Hemp Growing

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.

The observed marijuana-oropharyngeal cancer associationwas then divided by the bias factor to estimate an adjusted OR which accounted for confounding by HPV. The studies included in this analysis primarily collected information on marijuana use using interviewer or self-administered questionnaires. Therefore, differential misclassification of the reporting of marijuana use between cancer cases and controls is a possibility. To estimate the potential effect of reporting bias, simple probabilistic sensitivity analyses were conducted based on methods previously described . Sensitivity and specificity estimates used in this analysis were deriv.The rising incidence of oropharyngeal and oral tongue cancers over the last twenty years has paralleled trends of increasing use of marijuana among individuals born after 1950 . Therefore, we initially hypothesized that marijuana use could, in part, have contributed to the rising incidence of these cancers. Using pooled data from 9 case-control studies that contributed to the INHANCE consortium, we found evidence of a possible positive association of marijuana use with oropharyngeal cancer and a negative association with oral tongue cancer.. Our findings of a positive association of marijuana use and oropharyngeal cancer while in agreement with two prior studies contrasts with findings from five studies that showed no association . The possibility of a true association of marijuana use with oropharyngeal cancer risk was supported in the present study by the consistency of the observed associations with multiple measures of marijuana use including ever use, duration and frequency of use and was unaffected across strata of smoking and drinking. However,microgreens shelving the inconsistent association across studies in this pooled analysis combined with an attenuation in the association after adjustment for smoking and drinking make the effect of residual and unmeasured confounding highly plausible.

Differential exposure to HPV infection among marijuana smokers as compared to nonsmokers could be one source of potential confounding to explain the association of marijuana use with oropharyngeal cancer, as marijuana users engage more frequently in risky sexual behaviors leading to higher rates of sexually transmitted infections . We had serologic information on HPV 16 from four studies. Unfortunately, the association of marijuana use and oropharyngeal cancer among these four studies was not representative of all the studies included in the pooled analysis, although stratified analyses among these four studies by HPV 16 L1 serostatus revealed a modest positive association of ever and long duration marijuana use oropharyngeal cancer among seropositive individuals. Therefore, we attempted to estimate the potential confounding effect of HPV on this association using plausible estimates of the association of HPV infection on oropharyngeal cancer risk as well as differences in oral HPV prevalence by marijuana usage. This approach revealed a substantial and nearly complete attenuation of the association of marijuana use with oropharyngeal cancer risk. Lastly, the association of marijuana use appeared to be specific for those oropharyngeal cancers most likely to be HPV-associated: non-smoker/nondrinkers, and those with tonsil or base of tongue sites. These data suggest that the positive association of marijuana use and oropharyngeal cancer may be dependent on exposure to HPV. In lieu of more definitive information on tumor HPV infection status among cases and oral HPV infection status among cases and controls, the role of marijuana use as a potential risk factor in oropharyngeal cancer cannot be determined. We observed that marijuana use was strongly inversely associated with oral tongue cancer specifically, which is similar to what has been reported previously among oral cavity cancers in general . This association remained robust across all marijuana use metrics, was strengthened after adjustment for tobacco and alcohol use, and was consistent across the five studies that had sufficient numbers of cases. Given that a very small fraction of oral cavity cancers are attributed to HPV , it is not surprising that marijuana use remained strongly inversely associated with oral tongue cancer even after adjustment for HPV . Lastly, the inverse association appeared to be strongest amongst individuals <50 years of age, which are the same individuals that have the greatest observed per year increases in oral tongue cancer incidence . Therefore, this association may reflect a true inverse association of marijuana use on oral tongue cancer.

The major bio-active cannabinoid compound found in marijuana smoke, Δ – tetrahydrocannabinol -THC, has been shown to have both pro- and anti-carcinogenic capabilities. This cannabinoid functions primarily through engagement of specific cell surface receptors CB1, expressed on a range of cell types and CB2 present primarily on a variety of immune cells, particularly those found in the human tonsil . Engagement of these receptors on immune cells has been shown to suppress pro-inflammatory cytokine production and enhance anti-inflammatory cytokine production leading to reduced host immune responses to infectious agents as well as suppression of anti-tumor immunity . Conversely, Δ -THC has also been shown in epithelial cell lines to have distinct antitumor effects through arrest of uncontrolled cell growth, enhancement of apoptosis, and down regulation of angiogenesis and cellular migration . As a result, this cannabinoid has been investigated as a potential therapeutic agent in the treatment of glioma, breast and prostate cancers . Interestingly, the anti-tumor effect of this cannabinoid is mediated through the same CB1 and CB2 receptors. The effects of tetrahydrocannabinol -THC and other cannabinoids on modulating tumorigenesis may be cell and tissue specific based on receptor expression profiles. This may help explain the differing associations of marijuana smoke with oropharyngeal and oral tongue cancers. Lastly, the presence of other carcinogenic compounds present in marijuana smoke may also play a role in driving the association. Differences in the measurement of marijuana use, study sample recruitment, and measurement of demographic and other risk factors for Head and Neck Squamous Cell Carcinoma across the studies included in this analysis may have contributed to the heterogeneity observed across study sites. However, this heterogeneity was observed only for oropharyngeal cancer and not oral tongue cancer. Nevertheless, we included in our logistic regression models a random-effects term for each study to account for the heterogeneity of the association of marijuana use with oropharyngeal cancer outcomes. Furthermore, we acknowledge the possibility that misclassification in the measurement of marijuana use between cases and controls may explain some of these findings. Misclassification of marijuana exposure due to the use of self-administered or interviewer administered questionnaires has been suggested previously to be significant source of error in the observed association with head and neck cancers .

