Future studies might attempt to identify potential premorbid characteristics that contribute to brain function abnormalities among marijuana users, such as additional facets of personality and psychological functioning, genetic markers, and hormonal influences. In addition, emerging evidence suggests shifts in neural processing during the initial stages of abstinence, and longitudinal examinations are needed to elucidate the time course and pattern of response through different stages of sobriety, which may inform treatment program design. Further, longitudinal follow-ups are needed to determine whether observed group differences will resolve with extended abstinence. Finally, diffusion tensor imaging and functional connectivity analyses could better delineate the neural networks and neurocognitive strategies influenced by marijuana use, while magnetic resonance spectroscopy could describe the cellular and metabolic changes associated with marijuana use.In summary, adolescent marijuana users demonstrated different patterns of fMRI brain response during spatial working memory after 28 days of monitored abstinence, despite similar task performance as non-using controls. MJ teens showed decreased right dorsolateral prefrontal response and increased right posterior parietal activation during SWM, as well as increased vigilance response in medial occipital regions. Together,ebb and flow tables these results point to increased spatial rehearsal and attention, but decreased executive strategies among MJ teens.
These findings suggest the possibility that heavy marijuana use in adolescence may be associated with persisting neurocognitive abnormalities, which could have important implications for future functioning among these youths.There is a national trend toward statewide legalization of medical marijuana despite federal classification of marijuana as a Schedule I illicit drug. There are compelling arguments for and against medical marijuana legalization and its potential impact on an array of complex social issues . Residents in states where medical marijuana is legal are more likely to have tried marijuana, report current marijuana use, and be diagnosed with marijuana abuse or dependence . Additionally, there is preliminary evidence to suggest that there is likely a dose-response relationship between the number of years since legalization and marijuana prevalence rates . A key question regarding more liberal marijuana policies is whether and how they affect use of other drugs including addictive and harmful substances like tobacco. Epidemiologic data indicate that the prevalence of tobacco and marijuana co-use has increased from 2003 to 2012 . Moreover, the increase in co-use occurred specifically among those ages 26–34 years, and the greatest percent increase, in those ages 50 years and older . It is unknown, however, if this national increase in co-use is directly associated with statewide legalization of medical marijuana. If marijuana policies are indeed associated with co-use, the current trend toward legalization of medical and/or recreational marijuana, without any regulatory action, has the potential to influence patterns of cigarette and marijuana use/co-use over time.
An increase in cigarette and marijuana co-use has the potential to create challenges for cigarette smokers who want to quit. There is evidence to suggest that cigarette and marijuana co-use is associated with greater nicotine dependence . Possible explanations for this link include the role of the endocannoboid system in nicotine metabolism , genetic predisposition for co-use , and various environmental and cultural influences . The relationship between co-use and nicotine dependence, however, is understudied in adults, particularly among those ages 50 years and older. Since nicotine dependence is influenced by both nicotinic receptors and nicotine associated metablism that change with age , we can expect nicotine dependence among cigarette and marijuana co-users will also vary over the lifespan. Few studies have examined cigarette and marijuana co-use and nicotine dependence from adolescence through adulthood. As the nation is well-past the tipping point on medical marijuana legalization, studies are needed to take a closer look into whether marijuana policies have the potential to influence tobacco control efforts at the population level. For example, over time, it is likely that greater access to legal marijuana will increase the absolute number of co-users who have greater nicotine dependence and difficulty quitting cigarettes. Such data can help to identify subset populations at higher risk of nicotine dependence and could have both policy and treatment implications in tobacco control. In this study, we sought to examine relationships between medical marijuana laws and cigarette and marijuana co-use. Additionally, we examined the likelihood of nicotine dependence in co-users. We analyzed data from the 2013 National Survey on Drug Use and Health and stratified the analysis by age categories. Results from this study can inform the direction of future medical marijuana policies that may inadvertently affect tobacco control efforts.
We analyzed cross-sectional data from the 2013 NSDUH conducted by the Substance Abuse Mental Health Services Administration . The primary purpose of NSDUH is to measure prevalence and correlates of drug use in the civilian, non-institutionalized U.S. population aged 12 years and older. Since 1991, NSDUH has consisted of an independent multistage area probability sampling design for each state and the District of Columbia and uses a combination of the Computer-Assisted Interviewing and Automated Computer Assisted Interviewing instruments in selected individuals and households . The survey offered $30 in cash to participants and was conducted in 2013 by Research Triangle Institute . The final survey consisted of 67,838 CAI interviews with a weighted screening response rate of 84% and an interview response rate of 72%. The public use file consisted of 55,160 records due to a sub-sampling step which included a minimum item response requirement for weighting and further analysis. A detailed description of the questionnaire items, sampling methodology, data collection/ response rates, and sample weights is published elsewhere . The present study was exempt from the University of California San Francisco’s Human Research Protections Program approval since data were publically available and subjects cannot be identified. In this analysis, only those with complete responses for all measures were included. Additionally,industrial drying racks while the analysis included participants aged 50–64 years, those 65 years of age and over were excluded due to a small sample size . The final sample included 51,993 participants. The item “How long has it been since you last used marijuana or hashish?” was used to classify respondents into three categories: “Within the past 30 days” ; “more than 30 days” ; and “never used marijuana” . Current marijuana users reported frequency of past 30-day use [Range = 1–30 days]. Cigarette use was assessed with an item asking whether and how recently participants had smoked “part or all of a cigarette.” Past 30 day users were categorized as current cigarette smokers, other than “within the past 30 days” as former smokers, and “never used cigarettes” as never smokers. Participants were coded as co-users if they had smoked at least one cigarette in the past 30 days and used marijuana in the past 30 days. Respondents who indicated blunt use were not included in our analysis since our analysis includes comparison of nicotine dependence in cigarette smokers who use marijuana vs. those who do not marijuana . Nicotine dependence was measured in two ways: the 17-item Nicotine Dependence Syndrome Scale and the single “time to first cigarette” item from the Fagerstrom Test of Nicotine Dependence . Respondents’ average NDSS scores were calculated over 17 items across five aspects of dependence and current smokers with a cutoff score of 2.75 or above were categorized as nicotine dependent. Those who responded smoking cigarettes in the past month and having their first cigarette of the day within 30 minutes of waking on the TTFC were categorized as nicotine dependent. Additional information on NDSS and TTFC questionnaire items, scoring procedure, and methods used for cutoff scores are published elsewhere .
