The net impact on population health and health system costs of vaporized nicotine products is uncertain. We modeled, with uncertainty, the health and cost impacts of liberalizing the vaporized nicotine market for a high-income country, New Zealand (NZ).
We used a multistate life-table model of 16 tobacco-related diseases to simulate lifetime quality-adjusted life-years (QALYs) and health system costs at a 0% discount rate. We incorporated transitions from never, former, and current smoker states to, and from, regularly using vaporized nicotine and literature estimates for relative risk of disease incidence for vaping compared with smoking.
Compared with continuation of baseline trends in smoking uptake and cessation rates and negligible vaporized nicotine use, we projected liberalizing the market for these products to gain 236,000 QALYs (95% uncertainty interval [UI] = 27,000 to 457,000) and save NZ$3.4 billion (2011 NZ$) (95% UI = NZ$370 million to NZ$7.1 billion) or US$2.5 billion (2017 NZ$). However, estimates of net health gains for 0- to 14-year olds and 65+ year olds had 95% UIs including the null. Uncertainty around QALYs gained was mainly driven by uncertainty around the impact of vaporized nicotine products on population-wide cessation rates and the relative health risk of vaping compared with smoking.
This modeling suggested that a fairly permissive regulatory environment around vaporized nicotine products achieves net health gain and cost savings, albeit with wide uncertainty. Our results suggest that optimal strategies will also be influenced by targeted smoking cessation advice, regulations around chemical constituents of these products, and marketing and age limits to prevent youth uptake of vaping.
From the aBurden of Disease Epidemiology, Equity, and Cost-Effectiveness (BODE3), Department of Public Health, University of Otago, Wellington, New Zealand
bCentre for Applied Health Economics (CAHE), School of Medicine, Griffith University, Nathan, Queensland, Australia
cSchool of Public Health, The University of Queensland, Herston, Queensland, Australia
dMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Submitted May 15, 2018; accepted January 23, 2019.
The authors report no conflicts of interest.
Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).
Data availability: Supporting information regarding the multistate life-table model approach and data inputs can be found online in Blakely et al. and Pearson et al. Data sharing with other researchers or official agencies of the precise data used in the modeling is potentially possible subject to agreement with the government agencies making it available to the researchers (the Ministry of Health).
Correspondence: Frederieke S. Petrović-van der Deen, Burden of Disease Epidemiology, Equity, and Cost-Effectiveness (BODE3), Department of Public Health, University of Otago, 23 Mein Street, Newtown, Wellington 6242, New Zealand. E-mail: email@example.com.