Evidence map›Paper›PMID 42875776›Full record

ArticleBMC health services research2026

Mismatch between urban eco-sanitation improvement and health service supply capacity: evidence from Chinese city panel data and interpretable machine learning.

Zhen Peng, Lin Wang

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. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Zhen PengSchool of Architecture and Urban Planning, Qingdao University of Technology, Qingdao, 266033, China. pengzhen@qut.edu.cn.
Lin WangSchool of Architecture and Urban Planning, Qingdao University of Technology, Qingdao, 266033, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth service supply capacity depends not only on medical resource stocks but also on urban eco-sanitation conditions and resource-allocation mechanisms. Existing studies focus mainly on environmental exposure and health outcomes, with limited attention to whether eco-sanitation improvements can be converted into health service supply capacity.

methodsThis study constructed a panel of Chinese prefecture-level and above cities for 2002-2024, using the health service supply capacity index as the dependent variable and the eco-sanitation environment index as the core explanatory variable. Two-way fixed effects models, dimension-specific analysis, mechanism tests, heterogeneity analysis, robustness checks, and interpretable machine learning identified mismatch mechanisms and boundary conditions. The mechanism analysis was extended to two- and three-year ESE lags and one- and two-year lagged investment variables. Carbon-emission comparability was reassessed on exact CEADs-matched samples for 2002-2019. Hu Huanyong line subgroup models were additionally estimated with city and province-year fixed effects.

resultsThe eco-sanitation environment, green infrastructure, and municipal sanitation facilities improved continuously, whereas health service supply capacity increased more slowly. The baseline model does not support a stable positive conversion from eco-sanitation improvement to stronger supply capacity. Dimension-specific results reveal differentiated roles. The positive PPI coefficient must not be read as a pollution benefit; it is consistent with a demand-induced or compensatory resource-allocation response. Neither two- to three-year ESE lags nor one- to two-year lagged investment variables produced a stable urban construction investment transmission chain. The positive CEADs interaction was confirmed only within the 2002-2019 matched sample and therefore represents pre-pandemic evidence. The southeastern Hu-line coefficient attenuated and lost conventional significance after province-year policy shocks were absorbed. Machine learning indicates the relationship is shaped by development stage, population size, fiscal capacity, and nonlinear boundaries.

conclusionsEco-sanitation improvement is not a sufficient condition for enhancing health service supply capacity. Healthy city development should integrate eco-sanitation governance, infrastructure investment, workforce allocation, and fiscal arrangements into a unified governance framework. Because HSC is a supply-side proxy based on resource counts, these implications concern resource availability and network density rather than quality of care, realized utilization, accessibility, or overall health-system performance.

Indexed as

Health ServicesMachine LearningSanitationChinaCitiesHumansChinese citiesHealthcare resource allocationHealth service governanceHealth service supply capacityInterpretable machine learningUrban eco-sanitation environment

Identifiers

PMID42875776
PMCPMC13670610

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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.