Spatially heterogeneous associations between the built environment and objective health outcomes in Japanese cities.
The built environment is a structural determinant of health. Here we reveal spatially heterogeneous associations of built environment indicators with objective health outcomes (morbidity) by combining a random forest (RF) approach and a multiscale geographically weighted (MGWR) regression method. Us...
| Published in: | International Journal of Environmental Health Research Vol. 33; no. 12; pp. 1205 - 1218 |
|---|---|
| Main Authors: | , , , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Taylor & Francis Ltd
Dec2023
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=174203820&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174203820 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09603123 57L jtl: International Journal of Environmental Health Research issn: 09603123 maglogo: Y pubinfo: dt: Dec2023 vid: 33 iid: 12 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 174203820 157302846 174203820 174203820 10.1080/09603123.2022.2083086 174203820 ppf: 1205 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Spatially heterogeneous associations between the built environment and objective health outcomes in Japanese cities. aug: au: Li, Shuangjin Zhang, Junyi Moriyama, Michiko Kazawa, Kana affil: Mobilities and Urban Policy Lab, Graduate School for International Development and Cooperation, Hiroshima University, Higashihiroshima, Japan sug: subj: Built Environment Japan Health Status Evaluation Urban Population Environmental Health Human Japan Urban Areas Random Forest Regression Morbidity Risk Factors Hospitals Risk Assessment Public Spaces Geographic Factors ab: The built environment is a structural determinant of health. Here we reveal spatially heterogeneous associations of built environment indicators with objective health outcomes (morbidity) by combining a random forest (RF) approach and a multiscale geographically weighted (MGWR) regression method. Using data from six Japanese cities, we found that the ratio of morbidity has obvious spatial agglomerations. The mixed land-use diversity with 1000 m buffer, distance to hospital, proportion of park area with 300 m buffer, and house price with 2000 m buffer, negatively affect health outcomes at all locations. For most locations, high PM2.5 or high floor area ratio with 2000 m buffer are linked to a high ratio of morbidity. Our findings support the use of such data for long-term urban and health planning. We expect our study to be a starting point for further research on spatially heterogeneous associations of the built environment with comprehensive health outcomes. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|