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TIME-SPACE PATTERNS OF RISK CLUSTER OF POPULATION AGING IN CHINAAT MULTI-SCALES: THE APPLICATION OF FLEXIBLE SPATIAL SCAN STATISTICS |
JI Xiao-mei1, ZENG Qun-zhou1, WANG Chao2 |
1. College of Tourism, Nanchang University, Nanchang 330031, China;
2. College of Business, Guizhou University of Finance and Economicas, Guizhou 550025, China |
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Abstract Population aging is one of the most heated topics among domestic and foreign societies which has been attached numerous attention by scholars from variant research fields. On the one hand, under the context where the social and spatial reconfiguration take places, population aging in China tends to be increasingly complicated, the new normalcy characterized as getting old before being rich is throwing a great threaten to the sustainable development. On the other hand, due to the fact that regions vary in development stage and geographical condition, population aging in China displays its strikingly spatial and temporal imbalance. Using Flexible Spatial Scan Statistic, this paper scrutinized spatiotemporal disparity in aging risk clusters at provincial, prefectural and county scales. The authors found that, aging has become the main melody of Chinese population transformation, and low birth rate has been the new normal at nation-wide. The regional imbalance comes to be increasingly worsened and there exist diverse regional models. All three scales share such common features as followings:aging risk clusters are spatially concentrated on the southeast part of China, the risk degree and distributional area become larger, but the gap among clusters comes to be narrowed. Generally, the smaller spatial scale Flexible Spatial Scan Statistic adopts, the more scattered, precise and higher-risk clusters will be identified, and gaps between them become enlarged.
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Received: 19 February 2017
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[29] |
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[30] |
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[29] |
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Kulldorff M, Huang L, Pickle L, et al. An elliptic spatial scan statistic[J]. Statistical of Medicine, 2006,25(22):3929-3943.
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Tango T. A spatial scan statistic with a restricted likelihood ratio[J]. Japanese Journal of Biometrics, 2008,29(2):75-95.
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