relationships, the same models were used with the primary predictor of interest being categorical joint-year history at baseline.A consort diagram describing the derivation of the study cohort is shown in Figure 1. At enrollment, CMSs, when compared with NMSs, tended to be younger and more often current tobacco smokers, men, and Black .They also had fewer exacerbations during the year prior to enrollment, had a better FEV1, less frequent airflow obstruction, and less emphysema and air trapping, but had similar levels of respiratory symptoms. Similar findings were noted in comparison of FMSs with NMSs. Due to incomplete reporting, calculating the cumulative lifetime amount of marijuana use in joint years was not possible for all participants, so that the number of those classified by joint-year category is lower than that of the total analysis sample. Among those with the heaviest marijuana use , directionally similar baseline differences were noted in age, sex, the proportion of Black participants,industrial rolling racks and current tobacco-smoking status compared to those with 0 joint years, as were found in comparison between CMSs and FMSs with NMSs . The estimated rates of change in continuous outcomes by baseline marijuana-smoking status are shown in Table 3A.

While numerically higher annual rates of FEV1 and FVC decline and higher rates of worsening CAT and total SGRQ scores were found comparing CMSs with NMSs, these differences were neither clinically nor statistically significant . Similar rates of change in these parameters were found on comparison of FMSs with NMSs. Estimated rates of change in continuous outcomes between joint-year-based categories were similar across all joint-year groups and between groups . Estimated annualized FEV1 decline during follow-up by marijuana joint years stratified by former and current tobacco-smoking history were similar, irrespective of tobacco smoking status . Estimated participant-specific yearly changes in odds for worsening respiratory symptoms during follow-up compared to the baseline visit by baseline marijuana status and baseline joint years are shown in e-Table 9A and B and e-Figures 1 and 2 in the online supplement, respectively. The odds over time of more cough and sputum, but not more wheeze or dyspnea, were significantly higher in CMSs compared to FMSs or NMSs , while no significant differences were found across the different joint-year categories that included both CMSs and FMSs . Estimated yearly changes in CAT and SGRQ scores were not significantly different across marijuana-smoking status and joint-year categories as shown both in Tables 3A and B in the online supplement, respectively, and e-Tables 5 and 6 in the online supplement, respectively. Our analysis showed nominally less emphysema, air trapping, and functional small airways disease progression without statistical significance among CMSs compared to NMSs. Similarly, a comparison between NMSs, FMSs, and CMSs showed no significantly different changes in HRCT metrics, except for unadjusted increased total tissue volume loss among FMSs compared to NMSs . No difference in tissue volume loss between CMSs and NMSs was found.

Estimated rates of change in HRCT metrics were generally similar across all joint-year groups , except for a higher rate of increase in PRMf SAD on comparison of those with ≥20 joint years versus 0 joint years , with a between-group difference 0.393 when unadjusted for multiple testing . Estimated yearly rates of 1 or more total or severe exacerbations during the first 365 days or the total follow-up period by baseline marijuana-smoking status and marijuana joint years are shown in Table 4 A and B and e-Figures 3 and 4 in the online supplement. While rates of total and severe exacerbations were numerically lower among both CMSs and FMSs versus NMSs during the first follow-up year, and severe exacerbation rates were slightly higher among CMSs versus NMSs during the total follow-up period, none of these differences were statistically significant . Estimated rates of total and severe exacerbations were numerically higher among those with ≥20 versus those with 0 joint years during the first follow-up year. During the total follow-up period, rates of total exacerbations, but not severe exacerbations, were slightly higher among those with ≥20 versus those with 0 joint years. However, none of these between-group differences were statistically significant .Estimated hazard ratios for the development of COPD during follow-up by baseline marijuana-smoking status and joint years among participants without spirometric evidence of COPD at baseline are shown in Table 5 and e-Figures 5 and 6 in the online supplement. The odds of developing COPD by spirometric criteria were lower among CMSs and FMSs versus NMSs, as well as among those with ≥20 versus those with 0 joint years, although these differences were not statistically significant.The increasing prevalence of marijuana smoking among adolescents and adults,including aging adults,in the wake of a growing number of states legalizing marijuana use underscores the need to better understand the impact of marijuana use on lung health. This need is particularly evident among adult tobacco smokers in their mid- and older life who have been understudied previously.

The current analysis of the pulmonary consequences of marijuana smoking in the SPIROMICS cohort of current and former tobacco smokers with or at high risk of developing COPD is a longitudinal extension of a cross-sectional analysis of the baseline findings in the same cohort.10 While the latter cross-sectional study failed to identify deleterious effects of concomitant marijuana smoking on lung function or baseline structural radiographic abnormalities when compared with the effect of tobacco smoking alone, it could not answer the question of whether marijuana drying racks affects changes in these outcomes over 1 to several years of follow-up. In addition, the current study overlaps to some extent with a recent longitudinal analysis focused mainly on the trajectory of lung function in SPIROMICS participants limited to those with ≥3 spirometry visits.By including all those participants with ≥2, rather than only ≥3, spirometry visits at least 1 year apart, the current study has the advantage of including in the analysis larger numbers of CMSs and FMSs, most importantly of those heavy MSs with ≥20 joint years, in an effort to achieve greater statistical power in examining the influence of marijuana smoking on lung function decline. Furthermore, the current study examined changes in respiratory symptoms and HRCT metrics during follow-up that were not included in the previous report. Our study revealed trends toward higher rates of decline in post-bronchodilator FEV1 and worsening CAT and SGRQ scores among CMSs compared with NMSs and contrastingly, smaller rates of change in percentage of emphysema and functional small airways disease. However, none of these differences were statistically significant. Similarly, when we compared different categories of lifetime cumulative amounts of marijuana smoking, no significant differences were noted in rates of change in lung function, CAT or SGRQ scores, or HRCT metrics, except for an increase in PRMfSAD among the heaviest marijuana-smoking category in comparison to those with 0 joint years. It is noteworthy that significantly higher odds of worsening cough and sputum were noted among CMSs in comparison with both NMSs and FMSs, but not between FMSs and NMSs. The latter finding is consistent with previous data showing a significant reduction in symptoms of chronic bronchitis after cessation of marijuana smoking. Although some numerical differences were noted in rates of exacerbations across marijuana-use status and joint-year categories, none of the between-group differences were statistically significant. Finally, while the probability of subsequently developing COPD among tobacco smokers without COPD at baseline was lower among CMSs and FMSs compared with NMSs, as well as between the heaviest marijuana smokers versus those with no history of marijuana smoking, none of these differences reached statistical significance.

Taken together, the aforementioned data failed to demonstrate that marijuana smoking of any lifetime cumulative amount had a demonstrable effect on changes over time in clinical outcomes relevant to COPD, including respiratory symptoms, health status, HRCT metrics, or frequency of exacerbations. Our failure to find any impact of even heavy marijuana smoking on lung function decline in ever-tobacco smokers with or at risk of COPD differs substantially from the findings of Tan et al.The authors demonstrated a dose-response effect of marijuana on lung function decline in the CanCOLD study subcohort with a significantly greater rate of decline in FEV1 only among those with ≥20 joint years compared to those who never used marijuana . Surprisingly, in the same study, among those with ≥20 joint years of marijuana smoking, the rates of FEV1 decline were very similar for CMSs and FMSs, compared to NMSs. In contrast, the average rate of FEV1 decline among the heaviest former tobacco smokers was substantially lower than that of the current tobacco smokers. Since tobacco smokers with COPD have a substantial reduction in the rate of FEV1 decline after sustained smoking cessation,34 the disparate findings of Tan et al15 comparing the impact of quitting marijuana with that of quitting tobacco is surprising. The absence of a difference in the rates of decline between their current and former marijuana smoking participants, most of whom were dual smokers of marijuana and tobacco, may be a reflection of the impact of continuing tobacco smoking among those who had quit using marijuana rather than of an enduring effect of marijuana among the quitters. It is also noteworthy that the number of SPIROMICS participants who were particularly heavy marijuana smokers  was almost 3 times higher than the number of CanCOLD participants with a heavy marijuana smoking history , suggesting that our analysis of the impact of heavy marijuana use on lung function decline had greater statistical power. Finally, while the reference control group in our analysis of FEV1 decline in relation to marijuana smoking consisted of NMSs with a history of at least 20 pack years of tobacco smoking, the reference group in the analysis reported by Tan et al was comprised solely of never smokers of either substance. Thus, our aim was to examine whether marijuana smoking had an impact on the progression or development of COPD in current or former smokers of tobacco who already had COPD or were at increased risk of developing COPD, while Tan et al evaluated whether marijuana smoking led to an accelerated decline in lung function in a population of whom 43% were nonsmokers of tobacco.Our findings are also at odds with the results of another recent study by Winhusen et al.Using data from electronic health records of patients treated in an integrated health care system located in Northeast Ohio, the authors reported a significantly greater risk for COPD, defined using International Classification of Diseases, 9th and 10th revisions’ codes, among persons with a diagnosis of cannabis use disorder compared to propensity-matched controls in a subgroup of patients with a diagnosis of tobacco use disorder . These findings imply an additive effect of cannabis on top of tobacco use. However, limitations of the latter study include misclassification of COPD in the absence of spirometry data, suggested by the relatively young average age of the authors’ analysis population versus ours , as well as the absence of data on the route of cannabis administration and the intensity and duration of its use. The marked disparity of these results with ours underscores the need for additional study. The possibility of a dose–response impact of marijuana exposure is suggested by our finding of a significantly larger effect of ≥20 joint years on PRMfSAD in comparison with 0 joint years , consistent with a deleterious effect of heavy marijuana use on small airways. The latter observation is consistent with the recently reported finding in a New Zealand birth cohort at age 45 years of an association of lifetime cannabis use, adjusted for tobacco pack years, with pre-bronchodilator peripheral airways resistance and reactance using impulse oscillometry.

We also adjusted for the current use of each of these products/substances to address the potential confounding in all the models except for any use of the three. For example, we coadjusted for the use of e-cigarettes and marijuana in the model regressing the odds of using cigarettes. A jackknife method based on design-based replicate weights was used to estimate variances and significance values of regression coefficients. The same types of analyses were conducted separately for use of different types of products/substances. All analyses were implemented using SAS 9.4 . In 2018, 1.66 million California young adults, ages 18 to 25, were currently using at least one form of cigarette, e-cigarette, or marijuana: 314,000 smoked cigarettes, 682,000 used e-cigarettes, and 1.3 million used marijuana. There was no statistically significant change in cigarette use between 2017 and 2018 . In contrast, there was escalating use of e-cigarettes and marijuana. Between 2017 and 2018, current e-cigarette use climbed by 4.8% and current marijuana use rose by 4.6% among young adults. The proportion of young adults currently using any of these products/substance increased by 5.5% between 2017 and 2018 . Table 1 presents descriptive analyses of the current use of cigarettes, e-cigarettes, marijuana, and any use of the three by age, gender, race/ ethnicity, income , psychological distress, urban/ rural residence, and region of residence. Young adults aged 18–20 were smoking cigarettes at significantly lower rates than other young adults aged 21–25 . Underage use was substantial for e-cigarettes and marijuana. About 17% of underage young adults were current e-cigarette users. About 27% of underage young adults were current marijuana users. A wide and significant male–female difference was seen in e-cigarette use , vertical farming system with male e-cigarette use nearly doubled female e-cigarette use. Any use of cigarettes, e-cigarettes, or marijuana was also significantly higher for males than females.

Young adults who were white have higher rates of cigarette and e-cigarette use than those who were Latino. Approximately 27% of young adult Latino, whites, and Asians used marijuana. Only e-cigarette rates differed significantly by income: young adults with incomes at or below 200% FPL- used e-cigarettes at lower rates than young adults with incomes greater than 200% FPL. Young adults with psychological distress had higher rates of use of cigarettes, e-cigarettes, marijuana, or any use of the three.From 2017 to 2018, California saw an increase in e-cigarette and marijuana use among young adults, while cigarette smoking remained flat. Psychological distress was observed to be associated with cigarette, e-cigarette, marijuana use, or any use of the three. Using cigarettes, ecigarettes and marijuana were also found mutually correlated. California’s trends in cigarette and e-cigarette smoking are parallel to those observed nationwide . What stands out in our findings are several aspects. One is that the percentage of California young adults using marijuana increased to 28.5% from 2017 to 2018 while the national rate remained to be 22% for both years Another finding is that in 2018, those young adults who were using each of these products/substance also significantly increased the odds of using cigarettes, e-cigarettes, or marijuana than their counterparts. Importantly, we found that severe psychological distress was significantly associated with the use of cigarettes and marijuana. Although many tobaccos and recreational cannabis use policies restrict sales to young adults under age 21, underage use is considerable– about half of the young adults were current e-cigarette users and more than half a million or 40% of current marijuana users were underage. Our findings that cigarette smoking rates remained flat between 2017 and 2018, but e-cigarette smoking and marijuana increased could be possibly explained by the current policy changes related to the cigarette tax increase and recreational marijuana legalization in California.

