The environmental impacts of stream diversions are likely to be greatest during the dry summer months,which coincide with the peak of the growing season for cannabis. Further, because cannabis cultivation operations often exhibit spatial clustering , some areas with higher densities of cultivation sites may contain multiple, small diversions that collectively exert significant effects on streams . An important assumption underlying these concerns, however, is that cultivators rely primarily on surface water diversions for irrigation during the growing season. Assessments of water use impacts on the environment may be inaccurate if cultivators in fact use water from other sources. For instance, withdrawals from wells may affect surface flows immediately, after a lag or not at all, depending on the well’s location and its degree of hydrologic connectivity with surface water sources . Documenting the degree to which cannabis cultivators extract their water from above ground and below ground sources is therefore a high priority. In 2015, the North Coast Regional Water Quality Control Board , one of nine regional boards of the State Water Resources Control Board, developed a Cannabis Waste Discharge Regulatory Program to address cannabis cultivation’s impacts on water, including stream flow depletion and water quality degradation. A key feature of the cannabis program is an annual reporting system that requires enrollees to report the water source they use and the amount of water they use each month of the year. Enrollees are further required to document their compliance status with several standard conditions of operation established by the cannabis program. These include a Water Storage and Use Condition, which requires cultivators to develop off-stream storage facilities to minimize surface water diversions during low flow periods, among other water conservation measures. Reports that demonstrate noncompliance with the Water Storage and Use Standard Condition indicate that enrollees have not yet implemented operational changes necessary for achieving regulatory compliance. In this research, we analyzed data gathered from annual reports covering 2017 to gain a greater understanding of how water is extracted from the environment for cannabis cultivation. The data used in this study was collected from cannabis sites enrolled for regulatory coverage under the cannabis program.

The program was adopted in August 2015, with the majority of enrollees entering the program in late 2016 and early 2017. The data presented in this article was collected from annual reports submitted in 2018 ,flood and drain tray which reflected site conditions during the 2017 cultivation year. The data therefore represents, for the majority of enrollees in the cannabis program, the first full season of cultivation regulated by the water quality control board. Because the data was self-reported, we screened reports for quality and restricted the dataset to reports prepared by professional consultants. Most such reports were prepared by approved third-party programs that partnered with the board to provide efficient administration of, and verification of conformity with, the cannabis program. Additional criteria for excluding reports included claims of applying water from storage without any corresponding input to storage, substantial water input from rain during dry summer months and failure to list a proper water source. Reports containing outliers of monthly water extraction amounts were also identified and excluded due to the likelihood of erroneous reporting or the difficulty of estimating water use at very large operations. Extreme outliers were defined as those values outside 1.5 times the bounds of the interquartile range . Farms were not required to use water meters, and those without meters often estimated usage based on how frequently they filled and emptied small, temporary storage tanks otherwise used for gravity feed systems or nutrient mixing. The final dataset included 901 reports. Parcels of land where cannabis was cultivated — including multiple contiguous parcels under single ownership — constituted a site, and this is the scale on which reporting was conducted. The spatial extent of the cannabis program included all of California’s North Coast region ; however, only a subset of the counties in this region allow cannabis cultivation and therefore reports were only received from the following counties: Humboldt , Trinity , Mendocino and Sonoma . Because Sonoma County contributed relatively little data, we combined Sonoma County’s enrollments with those from Mendocino County when making county-level comparisons. The data used for this analysis included the source and amount of water that cultivators added to storage each month as well as the source and amount of water applied to plants each month. We did not analyze absolute water extraction rates. Rather, we used the amount of water extracted each month — whether water was added to storage or applied to plants directly from the source — to analyze seasonal variation in each water source’s share of total water extraction. Water sources included: surface , spring , rain , well , delivery and municipal.

