Evidence map›Paper›PMID 42012222›Full record

ArticleGeospatial health2026

Optimizing mobile mammography deployment in Oklahoma 2024: a two-step floating catchment area approach.

Janis E Campbell, Amanda Janitz, Ayesha B Sambo, Nubwa St James, Stephanie F Pharr, Mark P Doescher

Abstract read
In one paragraph

Article in Geospatial health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Janis E CampbellDepartment of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK; Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK.
Amanda Janitzepartment of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK.
Ayesha B SamboStephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK.
Nubwa St JamesDepartment of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK.
Stephanie F PharrStephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK.
Mark P DoescherStephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK.

Funding

Tracking and Evaluation CoreU54GM104938 · NIGMS · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI Janis E Campbell · 2013 to 2026
$68.2M
Tissue Pathology Shared ResourceP30CA225520 · NCI · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI ROBERT S. MANNEL · 2018 to 2026
$27.1M
NCI NIH HHS P30 CA225520NIGMS NIH HHS U54 GM104938
6 · The paper itself

Abstract

This study assessed spatial accessibility to fixed mammography centres across Oklahoma State, USA using the Two-Step Floating Catchment Area (2SFCA) and the Enhanced Two-Step Floating Catchment Area (E2SFCA) methods to identify areas with limited or no access. For this analysis, we used data from the mammography facilities database of the US Food and Drug Administration verified by direct contact with the facility and the U.S. Census block group population and demographics for women aged 40 years and older. Analyses were stratified by urban areas; large rural areas; and small rural areas. Accessibility scores were calculated using the 2SFCA method with 30-minute drive times and the E2SFCA method with drive times of 10, 20 and 30 minutes weighted by distance decay. Block groups were categorized into quartiles based on accessibility scores. Among 940,994 eligible women, 10% lived in areas with no access. Small rural regions faced the greatest barriers. Spatial disparities were linked to racial and socioeconomic differences: non-Hispanic American Indian/Alaska Native and non-Hispanic White populations were more likely to reside in noaccess zones, while Black and Hispanic populations clustered in high-access urban areas. Spatial analysis reveals significant rural disparities in mammography access. Mobile machines should prioritize underserved rural regions to improve equity.

Indexed as

Catchment Area, HealthHealth Services AccessibilityMammographyMobile Health UnitsAgedFemaleHumansOklahomaRural PopulationHealth DisparitiesMammographyRuralScreeningUrban

Identifiers

PMID42012222
PMCPMC13255058

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.