中国城市群人口老龄化时空格局

doi:10.11821/dlxb201706005

摘要/Abstract

摘要：

老龄化和城市化是当今世界面临的两大人口问题。城市群是城市发展到成熟阶段的空间组织形态,是老龄化的特殊区域。本文基于2000年和2010年全国人口普查分县数据,综合应用地理探测器和变异系数等方法,清晰地刻画了中国20个城市群人口老龄化的空间格局及其变化特征,审视了人口老龄化变化的影响因素。结果表明：① 2000年中国城市群人口老龄化平均水平为7.32%,其中12个城市群的人口属于成年型,到2010年时人口老龄化平均水平已上升为9.00%,除珠三角与宁夏沿黄城市群外,其余18个城市群均步入了老年型人口,表现出明显的水平升级与类型替变态势。② 老龄化高值、较高值区域不断向内陆城市群跃迁。③ 城市群老龄化的增量和增速存在显著的区域差异,老龄化水平的低值区和高值区增量少、增速慢,而较低值、中值和较高值区增量多、增速快。总体上表现出区域性城市群——国家级城市群——地区性城市群老龄化速度递减的态势。④ 在城市群内部,老龄化分布格局表现出隆升—塌缩并存的现象。国家级城市群内部老龄化分布格局从隆升结构向塌缩结构转变,城市群中心区人口老龄化水平降低;而地区性城市群和区域性城市群内部老龄化分布格局则从均质结构向隆升结构转变,中心区人口老龄化水平上升。⑤ 城市群人口老龄化是内外因素综合影响的结果,基期老龄化程度、人口年龄结构替变和人口流动性是主导性因素。其中人口年龄结构的普遍性抬升是城市群老龄化升级与类型替变的关键,低龄人口迁入到城市群对人口老龄化则起到“稀释作用”,城市群发育阶段不同引致的聚集和扩散效应对老龄化则起到诱导作用。

关键词: 城市群, 人口老龄化, 时空格局, 影响因素, 地理探测器, 中国

Abstract:

Aging and urbanization are two major population issues currently facing the world. Urban agglomeration is an advanced form of urbanization that encompasses the spatial organization of cities within a specific geographical area, and in which the process of aging differs from that in other regions. Based on county-specific data from population surveys in 2000 and 2010, we determined the spatial patterns and variations of aging populations in 20 urban agglomerations in China using geographical detector-based and coefficient of variation methods. We also examined the contributing factors of population aging variability. Results demonstrated that in 2000, older people accounted for 7.32% of the urban agglomeration demographic structure, with 12 of the 20 urban agglomerations defined as adult-type populations. In 2010, however, older people accounted for 9.00% of the urban agglomeration demographic structure and, except for those in the Pearl River Delta and Ningxia areas along the Yellow River, all the urban agglomerations entered the elderly population stage. Moreover, high-age and moderately high-age regions expanded towards inland urban agglomerations, with population aging increasing obviously and population type changing from adult to aging. In addition, significant regional differences in the incremental increases in the number of older people and growth rates of the aging populations existed in the urban agglomerations. Low-age and high-age regions had smaller increments and growth rates, whereas moderately low-age, mid-age, and moderately high-age regions had greater increments and growth rates, indicating a declining aging rate in the order of regional, national, and local urban agglomerations. Within each urban agglomeration, the distribution pattern of aging showed the coexistence of uplift and collapse. The distribution pattern of aging within national urban agglomerations changed from an increasing to collapsing structure, and population aging in central China reduced. Conversely, regional urban agglomerations changed from a homogeneous to an increasing structure, and population aging in the central region increased. Population aging of urban agglomerations was the result of internal and external factors, with changes in base period aging, population age structure, and population fluidity being the predominant factors. Universal uplift of the population age structure was a key factor affecting aging and population types in urban agglomerations. Furthermore, low-age population immigration into urban agglomerations had a "diluting effect" on population aging, and aggregation and diffusion effects caused by different development stages of urban agglomeration played important roles in aging and population migration.

