Restricting supply of tobacco products to pharmacies: a scoping review.

OBJECTIVE: We synthesised the published literature on proposals to restrict tobacco supply to pharmacies, covering (1) policy concept/rationale/attempts, (2) policy impact and implementation and (3) policy and research recommendations. DATA SOURCES: We searched eight databases (PubMed, CINAHL, Scopus, Web of Science, Embase, IPA, ProQuest and OATD) for publications with at least an English-language abstract. We searched reference lists of included publications manually. STUDY SELECTION: One author screened all publications, and a second author reviewed a 10% subset. We focused on approaches to restrict the supply of tobacco products to pharmacies, without any restrictions on study design, location, participants or publication date. DATA EXTRACTION: Data extraction adhered to the JBI Scoping Review Methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. DATA SYNTHESIS: We included 18 publications. Among the 13 studies conducted in specific geographical contexts, 8 were from Aotearoa/New Zealand. Most publications (n=8) focused on effectiveness domains, indicating potential reductions in retailer density, smoking prevalence, disease burden, cost and increased opportunities for cessation advice. Seven explored policy acceptability among experts, pharmacists and people who smoke. Publications noted that pharmacy-only supply aligns with other programmes involving pharmacists, such as needle exchange programmes, but conflicts with efforts to phase out tobacco sales from the US and Canadian pharmacies. CONCLUSIONS: Progress in tobacco retailing policy (eg, licensing, retailer incentives) and research (eg, assessment of policy equity and durability, application in other geographical contexts) are needed before a pharmacy-only tobacco supply model would be feasible.

Will Australia's tightened prescription system reduce nicotine vaping among young people?

BACKGROUND: Australia introduced a prescription only policy for e-cigarettes in 2011 to prevent uptake among youth while allowing smokers to access e-cigarettes for cessation. This is one of the restrictive forms of regulation for e-cigarettes recommended by the World Health Organisation. AIMS: To assess whether the policy has prevented e-cigarette youth uptake and facilitated smokers' access to e-cigarettes for cessation; and to examine a proposed toughening of the policy. METHODS: An analysis of survey and administrative data on e-cigarette use and smoking and a critical analysis of the contents of submissions to parliamentary inquiries into the policy. RESULTS: E-cigarette use among youth and young adults has increased steeply since 2016 but very few of these products have been obtained through the prescription system, because medical authorities discourage their use. A policy change in 2021 to increase the prescription of e-cigarettes has not reduced e-cigarette use among youth and only marginally increased rates of prescribing. Australian policy makers have nonetheless tightened the prescription system by banning any use of e-cigarettes unless prescribed by a doctor and dispensed by a pharmacist. IMPLICATIONS: Australia's tightened prescription policy for e-cigarettes may reduce adolescent vaping but at the risk of reducing smokers' access to e-cigarettes and increasing the size of the illicit market for combustible cigarettes and e-cigarettes. A more effective policy would allow vapes to be sold as consumer products by licensed tobacconists under regulations that require prior product approval, plain packaging, bans on their promotion and enforced age restrictions on purchases.

Designing observational studies for credible causal inference in addiction research-Directed acyclic graphs, modified disjunctive cause criterion and target trial emulation.

Randomized controlled trials (RCTs) are considered the gold standard for causal inference. With a sufficient sample size, randomization removes confounding up to the time of randomization and allows the treatment effect to be isolated. However, RCTs may have limited generalizability and transportability and are often not feasible in addiction research due to ethical or logistical constraints. The importance of observational studies from real-world settings has been increasingly recognized in research on health. This paper provides an overview of modern approaches to designing observational studies that enable causal inference. It illustrates three key techniques, Directed Acyclic Graphs (DAGs), modified Disjunctive Cause Criterion and Target Trial Emulation, and discusses the strengths and limitations of their applications.

Participation in Australian drug treatment programs for individuals engaging in high-risk substance use: Data from a nationally representative sample.

