We appreciate the careful reading of our editorial [1] by Drs.
Mikkelsen and Andersen. We regret our omission of the one published NUDATA
study available at the time our editorial was submitted [2]. That study
reported significant associations between mouse usage time collected with
memory resident software and both, acute neck pain and acute shoulder
pain, among 2146 technical assistants. However, because i) median mouse...
We appreciate the careful reading of our editorial [1] by Drs.
Mikkelsen and Andersen. We regret our omission of the one published NUDATA
study available at the time our editorial was submitted [2]. That study
reported significant associations between mouse usage time collected with
memory resident software and both, acute neck pain and acute shoulder
pain, among 2146 technical assistants. However, because i) median mouse
usage time was 5.2 hours/week and median keyboard usage time was 0.9
hours/week, and ii) rates of moderate or greater musculoskeletal pain were
very low among the participating computer users, we are concerned about
the generalizability of the observed associations to workers with greater
mouse and keyboard use.
Regarding differences in associations with musculoskeletal disorders
(MSDs) observed across studies using self-reported estimates of computer
use versus memory resident software documentation of computer use, we made
no argument that one was correct and the other was incorrect. Rather, we
raised the concern that these two exposure assessment methods capture
different (but not totally unrelated) aspects of computer use relevant to
MSD risk. The absence of perfect correlation between self-reported
estimates of computer use and memory resident software documentation of
computer use may be due to error in self report, differences in the kind
of exposure information captured, or both. The claims of methodological
objectivity and validity presented by Mikkelsen and Andersen do not
address this fundamental question. We continue to believe, as noted in our
editorial, that a better understanding of the attributes of work captured
by self report and by computer registration software will clarify what
appear to be inconsistent results reported by studies using them.
1. Gerr F, Fethke N. Ascertaining computer use in studies of
musculoskeletal outcomes among computer workers: differences between self-
report and computer registration software. Occup Environ Med 2011; 68: 465
-66.
2. Andersen JH, Harhoff M, Grimstrup S, et al. Computer mouse use
predicts acute pain but not prolonged or chronic pain in the neck and
shoulder. Occup Environ Med 2008;65 :126-31.
In a recent editorial Gerr et al.[1] discuss computer work and
musculoskeletal outcomes based on self-reported exposure versus objective
recordings using computer software. They state that only one small study
(n=27) using objective recordings was published before a large study by
Ijmker et al.[2], published in the same issue as the editorial. They
failed to consider the results of two NUDATA papers based on more than
2...
In a recent editorial Gerr et al.[1] discuss computer work and
musculoskeletal outcomes based on self-reported exposure versus objective
recordings using computer software. They state that only one small study
(n=27) using objective recordings was published before a large study by
Ijmker et al.[2], published in the same issue as the editorial. They
failed to consider the results of two NUDATA papers based on more than
2000 study participants, one of them published in the OEM[3].
The results of the study of Ijmker et al. and the NUDATA studies
consistently indicate that sustained or severe pain outcomes were not
related to objective computer work recordings.
The editorial argues that the results of the study of Ijmker et al does
not invalidate the much larger literature in which self-reported computer
use was associated with musculoskeletal symptoms. The main argument seems
to be that objective recordings do not capture the relevant exposures,
e.g. holding the hands over the keyboard without keying and that different
cut points for such non-activity periods may invalidate the objective
recordings. However, objective software-based computer work recordings are
in very good accordance with other objective measures like video-
recordings, and much better than self-reported exposure. Furthermore,
within reasonable limits, different cut-off values for non-activity
periods do not change these relations or computer times very much. This is
consistent evidence from several studies and not from "preliminary
investigations", as stated in the editorial. Finally, exposure times based
on different cut off's are highly correlated, and their relation to
musculoskeletal outcomes will not vary much with different cut-offs [4].
Contrary to the editorial, we find it very unlikely that retrospective
self-reports about computer use during several months should capture
biologically important aspects of computer work which are not captured by
a validated objective method, which prospectively collects exact computer
use data on a daily basis.
