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Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China

Life expectancy (LE) is a comprehensive and important index for measuring population health. Research on LE and its influencing factors is helpful for health improvement. Previous studies have neither considered the spatial stratified heterogeneity of LE nor explored the interactions between its inf...

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Autores principales: Wu, Yafei, Hu, Ke, Han, Yaofeng, Sheng, Qilin, Fang, Ya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036915/
https://www.ncbi.nlm.nih.gov/pubmed/32024116
http://dx.doi.org/10.3390/ijerph17030906
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author Wu, Yafei
Hu, Ke
Han, Yaofeng
Sheng, Qilin
Fang, Ya
author_facet Wu, Yafei
Hu, Ke
Han, Yaofeng
Sheng, Qilin
Fang, Ya
author_sort Wu, Yafei
collection PubMed
description Life expectancy (LE) is a comprehensive and important index for measuring population health. Research on LE and its influencing factors is helpful for health improvement. Previous studies have neither considered the spatial stratified heterogeneity of LE nor explored the interactions between its influencing factors. Our study was based on the latest available LE and social and environmental factors data of 31 provinces in 2010 in China. Descriptive and spatial autocorrelation analyses were performed to explore the spatial characteristics of LE. Furthermore, the Geographical Detector (GeoDetector) technique was used to reveal the impact of social and environmental factors and their interactions on LE as well as their optimal range for the maximum LE level. The results show that there existed obvious spatial stratified heterogeneity of LE, and LE mainly presented two clustering types (high–high and low–low) with positive autocorrelation. The results of GeoDetector showed that the number of college students per 100,000 persons (NOCS) could mainly explained the spatial stratified heterogeneity of LE (Power of Determinant (PD) = 0.89, p < 0.001). With the discretization of social and environmental factors, we found that LE reached the highest level with birth rate, total dependency ratio, number of residents per household and water resource per capita at their minimum range; conversely, LE reached the highest level with consumption level, GDP per capita, number of college students per 100,000 persons, medical care expenditure and urbanization rate at their maximum range. In addition, the interaction of any two factors on LE was stronger than the effect of a single factor. Our study suggests that there existed obvious spatial stratified heterogeneity of LE in China, which could mainly be explained by NOCS.
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spelling pubmed-70369152020-03-11 Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China Wu, Yafei Hu, Ke Han, Yaofeng Sheng, Qilin Fang, Ya Int J Environ Res Public Health Article Life expectancy (LE) is a comprehensive and important index for measuring population health. Research on LE and its influencing factors is helpful for health improvement. Previous studies have neither considered the spatial stratified heterogeneity of LE nor explored the interactions between its influencing factors. Our study was based on the latest available LE and social and environmental factors data of 31 provinces in 2010 in China. Descriptive and spatial autocorrelation analyses were performed to explore the spatial characteristics of LE. Furthermore, the Geographical Detector (GeoDetector) technique was used to reveal the impact of social and environmental factors and their interactions on LE as well as their optimal range for the maximum LE level. The results show that there existed obvious spatial stratified heterogeneity of LE, and LE mainly presented two clustering types (high–high and low–low) with positive autocorrelation. The results of GeoDetector showed that the number of college students per 100,000 persons (NOCS) could mainly explained the spatial stratified heterogeneity of LE (Power of Determinant (PD) = 0.89, p < 0.001). With the discretization of social and environmental factors, we found that LE reached the highest level with birth rate, total dependency ratio, number of residents per household and water resource per capita at their minimum range; conversely, LE reached the highest level with consumption level, GDP per capita, number of college students per 100,000 persons, medical care expenditure and urbanization rate at their maximum range. In addition, the interaction of any two factors on LE was stronger than the effect of a single factor. Our study suggests that there existed obvious spatial stratified heterogeneity of LE in China, which could mainly be explained by NOCS. MDPI 2020-02-01 2020-02 /pmc/articles/PMC7036915/ /pubmed/32024116 http://dx.doi.org/10.3390/ijerph17030906 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Yafei
Hu, Ke
Han, Yaofeng
Sheng, Qilin
Fang, Ya
Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China
title Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China
title_full Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China
title_fullStr Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China
title_full_unstemmed Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China
title_short Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China
title_sort spatial characteristics of life expectancy and geographical detection of its influencing factors in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036915/
https://www.ncbi.nlm.nih.gov/pubmed/32024116
http://dx.doi.org/10.3390/ijerph17030906
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