INTRODUCTION: Substance use, including drugs, alcohol and smoking have a significant health, social and economic impact. We aim to assess the rate and factors associated with treatment access among individuals with high-risk substance use. METHOD: This study is a cross-sectional analysis of the 2019 Australian National Drug Strategy Household Survey (N = 22,015). Participants were persons with high-risk substance use based on the Alcohol, Smoking and Substance Involvement Screening Test-Lite (ASSIST-Lite) and current smokers. We measured self-reports of past 12-month engagement in a tobacco, alcohol or other drugs treatment program. RESULTS: Overall, 0.4% had high-risk drug use (0.3% cannabis, 0.1% meth/amphetamine or 0.1% opioids), 7.4% had high-risk alcohol use, and 14.0% currently smoked. Among high-risk users, past 12-month treatment access rates were 50.6% [22.3-78.9%] for opioids, 27.1% [8.1-46.1%] for meth/amphetamine, 14.5% [4.3-24.7%] for cannabis, 9.6% [8.1-11.0%] for alcohol and 11.7% [10.6-12.9%] for current smoking. The primary source of treatment support was information and education (12.7% drugs, 4.6% alcohol, 4.0% smoking), followed by counselling (6.7% drugs, 4.5% alcohol, 3.0% smoking). Online or internet support was accessed by 5.9% (drug) and 1.6% (alcohol) people with high-risk use. Psychological distress was associated with treatment access (drugs: odds ratio 3.03 [0.77-11.95], p = 0.111; alcohol: odds ratio 3.16 [2.20-4.56], p ≤ 0.001; smoking: odds ratio 1.95 [1.52-2.49], p ≤ 0.001). DISCUSSION AND CONCLUSIONS: The proportion of people engaging in risky substance use who had used treatment programs remains low, especially for alcohol. Public health strategies to scale up treatment access are warranted.

How much cannabis is used in a joint in Australia? An experimental investigation into use by potency and frequency.

INTRODUCTION: Cannabis use is highly prevalent in Australia, yet current survey metrics measure tetrahydrocannabinol (THC) exposure with limited accuracy. Often survey items measure cannabis quantity by assuming specific modes of use (i.e., 'how many joints do you use?'), which fail to capture variations in cannabis use and the diverse modes of use (e.g., joints, cones, spliffs). This study investigated how much cannabis is used in these modes of administration in an Australian sample. METHODS: Participants (N = 31, Mage = 25.77; 51% university students) completed the Roll a Joint Paradigm in which they rolled joints, spliffs and packed cones as they would typically, using oregano as 'cannabis.' Participants then prepared each again but with cannabis of higher or lower potency. RESULTS: The amount of cannabis used across different modes of administration was variable: joints (range 0.10-1.25 g), spliffs (range 0.12-1.21 g) and cones (range 0.03-0.41 g). Participants who used cannabis daily rolled three times the amount of cannabis into a joint. DISCUSSION AND CONCLUSIONS: The amount of cannabis used in common modes of administration may be highly variable. Daily use may be associated using larger quantities of cannabis. Titration attempts based on potency were not proportional or consistent across modes of administration. The results indicate people may adjust the quantity of cannabis based on perceived potency, however, not proportional to THC concentration. Inconsistency in the amount of cannabis used based on potency and within different modes of administration may represent a problem for self-report metrics which ask participants to report cannabis use in joints.

Longitudinal association between exposure to e-cigarette advertising and youth e-cigarette use in the United States.