References
1. Gerr F, Fethke N. Ascertaining computer use in studies of
musculoskeletal outcomes among computer workers: differences between self-
report and computer registration software. Occup Environ Med 2011; 68: 465
-66
2. IJmker S, Huysmans MA, van der Beek AJ, et al. Software-recorded
and self-reported duration of computer use in relation to the onset of
severe arm-wrist-hand pain and neck-shoulder pain.
Occup Environ Med 2011; 68: 502-9
3. Andersen JH, Harhoff M, Grimstrup S, et al. Computer mouse use
predicts acute pain but not prolonged or chronic pain in the neck and
shoulder. Occup Environ Med 2008;65 :126-31.
4. Mikkelsen S, Lassen CF, Vilstrup I, et al. Does computer use
affect the incidence of distal arm
pain? A one-year prospective study using objective measures of computer
use. Int Arch Occup Environ Health 2011 May 24 [Epub ahead of print]
We thank Dr. Mikkelsen and colleagues for their constructive comments
on our paper. Our responses to their three major questions are listed
below.
1) Why did we present various formulations of job strain?
The five formulations of job strain have been commonly reported in
the literature. Often, authors chose one or two formulations and thus
would not know if their results were consistent across differe...
We thank Dr. Mikkelsen and colleagues for their constructive comments
on our paper. Our responses to their three major questions are listed
below.
1) Why did we present various formulations of job strain?
The five formulations of job strain have been commonly reported in
the literature. Often, authors chose one or two formulations and thus
would not know if their results were consistent across different
formulations. In our study, with the encouragement of an OEM peer
reviewer, we presented results for all five formulations so that readers
can compare the results both across different formulations and with
previous job strain studies. We agree with Mikkelsen et al. that four of
the five formulations of job strain we examined could be the result of the
effect of job control only. As shown in Table 3, job demands was not
significantly associated with IMT whereas job control was.
2) Why did we not show the main effect coefficients for job demands
and control as we showed the coefficient for the multiplicative term in
Table 4?
When a multiplicative term is included in a regression model, the
main effects of the interacted variables have a more complex
interpretation;1 that is, the coefficients represent the magnitude of
effect for each variable when the other is 0. We showed the main effects
of the two variables in Table 3, which represent the magnitude of each
variable's effect when the other is controlled for. For the sake of
brevity, we did not show the coefficients for demands and control after
the multiplicative term was included in the model. This was explained in
the footnote for Table 4.
3) Why did we illustrate the interaction in dichotomous terms (Figure
1) and ignored that high job demands were protective?
Figure 1 is an illustration of the interaction, which could have been
constructed using the mean+1SD as "high" and the mean-1SD as "low" or
other ways. We used the median split again for the sake of simplicity and
also because it is a commonly used approach in the job strain literature.
We do recognize that the demand-control model was only partially supported
in our study; that is, job control was protective only for those who
reported high job demands. Overall, job demands did not have a
significant association with IMT, as shown in Table 3. The following
paragraph is our discussion on this finding from an earlier draft.
Unfortunately, this paragraph was excluded from the final version because
of the word limit.
Contrary to the demand-control model's prediction,2 we did not find
significant associations between IMT and job demands. The Cardiovascular
Risk in Young Finns Study also failed to find the same significant
association.3 The majority of CVD studies have found positive
associations between job demands and CVD,4 but Belki? et al.4 identified
five studies that reported an inverse association between psychological
job demands and CVD.5-9 In the MESA cohort, of which about 30% were
immigrants, the job demands scale had acceptable scale reliability among
U.S.-born participants but not among immigrants (Cronbach's alpha = 0.75
for U.S.-born, ranged from 0.45 to 0.65 for immigrants, depending on the
language used in data collection10). Limitations in the measure of job
demands used in heterogeneous samples like ours may have limited our
ability to detect associations of job demands with IMT.
References:
1. Cohen J, Cohen P. Applied Multiple Regression: Correlation
Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence
Erlbaum, 1983.
