Evidence map›Paper›PMID 35394965›Full record

ArticleEpidemiology (Cambridge, Mass.)2022

e-Cigarette Use and Combustible Cigarette Smoking Initiation Among Youth: Accounting for Time-Varying Exposure and Time-Dependent Confounding.

Alyssa F Harlow, Andrew C Stokes, Daniel R Brooks, Emelia J Benjamin, Jessica L Barrington-Trimis, Craig S Ross

Abstract readVideo-Audio Media
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 4 pooled it
–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

19 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Review
  12. Factors influencing JUUL e-cigarette nicotine vapour-induced reward, withdrawal, pharmacokinetics and brain connectivity in rats: sex matters.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Alyssa F HarlowFrom the Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA.
Andrew C StokesDepartment of Global Health, Boston University School of Public Health, Boston, MA.
Daniel R BrooksDepartment of Epidemiology, Boston University School of Public Health, Boston, MA.
Emelia J BenjaminDepartment of Epidemiology, Boston University School of Public Health, Boston, MA.
Jessica L Barrington-TrimisFrom the Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA.
Craig S RossDepartment of Epidemiology, Boston University School of Public Health, Boston, MA.

Funding

ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
Novel Methods for Evaluating the Association of Electronic Cigarette Use with Cardiovascular HealthK01HL154130 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI STOKES, ANDREW · 2020 to 2024
$904k
NHLBI NIH HHS K01 HL154130NHLBI NIH HHS U54 HL120163
6 · The paper itself

Abstract

backgroundYouth e-cigarette use is associated with the initiation of combustible cigarette smoking, but prior studies have rarely accounted for time-varying measures of e-cigarette exposure or time-dependent confounding of e-cigarette use and smoking initiation.

methodsUsing five waves of the Population Assessment of Tobacco and Health (2013-2019), we estimated marginal structural models with inverse probability of treatment and censoring weights to examine the association between time-varying e-cigarette initiation and subsequent cigarette smoking initiation among e-cigarette- and cigarette-naïve youth (12-17 years) at baseline. Time-dependent confounders used as predictors in inverse probability weights included tobacco-related attitudes or beliefs, mental health symptoms, substance use, and tobacco-marketing exposure.

resultsAmong 9,584 youth at baseline, those who initiated e-cigarettes were 2.4 times as likely to subsequently initiate cigarette smoking as youth who did not initiate e-cigarettes (risk ratio = 2.4, 95% confidence interval [CI] = 2.1, 2.7), after accounting for time-dependent confounding and selection bias. Among youth who initiated e-cigarettes, more frequent vaping was associated with greater risk of smoking initiation (risk ratio ≥3 days/month = 1.8, 95% CI = 1.4, 2.2; 1-2 days/month = 1.2; 95% CI = 0.93, 1.6 vs. 0 days/month). Weighted marginal structural model estimates were moderately attenuated compared with unweighted estimates adjusted for baseline-only confounders. At the US population level, we estimated over half a million youth initiated cigarette smoking because of prior e-cigarette use over follow-up.

conclusionsThe association between youth vaping and combustible cigarette smoking persisted after accounting for time-dependent confounding. We estimate that e-cigarette use accounts for a considerable share of cigarette initiation among US youth. See video abstract at, http://links.lww.com/EDE/B937.

Indexed as

Cigarette SmokingElectronic Nicotine Delivery SystemsTobacco ProductsVapingAdolescentHumans

Identifiers

PMID35394965
PMCPMC9156560

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.