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CHAPTER 17/OCCUPATIONAL ERGONOMICS / 183
would be at risk (68). Contemporary quantitative assessments are recognizing the complex interaction of spine
position, frequency, and complex spine forces (compression, shear, and torsion) as more realistic assessments of
risk. However, these contemporary ergonomic assessments have not resulted in best practices or standards by
governmental agencies to date.
Ligament Tolerance Limits
The literature suggests that ligament tolerances are
affected by the load rate (69). Avulsion occurs at low load
rates and tearing occurs at high load rates. Hence load
rate may explain the increased risk associated with bending motions (velocity) that have been observed in surveillance studies (70) as well as injuries from slips or falls
that may be a result of injuries at greater load rates (24).
Posture can also play a role in tolerance. Under load, the
architecture of the interspinous ligaments can result in
significant anterior shear forces on the spine when flexed
in a forward bending posture (71). This result is consistent with the recent field obser vations of risk (10,54–56,
72,73). Studies have identified 60 Nm as the point at
which damage begins to occur (74). This f inding is consistent with the field observations (55,56) that ha ve found
exposures to external load mov ements of at least 73.6 Nm
as associated with high risk of occupationally related lo w
back pain reporting. Similarly, Norman et al. (10)
reported nearly 30% greater load movement exposure in
those jobs associated with risk of LBP. Mean movement
exposure associated with the LBP cases in this study was
182 Nm of total load movement (due to the load lifted
plus body segment weights).
Lordic spine curvature may also affect the loading and
tolerance of the spinal structures. The research team at
the University of Waterloo has shown that when lumbar
spinal curvature is maintained during bending the extensor muscles support the shear forces of the torso. If the
spine is flexed during bending and posterior ligaments
are flexed, then significant shear can be imposed on the
ligaments (75–77). Other studies have indicated that
shear tolerance (2000 to 2800 N) of the spine can be easily exceeded when the spine is in full flexion (49).
A strong temporal component to ligament recovery
appears to exist. Solomonow has found that ligaments
require long periods to regain structural integrity and
compensatory muscle activities are recruited (78–84).
Recovery time has been found to be se veral-fold the loading duration and can easily exceed the typical work-rest
cycles observed in industry.
Facet Joint Tolerance
Failure of the facet joints can occur in response to
shear loading. Investigations by McGill have concluded
that much of the tissues that load the facets have signif-
icant horizontal loading components and thus place
these structures at risk from occupational tasks (85).
Cripton et al. have estimated a shear tolerance for the
facet joints of 2000 N (86). These findings are consistent with industrial observations that have shown that
exposure to lateral motions and shears is associated with
increased risk of LBD reporting (10,55,56). Laboratory
assessments have confirmed that exposure to high lateral velocities can result in significant lateral shear
forces (87).
Torsional forces can also cause the facet joints to fail
(60). Exposure to high torsional movements, especially
when combined with high velocity, have been associated
with increased loading (88–91). Field studies have also
shown that these movements are associated with highrisk jobs (10,55,56). Loading when exposed to torsional
moments also depends upon the posture of the torso, with
greater load observed with more deviated postures from
neutral (89). Specific structure loading depends upon
specific posture and curvature of the spine since load
sharing occurs between the apoph yseal joints and the disc
(74). Therefore, spine posture dictates both the nature of
spine loading and whether damage might occur to the
facet joints or the disc.
Adaptation
An important consideration in the load-tolerance relationship is that of adaptation. Wolff ’s law dictates that
tissues adapt and remodel in response to load. In the case
of the spine, adaptation in response to load has been
acknowledged for bone (92), the ligaments (93), the disc
(94), and the vertebrae (95). Adaptation may explain the
observation that the greatest risk has been associated with
jobs involving both high loading and very low levels of
spinal loading, whereas job demands associated with
moderate spine loading have the lowest levels of risk
(96,97). Hence, there appears to be an ideal zone of loading that minimizes risk of exceeding the tolerance limit.
Psychophysical Tolerance Limits
The tolerance limits of tissue are typically derived
from cadaveric studies. While these mechanical limits
of performance may be adequate for the analysis of
tasks that may lead to an acute trauma event, their application to tasks that may lead to cumulative trauma disorder may be less clear. Since adaptation may play a
role, such quantitative analyses of the load-tolerance
relationship becomes difficult. In addition, some dynamic tasks such as pushing and pulling may be diff icult to characterize through quantitative biomechanical
analyses and their injury pathway may be poorly understood.