2. Karasek RA. Job demands, job decision latitude, and mental strain:
Implications for job redesign. Administrative Science Quarterly
1979;24:285-308.
3. Hinsta T, Kivim?ki M, Elovainio M, Vahtera J, Hintsanen M, Viikari
JSA, et al. Is the association between job strain and carotid intima-media
thickness attributable to pre-employment environmental and dispositional
factors? The Cardiovascular Risk in Young Finns Study. Occupational and
Environmental Medicine 2008;65:676-82.
4. Belki? KL, Landsbergis PA, Schnall P, Baker D. Is job strain a
major source of cardiovascular disease risk? Scand. J. Work Environ.
Health 2004;30(2):81-128.
5. Alterman T, Shekelle RB, Vernon SW, Burau KD. Decision latitude,
psychologic demand, job strain and coronary heart disease in the Western
Electric Study. American Journal of Epidemiology 1994;139:620-27.
6. Bobak M, Hertzman C, Skovoda Z, Marmot MG. Association between
psychosocial factors at work and non-fatal myocardial infarction in a
population based case-control study in Czech men. Epidemiology 1998;9:43-
47.
7. Hall EM, Johnson JV, Tsou TS. Women, occupation, and risk of
cardiovascular morbidity and mortality. Occupational Medicine 1993;8:709-
19.
8. Johnson JV, Stewart W, Hall EM, Fredlund P, Theorell T. Long-term
psychosocial work environment and cardiovascular mortality among Swedish
men. American Journal of Public Health 1996;86:324-31.
9. Steenland K, Johnson JV, Nowlin S. A follow-up study of job strain
and heart disease among males in the NHANES1 population. American Journal
of Industrial Medicine 1997;31:256-59.
10. Fujishiro K, Landsbergis P, Diez Roux AV, Hinckley Stukovsky K,
Shrager S, Baron S. Factorial invariance, scale reliability, and validity
of the decision latitude and psychological demands scales for immigrant
workers: The Multi-Ethnic Study of Atherosclerosis (MESA). Journal of
Immigrant and Minority Health 2010;13:533-40.
Self-report of duration of computer use is usually overestimated. The
search for a valid measure of exposure to keyboard/mouse use resulted in
the development of a computer registration software. The use of this new
software generated unexpected results when IJmker et al.1 found software-
recorded computer use was not significantly associated with upper
extremity/neck symptom onset while self-reported computer use was
sig...
Self-report of duration of computer use is usually overestimated. The
search for a valid measure of exposure to keyboard/mouse use resulted in
the development of a computer registration software. The use of this new
software generated unexpected results when IJmker et al.1 found software-
recorded computer use was not significantly associated with upper
extremity/neck symptom onset while self-reported computer use was
signficantly associated with symptoms in the neck/shoulder and arm/hand.
What is captured in the self-report that is missing in the software-
recorded duration of computer use? In the editorial by Gerr and Fethke2
reference is made to work by Homan and Armstrong3 that noted the potential
negative effect of time spent with hands held over the keyboard but
without keying. In our Medical-Ergonomic Program4 we refer to this
position as the 'action ready' posture when the forearm(s) is in full
pronation over the keyboard or mouse causing muscle activation of the
forearm extensor muscles. This may lead to the development of painful
trigger points in the forearm extensor muscles, a common area of
complaints by computer users.4 Activities such as reading, talking,
thinking etc. while using the computer are frequently accompanied by this
'action ready' posture. Time spent in these activities is included when
self-reporting duration of computer use but would not be captured in
computer registration software.
Other posture issues without keystrokes or mouse clicks involve the
neck/shoulder area. Computer users have a habit of not sitting up
straight against the back of the chair and carry their shoulders forward.
This posture activates the muscles involved with scapulae stabilization
and shortens the pectoralis minor4 resulting in painful trigger points in
the overused muscles . Neck/shoulder muscles are also activated when mouse
use is with the arm extended away from the body, when the monitor is too
far away and the chin juts forward or when the keyboard is too high and
the shoulders remain hiked to compensate. Maintenance of these postures
with or without keystrokes and mouse clicks are an etiology for upper
extremity symptoms that needs to be added to the exposure equation for
computer use.
