Addiction最新文献

{"title":"Household vaping bans and youth e-cigarette use","authors":"Jeremy Staff, Jessica M. Mongilio, Jennifer L. Maggs, Mike Vuolo, Brian C. Kelly","doi":"10.1111/add.16335","DOIUrl":"10.1111/add.16335","url":null,"abstract":"AIMS The aims of this study were to measure whether household bans on vaping were associated with lower odds of youth past-month vaping when compared with (1) otherwise similar youth whose households did not have a vaping ban (using coarsened exact matching); and (2) themselves in waves when their household did not have a ban (using hybrid panel models). We used the same analytical strategies to examine cross-sectional associations between household smoking bans and adolescents' past-month cigarette smoking. DESIGN This was a longitudinal study using data from a nationally representative sample of youth (age 12-17 years) in the Population Assessment of Tobacco and Health Study. SETTING United States of America. PARTICIPANTS A total of 16 214 adolescents followed over 48 103 total observations (approximately three waves). MEASUREMENTS Measurements comprised youth past-month e-cigarette and cigarette use and parent-reported household bans on vaping and smoking. Potential confounders were prior adolescent smoking, vaping, and other nicotine product use; parent current smoking, vaping, and other nicotine use; adolescent peer e-cigarette/cigarette use; parental monitoring; and demographic characteristics. FINDINGS Before matching, smoking bans were associated with 46% lower odds of youth smoking [odds ratio (OR) = 0.54; 95% confidence interval (CI) = 0.41-0.70] and vaping bans with 37% lower odds of youth e-cigarette use (OR = 0.63; 95% CI = 0.50-0.80). However, households with and without bans differed significantly on all confounders before matching. After matching, household vaping bans were associated with 56% lower odds of youth vaping (OR = 0.44; 95% CI = 0.33-0.58). Results from hybrid panel models also revealed 37% lower odds of vaping in waves when youth lived in a vape-free household compared to waves when they did not (OR = 0.63; 95% CI = 0.50-0.78). Associations between smoking bans and youth smoking were not statistically significant after matching or when using hybrid panel models. CONCLUSIONS Household vaping bans appear to be associated with lower odds of past-month vaping among US adolescents, compared with similar youth whose households did not have a ban and to themselves in waves when their households did not have a ban.","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 1","pages":"74-83"},"PeriodicalIF":6.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10610950","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":"Charting the fourth wave: Geographic, temporal, race/ethnicity and demographic trends in polysubstance fentanyl overdose deaths in the United States, 2010–2021","authors":"Joseph Friedman, Chelsea L. Shover","doi":"10.1111/add.16318","DOIUrl":"10.1111/add.16318","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>To characterize polysubstance death in the United States during the transition to the fourth wave of the drug overdose crisis. To characterize co-involved substances in fatal overdose involving synthetic opioids (mainly illicitly manufactured fentanyl analogues) by year, state, and intersectional sociodemographic groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Population-based study of national death records.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting</h3>\u0000 \u0000 <p>United States.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Participants/cases</h3>\u0000 \u0000 <p>All people who died from drug overdose in the United States between 2010 and 2021.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>Percentage of all fatal overdose involving fentanyls, stimulants, and other drugs. Most commonly co-involved substances in fentanyl overdose by state and year. Percentage of fatal fentanyl overdose co-involving stimulants by state and year. Percentage of fatal fentanyl overdose co-involving stimulants by intersectional region, race/ethnicity, age, and sex.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>The percent of US overdose deaths involving both fentanyl and stimulants increased from 0.6% (<i>n</i> = 235) in 2010 to 32.3% (34 429) in 2021, with the sharpest rise starting in 2015. In 2010, fentanyl was most commonly found alongside prescription opioids, benzodiazepines, and alcohol. In the Northeast this shifted to heroin-fentanyl co-involvement in the mid-2010s, and nearly universally to cocaine-fentanyl co-involvement by 2021. Universally in the West, and in the majority of states in the South and Midwest, methamphetamine-fentanyl co-involvement predominated by 2021. The proportion of stimulant involvement in fentanyl-involved overdose deaths rose in virtually every state 2015–2021. Intersectional group analysis reveals particularly high rates for older Black and African American individuals living in the West.