Urban Ageing in Europe—Spatiotemporal Analysis of Determinants

The aim of this study was to identify determinants of the population ageing process in 270 European cities. We analyzed the proportion of older people: men and women separately (aged 65 or above) in city populations in the years 1990–2018. To understand territorially-varied relationships and to incr...

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Main Authors: Karolina Lewandowska-Gwarda, Elżbieta Antczak
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/9/7/413
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spelling doaj-6a9936c7d9384d76a875fdc02295fc2d2020-11-25T02:45:34ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-06-01941341310.3390/ijgi9070413Urban Ageing in Europe—Spatiotemporal Analysis of DeterminantsKarolina Lewandowska-Gwarda0Elżbieta Antczak1Faculty of Economics and Sociology, University of Lodz, Rewolucji 1905 r. 37 Street, 90-214 Lodz, PolandFaculty of Economics and Sociology, University of Lodz, Rewolucji 1905 r. 37 Street, 90-214 Lodz, PolandThe aim of this study was to identify determinants of the population ageing process in 270 European cities. We analyzed the proportion of older people: men and women separately (aged 65 or above) in city populations in the years 1990–2018. To understand territorially-varied relationships and to increase the explained variability of phenomena, an explanatory spatial data analysis (ESDA) and geographically weighted regression (GWR) were applied. We used ArcGIS and GeoDa software in this study. In our research, we also took into account the spatial interactions as well as the structure of cities by size and level of economic development. Results of the analysis helped to explain why some urban areas are ageing faster than others. An initial data analysis indicated that the proportion of the elderly in the population was spatially diversified and dependent on gender, as well as the size and economic development of a unit. In general, elderly individuals were more willing to live in larger and highly developed cities; however, women tended to live in large areas and men in medium-sized to large urban areas. Then, we conducted the urban ageing modelling for men and women separately. The application of GWR models enabled not only the specification of the city population ageing determinants, but also the analysis of the variability in the strength and direction of dependencies occurring between the examined variables in individual cities. Significant differences were noted in the analysis results for specific cities, which were often grouped due to similar parameter values, forming clusters that divided Europe into the eastern and western parts. Moreover, substantial differences in results were obtained for women and men.https://www.mdpi.com/2220-9964/9/7/413urban ageing of men and womenEuropean citiesregional heterogeneity and spatial interactionssocioeconomic determinantsgeographically weighted regressionESDA tools
collection DOAJ
language English
format Article
sources DOAJ
author Karolina Lewandowska-Gwarda
Elżbieta Antczak
spellingShingle Karolina Lewandowska-Gwarda
Elżbieta Antczak
Urban Ageing in Europe—Spatiotemporal Analysis of Determinants
ISPRS International Journal of Geo-Information
urban ageing of men and women
European cities
regional heterogeneity and spatial interactions
socioeconomic determinants
geographically weighted regression
ESDA tools
author_facet Karolina Lewandowska-Gwarda
Elżbieta Antczak
author_sort Karolina Lewandowska-Gwarda
title Urban Ageing in Europe—Spatiotemporal Analysis of Determinants
title_short Urban Ageing in Europe—Spatiotemporal Analysis of Determinants
title_full Urban Ageing in Europe—Spatiotemporal Analysis of Determinants
title_fullStr Urban Ageing in Europe—Spatiotemporal Analysis of Determinants
title_full_unstemmed Urban Ageing in Europe—Spatiotemporal Analysis of Determinants
title_sort urban ageing in europe—spatiotemporal analysis of determinants
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2020-06-01
description The aim of this study was to identify determinants of the population ageing process in 270 European cities. We analyzed the proportion of older people: men and women separately (aged 65 or above) in city populations in the years 1990–2018. To understand territorially-varied relationships and to increase the explained variability of phenomena, an explanatory spatial data analysis (ESDA) and geographically weighted regression (GWR) were applied. We used ArcGIS and GeoDa software in this study. In our research, we also took into account the spatial interactions as well as the structure of cities by size and level of economic development. Results of the analysis helped to explain why some urban areas are ageing faster than others. An initial data analysis indicated that the proportion of the elderly in the population was spatially diversified and dependent on gender, as well as the size and economic development of a unit. In general, elderly individuals were more willing to live in larger and highly developed cities; however, women tended to live in large areas and men in medium-sized to large urban areas. Then, we conducted the urban ageing modelling for men and women separately. The application of GWR models enabled not only the specification of the city population ageing determinants, but also the analysis of the variability in the strength and direction of dependencies occurring between the examined variables in individual cities. Significant differences were noted in the analysis results for specific cities, which were often grouped due to similar parameter values, forming clusters that divided Europe into the eastern and western parts. Moreover, substantial differences in results were obtained for women and men.
topic urban ageing of men and women
European cities
regional heterogeneity and spatial interactions
socioeconomic determinants
geographically weighted regression
ESDA tools
url https://www.mdpi.com/2220-9964/9/7/413
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