Beyond experimentation: Five trajectories of cigarette smoking in a longitudinal sample of youth

Abstract

The first goal of this study was to identify the most appropriate measure of cigarette smoking for identifying unique smoking trajectories among adolescents; the second goal was to describe the resulting trajectories and their characteristics. Using 15 annual waves of smoking data in the National Longitudinal Survey of Youth 1997 (NLSY97), we conducted an exploratory latent class growth analysis to determine the best of four outcome variables for yearly smoking (cigarettes per day on days smoked, days smoked per month, mean cigarettes per day, and total cigarettes per month) among individuals aged 12 to 30 (n = 8,791). Days smoked per month was the best outcome variable for identifying unique longitudinal trajectories of smoking and characteristics of these trajectories that could be used to target different types of smokers for prevention and cessation. Objective statistics were used to identify four trajectories in addition to never smokers (34.1%): experimenters (13.6%), quitters (8.1%), early established smokers (39.0%), and late escalators (5.2%). We identified a quitter and late escalator class not identified in the only other comparable latent class growth analysis. Logistic regressions were used to identify the characteristics of individuals in each trajectory. Compared with never smokers, all trajectories except late escalators were less likely to be black; experimenters were more likely to be out of school and unemployed and drink alcohol in adolescence; quitters were more likely to have a mother with a high school degree/GED or higher (versus none) and to use substances in adolescence and less likely to have ever married as a young adult; early established smokers were more likely to have a mother with a high school diploma or GED, be out of school and unemployed, not live with both parents, have used substances, be depressed, and have peers who smoked in adolescence and to have children as young adults and less likely to be Hispanic and to have ever married as young adults; and late escalators were more likely to be Hispanic, drink alcohol, and break rules in adolescence and less likely to have ever married as young adults. Because of the number of waves of data analyzed, this analysis provided a clearer temporal depiction of smoking behavior and more easily distinguishable smoking trajectories than previous analyses. Tobacco control interventions need to move beyond youth-focused approaches to reach all smokers.

Early Predictors of Trajectories of Tobacco Use Level from Adolescence to Young Adulthood: A 16-Year Follow-Up of the TEMPO Cohort Study (1999–2015)

“…Second, the statistical power of our analyses was limited for the study of some factors (e.g., the role of vocational training). Additional studies, examining long-term smoking trajectories in larger samples with sufficient numbers in all groups (particularly smokers who quit and who are underrepresented prior to age 40 [42][43][44]) are needed. Third, we did not study certain factors associated with long-term smoking such as adverse childhood experiences and peer smoking because this information was not Statistically significant results are presented in bold type.…”

Smoking susceptibility as a predictive measure of cigarette and e-cigarette use among early adolescents

“…Recently, four trajectories in the smoking uptake behavior have been identified: experimenters, quitters, early established smokers and late escalators. 34 Our study only considered experimenters and current smokers.…”

The Effect of Smoking Cessation on Sleep Patterns of Young Adults

“…The positive correlation found in the current study between scores on the MSQ-insomnia and levels of urge to smoke (QSU scores) following one week of abstinence from smoking is consistent with several studies in older adults. In these studies, the severity of sleep disturbances before and during smoking cessation predicted difficulties to remain abstinent and eventual relapse [9,20,33]. For example, higher frequency of awakenings during the first nights of abstinence from smoking was inversely related to successful smoking cessation [53,54].…”

“…On the other hand, insufficient sleep is very common among young adults in general and college students in particular [15,16], particularly due to poor sleep habits such as irregular bedtime schedule and the use of electronic devices, such as tablet computers and smartphones, before going to bed [16][17][18]. As smokers tend to establish their smoking dependence during early adulthood [19,20], it is imperative to clarify the extent to which insufficient sleep is involved in the progression and persistence of smoking dependence among young adults. This has significant clinical implications, as evidence pointing to sleep-associated difficulties hindering smoking cessation may lead to the incorporation of sleep-promoting therapies in smoking cessation [9].…”