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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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 |
work_keys_str_mv |
AT karolinalewandowskagwarda urbanageingineuropespatiotemporalanalysisofdeterminants AT elzbietaantczak urbanageingineuropespatiotemporalanalysisofdeterminants |
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