Future studies will need to elucidate the mechanisms responsible for increased renal 2-AG levels in IRI and its potential utility as a therapeutic agent. The COVID-19 pandemic poses great challenges for older adults and their families, support systems, caregivers, and medical and mental health care providers. Increased mortality among older adults following infection with SARS-CoV-2, the novel coronavirus, is now well established. Older people already are vulnerable to the detrimental effects of isolation and face disproportionate adverse consequences from social distancing and shelter-in-place guidelines, which may trigger or worsen anxiety, depression, substance use, and other psychiatric disorders. As long as social distancing guidelines remain in place, older adults in recovery from substance use disorders may find themselves cut off from support if they are unable to effectively use online treatment and self-help resources. Here we outline several key areas of clinical concern for mental health providers who work with older patients as well as issues for consideration in future COVID-19 research.Alcohol is the substance most commonly used across the age span, and can lead to severe medical, functional, and psychiatric problems for older adults, as well as sleep disruption, falls, and other injuries and accidents. Unhealthy alcohol consumption is associated with a number of chronic medical conditions common in older adults.Of particular concern, suicide risk is elevated among older adults with both depression and alcohol use disorders. In 2015−2017, 10.6% of adults over 65 reported unhealthy drinking in the prior 30 days, an increase over previous years.Current National Institute of Health guidelines recommend that adults age 65 and over consume no more than 7 drinks per week and no more than 3 drinks in 1 day. However,cannabis hydroponic set up for older adults with common medical conditions or psychiatric disorders there may be no level of safe alcohol use. Because alcohol-related immune system impairment increases susceptibility to pneumonia and other infectious disease, minimizing alcohol consumption may be critical for older adults during the pandemic.

Providers working with older patients, either in-person or using remote technologies, should ask about current quantity and frequency of alcohol use and about any recent increases in drinking that may be connected to social isolation or financial stressors, anxiety, depression, or suicidal ideation. Pharmacologic treatments for alcohol use disorders and brief behavioral interventions such as motivational interviewing for patients with lower-severity alcohol problems can be effectively integrated into care, even with increased use of telemedicine.Although tobacco use in the United States has decreased over time, about 8% of adults aged 65 and over smoked cigarettes in 2018.In contrast, the proportion of adults 65 years and older who reported prior year cannabis use increased from 2.4% in 2015 to 4.2% in 2018, with a greater increase among those who reported receiving mental health treatment or who also used alcohol.There is strong evidence that smoking tobacco puts people at risk for more severe COVID-19- related symptoms; data from China indicate a case fatality rate of 6.3% for individuals with chronic respiratory disease, compared with 2.3% overall.Vaping nicotine is thought to be less harmful than combustible tobacco yet there are also growing concerns that vaping nicotine may damage lungs in ways that make users especially vulnerable to COVID-19-related symptoms.In the context of the pandemic, providers should advise older adults to eliminate smoked tobacco and nicotine vaping, and encourage patients to use nicotine replacement or anticraving medications such as bupropion. Among older adults, smoking cessation reduces cardiovascular and other health problems,likely improving COVID-19 survival chances. For people using cannabis, edible forms of cannabis should replace smoking or vaping. Finally, providers should remain alert to adverse effects of cannabis on older adults including falls, anxiety and dependence.Older adults have higher rates of chronic pain than younger adults and are more likely to be prescribed opioids ,leading to potential for dependence over time. As with younger adults, older people who misuse opioids are likely to have comorbid psychiatric and other substance use disorders.

The COVID-19 pandemic poses substantial challenges to effective pain management and to addiction treatment for older adults. For those who use medications as prescribed, interruption of regular medical visits is a barrier to careful monitoring. Among individuals with an opioid use disorder who are engaged in treatment, care disruption may lead to decreased access to methadone, buprenorphine, naloxone treatment for overdose, as well as critical social services.Lack of treatment access, in combination with social isolation, increases vulnerability to relapse and overdose for older adults during the pandemic. Older adults are also at higher risk of experiencing negative effects of benzodiazepines, commonly prescribed for anxiety and insomnia.Between 2010 and 2016, among older adults in the Veterans Administration, the prevalence of benzodiazepine use has ranged from approximately 9%−11% and incidence of new prescriptions has held steady at approximately 2%.As of this writing, there are no published data regarding changes in benzodiazepine prescription rates associated with COVID-19; however, previous research has demonstrated increased use associated with disaster situations.The American Geriatrics Society Beers Criteria strongly recommends avoiding benzodiazepine use, except in specific circumstances , because of the potential for cognitive impairment, falls, fractures, motor-vehicle accidents, other serious injuries, and delirium.These hazards may be magnified by concurrent alcohol consumption, illicit substance and opioid use, and opioid-replacement therapy with methadone or buprenorphine.Since the 1970s, Dutch drug law and policy have moved away from punitive prohibition toward a harm reduction model, with the objective of minimizing the harms associated with both drug abuse and drug policy. Scott Jacques, Richard Rosenfield, Richard Wright, and Frank van Gemert investigate whether the de facto decriminalization of cannabis in the Netherlands, with its semi-licit system of licensed retail sales in “coffee shops,” reduces the crime and violence often found in illicit drug markets.

I say “de facto decriminalization” and “semi-licit system” because, as the authors note, the Dutch have made it effectively legal for anyone older than 18 years of age to walk in the front door of coffee shops and buy small amounts of cannabis, but it remains illegal to bring supplies of that cannabis in the back door of coffee shops. This “back door problem,” as the Dutch call it, has caused trouble for coffee shop owners and growers and no shortage of debate in Parliament. But for decades, coffee shops have functioned reasonably well within this legally ambiguous space, with cannabis finding its way to consumers with few problems and little policing. To contextualize Jacques et al.’s contribution, it may be useful to recall how cannabis was criminalized and why the Dutch departure from criminalization is historically significant. Until the Netherlands shifted its drug policy toward harm reduction in 1976, cannabis was prohibited around the world on pain of criminal punishment . Cannabis criminalization began with “the malevolence assumption” , which still serves as its logical fundament. In national legislative histories, deliberations over the United Nations’ drug control treaties that globalized cannabis criminalization, or current claims by those who still defend it, one finds the same premise: Cannabis is so dangerous it cannot be allowed to be legally available. Dutch cannabis policy is interesting largely because it challenges this premise.U.S. officials cultivated the malevolence assumption. The legal status of cannabis was initially transformed from a prescribed medicine into a proscribed vice by the moral entrepreneurship of the Bureau of Narcotics during the Great Depression . A 1934 Bureau report to the League of Nations, for example, asserted that “fifty percent of the violent crimes committed in districts occupied by Mexicans, Turks, Filipinos, Greeks, Spaniards, Latin Americans and Negroes may be traced to the abuse of marijuana” . Beyond stoking racial and ethnic prejudice that demonized cannabis users,hydroponic system for cannabis the Bureau also generated fear around the effects of cannabis itself. The report approvingly quoted a narcotics officer who claimed that “Marijuana has a worse effect than heroin. It gives men the lust to kill, unreasonably, without motive – for the sheer sake of murder itself” . In 1936, just prior to passage of the Marijuana Tax Act of 1937 that criminalized cannabis in federal law, the Bureau-sponsored film, Reefer Madness, depicted American youth smoking a few puffs of cannabis and quickly engaging in wild sex, assault, and even homicide. When cannabis use spread among White middle-class youth in the 1960s, however, the alleged malevolence shape-shifted: Then drug control officials claimed cannabis caused not violence but an “amotivational syndrome” that sapped energy and ambition, leaving a generation of stoners.The Bureau helped lead the drive for global cannabis criminalization, which reached fruition in a 1961 UN drug control treaty.The Netherlands is a signatory to this treaty, so how did the Dutch manage—in splendid isolation until recently—to avoid the malevolence assumption and demonization and to effectively decriminalize cannabis ? .First, the Netherlands has long been known for its culture of tolerance , which has deep roots . With nearly half their land mass below sea level, the Dutch have always faced the primal threat of inundation. But as the enemy sea could not be defeated, they learned to accommodate it with dykes, pumps, and sluices that channel it in less harmful directions. The Netherlands also has a long history of bloody religious wars, being on the front lines of Europe’s Reformation battles.

Slowly the Dutch developed a pluralist state structure in which Protestants, Catholics, and later others agreed to tolerate each other under the same civic roof to the benefit of all . The pragmatic advantages of pluralism and tolerance were further highlighted by centuries of Dutch success in international trade . Add to this history the painful experience of Nazi occupation during World War II and you can see why tolerance remains woven into the cultural DNA of the Netherlands. Their pioneering move to a harm reduction drug policy was a natural extension of Dutch gedogen. Second, the officials who developed modern Dutch drug policy had an intuitive understanding of labeling theory and the risks of punitive prohibition. Their first moves toward cannabis decriminalization were based on reports from two expert national commissions in the late 1960s . Neither expressed moral approval of drug use, but both paid close attention to evidence showing that although experimentation was common, addiction was rare and controlled use was the norm. The culture of tolerance allowed both commissions to distinguish between acceptable and unacceptable risks, which led them to propose separating the market for cannabis from the market for riskier drugs. And both emphasized the importance of avoiding punishments likely to stigmatize and marginalize users, thereby intensifying their deviance and making it harder to return to socially accepted lifestyles. These consequences were the type labeling theorists hypothesized—what Lemert called “secondary deviance” and Becker described as developing deviant identities and careers. Both commissions concluded that cannabis use should be removed from the province of criminal law.Third, there is flexibility in the Dutch legal culture, starting with a preference for informal over formal social controls whenever feasible . The Dutch legal system distinguishes between law and policy and operates under “the expediency principle” , which is also part of European Union law; the words in Dutch denote something that is suitable and well timed. This principle allows prosecutors wide latitude to decide whether enforcing a law makes sense as practical policy “in the public interest” . As a matter of statutory law, cannabis remains criminalized, but the Dutch Prosecutors General have decided that enforcing that law is not expedient or practical and so have made it national policy to not enforce it. In short, Dutch policy makers had a more open juridical path to decriminalization than policy makers elsewhere.Returning to the article at hand, Jacques et al.’s beginning premise is that “prohibition undercuts the state’s regulatory capacity by producing zones of virtual statelessness” where law and legal means of dispute resolution are not available, which in turn increases the likelihood of victimization and extralegal retaliation. The Dutch Opium Act of 1976 that allowed cannabis sales and “separation of markets” was designed to reduce some of theseillicit market risks and had the added virtue of constricting the geography of any potential “gateway” from cannabis to harder stuff. Jacques et al. hypothesized that illegal drug sellers would be more often victimized, and in response be least likely to mobilize law and most likely to retaliate; that legal sellers of alcohol in cafes would be least victimized, most likely to mobilize law, and least likely to retaliate; and that the semi-licit cannabis sellers in coffee shops would fall in between.

Products like SensePlace2, Twitter-based event detection and analysis system, DataSift, Gnip, SABESS, and others, enable those interested in crime or emergency detection to gather and aggregate publicly-available, geo-located, time-stamped information in real time about where and when an incident may have occurred, who was involved and how serious it was. Because these data are publicly available, issues that other forms of remote sensing bring up in terms of the invasion of privacy are avoided. Further, because reports are on the ground and produced by humans, they may offer information on the context of crimes and their perpetrators and an interpretation of the events that took place rather than leaving this work up to far-removed remote sensing analysts. While connectivity in rural areas is more limited than in urban spaces, the Pew Research Group has found that as of January 2014, 88% of rural Americans have a cellphone and 43% of rural Americans have smartphones, making such data gathering feasible in these areas. Landscape-scale ecological data: Remote sensing of large-scale cannabis production can be validated using landscape-scale ecological data, as well. Down-stream water quality is one way remote sensing of these grow sites can be validated, for example. Large-scale outdoor cannabis grow indoor production can threaten water quality through water diversion, erosion and sediment deposition due to grading, terracing, road construction, deforestation and clearing; as well as the inputs of harmful chemicals or other pollutants, such as rodenticides, fungicides, herbicides, fertilizers, trash, human waste, gasoline, oil and insecticides, into local water sources.