The finding that the smoking rates would remain flat is expected since the CHIS 2017 data were collected after the cigarette tax increase in April 2017. Studies have found that marijuana policy could inadvertently affect cigarette and marijuana use and this spillover effect poses challenges to tobacco cessation . Similar to our findings, other studies have also shown that cannabis and e-cigarettes uses have increased among youth, and these trends will likely continue as e-cigarettes remain to gain popularity and cannabis legalization policies proliferate . Our findings that the use of tobacco is positively associated with the use of marijuana or vice versa among young adults are consistent with other studies . There are several explanations for this association. One is that tobacco and marijuana use support and reinforce the use of each other Research has shown that tobacco use is associated with initiation and dependence on other substances, such as marijuana . Longitudinal studies that examined tobacco use before marijuana use generally supported a gateway sequence and progression, in that case, people smoked tobacco first, then marijuana . Additional studies have shown a “reverse gateway effect,” that those who used marijuana were at increased risk of initiating tobacco . Another explanation for the concurrent use of cigarettes, e-cigarettes and marijuana is that tobacco and marijuana use can co-occur via the same devices for both tobacco and marijuana . Studies showed that concurrent users were more likely to use e-cigarettes and blunts to administer marijuana. Vaporizers are increasingly popular among young people. Many youths replace nicotine with marijuana in battery-powered vaporizers . Another way is through the use of “blunts,” or rolling up marijuana in a cigar or cigarillo shell. Research has shown that ’smoking’ was found to constitute a social construct within which the use of cigarettes, cigars, and blunts was somewhat interchangeable among the youth . Tobacco and marijuana, taken in combination, potentially raise the likelihood of dependence on these substances and problems associated with their use.

For example, one study of University of Florida college students who used both cigarettes and marijuana found that 65% had smoked both substances in the same hour; 31% reported they smoked tobacco to prolong and sustain the effects of marijuana, and 55% had friends who engaged in these behaviors . Our findings that psychological distress was significantly associated with smoking cigarettes or using marijuana were supported by previous studies . Studies showed that adolescents and young adults with mental health problems were at high risk for tobacco and marijuana use, compared to those without such problems . Studies also showed that affective disorders and psychological distress were more common among those who smoke than those who do not smoke and among cannabis-dependent participants . Daily cannabis use was significantly more common among persons with serious psychological distress and was increasing in this group, as well as among those without . Lower quit rates among those with serious psychological distress are one factor that could contribute to the higher prevalence of smoking in this group . A study using the 2008–2016 National Survey on Drug Use and Health showed that quit rates among individuals with past-month psychological distress were approximately half than quit rates of those without psychological distress and had not increased over the past decade . Adults with depression or psychological distress had a lower quit ratio overall,vertical farming racks but were equally or even more likely to make quit or self-regulation attempts . One study’s findings suggest an increase in psychological distress among those who smoke over time may be due to the fact that as smoking has declined, thus those with psychological distress are comprising a greater proportion of those remaining to smoke. . Given that our study is cross-sectional, the direction of the association between substance use and mental health could not be established. If substance use is an antecedent to psychological distress, our estimated effects of psychological distress on smoking cigarettes and marijuana use may be biased upward. A few longitudinal studies provide causal evidence that smoking or marijuana use increased with psychological distress. For instance, a study using longitudinal data showed that smoking uptake was associated with an increase in psychological distress . Another birth cohort study that tracks youth longitudinally from before marijuana onset also reinforced that early-onset and chronic marijuana use was associated with a greater risk of psychiatric disorders . Data from a cohort study with an 8-year follow-up in the general population in Stockholm County also showed cannabis use was associated with an increased risk of psychological distress eight years later in Sweden women .

Regardless of the causal direction, to protect the health and well-being of young adults, decision-makers need to consider both the mental health and substance use behavior implications of less restrictive substance use policies. California laws banned sales of cigarettes, e-cigarettes in 2016, and marijuana to young adults under 21 years old. Though underage young adults had lower odds of smoking cigarettes than older young adults, the underage use was substantial for e-cigarettes and marijuana.The studies did show that California law reduced illegal sales to youth under 18 . Researchers from UC Davis used data from the 2012–2019 Behavioral Risk Factor Surveillance System and observed that although the trends of ever and current smoking did not change significantly before and after California’s T21 policy, while there was an 8% annual decrease of daily smoking before the policy and a 26% annual decrease after the policy among underage in California . Our study and others showed that underage use could still be an issue due to limited knowledge of such laws and other influencing factors . A study found that the knowledge of the minimum legal age was inversely associated with the intention to use tobacco among youth. Educational campaigns to raise awareness and support for MLA among youth may improve the impact of MLA policies . The strength of this study is that it is based on CHIS data, which is the largest state health survey in the nation, and it collects extensive information for assessing the health and health behaviors of adults, adolescents, and children in California. Each year, CHIS surveys over 20,000 households. Also, from 2016 to January 2018, California implemented a series of policies, including prohibiting the sale of tobacco products and e-cigarettes to persons under 21, a cigarette tax increase, and recreational marijuana legalization. All these state-level policy changes make California a natural experimental ground for studies on tobacco and marijuana use behaviors and risk factors associated with smoking behaviors among young adults. It is worth noting that the findings in this study are subject to some limitations. First, data were self-reported, which might have resulted in recall and social desirability biases. Specifically, we were unable to examine whether decriminalization and legalization of adult marijuana use affected self-reporting bias; that is, respondents might have felt more comfortable reporting marijuana use as it became legal in California. Second, the survey does not include institutionalized populations and persons in the military in its sample, so the results might not be generalizable to those populations. Lastly, as noted, it is based on cross-sectional data, it is difficult to determine the direction of the relationships we estimated, for instance, if cigarette use caused marijuana use or vice versa. The adverse consequences of illicit drug use on users’ physical and psychological health have been examined extensively. Substance abuse has been found to be associated with reduced cognitive abilities , educational attainment , as well as undesirable labor market outcomes such as unemployment , employment mobility and lower wages . Studies that specifically focus on marijuana-use and labor market outcomes have yielded similar findings , where regular cannabis use is associated with poor school performance, higher dropout rates , and lower levels of educational attainment – an important factor that facilitates subsequent labor market outcomes including occupational status and income . Despite the growing number of studies investigating the relationship between substance abuse and labor market outcomes, however, a closer examination of the empirical evidence reveals a surprising lack of concurrence among their findings. Using data from both the 1980 and 1984 waves of the National Longitudinal Survey of Youth , Gill & Michaels , examine the effects of substance abuse on wages. After accounting for what they refer to as “self-selection” effects, the authors conclude that users of illicit drugs receive higher wages than their non-drug using counterparts.

The association between marijuana use and the prevalence of diabetes has also been examined in the National Health and Nutrition Examination Survey III population. The researchers reported that marijuana use was associated with a lower odds of diabetes after adjustment for manifold demographic, lifestyle and clinical characteristics. The study population was restricted to individuals aged 20– 59 years; excluded 25% of the potential analysis population because of missing laboratory data; and, when examining age-stratified analyses , found the association was restricted to the older age stratum. A recent meta-analysis of eight independent replications from NHANES and the National Surveys on Drug Use and Health found a summary adjusted OR of 0.7 for the association of current marijuana use and prevalent diabetes; however, both marijuana use and diabetes status were ascertained via self-report. These associations might result from the self-exclusion of unhealthy individuals who frequently use marijuana from study participation, resulting in an underestimation of diabetes cases in marijuana users, and from reverse causation where individuals with diabetes abstain from marijuana use in older age because of concerns about and awareness of their health status. Recent analysis of NHANES 2005–2010 participants found marijuana use to be associated with lower levels of fasting insulin and HOMA-IR, and a decreased WC compared with individuals who reported never using marijuana, after adjustment for relevant covariates; however, no association was found between current marijuana use and fasting glucose, HbA1c or BMI. In a small study of otherwise healthy individuals, after matching cannabis users to non-users by sex, ethnicity, age and BMI, adipocyte insulin sensitivity was found to be higher in cannabis users compared with non-users; however, skeletal muscle insulin sensitivity, insulin secretion,clone rack fasting insulin and glucose, and HbA1c were not different between the two groups. Significant differences in diet quality between the two groups were noted, and the effect of tobacco use on the results is unknown.

Previous epidemiological research has cited animal models investigating the potential mechanisms underlying the metabolic effects of marijuana. Potential anti-inflammatory effects and improved metabolism by actions through the cannabinoid receptors have been suggested to reduce the progression of type 1 diabetes, improve beta cell function and decrease weight in mouse models. However, no models have assessed this association in healthy mice, and these studies administered cannabis/cannabidiol via ingestion or intravenously. The mode of administration and the dose should be considered when extending these results to public health studies, as the most common modes of consuming cannabis among the general population are cigarettes, pipes and bongs, in which the user inhales the chemical compounds in smoke form and the quantity consumed varies from user to user. Given the potential of marijuana smoke to increase the production of reactive oxygen species and oxidative stress, any potential anti-inflammatory benefit might be countered by detrimental oxidative effects from intake by smoking. Research on the prospective evaluation of marijuana use on metabolic health is scant. It is unclear how marijuana use could place an individual at increased risk for prediabetes yet not diabetes. This is a potential study limitation, and may reflect a spurious prediabetes association. Similarly, it is possible that it is an artefact arising from our exclusion criteria disproportionately affecting those with higher levels of marijuana use and greater potential for the development of diabetes. Individuals excluded from our analysis generally had higher levels of marijuana use and less favourable levels of traditional diabetes risk factors and were, historically, more likely to develop diabetes. Alternatively, the effect of marijuana use might have a more noticeable impact on glucose metabolism in the prediabetes range compared with the diabetes range, when traditional diabetes risk factors are far less favourable and might dominate over any effect of marijuana. This might explain the differing results in the linear trend of fasting glucose level at censoring. There are plausible ways to reconcile the seemingly contradictory tendencies between this prospective analysis , animal and cellular models, and prior cross-sectional findings in which current marijuana use coincided with a lower prevalence of prediabetes and diabetes.

We speculate, for example, that some people in ill health might choose to quit marijuana as a result of a physician’s recommendation to abstain from tobacco and other substances or a general concern for their health, or because of more complicated associations between poor health, income and drug access. This speculation awaits confirmation. In addition, previous work has not accounted for the use of other illicit drugs. While illicit drug use per se might not cause a decline in metabolic health, it might be an indicator of the propensity to use drugs or overall deleterious health behaviour, or cause declines in overall health.Recreational stimulant use is a growing concern among young adults, with 4.4% and 5% to 35% of college students endorsing cocaine and recreational amphetamine  use, respectively, and 16% of cocaine experimenters developing dependence within 10 years . To develop cost-effective prevention and intervention strategies, it is crucial to identify ultra–high risk recreational users. However, little is known about bio-behavioral markers forecasting trajectory of occasional stimulant use to stimulant use disorder . Previous stimulant use research is predominantly cross-sectional, comparing individuals with chronic stimulant use with healthy individuals; although findings from these studies highlight brain disruptions related to drug use, they cannot disentangle whether disruptions preceded or were a result of chronic use. Young adulthood is a period of increased independence, often providing more opportunities for risky behavior such as drug experimentation. Risky behavior can be defined as actions that may be subjectively desirable but are potentially harmful and is typically quantified in young adults by their degree of substance use, unprotected sex, health habits, and crime engagement . Risk taking often occurs in clusters of maladaptive behaviors, suggesting underlying impairments in decision making . Decision making involves several brain processes, including learning, inhibition, and outcome assessment, specifically appraising positive or negative valence of choices . Functional magnetic resonance imaging research indicates that individuals with SUD show impaired decision making associated with altered brain activation in executive control and reward processing regions . Decision making is thought to involve a cooperative relationship between an impulsive system activated by immediate rewards and aninhibitory control system. Through learning, the control network allows individuals to resist immediate attraction to rewards in favor of longer-term advantageous outcomes .

