Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models

Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Science of the total environment 2023-05, Vol.871, p.162005-162005, Article 162005
Hauptverfasser: Wang, Siqin, Cai, Wenhui, Tao, Yaguang, Sun, Qian Chayn, Wong, Paulina Pui Yun, Huang, Xiao, Liu, Yan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 162005
container_issue
container_start_page 162005
container_title The Science of the total environment
container_volume 871
creator Wang, Siqin
Cai, Wenhui
Tao, Yaguang
Sun, Qian Chayn
Wong, Paulina Pui Yun
Huang, Xiao
Liu, Yan
description Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate. [Display omitted] •This study develops a tri-environmental framework across social, built and natural environment.•This study contributes the first nationwide study of heat, air pollution and health outcomes in Australia.•The methodological novelty lies in using global and local machine learning models.•The nexus between exposure to temperature and air
doi_str_mv 10.1016/j.scitotenv.2023.162005
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2775613015</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0048969723006204</els_id><sourcerecordid>2775613015</sourcerecordid><originalsourceid>FETCH-LOGICAL-c420t-db15342a3e9770947a69958c11028178b703349a05ed013f4b7b4535cfb287e83</originalsourceid><addsrcrecordid>eNqFkcFu3CAQhlHVqNlu-wopx168BWMb-7iK2iZSpF6SMxrjcZYNhg3gNHmuvmDxbppruTAa_f_8Ax8hXzjbcMabb_tN1Cb5hO5pU7JSbHhTMla_Iyveyq7grGzekxVjVVt0TSfPyccY9ywf2fIP5Fw0sm4lYyvy584dQD8Yd0_TDqlxCUNBwQ1LGaCYQw-ODmYcMaDTGKkfj0qI0WsDyXhHe0y_ER3dIdi0O7rx-eDjHJAmv7TTsQkm0McZrEkveTzdzjFHWAN0jssC99b3YI9K63WuJtA745BahOAWxeQHtPETORvBRvz8eq_J3Y_vt5dXxc2vn9eX25tCVyVLxdDzWlQlCOykZF0loem6utU8_07LZdtLJkTVAatxYFyMVS_7qha1HvuyldiKNfl6mnsI_nHGmNRkokZrwaGfoyqlrBsuWI5ZE3mS6uBjDDiqQzAThBfFmVqIqb16I6YWYupELDsvXkPmfsLhzfcPURZsT4L8cnwyGJZBC4rBBNRJDd78N-QvG5euZQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2775613015</pqid></control><display><type>article</type><title>Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models</title><source>MEDLINE</source><source>Access via ScienceDirect (Elsevier)</source><creator>Wang, Siqin ; Cai, Wenhui ; Tao, Yaguang ; Sun, Qian Chayn ; Wong, Paulina Pui Yun ; Huang, Xiao ; Liu, Yan</creator><creatorcontrib>Wang, Siqin ; Cai, Wenhui ; Tao, Yaguang ; Sun, Qian Chayn ; Wong, Paulina Pui Yun ; Huang, Xiao ; Liu, Yan</creatorcontrib><description>Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate. [Display omitted] •This study develops a tri-environmental framework across social, built and natural environment.•This study contributes the first nationwide study of heat, air pollution and health outcomes in Australia.•The methodological novelty lies in using global and local machine learning models.•The nexus between exposure to temperature and air quality and health follows a V-shape pattern.•The impacts of heat/air pollution on health are obvious in/near the inner-city areas of capital cities.</description><identifier>ISSN: 0048-9697</identifier><identifier>EISSN: 1879-1026</identifier><identifier>DOI: 10.1016/j.scitotenv.2023.162005</identifier><identifier>PMID: 36758700</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Air Pollutants - analysis ; Air Pollution ; Air quality ; Built environment ; Cities ; Climate ; Geographically weighted random forest ; Heat ; Hot Temperature ; Humans ; Mental health ; Self-reported physical health ; Social environment ; Temperature</subject><ispartof>The Science of the total environment, 2023-05, Vol.871, p.162005-162005, Article 162005</ispartof><rights>2023 The Authors</rights><rights>Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-db15342a3e9770947a69958c11028178b703349a05ed013f4b7b4535cfb287e83</citedby><cites>FETCH-LOGICAL-c420t-db15342a3e9770947a69958c11028178b703349a05ed013f4b7b4535cfb287e83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.scitotenv.2023.162005$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,3551,27929,27930,46000</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36758700$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Siqin</creatorcontrib><creatorcontrib>Cai, Wenhui</creatorcontrib><creatorcontrib>Tao, Yaguang</creatorcontrib><creatorcontrib>Sun, Qian Chayn</creatorcontrib><creatorcontrib>Wong, Paulina Pui Yun</creatorcontrib><creatorcontrib>Huang, Xiao</creatorcontrib><creatorcontrib>Liu, Yan</creatorcontrib><title>Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models</title><title>The Science of the total environment</title><addtitle>Sci Total Environ</addtitle><description>Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate. [Display omitted] •This study develops a tri-environmental framework across social, built and natural environment.•This study contributes the first nationwide study of heat, air pollution and health outcomes in Australia.•The methodological novelty lies in using global and local machine learning models.•The nexus between exposure to temperature and air quality and health follows a V-shape pattern.•The impacts of heat/air pollution on health are obvious in/near the inner-city areas of capital cities.