Abstract
Background Noise induced hearing loss (NIHL) is a significant occupational health concern in many countries. Based on the realistic demands, we aimed to build the prediction risk model of noise induced hearing loss (NIHL) and developed the related risk point score (RPS). The results of this study expect to provide technology support for interventions and management, in order to enhance the application-orientated research on NIHL. Methods A total of 40433 participants of noise exposed workers were enrolled. The datasets from The National Key Occupational Diseases Survey (NKODS) from 2014 to 2017 in Sichuan province of China. The socio-demographic and occupational characteristics used the standardized questionnaires, and the level of NIHL were collected by audiometric testing, which was defined as binaural high-frequency threshold average (BHFTA) over 40dB. The prediction model expressed by linear format of logistic regression and based on model calculated the risk point score (RPS) of NIHL. Results Of the 40433 participants in the study, there are 9.97%(n=4029) of workers have NIHL (BHFBA >40). Age (OR=1.08, 95%CI: 1.071-1.083), sex (OR=3.34, 95%CI:2.997-3.715), noise exposure time (OR=1.01, 95%CI: 1.008-1.017), manufacturing industry(OR=1.35, 95%CI:1.207-1.500), construction industry (OR=2.59, 95%CI: 1.941-3.458), mining industry (OR=2.42, 95%CI: 2.132-2.740), foreign enterprise(OR=1.14, 95%CI: 0.962-1.353), private enterprise(OR=1.48, 95%CI: 1.361-1.603) are predictors of NIHL( P <0.05). The risk prediction model has a better effectiveness of NIHL (AUC= 0.7150). According to the NIHL- RPS calculated the individual score was 75 that the risk probability of NIHL was 37.97%. Conclusion The study found that the prevalence of NIHL at a moderate level in Sichuan province. Sex, age, noise exposure time, manufacturing industry, construction industry, mining industry, foreign enterprise, private enterprise are predictors of NIHL, and to develop the NIHL-RPS is necessary for application-orientated research on NIHL.