Addiction最新文献

{"title":"Does gambling expenditure have any effect on crime?","authors":"Wai Yin Wan Ph.D.,&nbsp;Joanna Wang Ph.D.,&nbsp;Donald J Weatherburn Ph.D.","doi":"10.1111/add.16648","DOIUrl":"10.1111/add.16648","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Australians spend more per capita on gambling than any other country in the world. Electronic gaming machines (EGM) expenditure accounts for almost 90% of this expenditure. No study to date has conducted a rigorous longitudinal analysis of the relationship between gambling expenditure and crime. This study aimed to estimate the short- and long-run relationship between gambling expenditure and crime.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Longitudinal analysis using panel autoregressive distributed lag (ARDL) modelling.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting and cases</h3>\u0000 \u0000 <p>Recorded property and violent crimes committed in New South Wales (NSW), Australia, between 28 December 2015 and 5 January 2020.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>Monthly gross EGM expenditure profit, broken down by Local Government Area (LGA). Monthly recorded rates of assault, break enter and steal (dwelling), break enter and steal (non-dwelling), break enter and steal (total), motor vehicle theft, stealing from a motor vehicle, stealing from a retail store, stealing from the person, stealing (total) and fraud.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Each 10% increase in gambling expenditure in NSW is associated with annual: 7.4% increase in assaults, 10.5% increase in break and enter (dwelling) offences; 10.3% increase in break and enter (non-dwelling) offences; 11% increase in motor vehicle theft offences; 8.2% increase in stealing from motor vehicle offences; and 7.4% increase in fraud offences.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Electronic gaming expenditure appears to be positively associated with property and violent crime in New South Wales, Australia.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 12","pages":"2197-2204"},"PeriodicalIF":5.2,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16648","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142015655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping consumptions and market size of cocaine, amphetamine and MDMA through wastewater analysis: A Dutch case study","authors":"Thomas L. ter Laak,&nbsp;Erik Emke,&nbsp;Nicole Dolot,&nbsp;Emiel E. van Loon,&nbsp;Margo M. E. van der Kooi,&nbsp;Arian C. van Asten,&nbsp;Pim de Voogt","doi":"10.1111/add.16649","DOIUrl":"10.1111/add.16649","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Aims</h3>\u0000 \u0000 <p>Illicit drug consumption is associated with public health effects and criminal activities. This study aimed to estimate Illicit drug consumption and annual market in the Netherlands from wastewater analysis of drug residues.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Residues of cocaine, amphetamine and 3,4-methylene dioxymethamphetamine (MDMA) were measured between 2015 and 2022 in 30 Dutch wastewater treatment plants serving both rural and urban populations. These wastewater treatment plants covered 20% of the total Dutch population. The Dutch annual retail market was estimated by extrapolating consumption to the total Dutch population, back-calculating consumption volume, correcting for drug purity and street price collected in voluntary checking services, and accounting for the correlation of consumption and urbanity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The per capita MDMA and cocaine consumption correlated positively with the urbanity of the wastewater treatment plant catchments with r² of 31% and 64%, respectively. Amphetamine did not show a significant correlation with urbanity. The three studied drugs were conservatively estimated to cover an average annual market value of 903 (95% prediction interval 829 to 987) million Euro for the studied period. Market estimations from prevalence figures and interceptions of international trade were similar.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Illicit drug consumption in the Netherlands appears to correlate positively with urban (in contrast to rural) areas. Wastewater analysis can be used to estimate the volume and monetary value of illicit drug markets as a proof of concept.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"120 1","pages":"116-125"},"PeriodicalIF":5.2,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142015656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining how the first year of the COVID-19 pandemic affected alcohol use in different socio-demographic groups in an Australian representative longitudinal sample","authors":"Yvette Mojica-Perez,&nbsp;Michael Livingston,&nbsp;Amy Pennay,&nbsp;Sarah Callinan","doi":"10.1111/add.16651","DOIUrl":"10.1111/add.16651","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Research examining how alcohol consumption changed across different socio-demographic groups during the pandemic has largely relied upon convenience samples recruited after the onset of the COVID-19 pandemic. The aim of this study was to measure whether the pandemic shifted alcohol consumption in different gender, age and income groups in Australia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design, setting and participants</h3>\u0000 \u0000 <p>This was a longitudinal study using four waves (2017–20) of the annual Household, Income and Labour Dynamics in Australia (HILDA) Survey to compare pre-pandemic consumption (2017–19) with consumption in 2020. A total of 11 636 participants in Australia aged 15 years and older took part.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>Participants were asked annually about their alcohol consumption, demographics and income.