James D Sargent1, Joy Gabrielli2, Alan Budney3, Samir Soneji4, Thomas A Wills5. 1. C Everett Koop Institute, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, United States. Electronic address: james.d.sargent@dartmouth.edu. 2. Department of Data Science, Geisel School of Medicine at Dartmouth, United States. 3. Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth, United States. 4. C Everett Koop Institute, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, United States. 5. Cancer Prevention in the Pacific Program, University of Hawaii Cancer Center, United States.
Abstract
OBJECTIVE: The utility of studying substance use during early adolescence depends on how well indicies of lower-level experimentation predict the development of substance use problems. We examined associations between experimental cigarette use at T1, recanting of use 8 months later (T2), and daily smoking at 2 years (T4). METHODS: Longitudinal telephone survey of 6522 US youth aged 10-14, examining lifetime cigarette smoking (none, just puffing, 1-19, 20-100, >100) and recanting (i.e., reporting lifetime use at T1, denying ever using at T2) as predictors of T4 daily smoking using multivariable logistic regression. Covariates included sociodemographics, friend/family smoking, school performance, and personality characteristics. RESULTS: The sample was 51% male, 18% Black, 17% Hispanic, with 70% retained at T2. At T1, 407 (8.9%) adolescents reported some smoking, of whom 85 (20.9%) recanted at T2. At T4, 970 reported any smoking, of whom 88 (9.1%) were daily smokers. Any T1 experimentation identified two-thirds of T4 daily smokers (sensitivity=66.7%) with a false positive rate of 7.8%. T1 lifetime smoking categories were associated with the following adjusted odds ratios for T4 daily smoking (vs. never smokers): 2.7 for recanters (95% confidence interval 0.82, 8.5), 3.5 for few puffs (1.7, 7.0), 9.6 for 1-19 cigarettes (4.1, 22.3), 3.8 for 20-100 cigarettes (1.0, 14.3), and 30.1 for >100 cigarettes (8.1, 111). CONCLUSIONS: In this sample experimentation with cigarettes predicted future daily smoking with high utility. The findings provide a rationale for monitoring and reporting any experimentation cigarettes as a tobacco surveillance outcome.
OBJECTIVE: The utility of studying substance use during early adolescence depends on how well indicies of lower-level experimentation predict the development of substance use problems. We examined associations between experimental cigarette use at T1, recanting of use 8 months later (T2), and daily smoking at 2 years (T4). METHODS: Longitudinal telephone survey of 6522 US youth aged 10-14, examining lifetime cigarette smoking (none, just puffing, 1-19, 20-100, >100) and recanting (i.e., reporting lifetime use at T1, denying ever using at T2) as predictors of T4 daily smoking using multivariable logistic regression. Covariates included sociodemographics, friend/family smoking, school performance, and personality characteristics. RESULTS: The sample was 51% male, 18% Black, 17% Hispanic, with 70% retained at T2. At T1, 407 (8.9%) adolescents reported some smoking, of whom 85 (20.9%) recanted at T2. At T4, 970 reported any smoking, of whom 88 (9.1%) were daily smokers. Any T1 experimentation identified two-thirds of T4 daily smokers (sensitivity=66.7%) with a false positive rate of 7.8%. T1 lifetime smoking categories were associated with the following adjusted odds ratios for T4 daily smoking (vs. never smokers): 2.7 for recanters (95% confidence interval 0.82, 8.5), 3.5 for few puffs (1.7, 7.0), 9.6 for 1-19 cigarettes (4.1, 22.3), 3.8 for 20-100 cigarettes (1.0, 14.3), and 30.1 for >100 cigarettes (8.1, 111). CONCLUSIONS: In this sample experimentation with cigarettes predicted future daily smoking with high utility. The findings provide a rationale for monitoring and reporting any experimentation cigarettes as a tobacco surveillance outcome.
Authors: James D Sargent; Michael L Beach; Anna M Adachi-Mejia; Jennifer J Gibson; Linda T Titus-Ernstoff; Charles P Carusi; Susan D Swain; Todd F Heatherton; Madeline A Dalton Journal: Pediatrics Date: 2005-11 Impact factor: 7.124
Authors: M L Saddleson; L T Kozlowski; G A Giovino; G G Homish; M C Mahoney; M L Goniewicz Journal: Drug Alcohol Depend Date: 2016-03-09 Impact factor: 4.492
Authors: Cassandra A Stanton; George Papandonatos; Elizabeth E Lloyd-Richardson; Raymond Niaura Journal: Addiction Date: 2007-09-03 Impact factor: 6.526
Authors: William G Shadel; Steven C Martino; Claude Setodji; Michael Dunbar; Daniela Kusuke; Serafina Lanna; Amanda Meyer Journal: Nicotine Tob Res Date: 2019-01-04 Impact factor: 4.244
Authors: Eleanor L S Leavens; Ellen Meier; Emma I Brett; Elise M Stevens; Alayna P Tackett; Andrea C Villanti; Theodore L Wagener Journal: Addict Behav Date: 2018-11-08 Impact factor: 3.913
Authors: Alyssa F Harlow; Andrew C Stokes; Daniel R Brooks; Emelia J Benjamin; Jessica L Barrington-Trimis; Craig S Ross Journal: Epidemiology Date: 2022-03-29 Impact factor: 4.860
Authors: Cassandra A Stanton; Maansi Bansal-Travers; Amanda L Johnson; Eva Sharma; Lauren Katz; Bridget K Ambrose; Marushka L Silveira; Hannah Day; James Sargent; Nicolette Borek; Wilson M Compton; Sarah E Johnson; Heather L Kimmel; Annette R Kaufman; Jean Limpert; David Abrams; K Michael Cummings; Maciej L Goniewicz; Susanne Tanski; Mark J Travers; Andrew J Hyland; Jennifer L Pearson Journal: J Natl Cancer Inst Date: 2019-10-01 Impact factor: 13.506