When mechanical tolerances are not known such as in
these circumstances, one approach used to establish tol-
184 /SECTION III/THE INJURED WORKER
erance limits has been the psychophysical approach. The
psychophysical approach is a means of strength testing
where subjects are asked to progressively adjust the
amount of load they can push, pull, lift, or carry until they
subjectively feel the load is of a magnitude that would be
acceptable to them over an 8-hour work shift. Task vari-
protective and minimizes low back pain at work. However, Snook (99) has observed that low back-related
injury claims were three times more prevalent in jobs
exceeding the psychophysically determined strength tolerance of 75% of men compared with jobs demanding
less strength.
ables such as lift origin, height, load dimensions, frequency of exertion, push/pull heights, carrying distance,
and so forth are all systematically altered so that a database of conditions and the acceptable exertion range is
cataloged for a spectrum of male and female subjects.
These data are typically presented in tables that indicate
the percentage of subjects who would f ind a particular
load acceptable for a given task. Snook et al. have produced extensive description of these tolerances (98–103).
An example of this information for pushing activities is
shown in T ab le 17-2.
Few investigations ha ve explored w hether the design of
work tasks through psychophysical tolerance limits is
TABLE 17-2. Example of psychophysical table used to determine the acceptable load an individual is willing to accept.
The table indicates the maximum amount of push force acceptable for males and females under various conditions.
Physiologic Tolerance Limits
Work tasks requiring high energy expenditure are
thought to limit the ability of the body to deliver oxygen
to the muscles. When oxygen debt occurs, insufficient
release of adenosine triphosphate (ATP) occurs within
the muscle and prolonged muscle contractions cannot be
sustained. Hence, under high-energy expenditure work
conditions, aerobic capacity may be considered as a ph ysiologic tolerance limit for low back pain.
Physiologic criteria for limiting low back pain due to
heavy physical work requiring high levels of energy
From Snook SH.The design of manual handling tasks. Ergonomics 1978;21:963–985, with per mission.
CHAPTER 17/OCCUPATIONAL ERGONOMICS / 185
expenditure hav e been defined by the NIOSH (104). This
document considers an energy expenditure rate of 9.5
kcal per minute as a baseline measure for maximum aerobic lifting capacity. Seventy percent of this baseline is
considered the aerobic tolerance limit for work that is
defined primarily as “arm work”. Of the baseline energy
expenditure, 50%, 40%, and 33% are considered the tolerance limits for lifting task durations of 1 hour, 1 to 2
hours, and 2 to 8 hours, respectively.
Minimal epidemiologic evidence is available to support these limits, although Cady et al. have demonstrated
the importance of aerobic capacity in back injury for a
large sample of firefighters (105,106).
PSYCHOSOCIAL PATHWAYS
A body of literature exists that has attempted to explain
how psychosocial factors might relate to the risk of suffering an LBD. Reviews have implicated psychosocial
factors as associated with risk (14,107) and some have
dismissed the role of biomechanical factors. However,
few studies have properly evaluated biomechanical exposure along with psychosocial exposure in these assessments. A recent study by Davis and Heaney (18) has
shown that no studies ha v e been ab le to adequately assess
both risk dimensions concurrently.
Recent biomechanical studies (108,109) have indicated that psychosocial stress does have the capacity to
influence biomechanical loading. These laboratory studies have demonstrated how individual factors such as personality can interact with perception of psychosocial
stress to increase trunk muscle coactivation and subsequent spine loading. Hence, these studies provide evidence that psychosocial stress may influence risk through
a biomechanical pathway.
SPINE LO AD ASSESSMENT
An important component of evaluating the load-tolerance relationship, and the potential risk associated with
work is an accurate assessment of the loading experienced by a tissue. The review of the tolerance literature
suggests that it is important to understand the specific
nature of the tissue loading including factors such as
compression force, shear force in multiple dimensions,
load rates, positions of the spine structures during loading, frequency of loading, and so forth. Thus, accurate
and specific information about loading is essential if one
is to use this information to assess potential risk associated with occupational tasks.
