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E-cigarette use and quantity of cigarette smoking among adolescent cigarette smokers: A finite mixture model analysis.
Drug and Alcohol Dependence 2018 April 2
BACKGROUND: E-cigarette use is popular among adolescents and youth, but its long-term public health implications remain largely unknown. Much of the literature has focused on understanding the relationship between e-cigarette use and youth cigarette initiation. However, very little is known about e-cigarette use and cigarette quantity among those who continue to smoke cigarettes. The objective of the present study was to examine the association between current e-cigarette use and quantity of cigarette smoking.
METHODS: Cross-sectional data on current smokers were drawn from the 2014-2015 Canadian Student Tobacco, Alcohol and Drugs Survey among high school students (n = 1411). A finite mixture model (FMM) was employed to account for unobserved heterogeneity due to clusters of finite sub-populations.
RESULTS: Current e-cigarette users reported smoking more conventional cigarettes in the past week compared to non-e-cigarette users (t [1409] = 4.7998; p < 0.001 in unadjusted analysis). Results from a finite mixture regression showed that current e-cigarette use was significantly associated with the number of cigarettes smoked in the past week, but only among light smokers (IRR = 1.40; CI = 1.05-1.85). However, additional analyses found that the association between e-cigarette use and quantity of cigarette smoked varied by individual smoking pattern. An FMM with a group or class modelling using individual smoking pattern showed a weaker association between e-cigarette use and quantity of cigarette smoking.
CONCLUSION: Findings of this study suggest that the significant association between e-cigarette use and quantity of cigarette smoking may be driven by patterns of use among experimental or beginner smokers.
METHODS: Cross-sectional data on current smokers were drawn from the 2014-2015 Canadian Student Tobacco, Alcohol and Drugs Survey among high school students (n = 1411). A finite mixture model (FMM) was employed to account for unobserved heterogeneity due to clusters of finite sub-populations.
RESULTS: Current e-cigarette users reported smoking more conventional cigarettes in the past week compared to non-e-cigarette users (t [1409] = 4.7998; p < 0.001 in unadjusted analysis). Results from a finite mixture regression showed that current e-cigarette use was significantly associated with the number of cigarettes smoked in the past week, but only among light smokers (IRR = 1.40; CI = 1.05-1.85). However, additional analyses found that the association between e-cigarette use and quantity of cigarette smoked varied by individual smoking pattern. An FMM with a group or class modelling using individual smoking pattern showed a weaker association between e-cigarette use and quantity of cigarette smoking.
CONCLUSION: Findings of this study suggest that the significant association between e-cigarette use and quantity of cigarette smoking may be driven by patterns of use among experimental or beginner smokers.
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