Evidence map›Paper›PMID 41446680›Full record

ArticlePreventive medicine reports2026

Differential Association of Exposure to advertising channels with ever

Elizabeth R Stevens, Michelle He, Mohsen Abbasi-Kangevari, Omar El-Shahawy

Abstract read
In one paragraph

Article in Preventive medicine reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Elizabeth R StevensDepartment of Population Health, New York University School of Medicine, New York, NY, United States of America.
Michelle HeDepartment of Population Health, New York University School of Medicine, New York, NY, United States of America.
Mohsen Abbasi-KangevariDepartment of Population Health, New York University School of Medicine, New York, NY, United States of America.
Omar El-ShahawyDepartment of Population Health, New York University School of Medicine, New York, NY, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine how exposure to advertising channels is associated with e-cigarette use among youth in the United States. Methods: This study included 161,700 middle and high school students aged 9-18 years from the 2014-2022 National Youth Tobacco Survey data. Multivariate logistic regressions estimated adjusted odds ratios (aORs) and 95 % confidence intervals (CIs) for the association between exposure to advertising channels and ever e-cigarette use. Annual percent change (APC) for ever e-cigarette use and exposure to each advertising channel were analyzed using Joinpoint regression. Data for 2014-2018 and 2019-2022 were analyzed separately due to the change in survey format and weighting procedure. Results: Ever e-cigarette use prevalence increased (APC = + 2.78: 95 % CI -13.65, 21.38) between 2014 and 2018, then declined (APC = -18.20 %: 95 % CI -27.11, 8.36) between 2019 and 2022. Exposure to retail (2014-2018 aOR = 1.36: 95 % CI 1.29, 1.43; 2019-2022 aOR = 1.46: 95 % CI 1.38, 1.54) and internet advertising (2014-2018 aOR = 1.43: 95 % CI 1.35, 1.51; 2019-2022 aOR = 1.19: 95 % CI 1.13, 1.25) were associated with higher odds of ever e-cigarette use. Conclusions: Exposure to retail and internet marketing increased the likelihood of ever-use of e-cigarettes among youth in the US. Additional regulations for point-of-sale and internet advertisements should be implemented.

Indexed as

AdolescentAdvertisementsElectronic cigarettesElectronic nicotine delivery systemsMass mediaTobacco use preventionYouth

Identifiers

PMID41446680
PMCPMC12723290

What OpenQuestion holds

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LicenceCC BY-NC
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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.