Presently it is not feasible to directly monitor the loads
imposed upon the spine structures and tissues while workers are performing an occupationally related task in the
workplace. Instead, indirect means such as biomechanical
models are typically used to estimate loading. All biome-
chanical models attempt to understand how exposure to
external loads results in internal forces that may exceed a
tolerance limit. External forces reside outside the body
(e.g., gravity or inertia) and must be overcome by the
worker to do work. Internal forces are the structures inside
the body (e.g., muscles, ligaments, etc.) that must supply
counterforces to support the external load. However, since
the internal forces are typically at a biomechanical disadvantage, these internal forces can be very large and result
in large force applications on spine tissues. Several approaches to biomechanical modeling have been used for
these purposes resulting in different trade-offs between
their ability to realistically assess spine loading associated
with a task and ease of model use.
The first models used to assess spine loading during
occupational tasks were reported in the 1970s. Early
models of spine loading made assumptions about which
trunk muscles supported the external load held in the
hands during a lifting task (110,111). These models
assumed that a single muscle vector within the trunk
could summarize the internal supporting force (and spine
loading) required to counteract an external load lifted by
a worker. The model assumes that a lift could be represented by a static equilibrium-lifting situation and that no
muscle coactivation occurs among the trunk musculature
during lifting. The model emplo ys anthropometric re gression relationships to estimate body segment lengths representative of the general population. Two output variables are predicted that can be used in a load-tolerance
assessment of work exposure. The first model output is
spine compression that is typically compared to the
NIOSH compression limits of 3400 N and 6400 N. The
second model output is population static strength of six
joints. L5/S1 joint strength is used to assess overexertion
risk to the back. The model has evolved into a computerbased model (3-dimensional static-strength prediction
program [3DSSPP]) and is typically used for general
assessments of materials handling tasks involving slow
movements where excessive compression loads are suspected of contributing to risk. An example of the computer program is shown in Fig. 17-3. The model can be
linked to field obser vations by videotaping a lifting task
and recording the weight of the object lifted. Early risk
assessments of the workplace have used this method to
assess spine loads on the job (112).
During the 1980s, biomechanical models were expanded to account for the contribution of multiple internal muscles’ reactions in response to the lifting of an
external load. Much of the spine tolerance literature was
beginning to recognize the significance of three-dimensional spine loads as compared to only compression loads
in defining potential risk. Thus, biomechanical models
were dev eloped that predicted compression forces as well
as shear forces imposed upon the spine. The first functional multiple muscle system model proposed for mate-
186 /SECTION III/THE INJURED WORKER
FIG. 17-3. Example of three-dimensional static strength prediction program. (Courtesy of D. Chaffin.)
rial handling assessments was developed by Schultz and
Andersson (113). This model demonstrated how loads
manipulated outside the body could impose large spinal
loads due primarily to the coactivation of trunk muscles
necessary to counteract this external load. The modeling
approach represented much more realism than previous
models, however, the approach resulted in indeterminate
solutions (since there were more muscles’ forces represented in the model than functional constraints unique
solutions became difficult). In order to overcome this
problem, modeling efforts attempted to determine which
muscles would be active (114–116). These efforts
resulted in models that worked well for static representations of a lift but not necessarily for dynamic lifting situations (117).
In order to better account for spine loads under
dynamic, complex lifting situations, later efforts
attempted to directly monitor muscle activity using electromyography (EMG) as an input to multiple muscle
models. EMG eliminated the problem of indeterminacy
since specific muscle activities were uniquely defined
through the neural activation of each muscle. These biologically assisted models were not only able to accurately assess compression and shear spine loads for specific occupationally related movements (88,89,118–129)
but are also able to predict differences among individuals so that variations in loading among a population
could be assessed (87,108,130–133) (Fig. 17-4). Validation measures suggest that these models have excellent
external as well as internal validity (133,134). Granata
and Marras (135) demonstrated the importance of
accounting for trunk muscle coactivation when assessing
spine loading and found that not accounting for coactivation could result in miscalculations of spinal loading
by up to 70%.
