https://orcid.org/0000-0003-1791-3351
Figures
Abstract
Background
Workplace atmospheric exposure monitoring is the standard method to assess and control hazardous dust exposure; however, feasibility and cost constraints often limit its application. In recent decades, evidence-based tools supporting exposure modelling and control banding have been developed to aid in predicting and/or controlling occupational exposure to various contaminants. However, there is limited information on the availability and applicability of evidence-based tools for predicting and/or controlling occupational dust exposure, as well as on the methods for evaluating these tools across different exposure scenarios. Therefore, this planned scoping review aims to identify existing evidence-based tools for dust exposure predicting and/or controlling and to present evaluation approaches.
Methods
We will employ the scoping review methods developed by the Joanna Briggs Institute (JBI). The search will be conducted on PubMed, Scopus, and Web of Science databases, in addition to grey literature from the National Institute for Occupational Safety and Health (NIOSH) and advanced Google searches. Studies will be included if they report evidence-based tools for predicting and/or controlling dust exposure using quantitative or semi-quantitative designs and provide a detailed explanation of the methods used for tool development. There will be no restrictions on publication date or geographical location; however, only studies published in English will be considered. Studies focusing exclusively on dust exposure in environmental settings will be excluded. Each member of the review team will screen titles, abstracts, and full texts independently and in collaboration, based on the inclusion criteria. The extracted data will encompass details such as author, title, country, accessible platforms, method/tool names, intended users, types of dust, and occupational settings. Descriptions of the identified tools will include numerical data and narrative summaries to ensure a comprehensive overview.
Citation: Kabito GG, Tefera Y, Ramkissoon C, Gaskin S (2024) Evidence-based dust exposure prediction and/or control tools in occupational settings: A scoping review protocol. PLoS ONE 19(10): e0309967. https://doi.org/10.1371/journal.pone.0309967
Editor: Pisirai Ndarukwa, Bindura University of Science Education, SOUTH AFRICA
Received: March 11, 2024; Accepted: August 21, 2024; Published: October 17, 2024
Copyright: © 2024 Kabito et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: There are no data sets associated with this protocol.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
The World Health Organization (WHO) defines dust as “solid particles ranging in size from below 1 μm up to at least 100 μm, which may be or become airborne, depending on their origin, physical characteristics, and ambient conditions” [1]. Thus, exposure to dust is typically evaluated based on particle size, which is categorized into coarse (> 2.5 μm), fine (< 2.5 μm), and ultrafine particles (UFP) (< 100 nm) [2]. In occupational settings, exposure to dust primarily arises from mechanical processes such as cutting, breaking, crushing, drilling, abrasive and sand blasting, digging, or hammering [3–5].
Occupational respiratory diseases (ORDs) related to overexposure to dust represent a significant global public health concern, contributing to approximately one-third of all documented work-related mortality [6, 7]. Moreover, the Global Burden of Disease (GBD) reported about 4 million deaths in 2019 [8] and 13.6 million disability-adjusted life years (DALY) due to ORDs [7]. Exposure to dust has also been associated with an increased risk of cardiovascular diseases, with heightened prevalence observed among mine workers and those exposed to silica, diesel exhaust, and inorganic dust, as well as in construction, metal industries, asphalt work, and heavy equipment operation [9, 10].
The prevention of dust-related health burdens critically depends on rigorous exposure assessment and effective dust control measures in the workplace [11]. Exposure assessments, a major component of the occupational health risk assessment process, have been applied across various occupational contexts, leading to the development of numerous definitions and methods (tools) for exposure estimation and control of risks to different toxic agents [12–14]. For example, conventional methods require measurements by trained professionals, such as certified occupational hygienists, who measure dust exposure levels and compare them against established Workplace Exposure Standards (WES) and recommend dust mitigation or control measures accordingly [15, 16]. While the conventional exposure monitoring method is considered the gold standard in dust exposure assessment and control, its application is not always practical for all exposure scenarios due to constraints related to time, expertise, and cost [17–19].
In such scenarios, exposure modelling tools are an alternative method [20]. Considering this, there has been a significant rise in the development and implementation of evidence-based tools in recent decades. In this context, ’evidence-based’ refers to tools that are supported by exposure models, exposure data (databases), and control banding techniques for predicting and/or controlling different contaminants in the workplace [21–23]. For example, exposure models are conceptual or mathematical models that enable the estimation of individual exposure parameters based on available input data from specific occupational exposure scenarios [24, 25]. Likewise, control banding employs models that provide control guidance (bands) based on input occupational exposure information [22]. Evidence-based tools can be accessed online through various platforms [26], including web-based interfaces [27, 28], software applications [29], mobile apps [30], and Microsoft Excel [22].