The two external sources — delivery and municipal — were consolidated into a single category.Because staff from the water quality control board were not able to corroborate the accuracy of reported data, enrollees may have classified water sources erroneously. A well placed in proximity to a stream, for example, might properly qualify as a diversion of surface water; so might rainwater catchment ponds or spring diversions that are hydrologically connected to a watercourse. We attempted to minimize these potential errors by restricting the dataset to reports prepared by professional consultants. As mentioned, enrollees were required to assess several standard conditions in their site reports, including water storage and use requirements. To encourage cultivators to join the regulated industry, and because many cultivation sites existed prior to adoption of the cannabis program, existing sites were not required to comply with standard conditions as a prerequisite for enrollment. Rather, cultivators unable to comply with the standards when they enrolled were required to indicate their lack of compliance and develop a plan for achieving compliance. Such sites were not held in violation of regulations, thus removing a potential motivation to falsely report site conditions. More than one-quarter of enrollees in the dataset reported noncompliance with the Water Storage and Use Standard Condition. To address question 1 — from which sources cannabis cultivators most frequently extract water across the North Coast region, and if extraction patterns differ across the region — we calculated the percentage of sites that reported use of each water source . We also calculated, for sites using each source, the percentage of sites that also used at least one other source category. Directly applying water to plants and also placing water in storage did not constitute use of multiple extraction sources if the water was drawn from the same source category. Additionally, sites that used multiple inputs from the same category — for example, multiple wells — were not considered users of multiple sources, as this classification was reserved for extraction from multiple categories of sources. We performed all elements of our analysis for the entire dataset and for each county individually. To address question 2 — how reliance on each water source differed from one month to another — we divided each site’s monthly water extraction total by its annual extraction total to calculate the relative percentage of water extracted in each month, and performed similar calculations for each source category. The median amount of water extracted and interquartile range were calculated for each month — both for overall extractions and for each source category individually. To address question 3 — whether sites reporting compliance with the Water Storage and Use Standard Condition relied on different water sources than those reporting noncompliance — we compared water source extraction patterns for sites of both types. Specifically, we calculated for each compliance status the percentage of sites that extracted water from each source category and made comparisons accordingly; and did likewise for monthly extraction patterns, following procedures similar to those described in regard to question 2.

The purpose of this comparison was strictly qualitative, and no inferential statistics were performed to determine statistically significant differences. Instead, this element of our analysis was performed for exploratory purposes, with the intention of identifying broad trends that warrant future attention.The most commonly reported water source was wells . Over half the sites reported at least some reliance on wells for their irrigation water.Rainwater catchment and off-site water were the least commonly used water sources . Sites using wells and off-site sources were the least likely to use additional sources . In contrast, sites using rain catchment systems most frequently reported using an additional source category,hydroponic tables canada followed by sites reporting use of spring diversions and surface diversions . To determine if the observed high frequency of well use was due to bias associated with examining only reports prepared by consultants, we reincorporated sites without consultants and reran the analysis on this dataset . Reported well use was slightly more common among sites not using consultants than among sites using consultants . Counties displayed notable variation in the frequency with which cannabis cultivators used particular water sources . Compared to all sites in the dataset, sites in Humboldt County relied more on surface water and spring diversions , with fewer relying on wells . The pattern was reversed in Trinity County, with a high percentage of sites there reporting well use and relatively few using surface and spring diversions. A large number of sites in Trinity County were located in a single watershed known for a high concentration of similar cultivation practices, so we recalculated the percentages with these sites excluded. The resulting totals for Trinity County were closer to the overall results: wells , surface , spring , rain and off-site . Mendocino and Sonoma counties reported a similar pattern of extraction sources per site: wells , surface , spring , rain and off-site . Patterns of using multiple sources varied among counties. Sites in Humboldt County using well water extraction much more commonly used additional sources of water than did similar sites in Trinity and Mendocino/Sonoma counties. Use of additional sources was also more common among Humboldt County sites extracting surface water and spring water than among sites using surface and spring water in Trinity County and Mendocino/Sonoma counties . Wells were a prominent water source for cannabis cultivators during the summer months . Extraction from wells generally peaked in August and declined in off-season months. The pattern was reversed for rainwater use, with most extraction occurring in off-season months. Spring water use was generally even across the year, with slightly higher use during the growing season. Surface diversions occurred throughout the year, but declined late in the growing season, likely reflecting declining availability of surface water. The pattern exhibited in off-site water use closely matched that of well water; the former, however, was a less substantial source of water in general. There appeared to be differences in the extraction sources reported by compliant and non-compliant sites .

