Identifying Safe Load Moment Exposures for the Back

2009 ◽  
Vol 53 (14) ◽  
pp. 883-883
Author(s):  
Steven A. Lavender ◽  
William S. Marras ◽  
Sue A. Ferguson ◽  
Riley E. Splittstoesser ◽  
Gang Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Injury Risk ◽  
Physical Workload ◽  
Back Injury ◽  
Low Back ◽  
Distribution Centers ◽  
Back Disorders ◽  
Low Back Injury ◽  
Low Back Disorders ◽  
Back Disorder

Low back disorders continue to be the most common and significant work-related musculoskeletal disorders in the US. Identifying what constitutes a “safe” physical workload has been the biggest challenge facing injury prevention efforts. Prior low back injury risk models have focused on manufacturing activities where there is limited variability in the parameters used to describe the exposures to low back disorder risk factors. Lifting tasks in distribution centers can have considerably more variability in load and physical layout. The goal of this project was to identify and quantify measures that characterize the biomechanical risk factors, including measures of the load moment exposure, and measures that characterize the duty cycle that are predictive of low back disorders in distribution centers. Thus, our hypothesis was that we could define a relationship between moment exposure parameters and the low back disorder incidence rates. A cross-sectional study was designed to examine the mechanical risk factors responsible for reported low back injury in distributions centers. The physical exposure was measured on 195 workers on 50 jobs in 21 distribution centers using a sonic-based Moment Exposure Tracking System (METS). The METS measures load, force, load moment, torso kinematics, and temporal parameters of the job simultaneously. For each job, low back injury rates were collected retrospectively from the company's records over the prior 3-year period. The data were used to develop a risk model designed to predict back injury risk based upon direct measures of load and load moment exposure. The model incorporates biomechanical variables which include the load moment and horizontal sliding forces, as well as a temporal variable indicating the opportunity for micro-breaks during the work process. Overall, the presented model has very good sensitivity (87%) and specificity (73%).

Measuring low back injury risk factors in challenging work environments: An evaluation of cost and feasibility

2007 ◽  
Vol 50 (9) ◽  
pp. 687-696 ◽  
Author(s):  
Catherine Trask ◽  
Kay Teschke ◽  
Judy Village ◽  
Yat Chow ◽  
Peter Johnson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Injury Risk ◽  
Work Environments ◽  
Back Injury ◽  
Low Back ◽  
Low Back Injury ◽  
Injury Risk Factors

scholarly journals Understanding Causal Pathways for Occupationally Related Low Back Disorders

2019 ◽  
Vol 63 (1) ◽  
pp. 955-956
Author(s):  
Sue A. Ferguson ◽  
William S. Marras ◽  
Jay M. Kapellusch ◽  
Matthew S. Thiese ◽  
Kermit G. Davis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Care ◽  
Risk Factor ◽  
Low Back Pain ◽  
Back Pain ◽  
Low Back ◽  
Back Disorders ◽  
Personal Risk ◽  
Low Back Disorders ◽  
Back Disorder

Extended Abstract Low back pain has been a leading cause of disability worldwide for nearly two decades (Hartvigsen et al 2018). In a study of US health care spending between 1996 through 2013, low back and neck pain was the health care condition with the highest increase in spending (Dieleman et. al. 2016). Continued increases in health care costs due to low back pain are not sustainable. Therefore, we need to develop better low back disorder prevention plans or tools. In order to prevent occupational low back disorders several tools (ie. NIOSH lifting guide, 3DSSPP, Snook Tables, Lumbar Motion Monitor risk model, REBA, LiFFT) have been developed to quantify the biomechanical or physical exposure risk. There are a multitude of risk factors for low back disorders including psychological, psychosocial, and personal factors none of which are included in the available ergonomics tools (Ferguson and Marras, 1997). The goal of this panel is to promote discussion of the biopsychosocial risk factors that lead to low back disorders and disability. Health care providers suggest that patient advocacy should include preventing prolonged work loss (Nguyen and Randolph, 2007) yet one of the most common personal risk factors of low back pain is previous history of low back pain. The prevention tools above do not include any personal risk factors regarding an individual’s low back health status or any other personal risk factor. Should a new low back injury prevention tool include some personal risk factors for previous low back injury or some other personal risk factor? What about a smoking status risk factor or since sitting is the new smoking what about a sitting risk factor? What about psychosocial factors such as supervisor support or co-worker support? What new tools might we need? What stakeholders to do we need or want at the table in order to develop a tool that will actually be effective and who will the users be? The National Institute of Occupational Safety and Health funded several field studies in the 2000s to examine biomechanical exposure as risk factors of low back disorders. Several of the panelists had studies in the group. A consortium was formed to pool data where possible to increase statistical power to measure these more complex relationships. The common surveillance questionnaire measures of low back disorder included varying degrees of low back disorder severity. The surveillance measures in order from least severe to most severe were 1) any low back pain, 2) seeking medical care due to low back pain and 3) self-reported lost time due to low back pain in the past year. The panelists will be asked to address how the role of their specific topic may change as a function of the various surveillance measures. What does a new tool being developed really need to prevent (low back pain, seeking medical care, self-reported lost time, low back disability)? We will have each panel member discuss causality from several different multidimensional perspectives and will have an open debate/discussion. We will also allow time for audience perspectives Panelist Roles Dr. Jay Kapellusch will be discussing the role of psychophysics and the NIOSH lifting equation. Dr. Matthew S. Thiese will be examining the role of psychosocial risk factors. Dr. Kermit Davis will address interventions. Dr. Sean Gallagher will be probing specific physical injury mechanisms. Dr. William S. Marras will be presenting the multidimensional causal pathway for low back disorders.