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>By 2021 stimulants were the most common drug class found in fentanyl-involved overdoses in every state in the US. The rise of deaths involving cocaine and methamphetamine must be understood in the context of a drug market dominated by illicit fentanyls, which have made polysubstance use more soug","PeriodicalId":109,"journal":{"name":"Addiction","volume":"118 12","pages":"2477-2485"},"PeriodicalIF":6.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10598206","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":"US tobacco companies selectively disseminated hyper-palatable foods into the US food system: Empirical evidence and current implications","authors":"Tera L. Fazzino,&nbsp;Daiil Jun,&nbsp;Lynn Chollet-Hinton,&nbsp;Kayla Bjorlie","doi":"10.1111/add.16332","DOIUrl":"10.1111/add.16332","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>US tobacco companies owned leading US food companies from 1980 to 2001. We measured whether hyper-palatable foods (HPF) were disproportionately developed in tobacco-owned food companies, resulting in substantial tobacco-related influence on the US food system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>The study involved a review of primary industry documents to identify food brands that were tobacco company-owned. Data sets from the US Department of Agriculture were integrated to facilitate longitudinal analyses estimating the degree to which foods were formulated to be hyper-palatable, based on tobacco ownership.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting and cases</h3>\u0000 \u0000 <p>United States Department of Agriculture data sets were used to identify HPF foods that were (<i>n</i> = 105) and were not (<i>n</i> = 587) owned by US tobacco companies from 1988 to 2001.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>A standardized definition from Fazzino <i>et al</i>. (2019) was used to identify HPF. HPF items were identified overall and by HPF group: fat and sodium HPF, fat and sugar HPF and carbohydrates and sodium HPF.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Tobacco-owned foods were 29% more likely to be classified as fat and sodium HPF and 80% more likely to be classified as carbohydrate and sodium HPF than foods that were not tobacco-owned between 1988 and 2001 (<i>P</i>-values = 0.005–0.009). The availability of fat and sodium HPF (&gt; 57%) and carbohydrate and sodium HPF (&gt; 17%) was high in 2018 regardless of prior tobacco-ownership status, suggesting widespread saturation into the food system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Tobacco companies appear to have selectively disseminated hyper-palatable foods into the US food system between 1988 and 2001.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 1","pages":"62-71"},"PeriodicalIF":6.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10186169","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":"New perspectives on how to formulate alcohol drinking guidelines","authors":"Kevin Shield,&nbsp;Catherine Paradis,&nbsp;Peter Butt,&nbsp;Tim Naimi,&nbsp;Adam Sherk,&nbsp;Mark Asbridge,&nbsp;Daniel Myran,&nbsp;Tim Stockwell,&nbsp;Samantha Wells,&nbsp;Nancy Poole,&nbsp;Jennifer Heatley,&nbsp;Erin Hobin,&nbsp;Kara Thompson,&nbsp;Matthew Young,&nbsp;the Low-Risk Alcohol Drinking Guidelines Scientific Expert Panel","doi":"10.1111/add.16316","DOIUrl":"10.1111/add.16316","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Low-Risk Alcohol Drinking Guidelines (LRDGs) aim to reduce the harms caused by alcohol. However, considerable discrepancies exist in the ‘low-risk’ thresholds employed by different countries.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Argument/analysis</h3>\u0000 \u0000 <p>Drawing upon Canada's LRDGs update process, the current paper offers the following propositions for debate regarding the establishment of ‘low-risk’ thresholds in national guidelines: (1) as an indicator of health loss, years of life lost (YLL) has several advantages that could make it more suitable for setting guidelines than deaths, premature deaths or disability adjusted years of life (DALYs) lost. (2) Presenting age-specific guidelines may not be the most appropriate way of providing LRDGs. (3) Given past overemphasis on the so-called protective effects of alcohol on health, presenting cause-specific guidelines may not be appropriate compared with a ‘whole health’ effect derived from a weighted composite risk function comprising conditions that are causally related to alcohol consumption. (4) To help people reduce their alcohol use, presenting different risk zones associated with alcohol consumption instead of a single low risk threshold may be advantageous.