Evidence map›Paper›PMID 36317059›Full record

ArticleTobacco induced diseases2022

Longitudinal analysis of tobacco and vape retail density in California.

Vidya Purushothaman, Raphael E Cuomo, Eric Leas, Jiawei Li, David Strong, Tim K Mackey

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  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

6 authors.

Vidya PurushothamanDepartment of Anthropology, University of California San Diego, San Diego, United States.
Raphael E CuomoDepartment of Anthropology, University of California San Diego, San Diego, United States.
Eric LeasHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, United States.
Jiawei LiGlobal Health Policy and Data Institute, San Diego, United States.
David StrongHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, United States.
Tim K MackeyDepartment of Anthropology, University of California San Diego, San Diego, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTobacco retailer density may be associated with greater youth initiation and reduced success during quit attempts; however, the extent to which tobacco retailer density has changed overtime across multiple categories of retailers has not been reported.

methodsData on licensed tobacco retailers within California from 2015-2019 were obtained from the California Department of Tax and Fee Administration. Store type was categorized by automated cross-referencing with Yelp. Geolocations were aggregated at county level for analyzing longitudinal trends in changes in tobacco retail density including demographic characteristics.

resultsThe number of active CA tobacco retailer licenses increased from 19825 in 2015 to 25635 in 2019. The highest percent increase in tobacco retailer licenses (9.1%) was observed in 2017. The number of specialized tobacco stores was highest in Los Angeles, San Diego, and Riverside counties. We observed a significant increase in the number of active licenses for non-specialized and specialized tobacco stores, both overall and after controlling for the size of populations within each region. Time was a statistically significant predictor for the number of active licenses for only non-specialized stores, after adjusting for covariates. Regional volume of retailers was positively associated with higher proportion of women, lower median household income, and higher proportion of Hispanic residents.

conclusionsMonitoring the changes in tobacco retail density and associated sociodemographic factors over time can help to identify communities at higher risk for tobacco and nicotine product exposure and access, and its associated health disparities.

Indexed as

ecological studylongitudinal studytobaccotobacco retailvaping

Identifiers

PMID36317059
PMCPMC9574848

What OpenQuestion holds

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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.