In SUD, bio-behavioral indices of risk taking suggest an underlying imbalance between the control and impulsive systems. The control system integral to decision making comprises prefrontal cortex , theorized as responsible for learning the relationship between stimuli and outcome, working memory, and inhibiting behavior . SUD samples exhibit frontal lobe impairments associated with compromised decision making and increased risk behavior . For example, cocaine abusers exhibit dorsolateral PFC hypoactivation during response inhibition and prediction of uncertain outcomes ; in cocaine dependence, orbitofrontal cortex and DLPFC attenuation are linked to reduced ability to differentiate between variable monetary gains . Similarly, methamphetamine users inaccurately process success or failure of available options, a pattern associated with orbitofrontal cortex/DLPFC hypoactivation . Working in conjunction with frontal regions is striatum, an area associated with reward processing , selecting and initiating actions , and learning . During the Iowa Gambling Task , healthy individuals show stronger striatal activation to wins than to losses ,4×8 tray grow but amphetaminedependent individuals demonstrate hypersensitive striatal responses to rewards . Cocaine and methamphetamine users also exhibit striatal hyperactivation but frontal hypoactivation during risky decision-making tasks such as the Iowa Gambling Task and the Balloon Analogue Risk Task that is linked to riskier behavioral performance .Evidence from fMRI studies has led researchers to theorize that frontal lobe and striatum form a functional circuit with insular cortex and anterior cingulate cortex ; these regions coordinate to integrate emotional and autonomic information about rewards into goal-oriented behavior . ACC is proposed to be involved in emotion and behavior management based on its neural connections to both the emotion processing limbic system and the cognitive control center, PFC . Insula is proposed to play a role in interoceptive processing, wherein individuals integrate physiological cues to differentiate between risky and safe decisions and transform these cues into conscious feelings and behaviors . ACC and insula hypoactivation is evident in chronic stimulant users in response inhibition and error monitoring during decision making . Evidence for aberrant activity in key components of the PFC-limbic network has led researchers to suggest that weakened ability to accurately process information about options and control behaviors leads to favoring choices that offer immediate, rather than delayed, rewards . Cross-sectional studies of occasional stimulant users report decision-making impairments that parallel findings in stimulant-dependent individuals, including 1) weakened inhibitory control and reduced cognitive flexibility ; 2) neuropsychological impairments in executive functions ; and 3) frontal, striatal, and insular attenuation during a Risky Gains Task paired with reduced ability to differentiate between safe and risky decisions . Several research groups have recognized limitations of cross-sectional addiction research and have shifted toward a longitudinal approach to understand the transition to problematic substance use . Structural MRI studies show that decreased brain volume in frontocentral regions at age 14 years predicts binge drinking at age 16 and that frontostriatal regions are linked to heightened stimulant use in OSUs 1 to 2 years later . However, fMRI has been less applied to predict the development of SUD.

The current longitudinal study used follow-up clinical and drug use data from OSUs 3 years after an fMRI scan to determine whether baseline behavioral and blood oxygen level–dependent responses during the RGT 1) differentiated young adults who became problem stimulant users from those who desisted from stimulant use during the 3-year interim and 2) predicted cumulative baseline and follow-up stimulant and marijuana use across OSUs, regardless of clinical status , to address concerns regarding significant rates of marijuana and stimulant co-use . Analyses compared BOLD activity related to specific task requirements: decision contrasts compared BOLD activity during risk-taking choice trials versus safe choice trials; outcome contrasts compared BOLD activity on trials where each subject took a risk and subsequently earned a win or a loss. Categorical hypotheses were tested based on prior bio-behavioral findings in stimulant- dependent individuals: 1) PSUs would exhibit riskier task performance than DSUs; 2) PSUs would show greater striatal BOLD signals than DSUs to outcomes, particularly in response to risky wins; and 3) PSUs would exhibit lower PFC, insular, and cingulate BOLD signals during decision making. Because dimensional analyses were exploratory, no a priori hypotheses were tested.The University of California, San Diego, Human Subjects Review Board approved the study protocol. Participants were recruited through newspapers, internet ads, and fliers mailed to college students. Figure 1 demonstrates participant recruitment and categorical/dimensional data analysis protocol. A total of 1025 individuals were phone screened, and 184 OSUs meeting study criteria provided written informed consent to participate. OSU inclusionary criteria were as follows: 1) within the last 6 months, two or more separate occasions of cocaine or prescription amphetamine use without a prescribed purpose; 2) no lifetime stimulant dependence; 3) no lifetime stimulant use for medical reasons; and 4) no drug treatment interest. Participants completed three sessions: 1) a baseline diagnostic interview to determine lifetime psychiatric diagnoses and current drug use patterns , 2) a neuroimaging session completing the RGT , and 3) a follow-up interview session 3 years later to determine changes in drug use and clinical diagnoses . The current study includes data from OSUs who completed all three sessions . No OSU reported using methamphetamines at baseline;all baseline stimulant use was of cocaine and prescription stimulants.Three hypotheses were tested. First, consistent with the prediction that PSUs would exhibit riskier task performance than DSUs, PSUs more frequently made a risky decision following a win compared with DSUs, while DSUs more frequently made a safe decision following a risky win. This pattern supports previous findings that PSUs are more reactive to rewards . Second, although it was predicted that PSUs would show greater activation in reward processing striatal regions to risky wins than to risky losses when compared with DSUs, our results demonstrated the opposite effect, with PSUs exhibiting lower striatal BOLD signals across outcomes than DSUs. However, this finding is consistent with a longitudinal study of sensation-seeking adolescents in which striatal hypoactivation predicted future problematic drug use; the authors theorized that lower striatal activity may lead to a compensatory mechanism in which one seeks out increased risk to gain greater stimulation, thereby balancing reward center hypoactivation .

Colorado, Washington state, Alaska and Washington, D.C., don’t allow home delivery of marijuana. Oregon, California and Nevada do, but services are not universal Colorado, Washington state, Alaska and Washington, D.C., don’t allow home delivery of marijuana. Oregon, California and Nevada do, but services are not universal. Colorado Governor John Hickenlooper stated one of chief concerns surrounding marijuana delivery services; that “delivery service offers more opportunity for that marijuana to get into the hands of kids.” . Another key concern for delivery services is enforcement. Many are based in cities where marijuana businesses are not permitted and it is impossible to monitor how often they deliver to cities in which MMDs are banned; even though some delivery business have put protocols in place that allow them to identify areas where delivery is prohibited and refuse to deliver to those jurisdictions , they represent only a handful of the hundreds of the businesses available to choose from for marijuana delivery. For example, neither medical or recreational marijuana business are currently legal in the cities shown in the screenshot below, but dozens of marijuana delivery businesses are based there and ready to service those regions. The results presented in Chapter 6 refuted Hypothesis 1.2, and established that dispensary bans do not have a direct effect on high school students’ marijuana use when controlling for student and school characteristics known to be associated with adolescent marijuana use. This diverged from findings from the trend analysis which found that over time a more restrictive dispensary policy in Los Angeles was followed by decline in lifetime marijuana use among the City’s 9th and 11th grade students. Before concluding that dispensary bans had no relevance to adolescent marijuana use, however, I investigated if a more complex relationship was masking an association.

By investigating indirect effects,drain trays for plants I hoped to learn identify indirect mediators of a relationship between dispensary bans have an impact on adolescent marijuana use, for example if their effect is dependent on them having a significant effect on another variable that has a significant influence on student marijuana use. This kind of hypothetical relationship is called indirect mediation . Often, the researcher’s interest switches to the variable with the direct effect once it is identified, but in the case of civic policies regulating dispensaries, learning more about these dependent relationships could also elucidate the mechanisms by which restrictive city regulations on legal, adult-use products might be effective in preventing substance use among adolescents. For example, if these analyses had demonstrated that the density of dispensaries was significantly correlated with adolescent marijuana use by city, policies that strictly limit the number of dispensary bans could pursued in lieu of dispensary bans. Recent studies have demonstrated that dispensary density is positively associated with higher prevalence of use and more frequent use among adults but their influence has not been studied among youth. Prevention research supports the idea that more convenient access to substances that are legal for adults, such as tobacco or alcohol, often has the end result of creating easier access for youth . This finding implies that youth living in or attending school in a city that allows dispensaries might obtain cannabis more easily or more often from adults in their social network. Considering that adolescents report older relatives and the illicit market as their primary sources of cannabis , a dispensary ban making access less convenient for adults could have the additional effect of making it less conveniently obtained by teens. The number of dispensaries in a community makes sense as a measure of convenience of access but could also be a marker for ineffective enforcement if it is larger than the number a city allows. Dispensary bans were significantly negatively associated with lower density of dispensaries, among the cities of LA County , which supported H2.2.

This means that the average city with a dispensary ban had less dispensaries operating there the average city that allowed dispensaries. I expected the number of dispensaries in a city to be positively correlated with the prevalence of marijuana use among students but instead found that there was not a statistically significant association . This finding refuted H2.2 and ruled out the rate of dispensaries per 10,000 residents as an indirect mediator that carries the effect of dispensary bans on students’ rates of lifetime and recent marijuana use. Included as a measure of the actual exposure to dispensaries in communities, the number of dispensaries per 10,000 had surprisingly little influence on the outcomes of interest for this study. As youth are not able to access these storefront outlets directly, the presence of dispensaries in their city may have little impact on the availability of marijuana within their social circles. That the number of dispensaries in a community normalized by population had no effect on high school students’ marijuana use was in line with research indicating that adolescents generally do not get marijuana directly from dispensaries, but rather from social sources like relatives or friends. I hypothesized that a greater number of dispensaries located within a city would create more convenient access for the adults that act as a conduit of marijuana to adolescents. However, creating easy access for adults through legitimate sources like dispensaries may have also shrunk the illicit market as a source for adolescents. One possibility is that the adults and adolescents that formerly supplied marijuana through the illegal market pursued other activities after losing a large proportion of their adult customers when access to dispensaries became legal. The finding that the rate of dispensaries per 10,000 population had no effect on high school students’ marijuana lifetime or recent use or perceptions of how easy it was to get marijuana was in line with research indicating that adolescents generally do not get marijuana directly from dispensaries, but rather from social sources like relatives or friends . It’s also possible that the predictions of marijuana legalization advocates are correct; that allowing easier access to marijuana through legitimate sources like dispensaries has starved the illicit market as a source.

Although this could be a factor, local research indicates that it could not be completely responsible for the results seen here. Two recent local studies have indicated that although use of dispensaries as a source for marijuana is preferred by the adult marijuana users in LA County, most of this population continues to access marijuana from illicit sources in addition to dispensaries . For example, a September 2018 community assessment published by the LA County Department of Public Health Substance Abuse and Prevention Program titled “Marijuana Use and Public Perceptions in Los Angeles County” indicates that dispensaries are still not the most common marijuana source for adult users. Instead, 58% of the LA County marijuana users surveyed cited friends as the primary source for their marijuana ,dry rack for plants whereas only 21% of respondents reported dispensaries as their primary source. However, only approximately 6% of the respondents in the 2018 study reported a “dealer” as their primary source, i.e., the illicit market. This is less than half of the proportion of marijuana users surveyed for a qualitative study of dispensary users conducted by SAPC and UCLA in 2014, which found that although dispensary customers unanimously preferred to get marijuana from dispensaries as compared to the illicit market, 13% also continued to get marijuana from the illicit market . Even if city ordinances do not have an effect on the supply of marijuana available to youth or ultimately impact their marijuana use behaviors, could they have an effect on their perceptions of risk and on youth social norms surrounding marijuana use? Attitudes toward drugs and alcohol are known to be powerful predictors of adolescent substance use , and changing attitudes to perceive cannabis use as more acceptable and less risky have been noted among youth populations . For example, qualitative research with at-risk youth in LA County indicates that many view marijuana use as having fewer negative consequences than drinking . A community assessment conducted in LA County also found that the risks of cannabis use were rated much lower among cannabis users than among non-users, indicating a potentially important relationship between perceptions of the risk of marijuana use and the willingness to use it. The results of the perceived mediation analysis indicate that while perceived risk has a strong association with the prevalence of students’ lifetime and recent marijuana use , it is not determined by their city’s dispensary policy . Perceiving great risk from frequent marijuana perceived risk could not therefore mediate the relationship between dispensary bans and student marijuana use . Perceived risk having a strong association with student marijuana use is consistent with well-known theoretical models like the Health Belief Model but it is outside of the scope of this analysis to determine what is determining students’ perception of the risks of marijuana use other than to note that it is not the dispensary ordinance in the city where they attend school and likely live.

