Evidence map›Paper›PMID 40788910›Full record

ArticlePloS one2025

Distribution of pharmacy deserts and its association with digital divide and residential redlining across the United States.

Giovanni Catalano, Selamawit Woldesenbet, Timothy M Pawlik

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Giovanni CatalanoDepartment of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, Ohio, United States of America.ORCID https://orcid.org/0000-0003-1440-7031
Selamawit WoldesenbetDepartment of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, Ohio, United States of America.ORCID https://orcid.org/0000-0002-5023-3561
Timothy M PawlikDepartment of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, Ohio, United States of America.ORCID https://orcid.org/0000-0002-7994-9870

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent pharmacy closures across the US has increased the number of communities characterized as "pharmacy deserts." Residential segregation and structural economic disinvestment including the digital divide may exacerbate inequities related to pharmacy access.

methodsIn this cross-sectional study, pharmacy deserts were defined at the census tract level and their distribution was analyzed relative to the digital divide index (DDI) and residential redlining using multivariate logistic regression.

resultsOverall, 3,105 (3.72%) census tracts were classified as pharmacy deserts comprising more than 10 million inhabitants (n = 10,215,249). Pharmacy deserts were more often Black (n = 398, 13% vs. n = 6142, 7.6%), Hispanic (n = 597, 19.0% vs. 7662, 9.5%), or American Indian and Alaska Native (n = 82,14.0% vs. n = 113, 0.1%) segregated communities (all p < 0.001). Census tracts with a high DDI (OR 6.94, 95%CI 5.82-8.32; p < 0.001; E-value = 4.70) had a higher likelihood of being a pharmacy desert versus low DDI areas. Furthermore, census tracts experiencing high residential redlining had a twofold increased risk of being pharmacy deserts (OR 2.18, 95%CI 1.90-2.50; p < 0.001; E-value = 2.31).

conclusionsUnderstanding how socioeconomic and infrastructure factors influence access to pharmacies is crucial to reduce health inequities. Efforts should be made to ensure equitable access to pharmacy services, especially for underserved populations in both rural and urban settings.

Indexed as

Digital DivideHealth Services AccessibilityPharmaciesCross-Sectional StudiesHumansResidence CharacteristicsUnited States

Identifiers

PMID40788910
PMCPMC12338793

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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.