The disadvantage of biologically assisted models is that
they require EMG recordings that are often not tolerated
well in the workplace. Therefore many of the studies of
loadings associated with the spine during work have been
performed under laboratory conditions and have attempted
to assess specific aspects of the work that may be common
to many work conditions. Several efforts used EMGassisted models to assess three-dimensional spine loading
during materials handling activities (87,118,123,136–138).
There are many examples of information provided from
these in-depth analyses using biologically assisted models.
Figure 17-5 shows the difference in spine compression as
subjects lift with one hand versus two hands as a function
of lift asymmetry (118). This figure indicates that compressive loading of the spine is not simpl y a matter of loadweight lifted. Significant trade-offs occur as a function of
asymmetry and the number of hands involved with the lift.
The concept of trade-offs among workplace factors was
reinforced in a study that evaluated order-selecting activi-
CHAPTER 17/OCCUPATIONAL ERGONOMICS / 187
FIG. 17-4. Electromyography (EMG)-assisted model used to evaluate spine loading during simulated
work activities. Sample window panels clockwise from upper left: spine position, velocity, and acceleration during task, EMG activities of 10 trunk muscles, muscle coactivation representation, movements
imposed on the spine by each muscle, and video of task activity.
ties in a laboratory setting (139). Some of the results from
this study are displayed in Table 17-3. This table shows the
interaction between load w eight, location of the lift (re gion
on the pallet), and presence of handles on spine compression (benchmark). This anal ysis indicates that all three factors significantly affected the loading on the spine. Another
study indicated the trade-offs between spine compression
and shear loads as a function of how many hands were
involved in the lift, whether both feet were in contact with
the ground, lift origin, and height of a bin from which subjects were lifted (140) (Table 17-4). Similar studies have
also helped to understand spine loading trade-offs associated with team lifting (141), patient lifting (Table 17-5)
(142), the assessment of lifting belts (77,143–146), and
while using lifting assistance devices (147). Efforts have
also been made to apply the in-depth knowledge obtained
from these biologically assisted models through re gression
models of workplace characteristics (148,149). Recently,
FIG. 17-5. Mean peak compression force
as a function of lift asymmetry [clockwise
(CW) versus counterclockwise (CCW)] and
hand(s) used to lift load. Results derived
from electromyography-assisted model simulation of tasks (118).
188 /SECTION III/THE INJURED WORKER
TABLE 17-3. Percentage of lifts during order selection tasks within various spine compression benchmark zones as a
function of the interaction between load weight, location of the lift (region on the pallet), and presence of handles. Spine loads
estimated by an EMG-assisted model (139).
Box weight
Region on compression
Spine
the pallet benchmarks Handles No handles Handles No handles Handles No handles
Front-top <3,400 N 100.0 100.0 100.0 99.2 99.2 100.0
3,400–6,400 N 0.0 0.0 0.0 0.8 0.8 0.0
>6,400 N 0.0 0.0 0.0 0.0 0.0 0.0
Back-top <3,400 N 98.2 89.1 84.5 76.4 83.6 67.3
3,400–6,400 N 1.8 10.9 15.5 23.6 16.4 32.7
>6,400 N 0.0 0.0 0.0 0.0 0.0 0.0
Front-middle <3,400 N 98.7 91.3 94.7 82.7 92.6 76.0
3,400–6,400 N 1.3 8.7 5.3 17.3 7.4 23.3
>6,400 N 0.0 0.0 0.0 0.0 0.0 0.7
Back-middle <3,400 N 88.7 82.0 80.7 75.3 76.7 64.7
3,400–6,400 N 11.3 18.0 19.3 24.7 23.3 34.6
>6,400 N 0.0 0.0 0.0 0.0 0.0 0.7
Front-bottom <3,400 N 45.3 30.0 29.3 14.0 16.0 3.3
3,400–6,400 N 52.0 62.0 62.7 65.3 72.0 66.0
>6,400 N 2.7 8.0 8.0 20.7 12.0 30.7
Back-bottom <3,400 N 35.3 24.0 30.0 10.7 9.3 2.0
3,400–6,400 N 60.7 67.3 56.7 65.3 71.3 62.0
>6,400 N 4.0 8.7 13.3 24.0 19.3 36.0
EMG, electromyogram; N, Newton.
