Identifying Safe Load Moment Exposures for the Back

下腰痛(LBP)仍然是最主要的 工人经历的职业性肌肉骨骼疾病。 以前的监测研究(Marras等人，1993；1995)表明 与职业相关的LBP风险的最可靠的个人标志是 载荷力矩(载荷大小x与脊椎的距离)。即使是这种粗略的措施 能够超越更复杂的计算评估工具，如 作为NIOSH提升指南和修正的方程(Marras等人，1999)。在……里面 此外，许多生物力学研究表明，负荷矩暴露 代表了一种生物学上看似可行的腰部损伤机制。 然而，还没有研究试图明确定义这种联系 各分量的负荷力矩暴露与LBP风险之间的关系。因此， 这项研究的目的是探索暴露于不同成分的 负荷矩(即占空比的组成部分)与LBP风险有关。这个目标 将通过开发和分析丰富多样的数据库来实现 其中时刻的大小以及时间曝光的大小是不同的。二 完成这一目标需要分阶段进行。第一阶段将使用现有的 包含515个制造工作岗位的数据库，以帮助了解 荷载力矩和曝光频率。将构建统计模型并 测试有助于理解时间暴露的哪些特征 可能会提供敏感的措施。此外，仪器设备将被 开发用于精确监控负载力矩曝光。的最后一个组件 第一阶段将涉及招聘所需的各种配送中心 创建预期数据库(第二阶段)。第二阶段将利用这一刻 材料搬运工业研究中的测量仪器。在……里面 这项前瞻性研究将对1200名参与者进行临床监测 18个月开始和结束时LBP状态的相关指标 曝光期。在暴露期间，工作场所的部件将 被监控，包括精确的负荷矩暴露、时间方面 曝光量(例如占空比、累积曝光量等)、负载位置等。 工人们将在8小时的班次中接受监控。在完成 前瞻性观察期、损伤报告、临床背部变化 状态等将作为负载力矩和时间的函数进行评估 使用统计模型的曝光特征。此外，易于测量 将制定最具预测性的模型措施的替代指标 这些发现可以用最少的设备来评估风险。 总的来说，这项研究不仅将增强我们对如何接触到 负荷矩的各个方面都会影响LBP风险，但也会导致 敏感度高、特异度高的防治措施 工作场所的风险。

Low back pain (LBP) continues to represent the leading occupationally-related musculoskeletal disorder experienced by workers. Previous surveillance studies (Marras et al., 1993;1995) have indicated that the most robust individual marker of risk for occupationally-related LBP is load moment (load magnitude x distance from the spine). Even this crude measure is capable of out performing more computationally complex assessment tools such as the NIOSH lifting guide and revised equation (Marras et al, 1999). In addition, many biomechanical studies suggest that the load moment exposure represents a biologically plausible pathway for a low back injury mechanism. However, no studies have attempted to specifically define the association between a various components of load moment exposure and LBP risk. Thus, the objective of this study is to explore how exposure to various components of load moment (i.e. components of the duty cycle) relate to LBP risk. This goal will be accomplished by developing and analyzing a rich and diverse database where the magnitude of the moments as well as the temporal exposure vary. Two phases will be necessary to complete this goal. Phase I will use an existing database of 515 manufacturing jobs to help understand the relationship between load moment and exposure frequency. Statistical models will be constructed and tested to help understand which features of the temporal exposure to moment might provide sensitive measures. In addition, instrumentation will be developed to precisely monitor load moment exposure. The final component of Phase I will involve the recruitment of various distribution centers needed to create a prospective database (phase II). Phase II will employ the moment measurement instrumentation in an industrial study of materials handling. In this prospective study, 1200 participants will be monitored for clinically relevant indicators of LBP status at the beginning and the end of an 18-month exposure period. During the exposure period, components of the workplace will be monitored including precise load moment exposure, temporal aspects of exposure (e.g. duty cycle, cumulative exposure, etc.), load position, etc. Workers will be monitored over an 8-hour shift. Upon completion of the prospective observation period, injury reporting, changes in clinical back status, etc. will be evaluated as a function of the load moment and temporal exposure characteristics using statistical models. In addition, easily measured surrogate indicators of the most predictive model measures will be developed so that these findings can be used to assess risk with minimal equipment. Collectively this study will not only enhance our knowledge of how exposure to various aspects of load moment affects LBP risk but will also lead to applicable measures with both high sensitivity and specificity for control of risk in the workplace.