Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population
•Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss.•We examined a sample of 1,418 workers from a wide range of jobs.•Variables used: gender, age, noise level and other non-work-related factors.•Bayesian networks. Introduction: This research relates the mo...
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Veröffentlicht in: | Journal of safety research 2022-02, Vol.80, p.428-440 |
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description | •Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss.•We examined a sample of 1,418 workers from a wide range of jobs.•Variables used: gender, age, noise level and other non-work-related factors.•Bayesian networks.
Introduction: This research relates the most important work-related factors affecting the development of hearing loss to the main methods used as medical assessment criteria in the diagnosis of occupational deafness. These criteria are the Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss, and are applied to data obtained from audiograms performed on workers in occupational medical examinations. Method: Depending on the assessment method selected, these often return different results in grading an individual's hearing status and predicting how it will evolve. To address this problem, medical examinations (including audiograms) were carried out on a heterogeneous sample of 1,418 workers in Spain, from which demographic or personal data (gender, age, etc.), occupational data (noise level to which each individual is exposed, etc.) and other non-work-related factors (exposure to noise outside work, family history, etc.) were also gathered. Using Bayesian Networks, the conditional probability of an individual developing hearing loss was obtained taking into account all these factors and, specifically, noise level and length of service in the workplace. Sensitivity analyses were also carried out using the three scales (SAL, ELI and Percentage Hearing Loss Index), proving their suitability as tools the diagnosis and prediction of deafness. These networks were validated under the Receiver Operating Characteristic curve (ROC) criterion and in particular by the Area Under the Curve (AUC). Results: The results show that all three methods are deficient in so far as detecting preventive hearing problems related to noise in most workplaces. Conclusions: The most restrictive methods for detecting possible cases of deafness are the SAL index and the Percentage Loss Index. The ELI index is the least restrictive of the three methods, but it is not able to discriminate the causes of hearing problems in an individual caused by exposure to noise, either by its intensity level or by the time of exposure to noise. Practical Applications: The use of the three methods in the field of occupational risk prevention is extremely limited and it seems reasonable to think that there is a ne |
doi_str_mv | 10.1016/j.jsr.2021.12.025 |
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Introduction: This research relates the most important work-related factors affecting the development of hearing loss to the main methods used as medical assessment criteria in the diagnosis of occupational deafness. These criteria are the Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss, and are applied to data obtained from audiograms performed on workers in occupational medical examinations. Method: Depending on the assessment method selected, these often return different results in grading an individual's hearing status and predicting how it will evolve. To address this problem, medical examinations (including audiograms) were carried out on a heterogeneous sample of 1,418 workers in Spain, from which demographic or personal data (gender, age, etc.), occupational data (noise level to which each individual is exposed, etc.) and other non-work-related factors (exposure to noise outside work, family history, etc.) were also gathered. Using Bayesian Networks, the conditional probability of an individual developing hearing loss was obtained taking into account all these factors and, specifically, noise level and length of service in the workplace. Sensitivity analyses were also carried out using the three scales (SAL, ELI and Percentage Hearing Loss Index), proving their suitability as tools the diagnosis and prediction of deafness. These networks were validated under the Receiver Operating Characteristic curve (ROC) criterion and in particular by the Area Under the Curve (AUC). Results: The results show that all three methods are deficient in so far as detecting preventive hearing problems related to noise in most workplaces. Conclusions: The most restrictive methods for detecting possible cases of deafness are the SAL index and the Percentage Loss Index. The ELI index is the least restrictive of the three methods, but it is not able to discriminate the causes of hearing problems in an individual caused by exposure to noise, either by its intensity level or by the time of exposure to noise. Practical Applications: The use of the three methods in the field of occupational risk prevention is extremely limited and it seems reasonable to think that there is a need for the construction of new scales to correct or improve the existing ones.</description><identifier>ISSN: 0022-4375</identifier><identifier>EISSN: 1879-1247</identifier><identifier>DOI: 10.1016/j.jsr.2021.12.025</identifier><identifier>PMID: 35249624</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Bayes Theorem ; Bayesian analysis ; Bayesian network ; Conditional probability ; Criteria ; Deafness ; Deafness - complications ; Diagnosis ; ELI ; Genetics ; Hearing loss ; Hearing Loss, Noise-Induced - diagnosis ; Hearing Loss, Noise-Induced - epidemiology ; Hearing Loss, Noise-Induced - prevention & control ; Hearing protection ; Humans ; Medical personnel ; Noise ; Noise level ; Noise levels ; Noise, Occupational - adverse effects ; Noise, Occupational - prevention & control ; Occupational Diseases - diagnosis ; Occupational Diseases - epidemiology ; Occupational Diseases - prevention & control ; Occupational Exposure ; Percentage ; Physical examinations ; Prevention ; SAL ; Sensitivity analysis ; Workplace ; Workplaces</subject><ispartof>Journal of safety research, 2022-02, Vol.80, p.428-440</ispartof><rights>2021 The Author(s)</rights><rights>Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Feb 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-3c4dd55c3e5303d4bf7104d4cd76264d7ea86af9a22337d770b11f82441c0a853</citedby><cites>FETCH-LOGICAL-c424t-3c4dd55c3e5303d4bf7104d4cd76264d7ea86af9a22337d770b11f82441c0a853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jsr.2021.12.025$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35249624$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Barrero, Jesús P.</creatorcontrib><creatorcontrib>García-Herrero, Susana</creatorcontrib><creatorcontrib>Mariscal, Miguel A.</creatorcontrib><title>Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population</title><title>Journal of safety research</title><addtitle>J Safety Res</addtitle><description>•Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss.•We examined a sample of 1,418 workers from a wide range of jobs.•Variables used: gender, age, noise level and other non-work-related factors.•Bayesian networks.