Using stream water quality analysis that picks up the chemical signatures of such pollutants may be one way to affirm that remote sensing analysts were correct in their characterization of given drug production sites. Though no studies using this approach to detect upstream drug growth exist to date, similar methods have been used in the early detection of sudden oak death. Stream monitoring efforts are able to detect Phytophthora ramorum even before signs of infection are even visible from over-flights. Surveys of local populations: The U.S. Bureau of Justice Statistics has conducted a National Crime Victimization Survey since 1973. This survey asks a representative sample of the national population about the frequency, characteristics and consequences of crimes they have experienced. This survey allows the Bureau to estimate the likelihood of victimization for certain subsets of the population in given areas. Because only 90,000 households spread across the United States are surveyed each year,these statistics are too dispersed be used for targeted accuracy assessments of remotely sensed crimes. The techniques used by the Bureau of Justice Statistics may be helpful for this purpose, however. This survey uses in-person or phone interviews that are strictly confidential about the nature of victimizations, where they occurred, the victim’s thoughts as to why these crimes happened and where they happened. Using structured phone interviews in the regions surrounding the remotely sensed sites of crime might be another manner in which analysts could assess the accuracy of their analyses. Conducting such interviews would, of course, require serious attention to maintaining the security and confidentiality of respondents, as well as the security of interviewers themselves. As we pointed out in the Introduction, different crimes occur over different spatial and temporal scales.For example, crimes taking place over larger geographical areas and longer periods of time will be easier to validate.

The second order validation methods we propose here together would be most useful in validating crimes occurring over longer periods of time and larger geographical areas. LBSN can, and has been, used in detecting crimes that happen rapidly and over smaller geographical areas, however. Because this is one of the first efforts in a hopefully fruitful conversation of the topic, we hope that future explorations will explore techniques that are scale specific.Although disparities in life expectancy among PWH continue to persist, there is an increasing prevalence of PWH 50 years of age and older.In addition, a proportion of incident HIV infections is occurring in older adults.As a result, some estimates indicate that over 70% of PWH will be 50 years of age or older by 2030.Compared to people aging without HIV, people aging with HIV experience a greater burden of aging-related conditions, including neurocognitive impairment, kidney disease, liver disease, osteoporosis, cardiovascular disease, and frailty.Understanding the interaction between HIV infection and aging is a high priority to best manage care and treatment for older PWH.In 2009, the annual International Workshop on HIV and Aging began as an effort to address the needs of aging PWH and as a unique opportunity to engage in scientific dialog about the clinical care of, and research with, people aging with HIV. The workshop has three goals: to stimulate and guide research that will enable better treatment methods and strategies for older PWH, to encourage young investigators to engage in research and clinical care of older PWH, and to foster collaborations among investigators, clinicians, advocates, and PWH. For the past decade, the workshop has brought together experts in pertinent cross-disciplinary fields, including basic mechanisms of aging, HIV biology and pathogenesis, clinical geriatrics, endocrinology, pharmacology, neurology, psychology, and social work. The 10th annual International Workshop on HIV and Aging was held on October 10 and 11, 2019, in New York, NY. In this study, we present a summary of the key oral presentations from the workshop, beginning with the current HIV epidemic both in high-income countries and in SubSaharan Africa, and then reviewing advances in understanding phenotypes that overlap between aging and HIV, such as frailty. We also summarize presentations related to factors that contribute to these aging phenotypes, including pathogenesis such as increased coagulation and social factors such as loneliness.

Current morbidity for PWH can be categorized into physical health morbidity , mental health morbidity , co-infections , and syndromes .Prevalence estimates of these morbidities in PWH vary. For example, globally, COPD prevalence is estimated to be 10.5%, 3% of PWH were co-infected with tuberculosis in 2017, 7% of PWH are co-infected with hepatitis B virus, and 6% of PWH are co-infected with hepatitis C virus.A systems biology approach over the life course will consider how factors earlier in life affect future burden of HIV associated comorbidities, co-infections, and complications.In addition, a ‘‘geroprotectors approach’’ to devise interventions that target common mechanisms of aging and delay the onset of more than one age-related disease at the same time may be especially relevant for PWH.With effective test and treat interventions now stimulated by Ending the HIV Epidemic in cities and countries worldwide, the risk profiles for comorbidities among PWH will likely shift.Overall, PWH will continue to age, but simulation models suggest that risk profiles and burden of outcomes will differ for sub-populations of PWH .Changing exposures to duration of uncontrolled viremia before ART initiation, antiretroviral drugs, and early- and mid-life intervention opportunities may also affect future morbidity. Those who have been infected more recently and have benefited from test and treat initiatives in the Treat All era, initiating ART immediately after HIV diagnosis with less toxic ART, may have a reduced burden of comorbidities as they age, compared to those with prior exposure to more toxic ART and longer durations of pretreatment viremia. In addition, there may be more opportunity for early- and mid-life interventions to reduce the prevalence of traditional risk factors for age-related comorbidities through HIV clinical care.Following the initiation of HIV treatment, long-term viral suppression, longer-term effects of current antiviral drugs , and changes in lifestyle behaviors, including substance, use will also influence the future burden of morbidity in PWH.In conclusion, interventions to address HIV-associated comorbidities, co-infections, and complications remain essential to reduce future morbidity for PWH and improve quality of life, even as efforts progress toward ending HIV epidemics around the world32,41; it will be important to consider how these interventions may need to be tailored for different sub-populations of PWH.As ART roll out continues to expand in low- and middle income countries, the aging of the HIV epidemic will be mirrored in sub-Saharan Africa,vertical farming supplies which is home to 70% of the world’s HIV epidemic. The associated increased life expectancy of PWH in this setting will lead to increases in HIV prevalence among older adults.Indeed, modeling by Hontelez et al. using South African data suggests that HIV prevalence among people older than 50 years will nearly double in the next 30 years, and the absolute number of similarly aged PWH will triple in the same period.To sustain the benefits of global investments in HIV care in Africa, there is a need for increased research on determinants of health and quality of life for older PWH in sub-Saharan Africa. To date, most studies of aging with HIV in the region have been cross-sectional, have focused on single comorbidity domains , and lack insight about local preferences for quality of life . In addition, available evidence suggests that some determinants of HIV-associated comorbidities among older PWH in Africa differ from those in the United States and Europe.For example, increased exposure to biomass cooking fuel commonly used in sub-Saharan Africa has been found to be associated with higher odds of metabolic syndrome among PWH in the Eastern Democratic Republic of the Congo.Host genetic predictors of kynurenine pathway of tryptophan metabolism and increase in K/T ratio also have been associated with an increased risk of atherosclerosis, depression, AIDS-related cancer, and all-cause mortality in Ugandan PWH.Elucidating these determinants and their relative contributions to comorbidities among older PWH in sub-Saharan Africa is essential to developing effective interventions to optimize health for a growing population of older PWH in this region.This will require investment in training and research infrastructure for HIV and aging in subSaharan Africa.

Understanding the evolution of frailty can help researchers identify the implications of and interventions for frailty in the context of HIV and aging. In the 1980s, frailty and disability were often considered synonymous, which caused problems in geriatric care and research due to the lack of specificity.The following decade saw an effort by researchers and clinicians to differentiate aging from disease, and further distinguish multi-morbidity, disability, and frailty, which were thought to be different from aging itself. Furthermore, frailty began to emerge as distinct from all of these. Over the last two decades, researchers have identified frailty not only as a unique medical syndrome linked to a particular underlying pathobiology that is aging related but also likely accelerated by catabolic disease.More recently, through the efforts of the National Institute on Aging leadership in geroscience, there is an emerging central thesis of shared biologic pathways that are aging associated and aging driven, which emerge in the presentation of a frailty syndrome and in disease development.The frailty phenotype,the theory for which was operationalized in the Cardiovascular Health Study and later validated in U.S. community-dwelling cohorts,includes five primary characteristics: shrinking, weakness, slowness, poor endurance, and low activity. Individuals with none of the five characteristics were classified as non-frail, those with one or two characteristics as prefrail, and those with three or more as frail. This identification of a constellation of symptoms and signs as diagnostic is consistent with the definition of a clinical syndrome. In subsequent studies, frail individuals had the highest risk of adverse health outcomes when compared to those who were nonfrail or prefrail, independent of disease.When examined together, studies from 1998 to 2008 show that frailty is clinically observable; is not synonymous with multi-morbidity, disability, or extreme old age; increases with age and varies by race and gender; behaves as a clinical syndrome; predicts disability and mortality independent of disease; and is associated with inflammation, and dysregulation of each of the core physiologic systems that regulate stress response and maintain homeostasis.It has a natural progression, with those who are prefrail at the highest risk for becoming frail and those who are frail at highest risk of dying within the next 6–36 months, depending on severity of frailty.Energy is a key factor in frailty, including energy homeostasis, energy production and utilization, and energy dysregulation. Energy is a driver at every level of the syndrome, cellular, physiologic, and phenotypic. When the individual is stressed, such as in challenge studies , frail, prefrail, and nonfrail can be clearly differentiated by the degree of response and rapidity in return to baseline, with the response to stressors in frail delayed and exaggerated, compared to the nonfrail.

The low dose and high dose particpants had detectable levels of CBN, THC, CBG, THC-V, and THCA-A following consumption of the joint. CBD was detected in the low dose participant immediately after smoking. THC was also detected in the placebo participant prior to smoking the joint. THCCOOH-gluc, THC-gluc, 11-OH-THC, and THCCOOH were not detected in any of the oral fluid samples tested.This work expands upon the prior knowledge of working with OF collected in the Quantisal devices and LC-MS/MS methods to simultaneously quantify ten cannabinoids. The simplistic design of this method was intentional to demonstrate feasibility in future use in driving under the influence of cannabis testing. Various parameters were optimized during method development. We evaluated multiple SPE bed volumes , with multiple combinations of washing and elution conditions . Additional LC columns evaluated included X Select HSS C18 2.5 μm beads 2.1 mm × 150 mm, XSelect HSS T3 2.5 μm beads 2.1 mm × 75 mm, and HSS PFP 1.8 μm beads 2.1 mm × 50 mm using either acidified methanol or acetonitrile based mobile phase buffers. Electrospray ionization in positive and negative ion mode was completed on each analyte. Ultimately, each parameter described in the method was selected based on largest peak area with highest signal to noise, while providing sufficient chromatographic separation. All analytes in this method had an inter-day analytical bias ± 15% with an imprecision ≤15% CV. Extraction efficiencies and matrix effects were similar to previous studies. The deuterated internal standards accounted for any extraction or matrix effects allowing for the quantification of analytes within ± 20%. Similar to Desrosiers et al., CBD-d3 was selected as the internal standard for THC-V and CBG,indoor garden table since at the time of validation no deuterated internal standards were available for these two compounds.

