ReJoyce Green1, James MacKillop2, Emily E Hartwell3,4, Aaron C Lim1, Wave-Ananda Baskerville1, Mitchell Karno5, Lara A Ray1,5. 1. Department of Psychology, University of California, Los Angeles, Los Angeles, CA. 2. Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, ON, Canada. 3. Mental Illness Research, Education and Clinical Center, Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA. 4. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. 5. Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA.
Abstract
INTRODUCTION: Previous studies have highlighted a strong bidirectional relationship between cigarette and alcohol consumption. To advance our understanding of this relationship the present study uses a behavioral economic approach in a community sample (N = 383) of nontreatment seeking heavy drinking smokers. AIMS AND METHODS: The aims were to examine same-substance and cross-substance relationships between alcohol and cigarette use, and latent factors of demand. A community sample of nontreatment seeking heavy drinking smokers completed an in-person assessment battery including measures of alcohol and tobacco use as well as the Cigarette Purchase Task and the Alcohol Purchase Task. Latent factors of demand were derived from these hypothetical purchase tasks. RESULTS: Results revealed a positive correlation between paired alcohol and cigarette demand indices (eg, correlation between alcohol intensity and cigarette intensity) (rs = 0.18-0.46, p ≤ .003). Over and above alcohol factors, cigarette use variables (eg, Fagerström Test for Nicotine Dependence and cigarettes per smoking day) significantly predicted an additional 4.5% (p < .01) of the variance in Persistence values but not Amplitude values for alcohol. Over and above cigarette factors, alcohol use variables predicted cigarette Persistence values (ΔR2 = .013, p = .05), however, did not predict Amplitude values. CONCLUSIONS: These results advance our understanding of the overlap between cigarette and alcohol by demonstrating that involvement with one substance was associated with demand for the other substance. This asymmetric profile-from smoking to alcohol demand, but not vice versa-suggests that it is not simply tapping into a generally higher reward sensitivity and warrants further investigation. IMPLICATIONS: To our knowledge, no study to date has examined alcohol and cigarette demand, via hypothetical purchase tasks, in a clinical sample of heavy drinking smokers. This study demonstrates that behavioral economic indices may be sensitive to cross-substance relationships and specifically that such relationships are asymmetrically stronger for smoking variables affecting alcohol demand, not the other way around.
INTRODUCTION: Previous studies have highlighted a strong bidirectional relationship between cigarette and alcohol consumption. To advance our understanding of this relationship the present study uses a behavioral economic approach in a community sample (N = 383) of nontreatment seeking heavy drinking smokers. AIMS AND METHODS: The aims were to examine same-substance and cross-substance relationships between alcohol and cigarette use, and latent factors of demand. A community sample of nontreatment seeking heavy drinking smokers completed an in-person assessment battery including measures of alcohol and tobacco use as well as the Cigarette Purchase Task and the Alcohol Purchase Task. Latent factors of demand were derived from these hypothetical purchase tasks. RESULTS: Results revealed a positive correlation between paired alcohol and cigarette demand indices (eg, correlation between alcohol intensity and cigarette intensity) (rs = 0.18-0.46, p ≤ .003). Over and above alcohol factors, cigarette use variables (eg, Fagerström Test for Nicotine Dependence and cigarettes per smoking day) significantly predicted an additional 4.5% (p < .01) of the variance in Persistence values but not Amplitude values for alcohol. Over and above cigarette factors, alcohol use variables predicted cigarette Persistence values (ΔR2 = .013, p = .05), however, did not predict Amplitude values. CONCLUSIONS: These results advance our understanding of the overlap between cigarette and alcohol by demonstrating that involvement with one substance was associated with demand for the other substance. This asymmetric profile-from smoking to alcohol demand, but not vice versa-suggests that it is not simply tapping into a generally higher reward sensitivity and warrants further investigation. IMPLICATIONS: To our knowledge, no study to date has examined alcohol and cigarette demand, via hypothetical purchase tasks, in a clinical sample of heavy drinking smokers. This study demonstrates that behavioral economic indices may be sensitive to cross-substance relationships and specifically that such relationships are asymmetrically stronger for smoking variables affecting alcohol demand, not the other way around.
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