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

机译:中国影响因素的预期寿命及地理检测空间特征

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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.
机译:预期寿命(LE)是衡量人口健康的全面和重要指标。对LE及其影响因素的研究有助于健康改善。以前的研究既没有考虑LE的空间分层异质性,也没有探索其影响因素之间的相互作用。我们的研究基于2010年中国2010年31个省份的最新可用的LE和社会和环境因素数据。进行描述性和空间自相关分析以探索LE的空间特征。此外,地理探测器(地理传染料)技术用于揭示社会和环境因素的影响及其对LE的相互作用以及最大LE水平的最佳范围。结果表明,LE的空间分层异质性存在明显的空间分层异质性,LE主要呈现出两种聚类类型(高低低),阳性自相关。地理委员的结果表明,每10万人(NOC)的大学生数量主要解释了LE的空间分层异质性(决定性的功率(Pd)= 0.89,P <0.001)。随着社会和环境因素的离散化,我们发现,LE达到了出生率,总抚养率,每家家庭居民数量的最高级别,人均居民的最小范围;相反,LE达到了消费水平,人均GDP,每10万人的大学生数量,医疗支出和最大范围的城市化率。此外,对le上任何两个因素的相互作用比单一因素的效果强。我们的研究表明,中国的LE存在明显的空间分层异质性,主要可以通过NOCS解释。

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