Additionally, there was a trend for female participants to have lower net IGT scores than male participants . In the current study, the trend towards poorer net IGT performance in female relative to male participants appears to be driven by females tending to make more disadvantageous selections from deck B, where rewards are frequent and losses are infrequent, while at the same selecting fewer cards from advantageous deck C in which loss frequency is equal to gain frequency. Females may also be performing worse than males due to differences in the time needed to develop decision-making strategies towards advantageous choices. Male participants may be better at suppressing reward-driven behaviors due to activity in the right dorsolateral prefrontal cortex activity that has been shown in males but not females completing the IGT . A previous study that examined sex differences between young adult male MJ and female MJ users found that life timeMJ use was associated with poorer decision-making performance in male but not female participants . However, this study did not perform an interaction between group and sex on net IGT scores due to the absence of healthy controls. Thus, it is unknown whether similar findings would have also been seen if female and male non-MJ users had been included. The observed trend for sex differences on the IGT may also be attributed to the possible influence of sex hormones on executive functioning. A study examining the interactive effects of dopamine base levels and cycle phase on executive functions found that women were significantly faster on the Stroop during the luteal phase compared to menses and pre-ovulatory phases . This suggests women have improved verbal skills during the luteal phase when levels of progesterone and estradiol are high. Another study found that women ovulating were more likely to choose risky options than men . In the current study, females may have performed worse on the IGT because we may have unknowingly sampled a high percentage of women in a stage of their menstrual cycle where they are more likely to take risks.
However, since we did not ask female participants to report menstrual cycle stage at the time of the study visit, we are unable to confirm whether hormone levels may have influenced IGT performance. No differences were observed between MJ+ and HC mean reaction times during the IGT, cannabis hydroponic setup which is inconsistent with our initial hypothesis. To our knowledge, no studies in MJ users have examined mean reaction times on the IGT. While risky decision-making may be related to impulsivity, it may be important to utilize other neurocognitive measures that assess motor impulsivity and response inhibition. In a fMRI study investigating the relationship between MJ use and inhibitory control processing, MJ users tended to have faster reaction times than healthy controls . Additionally, brain activity differences were observed in the dorsal anterior cingulate cortex, a region of the brain thought to be involved in impulse control. In the present study, as mean reaction time was not significantly related to IGT performance, MJ+ took the same amount of time as HC to make decisions during card selection. This finding suggests that lower net IGT scores in MJ+ relative to HC may be related to maladaptive decisions that are not associated with motor impulsivity during card selection. Although age at first MJ use, 30 day MJ use and lifetime MJ use were not significantly related to IGT performance among MJ+, between group differences on the IGT suggests there may be potential differences between MJ+ and HC that could be related to pre-morbid vulnerability for risk-taking tendencies and/or the effects of substance use itself. Underlying differences in prefrontal cortex development between MJ+ and HC could explain some of these findings. For example, a previous study showed that early-onset frequent marijuana users had a thicker prefrontal cortex than late-onset frequent MJ users, which could indicate reductions in normative grey matter pruning in the prefrontal cortex in participants who begin using MJ at a younger age . While previous studies have found associations between early adolescent MJ use and impairments in executive functioning , we did not find a relationship between age at first MJ use and risky decision-making.
In the current study, we asked participants to report their age at first MJ use instead of age at regular MJ use, which may be more closely associated with patterns of MJ use that could predict neurotoxic consequences of use. Age at first use can be a difficult variable to assess, especially in young adults aged 18–22 years, since age at first MJ use may have occurred very recently in this population and thus, participants may have only had a year or two of substance use prior to the study visit.One limitation of the current study is the modest sample size. Although our sample was relatively well matched in the number of participants in each group, our findings may not be readily generalizable to young adult college students. Another related issue is the over representation of males in the MJ group. Although the prevalence of MJ use is higher in males than females , our findings may not be generalizable to female MJ users. Although onset of cannabis withdrawal symptoms typically occur in frequent MJ users after 24 h of abstinence, and peak 2–6 days post cannabis abstinence , we cannot confirm whether or not participants were in active withdrawal during the study visit. Future studies should administer the Marijuana Withdrawal Symptoms checklist to assess withdrawal symptoms in participants at the time of the study visit. In addition, the potency of MJ is not standard and our study design does not take into account dose-response associations in MJ+. Future studies will need to assess other indicators of MJ use, such as asking participants to report THC content of the MJ they typically use. Another limitation is that we utilized a laboratory task of decision making and provided participants with hypothetical earnings rather than tangible incentives. In future studies, it will be important to use other real-life decision-making measures to determine if our findings are specific to the IGT, are associated with non-monetary risk-taking behaviors, or are associated with decision-making in general. As we only used one task of decision-making, our findings may not generalize across a wide range of decision-making tasks. Future studies may want to utilize additional tasks to assess risky decision-making, such as the Balloon Analogue Risk Task or Cambridge Risk Task . Additionally, as most MJ users are also alcohol users, alcohol was not used as exclusionary criteria for MJ+. While post-hoc analyses suggested alcohol use was not related to IGT performance, we cannot rule out the possibility that the neurotoxic effects of alcohol may play a role in the observed group differences on decision-making performance.
