乡镇尺度上的山东省人口老龄化空间格局演变与影响因素研究

doi:10.18306/dlkxjz.2019.04.009

摘要/Abstract

摘要：

基于第五次和第六次人口普查数据,研究了乡镇尺度上山东省人口老龄化的空间格局及其演变特征,并采用空间计量方法定量探讨了其影响因素。研究发现：① 山东省人口老龄化发展迅猛,但乡镇街道之间在老龄化水平、老年人口密度和增长速度等方面均存在非常显著的地域差异。② 按照不同的分析维度,山东省乡镇街道涵盖了丰富的人口老龄化地域类型,其中的2个类型形成了典型的空间分异格局。一类主要聚集在县级以上城市及其周边地域,总体上具有老年人口低占比、高密度、高绝对增长、低相对增长的特点;另一类是主要分布在胶东地区、黄河三角洲地区、沂蒙地区和鲁西地区等4个区域的一般乡镇,大体表现为高占比、低密度、低绝对增长、高相对增长特征。③ 空间滞后模型回归结果显示,老龄化动态演变过程的不确定性更强、影响因素更为复杂,基期老龄化基础对其影响效应不显著,经济增长速度有显著负向影响,但经济发展水平对老龄化静态格局的影响却不显著,使得乡镇尺度上老龄化空间格局的演变机制呈现出特殊性。

关键词: 人口老龄化, 空间格局, 乡镇尺度, 空间计量模型, 山东省

Abstract:

Based on the 2000 and 2010 censuses, this study examined the change of the spatial pattern of population aging of Shandong Province and its influencing factors by spatial statistical analysis and spatial econometric model at the township scale. It concluded that population aging is developing rapidly in the province, but the differences between the towns are very significant. Two types of territories with clear spatial agglomeration trends are recognized. One type is concentrated near cities and their surrounding areas, characterized by lower proportion, higher density, higher absolute growth rate, and lower relative growth rate of elderly population. The other type is towns located in the Jiaodong Peninsula area, the Yellow River Delta area, Yimeng Mountain area, and the West Shandong area, and mainly featured by higher proportion, lower density, lower absolute growth rate, and higher relative growth rate of elderly population. In contrast with the previous studies, we obtained several new findings on the driving forces of population aging in Shandong Province, reflecting the particular mechanism of change at the township scale. According to the regression results of the spatial econometric model, the population aging foundation does not have evident influence on the range of change, although it affects the static pattern in the next period, which means that the process of change is more complex and uncertain to predict than its spatial distribution. In addition, economic growth has a significantly negative effect on the spatial evolution of population aging, but the relationship between economic development level and the static aging level is unnoticeable.

Key words: population aging, spatial pattern, township scale, spatial econometric model, Shandong Province

李少星, 王先芝, 纪小乐, 张烨. 乡镇尺度上的山东省人口老龄化空间格局演变与影响因素研究[J]. 地理科学进展, 2019, 38(4): 567-576.

Shaoxing LI, Xianzhi WANG, Xiaole JI, Ye ZHANG. Spatial change and influencing factors of population aging in Shandong Province at the township scale[J]. PROGRESS IN GEOGRAPHY, 2019, 38(4): 567-576.