A quantifier to qualifier ion ratio flag was observed at 0.4 ng/mL for CBG resulting in an elevated LLOQ for CBG to 1 ng/mL. THC-d3 was employed as the deuterated internal standard for THCA-A due to the closeness in retention time. THCA-A had the lowest extraction efficiency and largest matrix effect of all the cannabinoids tested. This is likely due to the adhesiveness of this molecule to glass and plastics used throughout the procedure. We did not detect 11-OH-THC, THCCOOH, THC-gluc or THCCOOHgluc in the first three participants of each group using this method. However it does seem unlikely that glucuronidated molecules will be present above those lower limits in oral fluid, since concentrations of THC-gluc in blood following controlled cannabis smoking were < 1.1 ng/mL. Negligible amounts of THC-gluc in OF has been suggested by the lack of increased THC concentrations following glucuronidase treatment. The lack of 11-OH-THC and THCCOOH in OF collected using quantisal devices is not unexpected as other published works have measured these analytes in the 0.01–0.35 ng/mL range, which is below our LLOQ in this method. Furthermore, THCCOOH has been notoriously difficult to quantify using OF collected from the quantisal device with most methods utilizing 2-dimensional GC–MS or atmospheric pressure chemical ionization LC-MS/MS with a enzymatic hydrolysis to enrich the THCCOOH pool. The inclusion of THCCOOH in OF was suggested to confirm direct inhalation and help establish a limit to rule out passive exposure. However, due to the analytical difficulties of measuring to such a small concentration THCCOOH is likely to be only useful to rule in consumption with a negative result unable to accurately rule out. We included THC-V, CBG, and THCA-A in this method to incorporate as many available cannabinoid markers as possible since this method will be used to support pharmacokinetic and pharmacodynamics studies of marijuana use. This method differs from previous methods measuring cannabinoids in OF after solid phase extraction such that this method quantifies 10 cannabinoids, whereas others have measured 6–8 in one method.

The recreational and medicinal properties of cannabis-derived preparations have been known for centuries. The pharmacological actions of cannabis have been ascribed to its major constituent, D 9 -tetrahydrocannabinol, which binds with high affinity to specific cannabinoid receptors, named CB1 and CB2 . Both receptors belong to the super family of G protein-coupled membrane receptors, inhibit adenylate cyclase and N– and Q-type calcium channel activity and stimulate potassium channel conductance . Despite these similarities, substantial differences in the primary structures of these receptors as well as in their anatomical distribution have been reported . Although expressed throughout the body,CB1 receptors are particularly abundant in the central nervous system , where they mediate the psychotropic effects of cannabimimetic drugs . By contrast, CB2 receptors have been primarily found in immune cells, suggesting a possible contribution of this receptor sub-type to cannabino idmediated modulation of the immune response . Just as the finding of opiod receptors led in the 1970s to the discovery of a series of morphine-like chemicals in the brain — the enkephalins and the endorphins —the identification of cannabinoid receptors has prompted a vast search for their naturally occurring ligands. As a result, two endogenous substances displaying cannabinoid-like effects have been identified , arachidonoylethanolamide and 2-arachidonoylglycerol . Unlike classic neurotransmitters, anandamide and 2-AG are not stored into synaptic vesicles, but are produced upon demand through the cleavage of two distinct membrane phospholipid precursors . This reaction appears to be initiated by activation of neurotransmitter receptors, as indicated by the enhanced outflow of anandamide in rat striatum following stimulation of dopamine D2-family receptors . Similarly, application of cholinergic agonists has been shown to increase 2-AG production in the rat aorta . After its release, anandamide is inactivated by carrier-mediated transport into cells followed by intracellular hydrolysis, catalyzed by a rather non-selective amidohydrolase enzyme . 2-AG, which may be taken up by cells through the same transport system as anandamide , is hydrolyzed intracellularly into glycerol and arachidonic acid by enzyme systems that include anandamide amidohydrolase and an uncharacterized monoacylglycerol lipase .

In intact astrocytoma cells, however, the contribution of anandamide amidohydrolase to anandamide hydrolysis appears to be minor, as indicated by the ineffectiveness of amidohydrolase inhibitors to prevent 2-AG metabolism . The discovery of natural agonists at cannabinoid receptors and the identification of their biochemical pathways of formation and inactivation have spurred new interest on the physiological roles of these molecules throughout the body. These efforts have led to the identification of a possible regulatory function of the endocannabinoid system in the processing and execution of motor behaviors.The ability of cannabimimetic drugs to influence motor and cognitive performances is well documented . Indeed, cannabinoid administration in animals is accompanied by profound effects on motor behaviors , which include catalepsy, decreased motor activity and attenuation of d-amphetamine-induced hyperactivity and stereotypy . In humans, marijuana intoxication causes impaired performances in tests requiring fine psychomotor control . Moreover, cannabinoid substances produce a large spectrum of psychotropic effects, including euphoria, working memory deficits and altered perception of space and time . The psychomotor effects of cannabimimetic drugs are consistent with the anatomical distribution of CB1 receptors, which are highly expressed in areas of the CNS that play a key role in the regulation and planning of motor actions, such as the basal ganglia, cerebellum and neocortex . In keeping with this distribution, the inactivation of the CB1 receptor gene by homologous recombination produced a phenotype characterized by severe motor impairment and functional reorganization of the basal ganglia , a forebrain region involved in the sensorimotor and motivational aspects of behavior . Furthermore, in vivo microdialysis studies carried out in the rat striatum have shown the presence of extracellular levels of anandamide, which are modulated by activation of dopamine D2-family receptors . These observations not only indicate that anandamide represents a primary component of the network of neurochemicals in the striatum, but also suggest a possible cross-talk between the endocannabinoid system and other neurotransmitters regulating basal ganglia functions. Although conclusive evidence for such interactions is still lacking,microgreens grow rack neuroanatomical studies have shown that striatal CB1 receptors are mainly localized in GABA-ergic medium-spiny neurons and are co-expressed with m -opioid receptors . Moreover, it is known that exogenous administration of cannabinoids can inhibit the stimulation-evoked release of striatal neurotransmitters, such as g -aminobutyric acidand regulates proenkephalin mRNA levels in the striatum .There is substantial evidence supporting a role for the cannabinoid system as a modulator of dopaminergic activity in the basal ganglia. Administration of exogenous cannabinoids was found to increase dopamine release in rat nucleus accumbens and to excite dopaminergic neurons in the ventral tegmental area and substantia nigra . However, other studies indicate that cannabinoids potentiate the behavioral effects of dopamine antagonists and reduceelectrically evoked dopamine release from rat striatal slices . The possibility suggested by these results, that cannabinoids may regulate dopamine functions is supported by several biochemical and behavioral studies. In vivo experiments indicate that chronic treatment with dopamine D2-family receptor antagonists up-regulates CB1 receptor expression in the rat striatum . Further, injection of cannabinoid receptor agonists into the basal ganglia counteracts the motor responses of locally administered D2-receptor agonists . Even further, the hyperactivity associated with post-synaptic D2 receptor activation is accompanied by a dramatic increase of anandamide output in the striatum and is potentiated by the CB1 antagonist SR141716A . In keeping with these results, administration of the anandamide transport blocker, AM404 , has been shown to counteract several characteristic responses mediated by activation of post-synaptic D2-like receptors, such as apomorphine-induced yawning and quinpirole-induced motor activation . Taken together, these data point to a key role of the endogenous cannabinoid system in the regulation of psychomotor activity, and suggest that this system may offer a therapeutic target in pathologies involving a dysregulation of dopamine neurotransmission.The potential therapeutic use of cannabinoids for the treatment of psychomotor disorders is not only a matter of speculation. Indeed, pre-clinical studies have shown that blockade of CB1 receptors may be beneficial in the management of dyskinesias resulting from prolonged dopaminebased therapies in Parkinson’s disease . Furthermore, oral administration of D 9 -THC has been reported to alleviate tics and compulsive behaviors in patients affected by Tourette syndrome .

Certain similarities between cannabis intoxication and some psychotic symptoms have focussed the attention of psychiatrists on the possible involvement of cannabinoids in the pathogenesis of schizophrenia . Heavy cannabis use may precipitate a toxic psychosis in individuals with a previous history of psychotic illness . This observation has led to propose a ‘cannabinoid hypothesis of schizophrenia’, which postulates that the psychotic symptoms of this disease result from a over-activity of the endogenous cannabinoid system . In accordance with this theory, clinical trials of the CB1 receptor antagonist SR141716A, as a novel antipsychotic, are currently under way. However, down-regulation of CB1 cannabinoid receptors resulting from exposure to high levels of cannabinoid drugs may dampen the ability of the endogenous cannabinoid system to counteract dopamine actions, thus contributing to the manifestation of psychotic symptoms. This possibility is supported by the observation that chronic treatment with D2- family antagonists results in up-regulated expression of CB1 receptor mRNA in striatum , and by the finding that the behavioral responses induced by d-amphetamine — a screening test for antipsychotic drugs — are blocked by D 9 -THC administration in non-habituated animals, but are potentiated in animals made tolerant to cannabinoids . In this context, the elevated levels of anandamide found in the cerebrospinal fluid of schizophrenic patients might result from a homeostatic adjustment of the endogenous cannabinoid system to a functional hyperdopaminergia, rather than being a direct cause of psychosis. Likewise, the propensity of schizophrenic patients to consume more cannabis than normal individuals might be interpreted as a misguided attempt to ‘self-medicate’ the symptoms caused by a dysregulation of dopamine neurotransmission. Further investigations aimed at measuring CB1 receptor expression and determining the neuronal origin of the anandamide in CSF in a larger sample of patients may help elucidate the possible contribution of the endocannabinoid system to the pathogenesis of schizophrenia.Criminologists call crimes that have occurred, but that are not recorded or reported, the “dark figure of crime”, and they form a group of important missing statistics in understanding crime. Ever since crime statistics began being formally collected in the 19th century, this group of missing statistics has been a problem that has plagued law enforcement and criminologists.

Such models also demonstrate that HIV infection can alter the metabolism of alcohol, which has direct consequences for alcohol-induced expression of genes that affect neurotransmission . Combined, these data, collected at multiple levels of analysis, suggest that HIV infection has a direct impact on learning and memory and that it may also increase vulnerability to the effects of alcohol consumption on memory functioning. Consideration of the impact of problematic alcohol use on memory functioning may therefore further enrich our understanding of health outcomes among individuals with HIV. The current study is characterized by several strengths including examination of varying levels of alcohol use, comprehensive interview-based assessment of medication adherence, psychiatric illness, and co-occurring substance use, as well as evaluation of patient-perceived everyday memory functioning. However the current study is not without limitations. First, although the presented mediational results represent an important first step, without a prospective design our findings have limited interpretability. Future studies should longitudinally examine the influence of perceived memory functioning and problematic alcohol use on HIV symptom severity to confirm directionality of observed effects. Second, HIV symptom severity is a subjective self-report measure and represents only one index of HIV health. Future research should use a multi-method approach to determine how problematic alcohol use and self-reported memory functioning impact objective measures of adherence ,greenhouse tables engagement with care and biological markers of HIV disease severity . Third, we did not simultaneously employ laboratory based measures of neuropsychological performance traditionally used to establish cognitive impairment in clinical populations.

Indeed discordance between self-reported cognitive functioning and objective indices of neuropsychological performance has been documented among HIV infected individuals. However, other research has found increased cognitive complaints to predict poorerneuropsychological test performance and thus supports a relation between self-reported cognitive complaints and neuropsychological skills among HIV-infected individuals. Further, the majority of observed cognitive impairment among HIV-infected individuals in the post-ART era is mild, variable, and may go undetected . As such, it is possible that neuropsychological assessment measures, which possess somewhat less obvious face validity for real world impairment, are less sensitive to mild and fluctuating difficulties in everyday memory functioning. Hence, our reliance on patient’s self-report of memory dysfunction offers a unique understanding of how HIV symptom severity and problematic alcohol use can affect subjective experience. Nevertheless, future studies should employ a multi-modal assessment of cognitive functioning that includes both self-report and neuropsychological assessment tools. In addition, although the EMQ has been used with cognitively compromised clinical samples and is sensitive to differential use of alcohol, it has not been employed in previous studies with HIV-infected samples. Of note though, other studies have included similar measures of meta-memory to assess perceived memory difficulties in HIV-infected samples. Fourth, counter to expectations, our analyses did not reveal an association between self-reported medication adherence and HIV symptom severity. It is possible that memory problems may have impacted accuracy of self-reported adherence . Another potential reason for the lack of association could have been the differing time frames in which HIV symptom severity and medication adherence were assessed. It is possible that recent non-adherence may not yet have rendered increases in symptom severity. Accordingly, the shorter 2-week window in which medication adherence was assessed is a limitation of this study.