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>National LRDGs should be based on years of life lost and should be neither age-specific nor cause-specific. We recommend using risk zones rather than a single drinking threshold to help people assess their own risk and encourage the adoption of behaviours with positive health impacts across the alcohol use spectrum.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 1","pages":"9-19"},"PeriodicalIF":6.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10183924","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":"Craving modulates attentional bias towards alcohol in severe alcohol use disorder: An eye-tracking study","authors":"Zoé Bollen,&nbsp;Arthur Pabst,&nbsp;Nicolas Masson,&nbsp;Reinout W. Wiers,&nbsp;Matt Field,&nbsp;Pierre Maurage","doi":"10.1111/add.16333","DOIUrl":"10.1111/add.16333","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background and aims&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Competing models disagree on three theoretical questions regarding alcohol-related attentional bias (AB), a key process in severe alcohol use disorder (SAUD): (1) is AB more of a trait (fixed, associated with alcohol use severity) or state (fluid, associated with momentary craving states) characteristic of SAUD; (2) does AB purely reflect the over-activation of the reflexive/reward system or is it also influenced by the activity of the reflective/control system and (3) does AB rely upon early or later processing stages? We addressed these issues by investigating the time-course of AB and its modulation by subjective craving and cognitive load in SAUD.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A free-viewing eye-tracking task, presenting pictures of alcoholic and non-alcoholic beverages, combined with a concurrent cognitive task with three difficulty levels.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Setting&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A laboratory setting in the detoxification units of three Belgian hospitals.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Participants&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We included 30 patients with SAUD self-reporting craving at testing time, 30 patients with SAUD reporting a total absence of craving and 30 controls matched on sex and age. All participants from SAUD groups met the DSM-5 criteria for SAUD.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Measurements&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We assessed AB through early and late eye-tracking indices. We evaluated the modulation of AB by craving (comparison between patients with/without craving) and cognitive load (variation of AB with the difficulty level of the concurrent task).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Findings&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Dwell time measure indicated that SAUD patients with craving allocated more attention towards alcohol-related stimuli than patients without craving (&lt;i&gt;P&lt;/i&gt; &lt; 0.001, &lt;i&gt;d&lt;/i&gt; = 1.093), resulting in opposite approach/avoidance AB according to craving presence/absence. SAUD patients without craving showed a stronger avoidance AB than controls (&lt;i&gt;P&lt;/i&gt; = 0.003, &lt;i&gt;d&lt;/i&gt; = 0.806). AB did not vary according to cognitive load (&lt;i&gt;P&lt;/i&gt; = 0.962, η&lt;sup&gt;2&lt;/sup&gt;&lt;sub&gt;p&lt;/sub&gt; = 0.004).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The direction of alcohol-related attentional bias (approach/avoidance) appears to be determined by patients' subjective craving at testing time and does not function as a stable trait of severe alcohol use disorder. Alcohol-","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 1","pages":"102-112"},"PeriodicalIF":6.0,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10201533","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":"Behavioural self-control training versus motivational enhancement therapy for individuals with alcohol use disorder with a goal of controlled drinking: A randomized controlled trial","authors":"Stina Ingesson Hammarberg,&nbsp;Sara Wallhed Finn,&nbsp;Ingvar Rosendahl,&nbsp;Sven Andréasson,&nbsp;Nitya Jayaram-Lindström,&nbsp;Anders Hammarberg","doi":"10.1111/add.16325","DOIUrl":"10.1111/add.16325","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Controlled drinking (CD) is an attractive treatment goal for a large proportion of individuals with alcohol use disorder (AUD), but the availability of treatment methods supporting a goal of CD is scarce. We tested if behavioural self-control training (BSCT) was superior to motivational enhancement therapy (MET) for individuals with AUD with a treatment goal of CD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Randomized controlled two-group trial. Follow-ups were conducted at 12 and 26 weeks (primary end-point) after inclusion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting</h3>\u0000 \u0000 <p>Three specialized dependency care clinics in Stockholm, Sweden.