The Application of a Decision-Theoretic Model to Estimate the Public Health Impact of Vaporized Nicotine Product Initiation in the United States.
BACKGROUND
The public health impact of vaporized nicotine products (VNPs) such as e-cigarettes is unknown at this time. VNP uptake may encourage or deflect progression to cigarette smoking in those who would not have otherwise smoked, thereby undermining or accelerating reductions in smoking prevalence seen in recent years.


METHODS
The public health impact of VNP use are modeled in terms of how it alters smoking patterns among those who would have otherwise smoked cigarettes and among those who would not have otherwise smoked cigarettes in the absence of VNPs. The model incorporates transitions from trial to established VNP use, transitions to exclusive VNP and dual use, and the effects of cessation at later ages. Public health impact on deaths and life years lost is estimated for a recent birth cohort incorporating evidence-informed parameter estimates.


RESULTS
Based on current use patterns and conservative assumptions, we project a reduction of 21% in smoking-attributable deaths and of 20% in life years lost as a result of VNP use by the 1997 US birth cohort compared to a scenario without VNPs. In sensitivity analysis, health gains from VNP use are especially sensitive to VNP risks and VNP use rates among those likely to smoke cigarettes.


CONCLUSIONS
Under most plausible scenarios, VNP use generally has a positive public health impact. However, very high VNP use rates could result in net harms. More accurate projections of VNP impacts will require better longitudinal measures of transitions into and out of VNP, cigarette and dual use.


CONCLUSIONS
Previous models of VNP use do not incorporate whether youth and young adults initiating VNP would have been likely to have been a smoker in the absence of VNPs. This study provides a decision-theoretic model of VNP use in a young cohort that incorporates tendencies toward smoking and shows that, under most plausible scenarios, VNP use yields public health gains. The model makes explicit the type of surveillance information needed to better estimate the effect of new products and thereby inform public policy.
Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.
David T
DT
Levy
VicHealth Centre for Tobacco Control, The Cancer Council Victoria, Melbourne, Victoria, Australia.
Ron
R
Borland
Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington DC.
Andrea C
AC
Villanti
Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington DC.
Raymond
R
Niaura
Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.
Zhe
Z
Yuan
Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.
Yian
Y
Zhang
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI.
Rafael
R
Meza
Department of Biostatistics, Yale University, New Haven, CT.
Theodore R
TR
Holford
Department of Psychology, University of Waterloo, Waterloo, Ontario, Canada.|School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Geoffrey T
GT
Fong
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC.
K Michael
KM
Cummings
Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.|Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington DC.|Department of Health, Behavior, and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
David B
DB
Abrams
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003661:Decision Support Techniques; D003663:Decision Trees; D066300:Electronic Nicotine Delivery Systems / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015995:Prevalence; D011634:Public Health; D012907:Smoking / Q000401:mortality; D016540:Smoking Cessation / Q000379:methods*; D000074606:Smoking Prevention; D014481:United States / Q000453:epidemiology; D055815:Young Adult