Predictors of reduced smoking quantity among recovering alcohol dependent men in a smoking cessation trial. (September 2018)

• Record Type: Journal Article
• Authors: Worley, Matthew J.; Isgro, Melodie; Heffner, Jaimee L.; Lee, Soo Yong; Daniel, Belinda E.; Anthenelli, Robert M.
• Is Part Of: Addictive behaviors. Volume 84(2018)
• Page Start: 263
• Page End: 270
• Publication Date: 2018-09
• Subjects: Smoking cessation -- Nicotine -- Alcohol dependence -- Tobacco; Substance abuse -- Periodicals; Alcoholism -- Periodicals; Drug addiction -- Periodicals; Nicotine addiction -- Periodicals; Smoking -- Periodicals; Gambling -- Psychological aspects -- Periodicals; Electronic journals; 362.29
• DOI: 10.1016/j.addbeh.2018.05.004
• Languages: English
• ISSNs: 0306-4603

Abstract

Abstract: Introduction: Adults with alcohol dependence (AD) have exceptionally high smoking rates and poor smoking cessation outcomes. Discovery of factors that predict reduced smoking among AD smokers may help improve treatment. This study examined baseline predictors of smoking quantity among AD smokers in a pharmacotherapy trial for smoking cessation. Methods: The sample includes male, AD smokers ( N = 129) with 1–32 months of alcohol abstinence who participated in a 12-week trial of medication (topiramate vs. placebo) and adjunct counseling with 6 months of follow-up. Baseline measures of nicotine dependence, AD severity, psychopathology, motivation to quit smoking, and smoking-related cognitions were used to predict smoking quantity (cigarettes per day) at post-treatment and follow-up. Results: Overall, the sample had statistically significant reductions in smoking quantity. Greater nicotine dependence (Incidence rate ratios ( IRR s) = 0.82–0.90), motivation to quit ( IRR s = 0.65–0.85), and intrinsic reasons for quitting ( IRR s = 0.96–0.98) predicted fewer cigarettes/day. Conversely, greater lifetime AD severity ( IRR = 1.02), depression severity ( IRR s = 1.05–1.07), impulsivity ( IRR s = 1.01–1.03), weight-control expectancies ( IRR s = 1.10–1.15), and childhood sexual abuse ( IRR s = 1.03–1.07) predicted more cigarettes/day. Conclusions: Smokers with AD can achieve large reductions in smoking quantity during treatment, and factors that predict smoking outcomes in the general population also predict greater smoking reductions in AD smokers. Treatment providers can use severity of nicotine dependence and AD, motivation to quit, smoking-related cognitions, and severity of depression to guide treatment and improve outcomes among AD smokers. Highlights: Smokers with alcohol dependence have extremely low rates of smoking cessation. We examined baseline predictors of reductions in smoking among alcohol-dependent smokers in early sobriety from drinking. Less severe alcohol-related problems, depression severity, and impulsivity predicted greater reductions in smoking. Greater nicotine dependence, motivation to quit, and intrinsic reasons to quit predicted greater reductions in smoking. Predictors of reduced smoking could potentially be used to personalize treatment.