Although nearly one-third of non-compliant sites used well extraction, this source was more than twice as frequently reported among compliant sites . In contrast, non-compliant sites reported surface diversion and spring diversion more commonly than did compliant sites . Rain and off-site sources were the least commonly used for both compliant sites and non-compliant sites . Use of additional alternative sources was lower for compliant sites with wells than for non-compliant sites with wells . The seasonal extraction patterns of compliant and non-compliant sites were generally similar , following the overall pattern discussed above.We found that well water is the most commonly reported source of extracted water for cannabis cultivation in the North Coast region of California. Furthermore, among the source categories, wells are least frequently supplemented with alternative sources. Spring and surface water diversions together are also important water sources, with seasonal patterns of use that are distinct from well water extraction. Reported timing of well water extraction closely tracks the water demand patterns of plants, indicating that cultivators are applying well water directly to plants, rather than storing it. In contrast, the timing of extractions of spring water and surface water remains relatively consistent throughout the year, suggesting that water from these sources may be diverted to storage in the winter, reducing the need for extraction in the summer months. These seasonal extraction patterns and the relative predominance of each source may inform assessments of cannabis cultivation’s impacts on water availability.

Water pipes have become more popular in North America in recent years due to the belief that it is a safer alternative to cigarettes .This is a common misconception in young adults,as a water pipe smoking session can contain over 100 times the amount of smoke in comparison to a single cigarette .In Ontario,the rate of trying water pipes in adolescents has more than doubled from 6% in 2006 to 14% in 2013.Water pipe smoking is linked to several adverse health outcomes such as cancer,cardiovascular disease and decreased lung function.While the causal effect of water pipe smoke and asthma has not been demonstrated,exposure to tobacco smoke was shown to exacerbate asthma symptoms.Since water pipes produce tobacco smoke,it can be assumed that it will be harmful especially for those with asthma.Marijuana has been used as a forbidden medicine to treat asthma symptoms for years as it may have bronchodilator properties,while long term marijuana smoking has also been associated with increased respiratory symptoms.Overall,the relationship between marijuana and lung health is somewhat mixed and the connection may not be the same as tobacco smoke.Previous research has suggested that adolescents with asthma smoked significantly more marijuana than those without asthma.However,the number of adolescents who smoked marijuana in Canada has decreased from 32.7% in 2008 to 24.4% in 2013.Electronic cigarettes are battery powered devices that vaporise nicotine and/or other flavouring mixes,cannabis grow lights but do not burn tobacco.These products have become popular in recent years and they are perceived as a safer alternative to tobacco cigarettes.

