Bibliographic Details
| Title: |
Identifying the healthy places to live in Australia with a new environmental quality health index |
| Authors: |
Shuang Zhou, Zhihu Xu, Wenzhong Huang, Yao Wu, Rongbin Xu, Zhengyu Yang, Pei Yu, Wenhua Yu, Tingting Ye, Bo Wen, Shanshan Li, Yuming Guo |
| Source: |
Environment International, Vol 195, Iss , Pp 109268- (2025) |
| Publisher Information: |
Elsevier, 2025. |
| Publication Year: |
2025 |
| Collection: |
LCC:Environmental sciences |
| Subject Terms: |
New environmental quality health index, Environmental exposure, Socio-economic factors, Health risk, Environmental sciences, GE1-350 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
0160-4120 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S0160412025000194; https://doaj.org/toc/0160-4120 |
| DOI: |
10.1016/j.envint.2025.109268 |
| Access URL: |
https://doaj.org/article/ae49b7e2f447480884b291763b6a3ba4 |
| Accession Number: |
edsdoj.49b7e2f447480884b291763b6a3ba4 |
| Database: |
Directory of Open Access Journals |