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>There was a statistically significant increase in alcohol consumption during the first year of the pandemic [incident rate ratio (IRR) = 1.1, 95% confidence interval (CI) = 1.1, 1.1], largely driven by changes in drinking frequency. We found a significant difference in consumption change from pre-COVID-19 to during COVID-19 for participants aged under 55 years compared with those aged over 55 years. In addition, participants aged 15–34 reported less alcohol consumption during the pandemic than those aged 35 years and older. No significant differences were identified across gender and income groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Alcohol consumption in Australia increased during the first year of the COVID-19 pandemic. Survey participants aged 55 years and over seemed to be the least impacted by the public health measures introduced during the pandemic, such as the closure of licensed premises.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 12","pages":"2176-2184"},"PeriodicalIF":5.2,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142007884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mega-analysis of the brain-age gap in substance use disorder: An ENIGMA Addiction working group study","authors":"Freda Scheffler,&nbsp;Jonathan Ipser,&nbsp;Devarshi Pancholi,&nbsp;Alistair Murphy,&nbsp;Zhipeng Cao,&nbsp;Jonatan Ottino-González,&nbsp;ENIGMA Addiction Working Group,&nbsp;Paul M. Thompson,&nbsp;Steve Shoptaw,&nbsp;Patricia Conrod,&nbsp;Scott Mackey,&nbsp;Hugh Garavan,&nbsp;Dan J. Stein","doi":"10.1111/add.16621","DOIUrl":"10.1111/add.16621","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Aims</h3>\u0000 \u0000 <p>The brain age gap (BAG), calculated as the difference between a machine learning model-based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>This was a cross-sectional study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting</h3>\u0000 \u0000 <p>This is an Enhancing Neuro Imaging through Meta-Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Participants</h3>\u0000 \u0000 <p>This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Alcohol use disorder (β = −5.49, <i>t</i> = −5.51, <i>p</i> &lt; 0.001) was associated with higher global BAG, whereas amphetamine-type stimulant use disorder (β = 3.44, <i>t</i> = 2.42, <i>p</i> = 0.02) was associated with lower global BAG in the separate substance-specific models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>People with alcohol use disorder appear to have a higher brain-age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 11","pages":"1937-1946"},"PeriodicalIF":5.2,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16621","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142007885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prescribing of extended release buprenorphine injection for Medicaid beneficiaries, 2018–2022","authors":"Rachael K. Ross,&nbsp;Kara E. Rudolph,&nbsp;Chelsea L. Shover","doi":"10.1111/add.16652","DOIUrl":"10.1111/add.16652","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Extended release buprenorphine injection (INJ-BUP) has been available in the United States since 2018. INJ-BUP has the potential to positively impact opioid use disorder (OUD) treatment outcomes by providing additional treatment options. As one of the largest payers of OUD treatment in the US, Medicaid coverage is important for access and uptake of INJ-BUP. Uptake of INJ-BUP among Medicaid beneficiaries has not been described since 2019 and variation in uptake by state has not previously been explored. We aimed to measure prescribing of INJ-BUP for Medicaid beneficiaries since 2018, nationwide and by state.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed State Drug Utilization Data from 2017 to 2022 and calculated the number of prescription fills for INJ-BUP and oral buprenorphine paid by Medicaid. To compare across states, we calculated the number of prescription fills per 100 Medicaid beneficiaries treated for OUD using data from Transformed Medicaid Statistical Information System Substance Use Disorder (T-MSIS SUD) Data Books. Data sources are publicly available.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The number of prescription fills for INJ-BUP paid by Medicaid increased from 4322 (0.1% of all buprenorphine prescription fills) in 2018 to 186 861 (2.0%) in 2022. Each year the increase in fills exceeded the prior year change, indicating accelerating uptake. There was notable variability across states.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The number of extended release buprenorphine injection prescriptions among US Medicaid beneficiaries treated for opioid use disorder increased from over 4000 prescriptions in 2018 to over 185 000 in 2022 but uptake is much less than observed in other countries over shorter time periods.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 12","pages":"2211-2215"},"PeriodicalIF":5.2,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT-4: Alcohol use disorder responses","authors":"Alex M. Russell,&nbsp;Samuel F. Acuff,&nbsp;John F. Kelly,&nbsp;Jon-Patrick Allem,&nbsp;Brandon G. Bergman","doi":"10.1111/add.16650","DOIUrl":"10.1111/add.16650","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Alcohol use disorder (AUD) is characterized by low levels of engagement with effective treatments. Enhancing awareness of AUD treatments and how to navigate the treatment system is crucial. Many individuals use online sources (e.g. search engines) for answers to health-related questions; web-based results include a mix of high- and low-quality information. Artificial intelligence may improve access to quality health information by providing concise, high-quality responses to complex health-related questions. This study evaluated the quality of ChatGPT-4 responses to AUD-related queries.