Despite the low number of asthma respondents, the self-reported asthma prevalence rate of adolescents in this study  was similar to that reported  by the Ontario Asthma Surveillance Information System,which uses a validated health administrative data case definition to capture asthma with 84% sensitivity and 76% specificity. Secondly, the cross-sectional design of the survey is a major study limitation in assessing causal relation of asthma and smoking. It is unknown from this study whether adolescents with asthma smoked e-cigarettes more often or if smoking e-cigarettes contributed to the risk of asthma. Thirdly, asthma was self-reported and it not clinically confirmed. Self-reported asthma may over or under represent actual prevalence of asthma. Furthermore, many studies  that examined the relationship between asthma and smoking did not separate severe or “uncontrolled” asthma from those with well-controlled mild to moderate asthma. The effect of smoking on adolescents with severe or uncontrollable asthma may be different than on those with mild to moderate asthma. The definition of smoking used may influence the study findings. We classified smoking for cigarettes, marijuana and water pipes as smoking one or more time over the past 12 months or ever for e-cigarettes. This definition includes those who smoke regularly but also adolescents who experiment with the various types of smoking. This classification of smoking has been used previously in studies using the OSDUHS data-set. We conducted additional analyses using another method of classifying smokers reported by Wong and colleagues. In this method a regular smoker is defined as smoking more than 100 cigarettes in their lifetime and any cigarettes in the past month. Using this method the results and point estimates remained very similar. Given this method of classification was only available for cigarettes, we opted to retain the ‘any cigarettes over the past 12 months’ method to ensure measurement correspondence with the other types of smoking.

Nevertheless, results suggest that adolescents with asthma are at least experimenting with e-cigarettes or any type of smoking more often than their peers without asthma, which may lead to higher smoking rates later in life. Finally, we were unable to adjust for parental smoking or parental history of asthma as these data were not collected by the survey. Having a parent who smokes may relate to the respiratory health of children,pot for growing marijuana but it also increases the odds of smoking for adolescents. While information on parental smoking is not available in our data, further research should examine the association between parental smoking and asthma for all types of smoking. This paper adds discussion to the question of whether adolescents with asthma would be less likely to smoke cigarettes, water pipes, marijuana or e-cigarettes. Our study findings suggest that adolescents with asthma had a significantly higher odds of smoking e-cigarettes or any substance. This may suggest a lack of knowledge of the potential harmful long term effects of smoking ecigarettes or a general perception that e-cigarettes are “safer” than tobacco cigarettes. While recent research has suggested that ecigarettes are less harmful than tobacco cigarettes, the long term effects are still unknown. Furthermore, a recent study reported that e-cigarette usage for adolescents increases the odds of smoking tobacco cigarettes in adulthood by six times [OR:6.17; CI:3.3e11.6], suggesting that e-cigarettes may be used as a gateway among teens. Public health campaigns and education should target adolescents and especially those with asthma to raise their awareness of the risks  of all types of smoking. Results from this study suggest that adolescents with asthma are not more likely to be smoking cigarettes, water pipes or marijuana than those without asthma. As the means  of smoking change, how adolescents can smoke,presents new challenges in relation to adolescent smoking and asthma. This study found that adolescents with asthma were more likely to smoke e-cigarettes than those without.

The results did not change when we included any type of smoking. Our study findings can be used to target the adolescent asthma population for smoking prevention and education campaigns and to raise their awareness of the risks associated with smoking in general. Although recent studies have reported that adolescents with asthma are more likely to smoke cigarettes or water pipes, this does not appear to be the case in Ontario, after adjusting for confounding variables. While this is encouraging, our study suggests that e-cigarettes are now popular among youth with asthma. Work should continue with anti-smoking and prevention campaigns to try and further reduce all smoking rates for adolescents, with an emphasis on the unknown and potential serious long term risks associated with e-cigarettes or alternative types of smoking.Adolescence is a unique developmental period characterized by major physiological, psychological, and neuro developmental changes. These changes typically coincide with escalation of alcohol and marijuana use,which continues into early adulthood.The comorbid use of alcohol and marijuana among teens continues to subtly rise as perception of harm declines. Fifty-eight percent of alcohol drinking adolescents report using alcohol and marijuana simultaneously,,45% of youth endorse a lifetime prevalence of marijuana use by the 12th grade, and 22% of these youth endorse use in the past 30 days .The adolescent brain undergoes considerable maturation, including changes in cortical volume and refinement of cortical connections.These neural transformations  leave the adolescent brain more susceptible to potential neurotoxic effects of substances.Although overall brain volume remains largely unchanged after puberty, ongoing synaptic refinement and myelination results in reduced gray matter and increased white matter volume by late adolescence.Cortical gray matter follows an inverted U-shaped developmental course, with cortical volume peaking around ages 12–14.The mechanisms underlying the decline in cortical volume and thickness are suggested to involve pruning and elimination of weaker synaptic connections, decreases in neuropil, increases in intra-cortical myelination, or changes in the cellular organization of the cerebral cortex.In contrast, white matter development generally is characterized by linear volume increases driven by progressive axonal myelination.

