Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering

[EN] Research on occupational accidents is a key factor in improving working conditions and sustainability. Fatal accidents incur significant human and economic costs. Therefore, it is essential to examine fatal accidents to identify the factors that contribute to their occurrence. This study presen...

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Autores: Sánchez-Lite, Alberto, Iglesias, Iván, González-Gaya, Cristina, Fuentes Bargues, José Luis|||0000-0003-4877-3291
Tipo de documento: artigo
Data de publicação:2024
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositório:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglês
OAI Identifier:oai:riunet.upv.es:10251/220295
Acesso em linha:https://riunet.upv.es/handle/10251/220295
Access Level:Acceso aberto
Palavra-chave:Occupational accidents
Fatal accidents
Human and economic costs
Heart attack accidents
Workplace classification model
Occupational safety
Health engineering
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos
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repository_id_str
spelling Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineeringSánchez-Lite, AlbertoIglesias, IvánGonzález-Gaya, CristinaFuentes Bargues, José Luis|||0000-0003-4877-3291Occupational accidentsFatal accidentsHuman and economic costsHeart attack accidentsWorkplace classification modelOccupational safetyHealth engineering03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos[EN] Research on occupational accidents is a key factor in improving working conditions and sustainability. Fatal accidents incur significant human and economic costs. Therefore, it is essential to examine fatal accidents to identify the factors that contribute to their occurrence. This study presents an overview of fatal heart attack accidents at work in Spain over the period 2009¿2021. Descriptive analysis was conducted considering 13 variables classified into five groups. These variables were selected as predictors to determine the occurrence of this type of accident using a machine learning technique. Thirteen Naïve Bayes prediction models were developed using an unbalanced dataset of 15,616 valid samples from the Spanish Del ta@database, employing a two-stage algorithm. The final model was retained using a General Performance Score index. The model selected for this study used a 70:30 distribution for the training and test datasets. A sample was classified as a fatal heart attack if its posterior probability exceeded 0.25. This model is assumed to be a compromise between the confusion matrix values of each model. Sectors with the highest number of heart attacks are `Health and social work¿, `Transport and storage¿, `Manufacturing¿, and `Construction¿. The incidence of heart attacks and fatal heart attack accidents is higher in men than in women and higher in private sector employees. The findings and model development may assist in the formulation of surveillance strategies and preventive measures to reduce the incidence of heart attacks in the workplace.ElsevierDepartamento de Proyectos de IngenieríaCentro de Investigación en Dirección de Proyectos, Innovación y Sostenibilidad (PRINS)Escuela Técnica Superior de Ingeniería IndustrialRepositorio Institucional de la Universitat Politècnica de València Riunet20242024-09-30journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/220295reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2202952026-06-13T07:49:27Z
dc.title.none.fl_str_mv Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
title Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
spellingShingle Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
Sánchez-Lite, Alberto
Occupational accidents
Fatal accidents
Human and economic costs
Heart attack accidents
Workplace classification model
Occupational safety
Health engineering
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos
title_short Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
title_full Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
title_fullStr Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
title_full_unstemmed Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
title_sort Proposal of a workplace classification model for heart attack accidents from the field of occupational safety and health engineering
dc.creator.none.fl_str_mv Sánchez-Lite, Alberto
Iglesias, Iván
González-Gaya, Cristina
Fuentes Bargues, José Luis|||0000-0003-4877-3291
author Sánchez-Lite, Alberto
author_facet Sánchez-Lite, Alberto
Iglesias, Iván
González-Gaya, Cristina
Fuentes Bargues, José Luis|||0000-0003-4877-3291
author_role author
author2 Iglesias, Iván
González-Gaya, Cristina
Fuentes Bargues, José Luis|||0000-0003-4877-3291
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Proyectos de Ingeniería
Centro de Investigación en Dirección de Proyectos, Innovación y Sostenibilidad (PRINS)
Escuela Técnica Superior de Ingeniería Industrial
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Occupational accidents
Fatal accidents
Human and economic costs
Heart attack accidents
Workplace classification model
Occupational safety
Health engineering
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos
topic Occupational accidents
Fatal accidents
Human and economic costs
Heart attack accidents
Workplace classification model
Occupational safety
Health engineering
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos
description [EN] Research on occupational accidents is a key factor in improving working conditions and sustainability. Fatal accidents incur significant human and economic costs. Therefore, it is essential to examine fatal accidents to identify the factors that contribute to their occurrence. This study presents an overview of fatal heart attack accidents at work in Spain over the period 2009¿2021. Descriptive analysis was conducted considering 13 variables classified into five groups. These variables were selected as predictors to determine the occurrence of this type of accident using a machine learning technique. Thirteen Naïve Bayes prediction models were developed using an unbalanced dataset of 15,616 valid samples from the Spanish Del ta@database, employing a two-stage algorithm. The final model was retained using a General Performance Score index. The model selected for this study used a 70:30 distribution for the training and test datasets. A sample was classified as a fatal heart attack if its posterior probability exceeded 0.25. This model is assumed to be a compromise between the confusion matrix values of each model. Sectors with the highest number of heart attacks are `Health and social work¿, `Transport and storage¿, `Manufacturing¿, and `Construction¿. The incidence of heart attacks and fatal heart attack accidents is higher in men than in women and higher in private sector employees. The findings and model development may assist in the formulation of surveillance strategies and preventive measures to reduce the incidence of heart attacks in the workplace.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-09-30
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/220295
url https://riunet.upv.es/handle/10251/220295
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,223283

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