Evidence map›Paper›PMID 40890684›Full record

ArticleBMC health services research2025

Study on regional disparities and influencing factors of public health service supply in China from the perspective of fairness.

Shengjiao Zhu, Jinsi Liu, Zhihua Wang, Shixiang Chen

Abstract read
In one paragraph

Article in BMC health services research, 2025. 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.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

4 authors.

Shengjiao Zhu *School of Political Science and Public Administration, Wuhan University, Wuhan, China.
Jinsi Liu *School of Political Science and Public Administration, Wuhan University, Wuhan, China. liujinsi1798@whu.edu.cn.
Zhihua Wang *College of Public Administration, South-Central Minzu University, Wuhan, China.
Shixiang ChenSchool of Political Science and Public Administration, Wuhan University, Wuhan, China. chensx@whu.edu.cn.

Funding

"Research on the Optimization of the Management Standardization System of the Hubei Provincial Government" commissioned by the Standardization Department of Hubei Provincial Market Supervision Bureau Project No. 1203/250000471the Hubei University Provincial Teaching Research Project "Innovation Research on the Compound Talent Training Model of China's Administrative Management Disciplines under the Threshold of New liberal arts construction" Project No.2022014
6 · The paper itself

Abstract

backgroundThe public health service supply level is an essential factor affecting public health, and fairness is vital in distributing public health services. The spatiotemporal differences in public health services have attracted academic attention. However, few studies have systematically analyzed regional disparities and their influencing factors from a fair perspective. Therefore, this paper aims to explore the spatiotemporal distribution of public health service supply in China and its influencing factors from the standpoint of fairness.

methodsFirst, based on the panel data of 31 provinces in China from 2010 to 2023, this paper constructs an objective evaluation index system for the supply level of public health services. Secondly, through the empirical analysis of the Dagum Gini coefficient, the temporal and spatial differences in the supply of public health services are explored. Regional disparities are analyzed from the perspective of fairness. Finally, the Tobit model is used to examine the impact of factors such as the proportion of the elderly population, the level of economic development, and demographic factors on the fairness of public health service supply.

resultsThe study found that China's public health service supply has improved significantly since the new medical reform. However, there are still large differences between different regions, and the problem of unbalanced development within the region is prominent. The eastern coastal areas show a "polarization" trend, with hot spots and weak areas in public health service supply coexisting. Simultaneously, Tobit regression confirms that the deepening of aging and improving economic development significantly drive the supply of public health services.

conclusionsThe government should reasonably allocate public health resources according to the actual conditions of each region to achieve a "trickle-down effect." Especially in underdeveloped areas, the government should achieve fairness in service supply through precise policies. Concurrently, a cross-regional counterpart support mechanism should be established to promote soft power support, such as talent and technology. Medical and health services should be provided to the elderly and vulnerable groups through medical care and health industry models. Finally, relying on "Internet + medical health" to break down resource barriers and build a digital service platform covering the entire urban and rural areas to achieve fair distribution of public health resources and a "diffusion effect".

Indexed as

Healthcare DisparitiesSocial JusticeChinaHumansPublic HealthHealth equityInfluencing factorsPublic health servicesRegional distributionSupply level

Identifiers

PMID40890684
PMCPMC12403309

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.