ArticlePreventive medicine2020
Do mobile units contribute to spatial accessibility to mammography for uninsured women?
Article in Preventive medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Mobile Cancer Screening Programs: A Systematic Review of Implementation Challenges and Population Access.International journal of environmental research and public health · 2026Pooled it
- Role of Community-Clinical Partnerships to Promote Cancer Screening: Lessons Learned From the National Breast and Cervical Cancer Early Detection Program.Health promotion practice · 2026Article
- From Awareness to Action: A Review of Efforts to Reduce Disparities in Breast Cancer Screening.Cureus · 2023Review
- Understanding geographic and racial/ethnic disparities in mortality from four major cancers in the state of Georgia: a spatial epidemiologic analysis, 1999-2019.Scientific reports · 2022Article
- Identifying key barriers to effective breast cancer control in rural settings.Preventive medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Limited spatial accessibility to mammography, and socioeconomic barriers (e.g., being uninsured), may contribute to rural disparities in breast cancer screening. Although mobile mammography may contribute to population-level access, few studies have investigated this relationship. We measured mammography access for uninsured women using the variable two-step floating catchment area (V2SFCA) method, which estimates access at the local level using estimated potential supply and demand. Specifically, we measured supply with mammography machine certifications in 2014 from FDA and brick-and-mortar and mobile facility data from the community-based Breast Screening and Patient Navigation (BSPAN) program. We measured potential demand using Census tract-level estimates of female residents aged 45-74 from 5-year 2012-2016 American Community Survey data. Using the sign test, we compared mammography access estimates based on 3 facility groupings: FDA-certified, program brick-and-mortar only, and brick-and-mortar plus mobile. Using all mammography facilities, accessibility was high in urban Dallas-Ft. Worth, low for the ring of adjacent counties, and high for rural counties outlying this ring. Brick-and-mortar-based estimates were lower for the outlying ring, and mobile-unit contribution to access was observed more in urban tracts. Weak mobile-unit contribution across the study area may indicate suboptimal dispatch of mobile units to locations. Geospatial methods could identify the optimal locations for mobile units, given existing brick-and-mortar facilities, to increase access for underserved areas.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.