While preliminary studies suggest that they may be less harmful than cigarettes,the long term health effects and how e-cigarettes relate to asthma symptoms or severity are unknown.The Canadian Tobacco,Alcohol and Drug Survey reported that as many as one in five adolescents aged 15e19 tried e-cigarettes,however,the absolute trend of usage is still unknown as these products are relatively new.The purpose of this paper is to examine whether adolescents with asthma smoke cigarettes,water pipes,marijuana or e-cigarettes more or less than those without asthma.This study adds to the current literature by examining all smoking habits for youth with asthma,rather than focusing just on cigarettes.The 2013 Ontario Student Drug Use and Health Survey is a population based survey conducted every two years and completed by grade 7e12 students at publically funded schools in Ontario,Canada.Ontario is the largest province in Canada with a population of over 13 million residents.Ontario includes major urban centres such as Toronto and Ottawa,several smaller cities and an abundance of rural lands.The OSDUHS is designed to collect information about drug use and other health related behaviours among students in Ontario.All parents and students gave consent prior to participation.To examine the association between smoking and asthma,we limit our study sample to high school students in 109 schools.These schools were selected with probability proportional to size,to obtain a representative sample within the province.The survey included questions that captured information on self-reported doctor diagnosed asthma and data on tobacco,alcohol and drug use.The survey used a random split-ballot design where some of the questions change on each of the surveys.The sample is randomly divided into 2 groups to maximize questions included and minimize burden on students,but it reduces the sample size for some questions.In the OSDUHS,approximately half of the full sample answered questions pertaining to asthma and all types of smoking reducing the sub-sample to 2,840.

Data are representative of students in Grades 9 to 12 attending publicly funded schools in Ontario.Ages for respondents range from 12 to 19 years of age.In Ontario,the majority of children attended publically funded schools,5% attended private schools,and another 3% were either home schooled,institutionalized for correctional or health reasons,schooled on a First Nation reserve,military base or lived in remote northern region.This study was approved by the research ethics board at the Research Institute of The Hospital for Sick Children.The primary outcome variables in this study are smoking status with regard to cigarettes,water pipes,marijuana and e-cigarettes.Self-reported frequency and intensity of cigarette,water pipe,marijuana and e-cigarette smoking in the last 12 months and lifetime use were measured in the survey.Cigarette non-smokers were classified as those who never smoked a cigarette or smoked less than one cigarette in the last 12 months,while cigarette smokers were those who smoked more than one cigarette in the past 12 months.Similarly,smoking status for water pipe was also classified as a binary outcome variable.Respondents were asked how often they smoked a water pipe in the last 12 months.Those who smoked a few puffs,never smoked,haven’t smoked in the past 12 months or didn’t even know what it was were considered non-water pipe smokers.Those who smoked one or more times were defined as smokers.Marijuana smoking is also defined in a similar manner.Students were asked how often they smoked cannabis in the past 12 months.If they smoked 1 or more times in the past year they were classified as a marijuana smoker.Respondents who have never or not smoked in the last 12 months were considered to be non-marijuana smokers.Finally,respondents were classified as e-cigarette smokers if they smoked an e-cigarette with or without nicotine in it,while those who have never smoked or never heard of e-cigarettes were considered non-smokers.The primary risk factor of interest is the presence of asthma which is captured by the response to the question “has a doctor or nurse ever told you that you have asthma”.Other potential confounding variables include: grade,sex and socioeconomic status.

SES was measured by a 10-point social ladder.Students were asked to imagine that the ladder represents how Canadian society is set up,where the people at the top of the ladder are the “best off”,meaning they have the best jobs,make the most money and have the highest education.Those at the bottom of the ladder are the “worst off”,with no job,or a job no one wants,little education and the least money.Respondents reported what best represents their family on a 10-point scale,which was further grouped into three levels based on the interquartile ranges.The percent distributions of demographic characteristics and other co-variates were compared between smokers and nonsmokers of each type and the any smoking variable.The chi-square test was used to measure statistical significance between the respondents with and without asthma.Each type of smoking was modelled separately using a binary logistic regression.In addition to doctor diagnosed asthma,all co-variates outlined above were included in the regression models.All interactions of smoking types were examined but no significant relationships were found so this study focussed on the four individual models,plus the combined any smoking outcome.The following was used as the reference group in the logistic regression models: grade 9,female and high SES.Given the OSDUHS used a probability stratified cluster sampling design,all analyses were conducted with the sampling weights and utilized Taylor series methods within Stata 14 v14.1 to derive unbiased standard errors and point estimates.Results of the regression models were presented in adjusted odds ratios with 95% confidence intervals.Goodness of fit tests were completed with the F-adjusted mean test.While cigarette smoking may aggravate symptoms and severity for adolescents with asthma,some work on the topic suggests that the prevalence of cigarette,water pipe and marijuana smoking was actually higher in adolescents with asthma than those without.These studies,however,are not conclusive as at least one reported that adolescents with asthma were less likely to smoke cigarettes.It is reasonable to suppose that adolescents with asthma will not smoke as it will aggravate their asthma severity and symptoms,but this unfortunately may not be the case.

