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Louro H, Gomes BC, Saber AT, Iamiceli AL, Göen T, Jones K, Katsonouri A, Neophytou CM, Vogel U, Ventura C, Oberemm A, Duca RC, Fernandez MF, Olea N, Santonen T, Viegas S, Silva MJ. The Use of Human Biomonitoring to Assess Occupational Exposure to PAHs in Europe: A Comprehensive Review. TOXICS 2022; 10:toxics10080480. [PMID: 36006159 PMCID: PMC9414426 DOI: 10.3390/toxics10080480] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/05/2022] [Accepted: 08/13/2022] [Indexed: 06/02/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are among the chemicals with proven impact on workers' health. The use of human biomonitoring (HBM) to assess occupational exposure to PAHs has become more common in recent years, but the data generated need an overall view to make them more usable by regulators and policymakers. This comprehensive review, developed under the Human Biomonitoring for Europe (HBM4EU) Initiative, was based on the literature available from 2008-2022, aiming to present and discuss the information on occupational exposure to PAHs, in order to identify the strengths and limitations of exposure and effect biomarkers and the knowledge needs for regulation in the workplace. The most frequently used exposure biomarker is urinary 1-hydroxypyrene (1-OH-PYR), a metabolite of pyrene. As effect biomarkers, those based on the measurement of oxidative stress (urinary 8-oxo-dG adducts) and genotoxicity (blood DNA strand-breaks) are the most common. Overall, a need to advance new harmonized approaches both in data and sample collection and in the use of appropriate biomarkers in occupational studies to obtain reliable and comparable data on PAH exposure in different industrial sectors, was noted. Moreover, the use of effect biomarkers can assist to identify work environments or activities of high risk, thus enabling preventive risk mitigation and management measures.
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Affiliation(s)
- Henriqueta Louro
- Department of Human Genetics, National Institute of Health Dr. Ricardo Jorge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal
- Centre for Toxicogenomics and Human Health (ToxOmics), Nova Medical School, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria, 130, 1169-056 Lisbon, Portugal
| | - Bruno Costa Gomes
- Department of Human Genetics, National Institute of Health Dr. Ricardo Jorge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal
- Centre for Toxicogenomics and Human Health (ToxOmics), Nova Medical School, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria, 130, 1169-056 Lisbon, Portugal
| | - Anne Thoustrup Saber
- National Research Centre for the Working Environment, DK-2100 Copenhagen, Denmark
| | | | - Thomas Göen
- IPASUM, Institute and Outpatient Clinic of Occupational, Social and Environmental Medicine, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Kate Jones
- Health and Safety Executive, Buxton, Derbyshire SK17 9JN, UK
| | - Andromachi Katsonouri
- Cyprus State General Laboratory, Ministry of Health, P.O. Box 28648, Nicosia 2081, Cyprus
| | - Christiana M. Neophytou
- Cyprus State General Laboratory, Ministry of Health, P.O. Box 28648, Nicosia 2081, Cyprus
- Department of Life Sciences, European University Cyprus, Nicosia 2404, Cyprus
| | - Ulla Vogel
- National Research Centre for the Working Environment, DK-2100 Copenhagen, Denmark
- National Food Institute, Technical University of Denmark, Kemitorvet, Bygning 202, DK-2800 Kgs Lyngby, Denmark
| | - Célia Ventura
- Department of Human Genetics, National Institute of Health Dr. Ricardo Jorge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal
- Centre for Toxicogenomics and Human Health (ToxOmics), Nova Medical School, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria, 130, 1169-056 Lisbon, Portugal
| | - Axel Oberemm
- German Federal Institute for Risk Assessment, Max-Dohrn-Straße 8-10, 10589 Berlin, Germany
| | - Radu Corneliu Duca
- Unit Environmental Hygiene and Human Biological Monitoring, Department of Health Protection, Laboratoire National de Santé (LNS), 1, Rue Louis Rech, 3555 Dudelange, Luxembourg
- Centre for Environment and Health, Department of Public Health and Primary Care, KU Leuven (University of Leuven), O&N 5b, Herestraat 49, 3000 Leuven, Belgium
