Evidence map›Paper›PMID 41742136›Full record

ArticleBMC health services research2026

Bridging the healthcare gap for aging populations: rethinking spatial equity in high-density cities based on the SDMI index.

Wen Zhong, Lei Wang, Hao Long

Abstract read
In one paragraph

Article in BMC health services research, 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
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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

3 authors.

Wen ZhongSchool of Architecture and Urban Planning, Chongqing University, Chongqing, 400044, China.
Lei WangCenter Technology and Society (ZTG), Technical University of Berlin, 10623, Berlin, Germany.
Hao LongSchool of Architecture and Urban Planning, Chongqing University, Chongqing, 400044, China. longhao@cqu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Against the backdrop of global population aging and adjustments in health policies, the fair and efficient allocation of urban health resources for older adults has become a key issue in urban planning and resource management. From a supply-demand matching perspective, this study proposes a classification method for urban health resources for older adults, categorizing them into three types: uniform distribution, hierarchical, and independent. A classification and evaluation system is constructed based on four core dimensions: accessibility, service load, selectivity, and suitability. This study highlights the importance of spatial heterogeneity analysis and multi-source data integration. By combining GIS spatial analysis, network modeling, and the Analytic Hierarchy Process, a Spatial Demand-Supply Matching Index (SDMI) calculation model is developed. Through weighted evaluation, the model quantifies the degree of matching between supply and demand, assessing the balance of elderly health resource distribution across different regions. Using Chongqing, a typical high-density megacity, as a case study, the proposed evaluation framework effectively identifies areas with uneven resource distribution, excessive burden, or limited accessibility, providing data-driven optimization strategies. The results indicate that this method can systematically assess resource accessibility, supply-demand matching, and the rationality of spatial distribution across urban areas, thereby supporting improvements in equity and accessibility of healthcare resources allocation. This approach can be adapted to other high-density cities with context-specific calibration of indicators and weights, contributing to more efficient health resource provision in aging societies and the sustainable development of urban health service systems.

Indexed as

Healthcare DisparitiesHealth Services AccessibilityHealth Services for the AgedAgedChinaCitiesCity PlanningGeographic Information SystemsHumansSpatial AnalysisClassification assessmentData-drivenOlder adultsSDMISupply-demand matching

Identifiers

PMID41742136
PMCPMC13005325

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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.