Development and Evaluation of Three Risk Assessment Models for Hearing Loss: a Comparative Study

Background Hearing loss is highly prevalent in occupational populations, but it could be effectively prevented through early monitoring. There is still a lack of studies on the risk assessment of hearing loss. Objective To construct three risk assessment models for hearing loss in oil workers, and evaluate their performance to obtain the optimal one. Methods A cross-sectional study was conducted. Participants were 1 423 workers of an oil company who received the occupational health examination from 2018 to 2019 in the Jingxia Hospital of North China Petroleum Administration. Their general demographic data, audiometric test and laboratory test results were collected. Unconditional multivariable Logistic regression was used to explore the factors influencing hearing loss. Python was used to build the random forest, XG Boost, and BP neural network models with factors potentially associated with hearing loss determined based on a literature review and expert opinions incorporated. The discriminative ability of th