18.2 kg 22.7 kg 27.3 kg
efforts have also employed these models to assess the role
of psychosocial factors, personality , and mental processing
on spine loading (108,109).
to date has been directed toward static response of the
trunk as well as sudden loading responses (151,152,154,
155,158,159).
Efforts have also attempted to use stability as criteria
to govern detailed biologically assisted biomechanical
models of the torso (84,150–157). One potential injury
pathway for LBDs suggests that the unnatural rotation
of a single spine segment that may create loads on passive tissue or other muscle tissue can result in irritation
or injury (85). Much of the work performed in this area
TABLE 17-4. Spine forces (means and standard deviations for lateral shear, anterior-posterior shear, and compression) as a
function of the number of hands used, the number of feet supporting the body during the lift, the region of a pallet and the
Independent Lateral shear Anter ior-posterior Compression
measures Condition force (N) shear force (N) force (N)
Hand One-hand 472.2 (350.5)
Feet One-foot 401.7 (335.1)
Region Upper front 260.2 (271.7)
Bin height 94 cm 361.9 (328) 1089.9 (800.8) 5795.8 (2660.4)
a
Indicates significant difference at α = 0.05.
b–e
Region has four experimental conditions, therefore letters b–e are used to indicate which regions
are significantly different from one another .Regions with different letters were significantly different at α
= 0.05.
N, Newton.
height of a bin when lifting items from an industrial bin (140)
Two-hand 233.8 (216.9)
Two-feet 304.3 (285.1)
Upper back 317 (290.8)
Lower front 414.4 (335.0)
Lower back 420.4 (329.0)
61 cm 344.1 (301) 1140.3 (1009.1) 5980.2 (3027.4)
ASSESSMENT METHODS AND THE
IDENTIFICATION OF LBD RISK AT WORK
Previous sections have introduced methods used in
studies of the assessment of spine loads in response to
various work-related factors that are common to many
a
a
a
a
b
b
c
c
1093.3 (854.7) 6033.6 (2981.2)
1136.9 (964.1) 5742.3 (1712.3)
1109.4 (856.1) 6138.6 (2957.5)
1120.8 (963.3) 5637.3 (2717.9)
616.6 (311.1)
738.0 (500.0)
1498.3 (1037.8)
1607.5 (1058.4)
b
b
c
c
3765.7 (1452.8)
5418.1 (2364.2)
6839.8 (2765.4)
7528.2 (2978.4)
a
b
c
d
e
TABLE 17-5. Spine loads estimated during patient transfer as a function of the number of lifters
Maximum Maximum Maximum
and the transfer technique (142)
Transfer technique shear force (N) force (N) force (N)
Lifting phase
One-person
Hug 1060.7 (697.6)
Two-person
Left-side lifter Hook 731.7 (442.6)
Gait belt 702.6 (495.1)
Right-side lifter Hook 697.1 (435.8)
Gait belt 664.2 (461.5)
Lowering phase
One-person
Hug 1127.9 (621.6)
Two-person
Left-side lifter Hook 845.2 (489.0)
Gait belt 781.4 (506.1)
Right-side lifter Hook 830.4 (463.9)
Gait belt 815.5 (469.8)
*Different Alpha Characters Indicate Significant Difference at p = .05.
N, Newton.
lateral A-P shear compression
B
A
A
A
A
B
A
A
A
A
CHAPTER 17/OCCUPATIONAL ERGONOMICS / 189
Spinal loads
908.5 (555.9)
955.6 (436.5)
916.7 (549.1)
892.8 (495.6)
985.7 (567.6)
1111.69 (614.6)
1020.8 (503.0)
1005.4 (523.8)
935.6 (478.9)
1097.4 (487.6)
B
B
B
A
B
C
C
C
A
B
6336.3 (2044)
4948.2 (1598.6)
4895.5 (1633.1)
4455.8 (1539.9)
4600.9 (1437.6)
6007.9 (1859.2)
4713.4 (1640.1)
4597.5 (1454.9)
4314.1 (1694.4)
4571.8 (1529.7)A
C
B
B
A
AB
C
B
AB
A
B
workplaces (e.g., one-hand versus two-hand lifting).