BACKGROUND AND AIM: E-cigarette marketing strategies are targeting and appealing to youth, particularly through social media. This study examined the longitudinal relationship between recalled exposure to e-cigarette advertisements on social media and across five traditional advertising mediums, and e-cigarette use, a year later. DESIGN: Weighted regression analyses of waves 4 (W4; 2017), 4.5 (W4.5; 2018) and 5 (W5; 2019) from the Population Assessment of Tobacco and Health Study. SETTING: United States. PARTICIPANTS: Youth aged 12-17 years at W4 or W4.5 (N = 16,671). MEASUREMENTS: We examined the association between past 30-day recalled exposure to six different e-cigarette advertisement mediums (gas stations/convenience stores, social media/websites, newspaper/magazines, radio, billboard, TV) in W4.5 and past 30-day and past 12-month e-cigarette use in W5, while controlling for W4 e-cigarette use and covariates such as sociodemographic variables, academic performance, peer cigarette/e-cigarette use and other substance use. Associations between recalled exposure (W4.5) and lifetime use (W5) among e-cigarette naïve youth at W4.5 (N = 8,914) were also assessed. FINDINGS: Past 12-month and past 30-day e-cigarette use was significantly associated with recalled exposure to e-cigarette advertisement on social media/websites (aOR = 1.65 [99.17 %CI = 1.36,1.99; aOR = 1.49 [99.17 %CI = 1.13, 1.97]) and gas stations/convenience stores (aOR = 1.33; [99.17 %CI = 1.11,1.58]; aOR = 1.27 [99.17 %CI = 1.03,1.58]). Exposure to e-cigarette advertisement on social media/websites (aOR = 1.35 [99.17 %CI = 1.04,1.74]) and gas stations/convenience stores (aOR = 1.67 [99.17 %CI = 1.31,2.13]) was significantly associated with lifetime e-cigarette use among baseline youth who were e-cigarette naïve. CONCLUSIONS: Exposure to e-cigarette advertisement on social media/websites and gas stations/convenience stores was associated with youth e-cigarette use a year later. Stricter restrictions on marketing in these mediums is needed to limit youth exposure to e-cigarette marketing messages if we are to reduce e-cigarette use.

Predicting the long-term effects of electronic cigarette use on population health: a systematic review of modelling studies.

OBJECTIVE: To systematically review and synthesise the findings of modelling studies on the population impacts of e-cigarette use and to identify potential gaps requiring future investigation. DATA SOURCE AND STUDY SELECTION: Four databases were searched for modelling studies of e-cigarette use on population health published between 2010 and 2023. A total of 32 studies were included. DATA EXTRACTION: Data on study characteristics, model attributes and estimates of population impacts including health outcomes and smoking prevalence were extracted from each article. The findings were synthesised narratively. DATA SYNTHESIS: The introduction of e-cigarettes was predicted to lead to decreased smoking-related mortality, increased quality-adjusted life-years and reduced health system costs in 29 studies. Seventeen studies predicted a lower prevalence of cigarette smoking. Models that predicted negative population impacts assumed very high e-cigarette initiation rates among non-smokers and that e-cigarette use would discourage smoking cessation by a large margin. The majority of the studies were based on US population data and few studies included factors other than smoking status, such as jurisdictional tobacco control policies or social influence. CONCLUSIONS: A population increase in e-cigarette use may result in lower smoking prevalence and reduced burden of disease in the long run, especially if their use can be restricted to assisting smoking cessation. Given the assumption-dependent nature of modelling outcomes, future modelling studies should consider incorporating different policy options in their projection exercises, using shorter time horizons and expanding their modelling to low-income and middle-income countries where smoking rates remain relatively high.

Common adverse events of electronic cigarettes compared with traditional nicotine replacement therapies: A systematic review and meta-analysis.

ISSUES: Established literature suggests that electronic cigarettes (EC) are more effective than traditional nicotine replacement therapies (NRT) as a smoking cessation aid, but the factors that mediate this difference remain poorly understood. We examine how adverse events (AE) associated with EC use relative to NRTs differ, with the view that differences in AEs experienced may drive differences in use and compliance. APPROACH: Papers for inclusion were identified via a three-tiered search strategy. Eligible articles involved healthy participants and compared nicotine ECs to non-nicotine ECs or NRTs and reported frequency of AE as an outcome. Random-effects meta-analyses were conducted to compare the likelihood for each of the AEs between nicotine ECs, non-nicotine placebo ECs and NRTs. KEY FINDINGS: A total of 3756 papers were identified, of which 18 were meta-analysed (10 cross-sectional and 8 randomised controlled trials). Meta-analytic results found no significant difference in the rates of reported AEs (i.e., cough, oral irritation, nausea) between nicotine ECs and NRTs, and between nicotine and non-nicotine placebo ECs. IMPLICATIONS: The variation in the incidence of AEs likely does not explain user preferences of ECs to NRTs. Incidence of common AEs reported because of EC and NRT use did not differ significantly. Future work will need to quantify both the adverse and favourable effects of ECs to understand the experiential mechanisms that drive the high uptake of nicotine ECs relative to established NRTs. CONCLUSIONS: There is inconclusive evidence on the incidence of AEs experience when using ECs compared to NRTs, possibly given the small sample size of studies.