Key words: urban agglomeration, population ageing, spatial-temporal patterns, influencing factors, geographical detector tool, China

王录仓, 武荣伟, 李巍. 中国城市群人口老龄化时空格局[J]. 地理学报, 2017, 72(6): 1001-1016.

Lucang WANG, Rongwei WU, Wei LI. Spatial-temporal patterns of population aging on China's urban agglomerations[J]. Acta Geographica Sinica, 2017, 72(6): 1001-1016.

图/表 7

图1

表1

图2

表2

表3

中国城市群各影响因素对人口老龄化的决定力

城市群	决定力/ 显著性水平	初期老龄化水平(LLH₂₀₀₀)	2000年55~65岁人口比例(LL)	生育水平(SY)	迁入率(QRB)	迁出率(QCB)	人均GDP(PGDP)	人均病床数(YL)	人均受教育年限(EDU)
2010年城市群静态水平	决定力	0.5080	0.5966	0.0270	0.0931	0.1296	0.0136	0.0374	0.0840
2010年城市群静态水平	显著性水平	0.000	0.000	0.2336	0.000	0.000	0.6579	0.0028	0.000
2000-2010年间年城市群动态水平	决定力	0.0044	0.3141	0.0089	0.1431	0.2296	0.0680	0.0146	0.1144
2000-2010年间年城市群动态水平	显著性水平	0.4683	0.000	0.1332	0.000	0.000	0.000	0.0303	0.000
京津冀城市群	决定力	0.007	0.389	0.011	0.017	0.368	0.098	0.023	0.008
京津冀城市群	显著性水平	0.782	0.000	0.624	0.528	0.000	0.006	0.574	0.732
长三角城市群	决定力	0.156	0.462	0.194	0.345	0.151	0.214	0.029	0.174
长三角城市群	显著性水平	0.027	0.000	0.000	0.000	0.032	0.000	0.367	0.003
珠三角城市群	决定力	0.082	0.233	0.297	0.376	0.281	0.113	0.129	0.304
珠三角城市群	显著性水平	0.430	0.147	0.100	0.021	0.200	0.314	0.389	0.060
成渝城市群	决定力	0.003	0.076	0.205	0.355	0.418	0.209	0.075	0.361
成渝城市群	显著性水平	0.935	0.056	0.000	0.000	0.000	0.000	0.043	0.000
江淮城市群	决定力	0.037	0.152	0.236	0.191	0.302	0.121	0.172	0.235
江淮城市群	显著性水平	0.558	0.146	0.014	0.052	0.008	0.163	0.221	0.024
长江中游城市群	决定力	0.011	0.259	0.137	0.035	0.271	0.007	0.005	0.005
长江中游城市群	显著性水平	0.542	0.000	0.000	0.251	0.000	0.742	0.810	0.793
哈大长城市群	决定力	0.089	0.426	0.123	0.108	0.071	0.013	0.163	0.154
哈大长城市群	显著性水平	0.063	0.000	0.244	0.522	0.103	0.999	0.344	0.526
黔中城市群	决定力	0.014	0.299	0.307	0.085	0.130	0.199	0.030	0.030
黔中城市群	显著性水平	0.844	0.044	0.031	0.672	0.269	0.068	0.816	0.871
中原城市群	决定力	0.032	0.378	0.108	0.112	0.188	0.013	0.174	0.214
中原城市群	显著性水平	0.468	0.000	0.172	0.182	0.010	0.710	0.057	0.036
山东城市群	决定力	0.071	0.315	0.156	0.039	0.062	0.156	0.122	0.059
山东城市群	显著性水平	0.238	0.006	0.008	0.473	0.181	0.072	0.090	0.165
关中城市群	决定力	0.124	0.192	0.019	0.168	0.257	0.180	0.008	0.056
关中城市群	显著性水平	0.202	0.078	0.964	0.508	0.135	0.148	0.955	0.866
辽中南城市群	决定力	0.025	0.297	0.151	0.206	0.006	0.009	0.110	0.067
辽中南城市群	显著性水平	0.790	0.043	0.146	0.409	0.906	0.933	0.516	0.557

