Loading…
Health-Related Disparities in the Metropolitan Region Ruhr: Large-Scale Spatial Model of Local Asthma Prevalence, Accessibility of Health Facilities, and Socioeconomic and Environmental Factors
This paper investigates the area of the Metropole Ruhr in terms of spatial distributions of environmental factors that can prevent or cause a significantly lower or higher rate of respiratory diseases such as asthma. Environmental factors can have negative impact, like air pollution, and positive, l...
Saved in:
Published in: | Journal of photogrammetry, remote sensing and geoinformation science remote sensing and geoinformation science, 2022-10, Vol.90 (5), p.473-490 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | cdi_FETCH-LOGICAL-c286t-65219ab118808784ab9abb406fdb94769c5be4d708555e834e3fd5dad171d3c63 |
container_end_page | 490 |
container_issue | 5 |
container_start_page | 473 |
container_title | Journal of photogrammetry, remote sensing and geoinformation science |
container_volume | 90 |
creator | Ortwein, Annette Redecker, Andreas P. Moos, Nicolai |
description | This paper investigates the area of the Metropole Ruhr in terms of spatial distributions of environmental factors that can prevent or cause a significantly lower or higher rate of respiratory diseases such as asthma. Environmental factors can have negative impact, like air pollution, and positive, like the access to urban green areas. In the second part of the analysis, the accessibility of pharmacies, hospitals, and medical facilities that offer a special treatment for people with respiratory diseases will be spatially analysed and associated to those detected urban areas of higher and lower prevalence. The results of both approaches are spatially blended with socioeconomic and socio-demographic values of the respective residents. With this it is possible to point out whether accessibility of health facilities is a suitable and equitable for all people diagnosed with asthma regardless of their educational or migration background, their employment rate, salary or age. Consequently, all values will be disaggregated from large spatial units, such as city districts municipalities or neighbourhoods, to small city blocks, to assess large-scale spatial variability. This provides the opportunity of a point-by-point investigation and statistical analysis with a high level of detail that significantly exceeds previous study results. In the sociological context of environmental justice this highly interdisciplinary study contributes to the assessment of fair health conditions for people in densely populated conurbations. |
doi_str_mv | 10.1007/s41064-022-00213-z |
format | article |
fullrecord | <record><control><sourceid>crossref_sprin</sourceid><recordid>TN_cdi_crossref_primary_10_1007_s41064_022_00213_z</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_1007_s41064_022_00213_z</sourcerecordid><originalsourceid>FETCH-LOGICAL-c286t-65219ab118808784ab9abb406fdb94769c5be4d708555e834e3fd5dad171d3c63</originalsourceid><addsrcrecordid>eNp9UdtOAjEU3BhNJOgP-NQPsNp2b13fCIKYQDSiz5tuexZqlpa0hUT-zj-zsPrq0zlnMjNnkkmSG0ruKCHlvc8oKTJMGMOEMJriw1kyYDllmHFanf_tJa8uk2vvPwkhlNM8K6tB8j0D0YU1foNOBFDoUfutcDpo8EgbFNaAFhCc3dpOB2HQG6y0jWO3dg9oLtwK8FKKDtByK4IWHVpYBR2yLZrbiKORD-uNQK8O9pFlJNyikZTgvW50dPw6MvsIaCrkEYqfb5EwCi2t1BakNXaj5QmZmL121mzAhGgd-cE6f5VctKLzcP07h8nHdPI-nuH5y9PzeDTHkvEi4CJntBINpZwTXvJMNPFqMlK0qqmysqhk3kCmSsLzPAeeZpC2KldC0ZKqVBbpMGG9r3TWewdtvXV6I9xXTUl97KHue6hjD_Wph_oQRWkv8pFsVuDqT7tzJub8T_UDjx6PQA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Health-Related Disparities in the Metropolitan Region Ruhr: Large-Scale Spatial Model of Local Asthma Prevalence, Accessibility of Health Facilities, and Socioeconomic and Environmental Factors</title><source>Springer Nature</source><creator>Ortwein, Annette ; Redecker, Andreas P. ; Moos, Nicolai</creator><creatorcontrib>Ortwein, Annette ; Redecker, Andreas P. ; Moos, Nicolai</creatorcontrib><description>This paper investigates the area of the Metropole Ruhr in terms of spatial distributions of environmental factors that can prevent or cause a significantly lower or higher rate of respiratory diseases such as asthma. Environmental factors can have negative impact, like air pollution, and positive, like the access to urban green areas. In the second part of the analysis, the accessibility of pharmacies, hospitals, and medical facilities that offer a special treatment for people with respiratory diseases will be spatially analysed and associated to those detected urban areas of higher and lower prevalence. The results of both approaches are spatially blended with socioeconomic and socio-demographic values of the respective residents. With this it is possible to point out whether accessibility of health facilities is a suitable and equitable for all people diagnosed with asthma regardless of their educational or migration background, their employment rate, salary or age. Consequently, all values will be disaggregated from large spatial units, such as city districts municipalities or neighbourhoods, to small city blocks, to assess large-scale spatial variability. This provides the opportunity of a point-by-point investigation and statistical analysis with a high level of detail that significantly exceeds previous study results. In the sociological context of environmental justice this highly interdisciplinary study contributes to the assessment of fair health conditions for people in densely populated conurbations.