1. IJmker S, Huysmans MA, van der Beek AJ, et al. Software-recorder
and self-reported duration of computer use in relation to the onset of
severe arm-wrist-hand pain and neck-shoulder pain. Occup Environ Med
2011;68:502-209.
2. Gerr F and Fethke N. Ascertaining computer use in studies of
musculoskeletal outcomes among computer workers: differences between self-
report and computer registration software. Occup Environ Med 2011;68:465-
466.
3. Homan MM and Armstrong TJ. Evaluation of three methodologies for
assessing work activity during computer use. AIHA J (Fairfax, VA)
2003;64:48-55.
4. Bleecker ML, Celio MA, Barnes SK. A medical-ergonomic program for
symptomatic keyboard/mouse users. JOEM 2011;53:561-567.
Fujishiro et al.1 recently published data on the association of job
demands and control with carotid artery intima-media thickness (IMT). The
joined effect of demands and control (strain) was analyzed by five
different strain definitions:
1. a quadrant term (median splits of demands and control),
2. combinations of tertiles of demands and control,
3. an additive term (demands minus control) ,
4. a quotient term (the ra...
Fujishiro et al.1 recently published data on the association of job
demands and control with carotid artery intima-media thickness (IMT). The
joined effect of demands and control (strain) was analyzed by five
different strain definitions:
1. a quadrant term (median splits of demands and control),
2. combinations of tertiles of demands and control,
3. an additive term (demands minus control) ,
4. a quotient term (the ratio) and
5. a multiplicative term (the product).
The first three terms are linear combinations of demands and control,
which are less informative than the corresponding linear combination based
on regression analyses of the mutually adjusted effects of demands and
control. The quotient term implies interaction between demands and control
but does not examine if there is one, its size, form or statistical
significance. An effect of any of the first four strain terms may be due
to an effect of only one of the two factors. Why introduce a strain
measure of the joined effect of demands and control, if it may only
reflect the effect of one of these variables?
A parsimonious and informative way to examine the joined effect of demands
and control is regression analyses with demands, control and their
multiplicative term included as covariates. The authors published the
effects of the multiplicative term but not the main effects. These are
needed to evaluate the form of any interaction. The authors only
illustrate the form of the interaction by dichotomous combinations of
demands and control.
The authors interpret the interaction as confirmation of the job strain
theory because high job control protected against thick IMT, especially
among persons with high job demands. However, they overlook that high job
demands also protected against thick IMT. The interaction effect as a
whole was not in accordance with the job strain model.
References
1. Fujishiro K, Diez Roux AV, Landsbergis P, et al. Associations of
occupation, job control and job demands with intima-media thickness: The
Multi-Ethnic Study of Atherosclerosis (MESA). Occup Environ Med
2011;68:319-326.
The article by Clin et al. (1) provides additional information for a
dose-response relationship with asbestos and cancer. Information where a
response curve changes effect as observed from background is critical in
establishing a safe exposure limit (threshold -exposure/concentration-
dose). Some investigators have reported this threshold is around 25
fiber/ml-years (2); although for some members of an exposed group thi...
The article by Clin et al. (1) provides additional information for a
dose-response relationship with asbestos and cancer. Information where a
response curve changes effect as observed from background is critical in
establishing a safe exposure limit (threshold -exposure/concentration-
dose). Some investigators have reported this threshold is around 25
fiber/ml-years (2); although for some members of an exposed group this may
be lower (3). However, a cumulative no-effect value does not provide
information applicable for practical every day use when monitoring worker
exposure.
Recent studies (4,5,6) have suggested levels of exposure where there
was no excess increase in cancer, notably lung cancer and mesothelioma.