Sensitivity analyses that modeled the effects of differential and non-differential misclassification of marijuana exposure demonstrated that correction for misclassification did alter the strength of the association with each cancer outcome . Therefore,greenhouse tables it cannot be ruled out that either differential or non-differential misreporting of marijuana exposure may explain the observed associations of marijuana use with oropharynx and oral tongue cancers. This pooled analysis of nine case-control studies conducted in the US and Latin America is the largest to date to investigate the relationship of marijuana use specifically with cancers of the oropharynx and oral tongue. The differing associations of marijuana use on oropharyngeal and oral tongue cancers observed in this study provides some epidemiologic support for the biological effect of cannabinoids as both a pro- and anti-carcinogenic agent. However, given the strong association of HPV on orpoharyngeal cancer not measured in this study, the modest attenuated effect of marijuana on these caners may well be explained by confounding by HPV. Additional studies focusing on cannabinoid receptor expression profiles and downstream effector functions across cell types involved in tumorigenesis of these cancers may yield important etiologic information as to the role of marijuana on head and neck cancer risk. Depressive disorders have been associated with morphological brain abnormalities, although the majority of studies have been conducted in adults. Reduced hippo campal volumes have been found among depressed adults , although this may be associated with age of onset and one found no hippo campal differences . White matter abnormalities have also been associated with increased depressive symptoms and suicidality in adult populations . Due to adolescent neuromaturation, which includes pruning of gray matter and proliferation of white matter, these adult results cannot be generalized to depressed adolescents . Three studies including depressed children and adolescents found no significant differences in hippocampal volumes , although one did report larger amygdala-hippocampus ratios and another reported reduced amygdale volumes .Further, one study found that depressed adolescents had smaller overall and frontal white matter volumes compared to healthy controls . To make matters more complicated, marijuana use is highly prevalent among adolescents; nearly half of high school seniors have tried it during their lifetime . Further, marijuana use appears moderately associated with an increased risk of depressive symptoms in both adults and adolescents . While some longitudinal studies found no or weak links between marijuana use and depression , recent studies have shown that heavy marijuana use during adolescence is associated with later risk for depressive symptoms . There are several possible explanations for the link between major depressive disorders and chronic marijuana use. The endogenous cannabinoid system is widely distributed throughout the central nervous system, including the prefrontal and hippocampal regions , as well as white matter areas . Although animal studies have suggested cellular effects, especially in hippocampal regions , and despite developmental changes to the endogenous cannabinoid system during adolescence , no studies to date have examined structural brain changes associated with marijuana use among human adolescents. Adult animal models suggest that damage to the cannabinoid system, specifically to the CB1 receptors, results in depressive-like symptoms in mice .

Adult human studies utilizing magnetic resonance imaging have yielded conflicting results, with two studies finding gray and white matter abnormalities among young adult marijuana polydrug users and one study found no differences . Wilson and colleagues , found that adult participants who had used marijuana before age 17 had smaller gray matter and larger white matter volumes compared to later-onset users. In sum, because marijuana may disrupt adolescent neurodevelopment , including the developing endogenous cannibinoid system , previous findings among depressed adolescents without comorbid substance use cannot necessarily be generalized to the rather sizeable population of marijuana users . Therefore, the goals of the present study were to examine: 1) the relationship between white matter and hippocampal volumes and depressive symptoms and 2) whether marijuana use moderates the relationship between brain structure and depressive symptoms in a sample of thirty-two adolescents. Adolescents were recruited from high schools, universities, and through ads. All youth were between 16 to 18 years old, fluent in English, and had a parent/guardian available to consent and provide history. Other comprehensive exclusionary criteria included: psychotropic medication use; history of DSM-IV Axis I disorder ; LOC >2 minutes; serious medical illness; learning disability/mental retardation; significant maternal drinking or drug use during pregnancy; complicated birth ; parental history of bipolar I or psychotic disorders; left handedness; vision or hearing problem; and MRI contraindications. Finally, any youth with data suggestive of substance use in the 28 days prior to the session were excluded from analyses. All participants and, if under age 18, their parent/guardian, underwent written informed consent and, for minors, assent in accordance with the UCSD IRB. Of those eligible, data were collected from sixteen marijuana using and sixteen drug-free adolescents . MJ-users took marijuana at least 60 times in their lifetime, did not meet criteria for Heavy Drinker status , and did not use substances other than marijuana, alcohol, or nicotine > 25 times in their lifetime. Controls never met criteria for Heavy Drinker, had < 5 experiences with marijuana, and never used any other drug besides nicotine. Trained laboratory assistants administered the youth screening interviews to assess the aforementioned inclusion and exclusion criteria. Parents or guardians of youth were then contacted. Parents and youth were informed that they would not receive information regarding each other’s responses or test results. If still eligible, potential youth and parent/guardians were administered a detailed interview assessing demographic and psychosocial functioning, Axis I psychiatric disorders, and drug use history. To improve open disclosure, different lab assistants interviewed the parent and youth. If eligible, they were scheduled to begin the monitored abstinence protocol.

