贝叶斯决策分析法在某汽车制造企业苯职业暴露评估中的应用

Application of bayesian decision analysis in the assessment of benzene occupational exposure in one automobile manufacture enterprise

目的应用贝叶斯决策分析法进行汽车制造企业苯职业暴露评估,并与传统评估方法比较,为职业暴露风险评估和管控提供方法和依据。方法选取某汽车制造企业手工喷漆房的作业人员作为评估的相似暴露组,收集2013—2017年苯暴露水平监测数据,通过引入专家权重法对贝叶斯决策分析法进行优化,并应用优化后的方法对相似暴露组苯职业暴露进行评估,并将评估结果与传统统计方法所得结果进行比较。结果贝叶斯决策分析法评估结果显示,相似暴露组暴露水平为2级(10%~50%LTWA)。传统统计方法评估结果显示,当样本量少时,暴露水平为3级(50%~100%LTWA)或4级(>100%LTWA);当样本量充足时,传统统计方法判断结果与贝叶斯决策分析法判断结果相同,暴露水平均判定为2级。结论贝叶斯决策分析法结合了专家经验和监测数据,能有效解决小样本情况下用传统统计方法计算暴露水平结果偏高的问题,在职业暴露评估中有较强优势。

Objective To assess the exposure level of benzene of one automobile manufacture enterprise by bayesian decision analysis method, and to compare it with traditional evaluation method, thus to supply the reference for the benzene occupational protection in automobile manufacture enterprise. Methods Traditional statistical analysis method and bayesian decision analysis method which adopted the weighted expert method were used in evaluating benzene exposure level of hand spray-painted workers in an automobile manufacturing enterprise respectively, and the calculation results by these two methods were compared. Results Calculation results of bayesian decision analysis showed that exposure level of the similar exposure group is level 2（10%-50%LTWA）. The exposure level calculated by the traditional statistical method was higher than the one calculated by the bayesian decision analysis method,which was rated as level 3（50%-100% LTWA） or level 4（100% LTWA）.The exposure level calculated by traditional statistical method and bayesian analysis method were concordant when the sample size is enough. Conclusion Traditional statistic method was likely to overestimating the exposure level when the sample was small. The bayesian decision analysis method which combined the experts＇ experience and surveillance data could solve the problem mentioned above.