Cannabis Grow

Outcomes of such practices and variations between trauma registries leads to a lack of confidence regarding data accuracy and resulting analyses. Motor impairment and/or execution of complex behavioral sequences often accompany psychotic symptoms, as in the case of obsessive-compulsive disorders. Such an occurrence likely reflects the anatomical overlapping of brain areas serving both motor and cognitive functions.Cannabimimetic drugs represent an interesting tool to investigate psychomotor behaviors, because of their documented ability to influence both motor and cognitive performances . Indeed, cannabinoid administration is accompanied by profound effects on motor behaviors, as well as by attenuation of d-amphetamine-induced hyperactivity and stereotypy. In addition, cannabinoid substances produce a large spectrum of psychotropic effects in humans, ranging from euphoria, short-term memory impairment, altered perception of space and time, and dream states. Similarities between certain cognitive impairments occurring in psychoses and the pharmacological effects of D 9 -tetrahydrocannabinol, the active principle in marijuana and hashish, have also been documented. The discovery of the brain cannabinoid receptor, CB1, and the mapping of its neuroanatomical distribution, have greatly improved our understanding of the effects of cannabimimetic drugs on psychomotor functions. CB1 receptors are most concentrated in areas of the central nervous system that are critical for the regulation and processing of motor functions, cognition,stacking pots and motivation. In keeping with this distribution, disruption of the CB1 receptor gene has been shown to severely impair movement control and to result in a functional reorganization of the basal ganglia.

The pharmacological properties of cannabis-derived drugs have prompted clinical evaluations of marijuana use in motor disturbances, such as spasticity, tremor, and dystonias . At the same time, the discovery of naturally occurring ligands of cannabinoid receptors, and the identification of their pathways of biosynthesis and inactivation, have opened a new research field aimed at investigating the physiological role of these molecules in health and disease, as well as their possible use as a new target for therapeutic interventions. The purpose of this mini-review is to draw together these studies, pointing out to the potential involvement of the endogenous cannabinoid system in psychomotor disorders.The cloning of the CB1 cannabinoid receptor and the mapping of its distribution in the brain has impelled the search for the corresponding naturally occurring ligands within the brain. Two endogenous cannabimimetic substances have been identified so far, arachidonylethanolamide and 2-arachidonylglycerol. Unlike neurotransmitters that are released from synaptic terminals via vesicle secretion, both anandamide and 2-AG are thought to be produced upon demand through stimulus-dependent cleavage of two distinct phospholipid precursors present in neuronal membranes . Anandamide, but not 2-AG, is released extracellularly by neural activity evoked by localized pulses of high K1, and it is thought to act near its sites of production as a local neuromodulator. Whether 2-AG is produced in vivo under physiological circumstances and/or it exits neurons in other regions of the CNS, has not been determined yet. The biological actions of anandamide are terminated by two subsequent reactions consisting of high-affinity transport into cell, followed by hydrolysis catalyzed by an amidohydrolase enzyme. 2-AG is thought to be inactivated by cleavage into glyceroland arachidonic acid. The enzyme activity involved in this reaction has not been clearly identified, though anandamide amidohydrolase and monoacylglycerol lipase have been suggested to play a role. Other saturated and monounsaturated fatty acylethanolamides are produced by activated neurons together with anandamide.

Although these lipids share a common biosynthetic mechanism with anandamide, they do not bind to cannabinoid receptors and they are not released extracellularly in vivo. The possible physiological roles of these compounds are still largely unexplored. One exception is represented by palmitylethanolamide which was shown to exert peripheral anti-inflammatory and antinociceptive effects, mediated through a putative CB2-like cannabinoid receptor .The basal ganglia are a forebrain region playing a key role in sensorimotor and motivational aspects of behavior. The high density of CB1 receptors in this area indicates that cannabinoid substances may modulate essential aspects of basal ganglia physiology. The existence of an endogenous cannabinergic tone in the basal ganglia has been suggested by the finding that the CB1 receptor antagonist SR141716 was able to produce increased locomotion in mice and stereotypies in rats. These findings have been recently confirmed by in vivo microdialysis studies, showing that membrane depolarization stimulates the outflow of anandamide from striatal neurons. Functional interactions between endogenous cannabinoids and distinct neurotransmitter systems modulating basal ganglia functions have been also postulated. Neuroanatomical studies have shown that CB1 receptors are mainly located in the terminals of GABA-ergic medium-spiny neurons projecting from the striatum to the globus pallidum and substantia nigra. Although direct evidence for an interaction between endogenous cannabinoids and GABA-ergic system is still lacking, it is known that exogenously administered cannabinoids can modulate GABA transmission, as suggested by their ability to inhibit GABA release from striatal and hippocampal nerve terminals and potentiate GABA-induced catalepsy. Coexpression of m -opioid and CB1 receptors in striatal cells indicates that opioids and endocannabinoids can also interact within the striatum. In keeping with this, chronic cannabinoid exposure regulates proenkephalin mRNA levels in the rat striatum. Finally, a role for the cannabinoid system as a modulator of dopaminergic activity in basal ganglia is emerging.

Activation of cannabinoid receptors was shown to cause significant reductions of the electrically evoked dopamine release from rat striatal slices, and to potentiate neuroleptic-induced catalepsy. Moreover, injection of cannabinoid receptor agonists into the basal ganglia counteracts the motor responses of locally administered D2-receptor agonists. Conversely, cannabinoid-mediated motor behaviors can be affected by dopamine manipulations. For example, chronic administration of dopamine D1 and D2 receptor agonists results in differential modulation of the locomotor effects of the cannabinoid agonist HU-210, suggesting a possible cross-talk between dopaminergic and cannabinergic systems within the striatum. In this regard, the observation that anandamiderelease can be induced by pharmacological activation of the D2 class of dopamine receptors in freely moving animals suggests that endogenous cannabinoids may represent a primary component of the network of neurochemicals modulating striatal function. Further support to this hypothesis is provided by behavioral studies showing that the hyperactivity associated with post-synaptic D2 receptor activation is markedly potentiated by the CB1 antagonist SR141716A. Taken together, these data suggest that pharmacological blockade of cannabinoid receptors enhances quinpirole-induced motor activation by removing the inhibitory control exerted by the endogenously released anandamide. Furthermore, the lack of effect of SR141716A when given alone at the same dose used to potentiate quinpirole-induced motor activation, indicate that anandamide can reach a sufficient concentration to induce its behavioral effects only after stimulation of D2 receptors. Thus, the released anandamide may offset dopamine D2-induced facilitation of psychomotor activity . Functional interactions between endogenous cannabinoids and dopaminergic system may have important therapeutic implications in pathologies that involve disregulated dopamine neurotransmission, such as Parkinson’s disease, Tourette syndrome,grow lights and schizophrenia. On a speculative basis, the blockade of anandamide inactivation and the consequent increase of endogenous levels of this lipid, may be beneficial in reducing hyperactivity and hyperkinesia associated with Huntington’s disease, a pathology where a massive loss of CB1 receptor binding has been reported in the basal ganglia of postmortem patients. However, the potential therapeutic use of cannabinoids for the treatment of psychomotor disorders is not only matter of speculation. It has been shown that blockade of CB1 receptors may potentiate or prolong the effects of dopamine-based therapies currently used in Parkinson’s disease and use of D 9 -THC for the treatment of Tourette syndrome has been reported. Increasing evidence suggests that schizophrenia may be associated with abnormalities in the function of the endogenous cannabinoid system. Clinical evidence indicates that cannabis consumption is significantly higher in schizophrenic patients than normal individuals and chronic use of high doses of cannabinergic substances may precipitate schizophrenic symptoms in vulnerable patients. Additional support for a role of cannabinoid signaling in schizophrenia comes from the observation that anandamide is markedly elevated in the cerebrospinal fluid of schizophrenic individuals. The non-cannabinoid acylethanolamide PEA is also increased in these patients. Although PEA is produced in the CNS through a biosynthetic mechanism similar to anandamide’s, this lipid is not released in vivo as a consequence of D2-receptor stimulation. Therefore, further investigations are needed to clarify the physiological role of PEA in the CNS as well as its possible link to schizophrenia. Drugs that block D2-like dopamine receptors have been extensively used to mitigate symptoms of psychoses and motor disorders.

Given the linkage between D2-receptor activation and anandamide release, it is likely that the high CSF levels of this lipid may reflect homeostatic adaptations of the endogenous cannabinoid system to disturbances in dopamine neurotransmission occurring in schizophrenia. Additional support for this possibility comes from the observation that chronic treatment with D2-family antagonists results in upregulated expression of CB1 receptor mRNA in striatum. On the other hand, alterations in cannabinoid signaling may directly contribute to the manifestation of subgroups of symptoms in schizophrenic syndromes. Further investigations in larger populations of patients and studies aimed at determining the neuronal origin of the AEs in CSF may help elucidate the possible participation of these lipids in the pathogenesis of schizophrenia.Successful viral suppression from combination antiretroviral therapy has led to an increase in life expectancy among persons living with HIV . While severe HIVassociated neurocognitive disorder is less prevalent in the cART era, mild to moderate HAND persists despite virologic suppression. HAND affects up to 50% of HIV-positive persons, with older HIV-positive adults at greater risk for neurocognitive impairment than their younger counterparts.Among neurocognitive domains affected by HAND, complex motor skills are consistently compromised across time. Complex motor skills refer to a combination of cognitive and perceptual-motor abilities, including perception, planning, continuous tracking, and sequential movements.Although the prevalence of complex motor impairment has receded in comparison to the pre-cART era, deficits in complex motor functioning are still observed in approximately 30% of those with HAND. Complex motor impairment is related to everyday functioning impairment, including driving ability, highlighting the clinical relevance in understanding mechanistic pathways underlying HIV-associated motor dysfunction. A recent longitudinal study found that complex motor function is particularly vulnerable to the effects of age and stage of HIV infection, and implicated the basal ganglia as a neural correlate of interest.The effects of acute HIV infection on the basal ganglia are well documented, with greater atrophy associated with psychomotor slowing.Inflammatory processes are one putative factor that may contribute to central nervous system injury, including deficits in complex motor skills. Biomarkers of inflammation, such as cytokines and monocytes, are elevated in the context of HIV infection. HIV, viral products, and activated immune cells are able to cross the blood brain barrier and contribute to inflammation in the CNS. Neuroimaging studies have shown that peripheral inflammatory biomarkers are able to alter neural activity in the basal ganglia, including dopaminergic activity, which is reflected by psychomotor slowing in HIV-negative adults. Among HIV-positivepersons, global neurocognitive impairment is associated with elevation of various peripheral biomarkers of inflammation and coagulation . Taken together, deficits in complex motor performance are commonly observed among HIV-positive persons, and elevation in peripheral biomarkers of inflammation may be a contributing factor. Thus, we hypothesize that HIV will have negative direct and indirect effects via inflammation on complex motor performance.Participants were 90 HIV-positive and 94 HIV-negative persons, with balanced recruiting in each age decade , from the five-year Multi-Dimensional Successful Aging among HIV-Infected Adults study conducted at the University of California, San Diego .Only baseline data were included in this analysis. The study received approval from the UCSD Institutional Review Board. Participants provided written, informed consent. Exclusion criteria for the parent study were diagnosis of a psychotic disorder and presence of a neurological condition known to impact cognitive functioning . Additional exclusion criteria for current analyses included being off ART, having detectable HIV viral load , and meeting criteria for a current substance use disorder. HIV infection was screened via a finger stick test and confirmed with an Abbott Real Time HIV-1 test or by submitting specimens to a Clinical Laboratory Improvement Amendments -certified laboratory for HIV-1 viral load quantitation. Although neurologic findings commonly associated with HIV infection have been suggested to largely remit with initiation of cART, our cross-sectional study observed worse complex motor skills across the adult age continuum of HIV-positive, relative to HIV-negative, adults. Inflammation burden was higher among HIV-positive adults, compared to the HIV negative comparison group.

Study methods employed by each of the eight included studies varied with some studies utilizing medical chart reviews, while others utilized validated surveys and questionnaires to gather their data. The studies by Andelic et al., Barker et al., and Bombardier et al. all utilized the participants’ medical charts for retrospective review for presence of substances. The studies by Andelic et al., Nguyen et al., and O’Phelan et al. used trauma registry databases to collect data on TBI patients and the presence of substance abuse. Pakula et al. collected data on the presence of substance abuse in post-mortem patients with traumatic cranial injuries by evaluating autopsy reports. Finally, the studies by Bombardier et al., Kolakowsky-Hayner et al., and Kreutzer, Witol and Marwitz utilized questionnaires to interview participants. The variance in study methods, ranging from retrospective review of charts to the use of self-report methodology subjects the included studies to recall bias and unreliable data. A factor negatively contributing to the quality of the included studies is the variance in defining a TBI. Three of the studies did not provide a definition for what constitutes a TBI, nor did they describe the severity of TBI. The study by Andelic et al. defined TBI using the TBI Modified Marshall Classification. The study by Barker et al. defined TBI using the TBI Model Systems Data Base definition. Nguyen et al. used the International Classification of Diseases-Ninth Revision codes and the Abbreviated Injury Severity codes to define TBI. These codes are widely used in trauma data registries for entering and recording the injury type and severity,garden racks wholesale for performance improvement and billing purposes. However, reliability can be an issue as coding may be subjective. The information is extracted from the chart by registrars who read and enter notes written by physicians.

