Evidence map›Paper›PMID 42734782›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2026

Spatial Accessibility and Supply-Demand Mismatch of Primary Healthcare Facilities in the Main Urban Area of Guangzhou.

Xiaoya Chen, Qin Ye, Jianghong Zhu

Abstract read
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In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 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

3 authors.

Xiaoya ChenSchool of Public Administration, China University of Geosciences, Wuhan, Hubei, China.
Qin YeQinghai Provincial Institute of Territorial Spatial Planning, Xining, Qinghai, China.
Jianghong ZhuSchool of Public Administration, China University of Geosciences, Wuhan, Hubei, China. zhujh@cug.edu.cn.ORCID http://orcid.org/0000-0001-8443-1147

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Taking the main urban area of Guangzhou as a case study, this research employs the Gaussian two-step floating catchment area (Ga2SFCA) method to evaluate the spatial accessibility of primary healthcare (PHC) facilities under four travel modes-walking, e-bike, driving, and transit. By integrating spatial analysis with socioeconomic characteristics, the study reveals the spatial patterns and disparities of accessibility. The results show significant differences in accessibility among socioeconomic groups, with e-bike travel substantially improving overall accessibility. By further constructing a Demand Index for Vulnerable Groups (DIVG) and performing cluster analysis, the study identifies a pronounced spatial mismatch between PHC supply and demand across different areas. Some peripheral sub-districts exhibit relatively high accessibility but limited service demand, whereas the core urban area experiences a decline in relative accessibility due to concentrated population and healthcare needs. Meanwhile, the dynamics of the urban housing market exacerbate spatial injustice, resulting in the coexistence of relative shortages in high-demand areas and surpluses in low-demand areas. The findings suggest that improving non-motorized transport systems and optimizing spatial layouts guided by the needs of vulnerable populations are crucial pathways toward achieving spatial justice within the "15-minute neighborhood" and enhancing health equity in Guangzhou.

Indexed as

Gaussian two-step floating catchment area (Ga2SFCA)Primary healthcare facilitiesSpatial accessibilitySpatial justiceSupply–demand mismatch

Identifiers

What OpenQuestion holds

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Registered trials

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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.