This is especially noted for non-smokers where risk does not exceed unity
(lung cancer), even for high asbestos exposure, while there is a
significant increased risk for smokers and former smokers (6,7). Thus, it
appears smoking is the primary contributor and confounder of disease for
historical and current asbestos workers (6). Compounding this issue is
the high number of smokers performing asbestos abatement work
(approximately 60% or greater depending on the population observed even at
the present time) (8,9). The high rate of smoking makes it difficult to
estimate a threshold and subsequently establish an exposure value from
this type of information. Certainly, for today's asbestos workers smoking
constitutes their greatest risk (6,9,10).
Recent studies with direct (4,5) and indirect (e.g. Job Exposure Matrix
and Job Specific Modules) (6,11) exposure information do allow an estimate
of a threshold exposure dose. Although, exposure can greatly vary over
time (4), it appears even with mixed fiber exposure (chrysotile and
amphibole) (5) a threshold of 1.0 f/ml-year is applicable, but at the
upper range. If chrysotile alone is used in this estimate, it appears a
higher value would be warranted (5). Taken together, with a safety margin
to include a lower reported value in causation of asbestosis (about 23
f//ml - years) (11), a threshold of 0.8 f/ml-year would appear applicable
(20 f/ml - years). From this, using a work time period of 25 years, which
is not likely for asbestos workers in the United States, due to physical
demands of the occupation and actual length of the "industry", allows
suggestion for a threshold of 0.8 f/ml-Time Weighted Average. When
present exposure levels are included in this evaluation (12), it is
unlikely workers in developed nations will exceed a cumulative exposure of
20 or 25 fiber/ml-years. Comparison of this proposed threshold with data
reported by Clin et al., for lung cancer and mesothelioma, with 25 years
or less of exposure (table 1 in Clin et al.), provides support for this
threshold value. However, any value will be controversial, especially in
establishing a threshold.
References
1. Clin B, Morlais F, Launoy G, Guizard AV, Dubois B, Bouvier V,
Desoubeaux N, Marquignon MF, Raffaelli C, Paris C, Galateau-Salle F,
Guittet L, Letourneux M. Environ Occup Med 2011; First online March 15,
2011.
2. Lange JH. Emergence of a New Policy for Asbestos: A Result of the
World Trade Center Tragedy. Indoor and Built Environment 2004; 12:21-33.
3. Pierce JS, McKinley MA, Paustenbach DJ, Finley BL. An evaluation
of reported no-effect chrysotile asbestos exposures for lung cancer and
mesothelioma. Crit Rev Toxicol. 2008;38:191-214.
4. Sichletidis L, Chloros D, Spyratos D, Haidich AB, Fourkiotou I,
Kakoura M, Patakas D. Mortality from occupational exposure to relatively
pure chrysotile: a 39-year study. Respiration. 2009;78:63-8.
5. Dodic Fikfak M, Kriebel D, Quinn MM, Eisen EA, Wegman DH. A case
control study of lung cancer and exposure to chrysotile and amphibole at a
slovenian asbestos-cement plant. Ann Occup Hyg. 2007 51:261-8.
6. Frost G. The joint effect of asbestos exposure and smoking on the
risk of lung cancer mortality for asbestos workers (1971-2005). 2011;
Health & Safety Executive (HSE);
(http://www.hse.gov.uk/research/rrhtm/rr730.htm)
7. Frost G, Darnton A, Harding AH. The effect of smoking on the risk
of lung cancer mortality for asbestos workers in Great Britain (1971-
2005). Ann Occup Hyg. 2011 55:239-47.
8. Frost G, Harding AH, Darnton A, McElvenny D, Morgan D.
Occupational exposure to asbestos and mortality among asbestos removal
workers: a Poisson regression analysis. Br J Cancer. 2008 99:822-9.
9. Lange JH, Mastrangelo G, Buja A. Smoking and alcohol use in
asbestos abatement workers. Bull Environ Contam Toxicol 2006 77:338-42.
10. Harding A-H, Darnton A, Wegerdt J, McElvenny D. Mortality among
British asbestos workers undergoing regular medical examinations (1971-
2005). Occup Environ Med 2009;66487-495.