Global prevalence of heated tobacco product use, 2015-22: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Heated tobacco products (HTPs) are electronic devices that heat process tobacco to release an aerosol containing nicotine and other chemicals. Limited data exist on world-wide HTP use prevalence. This meta-analytic review estimated the prevalence of HTP use by country, World Health Organization (WHO) region, year, sex/gender and age. METHODS: Five databases (Web of Science, Scopus, Embase, PubMed and PsycINFO) were searched between January 2015 and May 2022. Included studies reported the prevalence of HTP use in nationally representative samples post-modern HTP device market entry (2015). A random-effects meta-analysis was used to estimate overall prevalence for life-time, current and daily HTP use. RESULTS: Forty-five studies (n = 1 096 076) from 42 countries/areas from the European Region (EUR), Western Pacific Region (WPR), Region of the Americas (AMR) and African Region (AFR) met inclusion criteria. Estimated pooled prevalence for life-time, current and daily HTP use was 4.87% [95% confidence interval (CI) = 4.16, 5.63], 1.53% (95% CI = 1.22, 1.87) and 0.79% (95% CI = 0.48, 1.18), respectively, across all years (2015-22). Life-time HTP use prevalence significantly increased by 3.39% for WPR [0.52% (95% CI = 0.25, 0.88) in 2015 to 3.91% (95% CI = 2.30, 5.92) in 2019] and 5.58% for EUR [1.13% (95% CI = 0.59, 1.97) in 2016 to 6.98% (95% CI = 5.69, 8.39) in 2020]. Current HTP use increased by 10.45% for WPR [0.12% (95% CI = 0, 0.37) in 2015 to 10.57% (95% CI = 5.59, 16.88) in 2020] and 1.15% for EUR [0% (95% CI = 0, 0.35) in 2016 to 1.15% (95% CI = 0.87, 1.47) in 2020]. Meta-regression revealed higher current HTP use in WPR [3.80% (95% CI = 2.88, 4.98)] compared with EUR [1.40% (95% CI = 1.09, 1.74)] and AMR [0.81% (95% CI = 0.46, 1.26)] and for males [3.45% (95% CI = 2.56, 4.47)] compared with females [1.82% (95% CI = 1.39, 2.29)]. Adolescents had higher life-time HTP use prevalence [5.25% (95% CI = 4.36, 6.21) than adults [2.45% (95% CI = 0.79, 4.97)]. Most studies scored a low risk of sampling bias due to their nationally representative sampling. CONCLUSION: The prevalence of HTPs use increased in the EUR and WPR between 2015 and 2020, with nearly 5% of the included populations having ever tried HTP and 1.5% identifying as current users during the study period.

National Wastewater Reconnaissance of Analgesic Consumption in Australia.

