Bryan W Heckman1,2, Geoffrey T Fong3,4,5, Ron Borland6,7, Sara Hitchman8,9, Richard J O'Connor10, Warren K Bickel11, Jeffrey S Stein11, Hua-Hie Yong6,12, Georges J Nahhas1,2, Derek A Pope11, Ce Shang13, Kai-Wen Cheng14,15, David T Levy16, K Michael Cummings1,2. 1. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA. 2. Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA. 3. Department of Psychology, University of Waterloo, Waterloo, Ontario, Canada. 4. Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 5. School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada. 6. Cancer Council Victoria, Melbourne, Victoria, Australia. 7. School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia. 8. Addictions Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. 9. UK Centre for Tobacco & Alcohol Studies, UK. 10. Department of Health Behavior, Roswell Park Cancer Institute, Buffalo, NY, USA. 11. Addiction Recovery Research Center, Virginia Tech Carilion Research Institute, Roanoke, VA, USA. 12. School of Psychology, Deakin University, Geelong, VIC, Australia. 13. Oklahoma Tobacco Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. 14. Department of Health Administration, Governors State University, University Park, IL, USA. 15. Health Policy Center, Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA. 16. Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.
Abstract
BACKGROUND AND AIMS: Government regulations of nicotine vaping products (NVP) have evolved rapidly during the past decade. The impact of NVP regulatory environment and vaping on cigarette demand is unknown. The current study aims to investigate whether or not respondents' reported cigarette demand, as measured by a hypothetical cigarette purchase task, varies with (1) smoking status, (2) vaping status or (3) NVP regulatory environment (country used as proxy). DESIGN: Cross-sectional survey data from wave 1 of the International Tobacco Control (ITC) Four Country Smoking and Vaping (4CV) Survey (2016). SETTING: Australia, Canada, England and the United States. PARTICIPANTS: A total of 10 316 adult smokers. MEASUREMENTS: A hypothetical purchase task asked smokers to estimate how many cigarettes they would purchase for consumption in a single day across multiple cigarette prices. Responses were used to derive measures of cigarette demand. Overall sensitivity of cigarette consumption to price increases was quantified to index cigarette demand elasticity, whereas estimated consumption when cigarettes are free was used to index cigarette demand intensity. FINDINGS: A majority of the non-daily smokers had previously smoked daily (72.3%); daily vapers were more likely to be former daily smokers (89.9%) compared to non-daily vapers (70.1%) and non-vapers (69.2%) (P < 0.001). The smoking status × vaping status interaction was significant for cigarette demand intensity (F = 4.93; P = 0.007) and elasticity (F = 7.30; P = 0.001): among non-daily smokers, vapers reported greater intensity but lower elasticity (i.e. greater demand) relative to non-vapers (Ps < 0.05). Among daily smokers, daily vapers reported greater intensity relative to non-vapers (P = 0.005), but vaping status did not impact elasticity (Ps > 0.38). Intensity was higher in Australia compared with all other countries (Ps < 0.001), but elasticity did not vary by country (F = 2.15; P = 0.09). CONCLUSIONS: In a hypothetical purchase task, non-daily smokers showed lower price elasticity if they used e-cigarettes than if they did not, while there was no clear difference in elasticity between e-cigarette users and non-users among daily smokers or according to regulatory environment of their country with regard to e-cigarettes.
BACKGROUND AND AIMS: Government regulations of nicotine vaping products (NVP) have evolved rapidly during the past decade. The impact of NVP regulatory environment and vaping on cigarette demand is unknown. The current study aims to investigate whether or not respondents' reported cigarette demand, as measured by a hypothetical cigarette purchase task, varies with (1) smoking status, (2) vaping status or (3) NVP regulatory environment (country used as proxy). DESIGN: Cross-sectional survey data from wave 1 of the International Tobacco Control (ITC) Four Country Smoking and Vaping (4CV) Survey (2016). SETTING: Australia, Canada, England and the United States. PARTICIPANTS: A total of 10 316 adult smokers. MEASUREMENTS: A hypothetical purchase task asked smokers to estimate how many cigarettes they would purchase for consumption in a single day across multiple cigarette prices. Responses were used to derive measures of cigarette demand. Overall sensitivity of cigarette consumption to price increases was quantified to index cigarette demand elasticity, whereas estimated consumption when cigarettes are free was used to index cigarette demand intensity. FINDINGS: A majority of the non-daily smokers had previously smoked daily (72.3%); daily vapers were more likely to be former daily smokers (89.9%) compared to non-daily vapers (70.1%) and non-vapers (69.2%) (P < 0.001). The smoking status × vaping status interaction was significant for cigarette demand intensity (F = 4.93; P = 0.007) and elasticity (F = 7.30; P = 0.001): among non-daily smokers, vapers reported greater intensity but lower elasticity (i.e. greater demand) relative to non-vapers (Ps < 0.05). Among daily smokers, daily vapers reported greater intensity relative to non-vapers (P = 0.005), but vaping status did not impact elasticity (Ps > 0.38). Intensity was higher in Australia compared with all other countries (Ps < 0.001), but elasticity did not vary by country (F = 2.15; P = 0.09). CONCLUSIONS: In a hypothetical purchase task, non-daily smokers showed lower price elasticity if they used e-cigarettes than if they did not, while there was no clear difference in elasticity between e-cigarette users and non-users among daily smokers or according to regulatory environment of their country with regard to e-cigarettes.
Authors: Warren K Bickel; Derek A Pope; Brent A Kaplan; William Brady DeHart; Mikhail N Koffarnus; Jeffrey S Stein Journal: Prev Med Date: 2018-04-24 Impact factor: 4.018
Authors: Jeffrey S Stein; Mikhail N Koffarnus; Sarah E Snider; Amanda J Quisenberry; Warren K Bickel Journal: Exp Clin Psychopharmacol Date: 2015-07-06 Impact factor: 3.157
Authors: Bryan W Heckman; K Michael Cummings; Georges J Nahas; Marc C Willemsen; Richard J O'Connor; Ron Borland; Alexander A Hirsch; Warren K Bickel; Matthew J Carpenter Journal: Nicotine Tob Res Date: 2019-05-21 Impact factor: 4.244
Authors: David T Levy; Ron Borland; Eric N Lindblom; Maciej L Goniewicz; Rafael Meza; Theodore R Holford; Zhe Yuan; Yuying Luo; Richard J O'Connor; Raymond Niaura; David B Abrams Journal: Tob Control Date: 2017-10-02 Impact factor: 7.552
Authors: Cloé Geboers; Ce Shang; Gera E Nagelhout; Hein de Vries; Bas van den Putte; Geoffrey T Fong; Math J J M Candel; Marc C Willemsen Journal: Nicotine Tob Res Date: 2022-03-01 Impact factor: 4.244
Authors: Kai-Wen Cheng; Ce Shang; Hye Myung Lee; Frank J Chaloupka; Geoffrey T Fong; Ron Borland; Bryan W Heckman; Sara C Hitchman; Richard J O'Connor; David T Levy; K Michael Cummings Journal: Tob Control Date: 2020-02-21 Impact factor: 7.552