11. Mastrangelo G, Ballarin MN, Bellini E, Bicciato F, Zannol F,
Gioffr? F, Zedde A, Tessadri G, Fedeli U, Valentini F, Scoizzato L,
Marangi G, Lange JH. Asbestos exposure and benign asbestos diseases in 772
formerly exposed workers: dose-response relationships. Am J Ind Med 2009
52:596-602.
12. Lange JH, Sites SL, Mastrangelo G, Thomulka KW. Exposure to
airborne asbestos during abatement of ceiling material, window caulking,
floor tile, and roofing material. Bull Environ Contam Toxicol 2006 77:718-
22.
I have read with the greatest interest the convincing study on the
dose-response of cadmium ions in kidneys (1). Cadmium compounds also harm
the proteoglycan metabolism (2), and by using the urinary proteoglycan
excretion as an indicator of cadmium effects the threshold would be at 5
microg/g creatinine (3). This agrees very well with the threshold found in
the current investigation.
I have read with the greatest interest the convincing study on the
dose-response of cadmium ions in kidneys (1). Cadmium compounds also harm
the proteoglycan metabolism (2), and by using the urinary proteoglycan
excretion as an indicator of cadmium effects the threshold would be at 5
microg/g creatinine (3). This agrees very well with the threshold found in
the current investigation.
1 Chaumont A, De Winter F, Dumont X, et al. The threshold level of
urinary cadmium associated with increased urinary excretion of retinol-
binding protein and beta-2-microglobulin: a reassessment in a large cohort
of nickel cadmium battery workers. Occup Environ Med 2011; 68: 257-264
Gan et al, 2011 [1] concluded that long-term, occupational noise
exposure was associated with increased prevalence of coronary heart
disease (CHD), for which the authors report a clear exposure-response
relationship that was particularly strong for participants aged < 50
years, men and current smokers. We do not believe the results support
these conclusions, particularly in light of notable study limitations.
Gan et al, 2011 [1] concluded that long-term, occupational noise
exposure was associated with increased prevalence of coronary heart
disease (CHD), for which the authors report a clear exposure-response
relationship that was particularly strong for participants aged < 50
years, men and current smokers. We do not believe the results support
these conclusions, particularly in light of notable study limitations.
The cross-sectional design is a significant drawback. Self-reported
exposure and outcome data created uncertainty, regarding time ordering of
events. Additionally, exposed subjects had many well-known risk factors -
representing strong confounders - for cardiovascular disease (CVD)/CHD,
the effects of which cannot be entirely removed by statistical adjustment.
Moreover, unrecognized bias was likely introduced by including potential
causal intermediates and over-adjusting logistic models,[2] for which a
mechanistic basis is not well established. Although the authors dismissed
the presence of misclassification as non-differential, simulations have
shown this argument to be less persuasive.[3]
We raise additional concerns. First, heterogeneity of effect (Figure
2) precluded reporting summary estimates. It was incorrect to state, for
example, that an increased odds of CHD were observed particularly for men
when they were observed only for them. Second, the authors misapplied the
test for trend of a monotonic exposure-response relationship.[4] Finally,
potentially important effect patterns were obscured by aggregating
outcomes to ascertain CVD/CHD prevalence. CVD, the primary endpoint of
interest and the aggregate of six variables, was not discussed. The
significant association reported for CHD was largely driven by the
relatively strong association observed only for angina pectoris.
Given the prevalence of occupational noise exposure, even a modest
association would represent an important contributor to the development of
CVD/CHD. Unfortunately, Gan et al [1] does little to advance our
understanding of whether such an association exists, particularly because
the mechanism of action is so poorly understood. We agree with the authors
that cohort studies are warranted. These studies should use objective
exposure and outcome measurements.