Often, coding depends on physician documentation, attention by trauma registrars to the various sources of documentation and communicating with physicians when necessary. If not subject to continuous data validation, a data gap may ensue. The study by Pakula et al. defined a central nervous system injury by the presence of any of the following written diagnosis as found in the autopsy reports: 1) TBI, 2) skull base fracture, 3) spinal cord injury, and 4) cervical spine injury. Only one study, the study by O’Phelan utilized a Glasgow Coma Score to define a severe TBI. Risk of bias in terms of selection and information was determined for each study. The majority of the articles were subject to selection bias in terms of their participant population and methods of data collection: See table 2 for specifics. The included studies varied in their definition of TBI. One study used the Modified Marshall Classification of TBI which is a Computed Tomography scan derived metric used to grade acute TBI on the basis of CT findings. Another study defined TBI using the TBI Model Systems National Database definition. The TBIMS-NDB has been funded by the National Institute on Disability and Rehabilitation Research in the U.S. Department of Education to study the course of recovery and outcomes following a TBI. They describe the TBIMS-NDB TBI as: Damage to brain tissue caused by an external mechanical force as evidence by medically documented loss of consciousness or post-traumatic amnesia , or by objective neurological findings on physical or mental examination that can be reasonably attributed to TBI. Three of the eight studies did not specify how TBI was defined. The procedures by which the presence of marijuana exposure was detected varied across the selected studies. In some of the studies, marijuana was detected via a positive urine drug screen or via blood alcohol levels. In addition to utilizing toxicology screening results to identify the presence of marijuana, the studies by Andelic et al., Kolakowsky-Hayner et al., and Kreutzer et al. also utilized the General Health and History Questionnaire to gather self-reported patient incidence or marijuana exposure. As described earlier, the GHHQ questionnaire aims at assessing the psychosocial, neuro behavioral and vocational status of patients with traumatic injuries. Although all eight studies investigated marijuana exposure in TBI patients, only one study specifically investigated the use of marijuana alone on outcomes in TBI.

All other remaining studies investigated the presence of all possible substances and/or drugs, meaning investigators were not specifically examining marijuana exposure by itself. In Nguyen et al. all patients who had sustained a TBI and had a urine toxicology screen were included. The actual noted presence of marijuana was obtained from the urine toxicology screen and not through any other modes of measurement. The authors classified study patients according to marijuana screen results which they defined as greater than 50 ng/ml. Though marijuana was noted to have been detected across all eight studies, the actual numerical or absolute value measured was never reported by any of the studies. Additionally, it is important to note that excluding the study by Nguyen et al., the presence of marijuana was not reported in a quantifiable manner, making any potential statistical inference impossible. Lastly, six of the included studies investigated the presence of marijuana at the time of injury, while the remaining two studies measured the presence of marijuana use during the past year and post-mortem respectively. The study by O’Phelan et al. did not investigate any other time frame for which marijuana may have been used, rather, the authors only collected data on the presence of drugs at the time of injury. An important finding from the systematic literature review showed that marijuana was the most favored drug reported. However, only one study of the eight studies included explicitly searched for and found a connection between the presence of a positive toxicology screen for marijuana and mortality outcomes in TBI patients. Nguyen et al. three-year retrospective review of trauma registry data found that 18.4 percent of all cases meeting inclusion criteria had a positive marijuana screen and overall mortality was 9.9 percent . Nguyen et al. found that mortality in the marijuana positive group was significantly lower when compared to the marijuana negative group . Authors adjusted for the following differences between study participants: age, gender, ethnicity, alcohol, abbreviated injury scores, injury severity scores, and mechanism of injury. After adjusting for differences, Nguyen et al. found that a positive marijuana screen was an independent predictor of survival in TBI patients .This review sought to determine the use of marijuana and its role in TBI prevalence and outcomes.

A key finding from this review is that there are few studies available that examine the specific role of marijuana exposure on TBI severity, leaving many questions unanswered. Furthermore, this review found that there is a significant variation in how substance abuse has been defined, conceptualized, and operationalized in TBI research. Another important finding was that the reviewed studies operationalized substance abuse inconsistently, often combining alcohol and drugs in one category titled ‘substance abuse,’ making it difficult to ascertain if there was an association between specific drugs, particularly marijuana,hydroponic racks and TBI severity and outcomes. The difference in how substance abuse was operationalized in these reviewed studies has important implications for how findings are interpreted as well as provide recommendations for future research. Although there was no restriction made to the countries in which these studies were conducted, those meeting inclusion criteria were all studies conducted in the US except one from Norway. Therefore, the applicability of findings from that one non American study is limited. Additionally, it is difficult to draw valid and reliable conclusions when the studies reviewed utilized a wide variety of study objectives, sample size, study methods, and varying definitions for substance abuse classification. The review showed a great variation existed across the studies in types of data collected and methods used, thus severely minimizing comparability. For example, the disparity in measurement of blood alcohol levels considerably reduce the reliability of data related to pre-injury intoxication. In the reviewed studies, information on alcohol and substance use was obtained from a range of different sources, including self-reports and patient records, as well as a variety of different measures rendering results unreliable across studies. This review set out to answer a specific question: what influence, if any, does marijuana exposure at time of injury have on TBI severity and outcomes? Only one study about marijuana’s effect on TBI outcomes was available. Nguyen et al. reported that a positive marijuana screen is an independent predictor of survival, suggesting a potential neuroprotective effect of cannabinoids in TBI. The rest of the studies yielded a variety of findings, with the most common finding being that marijuana and other drug use, including alcohol, are common before TBI. To clearly understand what marijuana’s influence on TBI is, potential confounding variables must be identified and controlled for.

The literature review identified no consensus on relevant confounding variables aside from age and gender. The variability in all other demographic variables highlights the lack of certainty of the full range of relevant demographic variables. Another potentially important confounding variable is mechanism of injury. Historically, the most frequent cause of TBI related deaths in civilians was considered motor vehicle crashes. However, recent data show that falls are actually the leading cause of TBI related hospitalizations, with the second leading cause is being struck by another object. Importantly, only six of the studies included mechanism of injury as a variable in their analysis of findings. Five of the eight included studies did not address TBI severity as a variable.Andelic et al. used the Marshall classification to classify neurological anatomical abnormalities as seen on CT scans. Nguyen et al. utilized the Abbreviated Injury Scale score for the head and neck region to classify TBI severity. The use of the AIS score is common in general research studies as often times the GCS score is not always recorded for each individual participant. Hence the only study showing a link between marijuana exposure and TBI severity did not use the gold standard of GCS to measure TBI specific severity. Finally, severity as a variable in the TBI population is an important characteristic and is a parameter of interest when answering the research question of whether or not marijuana influences TBI severity; available studies are not able to answer that question mostly because the majority of them did not measure severity in the first place. Severity is important because it provides a level of specificity about the injury which determines management of care. Additionally, TBI severity can yield valuable insight about proximal and distal outcomes. It seems reasonable that it would be an important measure to include when examining the relationship between TBI and all included variables. Additional tools, such as the AIS scores and imaging studies, may be necessary in accurately capturing TBI severity in study participants; these studies, in addition to GCS, should be considered an essential variable that must be accounted for. All of the studies measured presence of marijuana, yet the methods by which marijuana was measured varied. For example, urine was the most common way to measure marijuana concentration in patients in reviewed studies, but urine tests results are not specific to time of injury: The detectable level of marijuana can be present in urine for approximately 4.6 to 15.4 days after last use for infrequent and chronic users respectively. The presence of marijuana on a urine toxicology screen may not accurately reflect or correlate marijuana levels in an individual’s system at time of injury, rather, it reflects recent use. Therefore, when considered as a variable, a marijuana level should be considered as reflective of recent use at time of injury, not directly at time of injury. Finally, this review and other systemic reviews consistently identify blood alcohol concentration as an important potential confounder in TBI studies. All reviewed studies except included alcohol as one of the examined substances. Much has been studied about the relationship between alcohol and TBI. As a prominent pre-disposing factor in TBI, the implications alcohol intoxication has on TBI is important and must be accounted for when examining the effects of marijuana on TBI. The current systematic literature review has several limitations, the first of which was the inability to perform a meta-analysis with the studies acquired. There was heterogeneity across the studies addressing marijuana exposure and TBI; from different criteria used to classify TBI, to diverse populations of interest, to varied outcomes of measures, the studies varied widely preventing a meta-analysis of the 8 included studies.

There is a need to understand the nature of social support that is associated with an increased risk of arrest in order to interrupt this cycle, either by encouraging social networks with positive outcomes or by disrupting cycles of arrests. In this study, Black race was not associated with incarceration, although it is well established that Black Americans are disproportionately incarcerated due to structural racism.Black Americans are significantly more likely to become homeless due to structural racism so there may be lower rates of individual risk factors for incarceration .Thus, non-Black participants may have individual risk factors that elevated their risk of incarceration in a way that we did not account for.As continued homelessness is associated with incarceration, it is possible that rehousing older adults experiencing homelessness could reduce this risk. A recent randomized controlled trial of permanent supportive housing for chronically homeless adults did not find a reduction in jail use. This may have been explained by police having an increased ability to serve outstanding warrants to people upon rehousing.Given the high rates of substance use, expansion of substance use treatment programs might reduce older homeless adults’risk of incarceration. Among all variables that we tested,grow rack parole and probation had the highest hazard ratio. Recidivism may be driven by technical violations of probation or parole rather than new criminal offenses. There are movements to reform probation and parole because they may perpetuate incarceration.

Reform efforts include shortening supervision sentences, reducing conditions and cost, limiting incarceration for violations, and providing specialty community supervision programs which use probation officers with health-focused expertise who incorporate a treatment-oriented approach in collaboration with community resources.Future areas for research include whether reducing or tailoring supervision programs to the needs and risk factors of older homeless adults decreases recidivism. Another innovation is specialty courts , which emphasize connection to treatment, though there is mixed data on their impact on incarceration and recidivism.Subjects for these analyses were 397 men who completed baseline evaluations and all follow-ups from approximate ages 20 to 50 in the San Diego Prospective Study . These men represent 90.0% of 442 individuals who entered the study, were alive at the age 50 follow-up, and participated in all evaluations at 10 , 15 , 20 , 25 , and 30 years. At T1, these subjects responded to mailed questionnaires distributed annually between 1978 and 1988 to new groups of 18-to- 25-year-old Caucasian students and nonacademic staff at the University of California, San Diego, selecting those who indicated they had experience with alcohol but never developed an AUD or SUD. For the approximately 60% who responded, additional exclusion criteria included bipolar disorder, schizophrenia, or the report of physical problems that precluded alcohol challenges. The original protocol was limited to males to optimize the rate of expression of AUDs over time, and to Caucasians because few African-Americans attended UCSD and 40% of Asians had alcohol-related flushing that could affect their LR measures. The requirement that probands did not have an SUD or AUD excluded individuals with early onset substance-related disorders that often reflflect preexisting severe conduct or antisocial problems . Individuals were selected as matched pairs of sons of alcohol-dependent fathers and FH-negative controls who were similar on demography as well as alcohol and drug use histories. By T1, 64% of these probands had some experience with illicit substances.

Baseline data were gathered using a variation of the Renard Diagnostic Interview, and at follow-up using questions from the Semi-Structured Assessment for the Genetics of Alcoholism interview . The latter has 1-week retest reliabilities for SUDs and AUDs of approximately 0.75 . Follow-up information was gathered from subjects and resource persons who gave information using an interview similar to the probands, with the higher figure for an item from either informant used if the 2 sources disagreed. Follow-up data included the prior 5- year interval use of alcohol, illicit drugs, and cigarettes, as well as personal and FHs of DSM-IV substance-related and independent major depressive and anxiety disorders . The Family History Assessment Module was used to gather information regarding lifetime AUDs and SUDs in the proband’s biological parents . As described in detail elsewhere, baseline LRs for probands were determined through alcohol-related changes in subjective feelings of intoxication, standing steadiness, and hormones at breath alcohol concentrations of approximately 60 mg/dl, as measured by an Intoximeter . Across multiple sessions, all subjects consumed 0.75 ml of alcohol or placebo and were evaluated over 3 hours as their blood alcohol concentrations rose, peaked and decreased to close to zero. Z-scores were used to combine data into 1 overall LR score where lower values reflected lower LRs per drink. At T15, probands completed the Self-Report of the Effects of Alcohol questionnaire regarding the number of drinks required for effects during 3 life epochs . SRE5 and total scores incorporating all 3 epochs were generated by summing the number of drinks required for up to 4 effects , and dividing that by the number of the effects reported . Thus, higher SRE scores indicate more drinks needed for effects, or a lower LR per drink. The SRE Cronbach’s a is >0.90, with retest reliabilities of 0.8. Externalizing characteristics were first evaluated at T10 and T15 using the novelty seeking from the Tridimensional Personality Questionnaire, Sensation Seeking from the Zuckerman Questionnaire, and Impulsivity from the Karolinska Personality Questionnaire.

