Cigarette smoking trajectories in adolescents

Introduction: Despite undeniable progress, far too many Canadian youth still smoke cigarettes. Most smokers report initiation in adolescence or young adulthood. Developmental trajectories of cigarette smoking are descriptions of change in smoking over relatively long time-periods which can be modeled using software platforms which group individuals with similar developmental patterns into subgroups of trajectories. Trajectory analysis may be useful to public health efforts to curb smoking because it permits identification of subgroups that differ according to the pattern of growth in cigarette smoking. Risk factors for, and outcomes of these trajectories can be identified, which may be amenable to intervention to effect positive change in youth smoking. The objectives of this thesis were: (1) to synthesize the literature on studies of adolescent cigarette smoking trajectories; (2) in an adolescent cohort of 1293 participants age 12-13 years at inception, to model trajectories of incident cigarette smoking and compare incident trajectories with mixed (i.e. incident and prevalent smokers combined) trajectories; (3) in the same adolescent cohort, to study cannabis and cigarette initiation in relation to each other and to cigarette smoking trajectories. Methods: We carried out a systematic review of studies of cigarette smoking trajectories in adolescents. PubMed and EMBASE were searched 1980–2018 and 43 articles retained. Data were extracted from each article relating to study population, setting and design, statistical analyses, and results. In order to assess whether study design features might have influenced the number or shapes of trajectories identified, we collapsed studies into categories based on study sample size, type of cigarette smoking indicator used, time axis, and number of data points used to estimate trajectories. We examined the distributions of number and shapes of trajectories identified according to these characteristics. In Manuscript 2 we modeled and compared two sets of cigarette smoking trajectories. The first included incident cigarette smokers alone while the second included both incident and prevalent cigarette smokers. Data were from a cohort of 1293 grade 7 students at baseline. We used SAS Proc Traj to model trajectories of cigarette smoking in adolescence. Analysis of incident trajectories included 307 incident smokers; analysis of “mixed” trajectories included 307 incident and 338 prevalent smokers who reported having ever smoked at baseline. We studied various potential sociodemographic, smoking-related, psychosocial, and lifestyle risk factors in relation to trajectory group. Smoking status and nicotine dependence outcomes were assessed at age 24. Using these data, we compared participants across the cigarette smoking trajectories obtained in Manuscript 2, as well as never smokers during adolescence, baseline ever smokers, and incident smokers who stopped. Using descriptive methods, we compared these groups according to age at first cannabis use and determined the order of initiation of tobacco and cannabis among participants. Using regression, we identified predictors of elapsed time between tobacco and cannabis initiation. Results: The findings of our review revealed considerable heterogeneity between studies which may have reflected real variations in cigarette smoking but which may also have resulted from variation in study design features and modelling decisions. A key finding was that only two studies modeled incident smoking and depicted the natural course of smoking. Five trajectories were identified in incident smokers: stable-low consumers, low-level decreasers, slow escalators, moderate escalators, and early-rapid escalators. Four trajectories were identified in the mix of incident and prevalent smokers. The rate of change was generally attenuated across curves in the mixed trajectory analysis. Escalating trajectories in both analyses were associated with higher levels of cigarette consumption and nicotine dependence in early adulthood. When comparing these five incident trajectory groups with never smokers, prevalent smokers at baseline, and incident smokers who stopped, we report that while first puff on a cigarette usually preceded cannabis use, several groups had a number of participants who initiated cannabis before cigarettes. Age at first cannabis use was generally lower in participants with heavier cigarette consumption. Age at baseline was the only significant risk factor for time to first cannabis use among ever smokers; no factors were associated with time to first cigarette use among ever cannabis users. Ever use of cannabis was higher in trajectory groups with heavier cigarette consumption. Discussion: The literature published thus far has not established the usefulness of this methodology to public health: it is useful for summarizing and describing cigarette smoking patterns, yet it is not clear whether trajectory analyses offer additional information useful to public health. Modeling a mix of incident and prevalent adolescent smokers obscures depiction of the natural course of smoking onset and identification of factors associated with the natural course of cigarette smoking: we therefore recommend that future studies in this area model incident trajectories of cigarette smoking. Our findings also present new information on the initiation of cigarettes and cannabis which should lead to a greater understanding of the interplay between these substances. Cannabis use and cigarette smoking relate to each other in complex ways: our results suggest that it is important to consider use of any one substance in the context of use with other substances.

Keyphrases: Cigarette, Adolescence, Incidence, Prévalence, Cannabis, Cigarette smoking, Young adulthood, Developmental trajectories, Prevalence, Risk factors, Outcomes, Trajectory modeling