Given the importance of this issue for drug policy, research on the mechanisms through which medical marijuana laws promote the initiation of marijuana use by young adults should be prioritized. This study was subject to several limitations. We were unable to rule out the possibility that, over longer windows of time, state medical marijuana laws will exert impacts on marijuana consumption and initiation by younger people dwelling in these states. We tested models using variables representing the length of time that each state’s medical marijuana law had been in place but found no statistically significant effects. We also could not examine whether legalization of marijuana for medical purposes has different effects as compared with recreational legalization; the NSDUH data did not extend into the years after recreational policies were established. The NSDUH data collection takes place at various points through the calendar year, and the date of any given participant interview may or may not have matched up with enactment of new medical marijuana legislation in their state; however local variation in availability of marijuana would make even a stricter date-based classification subject to the same potential mismatch on the individual level. Under reporting of drug consumption and initiation is also likely because of social acceptability concerns and survey respondents’ fears of disclosure . The NSDUH used computer-assisted interviewing to increase the validity of self-reports consistently throughout the 10-year observation period. As young people’s views about marijuana grow more permissive over time , survey respondents could become more willing to report that they have tried marijuana thus introducing bias into this analysis. Our multivariate models controlled for time trends to address this problem. Finally, our analyses could not capture sub-state variation in the implementation of medical marijuana laws .Adolescence requires some risk-taking as independence from the family is taking form, but for some teens,rolling grow table risk taking may lead to unhealthy or unsafe decisions. Risky behaviors such as unprotected sex, reckless driving, and substance use are associated with lasting negative outcomes .

With regard to substance use, the annual Monitoring the Future study reported that marijuana is the most commonly used illicit drug in the United States, with 7% of 12th graders reporting daily use . Individuals who engage in regular substance use may have a higher propensity to take unsafe risks despite the possible negative consequences . Without testing adolescents prior to initiation of substance use, it is difficult to determine whether elevated levels of risk-taking predated substance use. However, risk-taking performances of adolescents with and without histories of regular marijuana use can help us to understand what leads some individuals to substance-related problems. The Balloon Analogue Risk Task offers a behavioral assessment of risk-taking. In adult samples, riskier BART performance has been associated with higher levels of alcohol use as well as substance use, gambling, unsafe sex, and stealing , and it has successfully differentiated MDMA 3,4-methylenedioxymethamphetamine; “ecstasy”) users from controls . Riskier BART performance was also associated with greater alcohol, cigarette, and poly drug use in a community sample of young adults . Among adolescents, riskier BART performance was related to greater self-reported substance use and safety risk behaviors . Adolescent patients with conduct disorder and co-morbid substance abuse/dependence have also shown greater risk-taking with the BART compared to healthy controls . Some studies have examined marijuana users specifically. For example, adolescent marijuana users demonstrated impulsive decision-making with the Information Sampling Test ; however, users had a median of less than 24 h of abstinence. Using the BART, Schuster et al. found that riskier BART performance was correlated with higher levels of risky sexual behavior among young adult marijuana users; however, participants may have used marijuana the day prior to testing and were not compared to non-users. Gonzalez et al. found no differences on the BART in a sample of young adult marijuana users versus non-using controls; however, Gonzales et al. allowed for recent marijuana use , with a median of three days since past use. Because previous studies of young marijuana users allowed for recent use, the effects of residual marijuana levels may have affected task performance. In the current study, we examined risk-taking via the BART in late adolescent marijuana users with at least two weeks of abstinence from marijuana, in comparison to non-using controls.

This approach considers how marijuana users function relative to their non-using peers and reduces possible residual effects from recent substance use. We hypothesized that participants reporting greater substance use would demonstrate riskier BART performance. Further, previous studies have not yet examined the relationship of risk-taking to executive functioning in adolescent marijuana users. Executive function is a complex collection of abilities primarily modulated by the prefrontal cortex. Several studies have found altered prefrontal cortex processing and executive dysfunction in marijuana users . Completing the BART has also been linked to increased prefrontal cortex activation in healthy controls , and a recent meta-analysis of neuroimaging studies suggested that individuals with substance use disorders may have altered risk processing compared to healthy controls, primarily in ventromedial prefrontal cortex, orbitofrontal cortex, striatum, and other areas involved in risk and decision-making . Given the involvement of the prefrontal cortex in both risk-taking and executive functioning, we examined whether elevated risk-taking, as measured by the BART, was associated with poorer executive functioning, as measured by traditional neuropsychological tests. We hypothesized that a riskier approach to the BART would be associated with poorer performance on executive function tests.Participants were part of a longitudinal study of marijuana’s effects on neurocognition during adolescence and young adulthood, with assessments at intake and at 18- and 36-month follow-ups . Adolescents were recruited from local high schools. Teens and their parents/guardians were screened for demographics, psychosocial functioning, and family history of Diagnostic and Statistical Manual for Mental Disorders, 4th Ed. , 2000) substance use and other Axis I disorders. Confidentiality was ensured within legal limits to encourage full disclosure. Prior to participation, written informed assent and consent were obtained in accordance with the University of California, San Diego Human Research Protections Program. At study intake, exclusionary criteria included history of psychiatric disorder other than substance use disorder, serious medical problem or head trauma, premature birth, prenatal drug or alcohol exposure, and substance use during monitored abstinence.