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参考文献 31

[1]	陈明华, 郝国彩. 2014. 中国人口老龄化地区差异分解及影响因素研究[J]. 中国人口·资源与环境, 24(4): 136-141. doi: 10.3969/j.issn.1002-2104.2014.04.018
	[Chen M H, Hao G C.2014. Research on regional difference decomposition and influence factors of population aging in China. China Population, Resources and Environment, 24(4): 136-141. ] doi: 10.3969/j.issn.1002-2104.2014.04.018
[2]	陈友华, 胡小武. 2011. 低生育率是中国的福音? 从第六次人口普查数据看中国人口发展现状与前景[J]. 南京社会科学, (8): 53-59. doi: 10.3969/j.issn.1001-8263.2011.08.009
	[Chen Y H, Hu X W.2011. Is low birth rate the evangel for China? Understanding China's population fact and prospect from the data of the Sixth National Census. Social Sciences in Nanjing, (8): 53-59. ] doi: 10.3969/j.issn.1001-8263.2011.08.009
[3]	胡述聚, 李诚固, 申庆喜, 等. 2018. 长春市人口老龄化时空演变及空间类型研究[J]. 人文地理, 33(3): 104-111.
	[Hu S J, Li C G, Shen Q X, et al.2018. The temporal-spatial evolution of population aging and its classification in Changchun. Human Geography, 33(3): 104-111. ]
[4]	康江江, 丁志伟, 张改素, 等. 2016. 中原地区人口老龄化的多尺度时空格局[J]. 经济地理, 36(4): 29-37. doi: 10.15957/j.cnki.jjdl.2016.04.005
	[Kang J J, Ding Z W, Zhang G S, et al.2016. Multi-scale spatio-temporal pattern of aging population in Central Plains region. Economic Geography, 36(4): 29-37. ] doi: 10.15957/j.cnki.jjdl.2016.04.005
[5]	梅林, 郭艳花, 陈妍. 2018. 吉林省人口老龄化时空分异特征及成因[J]. 地理科学进展, 37(3): 352-362.
	[Mei L, Guo Y H, Chen Y.2018. Spatiotemporal characteristics and influencing factors of population aging in Jilin Province. Progress in Geography, 37(3): 352-362. ]
[6]	单良, 丁莉. 2013. 中日人口老龄化旳空间分布特征比较研究[J]. 中国人口科学, 33(4): 89-97.
	[Shan L, Ding L.2013. Comparative research on the feature of spatial distribution of aging population between China and Japan. Chinese Journal of Population Science, 33(4): 89-97. ]
[7]	王桂新, 干一慧. 2017. 中国的人口老龄化与区域经济增长[J]. 中国人口科学, 37(3): 30-42.
	[Wang G X, Gan Y H.2017. Population aging in China and regional economic growth. Chinese Journal of Population Science, 37(3): 30-42. ]
[8]	王纪武, 邵雨莲. 2015. 杭州市老龄人口空间分布及演化规律研究[J]. 城市规划, 39(5): 47-51. doi: 10.11819/cpr20150508a
	[Wang J W, Shao Y L.2015. A study on the spatial distribution and evolution trend of aging population in Hangzhou. City Planning Review, 39(5): 47-51. ] doi: 10.11819/cpr20150508a
[9]	王录仓, 武荣伟. 2016. 中国人口老龄化时空变化及成因探析: 基于县域尺度的考察[J]. 中国人口科学, 36(4): 74-84.
	[Wang L C, Wu R W.2016. A study on spatial-temporal pattern of population ageing and its factors in China: Based on county-scale examination. Chinese Journal of Population Science, 36(4): 74-84. ]
[10]	王录仓, 武荣伟, 刘海猛, 等. 2016. 县域尺度下中国人口老龄化的空间格局与区域差异[J]. 地理科学进展, 35(8): 921-931. doi: 10.18306/dlkxjz.2016.08.001
	[Wang L C, Wu R W, Liu H M, et al.2016. Spatial patterns and regional differences of population ageing in China based on the county scale. Progress in Geography, 35(8): 921-931. ] doi: 10.18306/dlkxjz.2016.08.001
[11]	王新贤, 高向东, 陶树果. 2016. 上海市人口老龄化的空间分布及演化特征研究[J]. 上海经济研究, (8): 120-129.
	[Wang X X, Gao X D, Tao S G.2016. Research on the spatial distribution and evolution characteristics of aging population in Shanghai. Shanghai Economic Research, (8): 120-129. ]
[12]	王志宝, 孙铁山, 张杰斐. 2015. 人口老龄化区域类型划分与区域演变分析: 以中美日韩四国为例[J]. 地理科学, 35(7): 822-830. doi: 10.3724/SP.J.1011.2011.00415
	[Wang Z B, Sun T S, Zhang J F.2015. Regional types' division of population aging and analysis on population aging regional evolution: Based on China, America, Japan and R O Korea. Scientia Geographica Sinica, 35(7): 822-830. ] doi: 10.3724/SP.J.1011.2011.00415
[13]	魏秀梅, 李丁, 张超, 等. 2015. 甘肃省人口老龄化空间分异及影响因素研究[J]. 资源开发与市场, (3): 283-287. doi: 10.3969/j.issn.1005-8141.2015.03.007
	[Wei X M, Li D, Zhang C, et al.2015. Study on spatial disparity and its influencing factors of Gansu population aging. Resource Development & Market, (3): 283-287. ] doi: 10.3969/j.issn.1005-8141.2015.03.007
[14]	吴连霞, 赵媛, 吴开亚, 等. 2018. 中国人口老龄化区域差异及驱动机制研究[J]. 地理科学, 38(6): 877-884.
	[Wu L X, Zhao Y, Wu K Y, et al.2018. Regional variations and driving mechanism of aging population in China. Scientia Geographica Sinica, 38(6): 877-884. ]
[15]	谢波, 周婕. 2013. 大城市老年人口的空间分布模式与发展趋势研究[J]. 城市规划学刊, 25(5): 56-62.
	[Xie B, Zhou J.2013. A research on spatial patterns and development trajectory of the elderly population in the metropolis. Urban Planning Forum, 25(5): 56-62. ]
[16]	许昕, 赵媛, 郭爱妹. 2016. 基于街道尺度的南京市老年人口空间分布演变研究[J]. 人文地理, 31(6): 88-94.
