Evidence map›Paper›PMID 33865410›Full record

ArticlePopulation health metrics2021

Public health implications of vaping in the USA: the smoking and vaping simulation model.

David T Levy, Jamie Tam, Luz María Sanchez-Romero, Yameng Li, Zhe Yuan, Jihyoun Jeon, Rafael Meza

Abstract read
In one paragraph

Article in Population health metrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Recent Trends in Cigarette and HTP Use in Japan: A Scoping Review.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
    Article
  4. Article
  5. Observational
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Mortality Relative Risks by Smoking, Race/Ethnicity, and Education.American journal of preventive medicine · 2023
    Article
  17. Article
  18. Article
  19. Birth Cohort‒Specific Smoking Patterns by Family Income in the U.S.American journal of preventive medicine · 2023
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

David T LevyLombardi Comprehensive Cancer Center, Georgetown University, 3300 Whitehaven St, NW, Suite 4100, Washington, DC, 20007, USA. DL777@georgetown.edu.ORCID 0000-0001-5280-3612
Jamie TamSchool of Public Health, Yale University, New Haven, CT, USA.
Luz María Sanchez-RomeroLombardi Comprehensive Cancer Center, Georgetown University, 3300 Whitehaven St, NW, Suite 4100, Washington, DC, 20007, USA.
Yameng LiLombardi Comprehensive Cancer Center, Georgetown University, 3300 Whitehaven St, NW, Suite 4100, Washington, DC, 20007, USA.
Zhe YuanLombardi Comprehensive Cancer Center, Georgetown University, 3300 Whitehaven St, NW, Suite 4100, Washington, DC, 20007, USA.
Jihyoun JeonDepartment of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
Rafael MezaDepartment of Epidemiology, University of Michigan, Ann Arbor, MI, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Research Project 3: Modeling the Impact of Tobacco Control Policies on Polytobacco Use and Associated Health DisparitiesU54CA229974 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jihyoun Jeon · 2018 to 2026
$39.2M
Vaporized Nicotine Product Initiation Among Youth in the US, Canada, and England: Methods to Predict Uptake and Policy EfficacyP01CA200512 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI FONG, GEOFFREY T · 2016 to 2025
$25.3M
Comparative Modeling of Lung Cancer Prevention, Early Detection and Treatment InterventionsU01CA253858 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DE KONING, HARRY J, HOLFORD, THEODORE R · 2020 to 2025
$8.4M
NCATS NIH HHS UL1 TR001863NCI NIH HHS P01 CA200512NCI NIH HHS U01 CA253858NCI NIH HHS U54 CA229974NCI NIH HHS U54CA229974
6 · The paper itself

Abstract

backgroundNicotine vaping products (NVPs) are increasingly popular worldwide. They may provide public health benefits if used as a substitute for smoking, but may create public health harms if used as a gateway to smoking or to discourage smoking cessation. This paper presents the Smoking and Vaping Model (SAVM), a user-friendly model which estimates the public health implications of NVPs in the USA.

methodsSAVM adopts a cohort approach. We derive public health implications by comparing smoking- and NVP-attributable deaths and life-years lost under a No-NVP and an NVP Scenario. The No-NVP Scenario projects current, former, and never smoking rates via smoking initiation and cessation rates, with their respective mortality rates. The NVP Scenario allows for smoking- and NVP-specific mortality rates, switching from cigarette to NVP use, separate NVP and smoking initiation rates, and separate NVP and smoking cessation rates. After validating the model against recent US survey data, we present the base model with extensive sensitivity analyses.

resultsThe SAVM projects that under current patterns of US NVP use and substitution, NVP use will translate into 1.8 million premature smoking- and vaping-attributable deaths avoided and 38.9 million life-years gained between 2013 and 2060. When the NVP relative risk is set to 5%, the results are sensitive to the level of switching and smoking cessation rates and to a lesser extent smoking initiation rates. When the NVP relative risk is raised to 40%, the public health gains in terms of averted deaths and LYL are reduced by 42% in the base case, and the results become much more sensitive to variations in the base case parameters. DISCUSSION: Policymakers, researchers, and other public health stakeholders can apply the SAVM to estimate the potential public health impact of NVPs in their country or region using their own data sources. In developing new simulation models involving NVPs, it will be important to conduct extensive sensitivity analysis and continually update and validate with new data.

conclusionThe SAVM indicates the potential benefits of NVP use. However, given the uncertainty surrounding model parameters, extensive sensitivity analysis becomes particularly important.

Indexed as

Smoking CessationVapingCohort StudiesHumansPublic HealthSmokingUnited StatesNVPsPublic healthSimulation modelSmokingVaping

Identifiers

PMID33865410
PMCPMC8052705

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.