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Driscoll T, Turner MC, Villeneuve PJ, Scheepers PTJ, Schlünssen V, Cao B, Momen NC, Pega F. The WHO/ILO Joint Estimates approach to occupational risk factor and burden of disease estimation: providing actionable evidence with impact across sectors in countries. Ann Work Expo Health 2025; 69:337-343. [PMID: 39919221 PMCID: PMC11911508 DOI: 10.1093/annweh/wxae107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Indexed: 02/09/2025] Open
Affiliation(s)
- Tim Driscoll
- Sydney School of Public Health, University of Sydney, NSW, 2006, Australia
| | - Michelle C Turner
- Barcelona Institute for Global Health (ISGlobal), Doctor Aiguader 88, 08003 Barcelona, Spain
| | - Paul J Villeneuve
- Department of Neuroscience, Carleton University, Health Sciences Building, Room 6307, 1125 Colonel By Drive, Ottawa, ON K1S 5B6, Canada
| | - Paul T J Scheepers
- Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands
| | - Vivi Schlünssen
- Department of Public Health, Danish Ramazzini Centre, Aarhus University, Bartholins Allé 2, 8000 Aarhus, Denmark
| | - Bochen Cao
- Department of Data and Analytics, World Health Organization, 20 Avenue Appia, 1202 Geneva, Switzerland
| | - Natalie C Momen
- Department of Environment, Climate Change and Health, World Health Organization, 20 Avenue Appia, 1202 Geneva, Switzerland
| | - Frank Pega
- Department of Environment, Climate Change and Health, World Health Organization, 20 Avenue Appia, 1202 Geneva, Switzerland
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Schlünssen V, Ádám B, Momen NC, Nemery B, Pega F. Response to Letter to the Editor regarding "The prevalences and levels of occupational exposure to dusts and/or fibres (silica, asbestos and coal): A systematic review and meta-analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury". ENVIRONMENT INTERNATIONAL 2023; 179:108165. [PMID: 37669593 DOI: 10.1016/j.envint.2023.108165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/07/2023]
Affiliation(s)
- Vivi Schlünssen
- Department of Public Health, Danish Ramazzini Centre, Aarhus University, Aarhus, Denmark.
| | - Balázs Ádám
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, United Arab Emirates
| | - Natalie C Momen
- Department of Environment, Climate Change and Health, World Health Organization, Geneva, Switzerland
| | - Ben Nemery
- Centre for Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
| | - Frank Pega
- Department of Environment, Climate Change and Health, World Health Organization, Geneva, Switzerland.
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Svendsen C, Whaley P, Vist GE, Husøy T, Beronius A, Consiglio ED, Druwe I, Hartung T, Hatzi VI, Hoffmann S, Hooijmans CR, Machera K, Robinson JF, Roggen E, Rooney AA, Roth N, Spilioti E, Spyropoulou A, Tcheremenskaia O, Testai E, Vinken M, Mathisen GH. Protocol for designing INVITES-IN, a tool for assessing the internal validity of in vitro studies. EVIDENCE-BASED TOXICOLOGY 2023; 1:1-15. [PMID: 38264543 PMCID: PMC10805239 DOI: 10.1080/2833373x.2023.2232415] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 06/19/2023] [Accepted: 06/19/2023] [Indexed: 01/25/2024]
Abstract
This protocol describes the design and development of a tool for evaluation of the internal validity of in vitro studies, which is needed to include the data as evidence in systematic reviews and chemical risk assessments. The tool will be designed specifically to be applied to cell culture studies, including, but not restricted to, studies meeting the new approach methodology (NAM) definition. The tool is called INVITES-IN (IN VITro Experimental Studies INternal validity). In this protocol, three of the four studies that will be performed to create the release version of INVITES-IN are described. In the first study, evaluation of existing assessment tools will be combined with focus group discussions to identify how characteristics of the design or conduct of an in vitro study can affect its internal validity. Bias domains and items considered to be of relevance for in vitro studies will be identified. In the second study, group agreement on internal validity domains and items of importance for in vitro studies will be identified via a modified Delphi methodology. In the third study, the draft version of the tool will be created, based on the data on relevance and importance of bias domains and items collected in Studies 1 and 2. A separate protocol will be prepared for the fourth study, which includes the user testing and validation of the tool, and collection of users' experience.