表3

表4

表5

参考文献 45

[1]	Tine Buffel, Chris Phillipson.Can global cities be "age-friendly cities"? Urban Development and Ageing Populations. Cities, 2016, 55(6): 94-100. doi: 10.1016/j.cities.2016.03.016
[2]	UNDESA. World Population Ageing. New York: UN, 2013.
[3]	Gottmann J.Megaloplis or the urbannization if the northeastern aeabord. Economic Geography, 1957, 33(7): 31-40.
[4]	Scott A J.Global City-Regions: Trends, Theory, Policy. London: Oxford University Press, 2001.
[5]	Liu Shilin, Liu Xingjing.Urban Development Report on Urban Agglomeration, China, 2014. Biejing: Oriental Publishing Center, 2014: 12.
	[刘士林, 刘新静. 中国城市群发展报, 2014. 北京: 东方出版中心, 2014: 12.]
[6]	Wang Lucang, Wu Rongwei, Liu Haimeng, et al.Spatial patterns and regional differences of population ageing in China:based on the county scale. Progress in Geography, 2016, 35(8): 921-931. doi: 10.18306/dlkxjz.2016.08.001
	[王录仓, 武荣伟, 刘海猛, 等. 县域尺度下中国人口老龄化的空间格局与区域差异. 地理科学进展, 2016, 35(8): 921-931.] doi: 10.18306/dlkxjz.2016.08.001
[7]	Theresa Grafeneder-Weissteiner, Klaus Prettner.Agglomeration and demographic change. Journal of Urban Economics, 2013, 74(3): 1-11.
[8]	Suhong Zhou, Miao Xie, Mei-Po Kwan.Ageing in place and ageing with migration in the transitional context of urban China: A case study of ageing communities in Guangzhou. Habitat International, 2015, 49(10): 177-186. doi: 10.1016/j.habitatint.2015.05.022
[9]	Golant S M.The suburbanization of the American elderly//Elderly Migration and Population Redistribution: A Comparative Study. London: Belhaven Press, 1992: 163-180.
[10]	Nina Glasgow, David L Brown.Rural aging in the United States: Trends and contexts. Journal of Rural Studies, 2012, 28(4): 422-431. doi: 10.1016/j.jrurstud.2012.01.002
[11]	Zbigniew Długosz.Population ageing in Europe. Procedia-Social and Behavioral Sciences, 2011(19): 47-55.
[12]	Vanessa Burholt, Christine Dobbs.Research on rural ageing: Where have we got to and where are we going in Europe? Journal of Rural Studies, 2012, 28(4): 432-446. doi: 10.1016/j.jrurstud.2012.01.009
[13]	Rudolf Hartog.Europe's aging cities. Verlag Müller+Busmann KG and Rudolf Hartog, 2005.
[14]	Olga Theou, Lynne Cann, Joanna Blodgett, et al.Modifications to the frailty phenotype criteria: Systematic review of the current literature and investigation of 262 frailty phenotypes in the Survey of Health, Ageing, and Retirement in Europe. Ageing Research Reviews, 2015, 21(5): 78-94.
[15]	Chang Won Won.Elderly long-term care in Korea. Journal of Clinical Gerontology and Geriatrics, 2013, 4(1): 4-6. doi: 10.1016/j.jcgg.2012.11.001
[16]	Rafal Chomik, Peter McDonald, John Piggott. Population ageing in Asia and the Pacific: Dependency metrics for policy. The Journal of the Economics of Ageing, 11 May 2016.
[17]	Allon Smith R D. Long-term impacts o f rural migration of the elderly in England and Wales//Geographical Perspectives on the Elderly. Chichester: John Wiley and Sons Ltd, 1982: 35-52.
[18]	Daniel Botsman.Recovering Japan's urban past: Yoshida Nobuyuki, Tsukada Takashi, and the cities of the Tokugawa period. City, Culture and Society, 2012, 3(1): 9-14. doi: 10.1016/j.ccs.2012.06.004
