Evidence map›Paper›PMID 34017926›Full record

ArticleTobacco prevention & cessation2021

A geospatial analysis of age disparities in resolute localities of tobacco and vaping-specific storefronts in California.

Raphael E Cuomo, Joshua S Yang, Vidya L Purushothaman, Matthew Nali, Jiawei Li, Tim K Mackey

Abstract read
In one paragraph

Article in Tobacco prevention & cessation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Raphael E CuomoGlobal Health Policy and Data Institute, San Diego, United States.
Joshua S YangDepartment of Public Health, California State University, Fullerton, United States.
Vidya L PurushothamanGlobal Health Policy and Data Institute, San Diego, United States.
Matthew NaliDepartment of Anesthesiology, School of Medicine, University of California, San Diego, United States.
Jiawei LiGlobal Health Policy and Data Institute, San Diego, United States.
Tim K MackeyGlobal Health Policy and Data Institute, San Diego, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionConcomitant with the popularization of vaping, vape shops have dramatically proliferated over the past years. This study assesses whether vape storefronts in California are significantly associated with density of different age groups, and whether this differs between tobacco storefronts or non-specific tobacco retailers.

methodsAddresses for licensed tobacco retailers were obtained from the California Department of Tax and Fee Administration. Business names and addresses were used to obtain store categories cross-referenced from Yelp. Using a cross-sectional ecological design, stores categorized as 'Vape Shop' or 'Tobacco Shop' were geolocated and compared with age-related variables from the American Community Survey. Regression was conducted in R to determine relationships between age group concentration, in ventiles, and proportion of tracts with tobacco-specific or vape-specific stores. Geospatial visualization was conducted using ArcGIS.

resultsWe found 848 vape shops, 820 tobacco shops, 419 categorized as both, and 20320 retailers with neither category. Overall, 1800 tobacco and/or vape shops were categorized in 1557 of California's 23194 census tracts. A positive linear association was found between ventiles of two age categories, 20-24 and 25-34 years, and proportion of tracts with vape-specific or tobacco-specific shops separately.

conclusionsPositive associations were found for ages 20-34 years but not for other ages, suggesting vape shops are strategically located in areas populated by young adults. Location-based targeting increases access, thereby increasing proportion of tobacco users, and could be a critical factor in e-cigarette uptake and use. Further study to identify additional age-related demographic characteristics among clientele of tobacco storefronts is warranted.

Indexed as

agedisparitieselectronic nicotine delivery devicestobaccovaping

Identifiers

PMID34017926
PMCPMC8114581

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.