A wastewater-based epidemiology (WBE) method is presented to estimate analgesic consumption and assess the burden of treated pain in Australian communities. Wastewater influent samples from 60 communities, representing ∼52% of Australia's population, were analyzed to quantify the concentration of analgesics used to treat pain and converted to estimates of the amount of drug consumed per day per 1000 inhabitants using pharmacokinetics and WBE data. Consumption was standardized to the defined daily dose per day per 1000 people. The population burden of pain treatment was classified as mild to moderate pain (for non-opioid analgesics) and strong to severe pain (for opioid analgesics). The mean per capita weighted total DDD of non-opioid analgesics was 0.029 DDD/day/person, and that of opioid-based analgesics was 0.037 DDD/day/person across Australia. A greater burden of pain (mild to moderate or strong to severe pain index) was observed at regional and remote sites. The correlation analysis of pain indices with different socioeconomic descriptors revealed that pain affects populations from high to low socioeconomic groups. Australians spent an estimated US $3.5 (AU $5) per day on analgesics. Our findings suggest that WBE could be an effective surveillance tool for estimating the consumption of analgesics at a population scale and assessing the total treated pain burden in communities.

Efficacy of smokeless tobacco for smoking cessation: a systematic review and meta-analysis.

OBJECTIVE: Smoking remains prevalent in many countries despite rigorous tobacco control strategies. The use of Swedish snus, a type of low-nitrosamine smokeless tobacco, has been promoted as a tobacco harm reduction strategy. DATA SOURCES AND STUDY SELECTION: Three databases were searched for studies that assessed the effectiveness of snus in promoting smoking abstinence. A total of 28 studies were reviewed (5 randomised controlled trials (RCTs), 7 longitudinal and 16 cross-sectional studies). DATA EXTRACTION: Separate meta-analyses were conducted by study type, pooling effect estimates where outcome measures and design were sufficiently comparable. Study details and quality assessment (Risk of Bias 2 for RCTs, Newcastle-Ottawa Scale for observational studies) are provided for each study. DATA SYNTHESIS: While the meta-analysis of RCTs did not show a significant association between snus use and smoking cessation (risk ratio (RR)=1.33, 95% CI 0.71 to 2.47 and RR=0.62, 95% CI 0.27 to 1.41), the results of the meta-analysis of longitudinal cohort studies (RR=1.38, 95% CI 1.05 to 1.82, p=0.022) and cross-sectional studies (OR=1.87, 95% CI 1.29 to 2.72, p=0.001) indicated that use of snus was associated with an increased likelihood of quitting or having quit smoking. There was significant heterogeneity in the cross-sectional studies, and leave-one-out analysis indicated that the longitudinal cohort results were driven by one study. Most studies examined were subject to an elevated risk of bias. CONCLUSION: There is weak evidence for the use of snus for smoking cessation. Better RCTs and longitudinal studies are needed; meanwhile, existing cessation aids may be better placed than snus to promote abstinence.

Vaping on TikTok: a systematic thematic analysis.

INTRODUCTION: The rising popularity of TikTok among adolescents may influence their awareness and perceptions of e-cigarette use via user-generated content. This study aimed to examine how e-cigarette/vaping-related videos are portrayed on TikTok. METHODS: The nine most viewed hashtag based keywords were used to identify popular e-cigarette/vaping-related videos on TikTok (n=1000) from its inception (earliest upload date: January 2019) to November 2020. Five researchers independently coded the number of views, likes, user category and theme. RESULTS: A final sample of 808 e-cigarette/vaping-related videos that met study criteria were included. Collectively, these videos were viewed over 1.5 billion times, with a median view count of 1 000 000 (range 112 900-78 600 000) and a median 'likes' count of 143 000 (range 10 000-1 000 000). A majority of the videos portrayed e-cigarette use positively (63%; collectively viewed over 1.1 billion times). Neutral depictions of e-cigarette use were viewed a total of 290 million times (24%) and negative depictions of e-cigarettes were viewed a total of 193 million times (13%). The video themes included (not mutually exclusively): 'comedy and joke' (52%; total of 618 million views), 'lifestyle and acceptability' (35%; 459 million), 'marketing' (29%; 392 million), 'vaping tricks' (20%; 487 million), 'nicotine and addiction' (20%; 194 million), 'creativity' (16%; 322 million) and 'warning' (11%; 131 million). CONCLUSION: Our findings illustrated that positively framed e-cigarette and vaping-related postings available without age restrictions on TikTok-a rising video-sharing platform that is popular among adolescents-have been viewed many times. Effective age restrictions are needed to reduce adolescents' potential exposure to videos that portray vaping positively.

