Background The influencing factors of noise hazards in the automotive manufacturing industry are complex, diverse, and mutually correlated, resulting in significant health impacts on workers.
Objective To explore the application of generalized estimating equations (GEE) to analyze the factors affecting high-frequency hearing loss among noise-exposed workers in an automotive manufacturing company, guiding enterprises to scientifically carry out employee hearing protection programs.
Methods The data of occupational health field evaluation and occupational health surveillance of an automobile manufacturing company for five consecutive years from 2018 to 2022 were collected, and 806 noise-exposed workers with pure tone hearing test results for all five consecutive years were selected as study participants. The retrieved indicators were gender, physical examination year, noise intensity, blood pressure, white blood cell counts, red blood cell counts, platelet counts, concentrations of hemoglobin, alanine transaminase, aspartate aminotransferase, smoking, drinking, etc. Gender, noise intensity, blood pressure, white blood cell counts, red blood cell counts, concentrations of hemoglobin, platelet counts, glutamate aminotransferase, glutamate aminotransferase, smoking, and drinking were set as independent variables, and occurrence of high-frequency hearing loss was set as a dependent variable, and GEE were constructed by using the statistical software of SPSS 20.0 to analyze the influencing factors of high-frequency hearing loss.
Results Of the 806 workers, 698 were male (86.6%) and 108 were female (13.4%). The detection rates of high-frequency hearing loss in each year from 2018 to 2022 were 66.4% (535/806), 69.8% (563/806), 70.0% (564/806), 68.9% (555/806), and 68.2% (550/806), respectively. The detection rate of high-frequency hearing loss in the company was varied significantly by gender, lowered white blood cell counts, lowered red blood cell counts, lowered platelet counts, smoking, and drinking (P<0.05). The results of GEE analysis showed that after adjusting for selected confounding factors and excluding interaction effects, the risk of high-frequency hearing loss was higher in men than in women (P=0.001; OR=1.907, 95%CI: 1.286, 2.829); it was higher in workplace with disqualified noise intensity than in those without (P=0.043; OR=1.289, 95%CI: 1.009, 1.648); it was also higher in smokers than in non-smokers (P=0.004; OR=1.507, 95%CI: 1.137, 1.999).
Conclusion Gender, noise intensity, and smoking are the main influencing factors of high-frequency hearing loss in noise-exposed workers in this automobile manufacturing company. Controlling smoking and reducing noise exposure intensity may reduce the occurrence of high-frequency hearing loss in workers.
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