Introduction: Alcohol and marijuana are among the most commonly used substances together with tobacco worldwide, but their relationship to smoking cessation is unclear. Although alcohol use decreases the likelihood of abstinence from tobacco, mechanisms of this effect have not been identified. Moreover, a small literature has yielded inconsistent findings regarding the effect of marijuana use on tobacco dependence treatment outcome. The aims of this study were to test increased positive-reinforcement smoking urge as a mediator of the relationship between alcohol and cigarette use and evaluate the impact of marijuana use on abstinence from tobacco.
Methods: Participants were adult cigarette smokers (N = 739) from 3 randomized clinical trials of smoking cessation treatment. Alcohol consumption and marijuana use were assessed at pretreatment and postcessation. Biochemically verified, 7-day point prevalence smoking abstinence was determined at Weeks 12, 24, 36, and 52, as were urges to smoke as measured by the Questionnaire of Smoking Urges.
Results: Increased positive-reinforcement urge mediated the effect of postcessation alcohol use on smoking abstinence. Although pretreatment alcohol use was associated with a decreased likelihood of abstinence from tobacco, increased positive-reinforcement urge did not account for this relationship. Marijuana use was not associated with abstinence from tobacco.
Conclusions: Smoking cessation treatments should provide those who drink during a quit attempt techniques designed to mitigate positive-reinforcement urge to smoke. Additional research is needed to determine how pretreatment alcohol consumption exerts its effect on cigarette use. Modifying the use of marijuana might not be critical to the success of tobacco interventions.
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http://dx.doi.org/10.1093/ntr/ntr312 | DOI Listing |
Drug Alcohol Depend Rep
December 2024
Department of Family and Preventive Medicine, College of Medicine, The University of Oklahoma Health Sciences, Oklahoma City, OK, USA.
Background: Smoking prevalence among U.S. adults experiencing homelessness is ≥70 %.
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January 2025
Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy.
BackgroundTobacco use is linked to increased cancer risk, and people who smoke represent a large proportion of newly diagnosed patients with cancer. The fact that smoking cessation at the time of diagnosis can improve the patient's life expectancy is still not broadly understood. We conducted a systematic review and meta-analysis to quantify the survival benefits obtainable by quitting smoking on diagnosis.
View Article and Find Full Text PDFEur J Public Health
January 2025
Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
We quantified the fraction of cardiovascular deaths attributable to smoking in Germany over time, accounting for population ageing. We calculated population-attributable fractions to quantify cardiovascular deaths attributable to smoking for 1992 to 2021, and compared actual with age-standardized figures. We found a significant decline in the number of cardiovascular deaths attributable to smoking: from about 71 900 cases in 1992 to around 42 000 cases in 2021, with a steeper decline in men.
View Article and Find Full Text PDFIntern Emerg Med
January 2025
Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA.
Recent data on methods used by adults to stop smoking can inform tobacco control policies. Nationally representative Centers for Disease Control and Prevention survey data from the 2022 National Health Interview Survey (N = 27,651) were used to analyze populations of US adults who self-reported having stopped smoking cigarettes for 6 months or longer in the last year and the methods they used, or who did not stop smoking but tried in the last year (N = 1735). In 2022, an estimated 2.
View Article and Find Full Text PDFPsychol Methods
January 2025
Department of Psychology, University of Pittsburgh.
Intensive longitudinal data analysis, commonly used in psychological studies, often concerns outcomes that have strong floor effects, that is, a large percentage at its lowest value. Ignoring a strong floor effect, using regular analysis with modeling assumptions suitable for a continuous-normal outcome, is likely to give misleading results. This article suggests that two-part modeling may provide a solution.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!