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Affiliation(s)
- Camilla Svendsen
- Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Paul Whaley
- Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Gunn E. Vist
- Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway
- Division for Health Services, Norwegian Institute of Public Health, Oslo, Norway
| | - Trine Husøy
- Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway
- Department of Food Safety, Norwegian Institute of Public Health, Oslo, Norway
| | - Anna Beronius
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Emma Di Consiglio
- Environment & Health Department, Italian National Institute of Health (ISS), Rome, Italy
| | - Ingrid Druwe
- United States Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessments, Research Triangle Park, NC, USA
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, USA
- CAAT Europe, University of Konstanz, Konstanz, Germany
| | - Vasiliki I. Hatzi
- Laboratory of Toxicological Control of Pesticides, Scientific Directorate of Pesticides’ Control and Phytopharmacy, Benaki Phytopathological Institute, Kifissia, Greece
| | - Sebastian Hoffmann
- Evidence-Based Toxicology Collaboration (EBTC), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, USA
- SEH consulting + services, Paderborn, Germany
| | - Carlijn R. Hooijmans
- Department of Anesthesiology, Pain and Palliative Care, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Kyriaki Machera
- Laboratory of Toxicological Control of Pesticides, Scientific Directorate of Pesticides’ Control and Phytopharmacy, Benaki Phytopathological Institute, Kifissia, Greece
| | - Joshua F. Robinson
- Department of Obstetrics, Gynecology & Reproductive Sciences, University of California, San Francisco (UCSF), CA, USA
| | - Erwin Roggen
- 3Rs Management and Consulting ApS, Lyngby, Denmark
| | - Andrew A. Rooney
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Nicolas Roth
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
- Swiss Centre for Applied Human Toxicology (SCAHT), Basel, Switzerland
| | - Eliana Spilioti
- Laboratory of Toxicological Control of Pesticides, Scientific Directorate of Pesticides’ Control and Phytopharmacy, Benaki Phytopathological Institute, Kifissia, Greece
| | - Anastasia Spyropoulou
- Laboratory of Toxicological Control of Pesticides, Scientific Directorate of Pesticides’ Control and Phytopharmacy, Benaki Phytopathological Institute, Kifissia, Greece
| | - Olga Tcheremenskaia
- Environment & Health Department, Italian National Institute of Health (ISS), Rome, Italy
| | - Emanuela Testai
- Environment & Health Department, Italian National Institute of Health (ISS), Rome, Italy
| | - Mathieu Vinken
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Brussel, Belgium
| | - Gro H. Mathisen
- Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway
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Kaiser I, Pfahlberg AB, Mathes S, Uter W, Diehl K, Steeb T, Heppt MV, Gefeller O. Inter-Rater Agreement in Assessing Risk of Bias in Melanoma Prediction Studies Using the Prediction Model Risk of Bias Assessment Tool (PROBAST): Results from a Controlled Experiment on the Effect of Specific Rater Training. J Clin Med 2023; 12:jcm12051976. [PMID: 36902763 PMCID: PMC10003882 DOI: 10.3390/jcm12051976] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Assessing the risk of bias (ROB) of studies is an important part of the conduct of systematic reviews and meta-analyses in clinical medicine. Among the many existing ROB tools, the Prediction Model Risk of Bias Assessment Tool (PROBAST) is a rather new instrument specifically designed to assess the ROB of prediction studies. In our study we analyzed the inter-rater reliability (IRR) of PROBAST and the effect of specialized training on the IRR. Six raters independently assessed the risk of bias (ROB) of all melanoma risk prediction studies published until 2021 (n = 42) using the PROBAST instrument. The raters evaluated the ROB of the first 20 studies without any guidance other than the published PROBAST literature. The remaining 22 studies were assessed after receiving customized training and guidance. Gwet's AC1 was used as the primary measure to quantify the pairwise and multi-rater IRR. Depending on the PROBAST domain, results before training showed a slight to moderate IRR (multi-rater AC1 ranging from 0.071 to 0.535). After training, the multi-rater AC1 ranged from 0.294 to 0.780 with a significant improvement for the overall ROB rating and two of the four domains. The largest net gain was achieved in the overall ROB rating (difference in multi-rater AC1: 0.405, 95%-CI 0.149-0.630). In conclusion, without targeted guidance, the IRR of PROBAST is low, questioning its use as an appropriate ROB instrument for prediction studies. Intensive training and guidance manuals with context-specific decision rules are needed to correctly apply and interpret the PROBAST instrument and to ensure consistency of ROB ratings.