To evaluate the hypotheses, emphasis was placed on LR, externalizing characteristics and internalizing items along with the demographic and alcohol/drug variables likely to predict future alcohol and substance difficulties. Most analyses focused on 4 proband groups regarding substance-related diagnoses over the 30 years: men who developed both SUDs and AUDs over the follow-up ; those with follow-up SUDs only ; subjects who developed AUDs only ; and individuals developing neither diagnosis during the 3 decades . Comparisons regarding Hypotheses 2 to 4 used analysis of variance or chi-square across all 4 groups, with an emphasis on LR, externalizing, and internalizing characteristics along with demographic and earlier alcohol and drug use items. Significant differences were followed with a planned comparison to evaluate if the groups with AUD and/or SUD diagnoses differed from Group 4 with no diagnosis to identify relevant items to test regarding association with Groups 1, 2, and 3 separately. Those significant items were then entered into a series of backward elimination logistic regressions to evaluate if LR, externalizing, and/or internalizing items were still significantly related to each of the 3 groups with diagnoses when considered in the context of other significant items. Comparisons regarding Hypothesis 5 were limited to Groups 1 to 3 who had relevant diagnoses, where an overall significant difference across groups was followed by planned comparisons of how Groups 2 and 3 differed from the combined diagnosis Group 1. For all evaluations, missing data were handled through a maximum likelihood procedure , including 6.8% who needed correction for 1 item and 0.8% for 2 items.As demonstrated by the distribution of the 4 groups in Table 1, over the 30 years, 41.3% of the 397 men met criteria for an AUD,microgreens shelving while 20.6% fulfilled criteria for an SUD. The SUDs included 51.2% of the 397 men with a cannabis use disorder only, 25.6% with an amphetamine and/or cocaine diagnosis only, 14.6% with combined cannabis and stimulant diagnoses, and 8.5% with an SUD related to cannabis or stimulants combined with other drug conditions. Consistent with Hypothesis 1 , in this prospective study of men at high risk of AUDs, the rate of a second substance-related diagnosis was almost 2-fold higher among individuals who had either SUDs or AUDs. Thus, 62 of the 164 probands with an AUD in Groups 1 plus 3 also had an SUD, and 62 of the 82 men with an SUD in Groups 1 plus 2 also had an AUD. The 4 groups of subjects in Table 1 differed on a broad range of early life characteristics. The results indicated significant differences for earlier life LR and externalizing characteristics, but not for having seen a mental health worker or reporting depressive syndromes . There were also differences for several demographic, alcohol, and drug use items. All significant alcohol, drug, and externalizing items in that table also differentiated between the combined Groups 1 through 3 versus the no diagnosis Group 4. In Table 2, further analyses were then carried out to more directly evaluate how items from Table 1 that were significantly different across the combined Groups 1 to 3 versus Group 4 performed when each of Groups 1, 2, and 3 was evaluated for differences from Group 4.

This approach used a series of backward elimination logistic regressions to identify the odds ratios for optimal combinations of items for each group that best differentiated it from the no diagnosis Group 4. In Table 2, the regression predicting Group 3 from among Group 3 plus the no diagnosis Group 4 identified 6 items including: a lower LR per drink; a higher score on an externalizing questionnaire; 2 alcohol use characteristics; 1 drug use item; and lower T1 education. Five of these 6 items also related to the combined diagnosis Group 1 compared with Group 4, with the sixth characteristic similar to Group 3 in that it involved an externalizing questionnaire score. The regression relating to Group 2 from among Groups 2 plus 4 had contributions from 3 items: a higher score on an externalizing questionnaire, 1 alcohol, and 1 drug item . All 3types of items also related to Group 1 membership, but with a different externalizing questionnaire score. Thus, 5 of the 8 items that contributed to the regression for Group 1 versus Group 4, also related to Group 2 and/or Group 3, with 1 of the additional items relating to an externalizing score from a different questionnaire. Similar results for these 3 regressions were seen if hierarchical logistic regressions were used focusing on blocks of demographic items, alcohol, and drug use items, and then LR and externalizing items, with the exception that the equation relating to the block of externalizing characteristics and LR regarding the small Group 2 was a trend . In summary regarding Hypotheses 2 to 4 , externalizing characteristics related to all 3 diagnostic groups, while LR related only to groups with later AUDs. Overall, the characteristics that related to AUDs alone combined with those that best identified subjects with SUDs alone were associated with the combined diagnoses in Group 1, with few predictors that were uniquely related to Group 1. Table 3 addresses Hypothesis 5 . Here, planned comparisons were used because some items were only relevant to groups with AUDs and some were only appropriate for probands with SUDs. Beginning with demography, the only overall significant difference across the 3 groups at age 50 was the higher proportion of individuals in Group 3 who had ever been married, a finding that reflected higher proportions in Group 3 versus the comorbid diagnosis Group 1. The course of alcohol-related items for the 2 AUD groups indicated that members of the combined diagnosis Group 1 endorsed more AUD items, an earlier AUD onset, a higher risk of alcohol-induced mood disorders, and a greater proportion who received formal AUD treatment or who attended Alcoholics Anonymous meetings compared with Group 3. The drug-related items for the 2 SUD groups indicated that members of Group 1 were more likely to use tobacco and reported a higher number of SUD items. Mental health histories over the 30 years were generally similar across the 3 groups, except for a greater probability of having seen a mental health worker for the combined diagnosis Group 1 compared with the AUD diagnostic Group 3. The demographic and alcohol-related characteristics in Table 3 that differentiated between the AUD Groups 1 and 3 were likely to be correlated, so these 6 items were entered into a backward elimination logistic regression analysis to determine which variables remained significantly related to a combined AUD plus SUD outcome among individuals in Groups 1 plus 3. The results demonstrated significant ORs for Group 1 membership for the number of AUD items endorsed , an alcohol induced mood diagnosis , and having received formal AUD treatment . The 2 drug-related items and the SRET score that differentiated between Group 1 and Group 2 in Table 3 were entered into a logistic regression predicting Group 1 membership from among Groups 1 plus 2, with only the SRET contributing significantly .

The overall case-control effect size that we observed, 0.62, was somewhat lower than that reported in meta-analyses . Since the patient sample was older than the control sample and age significantly affected P300, the patient control difference was attenuated somewhat by inclusion of age as a covariate. The effect size was almost certainly also lowered by our conservative data strategy, which likely excluded a number of subjects – primarily patients – with negligible but real P300 responses. This moderately large effect is, nevertheless, well within the expected distribution of published studies. Although we observed a significant difference across test sites, this did not reflect differences in data quality, methodology, or experimental rigor. Rather it reflected differences in the stratification of the samples across sites, as this relates to clinical and socio-demographic confounds or modifiers. In patients, site differences were entirely explained by differences in the level of positive symptomatology. Although the P300 deficit is traditionally thought of as being immune to changes in patients’ clinical status , it should probably be considered as more of a relatively stable deficit. It clearly does not normalize with treatment, even when symptoms dramatically improve. However, it still exhibits modulation over time in association with positive symptoms . Indeed, it is this ability to reflect increasing positive symptomatology that underlies the emerging utility of P300 as a predictive biomarker for imminent prodromal conversion to psychosis . Except for MMSE and UPSA-B,growing indoor cannabis global indices of cognitive ability and real-world functional capacity, no other clinical measures were associated with P300, indicating that the association with positive symptoms is relatively specific.

Since these patients were all clinically stable outpatients on stable medication regiments, differences in positive symptomatology presumably reflected relatively stable trait-like differences on this dimension of illness severity. P300 may therefore be an endophenotype that is especially informative regarding the genetic basis of positive symptoms. The associations with MMSE and UPSA-B highlight the utility of the P300 as a sensitive physiological index of differences in brain function, even within a relatively homogeneous clinical sample. The magnitude of the P300 response has long been considered a broad indicator of “cognitive fitness” and, more specifically, of the ability to appropriately process and respond to task-salient environmental inputs — i.e., to correctly detect a signal within noise. It is thought to require intact attentional and working memory capacities , and to reflect complex neural processes of temporal and spatial integration across multiple brain regions . It is not surprising, therefore, that the P300 would correlate with other measures of cognitive and functional capacity. A similar association between P300 amplitude and MMSE has been reported previously in chronic Alzheimer’s disease patients and, acutely, in uremic patients undergoing dialysis , where the two measures showed a correlated improvement, as well, following treatment. There have been no prior studies reporting a relationship between P300 and specific measures of functional capacity, including UPSA-B, either in schizophrenia patients or other clinical samples. However, this association is entirely consistent with the relationship between P300 and cognition. Prior studies examining the relationship between neurocognitive and functional deficits have routinely found that cognitive ability, specifically working memory, is the strongest predictor of schizophrenia patients’ real-world functional capacity . Indeed, in our own data, we observed a similar robust correlation between MMSE and UPSA-B. These associations support the utility of P300 amplitude as a potential biomarker for predictive risk and treatment studies.

However, they also emphasize the relatively non-specific nature of the measure. This was evident, as well, in the control sample data. In these otherwise healthy subjects, P300 amplitude was affected by smoking, race and, as one mediator of the race effect, prior history of substance abuse or dependence. Previous studies have shown that nicotine reduces P300 , yet – despite the well-known propensity of schizophrenia patients to smoke – there has been virtually no consideration of the effect of smoking on the auditory P300 in patients. We observed no parallel effect of nicotine in patients, presumably because their ERPs were already suppressed. This is consistent with a recent small study of healthy subjects administered with intravenous ketamine. Ketamine induced schizophrenia-like symptoms and attenuated the auditory target P300 response, but this was unaffected by co-administration of nicotine vs. placebo . Similarly, reduced P300 has been associated with the use of stimulants , opioids and cannabis . Yet, again, we saw no effect of prior substance use on P300 in the schizophrenia patients. This mirrors what was recently reported in a study examining the effects of cannabis in prodromal subjects considered to be at ultra-high risk for developing psychosis. In this sample, those with a history of cannabis use were indistinguishable from those without. However, among the otherwise-healthy controls, those who used cannabis had reduced P300 responses that were indistinguishable from those of the prodromal sample . The impact of substance abuse on the African-American sample may reflect differences in the specific character and/or quantity of substance use within the different racial groupings, which are not captured by a simple dichotomous categorization. Similarly, the residual effects of race, independent of past substance use, could reflect the impact of other psychosocial stressors in the different racial communities. Unfortunately, we have no objective measures of either of stressful life events or physiological markers of stress to test this hypothesis.The fact that modulating factors such as nicotine and substance abuse can differential affect controls, but not patients, raises an important cautionary note about how to interpret study results, potential false negative findings, and what constitutes the best comparison sample for genetic or biomarker studies. A common recommended strategy is to recruit control subjects who are similar to the clinical sample on various modulating factors and co-morbid conditions. The results of this study would seem to temper that recommendation, at least for P300. It suggests that, in matching the samples, individual and group differences may be attenuated for reasons other than psychosis. Consequently, genetic associations with the endophenotype may be obscured and the ability of the measure to predict transition to psychosis may be weakened.

