Identifying Safe Load Moment Exposures for the Back

确定背部的安全负载力矩

• 批准号: 6314994
• 负责人: William Steven Marras
• 金额: $ 33.12万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-30 至 2005-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6314994
• 关键词: backache; biomechanics; clinical research; cooperative study; disease /disorder proneness /risk; human subject; occupational health /safety

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.

腰痛（LBP）继续代表领先 工人经历的与职业相关的肌肉骨骼疾病。 先前的监视研究（Marras等，1993; 1995）表明 与职业相关的LBP风险最强大的个人标记是 负载力矩（载荷幅度x距脊柱距离）。即使是这种粗略的措施 能够执行更多计算复杂的评估工具 作为NIOSH提升指南和修订方程（Marras等，1999）。在 此外，许多生物力学研究表明负载矩暴露 代表了下背部损伤机制的生物学上合理的途径。 但是，没有研究试图具体定义关联 在负载矩暴露的各个组件和LBP风险之间。因此， 这项研究的目的是探索如何暴露于各种组成部分 负载力矩（即占空比的组件）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完成 矩和时间暴露的大小各不相同。二 完成此目标是必要的。第一阶段将使用现有的 515个制造工作的数据库，以帮助了解 负载力矩和暴露频率。统计模型将被构建，并 经过测试以帮助了解时间暴露的哪些特征 可能提供敏感措施。此外，仪器将是 开发为精确监控负载矩暴露。最终组成部分 第一阶段将涉及所需的各个分销中心的招聘 创建一个前瞻性数据库（第二阶段）。第二阶段将利用这一刻 材料处理工业研究中的测量仪器。在 这项前瞻性研究，将在临床上监视1200名参与者 LBP状态的相关指标在开始和18个月的结束时 曝光期。在曝光期间，工作场所的组件将 受到监控，包括精确的负载力矩暴露，时间方面 暴露（例如占空比，累积暴露等），负载位置等。 工人将在8小时内进行监控。完成后 前瞻性观察期，伤害报告，临床背部变化 状态等将作为负载力矩和时间的函数评估 使用统计模型的暴露特征。另外，很容易测量 将制定最预测性模型度量的替代指标，因此 这些发现可用于评估最小设备的风险。 总的来说，这项研究不仅会增强我们对如何接触的了解 负载力矩的各个方面都会影响LBP风险，但也会导致 具有高灵敏度和特异性的适用措施以控制 在工作场所冒险。