Intake classification criteria for the marijuana-user group included >60 lifetime marijuana experiences; past month marijuana use; <100 lifetime uses of drugs other than marijuana, alcohol, or nicotine; and not meeting Cahalan criteria for heavy drinking status . To produce an adequate sample size, controls were included if they had <5 lifetime experiences with marijuana , no previous use of any other drug except nicotine or alcohol, and did not meet criteria for heavy drinking status. The current data were collected at the 18-month follow-up, when participants were aged 17–20 years. A total of 48 marijuana users and 52 controls completed the BART task at the 18-month follow-up; however, 24 marijuana users and 18 controls were excluded from analyses based on the following abstinence requirements: at least two weeks since last use of marijuana, other drugs, or alcohol binge ; and at least three days since last use of any alcohol or psychiatric medications . Beyond the abstinence requirements, follow-up controls were further excluded for meeting abuse or dependence criteria for alcohol or any other substance . One participant in the baseline marijuana group had no marijuana uses in the previous 18 months and was also excluded, and one additional control was excluded due to meeting DSM-IV criteria for current post-traumatic stress disorder. Following these exclusions, the resulting sample of 58 demographically matched adolescents and young adults included 24 marijuana users and 34 non-using controls. At the 18-month follow-up, marijuana users were about seven months older , and as expected, reported higher levels of marijuana, alcohol,indoor plant table and other drug use than controls. marijuana users had 200+ lifetime marijuana use episodes and <130 lifetime experiences with other drugs. In addition, 10 marijuana users met DSM-IV criteria for marijuana abuse and seven for marijuana dependence , 10 met criteria for alcohol abuse, and two met criteria for other drug abuse. At the 18-month follow-up, the 34 controls had ≤15 lifetime experiences with marijuana, minimal to no previous other drug use except nicotine or alcohol .A structured clinical interview measured psychosocial functioning, health history, and family history of psychiatric and substance use disorders . Probable DSM-IV Axis I disorders were determined by the computerized Diagnostic Interview Schedule for Children Predictive Scales . Adult participants living independently completed corresponding modules of the computerized Diagnostic Interview Schedule .Parent interview. A parent/guardian was interviewed on child development and behavior, and youth/family medical and psychiatric history . Parents/guardians corroborated youth diagnostic reports with the parent version of the Diagnostic Interview Schedule for Children Predictive Scales. If participant self-report and parent collateral data were discrepant, additional information was reviewed from the file, and data were coded to reflect the presence of the symptom, to reduce participant and researcher bias. Substance use. Participants were administered the Customary Drinking and Drug Use Record to evaluate their lifetime, past three-month, and past 18-month use of nicotine, alcohol, marijuana, stimulants , hallucinogens, inhalants, opiates , dissociatives , sedatives , and abuse of over-the-counter or prescription medications.

Teens were also assessed for alcohol and drug withdrawal symptoms, related life problems, and DSM-IV abuse and dependence criteria . The Timeline Follow back facilitated recall of substance use over the past 28 days through a calendar layout. BART. The BART is a computer-based risk-taking assessment . Participants used the space bar to pump 30 simulated balloons one at a time to achieve the highest possible score. Balloons pop at an unpredictable rate , and a noise follows each response . The points earned for a balloon are lost if it pops, but temporary points can be saved by choosing “Save Points.” Participants weigh the increasing risk of popping each balloon against the potential gain of continuing to pump the balloon . The primary outcome measures were the mean number of pumps for balloons that did not pop and the total number of popped balloons during the session. High values on either variable suggest greater risk taking. The number of points earned on any balloon and the total points saved are not revealed to the participant – only whether they had earned a small, medium, big, or bonus prize depending on the amount of points saved. They were shown the possible candy rewards prior to starting the task and received the reward immediately upon completion of the task. Participants had no practice trials to assess risk, and each participant completed the same task . This measure has good test-retest reliability . Mood and personality. Mood and personality were measured to help characterize the sample and examine whether elevations in depressive, anxiety, or internalizing/externalizing symptoms were related to BART performance. Mood and anxiety were assessed using the Beck Depression Inventory and the Spielberger State-Trait Anxiety Inventory . We used the Child Behavior Checklist Youth Self-Report and Adult Self-Report to measure internalizing and externalizing behaviors. Neuropsychological testing. General intellectual ability was assessed by the Vocabulary and Block Design subtests of the Wechsler Abbreviated Scale of Intelligence . Measures of executive function included the Digit Span task from the Wechsler Adult Intelligence Scale-Third Edition ; and the Trail Making, Towers, and Verbal Fluency tests from the DelisKaplan Executive Functioning System .Participants were abstinent from marijuana, other drugs, and alcohol binge for at least two weeks prior to the assessment, verified with biweekly breathalyzer tests and urine screens including at the neuropsychological testing session. The urine screen tested for major substances including amphetamines, barbiturates, benzodiazepines, cocaine metabolites, marijuana metabolites, and opiates.All participants completed questionnaires and the neuropsychological battery. Teens and their parents/guardians received monetary compensation upon study completion.We used Fisher’s Exact Tests to compare categorical variables between groups and analysis of variance to examine group differences on continuous variables. Some alcohol and drug use variables did not meet requirements for parametric analysis; therefore we used the Mann-Whitney procedure to compare these characteristics between groups. Because marijuana users were slightly older than controls, age was controlled in analyses of test performance using univariate analysis of covariance .