These studies have resulted in a rich body of literature
that can be used as a guide for the proper design of many
work situations. However, a need still exists for assessing
unique work situations that may not have been explored
in these laboratory studies. The more robust methods for
assessing spine loads (e.g., EMG-assisted models) may
not be usable for assessment on the job since they require
extensive instrumentation. This section reviews the methods and tools available for the assessment of LBD risk at
the work site along with a review of the literature that
supports their usage.
Three-Dimensional Static Strength Prediction
Program
The three-dimensional static strength prediction program (3DSSPP) has been described previously. This program considers the load-tolerance relationship from two
aspects. An estimate of spine compression is generated
and compared to the generally accepted tolerance limits
of 3400 N. In addition, the load imposed by the task on
six joints is compared to the static strength of the muscle
groups. This last relationship has been defined as a lifting
strength rating (LSR) and was used to prospectively
assess low back injuries in an industrial environment
(97). The LSR is defined as the weight of the maximum
load lifted on the job divided by the lifting strength measured in the same lifting posture for a large, strong man.
The study concluded that “the incidence rate of low back
pain [was] correlated [monotonically] with higher lifting
strength requirements as determined by assessment of
both the location and magnitude of the load lifted.” This
was one of the first quantitative ergonomic studies to
conclude that not only was load lifting potentially hazardous, but it was also important to consider the load
location when assessing risk. The study also suggested
that exposure to moderate lifting frequencies appeared to
be protective, whereas, high or low rates of lifting were
common in jobs with greater reports of back injury.
An industrial study using both the LSR and estimates
of back compression forces observed jobs over 3 years in
5 large industrial plants where 2,934 material handling
tasks were evaluated (112). The results suggested a positive correlation between the lifting strength ratio and
back incidence rates. The study also reported that musculoskeletal injuries were twice as likely for predicted spine
compression forces that exceeded 6800 N. However, this
was not true for back incidents specifically. The study
also suggested that prediction of risk was best associated
with the most stressful tasks (as opposed to indices that
represent risk aggregation).
Job Demand Index
A similar concept to the LSR was reported by Ayoub et
al. (160) in terms of a job severity index (JSI). This index
considers the ratio of the job demands relative to the lifting capacities of the worker. Job demands include factors
such as the weight of the object lifted, the frequency of
lifting, exposure time, and lifting task origins and destinations. A comprehensive task analysis is required to
assess job demands. The worker capacity includes the
strength and body size of the worker. Strength is deter-
190 /SECTION III/THE INJURED WORKER
mined through psychophysical testing. A prospective
study using the JSI was performed by Liles et al. (161).
Results suggested a threshold of a job demand relative to
worker strength above which the risk of low back injury
increased. The authors suggest that this method could
identify the more costly injuries.
NIOSH Lifting Guide and Revised Lifting Equation
The NIOSH has developed two tools to help industry
assess the risk associated with materials handling jobs.
The objective of both tools was to “prevent or reduce the
occurrence of lifting-related low back pain among workers” (162). Both tools considered biomechanical, physiologic, and psychophysical limits in their development.
The first tool was a guide based upon biomechanical,
physiologic, and psychophysical information (68). This
method assessed job characteristics and assessed the
magnitude of the load that must be lifted for spine compression to reach 3400 N (the action limit, or AL) or 6400
N (the maximum permissible limit, or MPL). The AL was
defined as the tissue tolerance where damage begins to
occur in the spine. In theory, to be protective, work tasks
should be designed so that the load lifted by the worker
was below the calculated AL limit. The AL was determined through a functional equation that considered four
discounting factors multiplied by a constant. The constant
(90 lbs or 40 kg) was assumed to be the magnitude of the
weight lifted under ideal lifting conditions that would
result in a spine compression of 3400 N. The four discounting factors consist of: (a) horizontal distance of the
load from the spine, (b) the vertical height of the load off
the floor, (c) the vertical travel distance of the load, and
(d) the frequency of lifting. These discounting factors
were governed by functional relationships that reduced
the magnitude of the allowable load (constant). An MPL
was determined by multiplying the AL by 3. It was
assumed that if the load lifted by the w ork er e xceeded the
MPL, more than 50% of the workers were at risk and
engineering controls were needed. If the load lifted by the
worker was between the AL and the MPL then the task
placed less than 50% of the workforce at risk and either
engineering or administrative controls w ere required. The
guide was designed to be used for primarily sagittally
symmetric lifts that were slow and smooth. Only one
evaluation of the guide’s effectiveness could be found in
the literature (73). Comparing the predictions with historical data of back injury reporting in industry, this evaluation indicated an odds ratio (OR) of 3.5 with good
specificity b ut low sensitivity.
