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化工行业职业性机械伤害危险因素的病例-交叉方法研究 被引量:8

A Case-crossover Study on Mechanical Injuries in Chemical Industry
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摘要 目的 研究化工行业机械伤害的有关诱发因素 ,估计其作用强度。方法 采用病例 -交叉设计的方法。以操作和检修时受伤的化工工人为研究对象 ,每个对象在受伤后 2d内完成调查 ,收集他们受伤前10min、上一工作日同一段时间和受伤前 1周内有关诱发因素暴露的信息 ,用配对时间段方法和一般频数法进行分析 ,评估各种诱发因素的危险度。结果 一般频数法分析的结果表明 ,操作方法异常、设备工具缺陷、工作紧迫、注意力不集中、不使用防护用品、精神状况较差、与同事配合不协调、工作环境发生变化等瞬时危险因素的RR值及 95 %可信限的下限均大于 1。配对时间段方法分析的结果与其相似 ,但 95 %可信限较宽。结论 化工行业职业性机械伤害的发生存在着诸多诱发因素。病例 -交叉研究中的一般频数法与配对时间段方法相比 ,前者所得结果较为可靠 ,研究的相对效率较高。建议进一步使用多个时间段方法进行研究 。 Objective To study potential risk factors of mechanical injuries in chemical industry and the intensity of these factors.Methods The case crossover design was used.Injured workers were interviewed within 2 days after got injured.Exposure information on potential risk factors at 10 minutes before the injury,the same period in previous working day and a week before was collected.Matched time interval approach and general frequency analysis were used to evaluate these factors.Results In general frequency analysis,instantaneous risk factors such as violation of operating procedure,malfunction of equipment,stress or work pressure,being distracted,without protective equipment,loss of spirit,coordinating badly with colleague and change of work environment were evaluated.All of their relative risks and lower limit of 95% CI were more than 1.In matched time interval analysis,results were similar to the above,except for much wider confidence intervals.Conclusions In chemical industry,the occurrence of occupational mechanical injuries could be related to many risk factors mentioned above.Compared with matched time interval approach,the general frequency analysis showed higher reliability and efficiency.It is suggested that the multiple interval approach should be used for further research to reduce biases of confounding factors.
出处 《工业卫生与职业病》 CAS CSCD 北大核心 2003年第2期88-91,共4页 Industrial Health and Occupational Diseases
基金 复旦-利宝职业安全研究基金 ( 2 0 0 0 -1)
关键词 化工行业 机械伤害 病例-交叉研究 诱发因素 Chemical industry Mechanical injuries Case crossover design Risk factors
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