We examine both NDSS and TTFC scores to potentially increase the reliability of our findings.Descriptive statistics are reported for demographics, cigarette and marijuana use, and lifetime depression as well as chi-square tests of differences by statewide medical marijuana legalization status . One-way ANCOVA models tested for differences in marijuana use and cigarette and marijuana co-use in the overall sample, and separately for each age category, between states where medical marijuana was legal vs. illegal, adjusting for age , gender, race/ethnicity, education, age at first cigarette initiation, age at first marijuana initiation, and lifetime depression. Additionally, we calculated mean NDSS and frequency of TTFC scores by statewide legalization categories across age groups. In the overall sample and within each age category, two logistic regression models examined nicotine dependence, as measured by NDSS and TTFC scores, in cigarette and marijuana co-users . Models were adjusted for age , gender, race/ethnicity, education, lifetime depression, and statewide medical marijuana legalization status. Bonferroni adjustments were applied to all models with over five independent variables . In this analysis, we used the Taylor series method for replication methods to estimate sampling errors of estimators based on complex sample designs. The regression coefficient estimators were computed by generalized least squares estimation using element-wise regression. The procedure assumes that the regression coefficients are the same across strata and primarily sampling units . All models were run in SAS 9.4 using the SURVEY procedures to obtain weighted estimates to increase the generalizability of the findings . The study sample was approximately half male, majority non-Hispanic White , and more than a quarter was college-educated . States where medical marijuana was illegal had higher proportions of non-Hispanic Whites and Blacks/ African-Americans and a slightly higher proportion of college graduates. In this analysis, 8.7% of the sample reported current marijuana use and 23.3% reported current cigarette use. As expected, there was a higher prevalence of current marijuana use in states that have legalized medical marijuana compared to those where medical marijuana was illegal , and this association was stable and significant across age categories, even after adjusting for covariates and applying a Bonferroni’s correction to account for multiple comparisons . Cigarette use was significantly lower in medical marijuana legal states compared to medical marijuana illegal states . Findings indicate an association between statewide legalization of medical marijuana and cigarette and marijuana co-use despite lower cigarette prevalence in states where medical marijuana was legal. Co-use was particularly robust among 18–34 year olds. Overall, cousers were more likely to be nicotine dependent compared to those who did not use marijuana, and 12–17 year old adolescent and 50–64 year old adult co-users were 3-times more likely to have nicotine dependence . These data suggest that medical marijuana legalization could inadvertently affect prevalence of co-use, which is linked to greater nicotine dependence, and the potential to create more barriers to smoking cessation . As more states pass marijuana laws, and the legal marijuana industry is poised to cultivate a landscape of greater access and exposure to marijuana , it is recommended that stakeholders in tobacco control prepare for any unintended effects on tobacco use including the possibility of tobacco initiation/ reinitiation among former smokers and greater nicotine dependence in current smokers . Longitudinal research is needed to evaluate the effect of state marijuana policy on tobacco use and marijuana and tobacco co-use. Co-use was higher and cigarette prevalence was lower in states where medical marijuana was legal. Given the nationwide increase in co-use , there may be uptake of marijuana use among cigarette users as states, change their marijuana policies and cigarettes smokers gain greater exposure and access to legal marijuana. It is possible that medical marijuana may be providing cigarette smokers with an alternative to tobacco especially as the stigma associated with tobacco continues to rise and the perceived harmfulness of marijuana decreases with legalization . Further, it might be perceived that the effects of marijuana can curb nicotine cravings and withdrawal symptoms to aid in smoking cessation . Finally, alternative tobacco products such as electronic nicotine delivery systems, which are commonly promoted as cessation aids and “safe” alternatives to smoking cigarettes , might also promote use of marijuana and THC oil with vaporizers . Co-use should therefore be monitored over time and examined in response to changes in marijuana policies that will further propel industry promotion of co-use and vaping. As expected, the prevalence of cigarette and marijuana co-use differed according to age. The positive association between medical marijuana legalization and co-use was greatest among 18–34 year olds. Previous studies with adolescents have reported greater prevalence but no increase in marijuana use or changes in permissive attitudes in states where medical marijuana was legal , suggesting that greater marijuana use, and therefore greater co-use, preceded medical marijuana legalization.