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Identifying the Impacts of Social, Economic, and Environmental Factors on Population Aging in the Yangtze River Delta Using the Geographical Detector Technique

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  • Xin Xu

    (School of Geographic Science, Nanjing Normal University, Nanjing 210023, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China)

  • Yuan Zhao

    (School of Geographic Science, Nanjing Normal University, Nanjing 210023, China
    Ginling College, Nanjing Normal University, Nanjing 210097, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China)

  • Xinlin Zhang

    (School of Geographic Science, Nanjing Normal University, Nanjing 210023, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China)

  • Siyou Xia

    (School of Geographic Science, Nanjing Normal University, Nanjing 210023, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China)

Abstract

Under the background of social transformation and space reconstruction, population aging in China is becoming more and more diverse and complex. “Aging before getting rich”, a notion in population and economic development, has been a serious threat to sustainable development in China. On the basis of town- and street block-scale data from the Fifth and Sixth National Census in the Yangtze River Delta, we studied spatial distribution characteristics of population aging using global Moran’s I and hotspot analysis, and applied the geographical detector technique to explain the spatial heterogeneity of population aging. Several conclusions were drawn. (1) The promotion and replacement of aging coexist. Cluster of aging degree exhibits an increasing trend. Population aging is more severe in suburban areas than urban areas. (2) Migration is the main factor affecting the spatial heterogeneity of population aging. Per capital GDP and road network density are the second most influential factors. By contrast, the relief degree of land surface and the air quality index minimally influence population aging. The mechanisms of aging in various regions are affected by varying development levels. (3) The interaction among social, economic, and environmental factors enhances their effects and, thus, interacting factors have a greater influence on population aging than any single factor. The findings of this study have significant implications for local inhabitants and policy makers to address the population aging challenge in achieving sustainability of society, economy, and environment.

Suggested Citation

  • Xin Xu & Yuan Zhao & Xinlin Zhang & Siyou Xia, 2018. "Identifying the Impacts of Social, Economic, and Environmental Factors on Population Aging in the Yangtze River Delta Using the Geographical Detector Technique," Sustainability, MDPI, vol. 10(5), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1528-:d:145762
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    5. Xinxin Wang & Jingjing Hong & Pengpeng Fan & Shidan Xu & Zhixian Chai & Yubo Zhuo, 2021. "Is China’s urban–rural difference in population aging rational? An international comparison with key indicators," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1866-1891, September.
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    7. Shangmei Zhao & Jiang He & Haijun Yang, 2018. "Population Ageing, Financial Deepening and Economic Growth: Evidence from China," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
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    9. Wenjuan Du & Jiayi Zhou & Jianjian Liu & Xuhao Yang & Hanxu Wang & Meikun He & Zongfu Mao & Xiaojun Liu, 2019. "Social-Demographic Correlates of the Mental Health Conditions among the Chinese Elderly," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
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