In models examining the effects of both MJ use and alcohol use on net IGT scores, neither significantly predicted decision-making performance in MJ+, which may be due to lack of refined measure to assess frequency of these substances and premorbid characteristics that distinguish MJ+ from HC. Other studies that reported group differences on the IGT between MJ users and healthy controls either did not examine relationships between marijuana use variables and IGT performance , only examined other substance use variables in relation to IGT performance , or did not find associations between substance use variables and IGT performance . One study by Verdejo-Garcia et al. reported greater joints smoked/week was associated with lower net IGT scores in abstinent marijuana users, but did not examine other substance use characteristics in relation to IGT scores within the same model. We believe future studies should consider the relationship between MJ use and decision-making performance, while accounting for poly-substance use. Finally, while we observed a trend for MJ+ to report greater recent anxiety on the Beck Anxiety Inventory , compared with HC , the main effect of group remained significant when controlling for BAI scores in the ANCOVA models with and without sex included as a factor. As anxiety levels may affect decision-making, future studies should ascertain that anxiety levels in MJ users are not driving any observed decision-making differences between MJ users and healthy controls. In summary, the current study examined the effects of frequent MJ on risky decision-making in college-aged young adults. We found a main effect of group on net IGT scores, such that MJ+ had overall lower net IGT scores than HC. These findings may highlight differences in decision-making performance between young adult MJ+ and HC. Results from this study underscore the importance of interventions targeted at reducing risky decision-making in young adult MJ users. As our study is cross-sectional, further longitudinal research is needed to understand whether impairments in MJ users are related to the neurotoxic effects of MJ or if riskier decision-making may be present in MJusers prior to initiation of use, and whether these differences persist after abstinence.Lung disease remains a common comorbidity in persons living with HIV, despite the widespread use of combination antiretroviral therapy that has substantially reduced morbidity and mortality related to opportunistic lung infections. Previous studies in the U.S. have reported higher incidence of both infectious and non-infectious lung diseases in HIV-infected compared to uninfected populations. This increased prevalence is explained, in part, by more tobacco smoking among HIV+ individuals, while HIV disease-related factors including unsuppressed viral load and low CD4 T cell count may also contribute to higher rates of lung disease. The high prevalence of non-infectious obstructive lung disease is expected to continue to increase among HIV+ individuals in the U.S. and globally, yet the potential contributions of other risk factors remain poorly defined.
Smoked cannabis is a potential risk factor for lung disease, as it contains many of the same toxic constituents present in tobacco smoke. In the U.S., the proportion of HIV+ individuals who frequently smoke marijuana is higher than in the general population and has increased in recent years. Previous studies of HIV-uninfected populations reported an association between long-term marijuana smoking and increased respiratory symptoms, chronic bronchitis, and chronic obstructive pulmonary disease and emphysema,hydroponic system for cannabis while other studies reported no significant association between marijuana smoking and these diagnoses or other measures of lung health. Among HIV-infected individuals, few data exist regarding the association between marijuana smoking and respiratory burden, despite high prevalence of lung disease in HIV-infected populations and its associated mortality and morbidity. The aims of this study were to investigate the effects of marijuana smoking on infectious and non-infectious pulmonary diagnoses in HIV-infected individuals in the combination antiretroviral therapy era, and to compare its effects in HIV-infected vs. uninfected individuals with similar demographic characteristics using data from a large prospective cohort of men who have sex with men .Participants were asked if, since their most recent visit, they were newly diagnosed with viral pneumonia, bacterial pneumonia, other pneumonia, or tuberculosis, or if newly diagnosed with or experienced recurring chronic bronchitis. These data were merged with additional variables provided as International Classification of Disease Codes, version 9 or version 10 as follows: influenza or viral pneumonia , bacterial pneumonia , other pneumonia , acute bronchitis , tuberculosis , chronic obstructive pulmonary disease or emphysema , pulmonary hypertension , other non-infectious diagnoses , pulmonary pneumopathy, and other lung disease, not otherwise-specified . Lung cancers were determined from cancer registry linkage data site codes 34.0–34.9, death registry data , and self-report .Chronic bronchitis was defined as the first of multiple bronchitis diagnoses or ICD codes 490–491. HIV serostatus, and CD4+ T lymphocyte count and viral load for HIV + participants, were obtained as previously described. Education level and race at study entry, ART use, and alcohol use were obtained from self-report. Missing time-varying data were imputed by carrying forward values from nearest available previous visit, and by multiple imputation in validation analyses using predictive mean matching with the R mice package .Cross-sectional analyses of baseline characteristics and prevalence of pulmonary diagnoses were stratified by HIV serostatus and marijuana smoking, and HIV serostatus, marijuana, and tobacco smoking, respectively. Marijuana smokers were defined as participants reporting ≥1 year of daily or weekly use in follow-up; tobacco smokers were participants reporting any tobacco smoking in follow-up. Cox proportional hazard models were used to assess the association between marijuana smoking and first incident infectious pulmonary diagnosis, and chronic bronchitis, which comprised the majority of noninfectious diagnoses.