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Affiliation(s)
- Isabelle Kaiser
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
- Correspondence:
| | - Annette B. Pfahlberg
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Sonja Mathes
- Department of Dermatology and Allergy Biederstein, Faculty of Medicine, Technical University of Munich, 80802 Munich, Germany
| | - Wolfgang Uter
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Katharina Diehl
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
| | - Theresa Steeb
- Department of Dermatology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Markus V. Heppt
- Department of Dermatology, University Hospital Erlangen, 91054 Erlangen, Germany
- Comprehensive Cancer Center Erlangen-European Metropolitan Area of Nuremberg (CCC ER-EMN), 91054 Erlangen, Germany
| | - Olaf Gefeller
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany
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Náfrádi B, Kiiver H, Neupane S, Momen NC, Streicher KN, Pega F. Estimating the population exposed to a risk factor over a time window: A microsimulation modelling approach from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. PLoS One 2022; 17:e0278507. [PMID: 36584100 PMCID: PMC9803131 DOI: 10.1371/journal.pone.0278507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 11/17/2022] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVES Burden of disease estimation commonly requires estimates of the population exposed to a risk factor over a time window (yeart to yeart+n). We present a microsimulation modelling approach for producing such estimates and apply it to calculate the population exposed to long working hours for one country (Italy). METHODS We developed a three-model approach: Model 1, a multilevel model, estimates exposure to the risk factor at the first year of the time window (yeart). Model 2, a regression model, estimates transition probabilities between exposure categories during the time window (yeart to yeart+n). Model 3, a microsimulation model, estimates the exposed population over the time window, using the Monte Carlo method. The microsimulation is carried out in three steps: (a) a representative synthetic population is initiated in the first year of the time window using prevalence estimates from Model 1, (b) the exposed population is simulated over the time window using the transition probabilities from Model 2; and (c) the population is censored for deaths during the time window. RESULTS We estimated the population exposed to long working hours (i.e. 41-48, 49-54 and ≥55 hours/week) over a 10-year time window (2002-11) in Italy. We populated all three models with official data from Labour Force Surveys, United Nations population estimates and World Health Organization life tables. Estimates were produced of populations exposed over the time window, disaggregated by sex and 5-year age group. CONCLUSIONS Our modelling approach for estimating the population exposed to a risk factor over a time window is simple, versatile, and flexible. It however requires longitudinal exposure data and Model 3 (the microsimulation model) is stochastic. The approach can improve accuracy and transparency in exposure and burden of disease estimations. To improve the approach, a logical next step is changing Model 3 to a deterministic microsimulation method, such as modelling of microflows.
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Affiliation(s)
- Bálint Náfrádi
- Labour Administration, Labour Inspection and Occupational Safety and Health Branch, International Labour Organization, Geneva, Switzerland
| | | | - Subas Neupane
- Department of Climate Change, Environment and Health, World Health Organization, Geneva, Switzerland
| | - Natalie C. Momen
- Department of Climate Change, Environment and Health, World Health Organization, Geneva, Switzerland
| | - Kai N. Streicher
- Department of Climate Change, Environment and Health, World Health Organization, Geneva, Switzerland
| | - Frank Pega
- Department of Climate Change, Environment and Health, World Health Organization, Geneva, Switzerland
- * E-mail:
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Pega F, Momen NC, Bero L, Whaley P. Towards a framework for systematic reviews of the prevalence of exposure to environmental and occupational risk factors. Environ Health 2022; 21:64. [PMID: 35794579 PMCID: PMC9258093 DOI: 10.1186/s12940-022-00878-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 06/27/2022] [Indexed: 06/15/2023]
Abstract
Exposure prevalence studies (as here defined) record the prevalence of exposure to environmental and occupational risk factors to human health. Applying systematic review methods to the synthesis of these studies would improve the rigour and transparency of normative products produced based on this evidence (e.g., exposure prevalence estimates). However, a dedicated framework, including standard methods and tools, for systematically reviewing exposure prevalence studies has yet to be created. We describe the need for this framework and progress made towards it through a series of such systematic reviews that the World Health Organization and the International Labour Organization conducted for their WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates).We explain that existing systematic review frameworks for environmental and occupational health cannot be directly applied for the generation of exposure prevalence estimates because they seek to synthesise different types of evidence (e.g., intervention or exposure effects on health) for different purposes (e.g., identify intervention effectiveness or exposure toxicity or carcinogenicity). Concepts unique to exposure prevalence studies (e.g., "expected heterogeneity": the real, non-spurious variability in exposure prevalence due to exposure changes over space and/or time) also require new assessment methods. A framework for systematic reviews of prevalence of environmental and occupational exposures requires adaptation of existing methods (e.g., a standard protocol) and development of new tools or approaches (e.g., for assessing risk of bias and certainty of a body of evidence, including exploration of expected heterogeneity).As part of the series of systematic reviews for the WHO/ILO Joint Estimates, the World Health Organization collaborating with partners has created a preliminary framework for systematic reviews of prevalence studies of exposures to occupational risk factors. This included development of protocol templates, data extraction templates, a risk of bias assessment tool, and an approach for assessing certainty of evidence in these studies. Further attention and efforts are warranted from scientific and policy communities, especially exposure scientists and policy makers, to establish a standard framework for comprehensive and transparent systematic reviews of studies estimating prevalence of exposure to environmental and occupational risk factors, to improve estimates, risk assessments and guidelines.