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Participants</h3>\u0000 \u0000 <p>Two hundred and fifty self-referred adults (52% men) fulfilling criteria of AUD (DSM-5) and a stated treatment goal of CD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Intervention and comparator</h3>\u0000 \u0000 <p>BSCT (<i>n</i> = 125), a five-session treatment based on cognitive behavioural therapy versus the active comparator, MET (<i>n</i> = 125), containing four sessions based on Motivational Interviewing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>Primary outcome measure was mean weekly alcohol consumption at the 26-week follow-up, adjusted for baseline consumption.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>A randomized controlled trial found no evidence of a difference between behavioural self-control training and motivational enhancement therapy in reducing weekly alcohol consumption. Both groups substantially reduced consumption and behavioural self-control training was superior in reducing hazardous drinking.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 1","pages":"86-101"},"PeriodicalIF":6.0,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16325","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10499253","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":"The estimated health impact of alcohol interventions in New Zealand: A modelling study","authors":"Tim Chambers,&nbsp;Anja Mizdrak,&nbsp;Sarah Herbert,&nbsp;Anna Davies,&nbsp;Amanda Jones","doi":"10.1111/add.16331","DOIUrl":"10.1111/add.16331","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Aims&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To estimate the health impacts of key modelled alcohol interventions among Māori (indigenous peoples) and non-Māori in New Zealand (NZ).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Multi-stage life-table intervention modelling study. We modelled two scenarios: (1) business-as-usual (BAU); and (2) an intervention package scenario that included a 50% alcohol tax increase, outlet density reduction from 63 to five outlets per 100 000 people, outlet hours reduction from 112 to 50 per week and a complete ban on all forms of alcohol marketing.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Setting and participants&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The model’s population replicates the 2018 NZ population by ethnicity (Māori/non-Māori), age and sex.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Measurements&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Alcohol consumption was estimated using nationally representative survey data combined with sales data and corrected for tourist and unrecorded consumption. Disease incidence, prevalence and mortality were calculated using Ministry of Health data. We used dose–response relationships between alcohol and illness from the 2016 Global Burden of Disease study and calculated disability rates for each illness. Changes in consumption were based on the following effect sizes: total intervention package [−30.3%, standard deviation (SD) = 0.02); tax (−7.60%, SD = 0.01); outlet density (−8.64%, SD = 0.01); outlet hours (−9.24%, SD = 0.01); and marketing (−8.98%, SD = 0.02). We measured health gain using health-adjusted life years (HALYs) and life expectancy.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Findings&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Compared with the BAU scenario, the total alcohol intervention package resulted in 726 000 [95% uncertainty interval (UI) = 492 000–913 000] HALYs gained during the life-time of the modelled population. Māori experienced greater HALY gains compared with non-Māori (0.21, 95% UI = 0.14–0.26 and 0.16, 95% UI = 0.11–0.20, respectively). When modelled individually, each alcohol intervention within the intervention package produced similar health gains (~200 000 HALYs per intervention) owing to the similar effect sizes.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Modelled interventions for increased alcohol tax, reduced availability of alcohol and a ban on alcohol marketing among Māori and non-Māori in New Zealand (NZ) suggest substantial population-wide health gains and reduced he","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 1","pages":"125-136"},"PeriodicalIF":6.