Two new methods for assessing risk factors for occupational low back pain due to manual lifting in a prospective epidemiological study.
Waters-TR; Lu-M-L; Piacitelli-LA; Werren-DM
NORA Symposium 2006: Research Makes a Difference! April 18-26, 2006, Washington, DC. Washington, DC: National Institute for Occupational Safety and Health, 2006 Apr; :288-289
Occupational low back disorders (OLBDs) represent a significant health problem for workers and a significant financial burden for industry. Most of these disorders are attributed to manual lifting on the job. Among the risks for OLBDs found in the literature, trunk posture and spinal loading are found to be two major predictors (Wells 1997, Norman 1998, Marras 1999). Traditionally, the peak and average of these two risk factors have been used as variables for predicting low back disorders; however, recent literature has indicated that accumulation and interaction of exposures to the two risk factors may also play an important role in developing OLBDs. In order to prevent these disorders, it is important to understand the physical risk factors associated with manual lifting that are responsible their development. One of the objectives of this study was to develop new methods for measuring the risk factors for OLBDs in a longitudinal field study of workers engaged in manual lifting activities. The methods must allow for the capture of spinal load data for every lift performed by a worker over a selected period of time and an analysis of adverse postures used by the worker during the course of the exposure period. The first method is a spinal load model for estimating cumulative spinal load-time integrals over a specified time period, such as a shift, week, month, or year. This method employs a laboratory-based motion capture technology whereby each lift is simulated by a subject in a laboratory and the posture is then passed to a 3D biomechanical model for computation of the disc compression force, anterior and posterior shear force, spinal moments, and other musculoskeletal loads for each lift. Custom software is then used to extract the posture data for each lift and translate it into readable data for the biomechanical model in order to calculate the total cumulative load which is obtained by summing the loads over time. Previous researchers have suggested that cumulative load may be a strong predictor of risk of OBLDs. The second method is a common metric approach involving calculating accumulation and interaction of the hand loading and posture to predict low back disorders using Multimedia Video Task Analysis software, developed by researchers at the University of Wisconsin. The software allows quantifying time-based postural and hand loading analysis by reviewing frames of video (10-15 minutes per job) containing manual lifting activities recorded in the study sites. Analysts review each frame of the selected video and code hand position and trunk posture of the workers using user-defined events including hand loading (yes, or no) and multiple levels of trunk deviation (flexion and asymmetry). The cumulative temporal interaction of the hand loading and trunk deviation data are calculated and used as the primary variable for predicting the low back disorder incidence rates surveyed by health questionnaires. Percent time and frequency of hand loading and trunk deviation for the job cycle are also included in the common metric approach for testing their significance of predicting low back disorder incidence rates.
Epidemiology; Occupational-health; Back-injuries; Risk-factors; Risk-analysis; Workers; Worker-health; Posture; Injury-prevention; Injuries; Models; Questionnaires
Disease and Injury: Low Back Disorders
NORA Symposium 2006: Research Makes a Difference! April 18-26, 2006, Washington, DC.