Despite the development of different evidence-based tools for predicting and/or controlling exposure to different contaminants, it is unclear which tools in the literature are specifically relevant for occupational dust exposure. Additionally, there is a lack of information on the evaluation approaches for these tools, which could guide users in selecting the tool for specific dust exposure scenarios.
We conducted a preliminary search across different databases, including PROSPERO, MEDLINE, PUBMED, the Cochrane Database of Systematic Reviews, and JBI Evidence Synthesis, to determine whether the topic has been addressed. We identified one systematic review [31] that synthesized evidence on the reliability of models recommended by the European Chemicals Agency (ECHA), evaluating their precision, accuracy, and robustness in exposure assessment [32]. However, there is no current or ongoing scoping or systematic reviews were found on the evidence-based tools used for occupational dust exposure and the evaluation approaches for these tools. We have chosen a scoping review as a suitable and comprehensive method for synthesizing evidence, as it allows us to examine a diverse body of evidence and outline the fundamental concepts within this research domain [33].
To address this gap, the proposed scoping review will identify existing evidence-based tools for predicting and/or controlling worker dust exposure, as well as explore methodologies/approaches used for evaluating these identified tools. We anticipate that this scoping review will serve as a valuable resource by presenting relevant evidence-based tools for dust exposure prediction and/or control in occupational settings, along with the evaluation approaches for these tools. This will serve as a reference for making informed decisions when selecting the appropriate tools for various dust exposure scenarios.
Methods
This study will utilize the Joanna Briggs Institute (JBI) method for scoping reviews, recognized for its structured approach to elements such as research questions, inclusion and exclusion criteria, search strategies, and data extraction, among others [34]. The final report of this proposed scoping review will follow the reporting guidance recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), enhancing transparency through specific reporting criteria and facilitating a thorough and standardized presentation of the scoping review findings (S1 Appendix) [35].
Protocol and registration
The protocol has been registered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/S6EZJ).
Review question
The specific research questions for this scoping review are:
- What evidence-based tools are available in the literature for predicting and/or controlling dust exposure in occupational settings?
- What evidence is available regarding the evaluation approaches for these tools?
Eligibility criteria
We utilized the PCC (Population/problem, Concept, and Context) framework as recommended by JBI [34].
Concept
The core focus of this proposed study is on evidence-based tools for predicting and/or controlling dust exposure, as well as the evaluation approaches relevant to these tools. According to the definition of ’evidence-based’ provided in the background section, a tool is deemed evidence-based in this review if it meets specific criteria: it must be incorporated into or based on databases (such as silica dust monitoring data from literature, exposure scenarios, measurements, or archived government data) and employ statistical, mathematical, or computational models to predict dust exposure levels and/or recommend control measures (control bands). Additionally, evaluation approaches are operationalized as the quantitative or qualitative methods used to assess the effectiveness of these tools, considering reliability, validity, applicability, and efficacy.
Problem
The study problem was occupational dust exposure, which includes respirable dust, respirable crystalline silica, and other hazardous dusts such as coal, minerals, wood, metal, and both organic and inorganic dusts generated in the workplace to which workers may be exposed during work activities.
Context
This proposed scoping review is limited to occupational settings, encompassing a wide range of work environments, including but not limited to construction sites, manufacturing plants, mining, and quarrying. This review will exclude studies conducted solely in environmental settings, which result in exposures that might occur outside of work environments (Table 1).
Information sources
The proposed scoping review will include peer-reviewed, primary, and grey literature sources that are accessible to the public and that fulfil the eligibility criteria (Table 2).
Search strategy
The databases that will be searched are PubMed, Scopus, and Web of Science. Grey literature will be sourced through the National Institute for Occupational Safety and Health (NIOSH) platform and advanced Google searches. The search strategy used relevant keywords, subject headings, and MeSH terms specific to each database, incorporating Boolean operators "AND" and "OR" to construct comprehensive search strings. This strategy was developed in consultation with a qualified librarian from the University of Adelaide. Initially, a preliminary search on PubMed was conducted to identify articles using terms such as dust exposure, exposure models, occupational exposure models, exposure band, exposure scenario, exposure prediction, tools, risk assessment, risk management, control banding, evaluation methods, and exposure control. The PubMed search query was subsequently refined by integrating text words from relevant article titles and abstracts, along with MeSH terms used to classify these articles (S2 Appendix). The ’concept’ and ’context’ were combined in our search strategy due to a low yield of citations when searched separately. For advanced Google Scholar searches, the same specific terms will be used, and the first 100 articles will be included (S3 Appendix). The search strategy was designed with data charting and literature mapping in mind, as detailed in (Table 3). The search process will be iterative, allowing for the identification and incorporation of additional keywords and relevant search terms as needed.