Future studies should aim to match assessment time periods for medication adherence and HIV symptom severity. In addition, given that some of the named symptoms included affective disturbance, medication adherence alone may not have been sufficient to reduce such symptoms. HIV infection is associated with a wide range of symptoms, and future research should examine the extent which problematic alcohol use and perceived memory functioning impact specific facets of HIV symptoms . Fifth, although our hypotheses were supported above and beyond the effects of sample stratification by cannabis use status, researchers should also examine associations between problematic alcohol use, memory functioning and HIV symptom severity in an a priori study. Last, the current study did not employ an objective measure of adherence and observed self-reported estimates may have been overinflated. Other studies with HIV-infected substance users have reported significantly lower adherence ratings with objective measures . In summary, problematic alcohol use, more so than medication non-adherence, current depression, or cannabis or tobacco use, was associated with greater perceived memory dysfunction in this HIV-infected sample. Additionally, perceived memory dysfunction emerged as a factor that may explain why individuals with problematic alcohol use experience increased HIV symptom severity. Accordingly, memory functioning may represent a high yield trans-disease target for interventions among individuals with co-occurring HIV and substance use disorders . Further, the current findings, in conjunction with previous work, suggest that assessment of cognitive functioning should precede symptom-focused empirically-supported interventions in order to bolster outcomes for HIV-infected individuals with problematic alcohol and substance use. Identification of cognitive deficits prior to treatment would afford clinicians the opportunity to modify intervention delivery and preemptively recruit organizational and community resources.

Finally, our results highlight the importance of integrated care for this high-risk population that includes cross training initiatives across health disciplines , co-location of services, enhanced provider communication, monitoring of drug interactions and side effects, and a united, multidisciplinary team approach to combating the serious social and economic consequences that typify HIV infection and substance use.That same year, with these high rates of prescribing, an average of 3.6% of Americans 12 and older self-reported prescription opioid abuse, resulting in 41 deaths per day.A major push to curtail opioid prescriptions has been initiated nationwide, yielding volumes of research and effective strategies to limit prescriptions. Opioid prescriptions in the emergency department have been identified as a possible gateway for drug overuse or addiction. In a recent study of 53 patients who reported using heroin or nonmedical opioids, 59% of patients were first exposed to opioids by prescription, 29% of whom were first prescribed opioids in the ED.Furthermore, 12% of patients with acute pain who are prescribed opioids for the first time in the ED will continue to refill them after one year.The decision to prescribe opioids, and the quantity of opioids, can be subjective and may be influenced by the provider’s explicit and implicit biases. Studies have found that opioid prescription rates are dependent on the facility, physician, geographic location, and situational or workload factors.Other more implicit factors that have been identified may include a patient’s age, race, ethnicity, socioeconomic status, gender, insurance, clinical presentation, and physician’s judgment as to whether a patient may display drug-seeking behaviors.Physicians are often wary of prescribing opioids to patients who have a history of drug abuse or are taking illicit drugs that may cause an accidental overdose. However, this situation is further complicated when patients require opioids due to a major injury. Literature is sparse regarding guidelines on prescribing controlled medications to patients with suspected or confirmed illicit drug use.Previous literature has identified that individuals with alcohol, marijuana, hallucinogen, cocaine, stimulant, heroin, and sedative use disorders, as well as those with nicotine dependence, had a higher prevalence of prescription opioid use disorders.These individuals were also found to have used prescription opioids non-medically more often than those without substance use disorders, with an incidence rate ratio between 1.46 to 1.96. Conversely, individuals misusing prescription opioids had much higher odds of using illicit drugs, including heroin, crystal methamphetamine, and cocaine.Given that nearly two-thirds of prescription opioid deaths co-occurred with cocaine, methamphetamine, or benzodiazepines, this presents a challenge to physicians who are prescribing opioids to patients with evidence of illicit substance use.Furthermore,vertical farming supplier a population-based cohort study of adolescents determined that illicit drug use is a risk factor for future opioid misuse in that population.24 In light of this evidence, it would be prudent for physicians to adjust their opioid prescribing habits, or coprescribe an overdose-reversing agent such as naloxone to patients who require opioids but present with evidence of prior illicit substance use. With the recent legalization and increase in the use of cannabis and cannabinoid products including tetrahydrocannabinol and cannabidiol in many states, it is important to consider the implications for opioid prescriptions. The most psychoactive component in the majority of cannabis products is THC, and it has been identified as playing a principal role in the analgesic effects of cannabis.To date, research bridging the years before and after medicinal and recreational cannabis legalization has demonstrated that the introduction of cannabis has either had no effect or decreased the quantity and dosage of opioid prescriptions.However, pre-clinical evidence is mixed regarding the opioid-sparing effects of THC. High quality clinical trials in humans are lacking, and results from the trials that have been conducted are mixed.Given the general lack of literature on opioid prescribing guidelines for patients with substance use disorder, we aimed to explore how a physician’s behavior and opioid-prescribing habits may be altered by knowledge of the patient’s concomitant use of psychotropic compounds as evidenced on urine and serum toxicology screens. Additionally, our goal was to elucidate which patient populations are more likely to receive naloxone, and whether knowledge of recreational drug use through toxicology screens is associated with higher rates of naloxone prescriptions.Patients 18 years of age and older who were discharged from the ED with a diagnosis of fracture, dislocation, or amputation and received an opioid prescription upon discharge were included in the study.

We excluded from the analysis patients who were admitted to the hospital, transferred to another hospital, or not discharged with an opioid prescription. The study was reviewed and approved by the university’s institutional review board as an exempt category . Patient informed consent was not applicable.We obtained our data from the hospital’s health records database. We extracted the following information for each patient: age; gender; diagnosis ; urine and serum toxicology results; prescription medication ; and quantity . For each patient we calculated a total prescribed milligram morphine equivalent by multiplying the prescribed amount by potency of prescribed medication. The data collection was performed by a single abstractor, a pharmacist trained in using structured query language and the Observational Medical Outcomes Partnership. The abstractor was blinded to the study hypothesis.We divided the study population into five subgroups: patients with negative urine and serum toxicology screen; those who tested positive for depressants; stimulants; mixed; and no toxicology screens. A basic urine drug screen was used without confirmation testing. The drugs identified on the urine drug screen were amphetamines, barbiturates, cocaine, benzodiazepines, methadone, opiates, phencyclidine, THC, propoxyphene, and MDMA . Alcohol was a quantitative test tested through serum. Depressants included patients who tested positive for alcohol, opiates, benzodiazepines, or methadone. The mixed subgroup contained urine or serum toxicology components from both the depressant and stimulant classes, as described above. Given that THC has a complex pharmacology and its effects can vary from having depressant or stimulant properties depending on the dose, type, and individual user, any patient found to be THC positive was categorized as “mixed.” Because opiates and benzodiazepines are often used in the ED to treat painful conditions or for conscious sedation for fracture or dislocation reductions, patients with urine toxicology screens obtained after the ED administration of opiates or benzodiazepines were presumed negative for the substance, and the data was analyzed accordingly. Nine cases were presumed negative due to the patients having received an opioid or benzodiazepine prior to obtaining a urine sample for drug screen analysis: seven patients were presumed negative for opioids and recategorized from the depressant group to the negative group; one patient was presumed negative due to both benzodiazepine and opioid administration and recategorized from the depressant group to the negative group; and one patient was presumed negative for opioids and recategorized from the mixed group to the stimulant group. Of 103 patients who had a urine toxicology screen, eight had opioids that could not be explained by a prior opioid prescription or ED administration of an opioid. None of the patients in the stimulants group had active prescriptions for amphetamine containing products such as dextroamphetamine for attention deficit hyperactivity disorder. All opioids and benzodiazepines identified to have been administered to these nine patients were confirmed by the institution’s lab to have been administered medications that are typically detected by the urine toxicology screen. Furthermore, for trauma activations, the trauma service was actively involved in the care of patients including decisions on imaging, inpatient analgesics, and disposition.

The point of this is to observe whether or not marijuana has a negative effect on drug and alcohol related deaths, implying that marijuana is a substitute for other drugs. Because cross-sectional data will be used, there are unobservable events that could affect the analysis within that time period. For example, the Great Recession occurred from 2007-2009, which could have possibly increased crime rates. In order to combat time trend errors in the model, I will add annual fixed effects. This will allow the model to absorb any overlooked effects dependent on time. Because California counties are diverse and not all of them implement laws to the same extent, county fixed effects are also necessary for all regressions. By using these fixed effects, we will control for county-specific omitted variables that are time invariant. Relevant county-controlled variables may include the number of police stations or type of legislation implemented within a single county. All regressions in this report will contain both county and year fixed effects.This data was collected by the California Department of Public Health when SB 420 was implemented in 2005. The count of MMICs is updated through September 2015,indoor plant table but we will only use the number of cards issued from 2005-2014 since all other data is given annually. The cards issued each year range from zero to 1475. Because each card is only valid for one year, we assume that these annual numbers include renewed cards.

There is a variation in these numbers between counties and time due to the fact that some patients may not have renewed their cards and every county implemented this system at different times. Because it is a voluntary identification system, any significant results would be under estimated. The MMIC data has been converted into number of MMICs issued per 100,000 people, as shown in 7.1.1 of the Appendix, in order for an easier interpretation between variables. It should be noted that some counties did not participate in some years and many others had zero medical marijuana cards issued at the beginning of 2006. Sutter and Colusa counties still have not applied this system and thus have no observations. Because there is no data on medical marijuana cards issued, Sutter and Colusa counties were omitted from all data sets. Table 4.1 below offers summary statistics for the MMICs issued per 100,000. In order to use unemployment as a right-hand side variable in the models, data from the California Employment Development Department was collected and offers per county unemployment rates from 1990-2014. This data will allow us to have a stronger model when examining the given research questions. Unemployment rates from 2005- 2014 will be used in order to compare it to our MMIC data. Referring again to Table 4.1, we observe a mean unemployment rate of 9.8. All data sets contain 560 total observations from the 56 counties used within the 10-year period. The mortality data to be used in this report comes from the Centers of Disease Control and Prevention. The mortality rates are divided into three categories: Alcohol-Induced Causes, Drug-Induced Causes, and All Other Causes. These rates are given per 100,000, as shown in 7.1.3 of the Appendix. Estimated population sizes per year are also included in the data set. Like the MMIC data, the crude rates are reported per county, per year from 2005-2014. Within this time period, these crude rates have ranged from 4.9 to 1328.6 per 100,000. Referring above to Table 4.1, the mean alcohol-induced, drug-induced, and other crude rates are 13.5, 15.8, and 759.4, respectively.

