Carla J Berg1, Devan R Romero, Kim Pulvers. 1. 1Department of Behavioral Sciences and Health Education, Emory University School of Public Health, Atlanta, Georgia, USA.
Abstract
INTRODUCTION: Given increases in nondaily smoking and alternative tobacco use among young adults, we examined the nature of change of various tobacco product use among college students over a year and predictors of use at one-year follow-up. METHODS: An online survey was administered to students at six Southeast colleges and universities (N = 4,840; response rate = 20.1%) in Fall 2010, with attempts to follow up in Fall 2011 with a random subsample of 2,000 participants (N = 718; response rate = 35.9%). Data were analyzed from 698 participants with complete data regarding tobacco, marijuana, and alcohol use over a one-year period, perceived harm of tobacco use, and schemas of a "smoker" (as per the Classifying a Smoker Scale). RESULTS: Baseline predictors of current smoking at follow-up included being White (p = .001), frequency of smoking (p < .001), alternative tobacco use (p < .001), and perceived harm of smoking (p = .02); marginally significant predictors included marijuana use (p = .06) and lower scores on the Classifying a Smoker Scale (p = .07). Baseline predictors of current smoking at follow-up among baseline nondaily smokers included more frequent smoking (p = .008); lower Classifying a Smoker Scale score was a marginally significant predictor (p = .06). Baseline predictors of alternative tobacco use at follow-up included being male (p = .007), frequency of smoking (p = .04), alternative tobacco use (p < .001), and frequency of alcohol use (p = .003); marginally significant predictors included marijuana use (p = .07) and lower perceived harm of smokeless tobacco (p = .06) and cigar products (p = .08). CONCLUSIONS: Tobacco control campaigns and interventions might target schemas of a smoker and perceived risks of using various tobacco products, even at low levels.
INTRODUCTION: Given increases in nondaily smoking and alternative tobacco use among young adults, we examined the nature of change of various tobacco product use among college students over a year and predictors of use at one-year follow-up. METHODS: An online survey was administered to students at six Southeast colleges and universities (N = 4,840; response rate = 20.1%) in Fall 2010, with attempts to follow up in Fall 2011 with a random subsample of 2,000 participants (N = 718; response rate = 35.9%). Data were analyzed from 698 participants with complete data regarding tobacco, marijuana, and alcohol use over a one-year period, perceived harm of tobacco use, and schemas of a "smoker" (as per the Classifying a Smoker Scale). RESULTS: Baseline predictors of current smoking at follow-up included being White (p = .001), frequency of smoking (p < .001), alternative tobacco use (p < .001), and perceived harm of smoking (p = .02); marginally significant predictors included marijuana use (p = .06) and lower scores on the Classifying a Smoker Scale (p = .07). Baseline predictors of current smoking at follow-up among baseline nondaily smokers included more frequent smoking (p = .008); lower Classifying a Smoker Scale score was a marginally significant predictor (p = .06). Baseline predictors of alternative tobacco use at follow-up included being male (p = .007), frequency of smoking (p = .04), alternative tobacco use (p < .001), and frequency of alcohol use (p = .003); marginally significant predictors included marijuana use (p = .07) and lower perceived harm of smokeless tobacco (p = .06) and cigar products (p = .08). CONCLUSIONS:Tobacco control campaigns and interventions might target schemas of a smoker and perceived risks of using various tobacco products, even at low levels.
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