For Research Question 4 I tested the mediating effect of the continuous distance from the study participants’ schools to the nearest dispensary in LA County. I hypothesized that dispensary bans would be associated with a greater average distance compared to cities that allowed dispensaries. I used the distance to the nearest unlicensed dispensary as the mediating variable based on a sub-analysis finding that unlicensed dispensaries had a stronger association with student marijuana use and because there were more unlicensed dispensaries located near schools. I found that dispensary bans were indeed associated with a significantly longer average distance between schools and the nearest unlicensed dispensary , and that a greater distance was in turn associated with lower rates of lifetime and recent marijuana use among students. Including the distance between schools and the nearest dispensaries in the regression equation greatly improved the model fit and the strength of the association between dispensary bans and student use, although it fell just short of statistical significance . This result indicated that to the extent that dispensary bans are effective, their effectiveness is partially determined by being associated with unlicensed dispensaries being located further from schools. The distance between schools and the nearest unlicensed dispensary has a powerful association with students’ marijuana use as well as the relationship between dispensaries and student use, suggesting that the usefulness of dispensaries in in keeping unlicensed outlets further away from schools. It’s important to note that a dispensary ban is not required to do this, but different approaches among cities that allow dispensaries may be required A sensitivity analysis using progressively smaller distances within a mile and testing for significant associations with rates of lifetime and recent marijuana use among students found that there was a statistically significant relationship between both lifetime and recent marijuana and having the nearest dispensary located within a mile. A mile is equivalent to 5,280 feet, which is more than 8 times the minimum distance the State of California requires dispensaries to be located away from schools. Interestingly, the presence of licensed dispensaries within a mile was not associated with greater likelihood of marijuana use among the study participants, but was instead significantly associated with lesser likelihood of both lifetime and recent marijuana use. The disparate effects of licensed and unlicensed dispensaries at distances within a mile of schools merits much more detailed study. How do licensed dispensaries prevent diversion to youth so much more effectively than unlicensed dispensaries, if indeed that that is the cause of the opposite effect on youth use? Could licensed dispensaries shrink the illicit market on such a localized level? Recent premise surveys conducted by the LA County Department of Public Health indicate that ID checks were nearly universal among both unlicensed and licensed dispensaries , so it’s unlikely that youth are buying it directly from unlicensed dispensaries themselves. Perhaps less easily observable differences occur with unlicensed dispensaries circumventing other regulations intended to prevent diversion to youth and the illicit market, like quantity limits on the amount customers can buy in a single transaction. Research on dispensaries business practices and compliance with state and city regulations to date is sparse but supports this possibility. For example, recent observational research among dispensaries in LA County indicates that unlicensed outlets were more likely to have violated several regulations designed to prevent youth harm, such as displaying products designed to be attractive to youth, displaying products outside of their original child resistant packaging .

All models controlled for gender, grade, race/ethnicity, and whether the student attended a nontraditional school. I assessed the parallel trends assumption of the difference-in-difference design by graphing simple prevalence of the marijuana outcomes among Los Angeles and the control group students over the study and visually assessing whether the trends were parallel. The assumption of parallel pretreatment trends was confirmed by the notably parallel trends before Proposition D was enacted. Table 6.2 presents the results of cross tabulation frequencies of the two marijuana measures with student demographic characteristics. Most of the results were consistent with expectations based on the body of literature, such as marijuana use among males being higher than females, use among Asian students being low, and use among students attending non-traditional schools being markedly higher than among students at traditional schools. Among all students the number who reported lifetime marijuana was about one-third but varied considerably by grade, which is not unexpected given that “lifetime” is a longer period of time among eleventh grade students than among ninth grade students. Recent marijuana use was also more common among eleventh grade students, however, with 19% reporting recent use compared to 13% of ninth grade students. These frequencies are consistent with both national and state-level reports. The national Monitoring the Future Study reports that as of 2017 prevalence for lifetime use ranged between 31% for 10th grade students to 45% for 12th grade students,greenhouse racking whereas prevalence of past month use ranged from 16% for 10th grade students to 23% for 12th grade students . State-level reports using a random sample of CHKS participants from 2015-2017 surveys found that 17% of 9th grade students and 32% of 11th grade students reported lifetime marijuana use, whereas prevalence of recent use was 9% and 17%, respectively, in the 2015-2017 survey years.

Table 6.6 presents the difference-in-difference estimates from the Poisson regression comparing marijuana use over time between the City of Los Angeles and the control group cities. The difference-in-difference coefficient is an interaction term comparing the difference in change between the two groups over time and quantifies the impact of Proposition D. Presented below as a risk ratio, the value for the estimate was less than one , which indicated a lower risk of lifetime marijuana use over time and a greater decline relative to the control group cities. That the coefficient was statistically significant means the decline in students’ marijuana use in Los Angeles surpassed the declining countywide trend to such a degree that it is unlikely to have occurred by chance . This result suggests that the decline in rates of lifetime marijuana use among City of Los Angeles high school students is attributable to the stricter regulations enacted with Proposition D and supports H1.2 for lifetime marijuana use. The difference-in-difference coefficients for the covariates presented in Table 6.6 are similarly presented as risk ratios. In this case, they represent the risk of a student within a category reporting lifetime marijuana use relative to the reference group for that category and holding constant all of the other covariates in the model. For example, the risk ratio for males reporting lifetime marijuana were 1.11, or 11% higher than the risk for females reporting lifetime marijuana use. Within racial/ethnic characteristics, students within the African-American, Hispanic, and Other racial/ethnic categories had significantly higher relative risk of reporting lifetime marijuana use than the reference category, Whites. In contrast, Asian students had significantly lower relative risk compared to Whites . The relative risk of eleventh grade students reporting lifetime marijuana use significantly higher than for ninth grade students, as indicated by the 95% confidence interval not including 1. The results for non-traditional schools were in the expected direction as well, with the relative risk of lifetime marijuana among students attending these schools reporting lifetime marijuana was estimated to be almost 75% higher compared to risk of lifetime marijuana use among students attending traditional schools.

The most interesting finding among the covariates was the association between the relative risk of students reporting lifetime marijuana by time. The risk ratios for the preProposition D time periods were all greater than one, indicating that reports of lifetime marijuana use during these periods were significantly greater than baseline . In contrast, the risk ratios for the post-Proposition D time periods were all lower than one, indicating significantly less risk of students reporting lifetime marijuana use during those time periods compared to baseline. The tighter regulations enacted in Los Angeles with Proposition D were followed with lower rates of lifetime marijuana use among high school students when accounting for regional trends and covarying factors. Parallel trends were observed in Los Angeles and the control cities for both lifetime and recent marijuana use, but declines in both these measures were steeper in the City of Los Angeles following enactment of Proposition D. This result supports the hypothesis of a causal effect, although it was not large enough relative to the control group to be statistically significant for recent marijuana use. These results supported Hypothesis 1.2, that cities that enacted more restrictive dispensaries policies would see a trend of declining marijuana use among students attending school there. That a decline in student reports of marijuana use was observed among the control group was unexpected. The similar trend among the control group cities may indicate that marijuana use among high school students is driven less by whether their city allows dispensaries than by secular trends driven by the media, by state and federal laws that impact availability and legal risk for adults. This finding also justified use of the difference-in-difference design to control for background trends in the outcome variable that cannot be attributed to the policy or event of interest. By using the control cities to represent the counterfactual case for student marijuana use trends in Los Angeles had Proposition D not been enacted, I was able to isolate the effect that can be attributed to the policy change and avoid making false conclusions about its impact on students’ marijuana use behaviors. The decline in rates of lifetime and recent marijuana use among the control group cities may have been related to federal enforcement efforts that closed down over 200 dispensaries in the LA County area in 2012 ,indoor cannabis grow system but very little information is available about which dispensaries were closed down in which cities and how many dispensaries were in operation countywide before the raid. It is unknown whether the Federal raids targeted the city of LA and the control cities equally, but if they did than these raids may have played part in the declines in marijuana use that was noted among students in the control group cities as well as among Los Angeles students.

It is difficult to attribute any impacts on student marijuana use to these enforcement actions due to the limited information available but further study of these events is certainly merited. I was not able to conclude that the decline in recent marijuana use observed to occur in the post-Proposition D period was not due to chance. Recent marijuana use is a less common behavior than lifetime marijuana use, and while the effect was in the expected direction, the smaller number of students reporting this behavior produced a wider confidence interval that included a null effect. Policies take time to have a measurable effect and the City of Los Angeles has experienced significant challenges to enforcing Proposition D’s limits on the number of dispensaries. Hundreds of unlicensed storefront dispensaries continue to operate throughout Los Angeles and each one of them could be expected to weaken the impact of Proposition D. It is possible that given more time and continued investment in enforcement an effect for recent marijuana could be documented as well. An additional explanation for why an effect was not observed for recent marijuana use could be contamination, or “spillover effects”, where people living in other cities in LA County may have obtained marijuana from the many dispensaries located in the City of Los Angeles. Car culture is firmly established in Southern California and vehicle ownership is high; close to 8 million vehicles were registered in LA County last in 2017 , for a county with an estimated population in 2017 of just over 10 million . Given the geographic sprawl of Los Angeles and the many other incorporated cities and unincorporated areas it borders, it is not difficult to imagine that LA County residents who lived outside of Los Angeles obtained marijuana from dispensaries located in Los Angeles if they couldn’t get it in their own city. This could be expected to make events that impact access to marijuana in the City of Los Angeles also have an impact in the other cities. It could also be expected to weaken the impact of dispensary bans altogether, as people could obtain marijuana from other cities if it is banned in theirs.

The ability for high school youth to travel to another city to get marijuana could be less of a concern than for adults but given that youth largely obtain marijuana from adults via the illicit market or their social networks , events impacting adult access could be expected to in turn affect youth access. Additionally, even if a city is successful in enforcing dispensary bans or caps on the number of outlets like Proposition D, policies such as these that restrict access to storefront outlets may still have a limited effect on the availability of marijuana given the many other sources by which residents can obtain it, such as from delivery services or by cultivating their own. In this chapter I will present results from analyses that tested several theories for why city dispensary bans may have an indirect effect on student marijuana use . The results presented in Chapter 5 tested the focal relationship for this dissertation using a cross-sectional sample that included students from 57 cities in LA County. That analyses did not provide evidence of a direct effect between city dispensary bans and high school students’ marijuana use when controlling for student and school characteristics known to be associated with adolescent marijuana use. In contrast, the trend analysis presented in Chapter 6 showed that in the City of Los Angeles enacting and implementing a policy intended to reduce the number of dispensaries and place additional controls on their operation was followed by a decline in lifetime marijuana use among students attending the city’s public high schools. Furthermore, city dispensaries were negatively associated with student marijuana, despite the associations falling short of statistical significance. In this chapter, I therefore conducted a series of mediation analyses to elaborate on the relationship between city dispensary bans and student marijuana use and whether their effect was dependent on some factor I had not accounted for. In this chapter I investigate indirect effects; circumstances where the effect of a variable is dependent on another variable. Identifying dependent relationships is important to elucidate some of the mechanisms by which restrictive city regulations on legal, adult-use products might be effective in preventing substance use among adolescents. The analyses that follow in this chapter tested indirect mechanisms through which I theorized city dispensary policies may influence students’ marijuana behaviors, such as by preventing excessive density of dispensaries in a city, signaling to youth that marijuana use represents a health risk, and/or by preventing dispensaries from operating near their high schools. These analyses will test the hypotheses for Research Questions 2-5. As described in the methods chapter , I used a variation of Baron and Kenney’s Product Method, which described in detail in Zhou et al., 2010, to test for mediation. Baron and Kenney’s Product Method first tests for direct relationship between the independent and dependent variable as a condition of testing for mediation , but this approach has been criticized as a relationship between the independent and dependent variables can be masked by a mediating variable or competing mediators . In the case of this research, the focal relationship is the influence of dispensary bans on student marijuana use and I will investigate the effect of several different mediators on this relationship.

