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市域人口老龄化空间特征与养老资源匹配关系研究——以东北三省为例
引用本文:赵东霞,韩增林,任启龙,刘万波,裴倩. 市域人口老龄化空间特征与养老资源匹配关系研究——以东北三省为例[J]. 资源科学, 2018, 40(9): 1773-1786. DOI: 10.18402/resci.2018.09.08
作者姓名:赵东霞  韩增林  任启龙  刘万波  裴倩
作者单位:1. 辽宁师范大学海洋经济与可持续发展研究中心,大连 116029
2. 辽宁师范大学 城市与环境学院,大连 116029
3. 辽宁师范大学 管理学院,大连 116029
4. 淮阴师范学院 城市与环境学院,淮安 223300
基金项目:国家自然科学基金青年科学基金项目(41601136)
摘    要:当老龄化先于经济发展时,老年人口养老资源配置问题会不断凸显。东北三省属于中度老龄化区,研究老年人口空间分布特征与养老资源优化配置将具有国家战略意义和示范效应。通过选取34个地级市和2个行政区作为研究对象,根据老年人口统计数据,基于空间自相关模型分析3个年份的市域人口老龄化时空演变特征,运用综合指数模型评价2015年36个对象的养老资源配置,依据地理集中度表示36个对象老年人口与养老资源的空间匹配关系。研究结果表明:2005年、2010年和2015年市域人口老龄化程度正逐渐加深,高密度地区范围扩大并由西南部向东北部推进,空间关联性特征仍在加强,高集聚区由南向北扩大,东北未来人口老龄化“稀释”面临严峻挑战;区域中心城市和政策扶持型城市的养老资源比区位边缘城市的丰富;老年人口和养老资源空间分布有明显的关联性,老年人口集中度和养老资源集中度都自南向北降低,其中辽宁省全境既是老年人口集中地区又是养老资源集中地区;匹配关系具有南北梯度差异,“辽中南”城市群发展水平明显高于“哈长”城市群;大多数城市仍面临养老资源浪费或供给不足的两级问题。

关 键 词:人口老龄化  时空演变特征  养老资源  空间匹配  城市  
收稿时间:2017-09-15
修稿时间:2018-07-03

Study on the relationship between the spatial feature of urban population aging and the pension resources matching ——take the three provinces of the Northeast China as an example
Dongxia ZHAO,Zenglin HAN,Qilong REN,Wanbo LIU,Qian PEI. Study on the relationship between the spatial feature of urban population aging and the pension resources matching ——take the three provinces of the Northeast China as an example[J]. Resources Science, 2018, 40(9): 1773-1786. DOI: 10.18402/resci.2018.09.08
Authors:Dongxia ZHAO  Zenglin HAN  Qilong REN  Wanbo LIU  Qian PEI
Affiliation:1. Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029, China
2. College of Urban and Environment Science, Liaoning Normal University, Dalian 116029, China
3. College of Management, Liaoning Normal University, Dalian 116029, China
4. College of Urban and Environment Science, Huaiyin Normal University, Huaian 223300, China
Abstract:With the population aging being ahead of economic development, the problem of pension resources configuration among aging population will stand out continually. The three provinces in the northeast of China are the moderate districts of aging. It is noted that there are national strategic meanings and demonstration effects to study the spatial distribution feature of aging population and the optimal configuration of pension resources. Taking 34 prefecture level cities and 2 administrative areas as the research objects, the spatial evolution features of population aging in the administrative regions in the 3 major years were characterized, based on the spatial autocorrelation analysis according to the statistical data of aging population. The pension resources configuration of 36 objects in 2015 were evaluated by using comprehensive index model and the spatial matching relationship between 36 groups’ aged people and pension resources was identified on the basis of geographic concentration. The results demonstrated that the degree of population aging in the administrative regions in 2005, 2010, and 2015 were deepening gradually. The high density areas were expanding from the southwest to the northeast and the spatial correlation features are enhancing; the high agglomeration areas were widening from the south to the north; and the “dilution” of population aging in the northeast in the future will face severe challenges. The pension resources in regional center cities and the cities with the government’s supports are richer than the peripheral cities. There is an obvious correlation of spatial distribution between aging population and pension resources. The concentration of aging population and pension resources is reduced from the south to the north. Among them, the whole area of Liaoning Province is both a concentrated area of aging population and pension resources. There is a diverse matching relationship between the south and the north, and the development level of the ‘Liaozhongnan’ urban agglomeration is significantly higher than that of the ‘Ha-Chang’ urban agglomeration. The most cities still face the two extreme problem, i. e. , a waste of and a short of pension resources.
Keywords:population aging  spatial evolution feature  pension resource  spatial matching  city  
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