| 摘 要: 目的 研究电焊烟尘致电焊工尘肺的风险分析方法，预测风险概率，为实施风险管理提供技术依据。方法 选取某大型农用机械加工电焊车间作为研究对象。采用Logistic回归模型的非线性回归分析，通过接尘浓度、工龄预测电焊工尘肺发病概率；采用计算机R语言进行接尘工龄、浓度与发病概率之间关系的风险分析；采用Logistic回归模型-蒙特卡洛模拟方法分析职业暴露与电焊工尘肺发病概率的分布规律。结果 依目前电焊烟尘浓度，电焊工暴露5年和10年、20年和30年发生尘肺的风险值分别为10-3~10-2、10-2~10-1。按职业生涯30年工龄计，发生电焊工尘肺的风险高于可接受风险水平，需要采取措施降低风险。结论 本研究建立的电焊工尘肺定量风险评价方法，以接尘工龄、烟尘暴露浓度与电焊工尘肺的风险概率作为风险目标，实用性强，易于在职业病危害评价中实际应用，为电焊工尘肺的预防控制提供了理论依据。 |
| 关键词: 电焊烟尘 电焊工尘肺 风险评价 Logistic回归模型 |
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中图分类号: R135.2
文献标识码:
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| 基金项目: 天津市科技支撑计划重点项目(13ZCZDSY02300) |
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| Risk assessment method of occupational exposure to welding fume and its application |
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Huang Deyin
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Institute of Occupational Health, Tianjin Bohai Chemical Industry Group Co. Ltd, Tianjin 300051
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| Abstract: Objective To research the risk assessment method of welder’s pneumoconiosis caused by welding fume exposure, predict its risk probability, thereby provide a theoretical basis for implementing risk management. Methods A electric welding workshop of certain large-scale agricultural machinery-processing factory was recruited in this study. The probability of welder’s pneumoconiosis was predicted according to welding fume concentration in air and exposure durations using logistic nonlinear regression analysis method; the relationship among probability of welder’s pneumoconiosis and exposure situation or concentration was studied by logistic regression model, and the distribution feature of the probability was assessed by Logistic regression model - Monte-Carlo simulation method. Results It was showed that under such levels of welding fume for 5 to 10 years, the risk values of pneumoconiosis would be between 10-3 and 10-2, if exposure time was 20 or 30 years, the value would be between 10-2 and 10-1. Assuming the welder’s career-life was 30 years,the risk was much higher than the acceptable level, therefore, the preventive measures must be taken for reducing the risk level. Conclusion This risk assessment method of welder’s pneumoconiosis was a quantitative approach, that could provide a practical tool and a theoretical basis for the prevention and control of welder’s pneumoco-niosis. |
| Keywords: welding fume welders' pneumoconiosis risk assessment logistic regression model |
