梁灿坤, 成财达, 胡魁, 符传东. 反事实分析方法在职业性噪声所致听力损失评估中的应用研究[J]. 职业卫生与应急救援, 2018, 36(2): 113-116. DOI: 10.16369/j.oher.issn.1007-1326.2018.02.006
引用本文: 梁灿坤, 成财达, 胡魁, 符传东. 反事实分析方法在职业性噪声所致听力损失评估中的应用研究[J]. 职业卫生与应急救援, 2018, 36(2): 113-116. DOI: 10.16369/j.oher.issn.1007-1326.2018.02.006
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LIANG Cankun, CHENG Caida, HU Kui, FU Chuandong. Application of counterfactual analysis in assessing hearing loss caused by occupational noise[J]. Occupational Health and Emergency Rescue, 2018, 36(2): 113-116. DOI: 10.16369/j.oher.issn.1007-1326.2018.02.006
Citation: LIANG Cankun, CHENG Caida, HU Kui, FU Chuandong. Application of counterfactual analysis in assessing hearing loss caused by occupational noise[J]. Occupational Health and Emergency Rescue, 2018, 36(2): 113-116. DOI: 10.16369/j.oher.issn.1007-1326.2018.02.006
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反事实分析方法在职业性噪声所致听力损失评估中的应用研究

Application of counterfactual analysis in assessing hearing loss caused by occupational noise

    摘要
  • 摘要:
    目的 评价反事实分析方法在职业性噪声所致听力损失评估中的应用价值。
    方法 以7类行业42家大中小型企业22 690名在岗期间接触有毒有害因素的作业工人为研究目标人群, 从目标人群中选择14 823名噪声作业工人纳入暴露组, 以42家企业中1 311名上岗前噪声作业工人为反事实背景, 评估职业性噪声所致听力损失的人群归因分值。
    结果 目标人群的噪声暴露率为65.33%, 暴露相对危险度为2.00, 人群归因分值为39.51%。36岁以上年龄组的人群归因分值高于35岁以下人群, 小型企业的人群归因分值高于大型和中型企业人群; 各类行业的人群归因分值比较, 金属制品业最高, 电子设备制造业最低。
    结论 人群归因分值能够反映职业性噪声所致听力损失的人群分布特征, 建议推广和应用反事实分析方法进行职业性噪声所致听力损失的归因研究。

     

    Abstract:
    Objective To evaluate the applied value of counterfactual analysis in assessing hearing loss caused by occupational noise.
    Methods Totally 22 690 workers exposed to occupational hazards employed in 42 enterprises distributed in 7 types of industries were considered to be the target population. Among them 14 823 noise-exposed workers were considered to be exposure group, while 1 311 workers who received pre-employment physical examination were considered to be counterfactual background. The population attributable fractions(PAF) of hearing loss caused by occupational noise were assessed.
    Results The noise-exposed rate of the target population was 65.33%, the relative risk was 2.00 and the PAF was 39.51%. The PAF of elder age group over 36 years old was higher. The PAF of small-scale enterprises was higher than medium or large-scale enterprises. The PAF of metal products industry was highest, while the PAF of electronics manufacturing industry was lowest among all kinds of industries.
    Conclusion Preliminary study showed that the PAF can reflect the population distribution characteristics of hearing loss. It is suggested to promote and apply counterfactual analysis to study on hearing loss caused by occupational noise.

     

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