References
1 Gan WQ, Davies HW, Demers PA. Exposure to occupational noise
exposure and cardiovascular disease in the United States: the National
Health and Nutrition Examination Survey 1999-2004. Occup Environ Med
2010;68:183-190
2 Schisterman EF, Cole SR, Platt RW. Overadjustment bias and
unnecessary adjustment in epidemiologic studies. Epidemiology 2009;20:488
-495
3 Jurek AM, Greenland S, Maldonado G. How far from non-differential
does exposure or disease misclassification have to be to bias measures of
association away from the null? Int J Epidemiol 2008; 37:382-5
4 Maclure M, Greenland S. Tests for trend and dose response:
misinterpretations and alternatives. Am J Epidemiol 1992;135:96-104
The publication of an editorial(1) and opposing commentaries(2,3)
underlines the profile OEM believes should be given to debate of the
proposal for observational epidemiologic studies and their protocols to be
registered in advance(4). I would however express my surprise that none
of these 3 offerings make mention of the workforce perspective in their
analyses of the issues. The editorial itself(1) and the commentary
o...
The publication of an editorial(1) and opposing commentaries(2,3)
underlines the profile OEM believes should be given to debate of the
proposal for observational epidemiologic studies and their protocols to be
registered in advance(4). I would however express my surprise that none
of these 3 offerings make mention of the workforce perspective in their
analyses of the issues. The editorial itself(1) and the commentary
opposing the protocol(3) do not make mention of workers at all, while the
pro-commentary(2) simply includes employees in a list of those involved in
collaboration to reduce difficulties in accessing data.
It may be possible to identify both pros and cons for the
registration proposal based on workforce issues, but to do so in this
letter would detract from its principal purpose in registering the
observation that these aspects have not been considered to date. Research
is a vital element of Occupational Health. OEM is the adopted official
Journal of the Faculty of Occupational Medicine of the Royal College of
Physicians (London). The Faculty first introduced a section dealing with
research in its ethical guidelines in 1999(5) identifying workers as key
customers of research, as well as identifying the need for clear and
detailed protocols, as well as worker consultation. As an Occupational
Physician, I am convinced that workers are owed a very real duty of care
in relation to research, whether there are clinical elements of the study
or not. The trauma and distress that research results publication and the
media response to such publication can cause a workforce, should not be
underestimated.
References
1 Loomis D. Journal Requirements to Register Observational Studies: OEM's
Policy. OEM 2011;68:83/4.
2 Rushton L. Should Protocols for Observational Research be Registered?
OEM 2011; 68:84-86.
3 Pearce N. Registration of Protocols for Observational Research is
Unnecessary and Would Do More Harm Than Good. OEM 2011; 68:86-88.
4 European Centre for Ecotoxicology and Toxicology of Chemicals. Workshop
Report, number 18: Enhancement of the Scientific Process and Transparency
of Observational Studies, 2009.
5 The Faculty of Occupational Medicine Guidance on Ethics for Occupational
Physicians, 5th Edition, May 1999.
Dr. Burstyn, in his commentary (1), underscores the critical
importance of using the best exposure assessment methods possible to
minimize misclassification. We agree about the value of expert formulated
models for systematically and transparently documenting exposure
assessment1, but caution that many existing studies may not be readily
adapted to such model building. For such studies, the best alternative
exposure ass...
Dr. Burstyn, in his commentary (1), underscores the critical
importance of using the best exposure assessment methods possible to
minimize misclassification. We agree about the value of expert formulated
models for systematically and transparently documenting exposure
assessment1, but caution that many existing studies may not be readily
adapted to such model building. For such studies, the best alternative
exposure assessment methodology should be employed, such as job-exposure
matrices (JEMs) or expert assessments of self-reported work histories.
Even though the relationships between the true exposure and estimates by
expert assessment and a JEM are unknown (which is the case for most
exposure assessments) we believe that understanding the differences
between the two methods is informative, especially given the considerable
time and resources necessary to carry out an expert assessment.
As Dr. Burstyn indicates (1), neither assessment approach used in our
study (2) allows us to claim that lead definitely causes brain tumors.
However, if this is the standard for judging the success of an exposure
assessment method, most methods are failures. Although only suggestive, we
do see some evidence of an association and indicate that future studies
would benefit from the most accurate exposure assessment method available.
