Evidence map›Paper›PMID 37239745›Full record

ArticleHealthcare (Basel, Switzerland)2023

Regional Differences, Dynamic Evolution and Convergence of Public Health Level in China.

Jixia Li, Mengzhi Xu, Tengfei Liu, Can Zhang

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

4 authors.

Jixia LiSchool of Government, Beijing Normal University, Beijing 100875, China.ORCID 0009-0001-4435-7613
Mengzhi XuSchool of Government, Beijing Normal University, Beijing 100875, China.ORCID 0000-0002-0400-3191
Tengfei LiuSchool of Business Administration, The Open University of China, Beijing 100039, China.ORCID 0000-0002-8879-1366
Can ZhangSchool of Government, Beijing Normal University, Beijing 100875, China.ORCID 0000-0002-1775-6432

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People's health is a necessary condition for the country's prosperity. Under the background of the COVID-19 pandemic and frequent natural disasters, exploring the spatial and temporal distribution, regional differences and convergence of China's provincial public health level is of great significance to promoting the coordinated development of China's regional public health and achieving the strategic goal of a "healthy China". Based on China's provincial panel data from 2009 to 2020, this paper constructs an evaluation index system for China's public health level from five dimensions: the popularization of a healthy life, optimization of health services, improvement of health insurance, construction of a healthy environment, and development of a health industry. In this paper, the entropy method, Dagum Gini coefficient, Kernel density function and spatial econometric model are used to analyze the spatiotemporal distribution, regional differences, dynamic evolution and convergence of China's public health level since the new medical reform. The study found that, first, China's public health level is generally low, structural contradictions are prominent and the construction of a healthy environment has become a shortcoming hindering the improvement of China's public health level since the new medical reform. The public health level of the four major regions showed a spatial distribution pattern of "high in the eastern, low in the northeastern, central and western" areas. Second, the overall Gini coefficient of China's public health level showed a "V-shaped" trend of first decreasing and then rising, but the overall decrease was greater than the increase, among which the regional difference was the main source of regional differences in China's public health level, but its contribution rate showed a downward trend. Third, except for the basic maintenance of a healthy environment, the Kernel density curves of China's public health level and its sub-dimensions have shifted to the right to a certain extent, and there is no polarization phenomenon. Finally, the level of public health in China has a significant spatial correlation. Except for the northeast region, the growth rate of low-level public health provinces in China and the other three major regions is higher than that of high-level public health provinces, showing a certain convergence trend. In addition, the impact of economic development, financial pressure, and urbanization on the convergence of public health levels in the four major regions is significantly heterogeneous.

Indexed as

dynamic evolutionpublic healthregional differencesspatial convergence

Identifiers

PMID37239745
PMCPMC10218456

What OpenQuestion holds

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LicenceCC BY
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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.