To a first approximation, the rate at which soiling occurs via partitioning is independent of surface orientation. Vertical surfaces soil at rates similar to horizontal surfaces. The surface accumulation resulting from partitioning is commonly referred to as a “film.” We estimate that a pollutant film of 5 to 10 monolayers is thick enough to alter the interface with which airborne organic compounds interact. For a film composed of primarily indoor SVOCs, this is equivalent to a thickness on the order of 10 nm or less. Rates at which films accumulate on initially clean impermeable indoor surfaces have been measured in different indoor environments and are summarized in Table 2 of Weschler and Nazaroff. Film growth rates in the range 0.1-0.2 nm/d have been reported. At such rates, films with thicknesses of 5-10 nm would accumulate on indoor surfaces in 1-3 months. In a composite sample of five homes in urban Toronto, a film thickness of 5 nm was measured 3-5 months after window cleaning.Toward the higher end of organic soiling conditions, Wu et al. exposed aluminum, polished glass and ground glass disks for 2-3 weeks in a kitchen where cooking occurred daily. Prior to exposure, the clean surfaces exhibited significantly different sorptive partitioning of DEHP. The 2-3 weeks of exposure was sufficient for the disks to acquire an organic film that resulted in similar sorptive partitioning of DEHP across diverse substrate materials. Taken together, these measurements suggest that within a period of a few months, impermeable indoor surfaces are covered by a film, acquired via partitioning, that is thick enough to alter the chemical surface that it presents to indoor air. We note that the deposition velocities for lower molecular weight organic acids are comparable to those for SVOCs. However, the indoor gas-phase concentrations of species such as formic and acetic acid are orders of magnitude larger than those of indoor SVOCs. Hence,vertical rack the flux of lower molecular weight organic acids to an aqueous surface is potentially orders of magnitude larger than the flux of SVOCs to an incipient surface film.

While the rate at which SVOC partitioning contributes to surface soiling is independent of the surface’s orientation, the rate at which particles deposit on a surface varies substantially with orientation. Because particles settle under gravity’s influence, upward facing horizontal surfaces soil much faster than vertical or downward-facing surfaces. Based simply on geometry, upward horizontal surfaces account for roughly 20% of exposed indoor surfaces. Table 3 in Weschler and Nazaroff presents estimated rates for particle accumulation on vertical and upward-facing horizontal surfaces. The rate at which vertical surfaces soil via particle deposition is predicted to be much slower than the rate at which they soil via partitioning. Even in the case of upward-facing horizontal surfaces, soiling by fine particle deposition is relatively slow. Since water soluble salts and associated water comprise larger mass fractions of fine particles than of coarse particles, this is an important consideration.In summary, on impermeable indoor surfaces, semivolatile organic compounds accumulate much faster than particle-associated water-soluble salts. Only in the instance of an upward facing horizontal surfaces does particle deposition become important, and, in this case, gravitational settling of coarse particles dominates the deposition process. Upward-facing horizontal surfaces can accumulate particles to a level of 1 µg/cm2 on a time scale as short as a few days, whereas surfaces of all orientation can have a 1 µg/cm2 accumulation of SVOCs in a few months. As expected from theoretical considerations, the specific SVOCs that comprise indoor organic films are similar to those found in indoor airborne particles. In a recent intensive field study conducted in a test house, the HOMEChem project, such similarity was observed experimentally: “the signal intensities of the mass spectra for the indoor aerosol filter and surface extracts have high overlap, with a dot product of 0.98.” While we know something about the formation and composition of films on impermeable indoor surfaces, we have little information about the soiling of semipermeable or porous surfaces such as paint films, vinyl flooring, brick, concrete, carpets and upholstery. Among other factors, morphology, as well as orientation, are expected to influence the soiling of such materials.

The chemicals that comprise surface films evolve. They might initially be dominated by SVOCs; however, over time, they acquire particles and the water-soluble salts associated with these particles. The initial SVOCs in the film oxidize, which should tend to increase the oxygen to carbon ratio. This process may make the surface film more hygroscopic. The acquisition of inorganic salts and increases in the O/C ratio should lead to increased water content of surface films, especially during periods with higher indoor humidity, and the viscosity of the film may decrease as a consequence. Such changes could influence heterogeneous acid/base reactions, making them more likely in aged films under high RH conditions. Oxidation of surface films may also lead to phase separations that might further influence acid/base reactions. Evidence from nicotine The pH of skin’s surface typically is in the range 4.5-6.The pKa of monoprotonated nicotine is 8.0.Hence, at skin’s pH, one would anticipate that most would be ionized . Based on measurements from excised pig skin, ionized nicotine passes through skin about fifty times slower than neutral nicotine. If there is a homogeneous film on the surface of skin that is a mix of water, salt and skin lipids with pH of 4.5-6, then the capacity of this film for acquiring a combination of ionized nicotine and neutral nicotine would be very large. Since only the much less abundant neutral fraction is rapidly absorbed by the skin, transport from air through skin to blood should be relatively slow. However, actual measurements of the dermal uptake of nicotine from the gas phase indicate a fast transport rate.A possible explanation is that skin surface lipids and aqueous salt solutions coexist on the skin isolated from one another rather than being homogeneously mixed.As a crude analogy, they may exist more in the fashion of oil and vinegar rather than as mayonnaise. According to this conceptualization, nicotine that partitions from the gas-phase into islands of skin lipids would remain neutral, subsequently passing through the stratum corneum and viable epidermis to the dermal capillaries. Something similar may occur on impervious indoor surfaces; there may exist regions with aqueous surface films isolated from regions with organic rich films. Within porous surfaces, there may exist pockets of aqueous solutions and pockets of hydrophobic organics. If such is the case, then organic acids and bases could partition to both aqueous and organic substrates, and the relative amounts in each phase could influence the resultant surface chemistry.

