Urban and rural geographies of aging: a local spatial correlation analysis of aging population measures

Shiode, Narushige; Morita, Masatoshi; Shiode, Shino; Okunuki, Kei-ichi

doi:10.1080/02723638.2014.905256

Cited by 41 publications

(24 citation statements)

References 22 publications

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“…However, the rural–urban pattern reversed with socioeconomic development, and rural–urban differences have declined over time (Du & Wang, ; Liu & Chen, ; Yuan, Wu, & Wu, ). These rural–urban differences are similar to those found in other countries, such as Japan, the United States, the United Kingdom, and Australia (Du & Wang, ; Shiode, Morita, Shiode, & Okunuki, ).…”

Section: Introductionsupporting

confidence: 84%

Understanding the spatial disparities and vulnerability of population aging in China

Cheng

Gao

et al. 2018

Asia & Pacific Policy Stud

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Understanding the regional pattern of population aging in China enables rational policy making to address the challenges of inequity in social welfare and care resources among the east-central-west regions and rural-urban areas of China. This study uses census data in 2000 and 2010, and aging population ratios, annual increase rates, and spatial autocorrelation analysis to examine spatial disparities in population aging in China. The results show that the population is more aged and aging more rapidly in rural areas than in urban areas. Spatial clusters of population aging expanded from the east coastal region in 2000, to inland provinces such as Sichuan and Chongqing in 2010. The vulnerable regions in terms of population aging, health status of the elderly population, and economic level at the prefectural level were also identified.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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Section: Introductionsupporting

confidence: 84%

Understanding the spatial disparities and vulnerability of population aging in China

Cheng

Gao

et al. 2018

Asia & Pacific Policy Stud

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“…The elderly depend heavily on young adults (15-29) in the capital, and senior adults (50-64) in the capital, towns and villages. In line with studies on the geography of aging (Harper & Laws, 1995;Shiode, Morita, Shiode, & Okunuki, 2014), our results suggest that age dependency varies strongly over space and between urbanisation levels. It should be noted that, a zero weight estimated by the regression model does not mean that there is no dependency between the populations, but that the dependency is statistically insignificant.…”

Section: Resultssupporting

confidence: 90%

Population and age structure in Hungary: a residential preference and age dependency approach to disaggregate census data

Juhász-Horváth²,

Harrison

et al. 2016

Journal of Maps

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We present a simple model to disaggregate age structured population census data to a 1-km grid for Hungary. A dasymetric approach was used to predict the spatial distribution of population in different age groups by distinguishing residential preferences (in relation to accessible social, economic and green amenities) for working age groups (15-29, 30-49 and 50-64) and population dependencies for children and the elderly (aged 0-14 and 65+). By using open-access land cover data and fine-level population census data as inputs, the model predicts the likely spatial distribution of population and age structure for Hungary in 2011. The resulting map and gridded data provide information to support spatial planning of residential development and urban infrastructure. The model is less data-demanding than most existing approaches, but provides greater power for describing population patterns. It can also be used to create scenarios of future demographic change. ARTICLE HISTORY

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“…Spatial distribution of aging also varies with scale. Several geographers have studied the spatial differentiations of aging at the international, intercontinental, national, and regional scales [25][26][27][28][29]. For example, Flynn (1980) focused on the regional differences of the distribution of the elderly population and found that the elderly population in the United States was concentrated in the central urban area and remote rural settlements, thereby forming a typical "retirement" center for polarization [30].…”

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confidence: 99%

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

Zhao

Zhang

et al. 2018

Sustainability

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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. will become the highest-aged country in the world [3]. Under the background of social transformation and space reconstruction, the aging of China is becoming more and more complex. "Aging before getting rich" and "demographic dividend disappeared", the notion in population and economic development, has been a serious threat to social sustainable development. On the other hand, an aging acceleration significantly affects the urban structure, urban formation, and land use of a city, all of which bring about new challenges for urban planning, especially with regard to the allocation of adequate facilities for an increasing number of elderly people [4]. Under such a circumstance, the aging issue has become a common and fundamental subject for local inhabitants, scholars, and governments all over the world. In the Yangtze River Delta in 2010, as an important economically developed area, the proportion of individuals who were over 60 years was 10.45%, which was significantly higher than the national average. Meanwhile, the Yangtze River Delta is a core area for rapid urbanization. In 2010, the region's gross domestic product (GDP) increased to 7.07 trillion RMB, accounting for 16.42% of the national total. It is not only an economically developed region but also an area where interaction occurs between nature and humans, which has resulted in various environmental and ecological problems and brought great challenges to regional sustainable development. R...

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Urban and rural geographies of aging: a local spatial correlation analysis of aging population measures

Cited by 41 publications

References 22 publications

Understanding the spatial disparities and vulnerability of population aging in China

Understanding the spatial disparities and vulnerability of population aging in China

Population and age structure in Hungary: a residential preference and age dependency approach to disaggregate census data

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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