Gary Chan1, Kylie Morphett2, Coral Gartner2,3, Janni Leung1,4, Hua-Hie Yong5,6, Wayne Hall1,7, Ron Borland7,8. 1. Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, QLD, Australia. 2. School of Public Health, The University of Queensland, Brisbane, QLD, Australia. 3. Queensland Alliance for Environmental Health Sciences, The University of Queensland, Brisbane, QLD, Australia. 4. National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia. 5. School of Psychology, Deakin University, Geelong, VIC, Australia. 6. Cancer Council Victoria, Melbourne, VIC, Australia. 7. National Addiction Centre, King's College London, London, UK. 8. School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia.
Abstract
AIM: To assess (1) how far smoking patterns, depression and smoking-related beliefs and intentions predict vaping uptake, current vaping and vaping frequency among daily smokers; and (2) how far the aforementioned predictors and baseline vaping frequency predict current vaping among those who reported ever vaped. DESIGN: Analysis of data from six waves of a longitudinal survey over 8 years. Longitudinal associations between predictors and outcomes were examined using multi-level models. SETTING: United Kingdom, United States, Canada and Australia. PARTICIPANTS: A total of 6296 daily smokers (53% females) who contributed data to at least two consecutive survey waves. MEASUREMENTS: The outcome variables were vaping uptake, vaping frequency and current vaping at follow-up. The key predictor variables, measured in previous waves, were time to first cigarette, cigarettes smoked per day, depressive symptoms, intention to quit smoking, quitting self-efficacy and worry about adverse health effects of smoking. FINDINGS: Number of cigarettes smoked daily was associated with (1) subsequent vaping uptake [odds ratio (OR) = 1.69, 95% confidence interval (CI) = 1.19, 2.39 for 30+ cigarette per day; reference category: 0-10 cigarettes] and (2) a higher frequency of current vaping (OR = 1.97, 95% CI = 1.36, 2.85 for 30+ cigarettes). Intention to quit was associated with a higher frequency of current vaping (OR = 1.48, 95% CI = 1.21, 1.82). Among those who reported ever vaped, higher baseline vaping frequency (OR = 11.98, 95% CI = 6.00, 23.93 for daily vaping at baseline; reference category: vaped less than monthly) predicted current vaping. CONCLUSION: Among daily smokers, amount smoked and intention to quit smoking appear to predict subsequent vaping uptake. Vaping frequency at baseline appears to predict current vaping at follow-up.
AIM: To assess (1) how far smoking patterns, depression and smoking-related beliefs and intentions predict vaping uptake, current vaping and vaping frequency among daily smokers; and (2) how far the aforementioned predictors and baseline vaping frequency predict current vaping among those who reported ever vaped. DESIGN: Analysis of data from six waves of a longitudinal survey over 8 years. Longitudinal associations between predictors and outcomes were examined using multi-level models. SETTING: United Kingdom, United States, Canada and Australia. PARTICIPANTS: A total of 6296 daily smokers (53% females) who contributed data to at least two consecutive survey waves. MEASUREMENTS: The outcome variables were vaping uptake, vaping frequency and current vaping at follow-up. The key predictor variables, measured in previous waves, were time to first cigarette, cigarettes smoked per day, depressive symptoms, intention to quit smoking, quitting self-efficacy and worry about adverse health effects of smoking. FINDINGS: Number of cigarettes smoked daily was associated with (1) subsequent vaping uptake [odds ratio (OR) = 1.69, 95% confidence interval (CI) = 1.19, 2.39 for 30+ cigarette per day; reference category: 0-10 cigarettes] and (2) a higher frequency of current vaping (OR = 1.97, 95% CI = 1.36, 2.85 for 30+ cigarettes). Intention to quit was associated with a higher frequency of current vaping (OR = 1.48, 95% CI = 1.21, 1.82). Among those who reported ever vaped, higher baseline vaping frequency (OR = 11.98, 95% CI = 6.00, 23.93 for daily vaping at baseline; reference category: vaped less than monthly) predicted current vaping. CONCLUSION: Among daily smokers, amount smoked and intention to quit smoking appear to predict subsequent vaping uptake. Vaping frequency at baseline appears to predict current vaping at follow-up.
Authors: M E Thompson; G T Fong; D Hammond; C Boudreau; P Driezen; A Hyland; R Borland; K M Cummings; G B Hastings; M Siahpush; A M Mackintosh; F L Laux Journal: Tob Control Date: 2006-06 Impact factor: 7.552
Authors: Jennifer L Pearson; Amanda Richardson; Raymond S Niaura; Donna M Vallone; David B Abrams Journal: Am J Public Health Date: 2012-07-19 Impact factor: 9.308
Authors: R L Spitzer; J B Williams; K Kroenke; M Linzer; F V deGruy; S R Hahn; D Brody; J G Johnson Journal: JAMA Date: 1994-12-14 Impact factor: 56.272
Authors: Muhammad Aziz Rahman; Nicholas Hann; Andrew Wilson; George Mnatzaganian; Linda Worrall-Carter Journal: PLoS One Date: 2015-03-30 Impact factor: 3.240
Authors: Beth Han; Nora D Volkow; Carlos Blanco; Douglas Tipperman; Emily B Einstein; Wilson M Compton Journal: JAMA Date: 2022-04-26 Impact factor: 157.335
Authors: Kim Agj Romijnders; Erna Jz Krüsemann; Sanne Boesveldt; Kees de Graaf; Hein de Vries; Reinskje Talhout Journal: Int J Environ Res Public Health Date: 2019-11-22 Impact factor: 3.390