[19]	Zhengtian Pan, Hiroatsu Fukuda.Research on the countermeasure of housing for the elderly in the aging background of Japan: A case study on typical welfare facilities of Kitakyushu City in Japan. Procedia-Social and Behavioral Sciences, 2016, 216(6): 119-128. doi: 10.1016/j.sbspro.2015.12.016
[20]	Tine Buffel, Chris Phillipson.Can global cities be 'age-friendly cities' ? Urban development and ageing populations.Cities, 2016, 55(6): 94-100. doi: 10.1016/j.cities.2016.03.016
[21]	Huang Runlong.Economic development and population migration aging in Yangtze River Delta Urban Agglomeration.Modern Economic Research, 2011(12): 34-38. doi: 10.3969/j.issn.1009-2382.2011.12.007
	[黄润龙. 长三角城市群的经济发展与人口迁移老龄化. 现代经济探讨, 2011(12): 34-38.] doi: 10.3969/j.issn.1009-2382.2011.12.007
[22]	Sun Maoling.The analysis of aging popultions spatial and temporal. Industrial Construction, 2014, 44(Suppl.1): 131-134.
	[孙茂龙. 长三角城市群人口老龄化时空变化分析. 工业建筑, 2014, 44(增刊): 131-134.]
[23]	Liu Shuang.China's urbanization and population aging. Northwest Population, 1998(3): 12-17.
	[刘爽. 中国的城镇化与区域人口老龄化. 西北人口, 1998(3): 13-17.]
[24]	Zhang Fan, Fang Dachun.The relationship between population aging, urbanization and urban-rural income gap, China:based on the Panel VAR Model. Journal of Jilin Business and Technology College, 2015, 31(2): 9-14.
	[张凡, 方大春. 中国人口老龄化、城市化和城乡收入差距关系研究: 基于面板VAR模型. 吉林工商学院学报, 2015, 31(2): 9-14.]
[25]	Gao Xiaolu, Wu Danxian, Xu Zening, et al.A review and frame-work setting of geographical research on aging in China. Progress in Geography, 2015, 34(12): 1480-1494. doi: 10.18306/dlkxjz.2015.12.001
	[高晓路, 吴丹贤, 许泽宁, 等. 中国老龄化地理学综述和研究框架构建. 地理科学进展, 2015, 34(12): 1480-1494.] doi: 10.18306/dlkxjz.2015.12.001
[26]	Li Yang, Liu Hiu, Jin Fengjun, et al.Spatio-temporal transition of the aging population based on ESDA-GIS in Beijing City. China Population, Resources and Environment, 2011, 21(11): 131-138. doi: 10.3969/j.issn.1002-2104.2011.11.022
	[李扬, 刘慧, 金凤君, 等. 北京市人口老龄化的时空变化特征. 中国人口·资源与环境, 2011, 21(11): 131-138.] doi: 10.3969/j.issn.1002-2104.2011.11.022
[27]	Lin Lin, Ma Fei.Spatial distribution and trends of the aging of population in Guangzhou. Geographical Research, 2007, 26(5): 1043-1054. doi: 10.3321/j.issn:1000-0585.2007.05.021
	[林琳, 马飞. 广州市人口老龄化的空间分布及趋势. 地理研究, 2007, 26(5): 1043-1054.] doi: 10.3321/j.issn:1000-0585.2007.05.021
[28]	Kang Chuankong.Population aging will hinder urbanization process? An empirical study of Chinese Provincial Panel Data. World Economic Papers, 2012(1): 91-105.
	[康传坤. 人口老龄化会阻碍城市化进程吗? 基于中国省级面板数据的实证研究. 世界经济文汇, 2012(1): 91-105.]
[29]	Li Pei.Temporal-spatial characteristics of Chinese rural-urban migration and its influencing factors. Economist, 2009 (1): 50-57.
	[李培. 中国城乡人口迁移的时空特征及其影响因素. 经济学家, 2009(1): 50-57.]
[30]	Li Qiiang.Ananalysis of push and pull factors in the migration of rural workers in China. Social Sciences in China, 2003(1): 125-136.
	[李强. 影响中国城乡流动人口的推力与拉力因素分析. 中国社会科学, 2003(1): 125-136.]