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10274542","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":"Changes to opioid overdose deaths and community naloxone access among Black, Hispanic and White people from 2016 to 2021 with the onset of the COVID-19 pandemic: An interrupted time-series analysis in Massachusetts, USA","authors":"Xiao Zang,&nbsp;Alexander Y. Walley,&nbsp;Avik Chatterjee,&nbsp;Simeon D. Kimmel,&nbsp;Jake R. Morgan,&nbsp;Sean M. Murphy,&nbsp;Benjamin P. Linas,&nbsp;Shayla Nolen,&nbsp;Brittni Reilly,&nbsp;Catherine Urquhart,&nbsp;Bruce R. Schackman,&nbsp;Brandon D. L. Marshall","doi":"10.1111/add.16324","DOIUrl":"10.1111/add.16324","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Aims</h3>\u0000 \u0000 <p>The onset of the coronavirus disease 2019 (COVID-19) pandemic was associated with a surge in opioid overdose deaths in Massachusetts, particularly affecting racial and ethnic minority communities. We aimed to compare the impact of the pandemic on opioid overdose fatalities and naloxone distribution from community-based programs across racial and ethnic groups in Massachusetts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Interrupted time-series.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting and Cases</h3>\u0000 \u0000 <p>Opioid overdose deaths (OODs) among non-Hispanic White, non-Hispanic Black, Hispanic and non-Hispanic other race people in Massachusetts, USA (January 2016 to June 2021).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Measurements</h3>\u0000 \u0000 <p>Rate of OODs per 100 000 people, rate of naloxone kits distributed per 100 000 people and ratio of naloxone kits per opioid overdose death as a measure of naloxone availability. We applied five imputation strategies using complete data in different periods to account for missingness of race and ethnicity for naloxone data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Before COVID-19 (January 2016 to February 2020), the rate of OODs declined among non-Hispanic White people [0.2% monthly reduction (95% confidence interval = 0.0–0.4%)], yet was relatively constant among all other population groups. The rate of naloxone kits increased across all groups (0.8–1.2% monthly increase) and the ratio of naloxone kits per OOD death among non-Hispanic White was 1.1% (0.8–1.4%) and among Hispanic people was 1.0% (0.2–1.8%). After the onset of the pandemic (March 2020+), non-Hispanic Black people experienced an immediate increase in the rate of OODs [63.6% (16.4–130%)], whereas rates among other groups remained similar. Trends in naloxone rescue kit distribution did not substantively change among any groups, and the ratio of naloxone kits per OOD death for non-Hispanic Black people did not compensate for the surge in OODs deaths in this group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>With the onset of the COVID-19 pandemic, there was a surge in opioid overdose deaths among non-Hispanic Black people in Massachusetts, USA with no compensatory increase in naloxone rescue kit distribution. For non-Hispanic White and Hispanic people, opioid overdose deaths remained stable and naloxone kit distribution continued to increase.</p>\u0000 </section>\u0000 </div>","PeriodicalId":109,"journal":{"name":"Addiction","volume":"118 12","pages":"2413-2423"},"PeriodicalIF":6.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10119999","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":"Austin Bradford Hill’s ‘Environment and disease: Association or causation’","authors":"Wayne Hall","doi":"10.1111/add.16329","DOIUrl":"10.1111/add.16329","url":null,"abstract":"&lt;p&gt;Austin Bradford Hill’s 1965 paper [&lt;span&gt;1&lt;/span&gt;] on disease and the environment is one of the most widely cited papers in public health and related fields [&lt;span&gt;2&lt;/span&gt;]. Hill’s nine ‘criteria’ for causal inferences were used in 87% of recent reviews of evidence on causality in population health [&lt;span&gt;3&lt;/span&gt;]. In the addictions field, Hill’s paper has been used to evaluate causal explanations of: associations between psychosis and the use of cannabis and nicotine [&lt;span&gt;4&lt;/span&gt;]; the effects of naloxone distribution on opioid overdose deaths [&lt;span&gt;5&lt;/span&gt;]; the effects of a minimum unit price for alcohol policy on alcohol-related harm [&lt;span&gt;6&lt;/span&gt;]; and the role played by vitamin E acetate in the 2019 outbreak of lung injury from vaping cannabis oil in the United States [&lt;span&gt;7&lt;/span&gt;]. Hill’s ‘criteria’ have also been used in courts in the United States to assess causal claims about injuries caused by chemical exposures [&lt;span&gt;8, 9&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Why has a paper that was based on a lecture given to occupational physicians over 50 years ago come to be regarded as an authoritative method for making causal inferences from observational data? Its continued role as a foundational citation classic is surprising because in the more than half-century since its publication there have been major advances in thinking about causal inference [&lt;span&gt;10-12&lt;/span&gt;] and in the development of advanced statistical methods and research designs to improve the quality of causal inferences from observational studies [&lt;span&gt;10, 11, 13-15&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Hill assumed that we have observations that: ‘… reveal an association between two variables, perfectly clear-cut and beyond what we would attribute to the play of chance’ and asked: ‘What aspects of that association should we especially consider before deciding that the most likely interpretation of it is causation?’ ([&lt;span&gt;1&lt;/span&gt;], p. 295).&lt;/p&gt;&lt;p&gt;Hill outlined nine factors that he thought needed to be considered in making this decision.&lt;/p&gt;&lt;p&gt;Hill stressed (p. 299) that it was not possible to ‘lay down some hard-and-fast rules of evidence that must be obeyed before we accept cause and effect. None of my nine viewpoints can bring indisputable evidence for or against the cause-effect hypothesis and none can be required as a sine qua non. What they can do, with greater or less strength, is to help us make up our minds on the fundamental question—is there any other way of explaining the set of facts before us, is there any other answer equally, or more likely than cause and effect?’&lt;/p&gt;&lt;p&gt;Hill was also clear that tests of statistical significance could not directly answer causal questions. At most they ‘can, and should, remind us of the effects that the play of chance can create, and they will instruct us in the likely magnitude of those effects’ (p. 299).&lt;/p&gt;&lt;p&gt;Finally, Hill asked: ‘what action may flow from a conclusion that an association is causal? In ‘occupational medicine our object is usually to t","PeriodicalId":109,"journal":{"name":"Addiction","volume":"119 2","pages":"386-390"},"PeriodicalIF":6.0,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/add.16329","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10085839","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":"The interaction of e-cigarette use and mental health symptoms on risk of cigarette smoking initiation among young adults in the United States","authors":"Alyssa F. Harlow,&nbsp;Dae-Hee Han,&nbsp;Sandrah P. Eckel,&nbsp;Rob McConnell,&nbsp;Adam M. Leventhal,&nbsp;Jessica L. Barrington-Trimis","doi":"10.1111/add.16319","DOIUrl":"10.1111/add.16319","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background and Aims&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;It is unknown whether young adults who vape nicotine and have poor mental health have greater risk of smoking initiation than expected based on individual risks of vaping and mental health alone. This study aimed to estimate the joint association of vaping and mental health symptoms with smoking initiation among young adults, and test for additive interaction between vaping and mental health in smoking initiation risk.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using five waves of the Population Assessment of Tobacco and Health (wave 1, 2013–2014; wave 2, 2014–2015; wave 3, 2015–2016; wave 4, 2016–2018; wave 5, 2018–2019), we estimated risk differences (RD) for the association of time-varying and time-lagged vaping and internalizing (e.g., anxiety, depressive) and externalizing (e.g., inattention/hyperactivity) mental health symptoms with cigarette smoking initiation at follow-up, over four 1-year intervals. We calculated interaction contrasts (IC) to estimate the excess risk of smoking initiation attributable to the interaction of vaping and mental health symptoms.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Setting&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;United States.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Participants&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A total of 6908 cigarette-naïve individuals aged 18–24 years.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Measurements&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Exposures included current (past-30 day) vaping and internalizing and externalizing mental health symptoms (high vs moderate/low symptoms). The outcome was smoking initiation (ever cigarette use) after 1 year.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Findings&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The per-interval risk of smoking initiation was 7.6% (1039 cases/13 712 person-intervals). Compared with noncurrent vaping and moderate/low mental health symptoms, adjusted RDs for current vaping and high mental health symptoms were 17.2% (95% confidence interval [CI]: 7.2% to 27.3%) for internalizing and 18.7% (95%CI: 8.1% to 29.2%) for externalizing symptoms. The excess risk attributed to interaction of current vaping and high externalizing symptoms was IC = 11.3% (95%CI: 1.3% to 21.2%; &lt;i&gt;P&lt;/i&gt; = 0.018), with inconclusive findings for internalizing symptoms (IC = 7.7% [95%CI: −2.2% to 17.7%; &lt;i&gt;P&lt;/i&gt; = 0.097]).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;","PeriodicalId":109,"journal":{"name":"Addiction","volume":"118 12","pages":"2317-2326"},"PeriodicalIF":6.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10459152","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}