</description><identifier>ISSN: 2512-2789</identifier><identifier>EISSN: 2512-2819</identifier><identifier>DOI: 10.1007/s41064-022-00213-z</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Aerospace Technology and Astronautics ; Astronomy ; Computer Imaging ; Earth and Environmental Science ; Geographical Information Systems/Cartography ; Geography ; Observations and Techniques ; Original Article ; Pattern Recognition and Graphics ; Remote Sensing/Photogrammetry ; Signal,Image and Speech Processing ; Vision</subject><ispartof>Journal of photogrammetry, remote sensing and geoinformation science, 2022-10, Vol.90 (5), p.473-490</ispartof><rights>The Author(s) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c286t-65219ab118808784ab9abb406fdb94769c5be4d708555e834e3fd5dad171d3c63</cites><orcidid>0000-0001-5133-4105</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Ortwein, Annette</creatorcontrib><creatorcontrib>Redecker, Andreas P.</creatorcontrib><creatorcontrib>Moos, Nicolai</creatorcontrib><title>Health-Related Disparities in the Metropolitan Region Ruhr: Large-Scale Spatial Model of Local Asthma Prevalence, Accessibility of Health Facilities, and Socioeconomic and Environmental Factors</title><title>Journal of photogrammetry, remote sensing and geoinformation science</title><addtitle>PFG</addtitle><description>This paper investigates the area of the Metropole Ruhr in terms of spatial distributions of environmental factors that can prevent or cause a significantly lower or higher rate of respiratory diseases such as asthma. Environmental factors can have negative impact, like air pollution, and positive, like the access to urban green areas. In the second part of the analysis, the accessibility of pharmacies, hospitals, and medical facilities that offer a special treatment for people with respiratory diseases will be spatially analysed and associated to those detected urban areas of higher and lower prevalence. The results of both approaches are spatially blended with socioeconomic and socio-demographic values of the respective residents. With this it is possible to point out whether accessibility of health facilities is a suitable and equitable for all people diagnosed with asthma regardless of their educational or migration background, their employment rate, salary or age. Consequently, all values will be disaggregated from large spatial units, such as city districts municipalities or neighbourhoods, to small city blocks, to assess large-scale spatial variability. This provides the opportunity of a point-by-point investigation and statistical analysis with a high level of detail that significantly exceeds previous study results. In the sociological context of environmental justice this highly interdisciplinary study contributes to the assessment of fair health conditions for people in densely populated conurbations.</description><subject>Aerospace Technology and Astronautics</subject><subject>Astronomy</subject><subject>Computer Imaging</subject><subject>Earth and Environmental Science</subject><subject>Geographical Information Systems/Cartography</subject><subject>Geography</subject><subject>Observations and Techniques</subject><subject>Original Article</subject><subject>Pattern Recognition and Graphics</subject><subject>Remote Sensing/Photogrammetry</subject><subject>Signal,Image and Speech Processing</subject><subject>Vision</subject><issn>2512-2789</issn><issn>2512-2819</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9UdtOAjEU3BhNJOgP-NQPsNp2b13fCIKYQDSiz5tuexZqlpa0hUT-zj-zsPrq0zlnMjNnkkmSG0ruKCHlvc8oKTJMGMOEMJriw1kyYDllmHFanf_tJa8uk2vvPwkhlNM8K6tB8j0D0YU1foNOBFDoUfutcDpo8EgbFNaAFhCc3dpOB2HQG6y0jWO3dg9oLtwK8FKKDtByK4IWHVpYBR2yLZrbiKORD-uNQK8O9pFlJNyikZTgvW50dPw6MvsIaCrkEYqfb5EwCi2t1BakNXaj5QmZmL121mzAhGgd-cE6f5VctKLzcP07h8nHdPI-nuH5y9PzeDTHkvEi4CJntBINpZwTXvJMNPFqMlK0qqmysqhk3kCmSsLzPAeeZpC2KldC0ZKqVBbpMGG9r3TWewdtvXV6I9xXTUl97KHue6hjD_Wph_oQRWkv8pFsVuDqT7tzJub8T_UDjx6PQA</recordid><startdate>20221001</startdate><enddate>20221001</enddate><creator>Ortwein, Annette</creator><creator>Redecker, Andreas P.