Are college student smokers really a homogeneous group? A latent class analysis of college student smokers

Abstract

Introduction: College smokers are often considered to be one homogenous group, those reporting smoking on at least one of the past 30 days. However, considerable heterogeneity exists among college students who report current smoking. The aim of this paper is to characterize disparate patterns of smoking among college students using latent class analysis (LCA). Methods:The sample consisted of 1,102 past-month smokers from 10 colleges in North Carolina who completed a Web-based survey. LCA was used to create homogeneous groups of smokers with similar patterns defi ned by multiple indicators of smoking behavior, including quantity and frequency of smoking, smoking contexts, and weekly patterns of smoking.Results: Five subclasses of smokers were identifi ed: " heavy smokers " (28%), moderate smokers (22%), social smokers (19%), puffers (26%), and no-context smokers (4%). Demographic characteristics that varied among these subgroups were year in school, Greek membership, and residence location. Puffers were more likely to be younger students than heavy and social smokers, suggesting a transition from experimentation to regular use over time. Social smokers and puffers were more likely to be involved in Greek organizations than were heavy and moderate smokers. Moderate and social smokers were more likely to be current drinkers and to have engaged in binge drinking in the past month than were heavy smokers. This fi nding suggests that, for moderate and social smokers, a strong relationship exists between alcohol and tobacco use. Discussion:The results highlight the heterogeneity of college student smokers and underscore the need for targeted interventions.

Examining the stability of young-adult alcohol and tobacco co-use: A latent transition analysis

“…Predetermined categories, as with studies that have used LTA to model transitions in stage of change for smoking cessation (Martin et al, 1996) or progression to alcohol dependence (Guo et al, 2000) are theory-driven predictions of diagnostic categories or readiness for treatment. However, discrete categories of young-adult substance use require further research and replication (Sutfin et al, 2009). …”

“…Smoking on an intermittent or occasional basis, i.e., a smoking pattern that is inconsistent over time, is more common than daily smoking among college students (S. Ames et al, 2009;Moran, Wechsler, & Rigotti, 2004;Sutfin, Reboussin, McCoy, & Wolfson, 2009). This pattern of smoking may reflect an early stage of smoking progression, with subsequent transition to heavier daily smoking and nicotine dependence, or a time-limited period of experimentation (Kenford et al, 2005).…”

Cancer Genetic Risk Assessment and Referral Patterns in Primary Care

“…The goal of latent class analysis is exploratory and descriptive, and hence hypothesis tests and associated p-values are not used to make inferences about the latent groups. Researchers have recently advocated using latent class analyses of multiple characteristics to identify subgroups that would benefit from targeted interventions (Coffman et al, 2007;Sutfin et al, 2009;Thompson et al, 2009). Indeed, latent class analysis is similar to cluster analysis that has been used to design and implement such interventions (Collins et al, 2008;Torres Campos et al, 2009).…”

Latent Classes of Young Adults Based on Use of Multiple Types of Tobacco and Nicotine Products

“…While a number of studies have been conducted that seek to classify tobacco users based primarily on their amount and frequency of tobacco use (e.g., Furberg et al, 2005;Storr, Zhou, Liang, & Anthony, 2004;Sutfin, Reboussin, McCoy, & Wolfson, 2009), only a few studies have attempted to create groups of tobacco users based on the types of tobacco products they use. Timberlake (2008) examined nicotine dependence, smoking levels, and alternative types of tobacco (smokeless tobacco, cigars, bidis [thin, hand-rolled cigarettes primarily imported from India and Southeast Asia]) in a sample of regular cigarette smokers using the Ad Health dataset.…”