Sources of noise exposure across Australian workplaces: cross-sectional analysis and modelling the impact of a targeted noise-source reduction initiative.

IF 1.8 4区医学 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals Of Work Exposures and Health Pub Date : 2024-07-08 DOI:10.1093/annweh/wxae029

Kate Lewkowski, Jane S Heyworth, Kahlia McCausland, Warwick Williams, Lin Fritschi

{"title":"Sources of noise exposure across Australian workplaces: cross-sectional analysis and modelling the impact of a targeted noise-source reduction initiative.","authors":"Kate Lewkowski, Jane S Heyworth, Kahlia McCausland, Warwick Williams, Lin Fritschi","doi":"10.1093/annweh/wxae029","DOIUrl":null,"url":null,"abstract":"Context: Workplace noise regulations and guidance follow the hierarchy of control model that prioritizes eliminating or reducing noise at its source.Objectives: To determine the main sources of workplace noise exposure in the Australian working population and estimate the reduction of workers exposed over the noise limit (LAeq,8h > 85 dB) if noise levels of specific tools or equipment were reduced by 10 dB.Methods: Information on the tools used and tasks performed during each participant's last working shift was collected from 4,977 workers via telephone survey. Using a predetermined database of task-based noise levels, partial noise exposures (Pa2h) were determined for each noisy activity performed by the workers and their daily noise exposure level (LAeq,8h) was estimated. Partial exposures were categorized into 15 tool/task groups and the tally, average, and sum (Pa2h) for each group were calculated. The impacts of 5 different scenarios that simulated a reduction of 10 dB in noise emissions for specific tool groups were modelled.Results: Powered tools and equipment were responsible for 59.3% of all noise exposure (Pa2h); vehicles for 10.6%; mining, refineries, and plant equipment for 5.1%; and manufacturing and food processing for 4.2%. Modelling demonstrated that a 10 dBA noise-level reduction of all powered tools and equipment would lead to a 26.4% (95% confidence interval: 22.7% to 30.3%) reduction of workers with an LAeq,8h > 85 dB. This could represent over 350,000 Australian workers no longer exposed above the workplace limit daily.Conclusions: A universal reduction of 10 dB to power tools and equipment would substantially reduce the future burden of hearing loss, tinnitus, workplace injuries, and other health effects. Initiatives to reduce the noise emissions of specific powered tool groups are warranted.","PeriodicalId":8362,"journal":{"name":"Annals Of Work Exposures and Health","volume":" ","pages":"626-635"},"PeriodicalIF":1.8000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals Of Work Exposures and Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/annweh/wxae029","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}

引用次数: 0

Abstract

Context: Workplace noise regulations and guidance follow the hierarchy of control model that prioritizes eliminating or reducing noise at its source.

Objectives: To determine the main sources of workplace noise exposure in the Australian working population and estimate the reduction of workers exposed over the noise limit (LAeq,8h > 85 dB) if noise levels of specific tools or equipment were reduced by 10 dB.

Methods: Information on the tools used and tasks performed during each participant's last working shift was collected from 4,977 workers via telephone survey. Using a predetermined database of task-based noise levels, partial noise exposures (Pa2h) were determined for each noisy activity performed by the workers and their daily noise exposure level (LAeq,8h) was estimated. Partial exposures were categorized into 15 tool/task groups and the tally, average, and sum (Pa2h) for each group were calculated. The impacts of 5 different scenarios that simulated a reduction of 10 dB in noise emissions for specific tool groups were modelled.

Results: Powered tools and equipment were responsible for 59.3% of all noise exposure (Pa2h); vehicles for 10.6%; mining, refineries, and plant equipment for 5.1%; and manufacturing and food processing for 4.2%. Modelling demonstrated that a 10 dBA noise-level reduction of all powered tools and equipment would lead to a 26.4% (95% confidence interval: 22.7% to 30.3%) reduction of workers with an LAeq,8h > 85 dB. This could represent over 350,000 Australian workers no longer exposed above the workplace limit daily.

Conclusions: A universal reduction of 10 dB to power tools and equipment would substantially reduce the future burden of hearing loss, tinnitus, workplace injuries, and other health effects. Initiatives to reduce the noise emissions of specific powered tool groups are warranted.

查看原文本刊更多论文

澳大利亚工作场所的噪声暴露源：横截面分析和有针对性的噪声源减少倡议的影响建模。

背景：工作场所噪声法规和指南遵循优先从源头消除或降低噪声的分级控制模式：确定澳大利亚工作人群暴露于工作场所噪声的主要来源，并估算如果将特定工具或设备的噪声水平降低 10 分贝，可减少多少工人暴露于超过噪声限值（LAeq,8h > 85 分贝）的噪声：方法：通过电话调查从 4,977 名工人中收集了每位参与者在最后一个工作班次中使用的工具和执行的任务的信息。利用预先确定的基于任务的噪声级数据库，确定了工人所从事的每项高噪声活动的部分噪声暴露量（Pa2h），并估算了他们的日噪声暴露量（LAeq,8h）。部分暴露量被分为 15 个工具/任务组，并计算出每组的总暴露量、平均暴露量和总暴露量（Pa2h）。模拟了 5 种不同方案的影响，这些方案模拟将特定工具组的噪声排放降低 10 分贝：结果：电动工具和设备占所有噪声暴露（Pa2h）的 59.3%；车辆占 10.6%；采矿、炼油和工厂设备占 5.1%；制造和食品加工占 4.2%。建模表明，如果所有电动工具和设备的噪音水平降低 10 分贝，那么 LAeq,8h > 85 分贝的工人将减少 26.4%（95% 置信区间：22.7% 至 30.3%）。这意味着超过 350,000 名澳大利亚工人每天不再暴露在超过工作场所限值的环境中：结论：将电动工具和设备的噪音普遍降低 10 分贝，将大大减轻未来听力损失、耳鸣、工伤和其他健康影响的负担。有必要采取措施减少特定电动工具组的噪声排放。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Annals Of Work Exposures and Health Medicine-Public Health, Environmental and Occupational Health

CiteScore

4.60

自引率

19.20%

发文量

期刊介绍： About the Journal Annals of Work Exposures and Health is dedicated to presenting advances in exposure science supporting the recognition, quantification, and control of exposures at work, and epidemiological studies on their effects on human health and well-being. A key question we apply to submission is, "Is this paper going to help readers better understand, quantify, and control conditions at work that adversely or positively affect health and well-being?" We are interested in high quality scientific research addressing: the quantification of work exposures, including chemical, biological, physical, biomechanical, and psychosocial, and the elements of work organization giving rise to such exposures; the relationship between these exposures and the acute and chronic health consequences for those exposed and their families and communities; populations at special risk of work-related exposures including women, under-represented minorities, immigrants, and other vulnerable groups such as temporary, contingent and informal sector workers; the effectiveness of interventions addressing exposure and risk including production technologies, work process engineering, and personal protective systems; policies and management approaches to reduce risk and improve health and well-being among workers, their families or communities; methodologies and mechanisms that underlie the quantification and/or control of exposure and risk. There is heavy pressure on space in the journal, and the above interests mean that we do not usually publish papers that simply report local conditions without generalizable results. We are also unlikely to publish reports on human health and well-being without information on the work exposure characteristics giving rise to the effects. We particularly welcome contributions from scientists based in, or addressing conditions in, developing economies that fall within the above scope.