The prediction and risk point score (RPS) of high frequency hearing loss in noise exposed workers
Abstract 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.