[31]	Song Jian.Study on flowing and moving old people: Comments on foreign documents. Population Journal, 2005(1): 28-32. doi: 10.3969/j.issn.1004-129X.2005.01.006
	[宋健. 流迁老年人口研究: 国外文献评述. 人口学刊, 2005(1): 28-32.] doi: 10.3969/j.issn.1004-129X.2005.01.006
[32]	Mincer J.Famlily migration decisions. Journal of political Economy, 1978, 86(5): 749-773.
[33]	Stark O D E. Bloom. The New economics of labor migration. American Economic Review, 1975. 75(2): 173-178. doi: 10.1016/0309-586X(85)90093-7
[34]	Yu Taofang.China's aging population and its spatial features in city areas (2000-2010). Urban Planning Forum, 2013.(6): 58-66.
	[于涛方. 中国城市老龄化空间特征及相关因素分析: 基于“五普”和“六普”人口数据的分析. 城市规划学刊, 2013(6): 58-66.]
[35]	Liu Yuting, Wang Yong, Wu Lijuan.Review on the definition and mechanism of urban agglomeration and its future research fields. Human Geography, 2013, 28(1): 62-68.
	[刘玉亭, 王勇, 吴丽娟. 城市群概念、形成机制及其未来研究方向评述. 人文地理, 2013, 28(1): 62-68.]
[36]	Wang J F, Li X H, Christakos G, et al.Geographical de-tectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China. International Journal of Geographical Information Science, 2010, 24(1): 107-127. doi: 10.1080/13658810802443457
[37]	Du Peng.Quantitative analysis on main factors of China's population aging. Population Science of China, 1992(6): 18-24.
	[杜鹏. 中国人口老龄化主要影响因素的量化分析. 中国人口科学, 1992(6): 18-24.]
[38]	Wang Zhibao, Sun Tieshan, Li Guoping.Regional differences and evolutions of population aging in China. Population Research, 2013, 37(1): 66-77.
	[王志宝, 孙铁山, 李国平. 近20年来中国人口老龄化的区域差异及其演化. 人口研究, 2013, 37(1): 66-77.]
[39]	Sun Lei, Chang Tian jiao, Guo Quanyu.On the spatial distribution of population aging and iIts synchronization with economic development in China. Journal of East China Normal University (Humanities and Social Sciences), 2014(3):123-132.
	[孙蕾, 常天骄, 郭全毓. 中国人口老龄化空间分布特征及与经济发展的同步性研究. 华东师范大学学报(哲学社会科学版), 2014(3): 123-132.]
[40]	Mc Carthy K F. The elderly population changing spatial distribution: Patterns of change since 1960. Santa Monica: Rand Corporation, 1983.
[41]	Rogers A, Woodward J.The sources of regional elderly population growth: Migration and aging in place. The Professional Geographer, 1988, 40: 450-459. doi: 10.1111/j.0033-0124.1988.00450.x
[42]	National Health and Family Planning of Floating Population Division.Development Report of Floating Population in China, 2015. Beijing: China Population Press, 2015.
	[国家卫生和计划生育委员会流动人口司. 中国流动人口发展报告2015. 北京: 中国人口出版社, 2015.]
[43]	Wang Guixin, Pan Zehan.The Robustness of China's Migration and Heihe-Tengchong Line. Chinese Journal of Population Science, 2016(1): 1-13.
	[王桂新, 潘泽瀚. 中国人口迁移分布的顽健性与胡焕庸线. 中国人口科学, 2016(1): 1-13.]
[44]	Liu Tao, Qi Yuanjing, Cao Guangzhong.China's floating population in the 21st century:Uneven landscape, influencing factors, and effects on urbanization. Acta Geographica Sinica, 2015, 70(4): 567-581.
	[刘涛, 齐元静, 曹广忠. 中国流动人口空间格局演变机制及城镇化效应: 基于2000和2010年人口普查分县数据的分析. 地理学报, 2015, 70(4): 567-581.]
[45]	Xie Miao, Zhou Suhong.Aging in place and residential relocation: Spatial transition and problems in Guangzhou.Planners, 2014(10): 96-103.
	[谢淼, 周素红. 就地老化与居住迁移: 广州市中心城区老龄化地域空间格局的变化及动因. 规划师, 2014(10): 96-103.]