The city population estimates included in the city boundary shapefiles are calculated by applying mortality and migration rates to the 2010 Census count and controlling for age, race-ethnicity, and gender proportions from the Census Bureau’s LA county population estimates for the previous year. These city boundary shapefiles are available for download and public use at the County of Los Angeles GIS Portal . To quantify the impact of multiple dispensaries being located near a school, I first calculated the association between the continuous distance between the school and the nearest dispensary in within a mile and within LA County. I wanted to know at which point a dispensary was located close enough to a school to have an influence on student marijuana use, so I also conducted sensitivity tests of distance within a mile using increments of a quarter mile. These distances are much further away from schools than the state requirement of 500 feet or and the maximum distance dispensaries are required to be located away from schools by a city ordinance in LA County, which is 1,000 feet. I then constructed a series of “buffers” using ArcMap 10.4 GIS Software and recorded counts of how many dispensaries were located within each buffer. A buffer is created by specifying the length and unit of measurement for the radius around a point of interest, such as LA County public high schools. A series of 3 buffers were created for this analysis. The first buffer was 500 feet in radius; the minimum distance a city in LA County allowed dispensaries to be located near schools in 2016,cannabis drying when the city policy data was collected. I suspected that dispensaries could have an impact at greater distances from schools than at 500 feet so I tested the impact of dispensaries being located with 1,000 feet and 2,000 feet. The dispensary count within 500, 1,000, and 2,000 feet of each school were imported into SAS and matched with the data for each school that participated in the CHKS survey by CDS code.

This allowed for information about student marijuana use to be associated with the number of dispensaries within a specific radius of each school. These buffer counts were then used as independent variables in the multilevel logistic regression analyses to determine the impact of the number of dispensaries near the schools on students’ marijuana use behavior. Student characteristics assessed include gender, ethnicity , race, grade , highest level of parent education, whether the student qualified for free or reduced-price meals, and whether the student attended their school’s after school program at least one day a week. Male gender is sometimes associated with greater likelihood of and higher rates of marijuana use , whereas female gender has been associated with lower rates of use overall, but with younger ages of initiation and faster transition to regular use . Some studies have found that rates of marijuana use among people of Latino ethnicity are higher relative to other racial/ethnic groups in early adolescence but are often overtaken by rates of use by white people in later adolescence .Therefore, the analyses presented in this dissertation use the students’ grade in school as a measure of student’s age. Older age is almost universally correlated with greater substance use among adolescents , so age is an important factor to account for in any analysis of the risk of substance use among high school age youth. The analyses presented in this dissertation are based on students in the 9th and 11th grade, per CHKS study protocol. Higher grade is logically a powerful predictor of lifetime marijuana use due to it being determined by greater age, but has also been shown to be associated with a greater likelihood of recent marijuana use , which is not necessarily dependent on greater age. Participation in after-school programs was included as a covariate because it has been shown to be a protective factor against adolescent substance use in general .

The count of days each student participated in after school programs was only used in the cross-sectional analyses, as it was not available for all of the school years between the 2005/2006 and 2016/2017 school years. Eligibility for school meals and highest parent education were included as a measure of social economic status because some studies have found higher SES to be associated with greater rates of marijuana use . Self-report of receiving free and reduced-price school meals was included as the only available proxy for low family income, based on California State eligibility criteria, e.g., annual income $ 32,630 for a family of four ,” n.d.). The school meals variable was ultimately found to have a high rate of “don’t know” responses , which were grouped with “no” responses using the logic that the student would likely be receiving free-reduced price meals if they were eligible and therefore would be aware of their eligibility. This variable was only used in the cross-sectional analyses, as it was not available for all of the school years between the 2005/2006 and 2016/2017 school years. After-school program participation was operationalized using a variable in CHKS that asked “How many days a week do you usually go to your school’s after school program?” and had ordinal response categories ranging from 0 – 5 days per school week. The ordinal form of this variable was used as a covariate to account for how many days a week the student spent time at an after-school program in the regression analysis. This variable was only used in the cross-sectional analyses, as it was not available for all of the school years between the 2005/2006 and 2016/2017 school years.An indicator variable for non-traditional schools was available in the CHKS dataset and a matched more detailed descriptions of school type from the CA Department of Education School Directory. The non-traditional school indicator variable was included in all of the cross-sectional analyses to account for the expectation that students attending non-traditional schools may be more likely to likely to use marijuana. This variable was included in the trend analysis as it was available for all of the school years between the 2005/2006 and 2016/2017 school years.

The number of dispensaries within 500 feet, 1,000 feet, and 2400 was initially used to measure the density of dispensaries near the students’ schools. I defined “near” as 2,000 feet, which was quadruple the distance of 500 feet that the State of California currently requires marijuana businesses to be located from schools . The 600-foot distance from schools set by the State may be rather arbitrary, however, as no existing research has established the distance threshold at which dispensaries no longer influence students’ marijuana use. Some the LA County cities that allowed dispensaries specified that they be located greater distances from schools, such as 1,000 feet,grow trays but it is similarly unknown whether these requirements place dispensaries sufficiently far enough away from schools to prevent them from having an impact on rates of lifetime and recent marijuana use among high school students. My preliminary analyses for the trend analysis indicated that I needed to revise the first hypothesis for Research Question 1 . While testing the parallel trends assumption for the difference in difference analysis, I compared frequencies by time for both lifetime and recent marijuana use by whether the city the school was located in allowed dispensaries. Figures 4.1 and 4.2 indicate that the intervention and control groups exhibited remarkably similar trends, where lifetime and recent marijuana use increased in both groups from baseline through the 2011-2013 combined school years and was followed by a decline that was maintained through the 2015-2017 school years. The evidence of similar trends between the intervention and control groups satisfied a key assumption of difference-in-difference analyses that trends in the outcomes under study were parallel between the intervention and control groups before an event of interest has occurred. However, the similar and non-linear nature of the trends in each group indicated a need to investigate if any events had occurred in LA County that could have influenced cities that allowed dispensaries and cities that did not in similar ways. After learning more about Proposition D and the impact it had on the medical marijuana market in the City of Los Angeles it was clear that Proposition D represented a significant event that affected the intervention group and not the control group. I felt that making any conclusions about trends in marijuana use differing between cities that allowed dispensaries and those that didn’t within LA County without accounting for the impact of Proposition D on Los Angeles students would be invalid. It was less clear whether the federal raids that occurred in 2011 and 2012 affected one of the study groups more than the other, but if it did affect both groups equally, the difference-indifference study design would account for any impact the federal raids had on the marijuana use behaviors of Los Angeles students. I therefore chose to address Research Question 1 by analyzing the impact of enacting stricter regulations on dispensaries students’ marijuana use within the City of Los Angeles, using the cities that had never allowed dispensaries as a control group. Research Question 1 was therefore revised to ask “Do city restrictions on dispensaries have an influence on trends in adolescent marijuana use time?” The revised hypothesis for this question was that cities that enacted more restrictive MMDS policies would see a trend of declining marijuana use among students attending school there . To focus on the impact of Proposition D on trends in student marijuana use in the City of Los Angeles, I excluded the 2005/2007 combined school years and used 2007/2009 as the baseline time period. The 2007/2009 time period was two time periods before Proposition D was enacted and the 2015-2017 time period concluded one time period after the enactment of Proposition D. The analysis plan for Research Question 1 was changed to focus on the impact of Proposition D within the City of Los Angeles compared to cities that did not allow dispensaries . The control group for this analysis includes the 436,834 students that attended school in the 70 LA County cities that had dispensaries bans in place throughout the study period. The cities excluded were cities that had changed dispensary policies between the 2005/2006 school year and the 2016/2017 school year, which excluded cases from the cities of Diamond Bar , Huntington Park , Long Beach , Malibu , Santa Monica , South El Monte , and West Hollywood , and students from schools that could not be matched to CA Dept of Education addresses . City of Los Angeles students were chosen as the intervention group because Los Angeles and the City of West Hollywood were the only cities in LA County that allowed storefront dispensaries to operate within their borders for the entire 12-year study period. West Hollywood schools, however, did not participate in the CHKS survey during the study period and therefore could not be included in an intervention group of cities that allowed dispensaries throughout the study period. Using students who attended school in the City of Los Angeles as the intervention group was preferable for the difference-in-difference analysis of marijuana use trends because data was available for City of Los Angeles schools for every year of the study period and the population of students within this large and diverse city mirrored the population of the County as a whole for most racial/ethnic categories. Exceptions were that City of Los Angeles students were more likely to be Hispanic and less likely to be Asian or White than the control cities . The association between policy changes and subsequent outcomes is often evaluated by pre-post assessments, where outcomes after implementation of the policy are compared with conditions and outcomes from before. This design is valid only if there are no underlying time dependent trends in outcomes unrelated to the policy change . If, for example, outcomes were already improving before the policy was enacted, using a pre-post study would lead to the erroneous conclusion that the policy was associated with better outcomes. The difference-in-difference study design addresses this problem by using a comparison group that is experiencing the same trends but is not exposed to the policy change .

The Department of Public Health licenses and oversees manufacturing and testing or marijuana products, and the State Board of Equalization collects taxes from marijuana businesses. Staffing and development in the state agencies that will carry out these aims is incomplete and ongoing to date. Approaches to limiting youth exposure to marijuana products have changed dramatically as marijuana has become a legal product offered in retail settings. With the expansion of medical marijuana into the retail domain, preventing youth access to marijuana took on a new dimension, where in addition to preventing access to marijuana through illicit markets and social networks it became necessary to prevent youth from accessing it from storefronts located in communities.Explicit regulations on business practices can be applied to legal retail environments while law enforcement agencies are often the only agencies with the authority to deal with illicit markets. Within legal markets, however, prevention advocates face new and different challenges and that may require different approaches. Policy-based prevention approaches have proven to be effective at reducing adolescent substance use, despite targeting the general population and have been particularly useful to address legal substances available in retail settings . With the movement of marijuana into the legal market, regulatory controls on business practices have become necessary tools for prevention of adolescent marijuana use. Practices currently required by California law to restrict youth access include requiring employee assistance to handle products, keeping all products in their original child-resistant packaging,cannabis cultivation technology checking ID electronically or manually, and prohibiting products designed to be attractive to youth . Other recommended approaches to prevent youth marijuana use include requiring increased retailer liability and enacting stiff penalties for providing marijuana to youth .

City policies intended to prevent underage marijuana use include limiting the density of marijuana outlets in a community, preventing them from being located near sensitive areas such as schools and parks, limiting billboard advertising, and limiting the extent of exterior signage on dispensaries. Key informant interviews with LA County residents recently conducted by the LA County Dept. of Public Health indicate that keeping dispensaries a safe distance from schools and residential areas and limiting the density of outlets in the city were the top concerns stated by residents, followed by concerns about the effects of allowing dispensaries on social acceptability, particularly among youth . Perhaps intimidated by the challenge of regulating dispensaries, 75 of the 88 cities in LA County have passed local ordinances prohibiting dispensaries from locating within city limits . In Los Angeles County, the ten cities that have passed ordinances that allow and regulate dispensaries have set forth detailed rules for how dispensaries can operate. Conditions that these cities have specified to minimize the impact of dispensaries on public health include requiring them to be located a minimum distance from schools, parks, libraries and other places frequented by youth, limiting the hours of operation, and controlling their density and location . However, research indicates that preventing unlicensed dispensaries and restricting them from sensitive areas has been a problem in cities that allow dispensaries as well as in cities that ban them . Enforcement of city regulations intended to prevent adolescent substance use is an important determinant of their effectiveness in preventing substance use behaviors . A key concern for this study is the degree to which adolescents are exposed to dispensaries in the city where they attend school and likely live. Exposure to dispensaries is therefore a factor that depends not only on the city ordinances regulating dispensaries but on how effectively those ordinances are enforced.