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>A comprehensive list of 64 AUD-related questions was developed through a combination of Google Trends analysis and expert consultation. ChatGPT-4 was prompted with each question, followed by a request to provide 3–5 peer-reviewed scientific citations supporting each response. Responses were evaluated for whether they were evidence-based, provided a referral and provided supporting documentation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>ChatGPT-4 responded to all AUD-related queries, with 92.2% (59/64) of responses being fully evidence-based. Although only 12.5% (8/64) of responses included referrals to external resources, all responses (100%; 5/5) to location-specific (‘near me’) queries directed individuals to appropriate resources like the NIAAA Treatment Navigator. Most (85.9%; 55/64) responses to the follow-up question provided supporting documentation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>ChatGPT-4 responds to alcohol use disorder-related questions with evidence-based information and supporting documentation. ChatGPT-4 could be promoted as a reasonable resource for those looking online for alcohol use disorder-related information.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 12","pages":"2205-2210"},"PeriodicalIF":5.2,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141981267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How psychedelics legalization debates could differ from cannabis.","authors":"Beau Kilmer","doi":"10.1111/add.16644","DOIUrl":"https://doi.org/10.1111/add.16644","url":null,"abstract":"","PeriodicalId":109,"journal":{"name":"Addiction","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Commentary on Conde et al.: Evidence and gap map offer an important opportunity for dialogue and refinement of the gateway hypothesis controversy","authors":"Arielle Selya,&nbsp;Joe G. Gitchell","doi":"10.1111/add.16645","DOIUrl":"10.1111/add.16645","url":null,"abstract":"<p>The question of whether e-cigarette use promotes subsequent cigarette smoking among youth (commonly known as the ‘gateway hypothesis’) is critical for understanding e-cigarettes' net impact on population health. Unfortunately, it is also a highly polarized topic. Not only is there no clear resolution (yet) embraced by both sides [<span>1, 2</span>], but the many studies published on the topic do not seem to have changed anyone's mind. This seems to be a real-life example of the epistemological network model described by O'Connor and Weatherall [<span>3</span>] (see the figures, particularly the polarization one) whereby levels of social trust and conformity are such that more research does not lead to a convergence on truth.</p><p>We hope that researchers willing to devote the effort and take the risks to work with ‘adversaries’ will draw motivation from peers in other fields taking the same risks and efforts.</p><p><b>Arielle Selya:</b> Conceptualization; project administration; writing—original draft; writing—review and editing. <b>Joe G. Gitchell:</b> Conceptualization; writing—review and editing.</p><p>Through Pinney Associates, A.S. and J.G.G. provide consulting services on tobacco harm reduction to Juul Labs (JLI). A.S. also individually provides consulting services on behavioural science to the Center of Excellence for the Acceleration of Harm Reduction (CoEHAR) through ECLAT Srl, which received funding from the Foundation for a Smoke-Free World (FSFW; now the Global Action to End Smoking [GA]). Neither JLI, CoEHAR, nor FSFW/GA had any role in, or oversight of, this commentary.</p>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 10","pages":"1709-1710"},"PeriodicalIF":5.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A clinical research perspective on the regulation of medical and non-medical use of psychedelic drugs.","authors":"Michael P Bogenschutz","doi":"10.1111/add.16647","DOIUrl":"https://doi.org/10.1111/add.16647","url":null,"abstract":"","PeriodicalId":109,"journal":{"name":"Addiction","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The relationship between cannabis and nicotine use: A systematic review and meta-analysis","authors":"Tesfa Mekonen Yimer,&nbsp;Caitlin McClure-Thomas,&nbsp;Daniel Stjepanovic,&nbsp;Jack Wilson,&nbsp;Gary Chung Kai Chan,&nbsp;Wayne Denis Hall,&nbsp;Janni Leung","doi":"10.1111/add.16642","DOIUrl":"10.1111/add.16642","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Cannabis and nicotine (tobacco or e-cigarettes) use commonly co-occurs and understanding their relationship can help to inform public health strategies to prevent their harms. We conducted a systematic review and meta-analysis to estimate the association of cannabis use given prior nicotine use and vice versa.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>PubMed, Embase, PsycINFO, Google Scholar and a hand-search were conducted in 2023 for longitudinal studies of the general population with no restrictions in settings (locations). Random-effects meta-analysis was conducted to estimate odds ratios between cannabis and nicotine use in both directions. The impact of unmeasured confounding was assessed using E-values.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>From 5387 identified records, we included 20 studies. Among cannabis-naïve youths, baseline use of any nicotine products was positively associated with initiation of any cannabis use at follow-up [odds ratio (OR) = 5.39, 95% confidence interval (CI) = 3.19, 9.11; adjusted OR (aOR) = 2.59, 95% CI = 2.01, 3.32]. In nicotine-naïve participants (youths + adults), baseline cannabis use was positively associated with the initiation of any nicotine use at follow-up (OR = 4.08, 95% CI = 2.05, 8.11; aOR = 2.94, 95% CI =1.54, 5.61). There were no significant associations between baseline cannabis use and subsequent initiation of any nicotine (aOR = 3.29, 95% CI = 0.85, 12.76) or daily nicotine use (aOR = 2.63, 95% CI = 0.41, 16.95) among youths. The median E-values were 5.5 for nicotine exposure and cannabis use initiation and 4.1 for cannabis exposure and nicotine use initiation, indicating that substantial unmeasured confounding would need to have a strong association with both outcomes to fully explain away the cannabis and nicotine relationship.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Although the evidence for associations between cannabis use and tobacco use is mixed, a majority of studies to date have found that cannabis use is associated with prior nicotine use and vice versa.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 12","pages":"2076-2087"},"PeriodicalIF":5.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16642","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}