Different methods have been used to characterize surface acidity.The more common methods have been reviewed by Sun and Berg. These include colloid titration, indicator dye adsorption, X-ray photo electron spectroscopy, and calorimetry. Most metal surfaces acquire a charge and, consequently,microgreen flood table an electrical double layer at an aqueous interface. The isoelectric point is defined as the pH value at which the potential of the double layer at the interface is zero. The isoelectric point is frequently used to characterize the acidity of solid surfaces. The IEP is measured by electrokinetic titration, which is a type of colloid titration. Another approach that has been used to evaluate the acidity and basicity of metal oxides is microcalorimetry. Using NH3 and CO2 as probe molecules, Auroux and Gervasini determined the number and character of basic and acidic sites on twenty metal oxides. Some metal oxides are basic , some are acidic , and some are amphoteric , reacting with both acidic and basic gases. Recently, Rindelaub et al. have made direct measurements of pH in individual particles using a Raman micro-spectrometer coupled with a confocal optical microscope. Wei et al. have applied a related method using 2D and 3D confocal Raman microscopy to determine the pH of suspended aerosol droplets smaller than 50 µm diameter. Such methods might be adapted to probe surface acidity. The acid-base properties of glass have received considerable attention. 500 Silicon dioxide, forming the chemical framework of glass, is acidic in a Lewis-acid sense . Glass is relatively inert to acids, but is attacked by bases, especially when an aqueous layer in contact with glass has pH > 9. The acid base properties of a polymer can often be described as those of its repeating unit. A substantial proportion of the SVOCs found in surface films are organic acids. Some of these can have human origins. Liu et al. measured the major organic constituents in films on impermeable indoor surfaces from five sites in greater Toronto.Monocarboxylic acids with 11-31 carbons accounted for between 76% and 81% by mass of the total organic fraction. Together, monocarboxylic acids, dicarboxylic acids with 6-14 carbon atoms, nine aromatic polycarboxylic acids, and five terpenoid acids accounted for 81- 95% by mass of the total organic fraction, which included n-alkanes, PAHs, PCBs, and pesticides. These study results demonstrate an acidic character for organic surface films. Surfaces that are basic and porous can be large sinks for acidic gases.

Concrete, especially if it is improperly cured, and brick are examples of surfaces with basic properties. In China it is common to whitewash walls in apartments and other buildings. , prior to the introduction of modern paints and sealants. Among some enthusiasts in the US and Europe, whitewashed wood walls, brick walls and furniture are making a comeback . Whitewash is made by mixing hydrated lime with water, producing a white sealant. A whitewashed/limed wall is chemically basic and would have a high capacity for sorptive uptake of gas-phase acids. To what extent is the pH of a surface determined by the surface itself versus gases dissolved in water associated with the surface? In the case of a hydrophobic surface, the amount of sorbed water is small and the nature of the surface itself should determine its acidity. In contrast, the acidity of a hydrophilic surface may be largely influenced by gases that have dissolved in the water associated with the material. Such may be the case for cotton fabrics or untreated nylon carpeting.Some surfaces attract water ; others repel water . Surfaces are somewhat arbitrarily categorized as hydrophilic or hydrophobic based on the contact angle between a water droplet and the surface. If the contact angle is < 90° , the surface is considered hydrophilic . Common hydrophilic surfaces indoors include nylon, glass, stainless steel, gypsum in wallboard, and cotton fabrics. Hydrophobic examples include untarnished silver, chromium, candle wax, and polypropylene. Surfaces that are extremely hydrophobic, such as Teflon or those treated with perfluorocarbon stain repellants, repel water and other highly polar compounds. Ionization of an acidic or basic species is limited on a hydrophobic surface with very little water available, and so, acid-base chemistry would be deterred on such a surface. The degree of hydrophilicity also influences processes such as the disproportionation of NO2 onto indoor surfaces to form HONO and HNO3. An example of the latter process has been reported for a series of experiments in which NO2 was injected into a 2.5-m3 chamber and the airborne concentrations of both NO2 and HONO monitored. The chamber surfaces were either all Teflon or all vinyl wallpaper ; in a subset of experiments, the floor of the Teflon or vinyl chamber was covered with a hydrophilic synthetic carpet. The measured NO2 surface removal rate was more than an order of magnitude larger with carpet on the floor of the chamber than when all the surfaces were Teflon or vinyl . Additionally, the peak gas-phase concentration of HONO, generated from the NO2 injection, was larger with carpet in the chamber than when all the surfaces were Teflonor vinyl . These results were likely due to a combination of increased surface area and the larger moisture content of the carpet compared to either Teflon or vinyl. When the chamber surfaces were vinyl wallpaper and the RH was either 50% or 70% RH, HONO decayed significantly more slowly than the air-exchange rate indicating prolonged release of HONO from the surface. However, when the chamber surfaces were Teflon, HONO decayed significantly slower than the air-exchange rate only at 70% RH; it decayed at a rate similar to the air exchange rate at 50% RH.

Given the presence of amines in outdoor air that ventilates buildings, amines are also common constituents of indoor air, including airborne particles, and in indoor surface films. Indoor sources of amines, in addition to outdoor-to-indoor transport, include smoking; cooking; anticorrosive agents used in humidification or HVAC units; textiles and textile carpet tiles; and the decomposition of casein-containing building materials. Amines, amino acids, and urea are also known constituents of human skin.These compounds are used as active agents in personal care products, including skin moisturizers. Schmeltz and Hoffmann reviewed amines and amino acids identified in tobacco smoke.Their tabulations included 36 aliphatic amines with one to eight carbons, 40 aromatic amines including many aniline related species, and 16 amino acids. The 16 amino acids are noteworthy, given their relatively low volatility. α-Alanine is the most abundant amino acid. Grimmer et al. measured aromatic amines in mainstream and sidestream cigarette smoke.The identified amines included 2-aminobiphenyl, 1-aminonaphthalene, 2- aminonaphthalene, 4-aminobiphenyl, 2-aminofluorene, 1-aminoanthracene, 9- aminophenanthrene, 2-aminoanthracene, 3-aminofluoranthene, 1-aminopyrene. Per cigarette, sidestream smoke contained about ten times the summed mass of amines as in mainstream smoke. Dolara and co-workers, 406 using a sensitive mass spectrometry method, also measured amines from mainstream and sidestream cigarette smoke. The summed mass of aniline, 2- toluidine, 3-toluidine, 4-toluidine, 2-ethylaniline, 3-ethylaniline, 4-ethylaniline, 2,3- dimethylaniline, 2,4-dimethylaniline, 2,5-dimethylaniline, 2,6-dimethylaniline, 1- naphthylamine, 2-naphthylamine, 2-methyl-1-naphthylamine, 2-aminobiphenyl,3- aminobiphenyl and 4-aminobiphenyl in mainstream smoke was 0.2-1.3 µg/cigarette,indoor garden table while in sidestream smoke the summed mass was 20-30 µg/cigarette. They also measured these and other aromatic amines in homes with and without smoking .