In addition to the mortality data, arrest rates will be examined to determine if medical marijuana is a substitute for other drugs and alcohol. The arrest data comes from the State of California Department of Justice’s Criminal Justice Statistics Center and includes 76 arrest variables. Of these 76 variables, I will be using 7 of them in my data analysis. These variables include marijuana, drunk, felony drug offenses, narcotics, dangerous drugs, other drugs, and total arrests. Other drugs represent all misdemeanor drug arrests excluding marijuana. However, the marijuana variable used in our data is the sum of both misdemeanor and felony marijuana arrests. As stated by the CJSC, “A felony offense is defined as a crime which is punishable by death or by imprisonment in a state prison. A misdemeanor offense is a crime punishable by imprisonment in a county jail for up to one year.” Full variable definitions are given in Table 7.2.1 in the Appendix. All variables in the data set were given as number of arrests per county, per year again from 2005-2014. As presented in part 7.1.2 of the Appendix, I converted these numbers into arrests per 100,000 so the analysis of all variables could be more easily interpreted. The CJSC has also provided crime data from 2005-2014 to be used in the regressions. Not to be confused with arrest data, the crime data set contains all individuals convicted of a crime, whereas arrests occur when a person is simply taken into custody for a crime. The crime data presented by the CJSC offers 66 variables, from which I selected the 10 main types of crime, including, violent crime, burglary, larceny/theft, property crime, aggravated assault, motor vehicle theft, robbery, forcible rape, homicide, and total crime. Property crime is the sum of burglaries, larceny/thefts, and motor-vehicle thefts and violent crime is the sum of forcible rapes, homicides, and robberies. For full definitions of crime variables, refer to Table 7.2.2 in the Appendix. The crime data set originally included city and county distinction, but I collapsed the data into strictly per county observations. Computed the same as the MMIC, crude, and arrest rates, the third calculation shown in 7.1.3 of the Appendix was used to convert the numbers into crimes per 100,000 people.

Table 4.2 below offers summarized statistics of all data collected from the CJSC.To begin analyzing the effect of medical marijuana in California, all nine individual crime rates and total crime rates were regressed on MMIC rates and unemployment rates with county and year fixed effects. It is necessary to include county fixed effects in the model because there are unobservable factors that could affect crime rates. For example, high-income counties in California may have lower crime rates by being able to afford tighter security. It is also obligatory to include year fixed effects in the crime rates model. This type of fixed effect absorbs any event or time trend that could potentially adjust crime rates. Because the data ranges from 2005- 2014, the housing market crash could have affected crime rates. Referring to Graph 5.1, it is indicated that crime rates don’t necessarily have a linear time trend. Thus, the individual year dummy variables will be the best fit to combat the unobservable events that occur across time. Here we see that for every additional medical marijuana card issued, total crime decreases by one and a half crimes. This appears to be a significantly large effect. However, looking at the average MMIC rate of 53 and the average total crime rate of 6,210, it is unlikely that medical marijuana could completely eradicate crime. The estimated results imply that if the mean of MMICs goes up to 54, crime rates will fall to an average of 6,208.5. This is only a decrease of 0.024% of total crime, which is a small, yet reasonable estimate. While this is a small effect on total crime, the 95% confidence level suggests the true estimate is between -2.46 and -0.55. Because these values are negative, it is acceptable to assume medical marijuana will not negatively impact society by increasing crime rates. After observing that medical marijuana has a negative effect on total crime,plant growing stand it can also be seen that medical marijuana also has negative effects on larceny-theft and property crime, with estimates shown in tables 5.4 and 5.5. Table 5.4 indicates that for every additional MMIC issued, larceny/theft declines by about half of a crime, while Table 5.5 suggests that for every additional MMIC issued, property crime decreases by ¾ a crime. Because property crime is defined as the sum of larceny/thefts, burglaries, and motor-vehicle thefts, the effect on larceny/theft is contained within the effect on overall property crime. As these estimates appear to be miniscule, they are both statistically significant at with t-statistics of -3.66 and -3.52, respectively. Many individuals who argue against the legalization of marijuana claim that marijuana usage would increase crime, thereby negatively impacting society. By building a 95% confidence interval it is shown that the true estimates are negative and that 95% of the time, the estimate will fall between -1.18 and -0.33. Thus, medical marijuana will not increase overall property crimes, specifically larceny/thefts. This answers the common argument that marijuana use increases crime rates.The other seven crime variables regressed on MMIC, using Equation 5.2, showed no significant effects of medical marijuana on crime. However, vehicle theft showed a statistically significant negative effect at the 90% confidence level. This can be explained by the above regression results on property crime, given that vehicle theft is included in the overall property crime rates by definition. All other crimes displayed zero effect from medical marijuana. While we can comfortably say that medical marijuana does not increase crime rates, there needs to be an explanation for why it has a significantly negative effect on both total crime and property crime. One explanation is that allowing consumers to purchase legally decreases the amount of associated crime that comes with the illegal marijuana market. It is often true that individuals who enact in criminal activity participate in more than one crime. This means when individuals are purchasing marijuana illegally, they are more likely to commit other crimes.

Thus, when additional MMICs are issued, individuals are purchasing marijuana legally and are less likely to be crime participants. This effect can be seen in the above regression results where additional MMICs lead to a slight fall in committed crimes. A second explanation could be that there are substitution effects for marijuana and other drugs and alcohol. With evidence of marijuana reducing violent behavior, as explained further below, individuals are less likely to commit crimes. Because many crimes are committed while drunk or intoxicated, an increase in marijuana use with significant substitution effects on other drugs or alcohol could lead to a slight decrease in crime.This brings us to the next two models, created to observe whether or not marijuana is a substitution drug for alcohol and/or other drugs. Equation 5.6 regresses every individual arrest rate on MMICs and unemployment rates, while Equation 5.7 regresses drug-induced, alcohol-induced, and all other mortality rates on MMICs and unemployment rates. These two equations will allow us to examine any substitution effects going on between marijuana and other drugs and alcohol. Both equations are again controlled for county and time fixed effects. This means that 99.9% of the time medical marijuana has a negative effect on drunken arrests. While this indicates that there may be a substitution effect for alcohol, it is a small effect with a 1:4 substitution ratio. For this effect to decrease drunken arrest rates by 1%, MMICs would have to increase by about 20 per 100,00. This could be a possible scenario, given that the standard deviation of MMICs is 95.34. In the likelihood of this event, medical marijuana could be a significant substitute for alcohol. As briefly mentioned earlier in this analysis, a substitution effect between marijuana and alcohol can justify why we see a decrease in crime. It has been observed by many studies that a large proportion of crimes are committed when an individual is intoxicated. According to the Huffington Post, the National Institute on Alcohol Abuse and Alcoholism “found that 25-30% of violent crimes are linked to alcohol use,” and the journal of Addictive Behaviors performed a study that suggested “cannabis reduces likelihood of violence during intoxication,” thus explaining why an increase in marijuana use can decrease crime rates.By finding a slight substitution effect between marijuana and alcohol, we are able to explain some of the negative effect that marijuana has on crime. After regressing all other arrest rates, drunken arrests remains the only significant category affected by MMICs. So with the given data, there is no evidence that marijuana is a substitute for dangerous drugs, other drugs, felony drugs, nor narcotics.

Linking measures from the Opportunity Atlas to the ABCD Study allows for objective measures of neighborhood economic opportunity to study in relation to health outcomes in ABCD youth. However, while the Opportunity Atlas estimates can be used as predictors of economic opportunity for children today, it is important to combine these estimates with additional data to determine applicability to neighborhoods that have undergone substantial change in the last several decades. There are vast differences in neighborhood access to opportunities and quality of conditions for children across America, including access to good schools and healthy foods, green spaces such as safe parks and playgrounds, safe housing and cleaner air. These inequitable neighborhood differences can negatively influence the current living conditions of a child, as well as development throughout childhood and subsequent health outcomes in adulthood . Children who grow up in neighborhoods with access to more educational and health opportunities are more likely to grow up to be healthy adults. The COI 2.0 is a national contemporary measure of neighborhood opportunity, comprising a comprehensive dataset that aggregates 29 indicators of neighborhood conditions for 72,000 census tracts in the United States. Beginning with the ABCD 4.0 data release, the ABCD Study provides scores for the COI 2.0 overall index, and the three domain indices that comprise the overall index: education , health and environment ,grow table and social and economic opportunities . We have also included scores for the 29 indicators that comprise the three domains. Detailed documentation describing the indicators that comprise each of the domains as well as the dataset source and year for each of the 29 indicators can be found in Supplemental Table 4 and the COI 2.0 technical documentation.

Given the diverse demographics of the ABCD Study participants, linking the COI 2.0 gives us objective measures of neighborhood opportunities for participants so that we can assess the influence of neighborhood quality on adolescent health and potential emerging health disparities. Crime rates are an important neighborhood characteristic that can cause distress on individuals’ mental well-being and has been linked with various children’s developmental outcomes . However, the impact of crime within the context of other neighborhood variables and how these impact neural mechanisms during children’s development is less clear. To empower researchers to investigate the impact of local crime rates in the broader context of the built environment, we obtained county-level crime statistics from Uniform Crime Reporting Data . In addition to the total crime rates, we also provided subcategories of the crime, including violent crimes, drug violations, drug sales, marijuana sales, drug possessions, and DUIs. The removal of lead from gasoline and house paint has been associated with dramatic declines in childhood lead exposure, which, given lead’s effects on child development , has been regarded as one of the greatest public health achievements of the 20th century . Unfortunately, exposure to lead remains a dire public health concern, as risk of exposure persists through lead-contaminated water pipes and ingestion of lead-contaminated dust and soil per leaded gas vehicular emissions and non-remediated lead-based paint . Collectively, children living in older homes are at greater risk of exposure . In 2016, Rad Cunningham at the Washington State Department of Health developed a nationwide map quantifying risk of lead exposure at the census-tract level, in which risk of lead exposure was a function of housing age and poverty rates . More specifically, “housing age” reflected the estimated number of homes in each census tract with lead-paint hazards based on decades of construction .

Marshall et al. and Wheeler et al. reported that these lead-risk estimates were valid proxies of childhood lead exposure, in that, across several states and cities, there was a greater prevalence of elevated blood lead levels in census tracts with higher risk scores; further research will permit determining the extent to which these lead-risk scores are predictive of individuals’ observed blood-lead levels. Accordingly, the ABCD Study incorporated the aforementioned lead-risk scores using code freely available on GitHub , to estimate census tract lead-risk scores of participants’ primary, secondary, and tertiary residential addresses. Air pollution, or the presence of toxic particulates and gases within the atmosphere, is one of the most widespread environmental issues affecting global health today. Adverse effects of air pollution exposure on mortality , and morbidity , as well as respiratory and cardiovascular health are well documented , but a growing body of evidence suggests that air pollution exposure may also compromise brain development with long lasting effects on cognition and mental health . However, because of challenges to accurately model air pollution exposure and a dearth of well-powered longitudinal neuroimaging studies that span adolescence, much remains unknown regarding the effects of air pollution on neurocognitive development during adolescence . ABCD provides a unique opportunity to investigate the effects of air pollution exposure during critical developmental periods on adolescent brain development and behavior. Using state-of-the-art air pollution modeling at high spatial resolution created by colleagues at Harvard University, ABCD provides a number of measures capturing participant’s residential exposure to three criteria ambient air pollutants: fine particulate , nitrous dioxide , and ozone . These ambient air pollutant exposure estimates are derived from a hybrid spatiotemporal model at the 1 × 1 km2 spatial resolution . This hybrid model combines the strengths of satellite-based aerosol optical depth models, land-use regression, and chemical transport models.

