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Can the Revised NIOSH Lifting Equation Be Improved by Incorporating Personal Characteristics?



Details

  • Personal Author:
  • Description:
    The impact of manual material handling such as lifting, lowering, pushing and pulling have been extensively studied. Many models using these external demands to predict injury have been proposed 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, height, age, gender and Body Mass Index (BMI) to the Revised NIOSH Lifting Equation (RNLE) with the goal to improve injury prediction. 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 1,022 subjects performing 667 jobs. RNLE performance was significantly 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, PPV: 0.60, NPV: 0.82) to 24.75 (CI: 2.8-215.4, PPV: 0.86, NPV: 0.80). The most promising RNLE change involved incorporation of the multiplier based on the estimated IVD cross-sectional area (CSA). This multiplier was developed by normalizing against the IVD CSA for a 50th percentile woman. This multiplier could assume values greater than one (for subjects with larger IVD CSA than a 50th percentile woman). Thus, CLI could both decrease and increase as a result of this multiplier. Increases in RNLE performance were achieved primarily by decreasing the number of RNLE false positives (e.g., some CLIs for uninjured subjects were reduced below 3.0). Results are promising, but confidence intervals are broad and additional, prospective research is warranted to validate findings. [Description provided by NIOSH]
  • Subjects:
  • Keywords:
  • ISBN:
    9783319960821
  • ISSN:
    2194-5357
  • Publisher:
  • Document Type:
  • Funding:
  • Genre:
  • Place as Subject:
  • CIO:
  • Topic:
  • Location:
  • Volume:
    820
  • NIOSHTIC Number:
    nn:20068839
  • Citation:
    Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018): Volume III: Musculoskeletal Disorders, (Advances in Intelligent Systems and Computing). Bagnara S, Tartaglia R, Albolino S, Alexander T, Fujita Y, eds. Cham, Switzerland: Springer, 2018 Aug; 820:553-560
  • Contact Point Address:
    Menekse Salar Barim, Oak Ridge Institute for Science and Education (ORISE) Research Fellow, Cincinnati, OH, 45202, USA
  • Email:
    mzs0053@auburn.edu
  • Editor(s):
  • Federal Fiscal Year:
    2018
  • Performing Organization:
    University of Alabama at Birmingham
  • Peer Reviewed:
    False
  • Start Date:
    20050701
  • Source Full Name:
    Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018): Volume III: Musculoskeletal Disorders, (Advances in Intelligent Systems and Computing)
  • End Date:
    20270630
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:c2e4094db7716746064adf3f74a749e906eeb99c0a5db9b542e5639e9515968ddda1a4f81dce68df9fc0383cd03b2af9e823c45b03a332ecf76564fb71d9f1c2
  • Download URL:
  • File Type:
    Filetype[PDF - 377.14 KB ]
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