Evidence map›Paper›PMID 40959203›Full record

ArticleInternational journal of geographical information science : IJGIS2025

Deconstructing rurality to better "place" health data.

Daniel Beene, Yan Lin, Joseph H Hoover, Xun Shi

Abstract read
In one paragraph

Article in International journal of geographical information science : IJGIS, 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

4 authors.

Daniel BeeneDepartment of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA.ORCID 0000-0003-1286-5514
Yan LinDepartment of Geography and the Social Science Research Institute, The Pennsylvania State University, State College, USA.ORCID 0000-0003-2266-0854
Joseph H HooverDepartment of Environmental Science, University of Arizona, Tucson, USA.ORCID 0000-0003-2566-8042
Xun ShiDepartment of Geography, Dartmouth College, Hanover, USA.

Funding

SOUTHWEST ENVIRONMENTAL HEALTH SCIENCES CENTERP30ES006694 · NIEHS · UNIVERSITY OF ARIZONA · PI George S Watts · 1994 to 2026
$36.7M
Understanding Risk Gradients from Environment on Native American Child Health Trajectories: Toxicants, Immunomodulation, Metabolic syndromes, & Metals ExposureUH3OD023344 · OD · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Johnnye L Lewis, Debra MacKenzie · 2019 to 2026
$21.1M
UNM Metals Exposure and Toxicity Assessment on tribal Lands in the Southwest (METALS) Superfund Research ProgramP42ES025589 · NIEHS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI HUDSON, LAURIE G · 2017 to 2025
$16.4M
Understanding Risk Gradients from Environment on Native American Child Health Trajectories: Toxicants, Immunomodulation, Metabolic syndromes, & Metals ExposureUG3OD023344 · OD · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI LEWIS, JOHNNYE L, MACKENZIE, DEBRA · 2016 to 2024
$14.1M
Role of open dumping and open burning of solid waste in the generation of microplastics and products of incomplete combustion on tribal landsP50MD015706 · NIMHD · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI MACKENZIE, DEBRA · 2020 to 2024
$6.8M
Pilot Project CoreP30ES032755 · NIEHS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI FENG, CHANGJIAN (JIM) · 2022 to 2025
$5.2M
NIEHS NIH HHS P30 ES006694NIEHS NIH HHS P30 ES032755NIEHS NIH HHS P42 ES025589NIH HHS UG3 OD023344NIH HHS UH3 OD023344NIMHD NIH HHS P50 MD015706
6 · The paper itself

Abstract

Rural-urban classification schemes are frequently used in ecological studies of population health. However, the algorithms used to produce these classifications as well as their underlying assumptions may not match their intended use in health research. Here, we focus on the spatial distribution of features of the physical environment that are related to health - such as healthcare - to examine the extent to which eight classification schemes capture the heterogeneous context of rural places. We further explore how well rural-urban classifications distinguish between different types of rural places by comparing rural Tribal reservations with other rural areas in the American southwest. Because health services and infrastructure are often distributed through state and federal programs to underserved populations in rural areas, this approach speaks to the broader political implications in how rural communities are defined and represented. Results indicate that rural-urban classifications do not adequately reflect heterogeneous contexts within and across rural places. We advocate for more appropriate population health models that explain contextual differences in the relationship between health and place.

Indexed as

GeoHealthGISrural healthruralityrural-urban classificationssocial determinants of health

Identifiers

PMID40959203
PMCPMC12435940

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.