Prediction Models for the Cross-Sectional Areas of Lower Lumbar Intervertebral Discs and Vertebral Endplates

Details

• Personal Author:
  Davis GA ; Foreman KB ; Gallagher S ; Gungor C ; Sesek RF ; Tang R
• Description:
  Current approaches to obtain lumbar morphometry data usually require expensive medical imaging technology, long processing time, and are often limited by small sample size. This study develops regression models for the cross-sectional areas (CSAs) of the lower lumbar (i.e., from L3/L4 to L5/S1 level) intervertebral discs (IVDs) and vertebral endplates (EPs) using both simple and complex anthropometric variables. CSAs were measured using OsiriX software, based on 3T magnetic resonance imaging (MRI) scans from a sample of 13 females and 22 males, aged between 20 and 40, and asymptomatic of low back disorders. Comprehensive body anthropometry data were collected and included in the regression analyses. Several multiple regression models were developed with varying levels of complexity. Subject stature, elbow dimensions, and ankle dimensions were statistically significant predictors for the CSAs of IVDs and EPs. Gender exhibited a more predictive relationship with the CSAs when compared to body weight and age. In general, regression models using newly proposed best subset procedure resulted in smaller prediction errors, compared to the models using easy-to-measure variables (i.e., gender, age, height, and weight). However, simple regression models are still worthy of investigation given the low cost, ease of data collection, and satisfactory model performance. [Description provided by NIOSH]
• Subjects:
  Biomechanical Phenomena Ergonomics Nervous System Occupational Health Safety
• Keywords:
  Anthropometry Author Keywords: Ergonomics Biomechanical Modeling Intervertebral Disc Low Back Disorders Lumbar Spine Magnetic Resonance Imaging MRI Regression Models Spinal Cord Vertebral Endplate

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• ISSN:
  0169-8141
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Alabama ; OSHA Region 4 ; OSHA Region 5 ; OSHA Region 8 ; Utah ; Wisconsin
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  12-34
• Volume:
  72
• NIOSHTIC Number:
  nn:20068592
• Citation:
  Int J Ind Ergon 2019 Jul; 72:12-34
• Contact Point Address:
  Ruoliang Tang, Department of Occupational Science and Technology, University of Wisconsin-Milwaukee, 2400 E. Hartford Ave., Milwaukee, WI, 53211, USA
• Email:
  tangr@uwm.edu
• Federal Fiscal Year:
  2019
• Performing Organization:
  University of Alabama at Birmingham
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  International Journal of Industrial Ergonomics
• End Date:
  20270630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:391cd76df6cafc1eecd7832c63d299e89fa0dfc9c44aacd7032f57e57d3caa449d285896a827c5525b38bfa5380bc64b6d3795bf19241c8357a9fb1b5ac427b3
• Download URL:
  https://stacks.cdc.gov/view/cdc/207198/cdc_207198_DS1.pdf
• File Type:
  [PDF - 1.18 MB ]