摘要
[目的]探索控制多种混杂因素对神经行为测试结果影响的途径。[方法]采用中文版计算机化神经行为测试组合(NES-C3),对作业场所平均空气铅尘轻微超过国家职业接触限值的某蓄电池厂37名工人(接触组)与不接触铅的他厂64名工人(对照组),采用SPSS统计软件中的广义线性模型(GLM)中的单因变量分析其性别、年龄、教育程度、计算机操作经验和测试前精神状态等混杂因素与效应指标的主效应。[结果]两组在短时记忆能力、计算能力、反应速度、注意力方面差异有显著性,而除平均反应时外,其他混杂因素对结果均无显著性影响。[结论] SPSS软件中的GLM单因交量分析,操作方便、可靠,可较好控制混杂因素对铅毒性神经行为作用测试结果之影响。
[Objective] To explore the statistical approach to control of confounding effects on neurobehavioral tests using NES-C3. [Methods] Neurobehavioral Evaluation System in Chinese Version 3(NES-C3) was applied to the industrial hygiene survey in a lead battery manufacturing company aimed at assessing lead-induced neurobehavioral effects among Pb-exposed workers. Thirth-seven workers, who had been exposed to an average lead levels slightly higher than that of national occupational exposure limit(0.05 mg/m^3, PC-TWA, lead dust),and 64 non-exposed workers as controls were involved in the study.The Univariate Analysis of General linear Model (GLM) was computed via SPSS statistical software to assess the confounding effects from gender,age,education,computer experience) and the mood state during testing. [Results] The results showed that the short-term memory, calculation ability,reaction time, and attention were significantly retarded compared with those of the controls( P < 0.05) .The confounding effects were well-assessed and controlled by the statistical approach with an exception of mean reaction time. [Conclusion] The Univariate Analysis of CLM seems to be a valid tool in the assessing and controlling of confounding effects on neurobehavioral tests.
出处
《环境与职业医学》
CAS
北大核心
2004年第S1期522-524,共3页
Journal of Environmental and Occupational Medicine
关键词
神经行为测试
混杂因素
神经性毒物
铅
Neurobehavioral Evaluation System-Chinese Version 3(NES-C3)
lead battery manufacturing
confounding effects
general linear model(GLM)
