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Predicting longitudinal changes in patterns of tobacco and nicotine product use among adolescents: A Latent
Lisbeth Lund1, Susan Andersen1, Christian Ritz1
1National Institute of Public Health, University of Southern Denmark, Studiestræde, 61455, Copenhagen, Denmark.
Introduction:
Understanding factors influencing the transition from non-use to tobacco and nicotine product initiation among adolescents is crucial for designing and implementing effective preventive strategies. This study explores transition patterns among 13-15-year-old adolescents in lower secondary school, focusing on the transition from non-use to tobacco and nicotine product initiation and the influence of individual, social, risk behavioral, and mental health factors on this transition.
Methods:
Based on data from a Danish smoking prevention trial between 2017 and 2019, this study employed questionnaire surveys at three time points: baseline (start of seventh grade, n = 1,990, response rate = 86.3%), eight-month follow-up (end of seventh grade, n = 1,666, response rate = 74,8%), and 20-month follow-up (end of eighth grade, n = 1,149, response rate = 70,6%). Tobacco and nicotine use indicators included current and lifetime use of cigarettes and lifetime use of e-cigarettes, smokeless tobacco, and hookah. A latent transition analysis was applied to identify longitudinal transition patterns across waves and to explore predictors of these patterns.
Results:
Three user classes emerged across all waves: none-use, lifetime e-cigarette and cigarette use, and poly-tobacco use. While the most prevalent class was the non-user class (71%-86%), the proportion of the lifetime e-cigarette and cigarette class increased over time (from 12% to 17%). Similarly, the poly-tobacco user class increased from 2% to 12%. The probability of transitioning from non-use to lifetime e-cigarette and cigarette use increased from 0.5% at baseline to 12% by the second follow-up, while the probability of transitioning from lifetime e-cigarette and cigarette use remained stable over time (12%-15%). Across all waves, elevated risk behavior predicted this transition. For instance, binge-drinking (OR = 3.76, 95% CI: 1.51-9.34), susceptibility to smoking (OR = 7.63, 95% CI: 3.68-16.83), and truancy (OR = 7.00, 95% CI: 1.98-24.59) influenced the transition from non-use at baseline to lifetime e-cigarette and cigarette use at first follow-up. Additionally, boys, adolescents with low socioeconomic status, low life satisfaction, and those with smoking friends or parents were more likely to transition from non-use to lifetime e-cigarette and cigarette use.
Conclusion:
This study demonstrates that sociodemographic, social risk, behavioral, and mental health factors impact the transition from non-use to lifetime e-cigarette and cigarette use. The findings provide valuable insights for developing targeted preventive strategies focusing on these influencing factors.
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