Introduction: This research relates the most important work-related factors affecting the development of hearing loss to the main methods used as medical assessment criteria in the diagnosis of occupational deafness. These criteria are the Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss, and are applied to data obtained from audiograms performed on workers in occupational medical examinations. Method: Depending on the assessment method selected, these often return different results in grading an individual's hearing status and predicting how it will evolve. To address this problem, medical examinations (including audiograms) were carried out on a heterogeneous sample of 1,418 workers in Spain, from which demographic or personal data (gender, age, etc.), occupational data (noise level to which each individual is exposed, etc.) and other non-work-related factors (exposure to noise outside work, family history, etc.) were also gathered. Using Bayesian Networks, the conditional probability of an individual developing hearing loss was obtained taking into account all these factors and, specifically, noise level and length of service in the workplace. Sensitivity analyses were also carried out using the three scales (SAL, ELI and Percentage Hearing Loss Index), proving their suitability as tools the diagnosis and prediction of deafness. These networks were validated under the Receiver Operating Characteristic curve (ROC) criterion and in particular by the Area Under the Curve (AUC). Results: The results show that all three methods are deficient in so far as detecting preventive hearing problems related to noise in most workplaces. Conclusions: The most restrictive methods for detecting possible cases of deafness are the SAL index and the Percentage Loss Index. The ELI index is the least restrictive of the three methods, but it is not able to discriminate the causes of hearing problems in an individual caused by exposure to noise, either by its intensity level or by the time of exposure to noise. Practical Applications: The use of the three methods in the field of occupational risk prevention is extremely limited and it seems reasonable to think that there is a need for the construction of new scales to correct or improve the existing ones.</description><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Bayesian network</subject><subject>Conditional probability</subject><subject>Criteria</subject><subject>Deafness</subject><subject>Deafness - complications</subject><subject>Diagnosis</subject><subject>ELI</subject><subject>Genetics</subject><subject>Hearing loss</subject><subject>Hearing Loss, Noise-Induced - diagnosis</subject><subject>Hearing Loss, Noise-Induced - epidemiology</subject><subject>Hearing Loss, Noise-Induced - prevention & control</subject><subject>Hearing protection</subject><subject>Humans</subject><subject>Medical personnel</subject><subject>Noise</subject><subject>Noise level</subject><subject>Noise levels</subject><subject>Noise, Occupational - adverse effects</subject><subject>Noise, Occupational - prevention & control</subject><subject>Occupational Diseases - diagnosis</subject><subject>Occupational Diseases - epidemiology</subject><subject>Occupational Diseases - prevention & control</subject><subject>Occupational Exposure</subject><subject>Percentage</subject><subject>Physical examinations</subject><subject>Prevention</subject><subject>SAL</subject><subject>Sensitivity analysis</subject><subject>Workplace</subject><subject>Workplaces</subject><issn>0022-4375</issn><issn>1879-1247</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kctu1DAUhi0EokPhAdggS2xYkOBrLmJVVS2MNBILYG157JOpQ8YOdtKqb8bj1WnaLkBiZeno-79j-0foLSUlJbT61Jd9iiUjjJaUlYTJZ2hDm7otKBP1c7QhhLFC8FqeoFcp9YSQSlL6Ep1wyURbMbFBf7a-G2bwBnDosA8uAR7gGgasvcUJvAvRTbfYeTxdAb4J8dc46IVeB9_Pdh_xxW57j48QDfhJH-5lV6Cj8wc8hJRy3joD6dFjnT74kFxaczFv9JPLzn9zT3uX2RjGedAL-Rq96PSQ4M3DeYp-Xl78OP9a7L592Z6f7QojmJgKboS1UhoOkhNuxb6rKRFWGFtXrBK2Bt1Uums1Y5zXtq7JntKuYUJQQ3Qj-Sn6sHrHGH7PkCZ1dMnAMGgPYU6KVbxqai7ogr7_C-3DHH2-XaaEbFpJZJspulIm5gdG6NQY3VHHW0WJWmpVvcq1qqVWRZnKtebMuwfzvD-CfUo89piBzysA-SuuHUSVjFtatS6CmZQN7j_6O-cqtHc</recordid><startdate>202202</startdate><enddate>202202</enddate><creator>Barrero, Jesús P.</creator><creator>García-Herrero, Susana</creator><creator>Mariscal, Miguel A.</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T2</scope><scope>C1K</scope><scope>K9.