Prevalence and correlates of cannabis use for medicinal reasons - An Australian cross-sectional study.

Objective: It is important to know the prevalence and source of medicinal cannabis use in the population because non-prescribed medicinal use of cannabis products places individuals at higher risk of harms. We estimated the prevalence and correlates of the use of cannabis for medicinal purposes in Australia, three years after Australians were given legal access. Design: Cross-sectional. Setting: The 2019 Australian National Drug Strategy Household Survey. Participants: Participants were 22,015 Australians aged 14 or above. Outcome measure: Self-reported cannabis use in the last 12 months for medicinal purposes only, both medicinal/recreational reasons, or recreationally only. Those who reported medicinal use were asked if it had been prescribed by a doctor. Prevalence estimates were weighted to the population and multinomial logistic regression examined the correlates. Results: The prevalence of any medicinal cannabis use in the past year was 2.6%. Only 0.8% of the sample reported using cannabis solely for medicinal reasons, 95.9% of whom did not have a prescription. A self-reported diagnosis of cancer was associated with medicinal use only. Self-reported chronic pain was associated with both medicinal only and medicinal/recreational use. Medicinal cannabis use was associated with opioids use. Conclusions: In 2019, the prevalence of cannabis use solely for medicinal reasons remains under 1%, was more common among people with specific medical conditions, but most individuals do not have a prescription. The prevalence of self-reported medicinal cannabis use in Australia is low and there is limited use of the legal pathway for medicinal cannabis.

Changes in patterns of youth multiple tobacco and/or e-cigarette product use in the US between 2014 and 2020: a multiple-group latent class analysis.

BACKGROUND: Multiple tobacco and e-cigarette product (MTEP) use, the concurrent use of two or more different types of tobacco and/or e-cigarettes products, is common among young people in the US. Changes in patterns of MTEP use among US youth between 2014 and 2020 were identified and the determinants of MTEP use were examined. METHODS: Four years of repeated cross-sectional data from the US National Youth Tobacco Survey of middle and high school students from grade 6 to 12 (Ntotal=77 402). Multigroup latent class analysis (LCA) was applied to the data series to allow for simultaneous identification of MTEP use patterns between 2014 and 2020. Logistic regression was used to predict class membership on demographic and tobacco-related variables. FINDINGS: Over the 7-year period, LCA identified three patterns: minimal/non-users (MNU: ~89.8%), mostly occasional e-cigarette and cigarette users (MOEC: ~9%) and polytobacco users (POLY: ~1.2%). From 2014 to 2020, MNU increased from 86.4% to 92% (p<0.05), while MOEC and POLY decreased from 11.2% to 7.9% and from 2.4% to 0.1%, respectively. The probability of regular e-cigarette use increased from 0 to 2.3% among MNU, 6% to 31.9% among MOEC and 29.6% to 67.6% among POLY (p<0.05). In binomial logistic regression, being male, in high school, non-heterosexual, living with someone who uses tobacco at home, having cognitive difficulties, having lower perceptions of tobacco's danger and exposure to tobacco marketing were associated with greater odds of MOEC and POLY than MNU. CONCLUSIONS: There was an increase in regular e-cigarette use in all three classes, but a corresponding decrease in the proportion of MTEP use. Public health interventions to discourage uptake of e-cigarettes, such as tighter restrictions on marketing to minors, are warranted and there is a need to consider disparities in the determinants of MTEP use.

Tobacco and nicotine use.

