Evidence map›Paper›PMID 41918090›Full record

ArticleBMC public health2026

Beyond green: how city greenspace shapes health outcomes in China.

Linjiang Wei, Jing Lin, Ziling Xie, Yihang Chu, Shujun Chai, Ying Han

Abstract read
In one paragraph

Article in BMC public 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.

Linjiang Wei *State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, 361102, China.
Jing Lin *School of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China.
Ziling Xie *School of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China.
Yihang Chu *Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China. yihang.chu@polyu.edu.hk.
Shujun Chai *School of Population and Health, Renmin University of China, 59 Zhongguancun Ave., Haidian District, Beijing, 100872, China. csj3210@163.com.
Ying Han *School of Nursing, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China. Hannah753@wmu.edu.cn.ORCID http://orcid.org/0000-0002-4291-0219

Funding

Basic Scientific Research Foundation of Wenzhou Medical University KYYW202338Talent Research Startup Project of Wenzhou Medical University SKODJ2309
6 · The paper itself

Abstract

backgroundUrban greenspace is increasingly acknowledged as a vital component of sustainable urban development. While being exposed to greenspace is associated with a lower risk of chronic diseases, the specific health effects of different types and functions of greenspace remain unclear. As a distinct category with clear boundaries, high accessibility, and multiple functions, urban parks may play a particularly important role in promoting health, yet research focusing specifically on urban parks remains limited, and the underlying mechanisms are still unclear.

methodsThe data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), the China Longitudinal Aging Social Study (CLASS), and the China Urban Construction Statistical Yearbook for 2016, 2018, and 2020. Spatial autocorrelation analysis was applied to identify clustering patterns and hot/cold spots of chronic disease prevalence and greenspace resources (including park area and green coverage). A Multiscale Geographically and Temporally Weighted Regression (MGTWR) model was applied to quantify the influence of green coverage and park area on chronic disease prevalence, supported by geographic information system (GIS) mapping to visualize spatial distributions.

resultsChronic disease prevalence followed an inverted U-shaped trend from 2016 to 2020, peaking in 2018. High-high clustering and hot spot shifted cyclically from the southwest to the northeast and back. Areas with high park greenspace remained consistently concentrated in the Bohai Rim and Pearl River Delta metropolitan regions, while those with high green coverage transitioned from the Yangtze River Delta and Pearl River Delta to the Middle Yangtze River urban agglomeration and finally to the southwestern ecological zone. The MGTWR model indicated a marginal effect: in eastern regions with ample green infrastructure, expanding greenspace yields limited returns, whereas in the less-green western regions, further development produces more significant health improvements.

conclusionsIt is recommended to adopt tailored chronic disease prevention strategies, focusing on high-risk areas. Urban planning should prioritize equitable access to greenspace rather than merely expanding their area. Long-term environmental health monitoring is also advised to better capture the lagged effects of ecological improvements. This research provides evidence for transforming green infrastructure into health assets, supporting equitable urban planning to reduce the burden of chronic diseases.

Indexed as

Parks, RecreationalChinaChronic DiseaseCitiesGeographic Information SystemsHumansLongitudinal StudiesPrevalenceChronic diseaseCity greenspaceMultiscale spatiotemporal analysisPark green area

Identifiers

PMID41918090
PMCPMC13169980

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.