A revision of this method was published in 1993 and
has become known as the “revised NIOSH lifting equation” (162). The revision was intended to consider asymmetric lifting situations as well as tasks with various
types of coupling (handles). The revised equation was
similar in form to the 1981 guide in that it included a load
constant that was mediated by several work characteristic
“multipliers.” However, several components of the equation were different. First, the value calculated was a recommended weight limit (RWL). If the load lifted by the
worker was below this value the load was considered
safe. Second, the load constant was reduced to 23 kg or
51 lbs (from the 40 kg or 90 lbs in the 1981 guide). Third,
the form of the multipliers was changed and the functional relationship between discounting and the workplace measure was slightly more liberal for the four factors originally contained in the 1981 guide (horizontal
distance, vertical distance, vertical travel distance, and
frequency). This w as done to compensate for a lower load
constant. Fourth, two new multipliers (task asymmetry
and coupling) were added to the equation. Once the RWL
is calculated for a given w ork situation, it is compared (as
a denominator) to the load lifted by the worker to form a
lifting index (LI). If the LI is less than the value 1, the job
is considered safe. If the LI is greater than 1, then risk is
present. LI values above 3 are thought to place nearly all
workers at increased risk (104).
Two assessments of the revised equation to injury
reporting have been performed. One assessment compared the ability of the tool to identify high- and low-risk
jobs based upon a historical database (73). This assessment yielded an OR of 3.1. Further analyses indicated
higher sensitivity than the 1981 guide but lower specificity. A second analysis using a different data set
assessed ORs as a function of the LI. For LIs between 1
and 3 the ORs ranged from 1.54 to 2.45, indicating an
increasing OR with increasing low back pain reporting.
However, the OR for LIs over 3 was lower (OR of 1.63)
indicating a nonmonotonic relationship between the LI
and risk.
Video-Based Biomechanical Models
Norman et al. (10) used a quasi-dynamic two-dimensional biomechanical model to assess cumulative biomechanical loading of the spine in 234 automotive assembly
workers. This study identified four independent factors
for LBD reporting consisting of integrated load movement (over a work shift), hand forces, peak shear force on
the spine, and peak trunk velocity. They concluded that
workers in the top 25% of loading exposure on all risk
factors were at about six times the risk of reporting back
pain than those in the bottom 25% of loading.
Lumbar Motion Monitor Risk Assessment
In an attempt to consider the contribution of trunk
dynamics as well as the traditional biomechanical factors
in workplace assessment of risk, Marras et al. (55,56)
biomechanically evaluated over 400 industrial jobs (with
documented LBD risk history) by observing 114 workplace and worker-related variables. Of the variables ex-
CHAPTER 17/OCCUPATIONAL ERGONOMICS / 191
plored, exposure to load movement (load magnitude ×
distance of load from spine) was found to be the single
most powerful predictor of LBD reporting. This study
also identified 16 tr unk kinematic variables that resulted
in statistically significant ORs associated with risk of
LBD reporting in the workplace. None of the single kinematic variables were as strong a predictor as load
moment, however, when load moment was combined
with three kinematic variables (relating to the three
dimensions of trunk motion) along with an exposure frequency measure, a strong multiple logistic regression
model resulted that described reporting of back disorder
well (OR of 10.7). The analysis indicated that risk was
multivariate in nature and that exposure to the combination of the five variables described reporting well. This
information was incorporated into a functional risk
model (Fig. 17-6) that accounted for trade-offs between
risk variables. For example, a job task that exposes a
worker to low magnitude of load moment can represent a
high-risk situation if the other four variables in the model
were of sufficient magnitude. The model has been validated in a prospective workplace intervention study (72).
The risk model has been linked with a lumbar motion
monitor (LMM) (Fig. 17-7) in a computer program to
document trunk motion exposure on the job.