However, the broad utility of P300 as a robust marker for large multi-site studies is confirmed, along with important associations with both positive symptoms and decreased cognitive and functional capacity.KNOWLEDGE ABOUT A person’s family history of a disorder can be useful in both clinical and research settings . For clinicians, knowing if relatives ever evidenced a Mendelian dominant or recessive genetic disorder can help identify early signs of the condition and might contribute to patients’ decisions about having children. Knowledge of a familial complex genetically influenced disorder is also useful, but less informative because each relevant gene probably contributes to only a small proportion of the risk and environment is likely to play a major role . Directly relevant to the current report, knowledge of a subject’s FH can also help researchers select individuals or families on which to focus efforts in order to control costs and maximize the usefulness of the data gathered . There is general agreement that the most accurate FH comes from the Family Study Method that uses personal interviews with all available first- and second-degree relatives . But that approach has downsides including high cost, the time,indoor cannabis growing and effort needed to gather the information from all available relatives, as well as the bias of nonrandom missing data resulting from lack of information on relatives who have died, those too ill to be interviewed, individuals who cannot be located, as well as those who refuse to participate. In an alternate approach, the Family History Method , data can be gathered relatively quickly and at lower cost. Here, relatively simple instruments ask informants about demography and clinical conditions regarding multiple relatives . FHM downsides include inconsistencies in an individual’s reports over time and disagreements among relatives regarding the familial problems . The most salient drawback is the relatively low sensitivity of FHMs . The specific disorder studied relates to FHM sensitivity where obvious medical conditions, are likely to have high FHM sensitivities , but identifying relatives’ psychiatric disorders have lower sensitivities . Regarding substance use disorders , more accurate FHM reports are seen for smoking tobacco with less impressive sensitivities for misuse of alcohol and illicit drugs. Regardless of the condition studied, specificities are often over 90%. The average sensitivities of FHM studies of familial alcohol problems, including AUDs, usually range between 30 and >50% . An example of more promising FHM results involved correlations of 0.70 between college students’ alcohol problems of their parents and those parents self-report using variations of the Short Michigan Alcohol Screening Test . However, offspring missed alcohol use disorder -like problems in 17% of fathers and 50% of mothers. In addition, the parents’ self-reports were not validated by repeated structured interviews over time, the analyses focused on problem patterns for the parents rather than AUDs, and no information was available regarding the performance of individual AUD criteria.

Another study evaluated twin pair concordance regarding their father’s alcohol problems , but the paper focused on agreement among the off- spring reports and did not include DSM AUD criteria. In addition to the condition being studied, other characteristics are also associated with higher FHM sensitivities. These include more severe alcohol histories in the subjects ; informants with conditions that are similar to the subject’s problems ; a subject for whom AUDs ran in their family ; a close genetic relationship between informant and subject ; a focus on more observable criteria such as having ever been in treatment ; the use of less demanding criteria for the subject’s condition ; and when multiple informants are used . The relationships of informants’ and subjects’ demographic characteristics to the accuracy of the informant’s reports vary across studies. Regarding sex, some investigations noted that female subjects with alcohol problems were more likely to be correctly identified than male subjects, although the sex of the informant might have less impact on the accuracy of the reports . However, other studies noted that male offspring might more accurately report alcohol problems in their mothers and female offspring be more accurate in reporting alcohol problems in their fathers . The importance to sensitivity of an informant’s education is also not clear, with one study reporting a fivefold lower accuracy for an informant’s report about a parent’s smoking history for informants with a college education compared to those with less than high school completion . The informant’s age was reported to have little relationship to the validity of their report in some studies , but Pape and colleagues reported a twofold higher odds ratio for correct offspring reports for older informants. The relationships of informants’ and subjects’ demographic characteristics to the accuracy of substance use histories using the FHM require additional study. If demography is closely related to FHM sensitivity, it could be easier to identify which informant is likely to give the most accurate FH. Our every 5-year evaluation over 35 years for members of 2 generations of the San Diego Prospective Study offers an opportunity to expand information regarding relationships of demography and other characteristics to the accuracy of reports of parental alcohol-related problems by offspring. The SDPS incorporates many of the better-established characteristics related to higher accuracy of informants’ FHM reports. These include using standardized personal interviews with subjects and informants, relatively severe alcohol problems and high levels of alcohol intake in subjects, a first degree genetic relationship between informants and subjects, high rates of alcohol problems in both generations, and the focus on relatively broad alcohol problems for fathers that do not require that full AUD criteria be met for the informant’s report to be considered valid. The data reported here were used to evaluate 3 hypotheses. These included the following: higher levels of education in the offspring with the potential greater understanding of human behavior and a greater awareness of problems in their environment will be associated with higher rates of recognition of paternal alcohol problems; for potential reasons similar to the impact of higher levels of education, older informants will more accurately report a father’s alcohol problems; and female offspring will more accurately report their father’s AUDs, as noted in some prior studies.After additional Human Subject’s Protection Committee review, beginning in 1988 100% of the original 453 SDPS probands were located, 99% of whom agreed to participate in the follow-up protocol.

Density of medical marijuana dispensaries and delivery services per city, however, was negatively and strongly associated with greater availability of these products at places where tobacco products are typically sold. The current study examined social factors associated with availability of tobacco products for blunts. Other studies have shown that the tobacco industry aggressively markets specific products, such as menthol cigarettes, in low-income communities and communities of color . This may not be the case for blunts and blunt wrappers. Results of our study indicate, that for the most part, availability of tobacco products associated with blunts was similar in neighborhoods with different socioeconomic status and racial and ethnic composition. Focusing on socioeconomic status, these results are less expected given the associations between some low socioeconomic indicators and use of blunts . Our results regarding racial and ethnic composition are consistent with recent findings that blunt smoking appears to be practiced among a growing number of racial/ethnic groups . Moreover, our finding about the positive association between percent of Whites and availability of cigars at the store is consistent with results of a recent study that cigar use including big cigars, cigarillos, and little cigars has increased among White non-Hispanic men aged 18 to 25 years . Additionally, our findings suggest that convenience stores, smoke/tobacco shops and liquor stores may provide greater availability of tobacco products associated with blunts than do other types of stores that sell tobacco. Because previous studies have shown that exposure to and availability of drugs increase drug use and abuse , policies that limit young people retail access to these products may help to reduce use of blunts and therefore related problems such as growing indoor cannabis and tobacco dependence and smoking-related diseases . Interestingly, all three community-level factors related to marijuana use and access to medical marijuana were found associated with availability of tobacco products associated with blunts. Specifically, higher prevalence of marijuana/hashish use and policy that permits medical marijuana dispensaries and private cultivation were positively associated with availability of tobacco products for blunts in tobacco outlets.

Density of medical marijuana dispensaries and/or delivery services, however, reduced odds of availability of these products. Possible explanations of these results include considering community norms and physical demand. Focusing on the associations between medical marijuana policy and availability, it is possible that community norms that support marijuana use may affect medical marijuana policy which in turn may increase availability of tobacco products associated with blunts. Using structural equations modeling, our previous studies indicated that community norms were directly related to tobacco and alcohol policies . Community-level prevalence of adult marijuana/hashish use was another important factor.In this case, higher rates of marijuana use contribute to more acceptability of marijuana which affects policy and availability. However, it is also possible that increased acceptability of marijuana affects policy and access to marijuana which in turn increases rates of marijuana/hashish users in the community. A recent study found higher odds of marijuana use in states that legalized medical marijuana . The cross-sectional design of the current study limits our understanding of these relationships. Future studies should explore these potential mediation effects and its relationships to youth and adults marijuana and blunts use. We also found that greater density of medical marijuana dispensaries and delivery services reduced odds of availability of tobacco products associated with blunts. These relationships may be explained by economic equilibrium theory . That is, tobacco stores may service demand for products associated with marijuana use when supply through medical marijuana dispensaries and delivery services is low. Also, tobacco stores that sell products associated with blunts and medical marijuana dispensaries and delivery services may serve different types of marijuana users and therefore emerge in different types of business. Some research suggests that blunts use is a distinct sub-cultural formation associated with hip hop or rap music and with distinct configuration of rituals, jargon, and drug use norms .

Results of this study should be considered in light of several limitations. First, the cross sectional design of the study limited our ability to make directional inferences about relationships between the community-level factors and availability. For example, prevalence of adult marijuana/hashish use can be a proxy of community norms or it can be a result of availability of marijuana and marijuana products through density of medical marijuana dispensaries and delivery services. Also, the study included only selected tobacco outlets in midsized cities. Including rural communities and a larger sample of tobacco outlets may help to more closely explore the relationships between neighborhood demographics and availability. Third, it is possible that our community-level measures do not capture societal level influences related to normalization of marijuana use comprehensively. Other studies should include other variables related to popular culture and more direct measures of adult beliefs. Finally, information about individuals’ blunts use in these communities was not available for the study. Prevalence of blunt smoking in regions of California is unknown. Such information is only available from of a qualitative study of Southeast Asian Americans in two communities in San Francisco Bay Area. In that study, 62% of youth and young adults and 10% of adults reported lifetime blunts use . This limits our understanding of the relationships among community norms, medical marijuana policy, availability of tobacco products associated with blunts and actual blunts use. Despite these limitations, results of this study suggest the important role that community norms that support marijuana use or legalization of medical marijuana and medical marijuana policy may play in increasing availability of tobacco products associated with blunts. Since blunts have become popular over time and expanded into growing number of racial/ethnic groups , these results may be of particular importance to different communities in California and elsewhere. Tobacco and marijuana policymakers should be aware of the larger social contexts of blunts use and availability and the importance of considering societal-level influences related to normalization of marijuana use to reduce blunts use and/or other forms of concurrent use of tobacco and marijuana.

Similarly, results of this study also suggest the importance of studying blunts use and availability within the larger social contexts of marijuana use, related policies and community norms to better inform policies to reduce blunts use and/or other forms of concurrent use of tobacco and marijuana.In January 2020, the United States Food and Drug Administration finalized a policy to prioritize enforcement against cartridge-based e-cigarettes in flavors other than tobacco and menthol, effective February 1, 2020 . At the time,indoor cannabis growing no e-cigarette product was authorized for sale in the United States, meaning that no e-cigarette was being sold with legal authorization. However, the FDA had exercised enforcement discretion to defer authorization requirements, effectively allowing all e-cigarettes into the marketplace. The FDA announcement cited “epidemic levels” of youth e-cigarette use , particularly use of mint and fruit flavors and cartridge-based systems , such as those sold under the JUUL brand, in which single-use cartridges, or pods, are swapped in and out of a reusable device. The policy goal was to focus on products most attractive to youth. Companies that did not cease manufacture, distribution and sale of prioritized products within 30 days “risked FDA enforcement actions ,” but those enforcement actions were not delineated. The policy was criticized for vague product definitions and for excepting menthol, refillable, and disposable e-cigarette products increasingly popular among youth . The policy was defended as providing flexibility to pursue action against any e-cigarette company selling products that target youth . E-cigarettes are the most commonly consumed tobacco product among adolescents . Flavors in e-cigarettes and other tobacco products and a cooling sensation from added menthol may increase product appeal and mask harshness, motivating youth experimentation and continued use . Fruit flavors and sweet/ dessert flavors are considered particularly popular among young e-cigarette users; however, combination fruit-ice flavors and mint flavors are also used commonly . While recent surveillance indicates a possible decline in e-cigarette use prevalence among adolescents, 80% of e-cigarette users report using flavored products . Emerging data also suggest that flavored and pod-based product use continued to be normative among young e-cigarette users in the months following the FDA enforcement prioritization policy. The 2020 National Youth Tobacco Survey , conducted from January to March , demonstrated that high school e-cigarette users most commonly used pod devices and fruit , mint , menthol , or sweet flavors.

In a May 2020 national online survey of adolescents and young adults, reusable pod/cartridge e-cigarettes and disposable e-cigarettes, such as those sold under the Puff Bar brand, were the most used devices, and mint, menthol, or ice was the most used class of flavors among both reusable and disposable users . Barshaped “fifth-generation” disposable devices, sometimes called “podmods” , do not actually contain pods, are not modifiable, and differ from first-generation “cigalike” disposable devices. This manuscript uses “modern disposable” to refer to these disposables and “reusable pod” to refer to reusable systems with single-use cartridges .The present study characterizes device type and flavor behaviors among young e-cigarette users approximately one year after the FDA policy announcement, allowing time for regulators, sellers, and users to adjust to the new policy. As the main goal of this study was descriptive, no numerical hypothesis was defined. Data are from a national online panel of e-cigarette repeated ever-users ages 14–20 years, conducted from March to April 2021. The investigation also examines participants’ e-cigarette flavor preferences and perceived access to flavors that they like. Finally, using latent class analysis , we classify participants according to their flavor preferences and examine how flavor preferences relate to sociodemographic characteristics, e-cigarette and other tobacco use behaviors, and reasons for e-cigarette use. Examining e-cigarette flavor preferences, rather than use behaviors alone, may help inform assumptions about how youth may respond to potential policies. Results are based on a national cross-sectional online survey of adolescents and young adults who reported e-cigarette ever use . Participants were recruited from existing, actively managed market research panels aggregated by a third-party vendor . Online research panels have gained wide use in behavioral health sciences research, including tobacco control research and with youth specifically . While panel members may not represent the general population, participants reflect a range of geography, age, income levels, and racial/ ethnic groups. For this investigation, panel members residing in the United States whose demographic profiles potentially matched study eligibility criteria were invited to complete a screener questionnaire to confirm their age and lifetime e-cigarettes use . A threshold of ≥3 times was set as an inclusion criterion to help assure that the study population included participants familiar with e-cigarettes from repeated use. Of 8860 completed screener questionnaires, 2712 participants met eligibility criteria and 2253 of these completed the survey. Surveys were administered from March 18 to April 25, 2021. Median completion time was 9 min. Participant incentives varied by panel but typically consisted of points redeemable toward merchandise, travel, or other awards. Before beginning the survey, potential participants were provided information stating that the survey was a research study and were informed of the study goals, its voluntary nature, and were asked to complete two items to confirm their comprehension. Signed informed consent was not collected to preserve anonymity. The University of California San Francisco Institutional Review Board approved all study procedures. All participants were provided with a list of 9 different tobacco products , 6 types of e-cigarette devices , marijuana, and alcohol and asked to endorse all of the products listed that they had ever used . The list included photographs and example brands. For each product ever used, participants reported how many days in the past 30 days they used that product . Past 30-day e-cigarette users were asked to endorse which e-cigarette flavors they had used in the past 30 days from a list . All participants, including e-cigarette non-users were asked, “Right now, how difficult or easy is it to find e-cigarettes or vapes in flavors that you like?” with 4 options . Participants were then asked how it is to find each of 8 specific e-cigarette flavors and how it is to find fruit, candy, fruit-ice, and/or dessert e-cigarette flavors from 5 specific sources . All participants were asked to respond to the prompt, “How much do you like the following flavors for e-cigarettes or vapes?” for 8 flavors .