</creator><creator>Moos, Nicolai</creator><general>Springer International Publishing</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-5133-4105</orcidid></search><sort><creationdate>20221001</creationdate><title>Health-Related Disparities in the Metropolitan Region Ruhr: Large-Scale Spatial Model of Local Asthma Prevalence, Accessibility of Health Facilities, and Socioeconomic and Environmental Factors</title><author>Ortwein, Annette ; Redecker, Andreas P. ; Moos, Nicolai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c286t-65219ab118808784ab9abb406fdb94769c5be4d708555e834e3fd5dad171d3c63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aerospace Technology and Astronautics</topic><topic>Astronomy</topic><topic>Computer Imaging</topic><topic>Earth and Environmental Science</topic><topic>Geographical Information Systems/Cartography</topic><topic>Geography</topic><topic>Observations and Techniques</topic><topic>Original Article</topic><topic>Pattern Recognition and Graphics</topic><topic>Remote Sensing/Photogrammetry</topic><topic>Signal,Image and Speech Processing</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ortwein, Annette</creatorcontrib><creatorcontrib>Redecker, Andreas P.</creatorcontrib><creatorcontrib>Moos, Nicolai</creatorcontrib><collection>SpringerOpen</collection><collection>CrossRef</collection><jtitle>Journal of photogrammetry, remote sensing and geoinformation science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ortwein, Annette</au><au>Redecker, Andreas P.</au><au>Moos, Nicolai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Health-Related Disparities in the Metropolitan Region Ruhr: Large-Scale Spatial Model of Local Asthma Prevalence, Accessibility of Health Facilities, and Socioeconomic and Environmental Factors</atitle><jtitle>Journal of photogrammetry, remote sensing and geoinformation science</jtitle><stitle>PFG</stitle><date>2022-10-01</date><risdate>2022</risdate><volume>90</volume><issue>5</issue><spage>473</spage><epage>490</epage><pages>473-490</pages><issn>2512-2789</issn><eissn>2512-2819</eissn><abstract>This paper investigates the area of the Metropole Ruhr in terms of spatial distributions of environmental factors that can prevent or cause a significantly lower or higher rate of respiratory diseases such as asthma. Environmental factors can have negative impact, like air pollution, and positive, like the access to urban green areas. In the second part of the analysis, the accessibility of pharmacies, hospitals, and medical facilities that offer a special treatment for people with respiratory diseases will be spatially analysed and associated to those detected urban areas of higher and lower prevalence. The results of both approaches are spatially blended with socioeconomic and socio-demographic values of the respective residents. With this it is possible to point out whether accessibility of health facilities is a suitable and equitable for all people diagnosed with asthma regardless of their educational or migration background, their employment rate, salary or age. Consequently, all values will be disaggregated from large spatial units, such as city districts municipalities or neighbourhoods, to small city blocks, to assess large-scale spatial variability. This provides the opportunity of a point-by-point investigation and statistical analysis with a high level of detail that significantly exceeds previous study results. In the sociological context of environmental justice this highly interdisciplinary study contributes to the assessment of fair health conditions for people in densely populated conurbations.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s41064-022-00213-z</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0001-5133-4105</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2512-2789 |
ispartof | Journal of photogrammetry, remote sensing and geoinformation science, 2022-10, Vol.90 (5), p.473-490 |
issn | 2512-2789 2512-2819 |
language | eng |
recordid | cdi_crossref_primary_10_1007_s41064_022_00213_z |
source | Springer Nature |
subjects | Aerospace Technology and Astronautics Astronomy Computer Imaging Earth and Environmental Science Geographical Information Systems/Cartography Geography Observations and Techniques Original Article Pattern Recognition and Graphics Remote Sensing/Photogrammetry Signal,Image and Speech Processing Vision |
title | Health-Related Disparities in the Metropolitan Region Ruhr: Large-Scale Spatial Model of Local Asthma Prevalence, Accessibility of Health Facilities, and Socioeconomic and Environmental Factors |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T23%3A07%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Health-Related%20Disparities%20in%20the%20Metropolitan%20Region%20Ruhr:%20Large-Scale%20Spatial%20Model%20of%20Local%20Asthma%20Prevalence,%20Accessibility%20of%20Health%20Facilities,%20and%20Socioeconomic%20and%20Environmental%20Factors&rft.jtitle=Journal%20of%20photogrammetry,%20remote%20sensing%20and%20geoinformation%20science&rft.au=Ortwein,%20Annette&rft.date=2022-10-01&rft.volume=90&rft.issue=5&rft.spage=473&rft.epage=490&rft.pages=473-490&rft.issn=2512-2789&rft.eissn=2512-2819&rft_id=info:doi/10.1007/s41064-022-00213-z&rft_dat=%3Ccrossref_sprin%3E10_1007_s41064_022_00213_z%3C/crossref_sprin%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c286t-65219ab118808784ab9abb406fdb94769c5be4d708555e834e3fd5dad171d3c63%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |