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pain (Brisson et al., 1999) and that shorter assembly line workers experienced greater reductions in dis-
comfort in legs and low back, when flooring was modified do be more absorbent (King, 2002).
19.4 How Can We Estimate the Contribution of
Individual Factors to MSK Disorders?
Clinical researchers and practitioners have often included individual factors as part of the descriptive epi-
demiology of MSK disorders. Some have argued the primacy of individual factors, construed narrowly, as
causes of MSK disorders. An example of such attribution occurs in the dissent appendix of the NRC
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IOM Panel report (Szabo, 2001), where the contribution of a wide variety of individual factors to
CTS etiology is argued to be stronger than occupational exposures. Such an assumption that if individual
factors are present, they must be the primary cause, must be examined in relation to one's conception of
what individual factors represent and one's understanding of the mechanisms of production of an MSK
disorder.
A common practice in occupational epidemiology is to “control for” or “adjust for” individual factors
while examining the role of occupational risk factors, either through stratified analyses or multivariate
models, in order to avoid the bias of confounding (Rothman and Greenland, 1998). A recent systematic
review on etiology of shoulder pain noted that most studies adjusted for age, with some also adjusting for
sex, smoking, hobbies, or even intelligence (van der Windt, 2000). Controlling for individual factors does
permit calculations of population attributable fractions due to work exposures among those exposed, as
in the NRC
IOM Panel, 2001). Unfortunately, adjustment
means that the independent effects of individual factors are not apparent. Hence, the report also esti-
mated population attributable fractions due to distress or depression, often called individual psychoso-
cial factors, with attributable fractions among the exposed (i.e., those with distress or depression) ranging
from 14 to 63% for MSK disorders (see Table 4.5, p. 107 of NRC
IOM Panel report, chapters 3 and 4 (NRC
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IOM Panel, 2001).
Unfortunately, adjustment of either individual factors or work exposures makes it impossible to
compare the independent contributions of each to the production of MSK disorders. Fortunately,
rather than treating either type of factor as less interesting and therefore needing to be controlled for
to eliminate confounding, researchers are increasingly adopting a multi-causal framework and laying
out the contribution of different factors. A good example can be found in the report on a case-
control study of low back pain reporting among automotive assembly workers, where the variance
explained by each domain of risk factors is set out (Kerr et al., 2001). The individual factors of body
mass index and a prior WC claim for low back pain accounted for 4.7% of the overall variance, while
workplace risk factor domains independently accounted for 11.5% (psychosocial), 11.8% (psychophysi-
cal), and 18.3% (biomechanical) of the variance, respectively.
When study populations are large enough, it becomes possible to go even further and examine the
ways that factors from different domains may influence the contribution of each other. Several analytic
techniques are available to assess such effect-measure modification or heterogeneity of effects of different
factors (Rothman and Greenland, 1998). In a study of predictors of time on total temporary wage loss of
WC benefits among WC claimants with soft-tissue disorders, we used interaction terms to take into
account the associations between changes in pain intensity (from the baseline to 4-week interviews)
and workplace offers of special arrangements to help injured workers return to work (workplace
offers) (Hogg-Johnson and Cole, 2003). We had found that among those with worsening of their
MSK pain (and hence a negative coefficient), the positive impact of a workplace offer (positive coeffi-
cient) was even greater, that is, the interaction term between change in pain and workplace offers had
a negative coefficient, which when multiplied by the negative for change in pain, created a big positive
impact, reducing the time on benefits to less than a third of that for those who didn't receive workplace
offers. This was a much bigger effect than that for those whose pain was improving, where reductions in
time on benefits with workplace offers ranged from almost the same to one-half of those who did not
receive workplace offers.
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