SWM task accuracy and reaction time were calculated for SWM and simple attention conditions. Group differences in neuropsychological test scores and SWM task performance were examined with one-way ANOVAs. We followed up significant ANOVAs with Tukey’s all pairwise t-tests between the three groups. Imaging data were processed and analyzed using the Analysis of Functional NeuroImages package . We first applied a motion-correction algorithm to the time series data . Second, we correlated the time series data with a set of reference vectors that represented the block design of the task and accounted for delays in hemodynamic response , while covarying for estimated motion and linear trends. Next, we transformed imaging data to standard coordinates then resampled the functional data into 3.5 mm3 voxels. Finally, we applied a spatial smoothing Gaussian filter to account for anatomic variability. After processing functional data, we examined average BOLD response to the SWM task in each group using one sample t-tests, and determined regions that showed greater response to SWM relative to simple attention , reduced response during SWM relative to rest , and greater simple attention response than SWM response. We next compared response during SWM relative to simple attention between groups with ANOVAs, and performed pairwise comparisons between groups. We performed group comparisons on the whole brain, rather than discrete regions thought to be activated by the task, because previous studies by our group and others have suggested neural reorganization and use of alternate brain systems during working memory among individuals with AUD. To control for Type I error in group analyses, we required significant voxels to form clusters ≥1072 μl , yielding a cluster-wise α < .0167 . We utilized the Talairach Daemon and AFNI to confirm gyral labels for clusters.

Previous research has suggested that neuropsychological deficits among adult marijuana users are associated with lingering effects of recent use, and that these impairments dissipate with extended abstinence . To understand whether group differences in the current study relate to recent cannabis growers use, we performed post-hoc regressions within the MAUD group. First, we extracted the average fit coefficient for each MAUD participant from each cluster where we observed a difference between MAUD and control or AUD teens. Next, we used regression analyses to examine whether days since last marijuana use predicted brain response within each group difference cluster.Mental health in young adulthood is the strongest predictor of mental health in adulthood. Mental health vulnerabilities present in young adulthood can be exacerbated by marijuana use, thus potentially hindering or delaying a successful transition to adulthood. Considering motives of marijuana use may provide insight into the associations between marijuana use and mental health in young adults. The purpose of this dissertation was to: 1) understand the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, and overall psychological distress in young adults, and 2) examine whether these associations vary by gender. Data come from the Cannabis, Health and Young Adult Study , a longitudinal study of young adults, in Los Angeles, who use marijuana for medical and/or recreational purposes. Exploratory and confirmatory analyses were performed to validate the factor structure of the instrument used to operationalize motives of marijuana use for the study. Multiple linear regressions were used to determine how motives of use are associated to mental health outcomes. Indirect effects between motives of use and mental health outcomes through frequency of use were also assessed.

Finally, gender was tested as a moderator for both direct and indirect associations between motives of use and mental health outcomes. Results validate the factor structure of the amended Comprehensive Marijuana Motive Questionnaire. Furthermore, results indicate that the coping motive of use is positively, significantly associated with mental health outcomes. The motives of conformity, pain, and attention are indirectly associated with symptoms of depression through frequency of use. Gender influences the association between the motive of social anxiety with symptoms of depression and overall psychological distress whereas women who endorse this motive of use report more symptoms of depression and overall psychological distress than men. None of the moderated mediation analyses were significant. These results emphasize the importance of considering motive of use in the development of interventions targeting marijuana use and mental health in young adults. These findings also highlight the need for gender specific interventions as men and women engage in use differently, and with different consequences to their mental health.Mental health in young adulthood is the strongest predictor of mental health in adulthood. Mental health vulnerabilities present in young adulthood can be exacerbated by marijuana use, thus potentially hindering or delaying a successful transition to adulthood. Considering motives of marijuana use may provide insight into the associations between marijuana use and mental health in young adults. The purpose of this dissertation was to: 1) understand the associations between motives of marijuana use and symptoms of depression, symptoms of anxiety, and overall psychological distress in young adults, and 2) examine whether these associations vary by gender. Data come from the Cannabis, Health and Young Adult Study , a longitudinal study of young adults, in Los Angeles, who use marijuana for medical and/or recreational purposes. Exploratory and confirmatory analyses were performed to validate the factor structure of the instrument used to operationalize motives of marijuana use for the study.

Multiple linear regressions were used to determine how motives of use are associated to mental health outcomes. Indirect effects between motives of use and mental health outcomes through frequency of use were also assessed. Finally, gender was tested as a moderator for both direct and indirect associations between motives of use and mental health outcomes. Results validate the factor structure of the amended Comprehensive Marijuana Motive Questionnaire. Furthermore, results indicate that the coping motive of use is positively, significantly associated with mental health outcomes. The motives of conformity, pain, and attention are indirectly associated with symptoms of depression through frequency of use. Gender influences the association between the motive of social anxiety with symptoms of depression and overall psychological distress whereas women who endorse this motive of use report more symptoms of depression and overall psychological distress than men. None of the moderated mediation analyses were significant. These results emphasize the importance of considering motive of use in the development of interventions targeting marijuana use and mental health in young adults. These findings also highlight the need for gender specific interventions as men and women engage in use differently, and with different consequences to their mental health.The advent of combination anti-retroviral therapy has transformed human immuno deficiency virus infection and its effects on the central nervous system . HIV infection is now a chronic disease with multiple interacting causes of morbidity. Although neurocognitive impairment remains common in some HIV cohorts , neurocognitive deficits now tend to be milder than in the preART era. Identifying persons with milder NCI is more difficult than identifying frank dementia and tends to require comprehensive and costly assessments. Even the milder forms of NCI may be associated with problems with everyday functioning. This highlights the importance of identifying, assessing and intervening in HIV-infected persons at risk for impaired and/or worsening neurocognitive function. Ascertaining biomarkers of HIV-associated NCI is one promising approach to detecting those at risk for NCI, particularly if these biomarkers are obtained as part of routine clinical care. Clinical investigation of biomarkers is also relevant to improve understanding of the biomedical mechanisms underlying NCI in the ART era. The Veterans Aging Cohort Study Index was developed as a composite marker of disease severity among HIV-infected persons based on routine clinical blood tests. It integrates age,“traditional” biomarkers of HIV disease and “nontraditional” biomarkers, including markers of renal and liver function, anemia,grow rack and hepatitis C virus coinfection. The VACS Index has been consistently associated with increased risk of death in HIV-infected persons. It has also been linked to poor health outcomes, including increased risk for hospitalizations and medical intensive care unit admissions,fragility fractures,frailty, and concurrent extremity strength. Prior work by our group found the cross-sectional association of the VACS Index with NCI to be significant but small, and particularly weak among Hispanics.The overall goal of the present study was to extend prior cross-sectional findings to examine the ability of the VACS Index to predict neurocognitive change and incident NCI in a large and well-characterized cohort of HIV-infected persons.

We did so by examining the association between baseline VACS Index scores and subsequent neurocognitive change; whether longitudinal changes in the VACS Index corresponded to changes in neurocognitive function; and whether VACS Index scores predicted time to incident NCI in a subgroup of participants who were neurocognitively normal at baseline.Participants included 655 HIV-infected individuals followed for up to 6 years in National Institutes of Health–funded cohort studies at the University of California, San Diego, HIV Neuro behavioral Research Program from 14 April 1999 to 11 May 2012. Studies were approved by the university’s institutional review board. All participants provided informed consent for participation in these cohort studies and agreed for their data to be used for future studies assessing the impact of HIV on the nervous system. Exclusion criteria included histories of neurological or severe psychiatric conditions. Inclusion criteria were being HIV infected , having ≥2 study visits with valid global neurocognitive scores, having laboratory data available to compute the VACS Index within 3 months of neurocognitive data, being primarily English speaking, providing informed consent, and being free of sensory or physical problems that would interfere with neurocognitive testing. Forty-five percent of the sample had previously undergone neurocognitive testing.Routine clinical chemistry panels, complete blood cell counts, rapid plasma reagin, HCV antibody, and CD4+ T-cell counts were performed at a Clinical Laboratory Improvement Amendments–certified, or equivalent, laboratory. HIV RNA levels in plasma were measured by means of reverse transcription polymerase chain reaction . CNS penetration effectiveness was ascertained as described elsewhere . Self-reported data were gathered on duration of HIV infection, nadir CD4+ T-cell count, history of ART, and duration of current ART. HCV status was based on HCV antibody testing and/or self-report. The VACS Index was computed as described elsewhere, with higher scores indicating worse disease status.The neurocognitive battery comprised 15 measures covering 7 neurocognitive domains . Raw test scores were transformed into scaled scores adjusted for repeated testing,which were then converted into T scores adjusted for demographics. The adjusted T scores for each test were then averaged to derive global and domain T scores, which were used for analyses in the overall sample. To determine whether the VACS Index predicted time to incident NCI, we converted the adjusted T scores for each test into deficit scores, ranging from 0 to 5 and averaged these scores to derive global deficit scores. Consistent with previous studies, NCI was defined as a global deficit score of ≥0.50.We assessed current mood symptoms via the Beck Depression Inventory and used published cutoff scores to determine severity of depression symptoms. Current and lifetime history of major depressive and substance use disorders were obtained using structured diagnostic interviews that follow criteria of the Diagnostic and Statistical Manual of Mental Disorders. Presence of a “substance use disorder” was defined as meeting criteria for abuse or dependence for alcohol, cannabis, and any of the following substances: opioids, methamphetamine, cocaine, sedatives, and hallucinogens. Data on lifetime intravenous drug use were ascertained by self-report.Three analytic approaches were used. First, to evaluate effects of baseline VACS Index scores on changes in neurocognitive function over time, we used a mixed effects linear regression with subject-specific random intercepts and slopes, which assumes that participants have different baseline T scores and varying trajectories of change in T scores over time . The model regressed mean global T scores on time . Individual slopes were obtained from the model and used as outcomes in a linear regression with baseline VACS Index as predictor. The slopes estimated the average changes in global T scores with every year passed. A second set of analyses was used to evaluate the association of the VACS Index as a time-dependent predictor of longitudinal cognitive status based on adjusted T scores.Because the model on global T scores was significant, we investigated the association of the VACS Index as a time-dependent predictor with changes in domain T scores using a similar approach and evaluated the impact of potential covariates.

These areas are particularly important for adolescents’ processing of social information . The greater activation of these regions during the neurodevelopmental period of adolescence may be the result of substantive neurodevelopmental changes . These changes peak during adolescence, resulting in a relatively greater release of DA during this time frame . Practically, this means that risk taking behaviors, which are inherently exciting, frightening, and fun, may indeed feel much more rewarding during middle adolescence While it is clear that peers take on newfound significance during adolescence and that this shift has the potential to increase risk behaviors, an important body of work is beginning to reveal important caveats to this thesis. First, peer influence is also a powerful motivator for prosocial behavior during adolescence . Relatedly, while neural reward circuits are linked to a variety of risk behaviors during adolescence, VS and vmPFC reactivity to social cues also portend positive, prosocial development . Second, while peers become increasingly important during adolescence, this does not render parents as unimportant. Despite spending less time with parents, connectedness with parents can attenuate the impact of the enhanced reward circuit responses typical during adolescence, serving as a protective force insulating adolescents against risk behavior, stress and even depression . In fact, when compared with peers, parents show a significantly greater impact on adolescent decision-making . Understanding how adolescents navigate not only risk,growing cannabis but also prosocial peer interactions is one of the ultimate challenges for adolescent addiction treatment developers. We believe that this challenge is not insurmountable . Our task is to determine how best to channel youths’ drive and developmentally-unique cognitive systems to help them make more healthy choices. Summary.