Our study showed that students in grades 9e12 with asthma in Ontario,had a higher odds of smoking e-cigarettes or any substance than their peers who do not have asthma.The odds of smoking ecigarettes for adolescents with asthma,was nearly twice as high as those without asthma after adjusting for age,sex and SES.Given the cross-sectional design of the survey,we cannot infer the causal relationship between smoking and asthma.Previous studies suggest that smoking for adolescents with asthma may relate to the desire to obtain social status among one’s peers,and not wanting asthma to interfere with their social status.Of all demographic characteristics studied,student’s grade was most significantly associated with smoking cigarettes,water pipes and marijuana.A longitudinal study in the United States found that rates of cigarette smoking increased from 1.8% at the age of 9 to 22.5% by age 16.Findings suggest that rates for smoking cigarettes and water pipes among grade 9 students were relatively low,but doubled in grade 10,tripled by grade 11 and quadrupled by grade 12.Cigarette and water pipe smoking became more popular in grade 10 and the trend continued as they aged.E-cigarette smoking on the other hand only marginally increased from grade 9 to 12.For adolescents with asthma,rates of e-cigarette smoking were similar to that of the entire sample,cannabis grow tent ranging from about 10% in grade 9 to 16.7% in grade 12.Our study also showed that cigarette,marijuana and any smoking rates were inversely related to SES,where lower SES was associated with higher odds of smoking.Our finding is consistent with the literature that suggests an inverse relationship between individual SES or parental education and cigarette smoking in adolescents.It has been suggested that lower SES households may have a poorer attitude towards health,fewer opportunities or more stressful situations which make them more likely to smoke.Results from our study emphasise the need for tailored interventions for youth from lower SES households.This study had many strengths which relate to the size and generalizability of the survey sample and the fact that it examined how all types of smoking related to asthma prevalence.That being said,there are also some limitations.The primary purpose of this survey is to examine health risk behaviours of adolescents in Ontario and not asthma.As such,the number of respondents with asthma was low and this may have contributed to some of the insignificant findings.

Despite the low number of asthma respondents,the self-reported asthma prevalence rate of adolescents in this study was similar to that reported by the Ontario Asthma Surveillance Information System,which uses a validated health administrative data case definition to capture asthma with 84% sensitivity and 76% specificity.Secondly,the cross-sectional design of the survey is a major study limitation in assessing causal relation of asthma and smoking.It is unknown from this study whether adolescents with asthma smoked e-cigarettes more often or if smoking e-cigarettes contributed to the risk of asthma.Thirdly,asthma was self-reported and it not clinically confirmed.Self-reported asthma may over or under represent actual prevalence of asthma.Furthermore,many studies that examined the relationship between asthma and smoking did not separate severe or “uncontrolled” asthma from those with well-controlled mild to moderate asthma.The effect of smoking on adolescents with severe or uncontrollable asthma may be different than on those with mild to moderate asthma.The definition of smoking used may influence the study findings.We classified smoking for cigarettes,marijuana and water pipes as smoking one or more time over the past 12 months or ever for e-cigarettes.This definition includes those who smoke regularly but also adolescents who experiment with the various types of smoking.This classification of smoking has been used previously in studies using the OSDUHS dataset.We conducted additional analyses using another method of classifying smokers reported by Wong and colleagues.In this method a regular smoker is defined as smoking more than 100 cigarettes in their lifetime and any cigarettes in the past month.Using this method the results and point estimates remained very similar.Given this method of classification was only available for cigarettes,we opted to retain the ‘any cigarettes over the past 12 months’ method to ensure measurement correspondence with the other types of smoking.Nevertheless,results suggest that adolescents with asthma are at least experimenting with e-cigarettes or any type of smoking more often than their peers without asthma,which may lead to higher smoking rates later in life.Finally,we were unable to adjust for parental smoking or parental history of asthma as these data were not collected by the survey.Having a parent who smokes may relate to the respiratory health of children,but it also increases the odds of smoking for adolescents.While information on parental smoking is not available in our data,further research should examine the association between parental smoking and asthma for all types of smoking.This paper adds discussion to the question of whether adolescents with asthma would be less likely to smoke cigarettes,water pipes,marijuana or e-cigarettes.

