Auburn University, Industrial and Systems Engineering Department, Auburn, AL, USA.
Auburn University, Industrial and Systems Engineering Department, Auburn, AL, USA.
Appl Ergon. 2019 Jan;74:67-73. doi: 10.1016/j.apergo.2018.08.007. Epub 2018 Aug 17.
The impact of manual material handling such as lifting, lowering, pushing, pulling and awkward postures have been studied, and models using these external demands to assess risk of injury have been developed and employed by safety and health professionals. However, ergonomic models incorporating personal characteristics into a comprehensive model are lacking. This study explores the utility of adding personal characteristics such as the estimated L5/S1 Intervertebral Disc (IVD) cross-sectional area, age, gender and Body Mass Index to the Revised NIOSH Lifting Equation (RNLE) with the goal to improve risk assessment. A dataset with known RNLE Cumulative Lifting Indices (CLIs) and related health outcomes was used to evaluate the impact of personal characteristics on RNLE performance. The dataset included 29 cases and 101 controls selected from a cohort of 1022 subjects performing 667 jobs. RNLE risk assessment was improved by incorporation of personal characteristics. Adding gender and intervertebral disc size multipliers to the RNLE raised the odds ratio for a CLI of 3.0 from 6.71 (CI: 2.2-20.9) to 24.75 (CI: 2.8-215.4). Similarly, performance was either unchanged or improved when some existing multipliers were removed. The most promising RNLE change involved incorporation of a multiplier based on the estimated IVD cross-sectional area (CSA). Results are promising, but confidence intervals are broad and additional, prospective research is warranted to validate findings.
已经研究了手动搬运(如举重、降低、推、拉和姿势不当)的影响,并且已经开发并由安全和健康专业人员使用了使用这些外部要求来评估受伤风险的模型。然而,将个人特征纳入综合模型的人体工程学模型却缺乏。本研究探讨了将个人特征(如估计的 L5/S1 椎间盘(IVD)横截面积、年龄、性别和体重指数)添加到修订后的 NIOSH 举重方程(RNLE)中的效用,目的是改善风险评估。使用具有已知 RNLE 累积举重指数(CLI)和相关健康结果的数据集来评估个人特征对 RNLE 性能的影响。该数据集包括从 1022 名受试者的队列中选择的 29 例和 101 例对照,这些受试者完成了 667 项工作。通过纳入个人特征,RNLE 风险评估得到了改善。将性别和椎间盘大小乘数添加到 RNLE 中,将 CLI 的 3.0 的优势比从 6.71(CI:2.2-20.9)提高到 24.75(CI:2.8-215.4)。同样,当删除某些现有乘数时,性能保持不变或得到改善。最有前途的 RNLE 变化涉及包含基于估计的 IVD 横截面积(CSA)的乘数。结果很有希望,但置信区间较宽,需要进行额外的前瞻性研究来验证发现。