	[Xu X, Zhao Y, Guo A M.2016. Spatial distribution of the elderly population in Nanjing based on the street scale. Human Geography, 31(6): 88-94. ]
[17]	许昕, 赵媛, 张新林, 等. 2017. 江苏省人口老龄化空间分异演变及影响因素[J]. 地理科学, 37(12): 1859-1866. doi: 10.13249/j.cnki.sgs.2017.12.009
	[Xu X, Zhao Y, Zhang X L, et al.2017. Spatial variation of population aging and associated factors in Jiangsu Province. Scientia Geographica Sinica, 37(12): 1859-1866. ] doi: 10.13249/j.cnki.sgs.2017.12.009
[18]	闫庆武. 2011. 空间数据分析方法在人口数据空间化中的应用 [M]. 南京: 东南大学出版社.
	[Yan Q W.2011. Application of the spatial data analysis in the population data spatialization. Nanjing, China: Southeast University Press. ]
[19]	杨彩萍, 汤茂林, 王爽. 2016. 江苏省县域老龄化空间格局及影响因素分析[J]. 南京师大学报(自然科学版), 39(2): 125-133. doi: 10.3969/j.issn.1001-4616.2016.02.022
	[Yang C P, Tang M L, Wang S.2016. The spatial pattern and its influencing factors of aging at county level in Jiangsu Province. Journal of Nanjing Normal University (Natural Science Edition), 39(2): 125-133. ] doi: 10.3969/j.issn.1001-4616.2016.02.022
[20]	杨继生, 万越. 2016. 中国人口政策的变轨效应[J]. 华中科技大学学报(社会科学版), 30(1): 103-114.
	[Yang J S, Wan Y.2016. Treatment effect of China's population policy. Journal of Huazhong University of Science and Technology (Social Science Edition), 30(1): 103-114. ]
[21]	易成栋, 张纯, 吴淑萍, 等. 2014. 2000—2010年北京市老年人口空间分布及其变动研究[J]. 城市发展研究, 21(2): 66-71. doi: 10.3969/j.issn.1006-3862.2014.02.011
	[Yi C D, Zhang C, Wu S P, et al.2014. Spatial restructuring of senior population in Beijing from 2000-2010. Urban Studies, 21(2): 66-71. ] doi: 10.3969/j.issn.1006-3862.2014.02.011
[22]	于涛方. 2015. 中国大城市中心城区人口老龄化空间特征与规划应对[J]. 规划师, 31(12): 95-100. doi: 10.3969/j.issn.1006-0022.2015.12.016
	[Yu T F.2015. Spatial characters of population aging in Chinese big cities. Planners, 31(12): 95-100. ] doi: 10.3969/j.issn.1006-0022.2015.12.016
[23]	袁俊, 吴殿廷, 吴铮争. 2007. 中国农村人口老龄化的空间差异及其影响因素分析[J]. 中国人口科学, 27(3): 41-47. doi: 10.3969/j.issn.1000-7881.2007.03.005
	[Yuan J, Wu D T, Wu Z Z.2007. Analysis on regional disparity and contributing factors of rural population aging in China. Chinese Journal of Population Science, 27(3): 41-47. ] doi: 10.3969/j.issn.1000-7881.2007.03.005
[24]	张开洲, 陈楠. 2014. 1990—2010年福建省县域人口老龄化时空演变特征及其驱动机制[J]. 地理科学进展, 33(5): 605-615. doi: 10.11820/dlkxjz.2014.05.002
	[Zhang K Z, Chen N.2014. Characteristics of spatial-temporal evolution in population aging and driving mechanism at county level in Fujian Province during 1990-2010. Progress in Geography, 33(5): 605-615. ] doi: 10.11820/dlkxjz.2014.05.002
[25]	赵东霞, 韩增林, 王利. 2017. 中国老年人口分布的集疏格局及其形成机制[J]. 地理学报, 72(10): 1762-1775. doi: 10.11821/dlxb201710003
	[Zhao D X, Han Z L, Wang L.2017. The spatial pattern of aging population distribution and its generating mechanism in China. Acta Geographica Sinica, 72(10): 1762-1775. ] doi: 10.11821/dlxb201710003
[26]	赵儒煜, 刘畅, 张锋. 2012. 中国人口老龄化区域溢出与分布差异的空间计量经济学研究[J]. 人口研究, 36(2): 71-81.
	[Zhao R Y, Liu C, Zhang F.2012. Spatial econometric research on regional spillover and distribution difference of population aging in China. Population Research, 36(2): 71-81. ]
[27]	周春山, 李一璇, 童新梅. 2016. 2000—2010年广州市人口老龄化空间变动及其影响因素研究[J]. 中山大学学报(自然科学版), 55(1): 114-122. doi: 10.13471/j.cnki.acta.snus.2016.01.020
	[Zhou C S, Li Y X, Tong X M.2016. Spatial change and influence factors of population aging in Guangzhou during 2000-2010. Acta Scientiarum Naturalium Universitatis Sunyatseni, 55(1): 114-122. ] doi: 10.13471/j.cnki.acta.snus.2016.01.020
[28]	周春山, 童新梅, 王珏晗, 等. 2018. 2000—2010年广州市人口老龄化空间分异及形成机制[J]. 地理研究, 37(1): 103-118. doi: 10.11821/dlyj201801008
	[Zhou C S, Tong X M, Wang J H, et al.2018. Spatial differentiation and the formation mechanism of population aging in Guangzhou in 2000-2010. Geographical Research, 37(1): 103-118. ] doi: 10.11821/dlyj201801008
[29]	左学金. 2012. 21世纪中国人口再展望[J]. 北京大学学报(哲学社会科学版), 49(5): 100-106.
	[Zuo X J.2012. A prospect for Chinese population in the 21st century. Journal of Peking University (Philosophy and Social Sciences), 49(5): 100-106. ]
[30]	He W, Goodkind D, Kowal P.2016. An aging world: 2015 [R]. Washington DC: United States Census Bureau.
[31]	Liu Z F, He C Y, Zhang Q F, et al.2012. Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008[J]. Landscape and Urban Planning, 106(1): 62-72. doi: 10.1016/j.landurbplan.2012.02.013