It not yet known whether banning outlets altogether or allowing and regulating them is more effective at keeping outlets a safe distance from schools and other sensitive areas, as unlicensed dispensaries have been found in sensitive areas in cities that ban dispensaries as well as in cities that allow them. Cities that allow dispensaries are faced with enforcing limits on density and keeping outlets a defined distance away from sensitive areas such as parks and schools and some cities are more successful than others in accomplishing this. For example, unlicensed marijuana outlets were found to greatly outnumber licensed outlets within the City of Los Angeles . Among cities that have banned dispensaries the enforcement challenge has been to shut down unlicensed outlets and prevent new ones from opening in a different area of the city. This has been a problem in the unincorporated areas of LA County as well. For example, the LA County Office of Marijuana Management recently reported that it had identified 75 unlicensed outlets operating in the unincorporated areas of LA County in 2017. Seven months later, 29 of those shops had been shut down, but 31 new ones had opened in their place . Differentiating between licensed and unlicensed medical marijuana dispensaries is important because each type of dispensary may comply with regulations intended to prevent marijuana related harm and youth use to different degrees. By already existing in defiance of local law by operating in a location where they are not permitted, unlicensed dispensaries may have little incentive to comply with medical marijuana regulations. Recent observational research on compliance with regulations among dispensaries in LA County indicates that unlicensed outlets were more likely to have violated several practices designed to restrict youth access, such as displaying products designed to be attractive to youth, displaying products outside of their original child resistant packaging, or allowing onsite consumption .

The same premise survey also found that unlicensed dispensaries are more likely to be found located near sensitive areas where dispensary regulations prohibit them than licensed dispensaries . Although a robust body of literature supports the efficacy of city ordinances in preventing alcohol and tobacco use among adolescents , there exists a gap in empirical literature evaluating the effectiveness of these approaches in preventing marijuana use among adolescents . While a handful of studies have examined the impacts of the local marijuana policy environment on adult marijuana use the ability to quantify the impacts of city dispensary policies on youth marijuana use and outcomes has thus far been severely hampered by a lack of available data on youth marijuana use at the local level. Population-based national surveys like the Youth Risk Behavior Survey, the National Survey on Drug Use and Health, and state-level surveys like the California Health Interview Survey do not sample with enough density to allow for comparison of teen marijuana use between the cities within Los Angeles County . Even the Los Angeles County Health Survey, a population-based survey of health behaviors among adults and children in LA County, does not sample enough youth under 18 to provide estimates of adolescent marijuana use for geographic units smaller than the County’s health districts,indoor grow cannabis most of which span several cities . It is important to know whether the hundreds of ordinances that have been enacted to ban dispensaries in local jurisdictions across California have any impact on young people or whether the many other ways people can obtain marijuana render them primarily symbolic. Even if city ordinances do not influence the supply of marijuana available to youth or ultimately impact their marijuana use behaviors, what effect do they have on their perceptions of risk and on youth social norms surrounding marijuana use? The primary aims of this dissertation will be to answer these research questions, i.e., to learn whether local policies governing dispensaries are linked to rates of use as well as risk perceptions among Los Angeles County adolescents. Effective prevention of adolescent substance use requires an understanding of the complex etiology behind this very common behavior. Explanatory theories of adolescent substance use must elucidate relationships within the wide variety of factors that have been shown to influence substance use behavior while accounting for the unique context of adolescence. Consequently, comprehensive theoretical models that incorporate factors from multiple domains of influence have gained prominence as the field of substance abuse prevention has developed . Key themes in the etiology of adolescent substance use are that there are both distal and proximal influences at work and that a young person’s developmental stage interacts with almost every other influence . This chapter will give more emphasis to theories that apply to community and societal-level domains of influence on adolescent substance use behaviors. These theories directly address important constructs for this study, such as how and why young people’s substance use attitudes and behaviors are responsive to community contexts.

Developmental theories encompassing a wide range of biological, psychological, and experiential factors are prominent among individual-level theories and provide an explanatory framework for the most proximal influences on adolescent substance use behavior . However, even developmental theorists are increasingly looking to community contexts to explain inconsistencies and conditional relationships that have been identified in individual and relationship influences, such as the ways neighborhood effects mediate peer and family relationships . Simultaneously, an increased interest in the social determinants of health has led to more examination of how cultural and economic community characteristics and local policy may act on adolescent substance abuse . Individual-level factors represent the most proximal motivations for substance use and therefore tend to be important predictors of substance use behaviors. Generally, life experiences and psychological factors that present challenges to mental and emotional health also present risk factors for substance use and SUD . Decades of research have found that sub-groups of adolescents who experience social isolation, abuse, trauma, and mood disorders are at very high risk for SUDs and resulting health harms . The most vulnerable adolescent populations include youth who are in the child welfare system , drop out of high school , are involved with the criminal justice system , or have a minority sexual identity . Peer-reviewed empirical research of the influence of parental marijuana use on individual-level risk factors for adolescent substance use is still relatively sparse to date. Freisthler and colleagues found that parents who reported that they were current marijuana users were more likely to be physically abusive and used corporal punishment more frequently, but current marijuana use was associated with neither supervisory neglect or physical neglect. This led the authors to theorize that marijuana might be used by highly impulsive and agitated parents to relax but that their marijuana use did not appear to impair parents’ ability to care for their children’s basic needs. Intra-personal correlates of adolescent marijuana use include social and friend networks, the quality of family interactions, and the influence of school peers . Social networks are important influences on adolescents’ behavior and often mediate more distal influences like community and societal-level factors . Peer and family values, attitudes, and beliefs about substance use help shape adolescents’ values, attitudes, and beliefs about acceptable levels substance use . More accepting attitudes toward substance use among adults are correlated with a greater likelihood of substance use among adolescents and several studies have replicated these findings for marijuana use specifically . For example, in the state of Montana, Friese and Grube found that adolescents who lived in counties with a higher percentage of adult voters reporting approval for legalization of medical cannabis were more likely to have used cannabis with the last 30 days, whereas the number of medical cannabis cards that had been issued by county was not associated with higher rates of recent or lifetime cannabis use among the adolescent residents. This finding suggests that adults’ favorable attitudes toward cannabis drove the association between state policy and adolescent marijuana use rather than an increase in the availability of cannabis in the community. A marijuana-using parent could present a predisposing factor for an adolescent to use marijuana from the standpoint that they are communicating social norms accepting of marijuana use and may possibly contribute to adolescents’ perceptions that marijuana use represents little risk for health harms. To date, very little research has been dedicated to examining the relationship of parental marijuana use with adolescent marijuana use. However, a national survey of young adults ages 18 to 25 found that children of parents who smoke marijuana were more than three times more likely to use it themselves. Among young adults whose parents had used marijuana, 72% had used it, while only 20% of those whose parents had never used marijuana reported having used it themselves .

The results of this study, which have been confirmed in several subsequent reports , demarcate the pharmacological profile of AM404 from those of direct-acting cannabinoid drugs. This distinction may result from the ability of AM404 to enhance anandamide signaling in an activity-dependent manner, causing anandamide to accumulate in discrete regions of the brain and only when appropriate stimuli initiate its release. Pharmacological activation of D2 receptors may represent one such stimulus, suggesting that blockade of anandamide transport might offer an innovative strategy to correct abnormalities associated with dysfunction in dopaminergic transmission. Initial tests of this hypothesis have shown that systemic administration of AM404 normalizes movement in spontaneously hypertensive rats , an inbred line in which hyperactivity and attention deficits have been linked to a defective regulation of mesocorticolimbic dopamine pathways .FAAH was first identified as an amide hydrolase activity present in rat liver tissue, which catalyzes the hydrolysis of the fatty-acid ethanolamides palmitoylethanolamide and oleoylethanolamide . That anandamide serves as a substrate for this activity was first suggested on the basis of biochemical evidence and later demonstrated by molecular cloning, heterologous expression and generation of FAAHnull mice by homologous recombination . FAAH belongs to a group of enzymes known as ‘amidase signature family’ and catalyzes the hydrolysis not only of anandamide and other fatty-acid ethanolamides,vertical cannabis but also of primary amides such as oleamide and even of fatty-acid esters such as 2-AG . Elegant site-directed mutagenesis and X-ray diffraction studies have demonstrated that this unusually broad substrate preference is due to a novel catalytic mechanism involving the amino-acid residue lysine 142. This residue may act as a general acid catalyst, favoring the protonation and consequent detachment of reaction products from the enzyme’s active site .

Three serine residues that are conserved in all amidase signature enzymes also may be essential for enzymatic activity: serine 241 may serve as the enzyme’s catalytic nucleophile, while serine 217 and 218 may modulate catalysis through an as-yet-unidentified mechanism . Electron microscopy experiments in the rat and mouse brain have shown that FAAH is predominantly, if not exclusively localized to intracellular membrane compartments, particularly to the endoplasmic reticulum and the mitochondria . Although FAAH appears to be the predominant route of anandamide hydrolysis in the brain, other enzymes are likely to participate in the breakdown of this endocannabinoid in peripheral tissues. An acid amide hydrolase activity catalytically distinct from FAAH has been characterized in human megakaryoblastic cells and shown to be highly expressed in the rat thymus, lungs and intestine .The search for small-molecule inhibitors of intracellular FAAH activity has led to the emergence of several potent and selective agents, which include substituted sulfonyl fluorides , alpha-keto-oxazolopyridines an d carbamic acid esters . The latter were identified during structure– activity relationship studies aimed at determining whether esters of carbamic acid such as the insecticide carbaryl inhibit FAAH activity. It was found that, although carbaryl is ineffective in this regard, variations in its template result in significant inhibitory potencies. Further structural optimizations yielded a group of highly potent inhibitors, a representative example of which is provided by the compound URB597 . Kinetic and dialysis experiments indicate that URB597 interacts non-competitively with FAAH, which is suggestive of anirreversible or slowly reversible association with the enzyme. Importantly, URB597 has no notable effect on CB1 or CB2 binding, anandamide transport, or rat brain monoglyceride lipase , a cytosolic serine hydrolase that catalyzes the hydrolysis of the second endocannabinoid, 2-arachidonoylglycerol  . Following administration to rats in vivo, URB597 produces profound, dose-dependent inhibition of brain FAAH activity.

After injection of a maximal dose of compound , FAAH inhibition is rapid , persistent and associated with a 3-fold increase in brain anandamide levels. Furthermore, the inhibitor intensifies and prolongs the effects produced by exogenous anandamide, yet it elicits no overt cannabinoid-like actions when administered alone; for example, it does not cause hypothermia, hot-plate analgesia, or hyperphagia .Although URB597 does not display a typical cannabinoid profile in live animals, it exerts several pharmacological effects that might be therapeutically relevant. One such effect, the ability to reduce anxiety-like behaviors in rats, was demonstrated in two distinct experimental models: the elevated ‘zero maze’ test, and the isolation-induced ultrasonic emission test . The ‘zero maze’ consists of an elevated annular platform with two open and two closed quadrants and is based on the conflict between an animal’s instinct to explore its environment and its fear of open spaces where it may be attacked by predators . Benzodiazepines and other clinically used anxiolytic drugs increase the proportion of time spent in, and the number of entries made into, the open compartments. In a similar fashion, URB597 elicits anxiolytic-like responses at a dose that corresponds to those required to inhibit brain FAAH activity. Moreover, these effects are prevented by the CB1-selective antagonist rimonabant. Analogous results were obtained in the ultrasonic vocalizationemission test, which measures the number of stress-induced vocalizations emitted by rat pups removed from their nest . If con- firmed in further behavioral models, these findings would suggest that inhibition of intracellular FAAH activity might offer an innovative target for the treatment of anxiety , which is also a feature of marijuana withdrawal .2-AG was identified as a second endocannabinoid substance in 1995 . The multiple roles of this lipid compound incell metabolism and its high levels inbraintissue— about 200-fold higher than those of anandamide—suggest that much of cellular 2-AG may be involved in housekeeping functions. The diversity of roles played by this compound also complicates our efforts to establish biochemical route involved in its physiological formation. Nevertheless, one pathway has emerged as the most likely candidate .