This model has previously been trained for the continental United States from 2000 to 2016 and tested with left-out monitors. Daily 1 × 1 km2 ambient exposure estimates were then averaged across the 2016 calendar year and linked to the nearest estimate of the 1 × 1 km2 grid for the latitude and longitudinal of the baseline residential addresses. In addition to computing average annual estimates for PM2.5, NO2, and O3, ABCD includes the minimum and maximum levels of all three pollutants in 2016 in the 4.0 annual release, as well as the number of days that PM2.5 levels exceeded the National Ambient Air Quality Standards threshold of 35 µg/m3 . By including this array of measures, researchers have the opportunity to gain insight into differential effects of long-term versus focal air pollution exposure, as well as the degree to which National Ambient Air Quality Standards’ thresholds are meaningful in terms of preventing adverse effects of air pollution exposure on the adolescent brain. The existing literature suggests that temperature, including heat and cold stress, can negatively impact how the human body functions, and cognitive functioning is no exception . Studies suggest heat waves can impact test scores across American high school students and that fluctuations in temperature may also increase symptom severity in individuals affected by certain neurological conditions . Moreover, climate change has already made temperatures hotter, producing more intensive heat waves in the U.S. . Thus, characterizing the climate that participants may have experienced at home prior to ABCD Study visits may be useful to determine how seasons or weather may relate to individual differences in brain functioning. By considering the climate, the ABCD Study holds the potential to answer pertinent questions regarding potential effects of hotter and/or greater fluctuations in temperature on brain function in today’s youth. Thus, to account for potential differences in climate, the ABCD Study has mapped temperature, humidity, and elevation to residential addresses as part of the 4.0 ABCD data release. Maximum daily temperature and vapor pressure deficit data derived at the 30-arcsec spatial resolution from 1981 through June of 2020 ,vertical rack were mapped to the residential address for the 7 days prior to each individual’s baseline study visit. Given that temperature and air pressure also decrease as a function of elevation, for completeness, elevation was also mapped to the residential address using the Google Maps Elevation API . The LED Environment Working Group strives to include additional information about the built and natural environments of all participants in the ABCD Study. These data provide an additional perspective about differences both between study sites and individual differences among children within even a single given study site location. Integrating these external environmental factors are likely important in considering both mediating and moderating effects and allows for important questions to be asked with implications for policies that may help ensure all children can thrive. That is, given the wealth of additional data collected in the ABCD Study, the addition of understanding the built and natural environment in ABCD provides the opportunity to think more broadly about how these factors may influence neurodevelopment of children within the established social determinants of health framework of public health . Specifically, health outcomes, including neurodevelopment, cognition, and mental health as measured extensively by the ABCD Study, have been recognized to be influenced by complex interactions among environmental, social, and economic factors that are ultimately closely tied to one another . Dahlgren and Whitehead provided a visual representation of such complex processes as a model of the main determinants of health and well-being in public health, which has since helped shape public health policy at both national and global scales . Thus, capturing the broader physical environment makes the ABCD Study an ideal resource for researchers interested in studying how various distal and proximal factors may impact developing children and their health.

While a number of development cognitive research studies have focused on individual factors, including socio-demographic factors , lifestyle , and social environments , additional natural and built environmental factors including neighborhood quality, community-level access to resources and opportunities, and exposure to harmful substances, provides an additional layer as to understanding and identifying key factors of neurodevelopment and to promote policies that lead to better health outcomes for all children across America. Specifically, these data can allow for researchers to examine if upstream built and natural factors might account for and/or moderate associations between physical activity and brain development, understanding the link between screen-time and mental health, determining how neighborhood conditions may impact the formation of peer groups, or exploring how recreational activities may moderate the relationship between adverse neighborhood conditions and mental health. In doing so, not only may we have a better understanding of the complex associations between the various factors contributing to neurodevelopment across childhood and adolescence, but research findings may also point to possible public health targets for intervention and treatment. While there are clear strengths in mapping the environmental context of today’s youth in the ABCD Study, there are also several important technical limitations as well as considerations for researchers planning to use and interpret these data. A vital consideration to this type of geospatial research and the variables derived from it, is the accuracy of the assignment of the exposure assessment at any given time.Any given geospatial database has both a spatial and temporal component. How these data were derived, and the degree of resolution is important to consider. For example, census tracts can be rather large, whereas in urban areas drastic differences in the environment can sometimes be noted to vary from street to street. Furthermore, individuals who live in the same census tract should not be considered to have the same experiences or the same amount of exposure in the neighborhood as others with similar demographics. Moreover, many times, geospatial databases are compiled after data is available from other sources, such as the American Community Survey or the Environmental Protection Agency. Thus, exposure estimates can often reflect a snapshot in time that may or may not overlap directly with the time period that the child was at that residential location; requiring the researcher to consider if the exposure of interest can or cannot be assumed to be stable beyond the temporal domains of the dataset. For example, many databases may create variables using 5-year averages that have then been linked to the baseline residential addresses which were collected in 2016–2018. Another technical challenge is that retrospective address collection is hindered by recall bias, or the differences in the accuracy or completeness of caregivers in the ABCD Study to recall address details over the 9–10 years prior to study enrollment. In addition, exposure assessment based on residential geospatial location also fails to capture individual data on percentage of time in which children in the current study spend time at their primary address versus other daily activities and/or various locations, such as in school. Of course, it is important to note that misclassification of exposure may be lower for children in that they may spend more of their time around the home, as compared to other populations such as adults who may spend more time commuting, time at work, or so forth.

We did not find an association with length of time spent homeless as an adult. These findings suggest participants may have had an increased risk for poor oral health status prior to becoming homeless. Consistent with prior research we found strong associations between having lost half or more of teeth and evidence of problem drinking, cocaine use, or having ever smoked . Alcohol may impair oral health through diminished salivary flow and altered salivary composition, which can exacerbate upper respiratory irritation, including gastric acid regurgitation, further worsening oral health . Cigarette smoking is an independent risk factor for chronic periodontal disease leading to tooth loss . Cigarette smoke contains toxins that locally alter salivary flow and systemically lead to destruction of tooth-supporting tissue . Cocaine use can increase the risk of tooth loss due to bruxism and a decrease in salivary pH . We found a non-statistically significant elevated odds of tooth loss with moderate to severe cannabis use, consistent with prior research . Cannabis use is thought to be related to tooth loss via an association with infrequent dental visits and high cariogenic diets after cannabis use. . We found an inverse association between moderate-to-high risk methamphetamine use and tooth loss. Other studies have found a positive association between methamphetamine use and better self-reported oral health among homeless populations or have not identified a significant association between methamphetamine use and oral health need . Our study has several limitations. As our analysis relies on cross-sectional data, we cannot establish causality. We used self-reports of tooth loss,hydroponic racks system rather than clinical dental exams. This left the potential for over or under-estimation of missing teeth and made it more difficult to make direct comparisons to other studies. In order to minimize misclassification, we used a broad measure of tooth loss that participants were more likely to understand. The study recruitment period occurred during a period of expansion of services, which could have increased access to dental care in those who were recruited later in the recruitment year.

Access to dental care may have improved with the expansion of Medi-Cal during the study period, or with recent increases in covered services . In one of the first studies of oral health in a population-sampled cohort of older homeless adults, we found evidence for poor oral health and limited access to dental care. There is an urgent need to increase the access to and provision of both preventive and restorative dental care to older homeless adults in order to decrease morbidity and improve quality of life. When it comes to science, we are living in strange times. Although much of the health, wealth, and power of our society derives from extraordinary achievements in physics, biochemistry, engineering, and medicine over the last 100 years, it seems curious indeed that political figures who trumpet America’s material success are launching assaults on the nature of scientific endeavor—challenging the value of expertise, positing ‘‘alternative facts,’’ rejecting evidence-based findings in favor of bombastic claims and personal beliefs. It is in this context of seeming open hostility toward scientific evidence that our society considers important deliberations about how to schedule, regulate, criminalize, and otherwise govern whether its citizens will have legal access to a host of molecules—some plant-derived, some synthesized—for therapeutic uses. For we palliative care clinicians, the paramount uses in question relate to reducing intractable suffering—in particular, suffering for which our available treatments are often inadequate. As an instructive example of the current disconnect between science and policy discourse in the public square, compare the scholarly 2017 monograph on the health effects of cannabis and cannabinoids produced by the National Academy of Sciences1 —which cites good clinical-trial evidence supporting the efficacy of cannabis and cannabinoids for pain management, —to an assertion by the future Attorney General of the United States during his Senate confirmation hearings: that ‘‘..good people don’t smoke marijuana..’’.

Witness also the Attorney General’s recent rollback3 of Obama-era directives that prohibited federal law enforcers from expending their resources to enforce the antiquated and unscientific 1970s-era Drug Enforcement Agency Controlled Substances Schedule in states with cannabis legalization statutes. In case readers need reminding, DEA still rates cannabis as a Schedule I compound . Elements of that four-decade-old assertion are simply false. In this issue of JPM, our colleague Ira Byock, a wise and thoughtful palliative care physician who helped introduce Western readers 20 years ago to the concept of ‘‘Dying Well,’’ —now brings to our Journal a provocative commentary on high-quality clinical data suggesting that ‘‘psychedelic’’ drugs may play an important new role in managing intractable suffering. specifically, Dr. Byock reviews recent trials of psilocybin, lysergic acid diethylamide , 3,4- methylenedioxy-methamphetamine , and ketamine, and describes strong evidence for improvement in refractory symptoms related to end-of-life anxiety/depression in patients with cancer and other terminal illnesses , treatment-resistant depression in healthy individuals and endof-life depression in cancer patients , and severe post-traumatic stress disorder . Byock weaves a compelling narrative, summarizing the unmet needs that are all-too common in patients who face catastrophic medical illness. He integrates into his review a discussion of the reasons given by patients who have sought to utilize the Oregon ‘‘Death With Dignity’’ act, pointing out that most of these patients are looking to death for relief from what Byock terms ‘‘nonphysical suffering’’—loss of autonomy, dignity, and the ability to enjoy life—symptoms that might, it turns out, be amenable to the therapeutic effects of psychedelics. In the face of Washington’s stubborn resistance to reclassifying anything in the Controlled Substance Act Schedule, perhaps a sense of common cause may emerge among those of us who would advocate for our palliative care patients a ‘‘right to try’’ psychedelics regardless of our personal positions on physician aid in dying. If larger scale trials confirm that safe therapeutic doses of any of these agents help reduce suffering, death fears, or treatment-resistant end-of-life depression, I believe our field and our patients would welcome them as important new options. It is hard to imagine that palliative care clinicians would object to the idea that in carefully supervised trials, these old/new drugs might be offered to patients with existential concerns, intense death anxiety/fear, or treatment resistant depression as primary drivers for their pursuit of physician aid in dying.

