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similar analysis but used the strength capacity of a large
strong man in the denominator of the LSR, thus
normalizing the data such that it would be very unlikely to encounter a job have lifting requirements with
an LSR exceeding 1.0. Their results showed that for jobs with a LSR between 0.8 and 1.0 the job-related
low back incidence rate approached 4 while the incidence rates associated with lower LSRs were less
than 2.
The strength of the 3DSSPP approach is in its ability to assess risks associated with one time exertions,
because it compares directly the required moments of the task with population strength data. Another
strength of the model is its ability to estimate spine compression values that can be compared with estab-
lished load limits to assess relative risk. The limitations of this approach are in its ability to quantify risk
in jobs that are highly repetitive in nature but do not have torque or spine compression forces that
approach human strength capabilities or spine compression load limits.
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35.5 Discussion of Similarities and Differences
There are several similarities between these three assessment tools that should be identified. First, and not
surprisingly, each considers the moment about the spine to be a central factor in quantifying risk. The
three tools do, however, take different approaches to using this moment value. The 3DSSPP model
uses the computed moment value in comparison to the moment generating capabilities of the popu-
lation. The LMM model uses peak moment value as one of five parameters in the multiple logistic
model, weighing it equally with the five other parameter. Finally, the NIOSH Lifting Equation considers
the components of the moment (i.e., the moment arm and the load) at two different stages of the analy-
sis. The moment arm is considered in the process of calculating the RWL (through the horizontal mul-
tiplier), while the load magnitude is not considered until the LI is computed. A second characteristic that
these models share is an appreciation for the importance of the trunk posture during the lifting activity.
In the LMM model, this comes in the form of the peak sagittal flexion parameter. In the 3DSSPP and
NIOSH Lifting Equation model this is considered more indirectly. In the 3DSSPP model, the posture
is reflected in the moment created by the mass of the torso in the static model, while in the NIOSH
model these postural effects are considered in the vertical multiplier (quantifying the degree of sagittal
flexion required) and asymmetry multiplier (describing the required trunk motion in the sagittal
plane). One limitation that all three assessment tools share is their limited ability to address highly vari-
able biomechanical requirements seen in some industries, the warehousing and construction industries
being two that are notorious for being high-risk industries for back injuries. Gaining an appreciation for
the range of stress levels that are experienced by the worker and the relative frequency of experiencing
these levels could provide valuable insight into the cumulative and acute trauma risk posed. This particu-
lar limitation is addressed in the hybrid modeling approach described later in this chapter.
There are some important differences in the conceptual approaches that are noteworthy as well. Based
on our current understanding of the etiology of occupation-related low back disorders it is clear that each
of these assessment tools addresses an important facet of the low back injury risk paradigm, but that
none of these models individually are able to identify all high risk activities. This notion is supported
by Lavender et al. (1999) that showed poor correlation between the estimates of low back disorder
risk that were produced by these three tools when assessing a variety of MMH tasks. These authors
used each of these three assessment tools (along two variations of the United Auto Workers (UAW)-
General Motors Ergonomic Risk Factor Checklist) to evaluate a mix of 93 randomly selected production
jobs performed by 178 autoworkers. These authors showed that the intercorrelations between methods
ranged from 0.21 to 0.80. For the three assessment tools considered in the paper the correlations were
0.54, 0.39, and 0.21 for LMM-NIOSH, LMM-3DSSPP, and NIOSH-3DSSPP comparisons, respect-
ively. These authors conclude by noting that some of the differences in this assessment techniques
may lie in their differential treatment of acute vs. cumulative loading characteristics.
Mirka et al. (2000) also highlighted some of the differences in these assessment tools but focused less
on the acute vs. cumulative trauma risk perspective and more on the mechanics of the tools themselves.
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