Occupational Mortality Matrix: A Tool for Epidemiological Assessment of Work-Related Risk Based on Current Data Sources
Mortality from occupational diseases significantly afflicts society, in terms of both economic costs and human suffering. The International Labour Organization (ILO) estimated that 2.4 million workers die from work-related diseases every year. In Europe, around 80,000 workers die from cancer attribu...
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| Published in | International journal of environmental research and public health Vol. 19; no. 9; p. 5652 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Switzerland
MDPI AG
06.05.2022
MDPI |
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| Online Access | Get full text |
| ISSN | 1660-4601 1661-7827 1660-4601 |
| DOI | 10.3390/ijerph19095652 |
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| Abstract | Mortality from occupational diseases significantly afflicts society, in terms of both economic costs and human suffering. The International Labour Organization (ILO) estimated that 2.4 million workers die from work-related diseases every year. In Europe, around 80,000 workers die from cancer attributed to occupational exposure to carcinogens. This study developed the Occupational Mortality Matrix (OMM) aimed to identify significant associations between causes of death and occupational sectors through an individual record linkage between mortality data and the administrative archive of occupational histories. The study population consisted of 6,433,492 deceased subjects in Italy (in the period 2005–2015), of which 2,723,152 records of work histories were retrieved (42%). The proportional mortality ratio (PMR) was estimated to investigate the excess of mortality for specific causes associated with occupational sectors. Higher PMRs were reported for traditionally risky occupations such as shipbuilding for mesothelioma cases (PMR: 8.15; 95% CI: 7.28–9.13) and leather production for sino-nasal cancer (PMR: 5.04; 95% CI: 3.54–7.19), as well as for unexpected risks such as male breast cancer in the pharmaceutical industry (PMR: 2.56; 95% CI: 1.33–4.93) and brain cancer in railways (PMR: 1.43; 95% CI: 1.24–1.66). The OMM proved to be a valid tool for research studies to generate hypotheses about the occupational etiology of diseases, and to monitor and support priority actions for risk reduction in workplaces. |
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| AbstractList | Mortality from occupational diseases significantly afflicts society, in terms of both economic costs and human suffering. The International Labour Organization (ILO) estimated that 2.4 million workers die from work-related diseases every year. In Europe, around 80,000 workers die from cancer attributed to occupational exposure to carcinogens. This study developed the Occupational Mortality Matrix (OMM) aimed to identify significant associations between causes of death and occupational sectors through an individual record linkage between mortality data and the administrative archive of occupational histories. The study population consisted of 6,433,492 deceased subjects in Italy (in the period 2005–2015), of which 2,723,152 records of work histories were retrieved (42%). The proportional mortality ratio (PMR) was estimated to investigate the excess of mortality for specific causes associated with occupational sectors. Higher PMRs were reported for traditionally risky occupations such as shipbuilding for mesothelioma cases (PMR: 8.15; 95% CI: 7.28–9.13) and leather production for sino-nasal cancer (PMR: 5.04; 95% CI: 3.54–7.19), as well as for unexpected risks such as male breast cancer in the pharmaceutical industry (PMR: 2.56; 95% CI: 1.33–4.93) and brain cancer in railways (PMR: 1.43; 95% CI: 1.24–1.66). The OMM proved to be a valid tool for research studies to generate hypotheses about the occupational etiology of diseases, and to monitor and support priority actions for risk reduction in workplaces. Mortality from occupational diseases significantly afflicts society, in terms of both economic costs and human suffering. The International Labour Organization (ILO) estimated that 2.4 million workers die from work-related diseases every year. In Europe, around 80,000 workers die from cancer attributed to occupational exposure to carcinogens. This study developed the Occupational Mortality Matrix (OMM) aimed to identify significant associations between causes of death and occupational sectors through an individual record linkage between mortality data and the administrative archive of occupational histories. The study population consisted of 6,433,492 deceased subjects in Italy (in the period 2005-2015), of which 2,723,152 records of work histories were retrieved (42%). The proportional mortality ratio (PMR) was