Given a high rate of overlap between marijuana and tobacco use among the participants, our study findings provide further support for implementing comprehensive tobacco control programs and underscore the importance of target interventions among high risk populations, including those using marijuana, in order to enhance the reach and effectiveness of prevention. Third, multiple unhealthy behaviors tend to co-occur but they are amenable to concurrent or sequential interventions. A successful change in one unhealthy behavior may lead to increased self-efficacy to modify other co-occurring unhealthy behaviors for which individuals may have low motivation to change.Finally, the difference in the prevalence of unhealthy behaviors across a number of sociodemographic subgroups highlights the need for evidence-based research to identify interdisciplinary intervention strategies that integrate science, practice, and policy to address health disparities among the population. Our study results also have several important clinical implications. SRH is an assessment tool for Patient-Reported Outcomes Measurement Information System that measures patient–reported health status for physical, mental, and social well-being.In light of the legalization of medical and recreational marijuana use in some US states, patients may be more likely to ask their healthcare providers about potential health effects of marijuana use. Many of the proposed health benefits and unintended consequences of marijuana use have not been fully explored. The findings of our study suggest that, in addition to receiving counseling about marijuana, patients with a history of marijuana use should obtain firm advice and support for not using tobacco. For those who plan to quit, evidence suggests that simultaneously quitting both tobacco and marijuana may yield important psychological and neurobiological benefits.Until more results from experimental research are forthcoming to provide guidance, it is important to encourage dual cessation. Our study has several limitations.
It was cross-sectional and cannot establish cause and effect. With the ongoing changes in medical cannabis grow setup law in a growing number of states, people with certain health conditions might be drawn into marijuana use. It might be possible that poor perceived health resulted in marijuana use rather than marijuana use caused poor perceived health. Research shows that the predictive power of SRH for mortality is robust across many subgroups of country of origin even after extensively controlling for numerous covariates. However, validation study has not been conducted among the population of US adult ever users of marijuana. We adopted serum cotinine as a biomarker to define current tobacco use, occasional tobacco users who had used tobacco beyond 3–5 days prior to examination may be included as non-current tobacco users. In addition, data on marijuana use were self-reported and were subject to potential recall bias or under-reporting of less socially desirable behaviors. Our study did not identify the use of specific tobacco products, including electronic cigarettes or electronic nicotine delivery systems that have been gaining popularity in recent years. Due to data constraints, we were unable to account for several potential confounders such as medication use, drug abuse, and other co-morbid conditions, as well as the difference in patterns of recreational versus medical marijuana use that might have had an effect on suboptimal SRH.In the present study, we assessed the impact of recent 30-day and 60-day regular marijuana use on suboptimal SRH among regular marijuana smokers. Because of the limited analytical sample size, we could not explore additional harmful marijuana and tobacco usage patterns related to quantity, frequency, timing, and duration of usage. It is worth noting that although several subgroups of the adult population were not evaluated in the current study due to a limited sample size, such adults are especially vulnerable to a multitude of health consequences associated with unhealthy behaviors even at low threshold levels for exposure. Long-term change of unhealthy behaviors is challenging and may require multifaceted efforts to effectively address the interplay of behaviors with biological, health, and social factors across various subgroups and environmental settings over persons’ life course .
Previous epidemiological studies have revealed strong negative impacts of marijuana use, suggesting that marijuana has similar potential for abuse as other illicit substances,is associated with respiratory illnesses, and leads to cognitive impairment.However, several focused empirical studies have countered these results, finding instead no significant effect of marijuana use on subcortical brain morphometry and only an uncertain effect on cognition.The past two decades have seen shifts in legal and societal attitudes toward marijuana use, with 23 states and the District of Columbia legalizing medical marijuana and four states legalizing recreational marijuana ; moreover, perceptions of the risk of regular marijuana use have decreased, even amongst adolescents, particularly in Colorado, recreational marijuana is now legal.As increases in the potency of marijuana have accompanied these shifts in attitudes,it is becoming increasingly important to understand the precise neural effects of long-term marijuana use and the impact of the age of first use. Adolescence is a sensitive period for brain development with white matter myelination and gray matter pruning, and, critically, an increase in the number of cannabinoid receptors that respond to marijuana.While preliminary studies of the effects of marijuana use on white matter integrity showed no significant effects in adolescents or adults,a growing body of research suggests that an adolescent onset of heavy marijuana use can have neurotoxic effects on developing white matter, reflected in decreased white matter coherence as assessed by measures of diffusivity, e.g., fractional anisotropy and radial diffusivity.Importantly, these effects have been observed longitudinally, suggesting a causation between marijuana use and white matter changes.However, most of these studies have relied on small sample sizes,so their ability to generalize to a broader population is limited. Moreover, the majority of these studies all examined the effects of heavy use,and much less is known about the effects of casual marijuana use on white matter integrity. As many white matter tracts continue to develop in adolescence and young adulthood,with maximal change in such development during this time frame,it is important to understand how the age of onset of marijuana use impacts neurodevelopment not only in heavy users but more casual users, especially considering that adolescence is often a time of experimentation with substances of abuse.
