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Decision support for risk prioritisation of environmental health hazards in a UK city

BACKGROUND: There is increasing appreciation of the proportion of the health burden that is attributed to modifiable population exposure to environmental health hazards. To manage this avoidable burden in the United Kingdom (UK), government policies and interventions are implemented. In practice, th...

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Autores principales: Woods, Mae, Crabbe, Helen, Close, Rebecca, Studden, Mike, Milojevic, Ai, Leonardi, Giovanni, Fletcher, Tony, Chalabi, Zaid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895771/
https://www.ncbi.nlm.nih.gov/pubmed/26961184
http://dx.doi.org/10.1186/s12940-016-0099-y
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author Woods, Mae
Crabbe, Helen
Close, Rebecca
Studden, Mike
Milojevic, Ai
Leonardi, Giovanni
Fletcher, Tony
Chalabi, Zaid
author_facet Woods, Mae
Crabbe, Helen
Close, Rebecca
Studden, Mike
Milojevic, Ai
Leonardi, Giovanni
Fletcher, Tony
Chalabi, Zaid
author_sort Woods, Mae
collection PubMed
description BACKGROUND: There is increasing appreciation of the proportion of the health burden that is attributed to modifiable population exposure to environmental health hazards. To manage this avoidable burden in the United Kingdom (UK), government policies and interventions are implemented. In practice, this procedure is interdisciplinary in action and multi-dimensional in context. Here, we demonstrate how Multi Criteria Decision Analysis (MCDA) can be used as a decision support tool to facilitate priority setting for environmental public health interventions within local authorities. We combine modelling and expert elicitation to gather evidence on the impacts and ranking of interventions. METHODS: To present the methodology, we consider a hypothetical scenario in a UK city. We use MCDA to evaluate and compare the impact of interventions to reduce the health burden associated with four environmental health hazards and rank them in terms of their overall performance across several criteria. For illustrative purposes, we focus on heavy goods vehicle controls to reduce outdoor air pollution, remediation to control levels of indoor radon, carbon monoxide and fitting alarms, and encouraging cycling to target the obesogenic environment. Regional data was included as model evidence to construct a ratings matrix for the city. RESULTS: When MCDA is performed with uniform weights, the intervention of heavy goods vehicle controls to reduce outdoor air pollution is ranked the highest. Cycling and the obesogenic environment is ranked second. CONCLUSIONS: We argue that a MCDA based approach provides a framework to guide environmental public health decision makers. This is demonstrated through an online interactive MCDA tool. We conclude that MCDA is a transparent tool that can be used to compare the impact of alternative interventions on a set of pre-defined criteria. In our illustrative example, we ranked the best intervention across the equally weighted selected criteria out of the four alternatives. Further work is needed to test the tool with decision makers and stakeholders. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12940-016-0099-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-48957712016-06-10 Decision support for risk prioritisation of environmental health hazards in a UK city Woods, Mae Crabbe, Helen Close, Rebecca Studden, Mike Milojevic, Ai Leonardi, Giovanni Fletcher, Tony Chalabi, Zaid Environ Health Research BACKGROUND: There is increasing appreciation of the proportion of the health burden that is attributed to modifiable population exposure to environmental health hazards. To manage this avoidable burden in the United Kingdom (UK), government policies and interventions are implemented. In practice, this procedure is interdisciplinary in action and multi-dimensional in context. Here, we demonstrate how Multi Criteria Decision Analysis (MCDA) can be used as a decision support tool to facilitate priority setting for environmental public health interventions within local authorities. We combine modelling and expert elicitation to gather evidence on the impacts and ranking of interventions. METHODS: To present the methodology, we consider a hypothetical scenario in a UK city. We use MCDA to evaluate and compare the impact of interventions to reduce the health burden associated with four environmental health hazards and rank them in terms of their overall performance across several criteria. For illustrative purposes, we focus on heavy goods vehicle controls to reduce outdoor air pollution, remediation to control levels of indoor radon, carbon monoxide and fitting alarms, and encouraging cycling to target the obesogenic environment. Regional data was included as model evidence to construct a ratings matrix for the city. RESULTS: When MCDA is performed with uniform weights, the intervention of heavy goods vehicle controls to reduce outdoor air pollution is ranked the highest. Cycling and the obesogenic environment is ranked second. CONCLUSIONS: We argue that a MCDA based approach provides a framework to guide environmental public health decision makers. This is demonstrated through an online interactive MCDA tool. We conclude that MCDA is a transparent tool that can be used to compare the impact of alternative interventions on a set of pre-defined criteria. In our illustrative example, we ranked the best intervention across the equally weighted selected criteria out of the four alternatives. Further work is needed to test the tool with decision makers and stakeholders. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12940-016-0099-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-08 /pmc/articles/PMC4895771/ /pubmed/26961184 http://dx.doi.org/10.1186/s12940-016-0099-y Text en © Woods et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Woods, Mae
Crabbe, Helen
Close, Rebecca
Studden, Mike
Milojevic, Ai
Leonardi, Giovanni
Fletcher, Tony
Chalabi, Zaid
Decision support for risk prioritisation of environmental health hazards in a UK city
title Decision support for risk prioritisation of environmental health hazards in a UK city
title_full Decision support for risk prioritisation of environmental health hazards in a UK city
title_fullStr Decision support for risk prioritisation of environmental health hazards in a UK city
title_full_unstemmed Decision support for risk prioritisation of environmental health hazards in a UK city
title_short Decision support for risk prioritisation of environmental health hazards in a UK city
title_sort decision support for risk prioritisation of environmental health hazards in a uk city
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895771/
https://www.ncbi.nlm.nih.gov/pubmed/26961184
http://dx.doi.org/10.1186/s12940-016-0099-y
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