类别	名称	老龄化程度				10年间老龄化变化
类别	名称	2000年			2010年	增量	增速(%)
国家级城市群	长江三角洲城市群	9.87	老年型Ⅰ期(L₁)	10.35	老年型Ⅱ期(L₂)	0.48	4.83
	珠江三角洲城市群	4.80	成年型Ⅰ期(C₁)	5.07	成年型Ⅰ期(C₁)	0.27	5.70
	京津冀城市群	7.66	成年型Ⅱ期(C₂)	8.59	老年型Ⅰ期(L₁)	0.93	12.17
	长江中游城市群	6.76	成年型Ⅱ期(C₂)	8.91	老年型Ⅰ期(L₁)	2.15	31.81
	成渝城市群	7.94	老年型Ⅰ期(L₁)	11.52	老年型Ⅱ期(L₂)	3.58	45.07
区域性城市群	哈长城市群	5.85	成年型Ⅱ期(C₂)	8.15	老年型Ⅰ期(L₁)	2.30	39.35
	辽中南城市群	8.00	老年型Ⅰ期(L₁)	10.35	老年型Ⅱ期(L₂)	2.35	29.38
	山东半岛城市群	8.68	老年型Ⅰ期(L₁)	10.28	老年型Ⅱ期(L₂)	1.60	18.40
	江淮城市群	7.51	老年型Ⅰ期(L₁)	10.14	老年型Ⅱ期(L₂)	2.64	35.10
	中原城市群	7.24	老年型Ⅰ期(L₁)	8.05	老年型Ⅰ期(L₁)	0.81	11.17
	海峡西岸城市群	6.73	成年型II期(C₂)	7.38	老年型Ⅰ期(L₁)	0.66	9.75
	关中城市群	5.98	成年型Ⅱ期(C₂)	8.50	老年型Ⅰ期(L₁)	2.52	42.05
	广西北部湾城市群	7.23	老年型Ⅰ期(L₁)	8.94	老年型Ⅰ期(L₁)	1.71	23.62
	天山北坡城市群	4.98	成年型Ⅰ期(C₁)	8.51	老年型Ⅰ期(L₁)	3.53	70.96
地区性城市群	晋中城市群	6.84	成年型Ⅱ期(C₂)	8.07	老年型Ⅰ期(L₁)	1.23	18.05
	兰西城市群	5.16	成年型Ⅱ期(C₂)	8.05	老年型Ⅰ期(L₁)	2.89	56.09
	呼包鄂榆城市群	6.04	成年型Ⅱ期(C₂)	7.03	老年型Ⅰ期(L₁)	0.99	16.33
	滇中城市群	6.42	成年型Ⅱ期(C₂)	8.12	老年型Ⅰ期(L1)	1.71	26.59
	黔中城市群	6.14	成年型Ⅱ期(C₂)	8.82	老年型Ⅰ期(L₁)	2.69	43.80
	宁夏沿黄城市群	4.56	成年型Ⅰ期(C₁)	6.31	成年型II期(C₂)	1.75	38.35