Studies of the effects of marijuana use on cortical and subcortical morphometrics in humans have typically focused on the amygdala and hippocampus and, to a lesser extent, the nucleus accumbens and orbitofrontal cortex. These structures are known to have important roles in reward processing and their function/structure is known to be disrupted by drugs of abuse.At least some, but far from all, of the evidence suggests an influence of marijuana on brain structure. For example, marijuana users compared to nonusers have been found to have reduced amygdala volume,and amygdala volume reductions have been correlated with increased levels of self-reported craving and relapse in consumption after 6-months from detoxification from alcohol dependence.On the other hand, a recent meta analysis of 14 studies of marijuana users compared to nonusers found no summary changes in amygdala volume, but did observe a consistent pattern of reduced hippocampal volume.In addition, a large number of studies with animals and humans have shown that marijuana affects the structure of the nucleus accumbens.Hence, there is evidence in the existing literature to suggest the possibility that marijuana influences the structure of these regions, all of which are known to be affected in addiction.Nonetheless, a recent well-controlled study by Weiland et al. found no evidence of an effect of marijuana on the morphometry of these structures. They compared morphometry in a sample of adult and adolescent daily users of marijuana to nonusers,while controlling for other confounding variables of tobacco use, depression, impulsivity, age, and gender. Importantly, they found no group differences in measures of brain morphometry for the nucleus accumbens, amygdala, hippocampus, cerebellum, or 35 cortical regions in each hemisphere. Interestingly, when they simply controlled for the amount of alcohol use, rather than matching users and nonusers, they replicated several findings of Gilman and colleagues. Furthermore, when examining effect size across previous studies, they found that the literature demonstrates a mean lack of effect. Given the discrepancies in the literature, we wanted to re-examine this issue using a large representative sample.
To this end, we analyzed extremely high-quality multi-modal neuroimaging data from 466 participants in the Human Connectome Project who reported using marijuana at least once during their lives.The participants in this sample consist of twins and their non-twin siblings who have no history of major psychiatric illness, but vary greatly in terms of race, education, income, BMI, and the degree of recreational drug use. A recent study used this HCP data-set to disentangle causal effects of marijuana use on regional brain volume from shared genetic effects and found that it was mainly shared genetic effects explained differences in bran volumes.However, this study did not investigate the effects of marijuana use on white matter integrity or the shape of subcortical regions, which was the focus of the current study. Rather than investigating extremes of marijuana use like most previous studies, we leveraged the large sample size to take a parametric approach, examining marijuana use along a spectrum, so as to search more specifically for dose-dependent effects. Nevertheless, a comparison of users and nonusers was also performed as a replication of prior work.Analyses of voxelwise gray matter morphometry were carried out with FSL-VBM an optimized VBM protocol carried out with FSL tools.First, structural images were brain-extracted and gray matter-segmented before being registered to the MNI 152 standard space using non-linear registration.The resulting images were averaged and flipped along the x-axis to create a left-right symmetric, study-specific gray matter template. Second, all native gray matter images were non-linearly registered to this study-specific template and “modulated” to correct for local expansion due to the non-linear component of the spatial transformation. The modulated gray matter images were then smoothed with an isotropic Gaussian kernel with a sigma of 3 mm. Finally, voxelwise GLM was applied using permutation-based non-parametric testing, correcting for multiple comparisons across space, using Threshold-Free Cluster Enhancement.Following Weiland et al.,we also performed a multivariate analysis on the effects of outdoor cannabis grow use on subcortical and cortical volumes and cortical thickness extracted with Free Surfer.
Rather than analyzing whether marijuana showed a multivariate effect across all 35 cortical regions contained in this table as did Weiland et al.,we chose an a priori approach, focusing on prefrontal regions and subcortical regions where marijuana has been shown to have significant effects.Regions of interest included 15 prefrontal cortical regions : medial and lateral orbitofrontal cortex, caudal anterior cingulate, caudal middle frontal, inferior frontal gyrus,rostral middle frontal, superior frontal, and frontal pole. Subcortical regions included nucleus accumbens, hippocampus, cerebellum cortex and white matter, thalamus, and amygdala.White matter volumes were included for the anterior and mid anterior corpus callosum.We then examined the effects of marijuana use on white matter diffusion parameters.The group comparison showed no significant effects, possibly suggesting that the frequency of marijuana use in the HCP sample is not severe enough to replicate previous studies, which largely focused on comparisons of non-users and daily marijuana users. In line with this possibility, there were no linear effects of the number of times used on white matter coherence in users.As shown in Fig. 2, age of first use had a positive association with FA as well as a negative association with RD, such that an earlier age of first use was associated with lower FA and greater RD in a large cluster of right hemisphere white matter. These tracts primarily subsisted of the Superior Longitudinal Fasciculus,Inferior Longitudinal Fasciculus,and Forceps Major and Minor. The SLF connects the prefrontal cortex and parietal cortex and is involved in executive functions,and the ILF connects the temporal and occipital cortices, has been shown to affected by adolescent marijuana abuse.The Forceps Major and Minor are extensions of the corpus callosum connecting the left and right occipital and frontal lobes, respectively. Thus, even though most of the effects on FA and RD were found in the right hemisphere, communication between the left and right hemispheres may be impacted by marijuana age of onset. When examining the subset of unrelated marijuana users, we confirmed the negative effect of an earlier age of first use on FA and RD in the SLF, as shown in Fig. 3.