Evidence map›Paper›PMID 32722407›Full record

ArticleHealthcare (Basel, Switzerland)2020

Spatio-Temporal Comprehensive Measurements of Chinese Citizens' Health Levels and Associated Influencing Factors.

Chenyu Lu, Shulei Jin, Xianglong Tang, Chengpeng Lu, Hengji Li, Jiaxing Pang

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Chenyu LuCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China.
Shulei JinCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China.
Xianglong TangSchool of Architecture & Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, China.
Chengpeng LuInstitute for County Economy Developments & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China.ORCID 0000-0002-2035-2295
Hengji LiInformation Center for Global Change Studies, Lanzhou Information Center of Chinese Academy of Sciences, Lanzhou 730000, China.
Jiaxing PangCollege of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China.

Funding

National Natural Science Foundation of China 41561110; 51568033; 41701142Science and Research Program in colleges and universities of Gansu Province 2018F-05
6 · The paper itself

Abstract

Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens' health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens' health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China's various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens' health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast-southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens' health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens' health status. The Engel coefficient, urban-rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens' health levels, these three factors have played important roles in hindering the improvements of citizen health.

Indexed as

Chinacomprehensive measurementGIShealth levelsinfluencing factors

Identifiers

PMID32722407
PMCPMC7551958

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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.