	PGDP	YL	EDU	QRB	QCB	LL	LLH₂₀₀₀	SY
LLH₂₀₀₀	0.0270
SY	0.0642	0.0136
GDP	0.0855	0.0732	0.0374
YL	0.2399	0.1296	0.1813	0.0840
EDU	0.2198	0.1249	0.1554	0.1535	0.0931
QRB	0.2410	0.1789	0.1971	0.2091	0.2438	0.1296
QCB	0.6391	0.6431	0.6180	0.6612	0.6781	0.6534	0.5966
LL	0.5275	0.5516	0.5250	0.5865	0.6098	0.6251	0.7349	0.5080

	初期老龄化水平(LLH)*	55~65岁人口比例(LL)*	生育水平 (SY)*	迁入率(QRB)**	迁出率 (QCB)**	人均GDP (PGDP)**	人均病床数(YL)**	人均受教育年限(EDU)**
京津冀城市群	0.3097	0.3982	0.0523	0.0257	0.0257	0.0035	0.1191	0.0106
京津冀城市群	0.007	0.389	0.011	0.017	0.368	0.098	0.023	0.008
差值	-0.3027	-0.0092	-0.0413	-0.0087	0.3423	0.0945	-0.0961	-0.0026
长三角城市群	0.4594	0.2542	0.1255	0.1063	0.1141	0.0894	0.0174	0.063
长三角城市群	0.156	0.462	0.194	0.345	0.151	0.214	0.029	0.174
差值	-0.3034	0.2078	0.0685	0.2387	0.0369	0.1246	0.0116	0.111
珠三角城市群	0.4817	0.5958	0.6856	0.801	0.2226	0.2932	0.0349	0.3104
珠三角城市群	0.082	0.233	0.297	0.376	0.281	0.113	0.129	0.304
差值	-0.3997	-0.3628	-0.3886	-0.425	0.0584	-0.1802	0.0941	-0.0064
成渝城市群	0.4047	0.2818	0.2438	0.0183	0.0602	0.0457	0.0492	0.1019
成渝城市群	0.003	0.076	0.205	0.355	0.418	0.209	0.075	0.361
差值	-0.4017	-0.2058	-0.0388	0.3367	0.3578	0.1633	0.0258	0.2591
长江中游城市群	0.513	0.484	0.168	0.011	0.035	0.089	0.007	0.165
长江中游城市群	0.011	0.259	0.137	0.035	0.271	0.007	0.005	0.005
差值	-0.502	-0.225	-0.031	0.024	0.236	-0.082	-0.002	-0.16

阶段	要素特征	空间特征	老龄化态势	老龄化变化	老龄化效应
低发育阶段	要素以聚集为主,被吸附到中心城市,高度发达的中心城市与相对滞后的周边地区形成典型的二元结构。	圈层结构	中心城区吸引了大量本地人口迁入,外围地区向中心城区贡献了低龄人口。	非老龄化转化为轻度老龄化	就地老化
中等发育阶段	城市群核心区对外围地区的辐射作用开始显现,周边发展较好的区域逐渐成为城市群的次中心,分担着从核心区外迁的部分生产功能或居住功能,区域交通体系逐步将中心城市与周边地区连接起来。	单中心与多个次中心并存的结构	中心城区由于将低层次、劳动密集型产业大量外迁,集中发展更高层次的智力密集型产业,从而将外来青壮年人口拦截在外围区县,导致核心区老龄化水平偏高,而外围地区老龄化水平较低的态势。	轻度老龄化转向中度老龄化,核心区>外围地区	升级替变型/迁入稀释型
发育成熟阶段	城市群核心区与周边地区关系紧密,基础设施、土地利用、生态环境等方面形成了共建共享格局,要素流动频繁,中心城市与周边区县联系的网络化体系已经出现,形成超越城市、区县行政区界的相对完整的区域空间组织。	网络结构	无论是城市群核心区,还是外围地区,都能均衡发展,对于外来人口的吸引力并无明显差异,而人口结构仍在不断演替,两者均处在高老龄化状,但老年人口向郊区处迁,导致中心区老龄化水平降低	中心区塌缩(由重度老龄化转向中度老龄化)	迁出塌缩型