Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/8/3/231 |
| _version_ | 1797561392057810944 |
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| author | Chenyu Lu Shulei Jin Xianglong Tang Chengpeng Lu Hengji Li Jiaxing Pang |
| author_facet | Chenyu Lu Shulei Jin Xianglong Tang Chengpeng Lu Hengji Li Jiaxing Pang |
| author_sort | Chenyu Lu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T18:13:17Z |
| format | Article |
| id | doaj.art-ae793e886f7048d99e1b2796bd661658 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-10T18:13:17Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-ae793e886f7048d99e1b2796bd6616582023-11-20T07:56:14ZengMDPI AGHealthcare2227-90322020-07-018323110.3390/healthcare8030231Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing FactorsChenyu Lu0Shulei Jin1Xianglong Tang2Chengpeng Lu3Hengji Li4Jiaxing Pang5College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, ChinaSchool of Architecture & Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, ChinaInstitute for County Economy Developments & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, ChinaInformation Center for Global Change Studies, Lanzhou Information Center of Chinese Academy of Sciences, Lanzhou 730000, ChinaCollege of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, ChinaHealth 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.https://www.mdpi.com/2227-9032/8/3/231health levelscomprehensive measurementinfluencing factorsChinaGIS |
| spellingShingle | Chenyu Lu Shulei Jin Xianglong Tang Chengpeng Lu Hengji Li Jiaxing Pang Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors Healthcare health levels comprehensive measurement influencing factors China GIS |
| title | Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors |
| title_full | Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors |
| title_fullStr | Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors |
| title_full_unstemmed | Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors |
| title_short | Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors |
| title_sort | spatio temporal comprehensive measurements of chinese citizens health levels and associated influencing factors |
| topic | health levels comprehensive measurement influencing factors China GIS |
| url | https://www.mdpi.com/2227-9032/8/3/231 |
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