Evidence map›Paper›PMID 33310775›Full record

ArticleTobacco control2022

A Simulation of the potential impact of restricting tobacco retail outlets around middle and high schools on tobacco advertisements.

Udoka Obinwa, Keryn E Pasch, Katelyn K Jetelina, Nalini Ranjit, Adriana Perez, Cheryl Perry, Melissa Harrell

Abstract read
In one paragraph

Article in Tobacco control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Correlation Among Neighborhood-Level Measures of the Tobacco Retail Environment.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
  3. School-Level Socioeconomic Status and Nutrient Content of Outdoor Food/Beverage Advertisements.International journal of environmental research and public health · 2023
    Article
  4. Article
  5. Restricting Tobacco Retail Outlets Around Middle and High Schools as a Way to Reduce Tobacco Marketing Disparities: A Simulation Study.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2022
    Article
  6. 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

7 authors.

Udoka ObinwaThe University of Texas Health Science Center at Houston (UTHealth), School of Public Health in Austin, Austin, Texas, USA.
Keryn E PaschKinesiology and Health Education, The University of Texas at Austin, Austin, Texas, USA kpasch@austin.utexas.edu.ORCID 0000-0002-6615-4796
Katelyn K JetelinaThe University of Texas Health Science Center at Houston (UTHealth), School of Public Health in Dallas, Dallas, Texas, USA.
Nalini RanjitThe University of Texas Health Science Center at Houston (UTHealth), School of Public Health in Austin, Austin, Texas, USA.
Adriana PerezThe University of Texas Health Science Center at Houston (UTHealth), School of Public Health in Austin, Austin, Texas, USA.ORCID 0000-0002-6859-9916
Cheryl PerryThe University of Texas Health Science Center at Houston (UTHealth), School of Public Health in Austin, Austin, Texas, USA.
Melissa HarrellThe University of Texas Health Science Center at Houston (UTHealth), School of Public Health in Austin, Austin, Texas, USA.

Funding

Training & Education Core p335-350P50CA180906 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI PERRY, CHERYL LEE · 2013 to 2017
$19.7M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI MARK D. HAYWARD · 2017 to 2026
$5.2M
ENDS use trajectories from adolescence through young adulthood: A longitudinal study of risk factors and profilesR01CA239097 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HARRELL, MELISSA BLYTHE · 2019 to 2023
$3.3M
NCI NIH HHS P50 CA180906NCI NIH HHS R01 CA239097NICHD NIH HHS P2C HD042849
6 · The paper itself

Abstract

objectiveTo examine (1) if tobacco retail outlets (TROs) closer to middle and high schools have more tobacco advertisements than TROs farther away and (2) the potential impact of two place-based tobacco control strategies on tobacco advertisements: a simulated ban of TROs (1) within 1000ft of schools and (2) within 500 ft of other TROs.

methodsTROs within half-mile of 53 middle and high schools in the four largest Metropolitan areas in Texas were audited for all tobacco marketing. ArcGIS was used for mapping and grouping TROs by distance from the schools and simulating the ban. Mean differences in the number of tobacco advertisements were examined with t-tests. Percentage reductions in tobacco advertisements were calculated after simulation of both bans, reported by school type and by location, product and flavour.

resultsTROs within 1000 ft of schools had significantly more tobacco advertisements as compared with TROs located within 1000-2000 ft (p=0.03) for all schools combined and middle schools. Simulation of the 1000 ft ban of TROs led to a slightly greater reduction in advertisements (19.4%) as compared with the 500 ft ban of TROs from other TROs (17.9%). The reduction in all advertisement types was greater around middle schools and greatest for e-cigarettes (23.6%).

conclusionStudents can be exposed to a great deal of tobacco advertising in TROs around their schools. The implementation of a 1000 ft ban of TROs, or at minimum a ban on tobacco advertising outside and within these outlets, is one way to prevent or reduce the use of tobacco among adolescents.

Indexed as

Electronic Nicotine Delivery SystemsTobacco IndustryTobacco ProductsAdolescentAdvertisingHumansMarketingSchoolsadvertising and promotionpreventionpriority/special populationspublic policytobacco industry

Identifiers

PMID33310775
PMCPMC8672537

What OpenQuestion holds

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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.