Occhipinti E, Colombini D
Research Unit 'Ergonomics of Posture and Movement, Foundation 'IRCCS Policlinico-Mangiagalli-Regina Elena', Milano, Italy.
Ergonomics. 2007 Nov;50(11):1727-39. doi: 10.1080/00140130701674331.
A database has been established combining existing data for 23 groups of workers with different level of exposure to repetitive movements of the upper limbs. For all groups, data were available regarding an exposure index (OCcupational Repetitive Actions - OCRA index) and clinically determined UL-WMSDs outcomes (PA = Prevalence of workers affected by one or more UL-WMSDs; PC = Prevalence of single diagnosed cases of an UL-WMSDs). Using these data, new critical values of the OCRA index have been estimated for discriminating different exposure levels (green, yellow, red areas) and new forecasting models of expected PA and PC in exposed populations based on OCRA exposure indexes. The new critical values of the OCRA index were estimated by an original approach in which data for the effect variable (PA) in a reference population not exposed to the relevant risks are combined with the regression function between OCRA and PA. The best simple regression functions between OCRA exposure indexes and health outcomes variables (PA; PC) were researched to obtain forecasting models of effects starting from exposure. Discussion of the results obtained considers their intrinsic limitations, as they are based on prevalence studies, as well as providing recommendations and cautions in the use of the proposed classification system and forecasting models when the OCRA method is applied.
已建立一个数据库,该数据库整合了23组上肢重复性运动暴露水平不同的工人的现有数据。对于所有组,均有关于暴露指数(职业重复性动作——OCRA指数)以及临床确定的上肢肌肉骨骼疾病结局的数据(PA = 受一种或多种上肢肌肉骨骼疾病影响的工人患病率;PC = 上肢肌肉骨骼疾病单例确诊病例的患病率)。利用这些数据,已估算出OCRA指数的新临界值,用于区分不同的暴露水平(绿色、黄色、红色区域),并基于OCRA暴露指数建立了暴露人群中预期PA和PC的新预测模型。OCRA指数的新临界值是通过一种原始方法估算得出的,该方法将未暴露于相关风险的参考人群中效应变量(PA)的数据与OCRA和PA之间的回归函数相结合。研究了OCRA暴露指数与健康结局变量(PA;PC)之间最佳的简单回归函数,以获得从暴露开始的效应预测模型。对所得结果的讨论考虑了其内在局限性,因为这些结果基于患病率研究,同时还就应用OCRA方法时所提议的分类系统和预测模型的使用提供了建议和注意事项。