| | - Mariana F. Fernandez
- Centre of Biomedical Research (CIBM), University of Granada, 18016 Granada, Spain
- Biosanitary Research Institute of Granada (ibs.GRANADA), 18012 Granada, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
| | - Nicolas Olea
- Centre of Biomedical Research (CIBM), University of Granada, 18016 Granada, Spain
- Biosanitary Research Institute of Granada (ibs.GRANADA), 18012 Granada, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
| | - Tiina Santonen
- Finnish Institute of Occupational Health, 00250 Helsinki, Finland
| | - Susana Viegas
- Public Health Research Centre, NOVA National School of Public Health, Universidade NOVA de Lisboa, 1600-560 Lisbon, Portugal
- Comprehensive Health Research Center (CHRC), 1169-056 Lisbon, Portugal
| | - Maria João Silva
- Department of Human Genetics, National Institute of Health Dr. Ricardo Jorge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal
- Centre for Toxicogenomics and Human Health (ToxOmics), Nova Medical School, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria, 130, 1169-056 Lisbon, Portugal
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Morton J, Sams C, Leese E, Garner F, Iqbal S, Jones K. Biological Monitoring: Evidence for Reductions in Occupational Exposure and Risk. FRONTIERS IN TOXICOLOGY 2022; 4:836567. [PMID: 35387427 PMCID: PMC8979160 DOI: 10.3389/ftox.2022.836567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 02/08/2022] [Indexed: 11/13/2022] Open
Abstract
Aims: The aim of this publication is to explore occupational exposure trends from biological monitoring data collected over a period of more than 20 years. The data is stored within the HSE database, which holds more than 950,000 results from 120,000 workers in 8,000 companies. The data were collated for all biological monitoring results for lead, mercury, benzene, and hexamethylene diisocyanate exposures where there have been some regulatory drivers within the reported time period of the data searched.Methods: Relevant results from sample analysed were extracted from the database and categorised by year from 1996 to the end of 2019 for individual blood lead results and individual urine results for mercury, benzene, and hexamethylene diisocyanate. Results were classed by broad occupational sector where possible. Data were reported graphically by analytical biomarker result (as 90th percentile (P90)) and number of samples per year as well as with overall summary statistics. To look at longer-term trends, results were also evaluated as P90 over 6-year periods.Results: In the period 1996–2019, 37,474 blood lead, 11,723 urinary mercury, 9,188 urinary S-phenylmercapturic acid (SPMA, benzene metabolite) and 21,955 urinary hexamethylene diamine (HDA, metabolite of hexamethylene diisocyanate, HDI) samples were analysed and reported. Over the time period the blood lead concentrations saw the P90 reduce from 53 μg/dl 1996) to 24 μg/dl in 2019; the P90 urinary mercury levels reduced from 13.7 μmol/mol creatinine to 2.1 μmol/mol creatinine and the P90 urinary SPMA levels reduced from 133.7 μmol/mol creatinine to 1.7 μmol/mol creatinine. For HDI the P90 results reduced from 2 µmol HDA/mol creatinine in 1996–2000 to 0.7 in 2005–2010 but levels have since increased to 1.0 µmol HDA/mol creatinine (2016–2019).Conclusion: There is strong evidence of reductions in exposure of GB workers to lead, benzene and mercury from the data presented here. These reductions may reflect the impact of national, regional and global regulatory action to reduce exposures however, the loss of high exposure industries (from either GB as a whole or just this dataset i.e., samples are being sent elsewhere) and the increase in automation or substitution also need to be considered as potential factors. The results for HDI show that whilst interventions can reduce exposures significantly, such initiatives may need to be refreshed at intervals to maintain the reductions in exposure. We have observed that exposures move between sectors over time. Waste and recycling (lead, mercury) and tunnelling through contaminated land (benzene) were sectors or tasks associated with significant exposures and may be increasingly areas of concern.
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