These four developmental domains interact dynamically throughout adolescence , and are highly relevant to the adolescent addiction treatment context. For example, an adolescent’s environment can impact the nature and timing of puberty and vice versa; adolescents who look older may be treated differently than same-age adolescents who appear younger . These pubertal changes can alter the social spheres that adolescents are introduced to and experience . Moreover, social experiences, in turn, shape adolescents’ cognitive opportunities and related development early . Considering the interplay of these factors is crucial for understanding adolescent development as well as cultivating impactful programs to prevent and treat adolescent substance use. Throughout the past 3 decades, adolescent addiction treatment has shown some degree of capacity to catalyze and sustain behavior change in adolescents, but overall, results have been underwhelming . More specifically, despite several decades of efforts by experts to identify the best avenues to prevent and reduce adolescent substance use, few youth receive treatment . Of those who do, even when the treatment is grounded in evidence-based approaches and works well for adults, many youth do not show significant long-term changes in their substance use , with 86% returning to use within a year of treatment . As reviewed in Feldstein Ewing , this contrasts with the adult addiction literature, wherein a number of psychosocial interventions have much stronger impact in terms of instantiating and sustaining meaningful behavior change . For example, meta-analyses examining the efficacy of motivational interviewing indicate that in the context of addiction treatment, MI’s effect sizes are notably less robust for adolescents as compared with their impact with adults . At issue is that most of the interventions clinicians use with adolescents are “borrowed” from adult clinical addiction research . Yet the samples and populations utilized in large scale adult addiction studies, such as Projects COMBINE and MATCH , included inherently different populations, such as adults who largely self-referred to treatment. As a result, there is a notable gap between the nature of adults from whom these treatments were derived, and the nature of adolescents that we are trying to implement the same interventions with . Ultimately, better targeting with adolescent neurodevelopment in mind is likely to improve adolescent addiction treatment outcomes.

The poor generalizability of “adult” treatment to adolescents revolves around the significantly different conditions that make interactions within adolescent addiction treatment highly disparate from adults; within treatment sessions, adolescents face inherently different neurodevelopmental issues , disparate sociodevelopmental concerns , are on a different addiction trajectory , and in turn, have different treatment outcome goals than adults . Here, we include a brief overview of the challenges facing adolescent addiction treatment and its reporting, and our recommendations for avenues to improve best practices for clinicians and clinical research in this critical area of adolescent addiction treatment development.Absence of uniformly-agreed upon outcome in the adolescent addiction treatment literature. The current status of the field renders it quite difficult, if not impossible, to compare adolescent treatment outcomes across different treatment approaches . This is in contrast to the adult literature, wherein there are common, widely-agreed upon outcome metrics, such as percent days abstinent or drinks per drinking day . In this brief examination, numerous different categories of outcome variables were reported. The most common included number of substance use days, substance-related consequences, and quantity of substance use. This range of outcomes is likely to reflect a number of issues; one, as observed throughout the adolescent addiction treatment literature, there may simply be different targets for adolescent treatment response. More likely, this reflects that adolescents often show behavior change within one dimension of substance use , while still retaining high scores on another . Of greater concern to adolescent addiction practitioners, variance on outcomes may reflect reporting bias that favors treatment outcomes that withstood the test of statistical significance. One avenue to improve the field may be to report on commonly-agreed upon adolescent treatment outcome measures and do so regardless of statistical significance. We believe that this recommendation, to move toward a core outcome set in the field of adolescent addiction treatment, is highly important, and follows recent relevant initiatives, including the Scottish National Health System’s core outcome work , and the Core Outcome Measure in Effectiveness Trials Initiative . Notably, while these examples serve as excellent models, they have thus far been largely implemented with adult, rather than adolescent, clinical research studies. This fact again highlights the need for identifying and rolling out jointly-agreed upon core outcome metrics for adolescents in addiction treatment.Additionally, even when effect sizes are significant, it is not clear the degree to which reported outcomes are clinically meaningful with adolescent addiction patients. For example, one less drinking day per month may achieve statistically significance, but not a meaningful clinical change in terms of adolescents’ overall health, social, cognitive, and academic outcomes. In the adult literature, clinical impact has been defined as a statistically significant reduction in initial rates or problem scores, or a halving of initial symptoms . As with many other forms of adolescent health risk behaviors , a central measurement challenge is that adolescents engage in substance use sporadically and inconsistently . This makes treatment outcome measurement quite different from adults, whose use is often characterized by heavy, consistent patterns. For example, an adolescent may use alcohol very heavily , but then not drink at all during the initial months of the school year . Another avenue to improve the field is to examine pre-to-post changes in interference in functioning for youth; this represents changes in the degree to which alcohol or other substance use disrupts interactions with peers, with family, with school/other academic,cannabis growing and/or other relevant work/extracurricular obligations. To this end, examining reductions in interference in functioning is likely a more meaningful metric .

Examples of measures that can effectively access and assess this factor include the Rutgers Alcohol Problems Index and the Marijuana Problems Index . Substance substitution? While it is clear that adolescents tend to gravitate toward poly substance, rather than mono-substance, use , many adolescent treatment studies do not report treatment outcomes for non-target substances of abuse. For example, many measured treatment outcomes in alcohol , cannabis , tobacco ; some examine 2 substance categories, but include inconsistent pairings across each study . This is relevant, as many contemporary adolescent addiction treatment teams are trying to disaggregate whether or not youth are “swapping” out one substance for another, particularly in the changing cannabis and opioid landscapes . Our fourth recommendation to the field is our encouragement to explicitly examine and report outcomes across all types of substance use, to ensure that we can disaggregate the differential impacts and interactions that each substance might be having with the developing brain . This is likely to become an increasingly important issue in the field of addiction treatment as researchers move towards a precision medicine lens for understanding the genetic, lifestyle, psychological, social, and other bio-behavioral markers associated with treatment responsiveness . Of course, it should be noted that this point applies equally to adult studies, and to psychosocial interventions for most kinds of behavior disorders. Sadly, adolescent treatment has continued to lag behind advances made in other age groups in the journey towards precision medicine . Summary. Many adolescent addiction treatments appear to have clinically meaningful outcomes, but cross-treatment comparison and interpretation is not truly possible in the literature’s current state. At this time, inconsistent targets and timing obscure careful detection of comparative clinically-meaningful treatment gains . In turn, it is currently quite difficult to access the driving mechanisms and their intersection with potential developmental cognitive factors, and true treatment success in this age group. In turn, we make these recommendations for the assessment of adolescent treatment outcomes, with examples of how each recommendation maps onto relevant neural targets . It will be fascinating to continue to see if and how these developmental neuroscience findings translate to the clinic.While the previous section indicates that existing treatments available to adolescents have had difficulty examining behavior change, it is our position that actively considering the nature of the developing adolescent brain can inform the revision and approach of interventions with this age group. In other words, the developing brain gives us an invaluable perspective regarding what might “work” better in this age group in terms of prevention/ intervention. As summarized in Figure 1, we propose four key neurodevelopmental features of adolescence, and encourage approaching addiction interventions from this foundation as a promising first step in articulating prevention and intervention to the adolescent age group. Compellingly, in largely overlapping neural networks, those four features include: Puberty; Surge of cognitive skills Sculpting out of self; and Changing social landscape. Collectively, consideration of these factors, and their interplay, highlights several important themes to consider in developing novel clinical addiction approaches with this age group. Benefit of a prosocial perspective on prevention and intervention. First, consistent with G. Stanley Hall’s “storm and stress” perspective of adolescence, many existing adolescent-focused prevention and intervention approaches hinge on “problem focused” perspectives in substance use and its resolution. However, this does not play to the nature of the adolescent brain, which is increasingly being recognized as evolving and adaptive . As cited by Ellis , integrating considerations of adolescent neurodevelopment would likely generate more positive treatment outcomes if we took a positive, adaptive-focused perspective that plays to and enhances adolescents’ existing strengths in resilience, natural penchant to cognitive flexibility, and socially-adaptive and prosocial growth. This is an arena that is gaining increasing traction in adolescent addiction contexts . Non-traditional, but potentially highly impactful examples here could include clinical approaches that engage adolescents in helping younger peers, pairing problem users up with more successful youth in the same age group, and engaging adolescents in avenues for more successful positive change in their peer and greater social communities . A relevant point in this examination is that while a handful of emerging studies are beginning to include prosocial, resilience-focused models of adolescent behavior , a careful synthesis of these models has not yet been created. This is a critical avenue for future work, and will likely require not only examination of quantitative, but also mixed method, and qualitative research, as much of this emerging research is still in its inception and early stages of implementation. Maximizing their drastically developing cognitive skills. Adolescents are in the midst of experiencing a surge of new cognitive skills; at the most fundamental level, adolescents’ brains are organized toward and ready for adaptation .

These medical diseases are frequently considered chronic medical conditions, and are included in either the validated Katz chronic disease comorbidity questionnaire 15 or the Hierarchical Condition Category system and obstructive sleep apnea, which is recognized as one of the most prevalent chronic respiratory disorders and therefore included in our analysis. Medical multi-morbidity is defined in the literature as 2 or more chronic diseases . Using the above conditions to study medical multi-morbidity with the NSDUH has been performed in other studies . Drug use was assessed by NSDUH by self-report of cannabis , cocaine , heroin, inhalants, hallucinogens, and non-medical use of prescription medications . Non-medical use of prescription medications was defined as use of a drug that was not prescribed or used for the experience or feeling it caused. Nicotine dependence was defined based on dependence criteria of the Nicotine Dependence Syndrome Scale and alcohol dependence was defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition . SUDs were determined by participant responses to a series of questions that determined if criteria would meet DSM-IV abuse or dependence categories for each drug. While NSDUH is not a diagnostic interview, this method provided a proxy diagnosis.Analyses include all respondents aged 18 and older. We aggregated data from the three separate cohort years into a single cross-section to be able to increase power for examining associations between variables with low prevalence . We first examined bivariable associations between demographic characteristics and number of self-reported conditions . Demographic measures included age , sex, race/ethnicity , education level ,roll bench total family income , marital status . NSDUH only provides pre-coded categorical responses for the age and income variables, and therefore could not be analyzed as a continuous variable.

Tobacco use , nicotine dependence, alcohol use , alcohol dependence, self-reported overall health , and self-reported mental health problems in the past-year were also compared among adults reporting 0, 1, and ≥2 chronic conditions. Bivariable analyses was also performed comparing past-year drug use and diagnosed substance use disorder for adults with 0, 1, and ≥2 chronic conditions. We evaluated correlates of past-year drug use among adults with medical multi-morbidity using binary logistic regression. We first estimated odds of each covariate separately, generating unadjusted odds ratios. We then fit covariates simultaneously using multiple logistic regression. All analyses were weighted as part of NSDUH to account for the complex survey design and to obtain accurate standard errors for estimates at the population level. More detailed information regarding the development of analysis weights are found elsewhere . Since our analyses utilized data from 3 cohorts, we divided the weights by 3 to obtain nationally representative estimates. Stata SE 13 was used for all analyses, and survey commands were utilized to provide accurate standard errors using Taylor series estimation methods . Secondary analysis of this publically available data was exempt for review by the New York University Langone Medical Center Institutional Review Board.The analytic sample included 115,335 respondents. Chronic medical conditions were common among respondents with weighted percentages of 29.5% of adults reporting 1 chronic condition and 17.4% reporting 2 or more conditions, and therefore 46.9% reported at least 1 chronic condition and 53.1% reported no chronic conditions . Most adults with medical multi-morbidity were middle-aged and older adults , while younger adults were more likely to report no chronic conditions . Compared with adults reporting no chronic conditions, adults with medical multi-morbidity were also more likely to be non-Hispanic white, less educated, married, have nicotine dependence, drink alcohol less frequently, report having worse health status, and more likely to have depression, anxiety, and need mental health treatment in the past year . Table 2 presents frequencies and weighted percentages of specific drugs used by 0, 1 or ≥2 chronic conditions. Overall, 16.1% of the full study sample reported past-year use of an illegal drug or cannabis and 2.6% reported meeting criteria for a SUD. The most common drug used in the past-year was cannabis, and cannabis use disorder was the most common SUD.