Marijuana has also been reported as a risk factor for stroke. Over 80 cases have been reported in which patients had strokes, with a higher prevalence of ischemic strokes, that were associated with either a recent increase, in the days leading up to the event, or chronic history of heavy marijuana use. They believed that the marked swings in blood pressure or the reversible cerebral vasoconstriction that resulted from marijuana use were likely mechanisms of stroke but admitted that no firm conclusions could be drawn without further studies.In addition, Lawson reported a similar belief that drug induced vasospasm was a plausible explanation for TIAs, but also with the caveat that due to the confounding medications/illicit substances being used in his patient, no direct association could be determined. Also of interest is marijuana use’s effect on other cardiovascular vessels. When cohort studies were performed comparing marijuana users with resultant limb arteritis to patients suffering from thromboangiitis obliterans, marijuana associated arteritis occurred in younger, usually male patients with a unilateral, lower limb as the common presentation.Due to the unfiltered nature of the marijuana cigarette compared to commercially available tobacco cigarettes,grow table the amount of carcinogens and irritants, like tar, that enter the upper airway is increased with approximately a three-fold increase in tar inhalation and one third more tar deposition in the respiratory tract.

More specifically, the tar produced from cannabis smoke contains greater concentration of benzanthracenes and benzopyrenes than tobacco smoke. In addition, as compared to smoking tobacco, there is a two-thirds greater puff volume, one-third greater depth of inhalation and a four-fold longer breath-holding time, all of which are common practices to try to maximize THC absorption, which is around 50% of cigarette content. These practices result in five times the amount of carboxyhemoglobin levels as compared to the typical tobacco smoker despite the presence of similar quantities of carbon monoxide from the incomplete combustion of the organic compounds found within each product. In reporting his case, Schwartz theorized that high temperatures in which marijuana burns compared to tobacco may increase the irritancy of marijuana to the mucous membranes. While the higher temperature is a possibility, the evidence of marijuana’s irritancy is well documented. In a cohort study comprised of 40 healthy patients, Roth et al. showed that cannabis smokers had significantly increased visual bronchitis index scores resulting from large airway epithelial damage, edema, and erythema. On mucosal biopsy, goblet cell hyperplasia with subsequent increase in secretions, loss of ciliated epithelium and squamous metaplasia were also present in 97% of smokers. They concluded that marijuana use is associated with airway inflammation that is similar to that of a tobacco smoker. A cross-sectional study on over 6000 patients, from 1988 to 1994, found an increased incidence of chronic bronchitis symptoms such as wheezing and productive cough occurring in patients 10 years younger, on average, than tobacco smokers. Case-control trials performed found similar findings with regards to increases in wheezing, shortness of breath, cough and phlegm as well as the similarities with tobacco use. Bryson also concluded based on his review of the literature, that the pulmonary complications in the chronic marijuana smoker are equivalent to those seen in the chronic tobacco smoker, while Wu et al. estimated that 3e4 cannabis cigarettes daily equates to about 20 tobacco cigarettes in terms of bronchial tissue damage.

