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Research article
The prediction and risk point score (RPS) of high frequency hearing loss in noise exposed workers
Yajia Lan
Sichuan University West China School of Public Health and West China Fourth Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-9818-3057
License:
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Background: Occupational hearing loss is a significant occupational health concern in many countries, and high frequency hearing loss (HFHL) is an early symptom. Based on realistic demands, we aimed to build a prediction risk model of HFHL and developed the related risk point score (RPS). The results of this study are expected to provide technological support for interventions and management to enhance application-oriented research of HFHL.
Methods: A total of 32121 participants who were noise exposed workers were enrolled. The datasets from the National key occupational diseases survey (NKODS) performed from 2014 to 2017 in Sichuan Province in China were utilized. The sociodemographic and occupational characteristics were assessed by standardized questionnaires, and the level of HFHL were collected by audiometric testing and was defined as a binaural high frequency threshold average (BHFTA) over 40 dB in the right and left ears. The risk prediction models were generated by linear logistic regression, and based on the models, the risk point score (RPS) of HFHL were calculated.
Results: Of the 32121 participants in the study, 9.97% (n=4029) of workers had HFHL (BHFTA ≥ 40 dB). Age (OR=1.08, 95% CI: 1.071–1.083), sex (OR=3.34, 95% CI: 2.880–3.636), noise exposure time (OR=1.01, 95% CI: 1.008–1.018), manufacturing industry (OR=1.46, 95% CI: 1.302–1.647), construction industry (OR=2.14, 95% CI: 1.488–3.069), mining industry (OR=2.57, 95% CI: 2.225–2.957), foreign enterprise (OR=0.94, 95% CI: 0.781–1.122), and private enterprise (OR=1.32, 95% CI: 1.200–1.442) were predictors of HFHL (P<0.05). By comparing the two risk prediction models, the 40 dB HL criterion model was found to be more effective than the 25 dB HL criterion model (AUC=0.637). Verification of the two models revealed that the 25 dB HL criterion model was more stable than the 40 dB HL criterion.
Conclusion: The study found that the prevalence of HFHL was moderate in Sichuan Province. Sex, age, noise exposure years, and employment in the manufacturing industry, construction industry, mining industry, foreign enterprise, or private enterprise were predictors of HFHL, and the development of the RPS of HFHL is necessary for application-oriented research on HFHL.
Keywords
High frequency hearing loss, Prediction model, Risk point score
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CURRENT STATUS: Under Revision
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Editorial decision: Major revision
On 20 May, 2020
Review #1 received
Received 09 May, 2020
Review #2 received
Received 06 May, 2020
Reviewer #2 agreed
On 15 Apr, 2020
Reviewer #1 agreed
On 13 Apr, 2020
Editor assigned
On 12 Apr, 2020
Reviewers invited
Invitations sent on 12 Apr, 2020
Submission checks complete
On 11 Apr, 2020
Editor invited
On 11 Apr, 2020
No comments provided
Editorial decision: Major revision
On 03 Mar, 2020
Review #2 received
Received 26 Feb, 2020
Reviewer #2 agreed
On 24 Feb, 2020
Reviewer #1 agreed
On 20 Feb, 2020
Review #1 received
Received 20 Feb, 2020
Reviewers invited
Invitations sent on 29 Jan, 2020
Editor assigned
On 24 Jan, 2020
Submission checks complete
On 15 Jan, 2020
Editor invited
On 15 Jan, 2020
First submitted
On 06 Jan, 2020
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Subject Areas
Health Policy
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This preprint is under consideration at BMC Public Health. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
The prediction and risk point score (RPS) of high frequency hearing loss in noise exposed workers
Yajia Lan
Sichuan University West China School of Public Health and West China Fourth Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-9818-3057
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Revision
Version 2
Posted 15 Apr, 2020
No community comments so far
Editorial decision: Major revision
On 20 May, 2020
Review #1 received
Received 09 May, 2020
Review #2 received
Received 06 May, 2020
Reviewer #2 agreed
On 15 Apr, 2020
Reviewer #1 agreed
On 13 Apr, 2020
Editor assigned
On 12 Apr, 2020
Reviewers invited
Invitations sent on 12 Apr, 2020
Submission checks complete
On 11 Apr, 2020
Editor invited
On 11 Apr, 2020
No comments provided
Editorial decision: Major revision
On 03 Mar, 2020
Review #2 received
Received 26 Feb, 2020
Reviewer #2 agreed
On 24 Feb, 2020
Reviewer #1 agreed
On 20 Feb, 2020
Review #1 received
Received 20 Feb, 2020
Reviewers invited
Invitations sent on 29 Jan, 2020
Editor assigned
On 24 Jan, 2020
Submission checks complete
On 15 Jan, 2020
Editor invited
On 15 Jan, 2020
First submitted
On 06 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Policy
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Occupational hearing loss is a significant occupational health concern in many countries, and high frequency hearing loss (HFHL) is an early symptom. Based on realistic demands, we aimed to build a prediction risk model of HFHL and developed the related risk point score (RPS). The results of this study are expected to provide technological support for interventions and management to enhance application-oriented research of HFHL.
Methods: A total of 32121 participants who were noise exposed workers were enrolled. The datasets from the National key occupational diseases survey (NKODS) performed from 2014 to 2017 in Sichuan Province in China were utilized. The sociodemographic and occupational characteristics were assessed by standardized questionnaires, and the level of HFHL were collected by audiometric testing and was defined as a binaural high frequency threshold average (BHFTA) over 40 dB in the right and left ears. The risk prediction models were generated by linear logistic regression, and based on the models, the risk point score (RPS) of HFHL were calculated.
Results: Of the 32121 participants in the study, 9.97% (n=4029) of workers had HFHL (BHFTA ≥ 40 dB). Age (OR=1.08, 95% CI: 1.071–1.083), sex (OR=3.34, 95% CI: 2.880–3.636), noise exposure time (OR=1.01, 95% CI: 1.008–1.018), manufacturing industry (OR=1.46, 95% CI: 1.302–1.647), construction industry (OR=2.14, 95% CI: 1.488–3.069), mining industry (OR=2.57, 95% CI: 2.225–2.957), foreign enterprise (OR=0.94, 95% CI: 0.781–1.122), and private enterprise (OR=1.32, 95% CI: 1.200–1.442) were predictors of HFHL (P<0.05). By comparing the two risk prediction models, the 40 dB HL criterion model was found to be more effective than the 25 dB HL criterion model (AUC=0.637). Verification of the two models revealed that the 25 dB HL criterion model was more stable than the 40 dB HL criterion.
Conclusion: The study found that the prevalence of HFHL was moderate in Sichuan Province. Sex, age, noise exposure years, and employment in the manufacturing industry, construction industry, mining industry, foreign enterprise, or private enterprise were predictors of HFHL, and the development of the RPS of HFHL is necessary for application-oriented research on HFHL.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5