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Affiliation(s)
- Frank Pega
- Department of Environment, Climate Change and Health, World Health Organization, Avenue Appia 20, 1202, Geneva, Switzerland.
| | - Natalie C Momen
- Department of Environment, Climate Change and Health, World Health Organization, Avenue Appia 20, 1202, Geneva, Switzerland
| | - Lisa Bero
- General Internal Medicine/Public Health/Center for Bioethics and Humanities, University of Colorado-Anschutz Medical Campus, Denver, CO, USA
| | - Paul Whaley
- Lancaster Environment Center, Lancaster University, Lancaster, UK
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Pega F, Momen NC, Gagliardi D, Bero LA, Boccuni F, Chartres N, Descatha A, Dzhambov AM, Godderis L, Loney T, Mandrioli D, Modenese A, van der Molen HF, Morgan RL, Neupane S, Pachito D, Paulo MS, Prakash KC, Scheepers PTJ, Teixeira L, Tenkate T, Woodruff TJ, Norris SL. Assessing the quality of evidence in studies estimating prevalence of exposure to occupational risk factors: The QoE-SPEO approach applied in the systematic reviews from the WHO/ILO Joint Estimates of the Work-related burden of disease and Injury. ENVIRONMENT INTERNATIONAL 2022; 161:107136. [PMID: 35182944 PMCID: PMC8885428 DOI: 10.1016/j.envint.2022.107136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 01/05/2022] [Accepted: 02/04/2022] [Indexed: 05/04/2023]
Abstract
BACKGROUND The World Health Organization (WHO) and the International Labour Organization (ILO) have produced the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates). For these, systematic reviews of studies estimating the prevalence of exposure to selected occupational risk factors have been conducted to provide input data for estimations of the number of exposed workers. A critical part of systematic review methodology is to assess the quality of evidence across studies. In this article, we present the approach applied in these WHO/ILO systematic reviews for performing such assessments on studies of prevalence of exposure. It is called the Quality of Evidence in Studies estimating Prevalence of Exposure to Occupational risk factors (QoE-SPEO) approach. We describe QoE-SPEO's development to date, demonstrate its feasibility reporting results from pilot testing and case studies, note its strengths and limitations, and suggest how QoE-SPEO should be tested and developed further. METHODS Following a comprehensive literature review, and using expert opinion, selected existing quality of evidence assessment approaches used in environmental and occupational health were reviewed and analysed for their relevance to prevalence studies. Relevant steps and components from the existing approaches were adopted or adapted for QoE-SPEO. New steps and components were developed. We elicited feedback from other systematic review methodologists and exposure scientists and reached consensus on the QoE-SPEO approach. Ten individual experts pilot-tested QoE-SPEO. To assess inter-rater agreement, we counted ratings of expected (actual and non-spurious) heterogeneity and quality of evidence and calculated a raw measure of agreement (Pi) between individual raters and rater teams for the downgrade domains. Pi ranged between 0.00 (no two pilot testers selected the same rating) and 1.00 (all pilot testers selected the same rating). Case studies were conducted of experiences of QoE-SPEO's use in two WHO/ILO systematic reviews. RESULTS We found no existing quality of evidence assessment approach for occupational exposure prevalence studies. We identified three relevant, existing approaches for environmental and occupational health studies of the effect of exposures. Assessments using QoE-SPEO comprise three steps: (1) judge the level of expected heterogeneity (defined as non-spurious variability that can be expected in exposure prevalence, within or between individual persons, because exposure may change over space and/or time), (2) assess downgrade domains, and (3) reach a final rating on the quality of evidence. Assessments are conducted using the same five downgrade domains as the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach: (a) risk of bias, (b) indirectness, (c) inconsistency, (d) imprecision, and (e) publication bias. For downgrade domains (c) and (d), the assessment varies depending on the level of expected heterogeneity. There are no upgrade domains. The QoE-SPEO's ratings are "very low", "low", "moderate", and "high". To arrive at a final decision on the overall quality of evidence, the assessor starts at "high" quality of evidence and for each domain downgrades by one or two levels for serious concerns or very serious concerns, respectively. In pilot tests, there was reasonable agreement in ratings for expected heterogeneity; 70% of raters selected the same rating. Inter-rater agreement ranged considerably between downgrade domains, both for individual rater pairs (range Pi: 0.36-1.00) and rater teams (0.20-1.00). Sparse data prevented rigorous assessment of inter-rater agreement in quality of evidence ratings. CONCLUSIONS We present QoE-SPEO as an approach for assessing quality of evidence in prevalence studies of exposure to occupational risk factors. It has been developed to its current version (as presented here), has undergone pilot testing, and was applied in the systematic reviews for the WHO/ILO Joint Estimates. While the approach requires further testing and development, it makes steps towards filling an identified gap, and progress made so far can be used to inform future work in this area.
