Evidence map›Paper›PMID 30167658›Full record

ArticleAnnals of internal medicine2018

Prevalence and Distribution of E-Cigarette Use Among U.S. Adults: Behavioral Risk Factor Surveillance System, 2016.

Mohammadhassan Mirbolouk, Paniz Charkhchi, Sina Kianoush, S M Iftekhar Uddin, Olusola A Orimoloye, Rana Jaber, Aruni Bhatnagar, Emelia J Benjamin, Michael E Hall, Andrew P DeFilippis and 3 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 180 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
180citing papers in PubMed, 2 pooled it
29.8field-weighted citation impact, top 1% of its field
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

180 citing papers in PubMed, 2 syntheses or guidelines pooled it, 335 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. E-Cigarette Use and Depression Among American Indian Adults Who Smoke.Journal of racial and ethnic health disparities · 2026
    Article
  8. Article
  9. Inhibition of Circadian Rhythm GeneEnvironment & health (Washington, D.C.) · 2025
    Article
  10. Review
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  12. Article
  13. Review
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  15. Review
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  17. Article
  18. Correlates of smoking during COVID-19 in the LGBTQI + cancer survivor population.Journal of cancer survivorship : research and practice · 2024
    Article
  19. Article
  20. Article

120 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 7 institutions in 2 countries.

Mohammadhassan MirboloukThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and Johns Hopkins University, Baltimore, Maryland (M.M., S.I.U., O.A.O., M.J.B.).
Paniz CharkhchiJohns Hopkins University, Baltimore, Maryland, and University of Michigan, Ann Arbor, Michigan (P.C.).
Sina KianoushJohns Hopkins University, Baltimore, Maryland, and Yale University School of Medicine, New Haven, Connecticut (S.K.).
S M Iftekhar UddinThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and Johns Hopkins University, Baltimore, Maryland (M.M., S.I.U., O.A.O., M.J.B.).
Olusola A OrimoloyeThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and Johns Hopkins University, Baltimore, Maryland (M.M., S.I.U., O.A.O., M.J.B.).
Rana JaberThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and Florida International University, Miami, Florida (R.J.).
Aruni BhatnagarThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and University of Louisville, Louisville, Kentucky (A.B., A.P.D.).
Emelia J BenjaminThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and Boston University, Boston, Massachusetts (E.J.B.).
Michael E HallThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and University of Mississippi Medical Center, Jackson, Mississippi (M.E.H.).
Andrew P DeFilippisThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and University of Louisville, Louisville, Kentucky (A.B., A.P.D.).
Wasim MaziakFlorida International University, Miami, Florida, and Syrian Center for Tobacco Studies, Aleppo, Syria (W.M.).
Khurram NasirJohns Hopkins University, Baltimore, Maryland, Yale University School of Medicine, New Haven, Connecticut, and Florida International University, Miami, Florida and Population Health & Health Systems Research, Center for Outcomes Research and Evaluation (CORE), Section of Cardiovascular Medicine, Yale University School of Medicine. (K.N.).
Michael J BlahaThe American Heart Association Tobacco Regulation and Addiction Center, Dallas, Texas, and Johns Hopkins University, Baltimore, Maryland (M.M., S.I.U., O.A.O., M.J.B.).
American Heart Association · USJohns Hopkins University · USFlorida International University · USSyrian Center for Tobacco Studies · SYUniversity of Louisville · USUniversity of Michigan–Ann Arbor · USYale University · US

Funding

Research Training and Education Core (Core D) P50HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BUTLER, JAVED · 2013 to 2017
$20.1M
ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
NHLBI NIH HHS P50 HL120163NHLBI NIH HHS U54 HL120163
6 · The paper itself

Abstract

Background: Contemporary data on the prevalence of e-cigarette use in the United States are limited. Objective: To report the prevalence and distribution of current e-cigarette use among U.S. adults in 2016. Design: Cross-sectional. Setting: Behavioral Risk Factor Surveillance System, 2016. Participants: Adults aged 18 years and older. Measurements: Prevalence of current e-cigarette use by sociodemographic groups, comorbid medical conditions, and states of residence. Results: Of participants with information on e-cigarette use (n = 466 842), 15 240 were current e-cigarette users, representing a prevalence of 4.5%, which corresponds to 10.8 million adult e-cigarette users in the United States. Of the e-cigarette users, 15% were never-cigarette smokers. The prevalence of current e-cigarette use was highest among persons aged 18 to 24 years (9.2% [95% CI, 8.6% to 9.8%]), translating to approximately 2.8 million users in this age range. More than half the current e-cigarette users (51.2%) were younger than 35 years. In addition, the age-standardized prevalence of e-cigarette use was high among men; lesbian, gay, bisexual, and transgender (LGBT) persons; current combustible cigarette smokers; and those with chronic health conditions. The prevalence of e-cigarette use varied widely among states, with estimates ranging from 3.1% (CI, 2.3% to 4.1%) in South Dakota to 7.0% (CI, 6.0% to 8.2%) in Oklahoma. Limitation: Data were self-reported, and no biochemical confirmation of tobacco use was available. Conclusion: E-cigarette use is common, especially in younger adults, LGBT persons, current cigarette smokers, and persons with comorbid conditions. The prevalence of use differs across states. These contemporary estimates may inform researchers, health care policymakers, and tobacco regulators about demographic and geographic distributions of e-cigarette use. Primary Funding Source: American Heart Association Tobacco Regulation and Addiction Center, which is funded by the U.S. Food and Drug Administration and National Heart, Lung, and Blood Institute.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsBehavioral Risk Factor Surveillance SystemCross-Sectional StudiesElectronic Nicotine Delivery SystemsFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsSex FactorsSocioeconomic Factors

Identifiers

PMID30167658
PMCPMC10534294
OpenAlexW2889528655

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.