A spatial vulnerability index for environmental health
Extreme natural hazards are increasing in frequency and intensity. These natural changes in our environment, combined with man-made pollution, have substantial economic, social and health impacts globally. The impact of the environment on human health (environmental health) is becoming well understo...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X2500723X |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1839626698170040320 |
|---|---|
| author | Aiden Price Michael Rigby Paula Fiévez Kerrie Mengersen |
| author_facet | Aiden Price Michael Rigby Paula Fiévez Kerrie Mengersen |
| author_sort | Aiden Price |
| collection | DOAJ |
| description | Extreme natural hazards are increasing in frequency and intensity. These natural changes in our environment, combined with man-made pollution, have substantial economic, social and health impacts globally. The impact of the environment on human health (environmental health) is becoming well understood in international research literature. However, there are significant barriers to understanding key characteristics of this impact, related to substantial data volumes, data access rights and the time required to compile and compare data over regions and time.This study develops a replicable method for constructing vulnerability indices weighted by observed all-cause mortality and applies it to three environmental hazards: extreme heat, extreme cold, and air pollution. Indices were produced across multiple spatial (SA2, SA3, SA4, LGA) and temporal (weekly, monthly, yearly) resolutions, allowing fine-grained analysis of population vulnerability over time and space. We compare the mortality-weighted indices with equal-weight and principal component analysis (PCA) approaches, which, despite their widespread use, do not directly incorporate or align with observed health outcomes. An index derived using empirical weights based on all-cause mortality will be well-aligned with other positively correlated health outcomes and so increases the generality of the index while reducing the requirements for a comprehensive suite of outcome data which can be difficult to obtain in practice.The mortality-weighted approach improves interpretability relative to methods that optimise statistical variance alone, such as PCA. The inclusion of time-series data and sub-yearly indices further reveal short-term fluctuations in vulnerability that are otherwise obscured in coarser temporal studies. Together, these results support a transparent and scalable framework for identifying population vulnerability and informing targeted public health and climate resilience strategies. |
| format | Article |
| id | doaj-art-dbae5d9abdb64169b818b25fe1b64600 |
| institution | Matheson Library |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-dbae5d9abdb64169b818b25fe1b646002025-07-17T04:44:09ZengElsevierEcological Indicators1470-160X2025-09-01178113793A spatial vulnerability index for environmental healthAiden Price0Michael Rigby1Paula Fiévez2Kerrie Mengersen3Centre for Data Science, Faculty of Science, Queensland University of Technology, Brisbane City, Brisbane, 4000, QLD, Australia; Australian Urban Research Infrastructure Network, University of Melbourne, Parkville, Melbourne, 3052, VIC, Australia; Corresponding author.Australian Urban Research Infrastructure Network, University of Melbourne, Parkville, Melbourne, 3052, VIC, AustraliaFrontierSI, Docklands, Melbourne, 3008, VIC, AustraliaCentre for Data Science, Faculty of Science, Queensland University of Technology, Brisbane City, Brisbane, 4000, QLD, AustraliaExtreme natural hazards are increasing in frequency and intensity. These natural changes in our environment, combined with man-made pollution, have substantial economic, social and health impacts globally. The impact of the environment on human health (environmental health) is becoming well understood in international research literature. However, there are significant barriers to understanding key characteristics of this impact, related to substantial data volumes, data access rights and the time required to compile and compare data over regions and time.This study develops a replicable method for constructing vulnerability indices weighted by observed all-cause mortality and applies it to three environmental hazards: extreme heat, extreme cold, and air pollution. Indices were produced across multiple spatial (SA2, SA3, SA4, LGA) and temporal (weekly, monthly, yearly) resolutions, allowing fine-grained analysis of population vulnerability over time and space. We compare the mortality-weighted indices with equal-weight and principal component analysis (PCA) approaches, which, despite their widespread use, do not directly incorporate or align with observed health outcomes. An index derived using empirical weights based on all-cause mortality will be well-aligned with other positively correlated health outcomes and so increases the generality of the index while reducing the requirements for a comprehensive suite of outcome data which can be difficult to obtain in practice.The mortality-weighted approach improves interpretability relative to methods that optimise statistical variance alone, such as PCA. The inclusion of time-series data and sub-yearly indices further reveal short-term fluctuations in vulnerability that are otherwise obscured in coarser temporal studies. Together, these results support a transparent and scalable framework for identifying population vulnerability and informing targeted public health and climate resilience strategies.http://www.sciencedirect.com/science/article/pii/S1470160X2500723XEnvironmental healthVulnerability indexAir pollutionExtreme heatSpatial dataHealth outcomes |
| spellingShingle | Aiden Price Michael Rigby Paula Fiévez Kerrie Mengersen A spatial vulnerability index for environmental health Ecological Indicators Environmental health Vulnerability index Air pollution Extreme heat Spatial data Health outcomes |
| title | A spatial vulnerability index for environmental health |
| title_full | A spatial vulnerability index for environmental health |
| title_fullStr | A spatial vulnerability index for environmental health |
| title_full_unstemmed | A spatial vulnerability index for environmental health |
| title_short | A spatial vulnerability index for environmental health |
| title_sort | spatial vulnerability index for environmental health |
| topic | Environmental health Vulnerability index Air pollution Extreme heat Spatial data Health outcomes |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X2500723X |
| work_keys_str_mv | AT aidenprice aspatialvulnerabilityindexforenvironmentalhealth AT michaelrigby aspatialvulnerabilityindexforenvironmentalhealth AT paulafievez aspatialvulnerabilityindexforenvironmentalhealth AT kerriemengersen aspatialvulnerabilityindexforenvironmentalhealth AT aidenprice spatialvulnerabilityindexforenvironmentalhealth AT michaelrigby spatialvulnerabilityindexforenvironmentalhealth AT paulafievez spatialvulnerabilityindexforenvironmentalhealth AT kerriemengersen spatialvulnerabilityindexforenvironmentalhealth |