estimated to investigate the excess of mortality for specific causes associated with occupational sectors. Higher PMRs were reported for traditionally risky occupations such as shipbuilding for mesothelioma cases (PMR: 8.15; 95% CI: 7.28-9.13) and leather production for sino-nasal cancer (PMR: 5.04; 95% CI: 3.54-7.19), as well as for unexpected risks such as male breast cancer in the pharmaceutical industry (PMR: 2.56; 95% CI: 1.33-4.93) and brain cancer in railways (PMR: 1.43; 95% CI: 1.24-1.66). The OMM proved to be a valid tool for research studies to generate hypotheses about the occupational etiology of diseases, and to monitor and support priority actions for risk reduction in workplaces.Mortality from occupational diseases significantly afflicts society, in terms of both economic costs and human suffering. The International Labour Organization (ILO) estimated that 2.4 million workers die from work-related diseases every year. In Europe, around 80,000 workers die from cancer attributed to occupational exposure to carcinogens. This study developed the Occupational Mortality Matrix (OMM) aimed to identify significant associations between causes of death and occupational sectors through an individual record linkage between mortality data and the administrative archive of occupational histories. The study population consisted of 6,433,492 deceased subjects in Italy (in the period 2005-2015), of which 2,723,152 records of work histories were retrieved (42%). The proportional mortality ratio (PMR) was estimated to investigate the excess of mortality for specific causes associated with occupational sectors. Higher PMRs were reported for traditionally risky occupations such as shipbuilding for mesothelioma cases (PMR: 8.15; 95% CI: 7.28-9.13) and leather production for sino-nasal cancer (PMR: 5.04; 95% CI: 3.54-7.19), as well as for unexpected risks such as male breast cancer in the pharmaceutical industry (PMR: 2.56; 95% CI: 1.33-4.93) and brain cancer in railways (PMR: 1.43; 95% CI: 1.24-1.66). The OMM proved to be a valid tool for research studies to generate hypotheses about the occupational etiology of diseases, and to monitor and support priority actions for risk reduction in workplaces. |
| Author | Malpassuti, Vittoria Carolina Binazzi, Alessandra Paris, Lorena Marinaccio, Alessandro Massari, Stefania Gariazzo, Claudio |
| AuthorAffiliation | 2 Department of Statistical Sciences, University of Rome La Sapienza, 00161 Rome, Italy; vittoriacarolina.malpassuti@uniroma1.it 1 Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy; a.binazzi@inail.it (A.B.); l.paris@inail.it (L.P.); c.gariazzo@inail.it (C.G.); a.marinaccio@inail.it (A.M.) |
| AuthorAffiliation_xml | – name: 1 Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Italian National Institute for Insurance against Accidents at Work (INAIL), 00143 Rome, Italy; a.binazzi@inail.it (A.B.); l.paris@inail.it (L.P.); c.gariazzo@inail.it (C.G.); a.marinaccio@inail.it (A.M.) – name: 2 Department of Statistical Sciences, University of Rome La Sapienza, 00161 Rome, Italy; vittoriacarolina.malpassuti@uniroma1.it |
| Author_xml | – sequence: 1 givenname: Stefania orcidid: 0000-0001-6364-2471 surname: Massari fullname: Massari, Stefania – sequence: 2 givenname: Vittoria Carolina surname: Malpassuti fullname: Malpassuti, Vittoria Carolina – sequence: 3 givenname: Alessandra orcidid: 0000-0002-0435-600X surname: Binazzi fullname: Binazzi, Alessandra – sequence: 4 givenname: Lorena surname: Paris fullname: Paris, Lorena – sequence: 5 givenname: Claudio orcidid: 0000-0003-2287-6364 surname: Gariazzo fullname: Gariazzo, Claudio – sequence: 6 givenname: Alessandro orcidid: 0000-0001-9068-2137 surname: Marinaccio fullname: Marinaccio, Alessandro |
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| CitedBy_id | crossref_primary_10_3390_ijerph20105767 crossref_primary_10_1097_JOM_0000000000003114 crossref_primary_10_3390_cancers16112053 crossref_primary_10_1186_s12889_025_21328_z crossref_primary_10_3390_cancers15082234 crossref_primary_10_1097_CEJ_0000000000000786 |
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| ContentType | Journal Article |
| Copyright | 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2022 by the authors. 2022 |
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| SubjectTerms | Age Archives & records Brain cancer Cancer Economic activity Employment Estimates GDP Gender Generalized linear models Gross Domestic Product Head & neck cancer Information systems Mens health Mortality Occupational diseases Population Risk factors Statistical analysis Tumors Workers |
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| Title | Occupational Mortality Matrix: A Tool for Epidemiological Assessment of Work-Related Risk Based on Current Data Sources |
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