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Exploring the spatial-temporal distribution and evolution of population aging and social-economic indicators in China

机译:探索中国人口老龄化和社会经济指标的空间分布及演变

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China is one of the world’s fastest-aging countries. Population aging and social-economic development show close relations. This study aims to illustrate the spatial-temporal distribution and movement of gravity centers of population aging and social-economic factors and thier spatial interaction?across the provinces in China. Factors of elderly population rate (EPR), elderly dependency ratio (EDR), per capita gross regional product (GRPpc), and urban population rate (UPR) were collected. Distribution patterns were detected by using global spatial autocorrelation, Kernel density estimation, and coefficient of variation. Further, Arc GIS software was used to find the gravity centers and their movement trends yearly from 2002 to 2018. The spatial interaction between the variables was investigated based on bivariate spatial autocorrelation analysis. The results showed a larger variety of global spatial autocorrelation indexed by Moran’s I and stable trends of dispersion degree without obvious convergence in EPR and EDR. Furthermore, the gravity centers of the proportion of EPR and EDR moved northeastward. In contrast, the economic and urbanization factors showed a southwestward movement, which exhibited an reverse trend compared to population aging indicators. Moreover, the movement rates of EPR and EDR (15.12 and 18.75?km/year, respectively) were higher than that of GRPpc (13.79?km/year) and UPR (6.89?km/year) annually during the study period. Further, the bivariate spatial autocorrelation variation is in line with the movement trends of gravity centers which showed a polarization trend of population aging and social-economic factors that the difference between southwest and northeast directions and exhibited a tendency to expand in China. In sum, our findings revealed the difference in spatio-temporal distribution and variation between population aging and social-economic factors in China. It further indicates that the opposite movements of gravity centers and the change of the BiLISA in space which may result in the increase of the economic burden of the elderly care in northern China. Hence, future?development policy?should focus on the social-economic growth and distribution of old-aged supporting resources, especially in northern China.
机译:中国是世界上最快的国家之一。人口老龄化与社会经济发展呈现密切关系。本研究旨在说明人口老龄化和社会经济因素和地区空间互动的空间 - 时间分布和流动?在中国的省份。收集了老年人人口率(EPR),老年人抚养比(EDR),人均区域产品(GRPPC)和城市人口率(UPR)的因素。通过使用全局空间自相关,内核密度估计和变异系数来检测分布模式。此外,ARC GIS软件已从2002年至2018年开始寻找重力中心及其运动趋势。根据双变空间自相关分析研究了变量之间的空间相互作用。结果表明,莫兰的I指数较大的全球空间自相关,并且在epr和EDR中没有明显会聚的稳定性分散程度的稳定趋势。此外,EPR和EDR比例的重力中心向东移动。相比之下,经济和城市化因素显示出一种西南运动,与人口老龄化指标相比表现出逆转趋势。此外,EPR和EDR的运动率(15.12和18.75 km /年)高于GRPPC(13.79 km /年)和在研究期间每年每年的UPR(6.89克/年)。此外,双变型空间自相关变化与重力中心的运动趋势符合,这表明了人口老龄化和社会经济因素的偏振趋势,西南和东北方向之间的差异并在中国扩展趋势。总而言之,我们的研究结果揭示了中国人口老龄化与中国人口老龄化与社会经济因素的变化差异。它进一步表明重力中心的相反运动和比利萨斯在太空中的变化可能导致中国北方老年人护理经济负担的增加。因此,未来?发展政策?应注重社会经济增长和古老的支持资源的分布,特别是在中国北方。

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