These processes refine motor functioning, higher-order cognition, and cognitive control.Studies show alterations in white matter integrity in adolescent marijuana users compared to non-users, particularly in fronto-parietal circuitry and pathways connecting the frontal and temporal lobes.Altered cortical morphometry has also been observed in adolescent marijuana users, with marijuana-using adolescents having larger cerebellar volumes than non-users,thinner cortices in prefrontal and insular regions, and thicker cortices in posterior regions when compared to controls.Structural neuro imaging studies have also examined whether structural brain alterations were present before onset of marijuana use.Notably, orbitofrontal cortex  volumes at age 12 predicted initiation of marijuana use at age 16 when controlling for other substance use. Regional volume vulnerabilities may increase risk for initiation and maintenance of marijuana misuse. This study builds on previous work by our laboratory examining the acute and longer-term impact of adolescent marijuana use on cortical thickness pre- and post 28-days of monitored abstinence from marijuana.We found increased temporal lobe thickness estimates in adolescent heavy marijuana users,and negative associations with cortical thickness and lifetime marijuana use both acutely and following prolonged abstinence from marijuana. It is unclear if such structural alterations of the cerebral cortex persist into young adulthood. The aim of this prospective study was to identify differences in cortical thickness between adolescent heavy marijuana users and control adolescents with minimal substance use histories assessed at three independent time points.We hypothesized that those individuals who initiated heavy marijuana use during adolescence would show thicker cortices over time compared to our control teens by young adulthood in frontal and temporal brain regions.This study looked at cortical thickness estimates at three independent time points  in adolescent marijuana and alcohol users compared to controls with limited substance use histories. We found significant between group differences in cortical thickness estimates after controlling for lifetime alcohol use. MJ +ALC demonstrated increased cortical thickness estimates in all four lobes of the brain, bilaterally.

Notably, 18 of 23 regions in which differences were observed were in the frontal and parietal cortex. Positive dose-dependent associations were identified in temporal brain regions,container for growing weed as cumulative marijuana use from ages 16 to 22 was associated with thicker cortices in inferior temporal and entorhinal cortex. Several negative associations were observed with lifetime alcohol use, as more alcohol use reported was associated with thinner cortical estimates in all four lobes. It is important to detail how these findings compare to our previous work with a similar sample, as we found both similarities and differences from our cortical thickness study in which adolescent marijuana users were observed pre- and post 28-days of monitored abstinence.In Jacobus et al.,increased thickness estimates in our marijuana users  was found in the entorhinal cortex compared to matched controls. Similarly,the present study found increased thickness estimates in our user group compared to our controls, and findings were more widespread and noted in all four lobes of the brain. The present study also found more lifetime marijuana use was associated with increased thickness in the entorhinal cortex, a region rich in cannabinoid 1  receptors and important for learning and memory.However, dose-dependent bivariate correlations were different in that previously we saw increased marijuana use associated with thinner cortices and increased alcohol use associated with thicker cortical estimates at age 17, pre- and post monitored abstinence. Our dose-dependent associations in the present study suggest otherwise. We found increased lifetime marijuana use reported associated with thicker cortical estimates and increased lifetime alcohol use reported associated with thinner cortices.This may reflect several points recently discussed by Filbey and colleagues  in the literature, including methodological issues,the present study assessed substance independently over the course of three years compared to 28-days at age 17;  age and maturational bias, correlations in the present study reflect associations following many years of substance use and potential for interference with complex neuro developmental processes;  changes in marijuana and alcohol use patterns, as individuals in the present study remain relatively chronic in their marijuana use over time but subtly increase in their alcohol use; and  possible interactions with pre-existing vulnerabilities that are present at age 17,but likely changes as the individual continues to chronically use substances and increase in age.Lopez-Larson and colleagues cross-sectionally investigated cortical thickness in adolescents ages 16–19 years, with heavy marijuana use histories.

They found decreased thickness in frontal regions and the insula, along with increased thickness in lingual, temporal, and parietal regions. The present study found increases in thickness in parietal, temporal, and occipital cortices, consistent with work by this team. The mechanism by which marijuana may alter the neural architecture and plasticity of the brain is undetermined. The endocannabinoid system plays a role in neuromaturational processes and modulates neurotransmission for several neurotransmitter systems .Interference with this system due to marijuana, or tetrahydro cannabinol  administration, likely causes a cascade of neuronal events  that changes brain structure and function,and thereby neurocognitive processing,emotional regulation and reward processing,and propensity for psychiatric comorbidities and addiction.It is unclear how associations with marijuana use and cortical thickness remodeling may be unique compared to alterations in macrostructural volume.Studies suggest that volume changes are driven by changes in surface area  whereas others suggest thickness as one ages,however relationships between these metrics are likely dynamic across the lifespan and represent different neuromaturational mechanisms at different stages of life and disease. Changes in regional brain volume associated with marijuana use have varied, as some have observed decreased volume  and others have identified macrostructural volume increases in CB1-dense brain regions such as neocortex, amygdala, striatum, hippocampus, and cerebellum.In reward-network regions specifically, such as the orbitofrontal cortex,a recent examination by Filbey and colleauges, found decreased orbitofrontal cortex  volume in heavy marijuana users compared to controls, and increased structural and functional connectivity within the OFC network. Lorenzetti and collages,did not find OFC differences in their sample of heavy marijuana users, but did see smaller hippocampus and amygdala volumes. Cheetham et al.  found that smaller OFC volume pre-initiation of marijuana use  predicted progression into use four years later.Taken together, findings underscore that alterations in cortical metrics are likely dynamic and influenced by age, pre-existing vulnerabilities, and exogenous factors such as marijuana use. Continuing to study associations between cortical metrics and substance use is important given estimates have been linked to cognitive functioning in several studies in our laboratory and others .