Cannabis use has also been linked to a higher risk in cancers, possibly due to the increased carcinogens entering the airway. Similar to tobacco use, marijuana use plays a significant role in the development of lung cancer. In a case control study performed in New Zealand, young adults had an 8% increase in lung cancer risk for each joint year of cannabis smoking after adjusting for the cofounders, such as age, sex, ethnicity and family history. Berthiller et al. pooled data from a multitude of institutions across multiple countries, comprising of over 1200 patients, and reported an increased risk of lung cancer for every marijuana use. In addition, a 40 year cohort study with about 48,000 patients reported an increased risk of lung cancer in young men who had smoked marijuana more than 50 times. This study was limited however by the nature of patient self-reporting. Head and neck cancers have also been theorized to be at a higher risk similar to that of tobacco smoking. However, a pooled analysis performed by Berthiller et al. found that infrequent marijuana smoking did not confer a greater risk after adjusting for cofounders. The authors did note that due to the low prevalence of frequent smoking within the study population, that a moderately increased risk could not be ruled out. In another population based casecontrol study, there was an increased incidence of head and neck cancers in patients with a 30 joint-year history, yet the association did not exist when accounting for tobacco smoking suggesting the risk is greater with tobacco than marijuana.Marijuana’s prevalence is evident amongst all patient populations. In a cross sectional study conducted by Mills et al., the rate of marijuana use via patient self-reporting was found to be 14% amongst surgical patients in 2003. This led the authors to conclude that questions about illicit drug use should be a routine part of the preanesthetic assessment, especially in patients that the anesthesiologist finds hard to settle, due to anxiety or other psychologic manifestations, because of the potential anesthetic complications that may occur.

In a series of case reports, Guarisco presented three patients who suffered from significant respiratory distress due to isolated uvulitis, a disease of low incidence typically associated with infection or traumatic irritation from instruments used in the airway. Investigating further, all three patients were found to have inhaled large quantities of cannabis within six to twelve hours of the onset of symptoms leading to the conclusion of a possible correlation with inhaled irritants such as cannabis. Due to known cases of isolated uvulitis and the possible link with marijuana, the authors suggest that toxicology urine and blood studies for THC should be performed in cases where marijuana use is suspected but not confirmed by history taking. Multiple other cases have also been reported with similar findings. In a case series by Sloan, three adolescents suffered acute uvular inflammation post the heavy use of marijuana, having smoking at least three marijuana cigarettes, despite negative throat cultures. In 1971, a cohort study was performed in which a large quantity of marijuana, over 100 grams, was smoked over several months. Of the 31 subjects, almost half suffered from recurrent rhinopharyngitis as well as developed acute uvular edema after the heavy marijuana inhalation which lasted approximately 12e24 hours. These findings stress the importance in the maintenance of the airway during anesthesia following acute marijuana use due to the potential airway obstruction that may occur. In fact, in presenting a case of uvular edema and airway obstruction with cannabis inhalation 4 hours prior to surgery, Pertwee recommended that elective operations should be avoided altogether if a patient was recently exposed to cannabis smoke. This recommendation seems reasonable when taking into consideration the life-threatening bronchospasm leading to asphyxia, brain damage or death resulting from tracheal intubation in patients with obstructive airways. One proposed course of action has been the therapeutic use of steroids. In Guarisco’s study, he theorized that steroids should help inhaled irritant uvulitis. As steroids increase endotracheal permeability, decrease mucosal edema and stabilize lysosomalmembranes, thus decreasing the inflammatory response, the theory has scientific basis. In a prospective, randomized,4×8 grow table with wheels double-blind study, Silvanus et al. found that the addition of methylprednisolone to salbutamol in patients with a partially reversible airway obstruction helped in the diminution of the reflex bronchoconstriction that can result from tracheal intubation.

