Evidence map›Paper›PMID 35005480›Full record

ArticleOhio journal of public health2019

The Relationship between Tobacco Retailer Density and Neighborhood Demographics in Ohio.

Chiche Adibe, Peter F Craigmile, Nathaniel Onnen, Elli Schwartz, Megan E Roberts

Abstract read
In one paragraph

Article in Ohio journal of public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
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  4. Tobacco retailer density and rurality across four US states: California, Connecticut, North Carolina, and Ohio.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2025
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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

5 authors.

Chiche AdibeCollege of Liberal Arts and Social Sciences, DePaul University, Chicago, IL, USA.
Peter F CraigmileDepartment of Statistics, The Ohio State University, Columbus, OH, USA.
Nathaniel OnnenDepartment of Statistics, The Ohio State University, Columbus, OH, USA.
Elli SchwartzCollege of Public Health, The Ohio State University, Columbus, OH, USA.
Megan E RobertsCollege of Public Health, The Ohio State University, Columbus, OH, USA.

Funding

Evaluating how licensing-law strategies will change neighborhood disparities in tobacco retailer densityR21CA212308 · NCI · OHIO STATE UNIVERSITY · PI ROBERTS, MEGAN ELEANOR · 2017 to 2018
$323k
NCI NIH HHS R21 CA212308
6 · The paper itself

Abstract

introductionStudies from various parts of the country suggest that tobacco-related health disparities are exacerbated by disparities in the distribution of tobacco retailers (convenience stores, tobacco shops, etc.). The purpose of the present study was to use advanced spatial modeling techniques for count data to estimate current disparities in tobacco retailer density in Ohio.

methodsWe identified and geocoded 11,392 tobacco retailers in Ohio. Next, we obtained census tract-level information on race/ethnicity, poverty, and age and obtained county-level information on whether an area was Urban, Suburban, or Rural. Finally, we used negative binomial generalized linear models, adapted for residual spatial dependence, to determine the association between per capita tobacco retailer density and demographic characteristics-summarized by adjusted rate ratios.

resultsThere were more (from 1.4-1.9 times as many) retailers per capita in high-poverty, vs. low-poverty tracts. Poverty also interacted with age: the association between high poverty and high retailer density was stronger for tracts with a low youth population. Density was also greater in tracts with a high (vs. low) prevalence of African Americans (1.1 times as many) and Hispanics (1.2 times as many). Finally, density was generally greater in rural (vs. suburban or urban) tracts, although the effect was modified by a three-way interaction: density was particularly high for rural tracts that also had both a high prevalence of poverty and a low youth population. DISCUSSION: Overall, our findings indicate that Ohio's vulnerable populations are exposed to a greater per capita density of tobacco retailers. PUBLIC HEALTH IMPLICATIONS: There is a need for state and local-level tobacco control policies that will improve equity and reduce health disparities.

Indexed as

disparitiesspatial modelingTobacco retailer density

Identifiers

PMID35005480
PMCPMC8734554

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.