Amines are anticipated to be emitted during the cooking of proteinaceous foods, especially meat. However, neither Rogge et al. nor Schauer et al. mention simple amines in their detailed studies of organic emissions from meat cooking. Certain heterocyclic aromatic amines are known carcinogens, and, consequently, several studies address their occurrence in cooked food products, especially meat, fish, and poultry. However, we have found no studies that have examined the emission of heterocyclic aromatic amines into air during cooking. Chiang et al. targeted aromatic amines in cooking oil fumes.They found that fumes from heated sunflower oil, vegetable oil and refined lard contained 2-naphthylamine and 4-aminobiphenyl.Amines are used as corrosion inhibitors in systems designed to humidify indoor air. Given their volatility, they can be present in the air of rooms that are humidified by such systems. They can also partition to indoor surfaces in the humidified rooms. Early indoor measurements were made by NIOSH investigators responding to employee complaints at a Cornell University museum in Ithaca, NY. At this site, diethylaminoethanol , also known as diethylethanolamine, was used as a corrosion inhibitor at the time of the investigation. Among 14 samples collected by Fannick et al., DEAE was detected in two, at concentrations of 40 and 50 µg/m3 . The investigators proposed that some of the complaints resulted from contact with surfaces onto which DEAE had sorbed. Volent and Baer review the Cornell museum case and other cases in which DEAE has been identified in the air of museums with humidification systems.They state that DEAE can react with acidic pollutants in museum environments to form hygroscopic salts that can accelerate metal corrosion. Edgerton et al. used a trace atmospheric gas analyzer to make continuous measurements of DEAE and cyclohexylamine in a typical steam-humidified room at the Battelle facility in Columbus, OH.At 42% RH, the concentration of DEAE and cyclohexylamine were 0.6 ppb and 0.7 ppb , respectively. At 61% RH, the concentrations were 2.4 ppb for DEAEand 0.8 ppb for cyclohexylamine.

During humidification, sorption to room surfaces was found to be a major sink for these amines, with reported rates of transfer to surfaces as follows: at 42% RH, 12 µg/s for DEAE and 8 µg/s for cyclohexylamine; at 61% RH, 14 µg/s for DEAE and 11 µg/s for cyclohexylamine. Given the volume of the room and an estimated surface area , the corresponding average deposition velocity for these amines to room surfaces would be ~ 16 m/h, a value that exceeds the likely mass-transport limit. When the humidification system was off, the amines decayed more slowly than would be the case for removal by air exchange, indicating that the amines were desorbing from room surfaces. Although numerous studies have examined the emission of amines from indoor sources, only a few have measured amines in indoor air. The Dolara group measured aromatic amines in outdoor and indoor air at offices and residences in the greater Florence region of Italy.Aniline and 2-toluidine were above the detection limit in all samples. Aniline ranged from 15 ng/m3 in outdoor air to 190 ng/m3 in a hairdresser’s shop with smokers, while 2-toluidine ranged from 2.5 ng/m3 in outdoor air to 17 ng/m3 in a recreation room with smokers. The concentrations of these species were elevated in the office of a nonsmoker adjacent to offices with smokers . Other amines whose average concentrations exceeded 2 ng/m3 in smoking environments included 3- and 4-toluidine and 2,3- 2,4- and 2,5-dimethylaniline. The Dolara group made more extensive measurements of aromatic amine concentrations in indoor and outdoor air in nine homes and 22 non-domestic buildings in Florence, Italy. Five of the homes were occupied by nonsmokers and four by smokers; the non-domestic sampling included both smoking and nonsmoking environments. Researchers focused on ten aromatic amines that they had measured in their earlier study: aniline, the three toluidine isomers , four dimethylaniline isomers , 2-naphtylamine and 4- aminobiphenyl. Excluding aniline, the summed indoor concentrations of nine of these amines were 5-11 ng/m3 in homes with nonsmokers and 15-34 ng/m3 in homes with smokers.

