Evidence map›Paper›PMID 38465634›Full record

ArticleGlobal health action2024

Population mobility : spatial spillover effect of government health expenditure in China.

Simin Wan, Mengying Wang

Abstract read
In one paragraph

Article in Global health action, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

2 authors.

Simin WanSchool of Public Finance & Public Administration, Jiangxi University of Finance and Economics, Nanchang, China.
Mengying WangSchool of Public Finance & Public Administration, Jiangxi University of Finance and Economics, Nanchang, China.ORCID 0000-0002-7873-1781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSince the 20th century, pursuing Universal Health Coverage (UHC) has emerged as an important developmental objective in numerous countries and across the global health community. With the intricate ramifications of population mobility (PM), the government faces a mounting imperative to judiciously deploy health expenditure to realise UHC effectively.

objectiveThis study aimed to construct a comprehensive UHC index for China, assess the spatial effects of Government Health Expenditure (GHE) on UHC, and explore the moderating effects of PM on this association.

methodA Dynamic Spatial Durbin Model (DSDM) was employed to investigate the influence of the GHE on UHC. Therefore, we tested the moderating effect of PM.

resultsIn the short-term, the GHE negatively impacted local UHC. However, it enhanced the UHC in neighbouring regions. Over the long term, GHE improved local UHC but decreased UHC in neighbouring regions. In the short-term, when the PM exceeded 1.42, the GHE increased the local UHC. Over the long term, when the PM exceeded 1.107, the GHE impeded local UHC. If the PM exceeded 0.91 in the long term, the GHE promoted UHC in neighbouring regions. The results of this study offer a partial explanation of GHE decisions and behaviours.

conclusionsTo enhance UHC, a viable strategy involves augmenting vertical transfer payments from the central government to local governments. Local governments should institute healthcare systems tailored to the urban scale and developmental stages, with due consideration for PM. Optimising the information disclosure mechanism is also a worthwhile endeavour.

Indexed as

Delivery of Health CareHealth ExpendituresChinaGlobal HealthGovernmentHumansdynamic spatial durbin modelGovernment health expenditure (GHE)population mobilityspatial spillover effectuniversal health coverage (UHC)

Identifiers

PMID38465634
PMCPMC10930106

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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.