Identifying the healthy places to live in Australia with a new environmental quality health index
Background: Existing environmental quality indices often fail to account for the varying health impacts of different exposures and exclude socio-economic status indicators (SES). Objectives: To develop and validate a comprehensive Environmental Quality Health Index (EQHI) that integrates multiple en...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Environment International |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412025000194 |
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| author | Shuang Zhou Zhihu Xu Wenzhong Huang Yao Wu Rongbin Xu Zhengyu Yang Pei Yu Wenhua Yu Tingting Ye Bo Wen Shanshan Li Yuming Guo |
| author_facet | Shuang Zhou Zhihu Xu Wenzhong Huang Yao Wu Rongbin Xu Zhengyu Yang Pei Yu Wenhua Yu Tingting Ye Bo Wen Shanshan Li Yuming Guo |
| author_sort | Shuang Zhou |
| collection | DOAJ |
| description | Background: Existing environmental quality indices often fail to account for the varying health impacts of different exposures and exclude socio-economic status indicators (SES). Objectives: To develop and validate a comprehensive Environmental Quality Health Index (EQHI) that integrates multiple environmental exposures and SES to assess mortality risks across Australia. Methods: We combined all-cause, cardiovascular, and respiratory mortality data (2016–2019) from 2,180 Statistical Areas Level 2 with annual mean values of 12 environmental exposures, including PM2.5, ozone, temperature, humidity, normalized difference vegetation index, night light, road and building density, and socioeconomic status. Exposure-mortality relationships were estimated using a spatial age-period-cohort model, and EQHIs (scored 0–100, with higher values indicating better conditions) were constructed. Validation was performed using K-fold cross-validation and spatial regression models. Results: Validation showed strong model performance (R-squared = 83.53 %, 75.55 %, and 52.44 % for EQHI-all cause, EQHI-CVD, and EQHI-Resp). Each interquartile increase in EQHI-all cause reduced all-cause mortality risk by 10 %, with similar reductions for cardiovascular and respiratory mortality. Geographically, EQHIs were higher in south, east, and southeast coastal regions. From 2016 to 2019, SA2s with the highest EQHI (>75) decreased from 27.1 % to 21.1 %. The population weighted EQHI was highest in Hobart and lowest in Darwin. Conclusions: We established, to our knowledge, the first tool to quantify and communicate environmental health risks using three types of mortality data and 12 environmental factors. This EQHI provides a robust framework to assess environmental health risks and guide targeted interventions. Our methodology can be adapted globally to standardize risk evaluation. |
| format | Article |
| id | doaj-art-ae49b7e2f447480884b291763b6a3ba4 |
| institution | Kabale University |
| issn | 0160-4120 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj-art-ae49b7e2f447480884b291763b6a3ba42025-01-24T04:44:17ZengElsevierEnvironment International0160-41202025-01-01195109268Identifying the healthy places to live in Australia with a new environmental quality health indexShuang Zhou0Zhihu Xu1Wenzhong Huang2Yao Wu3Rongbin Xu4Zhengyu Yang5Pei Yu6Wenhua Yu7Tingting Ye8Bo Wen9Shanshan Li10Yuming Guo11Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaCorresponding author at: Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University. Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia.; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaBackground: Existing environmental quality indices often fail to account for the varying health impacts of different exposures and exclude socio-economic status indicators (SES). Objectives: To develop and validate a comprehensive Environmental Quality Health Index (EQHI) that integrates multiple environmental exposures and SES to assess mortality risks across Australia. Methods: We combined all-cause, cardiovascular, and respiratory mortality data (2016–2019) from 2,180 Statistical Areas Level 2 with annual mean values of 12 environmental exposures, including PM2.5, ozone, temperature, humidity, normalized difference vegetation index, night light, road and building density, and socioeconomic status. Exposure-mortality relationships were estimated using a spatial age-period-cohort model, and EQHIs (scored 0–100, with higher values indicating better conditions) were constructed. Validation was performed using K-fold cross-validation and spatial regression models. Results: Validation showed strong model performance (R-squared = 83.53 %, 75.55 %, and 52.44 % for EQHI-all cause, EQHI-CVD, and EQHI-Resp). Each interquartile increase in EQHI-all cause reduced all-cause mortality risk by 10 %, with similar reductions for cardiovascular and respiratory mortality. Geographically, EQHIs were higher in south, east, and southeast coastal regions. From 2016 to 2019, SA2s with the highest EQHI (>75) decreased from 27.1 % to 21.1 %. The population weighted EQHI was highest in Hobart and lowest in Darwin. Conclusions: We established, to our knowledge, the first tool to quantify and communicate environmental health risks using three types of mortality data and 12 environmental factors. This EQHI provides a robust framework to assess environmental health risks and guide targeted interventions. Our methodology can be adapted globally to standardize risk evaluation.http://www.sciencedirect.com/science/article/pii/S0160412025000194New environmental quality health indexEnvironmental exposureSocio-economic factorsHealth risk |
| spellingShingle | Shuang Zhou Zhihu Xu Wenzhong Huang Yao Wu Rongbin Xu Zhengyu Yang Pei Yu Wenhua Yu Tingting Ye Bo Wen Shanshan Li Yuming Guo Identifying the healthy places to live in Australia with a new environmental quality health index Environment International New environmental quality health index Environmental exposure Socio-economic factors Health risk |
| title | Identifying the healthy places to live in Australia with a new environmental quality health index |
| title_full | Identifying the healthy places to live in Australia with a new environmental quality health index |
| title_fullStr | Identifying the healthy places to live in Australia with a new environmental quality health index |
| title_full_unstemmed | Identifying the healthy places to live in Australia with a new environmental quality health index |
| title_short | Identifying the healthy places to live in Australia with a new environmental quality health index |
| title_sort | identifying the healthy places to live in australia with a new environmental quality health index |
| topic | New environmental quality health index Environmental exposure Socio-economic factors Health risk |
| url | http://www.sciencedirect.com/science/article/pii/S0160412025000194 |
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