We would welcome the potential safe relief in suffering these substances might provide, and would consider it a therapeutic success if patients experiencing benefit might choose to rescind or defer their legal pursuit of Physician Aid in Dying or Physician Assisted Death . Why do I juxtapose a brief narrative about cannabis with the emerging data regarding psychedelics? Is there a unifying thread? Sadly, I think there is: it is the unfortunate legacy of the ‘‘drug culture’’ of the 1960s mixed with the legacy of the ‘‘club culture’’ of the 1980s. The excesses of those eras, mixed with the social upheaval and challenges to authority that accompanied them and terrified ‘‘the establishment’’,provide a rich topsoil of images and impressions to support reactionary resistance to the emerging evidence. Dr. Byock is no stranger to the politics and regulatory barriers that might lie ahead; he describes them plainly in the article. And even beyond those expectable barriers, we find ourselves in a ‘‘1984’’ world of political suppression of scientific and public policy discourse. A painful recent example: in an early 2018 editorial in the Annals of Internal Medicine, a group of Emory University public health experts called attention to an effort by the White House to ban specific words from the U.S. Center for Disease Control’s 2019 annual budget request.6 What those words mean—‘‘vulnerable, ‘‘diversity,’’ ‘‘transgender,’’ ‘‘fetus,’’ ‘‘evidence-based,’’ and ‘‘science based’’—is essential in all of medicine, and particularly in the field of palliative care. Is the idea that, if we do not use those words, vulnerability, diversity,rolling benches canada transgender people, unborn fetuses, evidence, and science will just go away? Palliative medicine physicians are accustomed to being outside the spotlight of high-tech modern medicine, and we routinely advocate for patients who do not get first-priority attention from our medical colleagues. If clinical trials continue to demonstrate new hope from psychedelics for some of our patients’ most intractable symptoms, we may find ourselves a bit blinded by an unfamiliar spotlight, and we may feel compelled to join an advocacy effort for the ‘‘right to try’’ these treatments. Common sense and good science are not likely to prevail on their own.Clinical settings offer an opportunity to address substance use in persons living with HIV . Substance use in PLWH is associated with HIV transmission risk behavior, low anti-retroviral therapy adherence, HIV progression, detectable viral load, and poorer perceived quality of life . Not all substance use that PLWH engage in constitutes an alcohol or substance use disorder; nonetheless, PLWH have reported experiencing physical, social, and psychological harmful effects of substance use. In addition, studies have reported the harms of alcohol, tobacco, and illicit substance use in this population . In the general population as well as in PLWH, the consequences of unrecognized and untreated substance use are clinically, socially, and economically significant. The U.S. Public Health Service has endorsed routine and universal alcohol and tobacco screening in primary care ; however, few HIV primary care clinics routinely assess patients for alcohol or other substance use .

The effects of alcohol, tobacco, and illicit substance use take a greater combined toll on the health and well being of Americans than any other preventable factor. Alcohol and tobacco use are significant risk factors for cardiovascular disease and cancer, which are the leading causes of death . In a national survey on substance use and health, more than 71% of U.S. adults reported alcohol use in the previous year . In 2007, substance use contributed to more than half of suicides and violent crimes in the United States . The economic cost of the global burden of disease and health care utilization that are attributable to alcohol use are immense . Alcohol, tobacco, and illicit drug use can complicate HIV health care and health outcomes by interfering with medication access and adherence, contributing to HIV pathogenesis, increasing transmission risk behaviors, and destabilizing sources of social and financial support. PLWH who use substances are less likely to be prescribed ART and those on ART have shown reduced ART adherence . Studies that have enrolled active substance users show mixed results on HIV medication adherence. Historically, studies with PLWH who reported illicit drug use while on ART had poorer health outcomes than those who did not use drugs, while more current studies among PLWH who inject drugs and are on HIV treatment show survival rates that are similar when comparing people who inject drugs with those who do not . In addition to complicating treatment and HIV outcomes, research has also shown an association between active substance use and high-risk HIV transmission behaviors, including unprotected anal and vaginal intercourse with uninfected partners .Cocaine use has been shown to enhance viral replication and quiescent T-cell permissiveness to HIV infection, increasing the viral reservoir; cocaine is also an independent factor for unsuppressed viral load and increased neurocognitive disorders . Methamphetamine use has been associated with primary drug resistance to non-nucleoside reverse transcriptase inhibitors, increased cognitive decline, inflammation in the brain, and ischemic events . Methamphetamine use also doubles or triples the probability of engaging in high-risk sexual behavior and acquisition of sexually transmitted infections including HIV . HIV infection is more likely among women who use crack cocaine than women who don’t, and suicide attempts for PLWH are more prevalent in persons who use drugs and are related to poorer emotional and cognitive quality of life measures. Several studies have now demonstrated the relationship between substance use and HIV acquisition and increased morbidity and mortality for PLWH . Screening for substance use and identifying those with risky alcohol and drug use behaviors in primary care settings allows for an integrated approach to respond to harmful substance use. As with many chronic diseases, screening and early detection can serve as a form of preventive care as well as to identify patients where further clinical intervention may be warranted. A study of alcohol and drug use screening is especially relevant in HIV clinical settings, where substance use is widespread . HIV care providers have the opportunity to identify and intervene with patients who otherwise would be unlikely to access specialty treatment for substance use.

Such targeted examination will help provide a foundation for prospective work on AS and the etiology and maintenance of sleep pathology, with a long-term goal of guiding intervention development. Because AS serves to amplify fearful responses, it was hypothesized that AS would be associated with decrements in global sleep quality. In addition, we sought to conduct exploratory analyses on the relations between AS and each of the specific components of global sleep quality. Based on previous research that suggested that age, gender, ethnicity , and negative affect were related to sleep disturbance, these factors were examined as potential covariates. Given that participants were categorized based on their cannabis use, and due to the elevated prevalence of alcohol use, both of which may impact sleep disturbance , these were also considered as potential covariates.Prior research examining the comorbidity of psychiatric conditions and substance use disorders suggests that alcohol use disorders are significantly comorbid with depression . In the United States, 7% of adults aged 18 or older had major depressive episodes in 2014–2015, and the prevalence of AUDs among adults with major depressive episodes was 14%, twice as prevalent with depression as any other SUD . Given the substantial comorbidity of depression and AUD, the characteristics and subsequent outcomes of persons with these disorders have become high priorities for prevention and treatment research. The significant comorbidity of depression and AUD found in the general population is more striking in clinical populations. specifically, studies conducted with either psychiatry or addiction treatment seeking samples have found 50–70% of patients with depression had AUDs . In addition, hydroponic tables canada patients with depression and AUDs who present for psychiatry treatment have higher rates of drug use, more severe depressive symptoms, and functional impairment than patients with depression but without AUDs .

A general population-based study found that individuals with co-occurring alcohol and marijuana use disorders were more likely to have major depressive episodes relative to those with either alcohol or marijuana use disorder alone . Longitudinal studies indicate that patients with both depression and AUDs continue to demonstrate greater depressive symptoms and functional impairment over time than patients with depression alone . Less is known, however, about the extent of drug use over time, and whether it has differential effects on clinical outcomes for those with depression and AUDs. Although a review by Conner et al. concluded that drug use was associated with greater depression severity and functional impairment in treatment seeking patients with depression and AUD, this review is almost 10 years old and was limited to cross-sectional studies. To our knowledge, there has been no recent longitudinal examination of symptom and functional outcomes in terms of marijuana use among psychiatry outpatients with depression and AUD. Marijuana is the most commonly used drug in the U.S. , with 8.3% of adults reporting past month use. General population-based research among individuals with depression has found no association between marijuana use and depression pathology over time . Yet, research in clinical samples has shown that marijuana use is associated with worse overall psychopathology and poorer functioning among psychiatry patients with depression, and that these adverse clinical outcomes persist over time . Psychiatry patients with comorbid depression and AUD may have additional problems related to marijuana use, owning to its association with poor clinical outcomes among clinical samples . A study focused on marijuana use in psychiatry patients with depression and AUD may characterize an important subgroup at risk of poor clinical outcomes and contribute information to future prevention and intervention strategies.

We explored whether marijuana use was associated with clinically problematic outcomes for patients with depression and AUD by analyzing 6 month follow up data in a secondary analysis of 307 individuals who participated in a randomized trial for substance use treatment, delivered in a psychiatry outpatient setting. This larger question was addressed through carrying out three study aims. First, we examined whether differences in marijuana use existed at baseline between patients with and without AUD. Second, we examined whether differences in marijuana use existed over 6 months between patients with and without AUD. Finally, we investigated whether differences existed between patients with and without AUD in terms of marijuana use, depressive symptom and functional outcomes over the follow-up. Building on our prior work showing that marijuana use has adverse effects on depression , findings will provide important information about the differential impact of marijuana use on those with comorbid depression and AUD, and inform drug use prevention and intervention efforts.Data for this secondary analysis were drawn from individuals who had participated in a randomized controlled trial of motivational interviewing for substance use treatment for patients with depression, delivered in an outpatient psychiatry setting. Patients were recruited from Kaiser Permanente Southern Almeda Medical Center Department of Psychiatry in Union City and Fremont, California. These psychiatry clinics provide evaluation, psychotherapy, and medication management for patients with a range of mental health conditions. These psychiatry clinics do not provide specialized services for individuals who present for treatment with serious substance use problems. At these psychiatry clinics, individuals are screened by telephone prior to intake, and those reporting serious alcohol or drug problems are referred to the Kaiser Chemical Dependency Recovery Program , located in the Union City medical center in a separate building from the psychiatry clinic. The parent MI trial sought to provide substance use services to psychiatry patients who used drugs or alcohol but who are not referred to CDRP for treatment. The results and methodological details of the parent MI trial are reported elsewhere . In brief, a total of 307 participants were recruited from the previously mentioned Kaiser psychiatry clinics. Participants were identified via provider referrals and self-referral in response to flyers in clinic waiting areas.

Study clinicians followed up by phone with patients who were interested in the study and determined eligibility based on inclusion criteria, which required patients to be ≥ 18 years old, have Patient Health Questionnaire score ≥ 5 indicating at least mild depression, and endorse hazardous drinking or illicit drug use within the past 30 days. The parent trial used a hazardous drinking standard slightly more conservative than that recommended for the general population because psychiatry patients are frequently prescribed antidepressants and other psychotropic medications that can have adverse interactions with alcohol and other drugs . Similarly, the depression score cutoff for enrollment was relatively low to capture a range of severity levels in the sample who might benefit from substance use reduction, and to include those in the maintenance phase of depression treatment as well as higher acuity patients starting care in psychiatry. Patients with mania or psychosis were excluded as such patients would likely require more intensive substance use services than the brief MI intervention model was designed to provide. The current analytic sample consisted of all 307 patients with depression who enrolled in the parent trial: 149 with AUD , and 158 without AUD. Participants who enrolled in the parent trial used laptop computers to complete the baseline measures , including self-report assessments of past 30 day illicit drug and alcohol use, the PHQ-9, and the Mental Health Sub-scale of the Short Form Health Survey . Then, participants were re-assessed using the same self-report substance use, symptom,microgreen rack for sale and functional assessments every 3 months via telephone interviews by trained raters and study clinicians during the 6 month study. Patients were offered $50 gift cards for completing each interview. After completing the baseline interviews, participants in the parent trial were randomized to one of two study arms, either MI or usual care. The MI intervention consisted of one 45-min session followed by two 15-min telephone “booster” sessions , about two weeks apart. MI sessions were delivered within 6 weeks of enrollment, based on MI counseling approach principles by Miller and Rollnick . Participants in the control group were given a 2-page brochure, produced by the National Institute of Health National Office of Drug Control Policy as part of their Fast Fact Series , on use risks specific to the substances reported at baseline . Patients also continued to receive usual depression care based on current best practices for medication management and evidence-based psychological treatment . All patients provided written informed consent at an in-person appointment in the same psychiatry clinic where they received usual care. Procedures were approved by the University of California, San Francisco and Kaiser Permanente Institutional Review Boards.Past 30-day alcohol and drug use were assessed during study interviews via patient self-report. specifically, patients were asked: “How many days in the past 30 days have you used alcohol” and “How many days in the past 30 have you used drugs ”. Patients were coded as using if they endorsed any use , providing dichotomous measures.Marijuana use was a predictor/outcome under study in longitudinal analyses, and alcohol use was a covariate.These analyses began with conditional growth models predicting symptom and functional outcomes from time and time-varying marijuana use , to investigate the effect of marijuana use on these clinical outcomes.