Tobacco smoking is a major determinant of preventable morbidity and mortality worldwide. More than a billion people smoke, and without major increases in cessation, at least half will die prematurely from tobacco-related complications. In addition, people who smoke have a significant reduction in their quality of life. Neurobiological findings have identified the mechanisms by which nicotine in tobacco affects the brain reward system and causes addiction. These brain changes contribute to the maintenance of nicotine or tobacco use despite knowledge of its negative consequences, a hallmark of addiction. Effective approaches to screen, prevent and treat tobacco use can be widely implemented to limit tobacco's effect on individuals and society. The effectiveness of psychosocial and pharmacological interventions in helping people quit smoking has been demonstrated. As the majority of people who smoke ultimately relapse, it is important to enhance the reach of available interventions and to continue to develop novel interventions. These efforts associated with innovative policy regulations (aimed at reducing nicotine content or eliminating tobacco products) have the potential to reduce the prevalence of tobacco and nicotine use and their enormous adverse impact on population health.

A wastewater-based assessment of the impact of a minimum unit price (MUP) on population alcohol consumption in the Northern Territory, Australia.

AIM: To test if there was a reduction in alcohol consumption in wastewater samples in the Northern Territory of Australia after the implementation of a minimum unit alcohol price policy (MUP) in October 2018. DESIGN, SETTING, CASES: Between August 2016 and February 2020, wastewater samples were collected across 66 sites in the Northern Territory and all other states and territories in Australia. Samples were collected every 2 months in capital cities and every 4 months in regional places during this period. Overall, 4917 samples were taken (2816 before MUP and 2101 after). MEASUREMENTS: The number of standard drinks per 1000 people per day in the respective catchment areas was estimated based on the concentration of an alcohol-specific metabolite, ethyl sulphate in the samples (using the excretion factor of ethyl sulphate, the flow of wastewater entering the wastewater treatment plants and the population of each wastewater catchment). FINDINGS: Results from a linear mixed model showed that there was a large drop in alcohol consumption immediately after the MUP in Northern Territory [estimated drop = 1231, 99% confidence interval (CI) = 830, 1633; 38.75%]. There was no significant drop in all other states/territories except for Queensland, which showed a significant but much smaller drop (estimated drop: 310; 99% CI = 114, 550). One year after the MUP, the drop narrowed to 520 (99% CI = 189, 851) and was no longer statistically significant in February 2020 (15 months after MUP; estimated drop = 283, 99% CI = -114, 681). CONCLUSIONS: Per-capita consumption of alcohol appears to have decreased substantially in the Northern Territory of Australia immediately after the implementation of a minimum unit price but consumption steadily recovered and almost returned to the pre-MUP consumption level after 15 months.

Clinical management of cannabis withdrawal.

BACKGROUND AND AIMS: Cannabis withdrawal is a well-characterized phenomenon that occurs in approximately half of regular and dependent cannabis users after abrupt cessation or significant reductions in cannabis products that contain Δ9 -tetrahydrocannabinol (THC). This review describes the diagnosis, prevalence, course and management of cannabis withdrawal and highlights opportunities for future clinical research. METHODS: Narrative review of literature. RESULTS: Symptom onset typically occurs 24-48 hours after cessation and most symptoms generally peak at days 2-6, with some symptoms lasting up to 3 weeks or more in heavy cannabis users. The most common features of cannabis withdrawal are anxiety, irritability, anger or aggression, disturbed sleep/dreaming, depressed mood and loss of appetite. Less common physical symptoms include chills, headaches, physical tension, sweating and stomach pain. Despite limited empirical evidence, supportive counselling and psychoeducation are the first-line approaches in the management of cannabis withdrawal. There are no medications currently approved specifically for medically assisted withdrawal (MAW). Medications have been used to manage short-term symptoms (e.g. anxiety, sleep, nausea). A number of promising pharmacological agents have been examined in controlled trials, but these have been underpowered and positive findings not reliably replicated. Some (e.g. cannabis agonists) are used 'off-label' in clinical practice. Inpatient admission for MAW may be clinically indicated for patients who have significant comorbid mental health disorders and polysubstance use to avoid severe complications. CONCLUSIONS: The clinical significance of cannabis withdrawal is that its symptoms may precipitate relapse to cannabis use. Complicated withdrawal may occur in people with concurrent mental health and polysubstance use.