This led to Hawkins et al.’s recommendation that at the first signs of airway obstruction, dexamethasone should be used as the drug of choice, 1 mg/kg every 6e12 hours over the course of one to two days. This recommendation gained credence in the dramatic relief that dexamethasone provided in the post-traumatic cases. However, Mallat et al. concluded that although marijuana-induced uvular edema is a serious postoperative complication that has a potential for simple treatment, in the case of an elective surgical procedure with an acute history of cannabis exposure, surgery should be can celled as prophylactic treatment may not be effiffifficient. The complications of the airway are not limited to intubation however. The inhalation of toxic chemicals as well as smoke can cause laryngospasm by chemoreceptor stimulation. In addition, the inhalation of hot gasses can trigger laryngospasm via thermoreceptor stimulation, especially in the case of lowered sensory afferent neuron threshold potentials such as in light anesthesia. In line with this, White presented a case in which a known cannabis smoker suffered severe laryngospasm following extubation. As found within the reviews, multiple observations have been made showing cross tolerance between marijuana and barbiturates, opioids, prostaglandins, chlorpromazine and alcohol. In addition, animal studies have shown additive effects amongst them all except for alcohol. These drug interactions have led to further exploration of its reactions to other medication groups. As a result of fat sequestration and subsequent slow elimination from the tissues, cannabinoids may be present to interact with multiple anesthetic agents. In Symons’s case report, the patient required multiple boluses of propofol and two additional doses of midazolam to achieve appropriate sedation. In a prospective, randomized, single-blind study of 60 patients, chronic marijuana users required significantly increased doses of propofol to facilitate successful insertion of the laryngeal mask and thus suggesting that the increased doses, in chronic marijuana users, may be a requirement for appropriate loss of consciousness as well as jaw relaxation and airway reflex depression. The authors theorized that the variations in the level of delta9-THC can explain variations in propofol responses.

In a review written in the American Association of Nurse Anesthetists Journal, Dickerson reported the synergistic effects of cannabis to include: potentiation of nondepolarizing muscle relaxants, potentiation of norepinephrine, the augmentation of any drug causing respiratory or cardiac depression, as well as a more profound response to inhaled anesthetics sensitization of the myocardium to catecholamines due to the increased level of epinephrine. On the subject of muscle relaxants, THC depletes acetylcholine stores and exerts an anticholinergic effect and thus creates a potentiation of the nondepolarizing muscle relaxants. Areview by Hall et al. explored THC’s interaction with drugs affecting heart rate and arterial pressure and found that due to cannabis’s own cardiovascular effects , it may interact with medications such as beta-blockers, anticholinergics and cholinesterase inhibitors. Due to these potential autonomic reactions, as well as theoretical psychiatric complications, such as withdrawal effects and their interference with anesthetic induction or postoperative recovery, there has been a stress made to inquiring about drug history or avoiding elective operations altogether. Dickerson, in his review, recommended that, due to all potential effects and interactions, not only should an extensive history of drug use be elicited at the time of the preoperative assessment, including the frequency of use and time of last use, but that anesthesia should be avoided in any patient with cannabis use within the past 72 hours.This gained further credibility in a randomized, double-blind trial, in which an apparent drug interaction was observed in the patient population who underwent general anesthesia within 72 hours of marijuana use leading to a sustained postoperative tachycardia, a finding potentially due to an interaction between cannabinol metabolites and atropine administration during anesthesia.One of the most researched and known risk factor for perior postoperative complications, increased hospitals costs and resource usage is smoking, specifically tobacco smoke. In fact, the rates of perioperative respiratory events, such as reintubation, hypoventilation, hypoxemia, laryngospasm, bronchospasm, and aspiration, have a total incidence of 5.5% in smokers compared to 3.1% in nonsmokers, making these events 70% more prevalent with smoking. In addition, in a randomized controlled trial out of Denmark, orthopedic surgery patients who smoked were compared to those who underwent cessation counseling and nicotine replacement therapy. In the study, they found an overall complication rate of 18% compared to the 52% found in the smoking group, including a cardiac event rate of 0% compared to 10%.