This pathway starts with the phospholipase-mediated generation of 1, 2- diacylglycerol . This serves as a substrate for two enzymes: DAG kinase, which catalyzes DAG phosphorylationto phosphatidic acid; and DAG lipase , which hydrolyzes DAG to monoacylglycerol . Pharmacological inhibition of phospholipase C and DGL prevent the Ca2+-dependent accumulation of 2-AG in rat cortical neurons, which suggests a key role of this pathway in2-AG generation . However, additional routes of 2-AG synthesis also may exist, including phospholipase A1 ,cannabis drying racks hormone-sensitive lipase or a lipid phosphatase . In neurons and glia, 2-AG synthesis may be initiated by a rise incytosolic Ca2+ levels. For example, incultures of rat cortical neurons, the Ca2+ ionophore ionomycin and the glutamate receptor agonist N-methyld-aspartate stimulate 2-AG productionina Ca2+-dependent manner . Similarly, infreshly dissected hippocampal slices, electrical stimulation of the Schaffer collaterals, a glutamatergic fiber tract that connects neurons in the CA3 and CA1 fields, causes a Ca2+-dependent increase in 2-AG content . This stimulation has no effect on the levels of non-cannabinoid monoacylglycerols, such as 1-palmitoylglycerol, which indicates that 2-AG formation may not be attributed to a broad, non-specific increase in lipid turnover. Furthermore, electrical stimulationof the Scheffer collaterals does not modify hippocampal anandamide levels, suggesting that the biochemical pathways leading to the production of 2-AG and anandamide may be independently controlled . In further support of this idea, activation of D2 receptors, a potent stimulus for anandamide formation in the rat striatum, has no effect on striatal 2-AG levels .Neuronal and glial cells internalize 2-AG through a mechanism apparently similar to that implicated in anandamide transport. Thus, human astrocytoma and other tumor cells accumulate [3 H]anandamide and [ 3 H]2-AG with similar kinetic properties and this process is blocked by the anandamide transport inhibitor AM404 . In addition, anandamide and 2-AG prevent each other’s transport . Nevertheless, there also appear to be differences between anandamide and 2-AG accumulation. For example, [3 H]2-AG internalization in astrocytoma cells is reduced by exogenous arachidonic acid, whereas [3 H]anandamide internalization is not. This discrepancy may be explained in two ways: arachidonic acid may directly interfere with a 2- AG carrier distinct from anandamide’s; or the fatty acid may indirectly prevent the facilitated diffusion of 2-AG by inhibiting its enzymatic conversion to arachidonic acid. If the latter explanation is correct, agents that interfere with the arachidonic acid esterification into phospholipids, such as triacsinC , should decrease [ 3 H]2-AG uptake. This was found indeed to be the case, at least inastrocytoma cells . Thus, while anandamide and 2-AG may be internalized through similar transport mechanisms, they appear to differ in how their intracellular breakdown can affect the rate of transport into cells.After removal from the external medium, 2-AG is hydrolyzed to arachidonic acid and glycerol.

In cellfree preparations, FAAH cleaves anandamide and 2- AG at similar rates, which has led to suggest that this enzyme may contribute to the elimination of both compounds. This appears to be unlikely, however, for three reasons. First, pig brain tissue contains two distinct 2- AG-hydrolase activities, both of which are chromatographically different from FAAH . Second, inhibition of FAAH activity in intact neurons and astrocytoma cells prevents the hydrolysis of anandamide, but has no effect on 2-AG degradation . Finally, 2-AG hydrolysis is entirely preserved in FAAH-null mice . These findings suggest that, although 2-AG can be hydrolyzed by FAAH in vitro, different enzyme may be responsible for its degradation in vivo. A possible candidate for this role is MGL, a cytosolic serine hydrolase that cleaves 2- and 1-monoglycerides into fatty acid and glycerol .MGL is abundantly expressed in discrete areas of the rat brain—including the hippocampus, cortex, and cerebellum—where CB1 receptors are also found. Moreover, adenovirus-induced over expression of MGL enhances the hydrolysis of endogenously produced 2-AG in primary cultures of rat brain neurons . Finally, recent experiments indicate that silencing the MGL gene through RNA interference markedly impairs 2-AG degradation in intact HeLa cells . Although these results strongly support a role of MGL in2-AG hydrolysis, the development of additional experimental tools will be needed to demonstrate such a role unambiguously.Currently, in the United States, there are more annual deaths and disabilities from substance abuse than from any other preventable health condition . A robust body of literature suggests that prevention interventions that delay and minimize marijuana and other substance use during childhood and adolescence could have a considerable impact on morbidity and mortality in addition to reducing associated social and economic costs . Adolescent substance use is also a problem that is ideal for intervention within a public health framework, as it is both widespread and amenable to population-level approaches designed to reduce youth exposure to harmful influences. While various community-level prevention approaches have been implemented to protect underage youth from exposure to factors that encourage them to use alcohol and drugs at an age when substance use can seriously disrupt their social, physiological, and emotional development , an issue addressed in this dissertation is whether policies that restrict access to marijuana by adolescents enacted at the local level have any measurable impact. One important question is whether restrictions on marijuana have any impact on youth use in the context of high vehicle ownership, marijuana delivery services, and contrasting marijuana regulations between neighboring cities. The research literature shows that local regulations on legal substances can have a significant, if not always dramatic, effect . Given the large numbers of people impacted, if city policies cause even an incremental reduction in substance use it can have a qualitatively larger impact on a community than more intensive interventions carried out with less people . Throughout the United States , marijuana policy has been changing rapidly and following a consistent national trend of less restrictive state laws controlling access to marijuana . In an enduring legal paradox, the marijuana plant and its products remain illegal under U.S. Federal law, but the Federal government has also allowed regulations on marijuana to be determined by each state independently and these laws now contrast with Federal marijuana law in the majority of U.S. states. California’s marijuana laws are among the most permissive in the U.S., allowing for home delivery of psychoactive marijuana products, storefront medical and recreational marijuana outlets, and no limits on the THC potency of products sold . An important feature of California’s state marijuana laws, however, is that they do not preempt local regulations, meaning that local jurisdictions like cities and counties have the prerogative to enact local ordinances that further restrict access to marijuana within their borders.

After meeting some of the young men that had been sent to prison and another friend who was arrested for possession of ecstasy, I became increasingly enraged that my otherwise law abiding friends had served prison time for using psychedelic drugs to explore their own consciousnesses. When I attended several Grateful Dead shows in the spring of 1995, I witnessed the DEA’s efforts to arrest people for LSD and read about sting operations in Rolling Stone and the local papers in the cities where the Grateful Dead was playing. The highly criminal status of cannabis, ecstasy, and LSD was a puzzle to me, one that continues to motivate my efforts to understand drug policy and how it changes. As a graduate student in Criminology and Criminal Justice, I joined the Florida State University chapter of NORML. As a member of this active chapter of NORML, I became familiar with the variety of tactics and approaches that drug policy reform organizations use. One area of concern for our chapter was a 1998 law that denied financial aid benefits to college students who had been convicted of drug offenses. One founding member of FSU NORML, Chris Mulligan, went on to found an organization called the Coalition for Higher Education Act Reform that focused exclusively on changing this law. The chapter was very active and had success with outreach. After forming the first NORML chapter at a public university in the state, it helped to found NORML chapters at many other public colleges in the state, including the University of Central Florida, Florida Atlantic University, and the University of South Florida. Additionally, the Florida State University chapter served as the launching platform for the non-college affiliated chapter, Florida NORML. In 2002, our chapter attempted to pass a city level initiative that would make marijuana law the lowest law enforcement priority in Tallahassee. Similar initiatives have been passed in several other cities across the country. Most notably, Ann Arbor, Michigan was the first city to pass such a measure in 1973. The city of Berkeley, California passed similar measures in 1972 and 1978. Although numerous states passed decriminalization bills in the 1970s,vertical grow shelf city level initiatives were largely abandoned until the late 1990s, and not used in earnest until the early years of the 2000s.

Trying to get such a measure on the ballot in Tallahassee, Florida, however, was an entirely different prospect. Unlike California and Michigan, Florida has been one of the least progressive states with regard to drug policy. Although our group gathered the requisite signatures to get the initiative on the ballot, and worked with an attorney to insure that the initiative would not violate the city’s constitution, the hostile city attorney single-handedly quashed the measure, on the grounds that it violated the city constitution. Our chapter also gathered signatures for a ballot measure that would have made marijuana the lowest law enforcement priority for the city of Tallahassee. Although we obtained the proper number of signatures, the City Attorney quashed the ballot measure on a legal technicality. This was my first experience of the state acting to shut down a legally available avenue to drug policy reform. Despite this setback, our chapter would persevere and have success on other fronts. We organized two campus “hemp rallies” that featured numerous speakers in the marijuana law reform movement, tables staffed by representatives from various organizations, and musicians. One symbolically significant action occurred at a community, “town hall” style meeting, entitled “United We Stand Against Drugs.” The meeting’s organizers presented at as a panel discussion and community forum. Additionally, it was a recruitment event for the Drug Enforcement Agency and local law enforcement agencies. While it was promoted as a community forum with a panel of experts, it was essentially a well-orchestrated public relations event for law enforcement and the continuation of a prohibitionist approach to drug policy. I became aware of the event after reading a placard touting the event as a D.E.A. recruitment event in the lobby of the School of Criminology and Criminal Justice. I notified several NORML members and about ten of us were able to attend. We dressed well for the event and planned to blend into the crowd, be dutifully polite, and then ask incisive questions that would undermine the positions that were put forth by the panel and its emcees. The event featured both a structured panel discussion with an attendee question and answer session, tables staffed by D.E.A. recruiters, and refreshments.

Two local T.V. personalities served as the event’s emcees. The panel was a veritable who’s who of Florida’s drug warriors with two treatment workers thrown in to give the appearance that the fight against drugs wasn’t exclusively law enforcement’s battle. The panel consisted of then-DEA head Asa Hutchinson, Florida’s state drug czar , the Tallahassee Chief of Police, the Leon County Sheriff, and the FSU Chief of Police. Outside the meeting room, several D.E.A. agents were staffing tables featuring promotional displays for the agency and handing out D.E.A. memorabilia including highlighters, flashlight key chains and pens. One table that was put together by the Tallahassee police displayed a city map of Tallahassee featuring red dots to mark each drug related arrest in the city. Not surprisingly, the vast majority of the dots were covering Tallahassee’s racially segregated “Frenchtown” neighborhood on the map. I took some pictures of the display and pointed out the apparent racial disparity in arrest practices to some of my fellow NORML activists. I also noted the apparent racial disparity to the police officer staffing the table. It soon became apparent that our group of well dressed and well scrubbed university students were not there to join the D.E.A. or the police, but to challenge the official line that they sought to present. After we left the T.P.D. table, we visited some of the D.E.A. tables and soon noticed that several suit-wearing individuals were watching and photographing us in a not too clandestine manner. We presumed that these people worked for the D.E.A., but were not dissuaded from going inside the event. After visiting some D.E.A. tables, I noticed that the police had removed the large folding map of the city . It was a made for T.V. event, but I doubt its promoters had any idea what kind of T.V. they were in for prior to our arrival. Inside the well-lit meeting room, the event’s organizers had set up a dais for the panel discussants. The room also featured a video screen, and several staffed T.V. cameras. Our group of activists separated and sat scattered throughout the room. During the panel presentation,cannabis grow indoor the movie screening and the beginning of the question and answer session, we all remained dutifully silent and respectful. Separately, we raised our hands and got in line to ask questions of the panel.

