刘浩中, 冯简青, 潘文娜, 王淑玉, 陈浩, 刘新霞. 某市汽车零件制造企业噪声危害分级及听力损失现状调查[J]. 职业卫生与应急救援, 2020, 38(3): 228-232. DOI: 10.16369/j.oher.issn.1007-1326.2020.03.004
引用本文: 刘浩中, 冯简青, 潘文娜, 王淑玉, 陈浩, 刘新霞. 某市汽车零件制造企业噪声危害分级及听力损失现状调查[J]. 职业卫生与应急救援, 2020, 38(3): 228-232. DOI: 10.16369/j.oher.issn.1007-1326.2020.03.004
LIU Haozhong, FENG Jianqing, PAN Wenna, WANG Shuyu, CHEN Hao, LIU Xinxia. Investigation on noise exposure level and workers' noise induced hearing loss in auto parts manufacturing enterprises[J]. Occupational Health and Emergency Rescue, 2020, 38(3): 228-232. DOI: 10.16369/j.oher.issn.1007-1326.2020.03.004
Citation: LIU Haozhong, FENG Jianqing, PAN Wenna, WANG Shuyu, CHEN Hao, LIU Xinxia. Investigation on noise exposure level and workers' noise induced hearing loss in auto parts manufacturing enterprises[J]. Occupational Health and Emergency Rescue, 2020, 38(3): 228-232. DOI: 10.16369/j.oher.issn.1007-1326.2020.03.004

某市汽车零件制造企业噪声危害分级及听力损失现状调查

Investigation on noise exposure level and workers' noise induced hearing loss in auto parts manufacturing enterprises

  • 摘要:
    目的 调查珠三角某市中型汽车零件制造企业生产岗位噪声危害分级及听力损失(noise induced hearing loss,NIHL)现状。
    方法 随机选择3家在珠三角某市的中型汽车零件制造企业的全部生产岗位及608名噪声接触人员作为研究对象,调查噪声危害情况及工人NIHL检出情况。用二元logistic回归模型探讨NIHL的影响因素。
    结果 3家汽车零件制造企业噪声作业岗位LEX,W值超标率为39.6%(89/225),NIHL的总检出率为26.3%(160/608)。冲压和钻孔岗位的中度和重度危害级别岗位占比及岗位工人NIHL的检出率高于其他岗位(P < 0.05)。中度危害和重度危害噪声作业岗位防护设施的配备率和生产工人佩戴护耳器的比例高于其他危害级别岗位(P < 0.01)。logistic回归分析结果显示:分别相比年龄 < 40岁、工龄 < 3年、噪声危害在轻度以下,年龄≥ 40岁、工龄≥ 3年、噪声危害在轻度及以上是NIHL的独立影响因素(OR = 1.75、2.03、1.99,P < 0.05);分别相比无防护设施、未佩戴护耳器,有防护设施、佩戴护耳器则是对抗噪声危害的保护因素(OR = 0.68、0.59,P < 0.05)。
    结论 珠三角某市中型汽车零件制造企业生产岗位噪声危害较重,作业工人NIHL患病率较高。工艺流程的改进是降低噪声水平的关键。应对工人进行全面的培训,使其了解噪声危害,正确使用护耳器。对接触噪声时间较长的工人应给予更多的关注。

     

    Abstract:
    Objective To understand the workers' noise exposure level and noise induced hearing loss (NIHL) in the middle-size auto parts manufacturing enterprises in a city.
    Methods A total of 3 enterprises, 608 noise-exposed workers in a city located in Pearl River Delta were studied. The noise level at their workplaces were measured and NIHL was examined among these workers. Binary logistic regression was used to analyze the affecting factors of NIHL.
    Results The noise level (LEX, W value)at 39.6%(89/225)workplaces were higher than 85 dB(A)and totally there were 160 workers (26.3%)diagnosed as the cases with NIHL. The highest noise level at both the stamping and the drilling worksites were found and most were ranked as severe. The workers in these sites had higher morbidity of NIHL(P < 0.05). It was found that the equipment of protective facilities at worksites with higher noise level (ranked as moderate or severe) was better than that in other worksites(P < 0.01)and the proportion of wearing ear protectors among the workers at these sites was higher than workers at other sites with relatively lower noise level. The binary logistic regression analysis showed that the older age (over 40 vs. under 40 year old), longer exposure time(over 3 vs. less 3 years) and higher noise exposure level(the moderate and/or severe vs. the mild ranking) were risk factors(OR = 1.75, 2.03 and 1.99, respectively, P < 0.05), while effective equipment of protective facilities and wearing ear protector were protective factors(OR = 0.68 and 0.59, respectively, P < 0.05).
    Conclusion The noise hazards in middle-size auto parts manufacturing enterprises in this city were severe and workers had a higher prevalence of NIHL. The improvement of technological process is the key to reduce noise level and the workers should be trained fully to understand the noise hazards and use ear protectors correctly. More attention should be given to older workers with longer exposure time.

     

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