</scope><scope>7X8</scope></search><sort><creationdate>202202</creationdate><title>Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population</title><author>Barrero, Jesús P. ; García-Herrero, Susana ; Mariscal, Miguel A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-3c4dd55c3e5303d4bf7104d4cd76264d7ea86af9a22337d770b11f82441c0a853</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Bayesian network</topic><topic>Conditional probability</topic><topic>Criteria</topic><topic>Deafness</topic><topic>Deafness - complications</topic><topic>Diagnosis</topic><topic>ELI</topic><topic>Genetics</topic><topic>Hearing loss</topic><topic>Hearing Loss, Noise-Induced - diagnosis</topic><topic>Hearing Loss, Noise-Induced - epidemiology</topic><topic>Hearing Loss, Noise-Induced - prevention & control</topic><topic>Hearing protection</topic><topic>Humans</topic><topic>Medical personnel</topic><topic>Noise</topic><topic>Noise level</topic><topic>Noise levels</topic><topic>Noise, Occupational - adverse effects</topic><topic>Noise, Occupational - prevention & control</topic><topic>Occupational Diseases - diagnosis</topic><topic>Occupational Diseases - epidemiology</topic><topic>Occupational Diseases - prevention & control</topic><topic>Occupational Exposure</topic><topic>Percentage</topic><topic>Physical examinations</topic><topic>Prevention</topic><topic>SAL</topic><topic>Sensitivity analysis</topic><topic>Workplace</topic><topic>Workplaces</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barrero, Jesús P.</creatorcontrib><creatorcontrib>García-Herrero, Susana</creatorcontrib><creatorcontrib>Mariscal, Miguel A.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of safety research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Barrero, Jesús P.</au><au>García-Herrero, Susana</au><au>Mariscal, Miguel A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population</atitle><jtitle>Journal of safety research</jtitle><addtitle>J Safety Res</addtitle><date>2022-02</date><risdate>2022</risdate><volume>80</volume><spage>428</spage><epage>440</epage><pages>428-440</pages><issn>0022-4375</issn><eissn>1879-1247</eissn><abstract>•Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss.•We examined a sample of 1,418 workers from a wide range of jobs.•Variables used: gender, age, noise level and other non-work-related factors.•Bayesian networks.
Introduction: This research relates the most important work-related factors affecting the development of hearing loss to the main methods used as medical assessment criteria in the diagnosis of occupational deafness. These criteria are the Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss, and are applied to data obtained from audiograms performed on workers in occupational medical examinations. Method: Depending on the assessment method selected, these often return different results in grading an individual's hearing status and predicting how it will evolve. To address this problem, medical examinations (including audiograms) were carried out on a heterogeneous sample of 1,418 workers in Spain, from which demographic or personal data (gender, age, etc.), occupational data (noise level to which each individual is exposed, etc.) and other non-work-related factors (exposure to noise outside work, family history, etc.) were also gathered. Using Bayesian Networks, the conditional probability of an individual developing hearing loss was obtained taking into account all these factors and, specifically, noise level and length of service in the workplace. Sensitivity analyses were also carried out using the three scales (SAL, ELI and Percentage Hearing Loss Index), proving their suitability as tools the diagnosis and prediction of deafness. These networks were validated under the Receiver Operating Characteristic curve (ROC) criterion and in particular by the Area Under the Curve (AUC). Results: The results show that all three methods are deficient in so far as detecting preventive hearing problems related to noise in most workplaces. Conclusions: The most restrictive methods for detecting possible cases of deafness are the SAL index and the Percentage Loss Index. The ELI index is the least restrictive of the three methods, but it is not able to discriminate the causes of hearing problems in an individual caused by exposure to noise, either by its intensity level or by the time of exposure to noise. Practical Applications: The use of the three methods in the field of occupational risk prevention is extremely limited and it seems reasonable to think that there is a need for the construction of new scales to correct or improve the existing ones.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>35249624</pmid><doi>10.1016/j.jsr.2021.12.025</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Bayes Theorem Bayesian analysis Bayesian network Conditional probability Criteria Deafness Deafness - complications Diagnosis ELI Genetics Hearing loss Hearing Loss, Noise-Induced - diagnosis Hearing Loss, Noise-Induced - epidemiology Hearing Loss, Noise-Induced - prevention & control Hearing protection Humans Medical personnel Noise Noise level Noise levels Noise, Occupational - adverse effects Noise, Occupational - prevention & control Occupational Diseases - diagnosis Occupational Diseases - epidemiology Occupational Diseases - prevention & control Occupational Exposure Percentage Physical examinations Prevention SAL Sensitivity analysis Workplace Workplaces |
title | Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population |
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