When I got my chance to speak I took the microphone from the emcee and began to read severally carefully selected points from a one-page fact sheet produced by the SMO The Sentencing Project. I highlighted the facts that we had the largest prison population of any nation, our punitive drug policy had contributed to the huge prison population, and ethnic minorities accounted for the vast majority of drug violation prisoners. While I was speaking I became very animated and visibly angry. It was very empowering to be able to look the men responsible for carrying out the drug war in the eye, and to decry the many hidden consequences of our drug policy in a public forum. I was fairly articulate yet animated too. We had infiltrated a carefully orchestrated public relations event organized by various members of the drug control industry and done our best to expose the negative consequences of drug prohibition. This action made for great television and the broadcast was played repeatedly on the local public access channel. By the time we left, we had been photographed numerous times by DEA agents, which we took as indicative of our success. Little did I know at the time, my performance would make me somewhat of a local celebrity. In the months after the event, numerous strangers would stop me in the supermarket and say that they had seen me on T.V. with an approving smile. This action solidified my resolve to challenge drug policy. The cavalier reaction of the panelists to our challenges and the attempt to intimidate us by D.E.A. agents served to strengthen my resolve to continue working for drug policy change. Since I moved to California in 2004, I have remained active in the drug policy reform movement in a variety of ways. I have worked at a medical marijuana dispensary in Berkeley, California for several years, volunteered for an organization called the Cannabis Action Network , and become a member of various drug policy organizations including Students for Sensible Drug Policy and the Drug Policy Alliance . One way that I stay aware of what various organizations are doing is through the social networking site, “Facebook.” Throughout this study, my analysis of the movement will be informed by the various ways that I participate in it.I have organized the dissertation into six chapters and a brief conclusion. Although the six chapters fit together to detail the pre-history and history of medical marijuana in California, they are also intended to be independent analyses of different aspects of drug policy reform. Consequently each chapter uses different theoretical lenses, samples of relevant literature and combinations of research methods to seek answers to diverse research questions. The six chapters link together to first situate my narrative of medical marijuana within the historical contexts of drug prohibition and drug policy reform. In the first three chapters I provide an analysis of drug prohibition, the history of the movement, and the spatial and organizational diffusion of drug policy reform. In the final three chapters, I analyze the medical marijuana movement in California as a case study of the wider movement’s biggest success. A major goal of the dissertation is to provide a social history of both the wider drug policy reform movement and the more focused medical marijuana branch of the movement. To my knowledge, this social history has not been written before, and narrating it with fidelity was both challenging and rewarding. It is my hope that each chapter is able to stand independently from the larger work, but that they are integrated to compose a richly contextualized and detailed narrative. In addition to contributing to the sociology of social movements and the sociology of drugs, providing the social history of the drug policy reform movement is an important product of my research. In chapter one, I seek to provide historical context for my study. By tracing the evolution of prohibition through its U.S. history I seek to show the roots of our current drug laws and the role of scapegoating, dichotomization, and racism in their passage. I begin the chapter with a brief review of relevant sociological literature and a short sketch of the historical development of prohibition, as drugs became the target of state and federal laws one by one. Next, I analyze the discourse of prohibition using conceptual tools from the sociology of affect. My goal in this chapter is to show the entrenched rhetoric and emotion of drug prohibition to give the reader an idea of the task confronting the drug policy reform movement. In chapter two I use in depth interviews, archival materials, and Internet research to trace the development of the drug policy reform movement. I theorize the movement as made up of three branches; marijuana law reform, harm reduction, and anti-prohibitionism. My analysis of the movement is guided by concepts from the social movement literature including insights and categories from Resource Mobilization theory. After a discussion of the historical context of the 1960s, I give an in-depth analysis of the development and decline of the National Organization for the Reform of Marijuana Laws in the 1970s. I use the categories of Resource Mobilization to emphasize the role of social movement organizations in the movement and to conceptualize the ways the various organizations in the movement relate to one another and funding sources as a social movement industry beginning in the 1980s.

The potential for cannabis withdrawal to mirror depressive symptoms may further contribute to under-detected drug use problems and unmet treatment needs. Regardless of cause, patients in depression treatment samples often have AUDs or use marijuana , and there is a need to initiate efforts in psychiatry treatment contexts that focus on marijuana use. This will be important as psychiatry providers often do not advise patients to reduce drug use in the context of depression treatment , and patients who use drugs and have depression often receive services in psychiatry contexts rather than specialty addiction treatment . Future work should address marijuana use, in addition to alcohol and depression symptoms, among patients with depression and AUD in psychiatry treatment settings. Limitations should be noted. Patients were recruited from an outpatient psychiatry setting, which may limit generalizability. Our enrollment criteria required participants to have mild depression based on having a PHQ-9 score ≥ 5. Yet, a PHQ-9 score of 10 only indicates the presence of major depression based on the DSM-IV criteria, after which thorough diagnostic assessments are required before patients can be assigned a formal diagnosis of major depressive disorder based on the DSM-IV or DSM-5 criteria. As only the PHQ-9 was available to measure depression in this study, and a relatively low cutoff score was used for enrollment, many of our participants would not have met criteria for major depressive disorder. Our findings should be considered within the context of these caveats. We know from the parent study that 12.0% had cannabis dependence , and it is possible that some participants were reporting symptoms consistent with cannabis withdrawal syndrome rather than depression. Our measure for AUD is limited because of its focus on the DSM-IV criteria and its reliance on self-report information. Due to changes in the DSM-5 criteria for AUD, our estimates based on the DSM-IV criteria may underestimate AUD compared to studies using the DSM-5. Our finding of worse functioning for AUD patients using marijuana was limited to PHQ-9 functional impairment,hydroponic racks which was assessed by one item and limited to depression related functioning.

Our use of the MCS-12 to measure mental health functioning is limited because of its global focus and its incorporation of depression symptomatology into the measurement . Future work would benefit from examining indicators of functional impairment potentially less confounded with symptoms. Marijuana use was dichotomized, which reduces statistical power and our understanding of patterns over time. We could not examine drug use other than marijuana over time due to low base rates. Because data on patterns of use and the primary compounds of marijuana were not available , we are precluded from commenting on the contribution of these factors to the outcomes studied. All measures were based on self-report, and future work may benefit from confirmatory structured assessments as well as laboratory tests to provide a more accurate assessment of psychiatric symptoms and drug use, respectively. While more research is required to replicate these results, findings indicate that whether patients with depression and AUD experience clinically problematic outcomes may be influenced by marijuana use. It would be valuable for future treatment and prevention efforts to assess and address marijuana in the context of outpatient psychiatry treatment, and such efforts should focus on patients with depression and AUD, in order to improve patient outcomes.Chronic pain affects approximately one-third of the U.S. population, and opioid prescriptions have substantially increased over the last 20 years . In parallel, there has been an increase in opioid-related complications, with opioid overdose deaths quadrupling between 1999 and 2015. Growing concerns about the risks of opioids, including overdose-related deaths and opioid use disorder, have prompted greater focus on the more judicious use of these agents for managing pain and the need to identify other agents to treat pain. The data on the efficacy of cannabinoids in the management of pain is evolving. In a systematic review, there was low-strength evidence that cannabis is effective for treating neuropathic pain and insufficient evidence of its effectiveness for other types of pain. The American Academy of Neurology has endorsed use of cannabinoids for the pain and spasticity associated with multiple sclerosis but cautions that the safety profile of cannabinoids has not been compared to other approved drugs.

Despite the lack of robust evidence for efficacy of cannabinoids in pain management, marijuana has been approved by legislatures or ballot initiative for the management of pain in over 30 states. Recent data suggest that medical marijuana laws have been associated with lower state-level opioid overdose mortality, hospitalizations related to opioid complications, detection of opioids among fatally injured drivers, and prescription of analgesics. These ecologic studies, while hypothesis generating, do not inform our understanding of the individual effects of marijuana use or combined marijuana and opioid use. Prospective cohort studies and clinical trials are needed to improve our understanding of the effects of cannabis on pain management. Nonetheless, these studies have spurred discussion about the potential for marijuana to serve as a substitute for opioids, particularly in contexts where marijuana is increasingly available through legalization. Small surveys of convenience samples of American and Canadian marijuana users have reported that substitution of marijuana for opioids is common, ranging from approximately 30% to 97% . To our knowledge, there are no nationally representative surveys examining substitution and reasons for substitution among the general US adult population. We examined the prevalence and reasons for substitution of marijuana for opioids among US adults taking opioids for pain, as well as the factors associated with substitution.Details of survey development have been previously published. The survey questions were designed based on a review of the literature and existing national surveys and interviews with substance abuse experts and marijuana distributors and dispensary staff . The survey asks about a wide range of topics, including perception of risks and benefits associated with marijuana use, comparisons of marijuana to other substances , and pertinent public health questions relevant to implementing marijuana legalization. The current study is based on the questions that were designed to assess the extent and reasons for substitution of marijuana for opioids. All questions used Likert scales for response options and were edited to meet an 8th-grade reading level. Prior to administration, our survey was tested on a convenience sample of 40 adults to ensure question reliability and validity. Volunteers were comprised of a panel of patients from the investigator’s clinics and were offered no incentives to volunteer . We ascertained opioid use with the following question: “In the past 12 months, have you regularly taken opiate medications such as Vicodin, Percocet, or OxyContin to treat pain? Do not include pain medications that can be bought without a prescription such as aspirin, Tylenol, or Advil.” We ascertained marijuana use with the following questions: “Have you ever used marijuana?” and “How long has it been since you last used marijuana?”

In 2017, we conducted an Internet-based survey of 16,280 adults about perceptions of marijuana using Knowledge Panel ,indoor garden table a nationally representative panel of the civilian, non-institutionalized US population. Knowledge Panel has been in use for surveying public opinion since 1999. GfK created a representative sample of US adults by random sampling of addresses. The address-based sampling covers 97% of the country and encompasses a statistical representation of the US population. Adults were invited to join through mailings, postcards, and follow up letters. Non-responding households were called. Participation included: completing and mailing back the paper invitation; calling a toll-free number provided by GfK; and completing a recruitment form online. All participants receive the survey in the same manner, households without Internet access are provided with an Internet connection and a tablet to ensure participation. All participants in the panel are sampled with a known probability of selection. No one can volunteer to participate. Participants do not receive monetary incentives to participate but receive points that can be used towards purchases. Participants are provided with no more than six surveys a month and are expected to complete an average of four surveys a month. . For the purposes of future investigation into the role of marijuana legalization on use, California residents and young adults aged 18 to 26 years old were over sampled. Sampling weights were provided by GfK.Our response rate, defined as the ratio of all respondents to all potential respondents, was determined using methodology as outlined by the American Association for Public Opinion Research. Characteristics of the survey respondents were weighted using weights provided by GfK to approximate the US population based on age, sex, race, ethnicity, education, household income, home ownership and metropolitan area. All analyses used weighting commands using the weight variable provided by GfK to generate national estimates. To determine how well our sample compared to a national federally-sponsored survey on substance abuse and marijuana use, we first compared the socio-demographic characteristics of our survey respondents to those of the National Survey on Drug Use and Health. NSDUH is an annual federal survey implemented by the Substance Abuse and Mental Health Services Administration , which is an agency of the Department of Health and Human Services . NSDUH provides data on substance abuse epidemiology in the US. We then examined opioid substitution among respondents with a history of ever using marijuana who used opioids in the past 12 months. We used logistic regression to determine associations between socio-demographic characteristics and status of marijuana legalization in the state of residence and substitution of marijuana for opioids. The cases who were categorized as “ever” marijuana users with opioid use within the past 12 months who refused to answer were excluded from this logistic model. Analyses were conducted using R statistical software . There were very few participants with missing data and these cases were dropped from the analysis. This study was considered exempt by the University of California, San Francisco Committee on Human Research.There were 9,003 respondents, corresponding to a 55.3% response rate. Baseline characteristics of respondents were similar to respondents from the National Survey on Drug Abuse and Health, though our respondents had a slightly higher average income, suggesting our sample was representative of the US population. The mean age was 48 years, 48% were male, 64% were white, and 64% lived in a state in which marijuana was legal. Among this national sample, forty-six percent reported ever using marijuana, and 8% reported regular use of opioids for pain in the past year. Among the 5% who reported ever using marijuana and using opioids in the past year, 43% used opioids daily, and 23% reported current marijuana use . Forty-one percent reported a decrease or cessation of opioid use due to marijuana use; 46% reported no change in opioid use; and 8% reported an increase in opioid use. The most commonly reported reasons for substitution were better pain management and fewer side effects and withdrawal symptoms , compared to the non-medical reasons for use: cheaper and more social acceptance from marijuana use . In multi-variable analyses, we found no association between socio-demographics or status of marijuana legalization in the state of residence and substitution .In a nationally representative survey of US adults, substitution of marijuana for opioids, which included a substantial degree of opioid discontinuation , was common. Better self-reported pain management and fewer side effects and withdrawal symptoms were the most common reasons for substitution. Our findings are consistent with prior surveys of American and Canadian marijuana users in which substitution of marijuana for opioids was prevalent due to better symptom management and fewer adverse and withdrawal effects. Our study overcomes the potentially biased reporting in favor of substitution from prior convenience samples of marijuana users. This may explain why the prevalence of substitution in our study was lower than that of other studies in which a prevalence of up to 97% has been reported . Additionally, we focused specifically on substitution of marijuana for opioids and asked about this practice directly whereas other studies asked about substitution of marijuana for prescription drugs more broadly or indirectly assessed opioid substitution. Our results were also inconsistent with a recently published Australian cohort study which followed approximately 1,500 people with chronic non-cancer pain prescribed opioids for four years.