Risk analysis of noise-induced hearing loss of workers in the automobile manufacturing industries based on back-propagation neural network model: a cross-sectional study in Han Chinese population

OBJECTIVES

This study aims to predict the risk of noise-induced hearing loss (NIHL) through a back-propagation neural network (BPNN) model. It provides an early, simple and accurate prediction method for NIHL.

DESIGN

Population based, a cross sectional study.

SETTING

Han, China.

PARTICIPANTS

This study selected 3266 Han male workers from three automobile manufacturing industries.

PRIMARY OUTCOME MEASURES

Information including personal life habits, occupational health test information and occupational exposure history were collected and predictive factors of NIHL were screened from these workers. BPNN and logistic regression models were constructed using these predictors.

RESULTS

The input variables of BPNN model were 20, 16 and 21 important factors screened by univariate, stepwise and lasso-logistic regression. When the BPNN model was applied to the test set, it was found to have a sensitivity (TPR) of 83.33%, a specificity (TNR) of 85.92%, an accuracy (ACC) of 85.51%, a positive predictive value (PPV) of 52.85%, a negative predictive value of 96.46% and area under the receiver operating curve (AUC) is: 0.926 (95% CI: 0.891 to 0.961), which demonstrated the better overall properties than univariate-logistic regression modelling (AUC: 0.715) (95% CI: 0.652 to 0.777). The BPNN model has better predictive performance against NIHL than the stepwise-logistic and lasso-logistic regression model in terms of TPR, TNR, ACC, PPV and NPV (p<0.05); the area under the receiver operating characteristics curve of NIHL is also higher than that of the stepwise and lasso-logistic regression model (p<0.05). It was a relatively important factor in NIHL to find cumulative noise exposure, auditory system symptoms, age, listening to music or watching video with headphones, exposure to high temperature and noise exposure time in the trained BPNN model.

CONCLUSIONS

The BPNN model was a valuable tool in dealing with the occupational risk prediction problem of NIHL. It can be used to predict the risk of an individual NIHL.

[Effects of electric welding on hearing loss and respiratory damage]

Objective: To investigate the occupational health status of electric welding workers and explore the effects of electric welding on hearing loss and respiratory damage. Methods: From August to December 2021, the cluster sampling method was used to select workers from an automobile manufacturer in Guangzhou City as research subjects: 636 welding workers in the welding workshop as the welding group, 757 assembly workers in the engine workshop and the final assembly workshop exposed to pure noise as the assembly group. Occupational disease hazard factors were detected for welding positions and assembly positions, and occupational health examination was carried out for research subjects. The occupational health status, the trends of hearing loss and respiratory abnormalities with working age were compared and analyzed between the two groups. Binary logistic regression was used to analyze the association between hearing loss and respiratory abnormalities in welding workers. Results: The excess rates of welding fumes, manganese and its compounds in the welding position were both 9.68% (3/31). Its noise exposure intensity [ (85.36±2.68) dB (A) ] and excess rate [48.39% (15/31) ] were not significantly different from those in the assembly position [ (84.86±3.28) dB (A) and 43.24% (16/37) ] (P>0.05). The results of the occupational health examination showed that the detection rates of hearing loss, digital radiography (DR) chest X-ray abnormality, alanine aminotransferase abnormality, deazelaic aminotransferase abnormality and white blood cell count abnormality of workers in the welding group were higher than those in the assembly group (P<0.05). The detection rates of hearing loss, DR chest X-ray abnormality, pulmonary ventilation abnormality in the welding group and the detection rate of hearing loss in the assembly group increased with the working age of the workers (P<0.05). The hearing loss detection rate and DR chest X-ray abnormality detection rate of the workers with ≥9 years working age in the welding group were both higher than those in the assembly group workers with same working age (P<0.05). The binary logistic regression analysis showed that abnormal pulmonary ventilation and abnormal DR chest X-ray were the risk factors for hearing loss in welding workers (OR=10.83, 95%CI: 7.31-16.06; OR=16.59, 95%CI: 5.72-48.10; P<0.05) . Conclusion: Hearing loss and respiratory damage are prominent problems among welding workers, and the detection rates of abnormality increase with the working age of the workers. Hearing loss in welding workers is associated with abnormal pulmonary ventilation and abnormal DR chest X-ray.

[Investigation of a carbon monoxide poisoning accident with a hidden source]

In June 2022, a carbon monoxide poisoning accident with hidden source occurred in a bonded gold/silver wire manufacturing enterprise in Guangzhou, causing 10 people to be poisoned, of which 1 was caused by carbon monoxide poisoning and 9 by carbon monoxide contact reaction. The symptoms were dizziness, fatigue and vomiting. After 5 to 7 h, the saturation of carboxyhemoglobin in finger pulse was 4% to 10%, and the saturation of carboxyhemoglobin in blood gas biochemical analysis was 1.9% to 5.8%. The concentration of carbon monoxide detected in the carbon borne purification plant of the enterprise was 34.46-37.26 mg/m(3). It was judged that the accident was carbon monoxide poisoning caused by carbon monoxide gas being transported to the work post along the gas transmission pipeline due to abnormal operation of the carbon borne purification plant. By investigating the source and cause of poison, this paper provides a warning for the similar process to prevent similar events, and provides a new idea for the identification of chemical poisoning risk. At the same time, it is warned that similar enterprises should fully consider the risk of poisoning under specific circumstances, strengthen equipment maintenance and repair, and prevent the occurrence of similar incidents.