When the findings from these studies are considered in
conjunction with previous epidemiologic studies in the
workplace (54), it is clear that w ork associated with acti vity performed in nonneutral postures increases the risk to
the back. Collectively these studies indicate that as trunk
posture becomes more extreme or the trunk motion
becomes more rapid, reporting of back disorder is greater .
These results suggest that occupational risk of LBD is
associated with mechanical loading of the spine and suggest that when tasks involve greater three-dimensional
loading, the association with risk becomes much
stronger.
A database of 126 jobs including LMM information
was evaluated by Fathallah et al. (70) to precisely quantify and assess the complex trunk motions of groups with
varying degrees of LBD reporting. They determined that
groups with greater reporting rates exhibited complex
trunk motion patterns involving high magnitudes of combined trunk velocities, especially at extreme sagittal flexion, whereas the low-risk groups did not exhibit these
patterns. This study suggested that elevated levels of
complex simultaneous velocity patterns along with key
workplace factors (load moment and frequency) were
unique to those with increased LBD risk.
Workplace Assessment Summary
The findings of recent quantitative studies used to
assess workplace LBD risk using available workplace
assessment tools are summarized in Table 17-6. The studies are consistent in that even though these studies have
not evaluated spinal loading directly, the exposure measures included were indirect indicators of spinal load and
suggest that as these risk factors increase in magnitude
the risk increases. Load location or strength ratings both
appear to be indicators of the magnitude of the load
imposed upon the spine. The e xposure metrics (load location, kinematics, and three-dimensional analyses) are
important from a biomechanical standpoint because they
FIG. 17-6. Lumbar motion monitor risk model. The probability risk of high risk (of low back pain) group
membership is quantitatively indicated for a particular task for each of five risk factors indicating how
much exposure is too much exposure for a particular risk factor.The vertical arrow indicates the overall
probability of high-risk group membership due to the combination of risk factors.
192 /SECTION III/THE INJURED WORKER
at the workplace, associations between biomechanical
factors and risk of LBD reporting are evident. Several
common components of biomechanical risk assessment
can be derived from these studies. First, increased LBD
reporting is associated with work primarily when the
specific load location relative to the body (load moment
or load location) is quantified in some way. Most studies have shown that these factors are closely associated
with increased low back pain reports. Second, many
studies have shown that increased reporting of low back
pain can be well characterized when the three-dimensional kinematic demands of the work are described.
Finally, nearly all of these assessments have demonstrated that risk is multidimensional in that there is a
synergy among risk factors that is often associated with
increased reporting of low back pain. Several studies
have also suggested that some of these relationships are
nonmonotonic. In summary, these efforts have suggested that the better the lift characteristics can be characterized in terms of biomechanical demand the better
the association with risk.
FIG. 17-7. The lumbar motion monitor used to track trunk
kinematics during occupational activities.
mediate the ability of the trunk’s internal structures to
support the external load. As these metrics change they
can change the nature of the loading on the back’s internal structures.
Collectively, these studies demonstrate that when
meaningful biomechanical assessments are performed
TABLE 17-6. Summar y of recent field evaluations of low back disorder risk factors and strength of
association with risk (odds ratio). The more precisely the lifting requirements (e.g., load location,
moment, etc.) are specified the better the association with risk
Risk factors identified
THE PROCESS OF IMPLEMENTING
ERGONOMIC CHANGE
Recent findings have shown that there are substantial links between biomechanical loading of the spine
and psychosocial factors (108,109). Hence, ergonomic
changes to the work environment must consider biomechanical loading as well as the psychosocial environment. A review of ergonomic interventions (163)
has shown that such interventions can reduce workers’
Capacity/demand ratio
Load location
Load moment
Frequency
Kinematics
2-D
3-D
Authors No. of jobs Odds ratio (CI)
Punnett et al., 1991 95 case x x x Max flex 5.7 (1.6–20.4)
124 refferant Twist/lat 5.9 (1.6–21.4)
Marras et al., 403 x x x x x x 5 var = 10.7 (4.9–23.6)
1993/1995
Norman et al., 1998 104 cases x x x x 4 var = 5.7 (1–31.2)
130 refferant
Waters et al., 1999 36 x x x x x x Max OR = 2.45 (1.29–4.85)
CI, confidence interval; OR, odds ratio.
Multiple factors