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Affiliation(s)
- Frank Pega
- Department of Environment, Climate Change and Health, World Health Organization, Geneva, Switzerland.
| | - Natalie C Momen
- Department of Environment, Climate Change and Health, World Health Organization, Geneva, Switzerland
| | - Diana Gagliardi
- Inail, Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Rome, Italy
| | - Lisa A Bero
- Charles Perkins Centre, The University of Sydney, Sydney, Australia; General Internal Medicine/Public Health/Center for Bioethics and Humanities, University of Colorado-Anschutz Medical Campus, Denver, CO, United States
| | - Fabio Boccuni
- Inail, Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, Rome, Italy
| | - Nicholas Chartres
- Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Francisco, San Francisco, United States
| | - Alexis Descatha
- AP-HP (Paris Hospital "Assistance Publique Hôpitaux de Paris"), Occupational Health Unit, University Hospital of West Suburb of Paris, Poincaré Site, Garches, France /Versailles St-Quentin Univ - Paris Saclay Univ (UVSQ), UMS 011, UMR-S 1168, France; Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S1085, CAPTV CDC, Angers, France
| | - Angel M Dzhambov
- Department of Hygiene, Faculty of Public Health, Medical University of Plovdiv, Plovdiv, Bulgaria; Institute for Highway Engineering and Transport Planning, Graz University of Technology, Graz, Austria
| | - Lode Godderis
- Centre for Environment and Health, KU Leuven, Leuven, Belgium; KIR Department (Knowledge, Information & Research), IDEWE, External Service for Prevention and Protection at Work, Leuven, Belgium
| | - Tom Loney
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Daniele Mandrioli
- Cesare Maltoni Cancer Research Center, Ramazzini Institute, Bologna, Italy
| | - Alberto Modenese
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Henk F van der Molen
- Coronel Institute of Occupational Health, Amsterdam UMC, location AMC, Amsterdam Public Health Research Institute, Amsterdam, Netherlands
| | - Rebecca L Morgan
- Department of Health Research Methods, Evidence and Impact, McMaster University, Ontario, Canada
| | - Subas Neupane
- Faculty of Social Science (Health Sciences), University of Tampere, Tampere, Finland
| | - Daniela Pachito
- Evidence-based Health, Universidade Federal de São Paulo, Sao Paulo, Brazil; Cochrane Brazil, Sao Paulo, Brazil
| | - Marilia S Paulo
- Institute of Public Health, College of Medicine & Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates; Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
| | - K C Prakash
- Faculty of Social Science (Health Sciences), University of Tampere, Tampere, Finland
| | - Paul T J Scheepers
- Radboud Institute for Health Sciences, Radboudumc, Nijmegen, the Netherlands
| | - Liliane Teixeira
- Workers' Health and Human Ecology Research Center, National School of Public Health Sergio Arouca, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
| | - Thomas Tenkate
- School of Occupational and Public Health, Ryerson University, Toronto, Ontario, Canada
| | - Tracey J Woodruff
- Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Francisco, San Francisco, United States
| | - Susan L Norris
- Oregon Health & Science University, Portland, OR, United States; Department of Quality Assurance, Norms and Standards, World Health Organization, Geneva, Switzerland
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