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Use of GIS in visualization of work-related health problems
BACKGROUND: Occupational health and safety (OHS) information is often complex, diverse and unstructured and suffers from a lack of integration which usually precludes any systemic insight of the situation. AIMS: To analyse to what extent the use of geographical information systems (GISs) can help to...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4661781/ https://www.ncbi.nlm.nih.gov/pubmed/26503981 http://dx.doi.org/10.1093/occmed/kqv152 |
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author | Delaunay, M. Van der Westhuizen, H. Godard, V. Agius, R. Le Barbier, M. Godderis, L. Bonneterre, V. |
author_facet | Delaunay, M. Van der Westhuizen, H. Godard, V. Agius, R. Le Barbier, M. Godderis, L. Bonneterre, V. |
author_sort | Delaunay, M. |
collection | PubMed |
description | BACKGROUND: Occupational health and safety (OHS) information is often complex, diverse and unstructured and suffers from a lack of integration which usually precludes any systemic insight of the situation. AIMS: To analyse to what extent the use of geographical information systems (GISs) can help to integrate, analyse and present OHS data in a comprehensive and communicable way relevant for surveillance purposes. METHODS: We first developed a ‘macro-approach’ (from national to local level), mapping data related to economic activity (denominator of active workers displayed by activity sectors), as well as work-related ill-health (numerators of workers suffering from work-related ill-health). The latter data are composed of compensated occupational diseases on the one hand and work-related diseases investigated by specialized clinics on the other hand. Then, a ‘micro-approach’ was worked out, integrating at a plant level, using computer-aided drawing, occupational risks data and OHS surveillance data (e.g. use of medication and sickness absence data). RESULTS: At the macro-level, microelectronics companies and workers were mapped at different scales. For the first time, we were able to compare, up to the enterprise level, complementary data showing different pictures of work-related ill-health, allowing a better understanding of OH issues in this sector. At the micro-level, new information arose from the integration of risk assessment data and medical data. CONCLUSIONS: This work illustrates to what extent GIS is a promising tool in the OHS field, and discusses related challenges (technical, ethical, biases and interpretation) and research perspectives. |
format | Online Article Text |
id | pubmed-4661781 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-46617812015-11-30 Use of GIS in visualization of work-related health problems Delaunay, M. Van der Westhuizen, H. Godard, V. Agius, R. Le Barbier, M. Godderis, L. Bonneterre, V. Occup Med (Lond) Original Paper BACKGROUND: Occupational health and safety (OHS) information is often complex, diverse and unstructured and suffers from a lack of integration which usually precludes any systemic insight of the situation. AIMS: To analyse to what extent the use of geographical information systems (GISs) can help to integrate, analyse and present OHS data in a comprehensive and communicable way relevant for surveillance purposes. METHODS: We first developed a ‘macro-approach’ (from national to local level), mapping data related to economic activity (denominator of active workers displayed by activity sectors), as well as work-related ill-health (numerators of workers suffering from work-related ill-health). The latter data are composed of compensated occupational diseases on the one hand and work-related diseases investigated by specialized clinics on the other hand. Then, a ‘micro-approach’ was worked out, integrating at a plant level, using computer-aided drawing, occupational risks data and OHS surveillance data (e.g. use of medication and sickness absence data). RESULTS: At the macro-level, microelectronics companies and workers were mapped at different scales. For the first time, we were able to compare, up to the enterprise level, complementary data showing different pictures of work-related ill-health, allowing a better understanding of OH issues in this sector. At the micro-level, new information arose from the integration of risk assessment data and medical data. CONCLUSIONS: This work illustrates to what extent GIS is a promising tool in the OHS field, and discusses related challenges (technical, ethical, biases and interpretation) and research perspectives. Oxford University Press 2015-11 2015-10-23 /pmc/articles/PMC4661781/ /pubmed/26503981 http://dx.doi.org/10.1093/occmed/kqv152 Text en © The Author 2015. Published by Oxford University Press on behalf of the Society of Occupational Medicine. http://creativecommons.org/licenses/by-nc/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Paper Delaunay, M. Van der Westhuizen, H. Godard, V. Agius, R. Le Barbier, M. Godderis, L. Bonneterre, V. Use of GIS in visualization of work-related health problems |
title | Use of GIS in visualization of work-related health problems |
title_full | Use of GIS in visualization of work-related health problems |
title_fullStr | Use of GIS in visualization of work-related health problems |
title_full_unstemmed | Use of GIS in visualization of work-related health problems |
title_short | Use of GIS in visualization of work-related health problems |
title_sort | use of gis in visualization of work-related health problems |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4661781/ https://www.ncbi.nlm.nih.gov/pubmed/26503981 http://dx.doi.org/10.1093/occmed/kqv152 |
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