Data collection on state medical marijuana laws included gathering all state statutes and subsequent regulations, and validating information against publicly available data sources and through telephone calls with state officials. Throughout the study, we conducted regular updates to monitor changes in regulations and amendments to state laws . Analyses incorporated a dichotomous measure reflecting whether a state did or did not have a medical marijuana law enacted during any given year of observation. Thus, a law passed or enacted at any point in a calendar year would count that state as a medical marijuana state for that year’s analysis. We also examined a wide range of characteristics of state laws, such as the amounts of marijuana legally allowed for possession and home cultivation, medical conditions covered, and the number of dispensaries in each state. Through a systematic measurement process, we created and validated a scale capturing the capacity of a given medical marijuana law to control marijuana distribution and diversion into illegal markets .We concatenated 10 annual waves of the NSDUH and all state-level indicators into a single data file. We conducted all analyses using Stata version 13 . For descriptive analyses of each survey year, we used weights to adjust for sampling design effects and non-response ; similar weights were not available for multi-year analyses. Following Williams and others , we accounted for shared variance among participants within states by calculating standard errors clustered at the state level in our regression models. Our analytic approach used logistic regression to predict marijuana consumption and initiation at the individual level separately for early adolescents, late adolescents,hydroponic tables canada and young adults. The regression models incorporated all individual- and state level controls and annual fixed effects. A key analytic concern is that people in states that pass medical marijuana laws hold more permissive views about the drug .
These more positive perceptions about marijuana may drive both the passage of the medical marijuana laws and higher rates of consumption . We incorporated that possibility into our uncontrolled comparisons of young people who dwell in states with medical marijuana laws compared to those who do not . By controlling for state-level fixed effects , we were able to examine whether medical marijuana laws have distinct causal impacts on marijuana consumption and initiation . The coefficients for each state controlled for any state-specific confounding not already captured by other control variables in the models. This technique allowed us to rule out the possibility that unobserved state-level con-founders account for any associations found between state medical marijuana laws and young people’s consumption and initiation of use.Using the most recent NSDUH survey, 2013, we compared rates of access to marijuana, past-month marijuana use and past-year initiation across early and late adolescent youth and young adults. Table 1 shows pronounced differences in the populations of young people living in states with medical marijuana laws compared with those who were not. These demographic differences—especially ones associated with drug-related attitudes—underscore the importance of applying individual-level controls in the analysis. For example, in 2013, individuals living in medical marijuana states were disproportionately white and Hispanic. Young adults living in medical marijuana states were comparatively less likely to be married and to have children. Figure 1 shows a positive age gradient in rates of reporting that marijuana is easily accessible and in past-month marijuana use: The highest prevalence occurred among young adults at 19.1%, then 11.9% of late adolescents and 2.2% of early adolescents . In contrast, initiation of marijuana use in the past year was most common among late adolescents , with young adults the next most likely to initiate marijuana use and early adolescents the least likely to have tried marijuana for the first time in the past year .
Table 2 shows logistic regression models predicting past month marijuana consumption that include all individual and state-level controls, and annual and state-level fixed effects. Results provided no evidence of a causal relationship between living in a state where medical marijuana was legal and the past month use of marijuana. Across all age groups, the odds ratio associated with medical marijuana state residence was not statistically significant. Table 3 provides similar fully controlled results for logistic regression analyses predicting past-year initiation of marijuana use. Results show that young adults dwelling in states that have legalized medical marijuana are significantly more likely to initiate marijuana use than counterparts in non-medical marijuana states . Such a relationship is not evident for early or late adolescents . We performed additional analyses to rule out several alternate explanations of these findings. Incorporating the amount of time since the passage of the medical marijuana law into our models produced similar results regardless of duration of the law. To rule out the possibility that young adults are more likely to initiate marijuana use due to mental health conditions, which in some states are legally allowed indications for a medical marijuana prescription, we estimated an alternate version of the models that included additional mental health-related variables, specifically, past-year use of mental health treatment and past-year unmet need for mental health treatment. After introduction of these additional controls, the effect of living in medical marijuana state remained statistically significant for young adults . We also considered the possibility that states with less restrictive medical marijuana laws could have more significant impacts on young people. We repeated all analyses with these variables and a summary scale reflecting the strength of controls on medical marijuana distribution, but these analyses failed to produce statistically significant results for any age group .Prior studies focusing on whether medical marijuana laws impact young people’s consumption of marijuana have produced mixed results. In the absence of robust evidence that medical marijuana laws are not adversely impacting young people, the number of states passing these laws has accelerated. The analyses presented here found that medical marijuana laws are not causally associated with recent marijuana consumption in young people.
However, we did find that medical marijuana laws impact the initiation of marijuana use, but that this is confined to young adults and does not include the more vulnerable populations of early and late adolescents.Prior research has largely focused on how medical marijuana laws impact rates of marijuana consumption, placing less emphasis on the initiation of marijuana use. But the potential for these laws to impact the age-at-first use of marijuana has considerable public health significance.Younger age at initiation is one of the strongest predictors of drug dependence and related problems later in life . Although we found a positive age gradient in the rates of consuming marijuana during the past month, patterns were different for initiating marijuana use. Our analysis showed that the initiation of marijuana use most commonly occurs during late adolescence. This finding is consistent with developmental theories suggesting that high-school age youth are uniquely prone to act on social messages and to experimentation with drugs . Fully controlled regression analyses showed that medical marijuana laws significantly increase the likelihood of trying marijuana for the first time among young adults, but not younger age groups. Young adults are in the peak years of engagement with illicit drugs during the life course . Compared to early and late adolescents, young adults have heightened availability and opportunities to use illicit drugs. This age group is past the peak age for initiating marijuana use and is therefore at a reduced risk for developing persistent marijuana-use disorders. However, our findings suggest that some of the young adults in this study might never have tried marijuana had they not been in a state that legalized medical marijuana. Future research should disentangle the mechanisms that account for why young adults in states with medical marijuana laws are more prone to initiating use. This finding is consistent with the notion that medical marijuana products may be diverted into illegal markets, thus increasing marijuana’s availability and driving down its price . Increased accessibility of illicit drugs is an important factor predicting the likelihood that individuals will initiate use . Where larger numbers are using marijuana, whether for medical or non-medical reasons, individuals interested in trying the drug can more easily access information on how to obtain it . Another possibility is that, in states with relatively lax enforcement of existing medical marijuana regulations,microgreen rack for sale young adults are more willing to try marijuana because they perceive that the risk of arrest is low or generally perceive the drug as less risky. 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, 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.