We continued to build upon the previous conditional models by predicting symptom and functional measures from time and a time × AUD interaction, to investigate whether these clinical outcomes varied by patients with and without AUD over the study. Finally, moderated analyses were conducted, predicting clinical outcomes from time and a time × AUD × marijuana use interaction, to determine whether continued marijuana use had different effects on the clinical outcomes of those with and without AUD. Conditional growth models adjusted for age, gender, race, employment status, marital status, treatment assignment, time varying psychiatry visits, time-varying alcohol use, as well as the initial levels of the outcome variable under study . As with the marijuana use outcome models, the expectation maximization method was used to handle missing data during maximum likelihood estimation at the time of analysis.Drug use is often comorbid with both depression and AUD, and may negatively affect the outcomes of patients receiving psychiatric services. We conducted secondary analyses of 307 patients with depression and AUD from a trial of substance use treatment for depression, and examined marijuana use, depressive symptoms, and functional outcomes over 6 months. Consistent with prior research on alcohol and drug use among psychiatry patients with depression , approximately half the sample met DSM-IV criteria for AUD at baseline, with a relatively high proportion of patients reporting marijuana use . Overall, this proportion was slightly higher than documented in prior studies among psychiatry treatment samples and may reflect normalizing views about marijuana within California . Over 6 months, the proportion of patients in our overall sample who used marijuana significantly declined. Yet the proportion of patients with AUD who used marijuana significantly increased over the followup compared to patients without AUD. These findings extend prior work showing a decreasing trend in psychiatry patients using marijuana post-treatment , as well as work showing variability in marijuana use by psychiatric diagnosis over time . As expected from prior work with this sample , patients who used marijuana had worse symptoms and poorer functioning. Patients with AUD who used marijuana had worse symptoms and functional impairment than those without AUD who used marijuana. Our findings reinforce prior work with clinical samples showing poor clinical outcomes in patients with AUD and depression , as well as work showing adverse effects of marijuana use among patients with depression . The present study has implications for future drug use prevention and treatment efffforts initiated in psychiatry settings. Patterns of marijuana use are rapidly changing as legislation to legalize use for recreational and medical purposes spreads . This has considerable implications for health systems, as evidenced by the recent increases in emergency department services observed for patients using marijuana with psychiatric conditions . The observation of high emergency department utilization among this population may be explained by associations of marijuana use with adverse health effects, such as addiction to other drugs, high prevalence of AUD, poor functioning, and worse depression severity . Although medical marijuana proponents often suggest that the drug may be used to effectively treat depression , its safety and efficacy in depression treatment has not been thoroughly examined or established . In addition, research with medical dispensary clients has found depressive symptoms to be associated with marijuana use problems, with only about 10% of clients reporting a reduction of symptoms as a primary benefit of use .

Combustible cigarette users have different motivations for e-cigarette use, and greater severity of nicotine dependence. They also use more NTP, cannabis, and alcohol use than non-combustible e-cigarette users or NTP naïve participants. While there were no differences in cognitive performance by nicotine group status, both nicotine groups reported higher levels of depression than those who were NTP naïve. In addition, male combustible users had higher levels of depression than male non-combustible users or naïve individuals. Taken together, individuals ages 16–22 are still using combustible products and those who use combustible NTP at any levels are likely qualitatively different than non-combustible using peers and may be more vulnerable to poorer health outcomes. Future research in our laboratory will investigate differences in trajectories of combustible NTP users and consider other potential brain-behavior outcomes as related to combustible and non-combustible NTP use. Marijuana use for medical purposes is now legal in 26 states and in Washington DC, and in addition, is now legal for recreational use in multiple states. Furthermore,vertical grow over the last several years, marijuana use has increased among the US adult population. Although numerous psychosocial and cognitive consequences are associated with marijuana use, Americans increasingly perceive marijuana use as safe and as offering health benefits for some conditions. Despite rising use and perception of decreased risk compared to alcohol and tobacco, the potentially harmful physical effects of marijuana have been inadequately studied.

Smoking tobacco is well known to cause numerous health problems, e.g., chronic lung disease, cancer, and cardiovascular disease. Compared to tobacco smoke, marijuana smoke has higher concentrations of particulate matter, toxins, and tar levels. Therefore, chronic use could plausibly lead to similar health problems. An area of particular concern is the impact of marijuana use on cardiovascular health, the main cause of morbidity and mortality in the US. While understanding the relationship between marijuana use and cardiovascular outcomes is important, a challenge in beginning to understand these relationships lies in developing prospective cohorts with sufficient marijuana exposure to facilitate research. Multiple studies on the effect of marijuana use on various domains of health have reported limitations in the literature due to small sample sizes with insufficient exposure. We therefore developed and tested a method to capture this information from the free text of notes stored in VA electronic medical records. The method we developed and tested consists of using string searches of medical notes to develop a prospective cohort of older veterans who differ on their level of marijuana exposure. In this study, we demonstrate the feasibility of this method to efficiently develop a prospective cohort of older veterans using text search methods.Through an iterative process we searched through the text notes of patients in the Veterans Health Administration to identify how the marijuana use was described. The terms “marijuana”, “cannabis”,”mjx” and “mj” were identified as potential search terms. Review of notes with corresponding terms demonstrated that “marijuana”, “cannabis”, and “mjx”, were the terms most frequently used to describe marijuana use in VA progress notes. “MJ” was discarded because of overlap with abbreviations for temporomandibular joint .

Before we built a more sophisticated natural language tool, we examined whether identifying marijuana, cannabis and mjx “mentions” in patient notes were sufficient to identify current or former users of marijuana. We used this approach for two main reasons. First, we determined that when clinicians mention a specific psychoactive substancein medical progress notes, the mention suggests current or former use and not lack of use. In other words, the presence of a word denoting marijuana use may be sufficient to preliminarily identify users. Second, the VA Informatics and Computing Infrastructure provides a search function that facilitates searching clinical notes for specific word strings. In this study, we examined whether we could use this search function to identify a cohort of marijuana users with sufficient exposure to examine the cardiovascular health risks of marijuana.Using data from an existing cohort of hospitalized Veterans, we first identified patients who were 65 to 67 years old and had a diagnosis of coronary artery disease using ICD-9 codes. We focused on this group because studying the cardiovascular effects of marijuana in a younger, healthier prospective cohort would require substantially longer follow-up. We then limited this sample to patients who had one primary care visit at the San Francisco Veterans Administration in 2015 to ensure the most recent data on marijuana use was available. The San Francisco VA serves a large geographic region in Northern California extending from San Francisco to small towns in rural areas, and thus cares for a diverse population. We identified 210 patients in this cohort with coronary artery disease who were 65 to 67 years old and who received care in 2015. We categorized these patients into 62 patients with evidence of marijuana use documented in the past 12 months and 148 patients with no evidence of marijuana use using the following text strings: “marijuana”, “mjx”, and “cannabis”. We randomly selected 51 users and 51 non-users based on this preliminary classification of marijuana use.

Three subjects were deceased, leaving 50 potential users and 49 potential non-users for a total of 99 patients.Among the 99 patients, 2 did not have phone numbers and clear contact information available in their medical record. The remaining 97 patients were sent a letter that described the study consisting of a “cardiovascular lifestyle interview” focused on understanding the relationship between cardiovascular events and lifestyle factors such as physical activity, mood, sleep, use of tobacco, and drugs. Standardized and validated instruments were used to assess marijuana use and amount of use, tobacco use, second-hand tobacco exposure, physical activity, alcohol use, substance abuse, depression, post-traumatic stress disorder, self-reported health, and socioeconomic status. The letter informed potential participants that they would receive a follow-up phone call unless they called the study contact telephone number and left a message saying that they did not wish to participate in the study. When potential participants were called, a verbal script was used that had been developed and customized for different anticipated scenarios. Specifically, participants were asked if they received a letter describing the study and whether they had read it. If they had not read it, the letter was read to the participant. Patients were then asked if they had any questions about the study, informed that they would receive a $20 gift card for participation, and if they agreed to participation, consented over the phone. The UCSF Human Research Protection Program approved this research and provided a waiver of written consent and a HIPAA waiver.Among the 35 patients identified by text mining as having a marijuana term in their notes in the previous year, 15 had used marijuana in the past 30 days , 17 self-reported using marijuana in the past year and 33 had used marijuana in their lifetime . Among those not identified by text mining as having a marijuana term in their notes, 3 had used marijuana in the past 30 days. Lifetime ever use also differed based on these terms, with 94.3% of the patients who had a marijuana term in their notes reported ever use and 67.6% of those without a term reported ever use . In other words, the probability of use in the past month increased from 8.8% to 42.9% in people who have these keywords in their medical record compared to those who did not have these terms. The probability of life time ever use also increased from 67.6% to 94.3% among those with these terms in their chart compared to participants without these terms in their chart .An Institute of Medicine report published in 1999 cautioned that marijuana use may present a serious problem for older subjects,indoor growers particularly those with cardiovascular disease. However, this relationship has never been examined in a prospective cohort study. Identifying a large cohort of current marijuana users with sufficient current marijuana exposure through standard research screening methods such as a mail, telephone, or web based screening is costly and challenging. In this study, we demonstrated that within a large health system, an automated string search of medical record notes in combination with standard survey methods can be used to efficiently develop a prospective cohort of current users and non-users. Our proposed method for cohort construction leverages information available in the free text of the medical record for rapid prospective cohort construction. The hybrid approach that combines a telephone health interview with data collected as part of routine care improves feasibility of a first assessment of the effect of marijuana use on health. The data collected through the health interview further validates the proposed method for cohort construction and is in line with the health characteristics of marijuana users collected in other studies.Our proposed approach reduces the resources required to conduct a prospective cohort study and demonstrates a feasible and efficient study recruitment method. These methods can potentially be used to develop other cohorts using data from other large health care systems. Multiple study limitations are noted. We tested our recruitment approach in only one facility. However, to determine if our text search methods were generalizable to the VA system, we used the same methods to search one year of text notes of patients in 2015 in a cohort of hospitalized VA patients from other states where marijuana is legal. We identified 24,267 patients 65 to 67 years old with coronary artery disease in states where marijuana was legal.

Among these patients, 7855 had a marijuana term in their notes suggesting that this proposed method of recruitment for a cardiovascular cohort study is feasible. Second, it is unknown whether VA providers are more likely to document marijuana use compared to providers in other health systems. Our cohort construction method should be replicated in other health systems as the availability of a VA search function as well as our ability to centralize all the notes from the sample aided our ability to implement this approach. Third, we had access to contact information and both home and cell phone numbers as part of the electronic medical record. This access significantly aided our recruitment methods. Medical marijuana is also legal in California, which may have also aided the response rate as well as improved the accuracy of documentation. Finally, the age range of this sample was narrow and the sample size small. The findings may not generalize to younger populations that may be more reluctant to share their use with health care providers. This method to identify marijuana users should be tested in larger datasets that are more representative of the population. Past research in the health effects of marijuana has been limited because developing sufficiently large cohorts with sufficient use to study has been challenging. In this study, we demonstrate the feasibility of developing large prospective cohorts of marijuana users. Such cohorts can be used to answer important questions regarding the health effects of marijuana in the era of legalization. We also demonstrate that methods that combine information available in the free text of the medical record with patient health interviews provide opportunities for a more efficient approach to the development of prospective cohort studies. Future work should replicate our method of cohort construction in other health systems, and for other health factors and outcomes.Denial in substance use disorders , including alcohol use disorders , might be broadly paraphrased as a group of processes where substance-related problems that are obvious to others are not recognized or appropriately acted upon by the individual with the problems . These concepts are complex and likely to develop in response to widely held societal beliefs as well as mechanisms reflecting an individual’s traits regarding how they handle problems and their specific beliefs and behaviors. The denial or minimization of substance related problems interferes with decisions to seek help, impedes behavior changes, and contributes to relapses into problematic behaviors . About 30 % to > 50 % of individuals with AUDs or other SUDs evidence denial .