</description><subject>Air Pollutants - analysis</subject><subject>Air Pollution</subject><subject>Air quality</subject><subject>Built environment</subject><subject>Cities</subject><subject>Climate</subject><subject>Geographically weighted random forest</subject><subject>Heat</subject><subject>Hot Temperature</subject><subject>Humans</subject><subject>Mental health</subject><subject>Self-reported physical health</subject><subject>Social environment</subject><subject>Temperature</subject><issn>0048-9697</issn><issn>1879-1026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkcFu3CAQhlHVqNlu-wopx168BWMb-7iK2iZSpF6SMxrjcZYNhg3gNHmuvmDxbppruTAa_f_8Ax8hXzjbcMabb_tN1Cb5hO5pU7JSbHhTMla_Iyveyq7grGzekxVjVVt0TSfPyccY9ywf2fIP5Fw0sm4lYyvy584dQD8Yd0_TDqlxCUNBwQ1LGaCYQw-ODmYcMaDTGKkfj0qI0WsDyXhHe0y_ER3dIdi0O7rx-eDjHJAmv7TTsQkm0McZrEkveTzdzjFHWAN0jssC99b3YI9K63WuJtA745BahOAWxeQHtPETORvBRvz8eq_J3Y_vt5dXxc2vn9eX25tCVyVLxdDzWlQlCOykZF0loem6utU8_07LZdtLJkTVAatxYFyMVS_7qha1HvuyldiKNfl6mnsI_nHGmNRkokZrwaGfoyqlrBsuWI5ZE3mS6uBjDDiqQzAThBfFmVqIqb16I6YWYupELDsvXkPmfsLhzfcPURZsT4L8cnwyGJZBC4rBBNRJDd78N-QvG5euZQ</recordid><startdate>20230501</startdate><enddate>20230501</enddate><creator>Wang, Siqin</creator><creator>Cai, Wenhui</creator><creator>Tao, Yaguang</creator><creator>Sun, Qian Chayn</creator><creator>Wong, Paulina Pui Yun</creator><creator>Huang, Xiao</creator><creator>Liu, Yan</creator><general>Elsevier B.V</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20230501</creationdate><title>Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models</title><author>Wang, Siqin ; Cai, Wenhui ; Tao, Yaguang ; Sun, Qian Chayn ; Wong, Paulina Pui Yun ; Huang, Xiao ; Liu, Yan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c420t-db15342a3e9770947a69958c11028178b703349a05ed013f4b7b4535cfb287e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Air Pollutants - analysis</topic><topic>Air Pollution</topic><topic>Air quality</topic><topic>Built environment</topic><topic>Cities</topic><topic>Climate</topic><topic>Geographically weighted random forest</topic><topic>Heat</topic><topic>Hot Temperature</topic><topic>Humans</topic><topic>Mental health</topic><topic>Self-reported physical health</topic><topic>Social environment</topic><topic>Temperature</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Siqin</creatorcontrib><creatorcontrib>Cai, Wenhui</creatorcontrib><creatorcontrib>Tao, Yaguang</creatorcontrib><creatorcontrib>Sun, Qian Chayn</creatorcontrib><creatorcontrib>Wong, Paulina Pui Yun</creatorcontrib><creatorcontrib>Huang, Xiao</creatorcontrib><creatorcontrib>Liu, Yan</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>The Science of the total environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Siqin</au><au>Cai, Wenhui</au><au>Tao, Yaguang</au><au>Sun, Qian Chayn</au><au>Wong, Paulina Pui Yun</au><au>Huang, Xiao</au><au>Liu, Yan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models</atitle><jtitle>The Science of the total environment</jtitle><addtitle>Sci Total Environ</addtitle><date>2023-05-01</date><risdate>2023</risdate><volume>871</volume><spage>162005</spage><epage>162005</epage><pages>162005-162005</pages><artnum>162005</artnum><issn>0048-9697</issn><eissn>1879-1026</eissn><abstract>Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate. [Display omitted] •This study develops a tri-environmental framework across social, built and natural environment.•This study contributes the first nationwide study of heat, air pollution and health outcomes in Australia.•The methodological novelty lies in using global and local machine learning models.•The nexus between exposure to temperature and air quality and health follows a V-shape pattern.•The impacts of heat/air pollution on health are obvious in/near the inner-city areas of capital cities.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>36758700</pmid><doi>10.1016/j.scitotenv.2023.162005</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0048-9697
ispartof The Science of the total environment, 2023-05, Vol.871, p.162005-162005, Article 162005
issn 0048-9697
1879-1026
language eng
recordid cdi_proquest_miscellaneous_2775613015
source MEDLINE; Access via ScienceDirect (Elsevier)
subjects Air Pollutants - analysis
Air Pollution
Air quality
Built environment
Cities
Climate
Geographically weighted random forest
Heat
Hot Temperature
Humans
Mental health
Self-reported physical health
Social environment
Temperature
title Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-11T21%3A05%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Unpacking%20the%20inter-%20and%20intra-urban%20differences%20of%20the%20association%20between%20health%20and%20exposure%20to%20heat%20and%20air%20quality%20in%20Australia%20using%20global%20and%20local%20machine%20learning%20models&rft.jtitle=The%20Science%20of%20the%20total%20environment&rft.au=Wang,%20Siqin&rft.date=2023-05-01&rft.volume=871&rft.spage=162005&rft.epage=162005&rft.pages=162005-162005&rft.artnum=162005&rft.issn=0048-9697&rft.eissn=1879-1026&rft_id=info:doi/10.1016/j.scitotenv.2023.162005&rft_dat=%3Cproquest_cross%3E2775613015%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2775613015&rft_id=info:pmid/36758700&rft_els_id=S0048969723006204&rfr_iscdi=true