Study selection
All records retrieved will be imported into Covidence (www.covidence.org) for screening and removing duplicates. To ensure that all members of the review team (S.G., C.R., Y.T., G.G.K.) are fully familiar with the eligibility criteria and selection process, we will pilot-test 25 articles during the title and abstract screening phase. Following this pilot test, three independent reviewers (G.G.K., C.R, S.G.) will screen all records by titles and abstract against the established eligibility criteria (Table 2). Any discrepancies between the reviewers’ assessments will be discussed and resolved, with the criteria refined as necessary. This iterative process will continue until both reviewers reach full agreement on the eligibility of the articles. After the title and abstract screening is completed, full-text screening of the selected publications will proceed. Two reviewers will independently assess the full-text articles to determine their inclusion. The team will then collaborate to reach a consensus on each article. Articles that do not meet the criteria will be excluded, with the reasons for exclusion documented and reported in the final scoping review report.
Data extraction
We customized the JBI data extraction tool to fit our study objectives, specifying the information required for each category (S4 Appendix). Two independent reviewers will extract data from the studies included using this tool and will collaborate to finalize the data. During the extraction process, the tool will be modified and revised as necessary to address any issues that arise. All modifications will be documented in the final scoping review report. The extracted data will encompass various study characteristics, including author, title, publication year, and country of origin. Additionally, it will cover details such as accessible platforms, method/tool names, intended users, types of dust, and occupational settings. Furthermore, the data will include information on the description of the methods/tools used, including control bands, databases, exposure bands, input parameters, model types, and evaluation methodologies. If further information is required, the authors of the included studies will be contacted.
Data analysis and presentation
Extracted data will be analysed using descriptive statistics (frequency and proportion) and a narrative summary. The results will be presented through tables and figures to facilitate clear understanding and contextualization. Additionally, the implications for future research and practical applications will be discussed.
Ethics and dissemination
Ethical approval is not required since the study is based on publicly available literature. The final report will be disseminated through peer-reviewed journals and relevant conferences.
Limitations
This planned scoping review will not assess the methodological rigor of the included studies. The diverse terminology used in exposure prediction and dust-related research may result in some relevant studies being overlooked in our search strategy. Finally, only studies published in English will be included in this review.
Conclusions
This planned scoping review will, to the best of the authors’ knowledge, be the first to address existing knowledge gaps in evidence-based tools for dust exposure prediction and/or control in occupational settings. It will systematically identify these tools and their evaluation methods. The findings from this review are expected to serve as a reference for selecting and applying evidence-based dust exposure prediction and/or control tools in various exposure scenarios.
Supporting information
S3 Appendix. Search strategy for Google advanced search logic grid.
https://doi.org/10.1371/journal.pone.0309967.s003
(DOCX)
Acknowledgments
The authors would like to thank Vikki Langton, a librarian at The University of Adelaide, for her invaluable assistance in developing a comprehensive search strategy for this proposed scoping review. G.G.K. acknowledges support from the Australian Government Research Training Program (RTP) Scholarship.
References
- 1.
WHO, Hazard prevention and control in the work environment: Airborne dust; https://www.who.int/publications/i/item/WHO-SDE-OEH-99-14. Accessed on February 10, 2024.
- 2. Moreno-Ríos A.L., Tejeda-Benítez L.P., and Bustillo-Lecompte C.F., Sources, characteristics, toxicity, and control of ultrafine particles: An overview. Geoscience Frontiers, 2022. 13(1): p. 101147.
- 3. Castillejos M., et al., Airborne coarse particles and mortality. Inhalation Toxicology, 2000. 12(sup1): p. 61–72.
- 4. Leung C.C., Yu I.T.S., and Chen W., Silicosis. The Lancet, 2012. 379(9830): p. 2008–2018. pmid:22534002
- 5.
Organization, W.H., Health aspects of air pollution with particulate matter, ozone and nitrogen dioxide: report on a WHO working group, Bonn, Germany 13–15 January 2003. 2003, Copenhagen: WHO Regional Office for Europe.
- 6. Zheng X.-Y., et al., Effects of occupational exposure to dust, gas, vapor and fumes on chronic bronchitis and lung function. Journal of Thoracic Disease, 2024. 16(1): p. 357.
- 7. Global and regional burden of chronic respiratory disease in 2016 arising from non-infectious airborne occupational exposures: a systematic analysis for the Global Burden of Disease Study 2016. Occup Environ Med, 2020. 77(3): p. 142–150. pmid:32054818
- 8. Momtazmanesh S., et al., Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019. EClinicalMedicine, 2023. 59. pmid:37229504
- 9. Kuempel E., et al., Pulmonary inflammation and crystalline silica in respirable coal mine dust: dose response. Journal of biosciences, 2003. 28: p. 61–69. pmid:12682426
- 10. Cullinan P., et al., Occupational lung diseases: from old and novel exposures to effective preventive strategies. The Lancet Respiratory Medicine, 2017. 5(5): p. 445–455. pmid:28089118
- 11.
Bullock, W.H., J. Ignacio, and J.S. Ignacio, A strategy for assessing and managing occupational exposures. 2006: AIHA.
- 12. Paustenbach D.J., THE PRACTICE OF EXPOSURE ASSESSMENT: A STATE-OF-THE-ART REVIEW. Journal of Toxicology and Environmental Health, Part B, 2000. 3(3): p. 179–291. pmid:10911984
- 13.
Watson A.Y., Bates R.R., and Kennedy D., Assessment of human exposure to air pollution: methods, measurements, and models, in Air pollution, the automobile, and public health. 1988, National Academies Press (US).
- 14. Barbosa F., Matos M.L.F., and Santos P., Different methods of sampling and analysis of occupational dust: equipment and techniques. CESET Journal: Comfort, Efficiency and Safety at Work, 2010.
- 15.
Ashley, K., NIOSH manual of analytical methods 5th edition and harmonization of occupational exposure monitoring. Gefahrstoffe, Reinhaltung der Luft = Air quality control/Herausgeber, BIA und KRdL im VDI und DIN, 2015. 2015(1–2): p. 7.
- 16. Maciejewska A., Occupational exposure assessment for crystalline silica dust: approach in Poland and worldwide. Int J Occup Med Environ Health, 2008. 21(1): p. 1–23. pmid:18482900
- 17. Vincent J.H., Occupational and environmental aerosol exposure assessment: a scientific journey from the past, through the present and into the future. Journal of Environmental Monitoring, 2012. 14(2): p. 340–347. pmid:22109739
- 18. Harper M., Assessing workplace chemical exposures: the role of exposure monitoring. Journal of Environmental Monitoring, 2004. 6(5): p. 404–412. pmid:15152307
- 19. Fenske R.A., For good measure: Origins and prospects of exposure science (2007 Wesolowski Award Lecture). Journal of Exposure Science & Environmental Epidemiology, 2010. 20(6): p. 493–502. pmid:20424649
- 20. Schlüter U. and Spinazzè A., Understanding the limitations and application of occupational exposure models in a REACH context. Journal of Occupational and Environmental Hygiene, 2023. 20(8): p. 336–349. pmid:37159939
- 21. Zalk D.M. and Heussen G.H., Banding the world together; the global growth of control banding and qualitative occupational risk management. Safety and health at work, 2011. 2(4): p. 375–379. pmid:22953222
- 22. Zalk D.M. and Nelson D.I., History and evolution of control banding: a review. J Occup Environ Hyg, 2008. 5(5): p. 330–46. pmid:18350442
- 23. Cherrie J.W., et al., Exposure Models for REACH and Occupational Safety and Health Regulations. Int J Environ Res Public Health, 2020. 17(2). pmid:31936022
- 24. Tischer M., et al., Evaluation of Tier One Exposure Assessment Models (ETEAM): Project Overview and Methods. Annals of Work Exposures and Health, 2017. 61(8): p. 911–920. pmid:29028257
- 25.
Organization, W.H., Methods of assessing risk to health from exposure to hazards released from waste landfills. 2000, Copenhagen: WHO Regional Office for Europe.
- 26. Albújar Verona C.E., et al., Digital platforms and indicators in the occupational safety and health management system: a systematic review. Dyna, 2022. 89(224): p. 165–172.
- 27. Marquart H., et al., ‘Stoffenmanager’, a web-based control banding tool using an exposure process model. Annals of occupational hygiene, 2008. 52(6): p. 429–441. pmid:18587140
- 28. Fransman W., et al., Advanced Reach Tool (ART): development of the mechanistic model. Annals of occupational hygiene, 2011. 55(9): p. 957–979. pmid:22003239
- 29. Daniels W., Lee S., and Miller A., EPA’s exposure assessment tools and models. Applied Occupational and Environmental Hygiene, 2003. 18(2): p. 82–86. pmid:12519680
- 30. Fanti G., et al., Features and practicability of the next-generation sensors and monitors for exposure assessment to airborne pollutants: a systematic review. Sensors, 2021. 21(13): p. 4513. pmid:34209443
- 31. Spinazzè A., et al., How to obtain a reliable estimate of occupational exposure? Review and discussion of models’ reliability. International journal of environmental research and public health, 2019. 16(15): p. 2764.
- 32.
Pascal, P., Guidance on Information Requirements and Chemical Safety Assessment Chapter R. 11: PBT/vPvB assessment. 2017.
- 33. Arksey H. and O’Malley L., Scoping studies: towards a methodological framework. International journal of social research methodology, 2005. 8(1): p. 19–32.
- 34.
Peters M.D., et al., Chapter 11: scoping reviews (2020 version). JBI manual for evidence synthesis, JBI, 2020. 2020.
- 35. Tricco A.C., et al., PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Annals of internal medicine, 2018. 169(7): p. 467–473. pmid:30178033