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The paper by Kraus and colleagues in the December 2002 issue of
Occupational and Environmental Medicine addresses the important issue of the
relationship of personal exposure to possible effect in an industrial
setting. After reading this paper I would like to make some comments with
regard to the design, conduct and statistical analysis of the study.
In an area where exposure assessment...
In an area where exposure assessment and confounding effects are so
important, it is interesting to see that seemingly important associations
are being drawn with so little information.
Kraus and colleagues state the goal of the paper as “To correlate the
prevalence of respiratory tract symptoms and diseases with dust and fibre
exposure in the soft tissue industry in Germany” rather than to
investigate whether such a relationship actually exists.
The authors state that: “In every company pure cellulose was the
basis of the production process. Recycled paper was not a relevant
component of the products.”, however, in the introduction they site many
references of toxicological studies that used insulation cellulose
(Isofloc, which is ground up used newspapers sprayed with boric acid) and
other not pure cellulose products. The contaminants in used newspapers
with boric acid would be expected to produce a radically different
toxicological response than inhaled pure cellulose. Only studies that
used pure cellulose of similar source and composition as used in the
plants in this study group should be sited and for such studies the route
of exposure and doses should be provided.
Sampling: From the text, it appears that in this study, data was
obtained on dust measurements in various places in the 7 chosen German
soft tissue companies. These were then compared to symptoms of persons
working in these companies.
The authors state that “According to the employers’ information, we
interviewed all persons from the different workshops employed during the
time period 1996–98.” They then explain that “The data concerning dust
measurements were gathered from 1991 to 1997.” Thus, it appears that the
dust measurements were not directly related to the individuals with the
symptoms nor were they even necessarily coinciding with the presence of
the symptoms. There is no mention of how and where within each plant the
exposures were determined, of whether the dust levels were similar from
1991 to 1997 and whether there was any personnel monitoring to determine
exposures. However, the authors do state that “Because of differences in
the exposure intensity between the seven companies a cumulative exposure
index was generated for describing the individual exposure.” And as such
mean exposure levels were used for comparison.
The confidence that can be placed in conclusions drawn from samples
depends in part on sample size. Small samples can be unrepresentative just
by chance, however, the scope for chance errors can be quantified
statistically. Given this importance, why haven’t the authors stated the
sample sizes in each of the groups used in the statistical analyses?
More problematic are the errors that arise from the method by which
the sample is chosen. In situations with high dust levels there is more
likelihood of sampling which would be atypical of the dust levels more
generally. Such systematic errors cannot usually be measured, and
assessment therefore becomes a matter for subjective judgment. Systematic
sampling errors can be avoided by use of a random selection process in
which each working condition has a known (non-zero) probability of being
included in the study sample. However, this requires an enumeration of all
working conditions in each plant over the entire sampling period (1991 –
Not only was there no mention of such a sampling procedure being
performed in this study but any sensitivity to specific plant conditions
has been lost through the use of mean values.
Group composition: The authors then gloss over the choice of controls
which were persons from the “management department”. Certainly the
working condition and environment of office workers is not comparable to
that of maintenance workers, electricians and mechanics. Also of concern
is the disproportionality in the controls compared to exposed in terms of
number, sex and smoking history. No mention is made of age and how long
the persons in each group worked in the plant. This information would
permit the reader to assess whether the symptoms were associated with
either age or length of employment. Also, the smoking histories are not
comparable between the groups. From the means in Table 1, there is a
positive association between exposure group and smoking which is never
discussed in the paper. If smoking habits were asked “in a detailed way”
as stated, why haven’t the data have been presented? As there appears to
be a dose relationship with smoking and exposure group, the authors should
have discussed in the introduction the possibility that smoking can also
produce similar effects as reported in this paper and provide appropriate
The authors mention using an attenuation factor (“divided by four and
multiplied by individual time of exposure”) under recommendation of
technical experts. This implies that it was not possible to obtain any
kind of relationships using the company individual monitoring data in
relationship to the individuals working in each company. What is the
rational and scientific basis for this? Without such information, the
choice of cut points for the attenuation factor appears arbitrary and
leads the reader to wonder whether the choice of cut points was determined
iteratively in order to find an attenuation factor which produced
Statistical analysis: The authors use the Cochran-Armitage trend test
without adjustment for other variables and even say “that the results are
prone to being confounded”. Yet, they discuss at length the results from
this test in Tables 3 and 4. Further, it is not at all clear that even
this analysis was performed correctly. Hothorn and Bretz (2000), explain
that the Cochran-Armitage trend test is a test based upon a linear dose
response relationship and that the test lacks power for other shapes.