In the non-domestic buildings, summed indoor concentrations of these nine amines were < 20 ng/m3 in environments without smokers and tended to be higher with smoking. Aniline concentrations were commonly larger than the sum of the other nine amines and did not correlate with the concentrations of these other amines. Several of the non-domestic settings had aniline levels > 400 ng/m3 , including a hospital ward and a hospital waiting room. It was apparent that there were indoor aniline sources other than tobacco smoke. Zhu and Aikawa targeted nicotine and seven monoaromatic amines, including aniline, in measurements made in 69 residences in two regions of Canada. Smoking occurred in seven of these homes. Of the targeted compounds, only nicotine and aniline were routinely measured at levels above their detection limits. N-Methylaniline was detected in one home at 23 ng/m3 and was otherwise below its detection limit of 6 ng/m3 . N,N-Dimethylaniline, 2-ethylaniline, and 2- chloroaniline had detection limits of 9-10 ng/m3, while 4-ethylaniline and 2,4-dichloroaniline had detection limits of 20 ng/m3 . None of these amines were detected in any of the homes. Aniline was detected in 26 of the 69 homes, including five of the seven homes with smoking, at concentrations above the detection limit of 7 ng/m3. The highest aniline concentration in a home without smoking was 35 ng/m3 , while the highest level in a home with smoking was 58 ng/m3 . Among the homes in which aniline was successfully measured, without smoking, the mean concentrations in outdoor and indoor air were equal at 11 ng/m3 . The mean aniline concentration was higher in homes with smoking, 34 ng/m3 . In one of the homes, shoe polishing was demonstrated to contribute to indoor aniline concentrations. Akyüz developed an analytical method for measuring amines in air samples and demonstrated the method’s applicability for indoor and outdoor sampling during summer and winter months at six locations in Turkey.The indoor sites included both smoking and nonsmoking areas. In smoking environments,grow rack piperazine was measured at mean concentrations of 8 ng/m3 in summer and 22 ng/m3 in winter. In nonsmoking settings, average concentrations were 5 ng/m3 in summer and 10 ng/m3 in winter. Corresponding averages for aniline were 6 ng/m3 and 21 ng/m3 in smoking environments versus 1 ng/m3 and 4 ng/m3 in nonsmoking environments. Summed across 33 reported species , the mean concentrations for summer sampling were 42 ng/m3 in smoking environments, 20 ng/m3 in nonsmoking environments, and 13 ng/m3 outdoors.

For winter sampling, analogous results were 117 ng/m3 for smoking environments, 47 ng/m3 for nonsmoking environments, and 35 ng/m3 outdoors. Based on this small set of studies, we conclude that amines are commonly much more abundant in smoking than nonsmoking locations. In smoking environments, aniline, methylaniline isomers, butylamine, and piperazine dominate, while in the nonsmoking environments, aniline and the alkylamines dominate. Aniline is typically the most abundant amine indoors. The other amines are substantially less abundant. Amines and amino acids that have been measured or are anticipated to occur indoors are listed with some of their key properties in Tables 25 and 26, respectively.Given the reported presence of amino acids in outdoor airborne particles collected at both marine and land-based locations, 385 coupled with outdoor-to-indoor transport of such particles, one can anticipate that amino acids are present in particles indoors. Amino acids are present in sweat;  in corneocytes; in skin surface films; and in natural moisturizing factor , which plays an important role keeping the stratum corneum hydrated. Hence, we expect these amino acids to be transferred to surfaces that humans contact, and to surfaces soiled with their squames . However, we found no peer-reviewed publications that report measurements of amino acids in either indoor airborne particles or indoor surface films.Dunstan et al. have reported amino acid levels in sweat collected from male athletes exercising at 32-34 °C. When the subjects began sweating, the net concentration of amino acids in their sweat was almost 10 mM. After 35-40 minutes of exercise, the net concentration in sweat had declined to match the net concentration of amino acids in plasma . That is, the sweat was no longer leaching amino acids from the stratum corneum. This abundance is presumably the lower bound for net amino acid concentration in sweat . In post-exercise sweat, the most abundant amino acids were histidine , serine , ornithine , glycine , and alanine ; total amino acid abundance was 8 mM. How significant are amino acids in sweat for potential accumulation on indoor surfaces? If an occupant transfers 10 ml of sweat to indoor surfaces , then ´ 10-4 moles of total amino acids would also be transferred. If the average molecular weight of the transferred amino acids is 100 g/mol, this equates to 3-10 mg of amino acids being transferred to indoor surfaces — equivalent to the whole-body emissions of ammonia over a period of 1-2 h approximately 5-10 h. The mass of amino acids transferred to clothing is expected to be substantially larger. Amines are the most abundant organic bases in outdoor air. Through acid-base reactions with sulfuric acid, they play key roles in atmospheric nucleation and particle formation. More generally, they can neutralize strong acids in outdoor air. For example, Shen et al. found that amines, emitted during the burning of coal in the Yangtze River Delta region of China, react with nitric and sulfuric acid to form aminium salts . Aminium nitrates were more abundant than aminium sulfates, with average concentrations of methylaminium, dimethylaminium and ethylaminium salts in aerosol particles of 6 ± 3 ng m−3 , 8 ± 5 ng m−3 , and 20 ± 17 ng m−3 , respectively. However, ammonium nitrate and ammonium sulfate tended to be 1000 to 10,000 times more abundant than these aminium salts, indicating the much more important role of ammonia as an atmospheric base. Reviews from the Wexler group discuss amine acid-base chemistry, and much of their discussion is applicable to indoor environments.Ge et al. specifically addresses chemical properties of amines, including Henry’s law constants, acid dissociation constants, vapor pressures, activity coefficients, solubilities, and solid/gas dissociation constants of their aminium salts. Amines contribute to new particle formation, including sulfuric acid nucleation.Reactions with strong acids such as HNO3, HCl and H2SO4 form aminium salts. Reactions with dicarboxylic acids form amides. Amines can also partition from the gas-phase to airborne particles. To have an impact on particle formation in outdoor or indoor environments, an amine must compete with ammonia for strong acids. Typically, outdoor ammonia concentrations are three orders of magnitude larger than outdoor amine concentrations, and indoor ammonia concentrations are even larger than those outdoors.