Non-medical use of opioid analgesics was the next-most common and opioid-related SUD was the second most common SUD. Among all adults with chronic conditions, past-year drug use was reported by 14.8% with 1 chronic condition and 11.6% with ≥2 conditions, and drug use was considerably higher among adults with no chronic conditions . Among adults reporting no chronic conditions, 5.5% used ≥2 drugs, while 4.3% of adults with 1 chronic disease and 3.2% of adults with ≥2 chronic diseases reported use of > 1 drug in the past year . Criteria for past-year SUD was met by 2.4% with 1 chronic condition and 2.1% with ≥2 conditions, and 2.9% of adults with no chronic conditions . In this large, nationally representative survey, we estimated the prevalence of past-year drug use among adults without chronic medical conditions and among those with one and two or more chronic medical conditions . While the prevalence of past year drug use was lower among adults with medical multi-morbidity, compared to adults with no chronic conditions, nearly 12% of adults with multi-morbidity reported engaging in past-year drug use. The lower prevalence of drug use among adults with multi-morbidity may be due to both the fact that younger adults were more likely to engage in drug use and less likely to have chronic medical conditions, and some of those with multi-morbidity may have stopped using drugs because of their morbidities . In alcohol studies for example, the “sick quitter” hypothesis proposes that adults may stop drinking due to medical illness, hospitalizations, or declining health, and therefore this group is not included as individuals with alcohol-related problems even though alcohol may have contributed to their illnesses . A similar phenomenon is likely occurring in observational studies with drug use including our study. However, we did find in multi-variable models that among adults with medical multi-morbidity, adults with alcohol dependence, current tobacco use, and adults with mental health problems were more likely to have engaged in past year drug use,drying rack cannabis and therefore be at particularly high risk for adverse effects of drug use. This emphasizes the importance of including SUDs and poly substance use disorders to the multi-morbidity framework as a distinct clinical profile that necessitates further research to better care for patients with complex multi-morbid disease . The intersection of substance use and medical multi-morbidity is complex. Drug use has a wide array of physiologic effects on the body, that may negatively impact existing chronic medical disease and complicate its management. For example, cocaine use can impact both the cardiovascular and cerebrovascular systems that can lead to stroke, disability or sudden death, particularly among adults with pre-existing disease . Second, substance use can also complicate the clinical management of existing chronic diseases.

Studies have shown decreased adherence to antiretroviral therapy among adults with HIV who engage in active substance use , and poor medication adherence for adults with psychosis who used cannabis . This is particularly relevant for adults with medical multi-morbidity, who often have complex medication schedules that demand careful monitoring and daily management. In addition, the complicated medical care that adults with medical multi-morbidity face places them at risk for medication management mistakes as well as adverse drug effects and interactions . This emphasizes the importance of substance use screening for adults with chronic conditions. In addition, since many adults in SUD treatment often have fragmented primary care , it is also important for SUD treatment providers to screen and ensure medical comorbidities are being managed. In our study sample, cannabis was the most commonly used drug among adults with chronic disease. This is not surprising since cannabis is the most common drug used in the NSDUH study sample and given more positive attitudes and policies related to cannabis use . Cannabis has been used and studied for medical treatment of chronic diseases including HIV, multiple sclerosis, chronic pain, seizure disorder, and other mental health disorders . Although this study cannot distinguish between medical use versus recreational use of cannabis, using cannabis for these types of conditions may partially explain its high prevalence use among adults with chronic disease . The risks of cannabis have not been well-documented, particularly among older adults with medical multi-morbidity who may be at higher risk for negative cardiovascular, pulmonary, and cognitive effects of cannabis use . Further study is needed to better assess the benefits and risks of cannabis use for specific chronic diseases and overall use by adults with medical multi-morbidity.

The statistically significant correlates of past-year drug use among adults with medical multi-morbidity identified in this study include younger age, male sex, low family income , current tobacco use, alcohol use and alcohol dependence, having had a major depressive episode, and having received mental health treatment. The demographic findings are similar to the overall results of NSDUH among the general adult population for illegal drug use including cannabis, such as adults with younger age and male sex having higher rates of use . However, our results are novel in that they identify a potentially very high-risk population of adults with the combination of medical multi-morbidity with poly substance use and/or mental health disorders. The strong association we found with alcohol dependence with concurrent drug use among adults with medical multi-morbidity is alarming. Unhealthy alcohol use itself can cause, exacerbate, and complicate the management of several chronic medical diseases , and therefore the combination of illegal drug use with alcohol use, especially if used concurrently, can be particularly dangerous for adults with existing chronic medical conditions. Further, the co-occurrence of substance use and SUD with mental health illnesses are well documented , and interventions for addressing patients with co-occurring conditions have been developed and studied . The added mental health comorbidity is particularly important as one recent study of 843,584 veterans in the VA system who had at least three visits to a mental health clinic found 30.6% had co-occurring psychiatric and SUDs . The added burden of poly substance use along with mental health problems highlights the need for a syndemic framework for caring for patients with compound multi-morbidity, where the focus is how multiple health conditions are adversely affected by behavioral, psychiatric, biological, and social conditions. The use of the syndemic framework can help identify intervention strategies to reduce harms and improve the management of chronic disease for adults with medical multi-morbidity, poly substance use, and mental health disorders. In practice, one approach using this framework could include the integration of primary care and chronic disease management into SUD and mental health treatment settings and vice-versa. There are important limitations to this study. First, the NSDUH responses are based on self-report and thus are subject to both recall and social-desirability bias; although the survey attempts to limit the latter via ACASI . Second, the NSDUH does not assess when a respondent fifirst experienced or was diagnosed with a chronic medical disease, but asks only for lifetime prevalence. Therefore, participants may have had a chronic medical condition years before being surveyed and that condition may have been resolved and not overlap with past year drug use. However, most of the conditions queried tend to be lifelong. In addition, while the specific chronic diseases chosen in the NSDUH study design were based on expert opinion of medical diseases that are often related to substance use , it does not include many chronic medical diseases that are often asked in clinical research and epidemiological studies to understand the burden of chronic disease in specific populations. It also does not specify “heart disease” further, thus this could include a wide range of cardiac diseases. Therefore, the generalizability of this study is limited to the specific chronic diseases asked of this study sample and how it was asked. Also, assessing DSM SUD criteria via surveys can also be limited as these are not full diagnostic interviews. Finally, our study classifies users of drugs if the individual used in the past-year and therefore does not distinguish between one-time use versus more frequent use, which may potentially have different risks and consequences.

Analyses proceeded in three stages. First, at baseline and 3, 6, and 12 months follow-up, the percent of participants at risk, and the identified preaction stage for those at risk, were determined for each HRB. Second, LCA was employed to discern the common patterns of HRBs at each time point. Third, LTA was used to examine the most likely patterns of HRBs over time. LCA was employed first at baseline, then each follow-up time point for evaluation of structure stability. LCA is a latent variable modeling technique that characterizes homogeneous populations within a larger sample who share common response patterns to categorical indicators . Models of 1–6 classes were fit and standard criteria were used to compare the models. Model selection was based on goodness of model fit, parsimony, and adequacy of the model with respect to the research questions being posed. Four sets of criteria were used for selecting the optimal number of latent classes in factor mixture models as recommended by Muthén and Muthén. First, the Bootstrapped Parametric Likelihood Ratio Test tested for model improvement in each successive model over a model with one fewer class. Second, the Sample Size Adjusted Bayesian Information Criterion and Aikaike’s information criterion were examined, with lower values indicating better model fit. Third, the entropy value, ranging from 0 to 1, measured the clarity of classification. Entropy values that are close to 1 indicate that a model has clearly identified individuals of different types, and it can be a useful summary measure. Finally, the usefulness of latent classes in practice was evaluated by substantive interpretation of the classes in a given model, as well as the parameter estimates including class membership or posterior probabilities and class-specific conditional response probabilities . With LCA,seedling grow rack observations are classified into their most likely latent classes on the basis of the estimated posterior probabilities for the observations. High diagonal and low off-diagonal values in the class classification table indicate good classification. CRPs reflect the probability that an individual within a particular class has a high-risk health behavior.

Based on the patterns of the estimated conditional probabilities, meaningful labels or definitions of the latent classes were made. LTA was then used to examine the extent to which patterns of HRBs at baseline were stable over time, using three analyses . Detailed statistical presentations of the general LTA framework are available in Humphreys and Janson and Reboussin et al.. LTA is a longitudinal strategy that assesses the probabilistic change in class membership over time with categorical latent variables. This analysis extends LCA by assigning transition probabilities, which are conditional probabilities describing the probability of being in a given state at time = t, conditional on the state at time = t − 1. We used an LTA to model the stability of HRBs over the course of 12 months; latent transition probabilities were then used to evaluate how individuals either exhibited the same HRB pattern or changed patterns over 12 months. We hypothesized a priori that the intervention may affect multiple HRBs, because multiple HRBs can occur following interventions aimed at changing a single behavior. Moreover, we found a significant intervention effect on smoking outcomes at 3 months in the RCT. Therefore, the models initially included treatment condition as a covariate. However, because very few participants transitioned between classes over time, adding treatment condition to the model resulted in several empty cells. For example, no participants in the control condition transitioned from substance use risk to low risk between baseline and 3 months. Because adding another parameter resulted in several empty cells, the estimates were unstable and could not be reliably interpreted. Moreover, treatment condition was not a significant covariate in the LCA models . Therefore, all models reported here are without the inclusion of treatment condition. LCA and LTA were conducted with Mplus version 7.4 due to the availability of multiple model fit indices not available in other statistics platforms and the ease of employing randomized starting values. Other analyses were conducted with IBM SPSS Statistics. All available cases were used at each time point.In our sample of young adult smokers, nearly all reported engaging in at least one other HRB at baseline and follow-up, the most prevalent at each time point being diet related. The most prominent patterns of HRBs at four time points highlighted that the more prevalent targets, in addition to tobacco, for behavioral change in young adult smokers are diet-inactivity, sleep habits, and cannabis use.

The 3-class solution that fit the data best at all time points was similar to that found in a sample of adult smokers in a mental health treatment setting, with profiles for a global high-risk group, consisting of substance use and metabolic risks, and one in which risks were primarily metabolic . Three very similar profiles emerged in two very different samples of smokers , suggesting that metabolic and substance use patterns ought to be assessed and ideally addressed through direct treatment or referral, in the context of smoking cessation interventions. HRB patterns in young adult smokers may differ from those of the general young adult population. Prior research in the general young adult population has found that smoking generally clusters with substance use and sexual risk behavior. In the present study, wherein all participants were smokers, likelihood of engaging in condomless sex did not systematically vary with other HRBs. Employing broader measures of sexual risk behavior may have yielded an association between sexual risk behavior and substance use. However, given the similarities in HRB profiles between the present sample and adult smokers with serious mental illness, it is also plausible that the HRB profiles of young adults who smoke differ from those of the general young adult population.There were notable differences in stages of change for different HRBs that could be informative when adding health-related content to smoking cessation interventions for young adults. Given that overall, participants were most ready to change their diet, stress management, sleep, or physical activity, an intervention targeting the metabolic risk group would likely be well-received. Membership in the metabolic risk group at baseline was associated with a greater likelihood of smoking daily and with smoking more cigarettes per day. Young adult smokers with metabolic risk factors may be a group that would particularly benefit from cessation medications. In contrast, motivation to change alcohol and drug use was generally low, suggesting that an intervention targeting the substance use group may need to especially focus on motivational enhancement. Cannabis use was common among participants in the substance use group, and those at risk for cannabis use were least ready to change this behavior compared to all other behaviors. Heavy alcohol use declined from baseline to follow-ups, while cannabis use remained elevated.

Given previous reported differences in stages of change for tobacco and other substance use among young adults, smokers of all types may be less receptive to interventions targeting other substance use than they are tobacco or other HRBs. The substance use group had a higher proportion of males,greenhouse growing racks suggesting that interventions with young adult male smokers may benefit from a focus on enhancing motivation to change substance use. Although class membership was mostly stable over the course of one year, transitions from low risk to metabolic risk were somewhat more frequent than transitions to substance use risk. This finding may reflect a general decline in substance use throughout one’s 20s and underscores the need for intervention on metabolic risk behaviors among the general population of young adult smokers. Given a significant difference in smoking abstinence between treatment and control groups at the 3 month follow-up in the clinical trial, we hypothesized that participants would be more likely to transition to classes characterized by lower risk if they had participated in the Facebook smoking cessation intervention compared to the control condition at each time point. Results showed that classes were very stable over time, with few participants transitioning between them. As such, the model could not be reliably fit when treatment condition was included. This reflects the notable stability of young adults’ patterns of HRBs over 12 months, which may be due to the demanding nature of multiple HRB change and limits of cognitive capacity and self-control, coupled with relatively low readiness to change. Results suggest extended intervention content enhancing motivation and supporting behavior change for a few HRBs is likely needed to create meaningful change in multiple HRBs among young adult smokers participating in any form of smoking cessation intervention. This study recruited a relatively diverse sample of young adult smokers in the USA. Notably, more than one in four participants identified as a sexual or gender minority . This may have been due to the high prevalence of both smoking and social media use among SGM individuals. Moreover, 8.2% of millennials identify as SGM compared to 3.5% of those in Generation X. In this sample, SGM and non-SGM young adults did not significantly differ in smoking cessation rates or other health behaviors, with the exception of physical activity, over time.