时间	统计参数	老年人口比重/%	老年人口密度/(人/km²)	老年人口年均增速/‰	老年人口与常住人口增速差/‰
五普	均值	8.12	46.29	—	—
	极大值	15.97	7340.36	—	—
	极小值	1.54	0.05	—	—
	变异系数	0.22	3.64	—	—
	莫兰指数	0.60	0.64	—	—
六普	均值	9.84	59.72	25.81	19.52
	极大值	22.52	7291.87	168.99	128.92
	极小值	3.50	0.07	-98.46	-96.99
	变异系数	0.24	3.16	—	—
	莫兰指数	0.59	0.65	0.33	0.39

时间	年轻型	成年型	浅度老龄化	中度老龄化	深度老龄化
五普	20	275	1075	274	34
六普	5	105	556	743	269

方程	变量	考察维度	具体指标(单位)	代码
方程1	被解释变量	人口老龄化格局演变	老年人口占比变化幅度(%)	ΔRAP
	解释变量	人口出生水平	0~14岁人口占比变化(%)	ΔRYP
		人口年龄结构基础	五普时65岁以上老年人口占比(%)	FRAP
		人口迁移水平	外来人口占比变化幅度(%)	ΔEP
		经济发展水平	灯光量年均增速(%)	ΔVLI
		地区受教育水平	万人学校数(个)	NS
		地区医疗卫生条件	万人医院卫生院数(个)	NH
		地区间相互作用	空间滞后项	WLAG
方程2	被解释变量	人口老龄化静态格局	六普老年人口占比(%)	RAP
	解释变量	人口出生水平	六普0~14岁人口占比（%）	RYP
		人口年龄结构基础	五普时65岁以上老年人口占比(%)	FRAP
		人口迁移水平	六普外来人口占比(%)	EP
		经济发展水平	六普万人灯光量(无量纲)	PLI
		地区受教育水平	万人学校数(个)	NS
		地区医疗卫生条件	万人医院卫生院数(个)	NH
		地区间相互作用	空间滞后项	WLAG

回归变量	方程1	方程2
回归变量	ΔRAP	RAP
ΔRYP	-0.026813^***	—
RYP	—	-0.148352^***
FRAP	0.00854982	0.643389^***
ΔEP	-0.0838488^***	—
EP	—	-0.0667621^***
ΔVLI	-0.0172225^*	—
PLI	—	-6.59999E-05
NS	0.0724394^***	0.0677682^**
NH	0.0501008^*	0.06076^**
WLAG	0.609856^***	0.347385^***
R²	0.542195	0.825258
样本数	1678	1678