The intent of our analysis was to compare two widely used approaches and
to encourage epidemiologists to pursue the best exposure assessment
methods possible. We acknowledge limitations with the expert assessment
approach and strongly support the development and use of new exposure
assessment methods. However, expert assessment may be the best approach
available to an existing study and could reveal important associations
that future studies can explore in greater detail using more refined
exposure assessment techniques.
1. Burstyn I. The ghost of methods past: exposure assessment versus
job-exposure matrix studies. Occup Environ Med 2010.
2. Bhatti P, Stewart PA, Linet MS, Blair A, Inskip PD, Rajaraman P.
Comparison of occupational exposure assessment methods in a case-control
study of lead, genetic susceptibility and risk of adult brain tumours.
Occup Environ Med 2010.
We appreciate the careful reading of our editorial [1] by Drs. Mikkelsen and Andersen. We regret our omission of the one published NUDATA study available at the time our editorial was submitted [2]. That study reported significant associations between mouse usage time collected with memory resident software and both, acute neck pain and acute shoulder pain, among 2146 technical assistants. However, because i) median mouse...
In a recent editorial Gerr et al.[1] discuss computer work and musculoskeletal outcomes based on self-reported exposure versus objective recordings using computer software. They state that only one small study (n=27) using objective recordings was published before a large study by Ijmker et al.[2], published in the same issue as the editorial. They failed to consider the results of two NUDATA papers based on more than 2...
We thank Dr. Mikkelsen and colleagues for their constructive comments on our paper. Our responses to their three major questions are listed below.
1) Why did we present various formulations of job strain?
The five formulations of job strain have been commonly reported in the literature. Often, authors chose one or two formulations and thus would not know if their results were consistent across differe...
Self-report of duration of computer use is usually overestimated. The search for a valid measure of exposure to keyboard/mouse use resulted in the development of a computer registration software. The use of this new software generated unexpected results when IJmker et al.1 found software- recorded computer use was not significantly associated with upper extremity/neck symptom onset while self-reported computer use was sig...
Fujishiro et al.1 recently published data on the association of job demands and control with carotid artery intima-media thickness (IMT). The joined effect of demands and control (strain) was analyzed by five different strain definitions: 1. a quadrant term (median splits of demands and control), 2. combinations of tertiles of demands and control, 3. an additive term (demands minus control) , 4. a quotient term (the ra...
The article by Clin et al. (1) provides additional information for a dose-response relationship with asbestos and cancer. Information where a response curve changes effect as observed from background is critical in establishing a safe exposure limit (threshold -exposure/concentration- dose). Some investigators have reported this threshold is around 25 fiber/ml-years (2); although for some members of an exposed group thi...
Dear Editor,
I have read with the greatest interest the convincing study on the dose-response of cadmium ions in kidneys (1). Cadmium compounds also harm the proteoglycan metabolism (2), and by using the urinary proteoglycan excretion as an indicator of cadmium effects the threshold would be at 5 microg/g creatinine (3). This agrees very well with the threshold found in the current investigation.
1 Cha...
Gan et al, 2011 [1] concluded that long-term, occupational noise exposure was associated with increased prevalence of coronary heart disease (CHD), for which the authors report a clear exposure-response relationship that was particularly strong for participants aged < 50 years, men and current smokers. We do not believe the results support these conclusions, particularly in light of notable study limitations.
...The publication of an editorial(1) and opposing commentaries(2,3) underlines the profile OEM believes should be given to debate of the proposal for observational epidemiologic studies and their protocols to be registered in advance(4). I would however express my surprise that none of these 3 offerings make mention of the workforce perspective in their analyses of the issues. The editorial itself(1) and the commentary o...
Dr. Burstyn, in his commentary (1), underscores the critical importance of using the best exposure assessment methods possible to minimize misclassification. We agree about the value of expert formulated models for systematically and transparently documenting exposure assessment1, but caution that many existing studies may not be readily adapted to such model building. For such studies, the best alternative exposure ass...
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