Evidence map›Paper›PMID 39927129›Full record

ArticlePreventive medicine reports2025

Smokeless tobacco excise taxes in the US: Standardizing the measurement for empirical analysis.

Yanyun He, Zezhong Zhang, Qian Yang, Ce Shang

Abstract read
In one paragraph

Article in Preventive medicine reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Yanyun HeCenter for Tobacco Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Zezhong ZhangCenter for Tobacco Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Qian YangCenter for Tobacco Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Ce ShangCenter for Tobacco Research, The Ohio State University Wexner Medical Center, Columbus, OH, USA.

Funding

The Ohio State University Tobacco Center of Regulatory Science (OSU-TCORS)U54CA287392 · NCI · OHIO STATE UNIVERSITY · PI Peter G. Shields, Theodore Lee Wagener · 2023 to 2026
$19.5M
The impact of ENDS tax policies on the consumption of ENDS and cigarettesR21CA249757 · NCI · OHIO STATE UNIVERSITY · PI SHANG, CE · 2021 to 2021
$401k
NCI NIH HHS R21 CA249757NCI NIH HHS U54 CA287392
6 · The paper itself

Abstract

Introduction: The effect of smokeless tobacco (SLT) taxes on SLT use has received relatively little research attention in the US compared to the extensive focus on cigarette and e-cigarette taxation. The scarcity of SLT literature is partially due to the complexities of SLT taxes and the lack of standardized taxes. While some states imposed specific taxes based on the weight of the products, others imposed Objective: We standardize SLT taxes into two measures: first, we convert Methods: We extracted sales-weighted retail prices from the Nielsen Retail Scanner Data between 2006 and 2020. We developed a method to standardize SLT taxes. Results: Overall, the standardized SLT taxes exhibit a steadily increasing trend. In the fourth quarter of 2020, the average specific tax for chewing tobacco, moist snuff, dry snuff, and snus was $0.36, $0.91, $0.74, and $1.27 per ounce, respectively. The average Conclusions: The SLT tax data provided here can serve as a valuable tool for policymakers in determining and refining SLT tax rates, further allowing future studies to understand their impacts on SLT use and related disparities.

Indexed as

Ad valorem taxExcise taxSmokeless tobaccoSpecific tax

Identifiers

PMID39927129
PMCPMC11803860

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.