Nonetheless, clustering of HRBs may vary by other individual differences , and future research could examine differences in the clustering of HRBs by individual characteristics. Notably, we identified few differences in latent class membership by individual characteristics, suggesting that the HRB profiles in this study have broad applicability to young adult smokers.Study limitations include that the data were self-reported and subject to recall bias. Due to empty cells when additional parameters were included, we were unable to include treatment condition as a covariate or incorporate stage of change into LCA and LTA models. Future research should incorporate these additional characteristics. The sample was neither randomly sampled nor representative, thereby limiting generalization of study findings; however, as an initial investigation, the volume of HRBs among young adult smokers appears high and the patterns stable over 12 months.Over the past century, California has built an extraordinarily complex water management system with hundreds of dams and a vast distribution network that spans the state. This system generates electricity, provides flood protection, delivers reliable water supplies to 40 million people and supports one of the most productive agricultural regions in the world. Yet development of the state’s water management system has come at a price. Damming waterways, diverting water from rivers and streams and altering natural flow patterns have transformed the state’s freshwater ecosystems, leading to habitat degradation, declines of freshwater species and loss of services that river ecosystems provide, including high-quality drinking water, fishing and recreational opportunities, and cultural and aesthetic values. The state aims to accommodate human water needs while maintaining sufficient stream flow for the environment. To support this mission, scientists from the U.S. Geological Survey , The Nature Conservancy and UC have developed new techniques and tools that are advancing sustainable water management in California. At the center of these new advances is the need to understand the natural ebbs and flows in the state’s rivers and streams. Natural patterns in stream flow are characterized by seasonal and annual variation in timing , magnitude , duration and frequency . California’s native freshwater species are highly adapted to these seasonally dynamic changes in stream flows. For example, salmon migration is triggered by pulses of stream flow that follow winter’s first storms, reproduction of foothill yellow-legged frogs is synchronized with the predictable spring snow melt in the Sierra Nevada, and many native fish breed on seasonally inundated floodplains, where juveniles take advantage of productive, slow-moving waters to feed and grow. When rivers are modified by dams, diversions and other activities, flows no longer behave in ways that support native species, contributing to population declines and ultimate extinction. Thus, understanding natural stream flow patterns and the role they play in supporting ecosystem health is an essential first step for developing management strategies that balance human and ecosystem needs. Unfortunately, our ability to assess alteration of natural stream flow patterns, and the ecosystem consequences, is hindered by the absence of stream flow data. California’s stream flow gauging network offers only a limited perspective on how much water is moving through our state’s rivers. In fact, it’s been estimated that 86% of California’s significant rivers and streams are poorly gauged and nearly half of the state’s historic gauges have been taken offline due to lack of funding .

They do, however, cast further doubt on the strength of empirical support for Miron’s intuitively plausible theory. Figure 10 reveals why the added data from the 1990s onward weakens the estimated relationship between prohibition enforcement expenditures and homicide: federal per capita drug prohibition spending has continued to rise despite a steady fall in the homicide rate. A number of more general problems potentially plague the basic regression specifications: the enormous difficulty of drawing causal inferences from national time series data; the possibility that causality runs in both directions; and the omission of state enforcement expenditures and other possible explanatory factors. However, bearing in mind these various provisos, Miron’s analysis is consistent with, and provides a notable supplement to, more targeted analyses—such as the aforementioned study of New York murders—supporting the theory that criminalization does more harm by the systemic crime and violence it creates than good in any toxicologically-induced crime it may prevent.Related problems with our current approach to cocaine are mandatory minimum sentences and the differential treatment of crack and powder cocaine. As discussed earlier, there is a large racial disparity between African-Americans and Caucasians in terms of the percentage imprisoned for drug-related offenses. Much of this racial disparity is the result of mandatory sentences for possession and trafficking of crack which have been far more severe than those in place for powder cocaine. In the early 1990s, over 90 percent of defendants in crack cases were African-American compared with only 25 percent of defendants in powder cocaine cases .Mandatory sentencing laws for drugs generally prescribe a sentence based on the quantity of the drug in question.

Until just recently,indoor grow shelves under federal sentencing guidelines a defendant needed to possess an amount of powder cocaine one hundred times greater than the amount of crack cocaine in order to receive an equivalent sentence.93 Thus a defendant convicted of possessing 50 grams of crack cocaine with intent to distribute faced a mandatory minimum sentence of ten years whereas a defendant would need to possess 5 kilograms of powder cocaine to expect the same sentence. Though President Obama recently signed the Fair Sentencing Act, which is set to reduce the sentencing disparity ratio from to 100 to 1 to 18 to 1 , a significant differential will remain, and some states also have adopted more stringent sentences for crack cocaine than powder cocaine . Differences in state law treatment of the two drugs have the potential to be more important because more prisoners are convicted of crack offenses at the state rather than federal level each year. In addition to the racial disparities created by mandatory sentencing laws, scholars have also noted additional concerns regarding their implementation. First among these is the fact that drug amounts are determined by mixture weight rather than pure weight. This introduces sentencing distortion because drugs sold in the illicit market vary greatly in their purity. For example, the sale of coca leaf, which contains only 2 percent cocaine, is treated the same as the sale of pure powder cocaine in terms of weight, even though 100 grams of coca leaf has the same amount of cocaine as 2 grams of pure cocaine. The focus on weight also prevents a distinction between large-scale dealers, the “kingpins” of the business, and small time dealers. A “kingpin”may operate in such a way that he carries very little of a drug substance on him at any given time and thus when caught in possession with an intent to sell, receives a lighter sentence than one of his subordinates, who carries larger quantities of the substance in order to make frequent sales. Without the mandatory minimum sentences, judges would have more discretion to differentiate between the “kingpin” and the small-time dealer. Mandatory sentences shift power from judges to prosecutors because prosecutors have discretion concerning whether to charge an individual with a crime carrying a given minimum sentence, whereas once the defendant is convicted, under a mandatory sentencing scheme the judge lacks the discretion to reduce a sentence .

Deciding whether it is preferable to grant more power to judges or prosecutors is a judgment call which depends on whether one believes such power should be vested in the executive or judicial branch; however, the shift in power is a clear impact of mandatory minimum sentencing laws. Given the substantial costs of mandatory minimums, are they necessary or cost-justified deterrence mechanisms? Credible evidence suggests they are not. A 1997 empirical evaluation of the cost-effectiveness of mandatory drug sentences found mandatory minimums are less effective at reducing cocaine use than both conventional enforcement and treatment programs . The authors, part of the RAND Drug Policy Research Center, attempted to measure the effects on cocaine consumption of spending an additional $1 million on conventional enforcement, mandatory minimum sentences, or treatment. Looking at the 184,548 drug dealers convicted in state and federal courts during 1990, the authors estimated that were the federal mandatory minimum drug sentences94 applied to all of these dealers, the cost to the public for the additional prison time would be $22.5 billion. According to the model tested in this study, longer sentences influence cocaine consumption by raising the price of cocaine as dealers increase prices in order to offset the increased probability of a longer prison sentence. Using an estimate that a drug dealer must be compensated an additional $37,500 per additional year of incarceration and a cost to the public of $25,000 per year of incarceration, they estimated that each $1 spent on longer sentences will translate into a $1.50 increase in total costs to consumers of cocaine. Thus they found that an additional $1 million spent on longer sentences would increase cocaine prices by 0.004 percent.95 Over a 15 year time horizon given a dealer discount rate of 12 percent and an elasticity of demand for cocaine of 1, they determined that each additional $1 million spent on longer sentences reduces cocaine consumption by 12.6 kilograms nationwide . Given estimated total annual consumption of 291,000 kilograms, this represents a change far less than one-hundredth of one percent. If one assumes the relationship to be linear over this range,indoor garden table every increase in incarceration costs of $1 billion per year might be expected to reduce cocaine consumption by about 4.3 percent.

When evaluating treatment programs, the RAND authors relied on Rydell’s and Everingham’s study of cocaine treatment reporting that 13 percent of cocaine addicts abstain from hardcore cocaine use in the long-run following treatment and that 79 percent abstain during the 0.3 year length of the average treatment program. Given the $1,740 average cost of a treatment program, an extra $1 million could treat 575 heavy cocaine users, resulting in a 16 kilogram reduction in the first year. Over a 15 year time horizon, given that 13 percent of heavy users quit heavy use following treatment, these authors estimated that each $1 million spent on treatment would reduce cocaine consumption by 103.6 kilograms, compared with 12.6 kilograms for longer sentences, making treatment appear much more effective . While the linearity assumption might be more strained over this range, the comparison to the incarceration-increase numbers is revealing: an annual increase of $1 billion in spending on treatment might be expected to reduce cocaine consumption by 35.6 per cent. These findings are in line with Rydell’s and Everingham’s examination of the effectiveness of treatment compared with three other drug enforcement policies: source country control , interdiction and domestic enforcement . The authors found that the cost of crime and productivity loss from cocaine use decreases by $7.46 for every $1 spent on treatment whereas the same figure for source country control is $0.15 per dollar, $0.32 for interdiction, and $0.52 for domestic enforcement. Rydell’s & Everingham’s initial study was criticized for underestimating the decrease in cocaine use stemming from increases in cocaine prices due to source-country control, interdiction, and domestic enforcement. Repeating their study of policy effectiveness in 2000 assuming a more elastic demand for cocaine, Caulkins, Chiesa, and Everingham determined that treatment has a four-to-one advantage over domestic enforcement in reducing the costs of crime and productivity losses. Overall, this evidence on treatment versus severe punishment for those found possessing or dealing cocaine today suggests that mandatory treatment for drug offenders is a more cost effective solution. As with marijuana policy, there appear to be many potential improvements for cocaine policy, even within the regime of criminalization. In the United States—indeed, throughout the world—many individuals are drawn to substances that may harm them greatly. Public policy varies enormously with respect to these substances, partly based on the degree of addiction, the nature of harms, and historical experience. Though sugar, saturated fat, and high fructose corn syrup impose enormous health costs, regulation to discourage consumption of them is virtually non-existent; in fact, corn subsidies in particular have been criticized for perversely incentivizing poor diets. In contrast, tobacco and alcohol are subject to considerable regulation while remaining legal, and a host of drugs ranging from heroin and cocaine to methamphetamine, ecstasy, LSD, and marijuana are banned by state and federal law. Tobacco imposes high costs on a large proportion of users because the addiction is powerful and the health cost of decades of use will likely be great. Nonetheless, consumption rates tend to be high because the health costs are temporally distant, and governments tend not to prohibit consumption because current productivity and parenting ability are not discernibly impaired. Interestingly, perhaps the greatest domestic success in reducing consumption of harmful substances came for this lawful product, engineered largely through tax hikes via the settlement of tort litigation against the tobacco companies. Other harmful recreational substances vary in terms of addictiveness and the ability of large numbers of users to enjoy them sporadically and without substantial health cost or productivity impairment for work and parenting. But for sizeable percentages—perhaps 10 percent for marijuana users, 15 percent for alcohol and cocaine users, and almost 25 percent for heroin users —the personal and social costs are dramatic and substantial. It is largely to reduce these costs to this minority of users that governments have banned, and tried to keep as many people as possible away from marijuana, cocaine, methamphetamine, and heroin . Estimates placing the economic costs of illegal drug abuse at levels roughly comparable to those costs for alcohol and tobacco underscore that there are no easy choices when it comes to drug policy. Aggressive efforts to limit consumption through a tough penal approach tend to restrain the costs from drug use while unleashing the high costs of enforcement and incarceration in a context of increased violence centered around the criminal gangs that run the drug trade. Conversely, legalization of alcohol and tobacco drastically reduces enforcement costs with respect to these substances while keeping the costs of consumption high. A cost-minimizing approach to drug policy might move us away from a punitive approach to control of the currently illegal drugs, while entailing aggressive measures to prevent underage consumption and constrain demand. On the other hand, while thorough consideration of policy toward legal drugs is beyond the scope of the present inquiry, comparisons of their toxicological effects and social costs with those attributable to such illegal drugs as marijuana and cocaine suggest that more vigorous pursuit of demand-restraint policies for alcohol and tobacco may result in a reduction of the social costs of those drugs. At some point, insights from social science and medical testing may be refined enough, and widely enough disseminated, to enable potential users to secure better advance notice regarding their particular susceptibility to the serious consequences of drug and alcohol abuse. At present, many individuals find out the hard way, at great cost to themselves and society. Despite the problem of moral hazard, greater treatment seems to offer a more cost effective method for dealing with these abusers than criminal penalties. Our analysis has also underscored that optimal drug policy is likely to differ from one drug to another, since, for example, the impact of government policies—current and hypothetical—may be substantially different for an extremely prevalent drug with relatively mild toxicological effects, such as marijuana, than for a far less common, but more addictive and dangerous drug, such as cocaine.