Building a Low Back Injury Risk Classifier Using Evolutionary Computation

1998 ◽  
Vol 42 (12) ◽  
pp. 881-885 ◽  
Author(s):  
Brian J. Carnahan ◽  
Mark S. Redfern
Keyword(s):  
Evolutionary Computation ◽  
Injury Risk ◽  
Classification Performance ◽  
Back Injury ◽  
Low Back ◽  
Risk Models ◽  
Low Back Injury ◽  
Low Back Disorders ◽  
Low Incidence ◽  
Gp Model

Injury risk models can play a key role in ergonomic worksite analysis directed at preventing low back disorders. Such models can be used to classify lifting tasks as having the same characteristics as those tasks which have had a high (or low) incidence rate of back injuries. Two evolutionary computation techniques (genetic algorithms GA, and genetic programming GP) were used to construct low back injury risk models. A GA model, GP model, logistic regression model, and an artificial neural network were constructed and tested using 235 documented lifting task cases. Results indicated that the evolutionary approaches were superior to the other models in terms of classification performance and parsimony.

Physical Demands and Low-Back Injury Risk Among Children and Adolescents Working on Farms

2004 ◽  
Vol 10 (4) ◽  
pp. 255-272 ◽  
Author(s):  
W. G. Allread ◽  
J. R. Wilkins III ◽  
T. R. Waters ◽  
W. S. Marras
Keyword(s):  
Children And Adolescents ◽  
Injury Risk ◽  
Back Injury ◽  
Low Back ◽  
Physical Demands ◽  
Low Back Injury

Health-Related and Sociodemographic Risk Factors for Disability Pension due to Low Back Disorders

2011 ◽  
Vol 53 (5) ◽  
pp. 488-496 ◽  
Author(s):  
Sanna Pietikäinen ◽  
Karri Silventoinen ◽  
Pia Svedberg ◽  
Kristina Alexanderson ◽  
Antti Huunan-Seppälä ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disability Pension ◽  
Low Back ◽  
Back Disorders ◽  
Low Back Disorders ◽  
Sociodemographic Risk ◽  
Health Related

Recurrence of Occupational Low Back Disorders: The Influence of the Definition of Recurrence

2005 ◽  
Vol 49 (14) ◽  
pp. 1283-1286
Author(s):  
Sue A. Ferguson ◽  
William S. Marras ◽  
Deborah L. Burr
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Medical Attention ◽  
Low Back ◽  
Back Disorders ◽  
Low Back Disorders ◽  
Back Disorder ◽  
Lost Time ◽  
Definition Of ◽  
Pain Symptoms

Recurrent low back disorder rates vary from as low as 1% to as high as 82%. The sample population as well as definition of recurrence influence the rate of recurrence found in the literature. The objective of this study was to examine four definitions of recurrent low back disorders on the same population. Two hundred and six workers with manual material handling jobs who had reported work-related low back pain were monitored prospectively for recurrent low back disorders for 1-year. Recurrence of low back disorder was defined as 1) low back pain symptoms, 2) a visit to a medical provider (company or personal) for low back pain, 3) self-reported time off work due to low back pain, and 4) confirmed (by employer) lost time due to back pain. The recurrence rates were 58% for pain symptoms, 36% for seeking medical attention, 15% for lost time and 10% for confirmed lost time.

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