Most of the parameters shown in Tables 3 and 4 of the Kraus paper do not
appear to have a linear dose-response.
More details of the results of the logistic regression analyses
should have been presented to support the conclusions stated by the
authors. At least an estimate of the percent variation in the data
explained by each of the logistic regressions should be provided in the
tables in order to assess the importance of each relationship. Grouped
and individual R2 values are well documented in Statistical texts and can
be calculated for each logistic regression in order to assess importance.
Results: The authors should have clearly state whether they used
inhalable dust or respirable dust in each analysis. Respirable is
probably more relevant, however, Table 2 indicates that there were only 24
respirable dust measurements. With 4 exposure categories (Controls,
<_25 _25100="_25100"/>100) and 7 companies this would amount to less than 1
respirable dust sample per category per company over an 8 year of
monitoring period! It is more likely that they used the inhalable dust
measurements for which there were 105 measurements. Even with the
inhalable dust measurements, this would amount to less than one inhalable
dust measurement every two years per category per company!
The authors state that “The mean sampling time was 1.97 hours (range
0.16–3.8).” This amounts to each category in each plant being monitored
for mean of 7.4 hours over a working time of 14,400 hours. Even if all
105 inhalable dust measurements were performed in one work year (which
they were not), each category in each plant would have been monitored for
a mean of 7.4 hours over a working time of approximately 1800 hours/year.
Yet, the authors are suggesting that somehow these few samples are
representative of what 441 workers were exposed to over an 8 year sampling
period. Not only are the samples not chosen correctly but the small
sample size assures that these measurements are not representative.
The need for statistical significance also seems to have escaped the
authors when discussing the disease parameters. The data presented
indicate that none of the disease parameters are significantly different
from the controls, yet the authors state that “However, sinusitis,
laryngitis, and chronic bronchitis (a disease parameter) showed increasing
odds ratios with increasing cumulative dust exposure (table 5).” What is
the validity of stating this when there is no statistical significance in
Again, in the discussion, the authors state that “After adjustment
for smoking habits, chronic bronchitis was no longer significantly
associated with dust or fibre exposure. However, the highest odds ratio
(1.57) in the subgroup with longest and highest exposure suggests some
deleterious potential.“ This is very worrisome that the authors suggest
that there is a ‘deleterious potential’ when in fact there is no
statistical basis from the data (95% CI of 0.7 to 4.0) for making such a
In Tables 7 and 8 the authors group the ‘Diseases’ as part of the
‘Symptoms’ no longer differentiating between Diseases and Symptoms.
They then go on to state that “For example, intensity and duration of
exposure have an almost equal influence on the symptom “blocked nose”. The
calculated ORs rise with increasing exposure intensity from 6.4 to 10.8
and with increasing exposure duration from 6.4 to 12.5.” Fortunately,
in Table 7 they present the 95% confidence limits which are (shown in
parenthesis) for these values 6.4 (1.2 to 49.7) and 10.8 (2.9 to 70.5)
which suggest that 6.4 is not different from 10.8 statistically. Not
surprising given the statements by Kraus and colleagues, Tables 7 and 8
present no measure of statistical significance for any of the parameters
yet they state that “For symptoms of the upper airways, clear dose-
response relations could be found with relation to cumulative exposure
indices”. This is certainly not supported by the data presented in these
Discussion: Again the authors cite references to articles not
dealing with the same pure cellulose as used in the plants. If there are
studies using the same pure cellulose, then a discussion of the route of
exposure and the exposed dose compared to what is seen here should have
The Ericsson reference and others are not quoted correctly from the
publications. As an example, Ericsson states that “There was a dose-
dependent increase of symptoms from the upper respiratory tract. However,
coughing and coughing with phlegm were not found to be more common among
persons with heavy exposure compared to those with low exposure to the
dust“, indicating that the Ericsson results are not comparable to those in
the current manuscript.
The statement by the authors that “As expected, because of the
distribution of inhalable and respirable dust fraction, symptoms of the
lower respiratory tract have a weaker association with exposure after
adjustment for confounders (for example, cough, phlegm, dyspnoea, and
exercise induced dyspnoea)” should from the data presented in the paper be
changed to state that “As expected, due to the distribution of inhalable
and respirable dust fraction, symptoms of the lower respiratory tract have
no statistically significant association with exposure after adjustment
for confounders (e.g. cough, phlegm, dyspnea, exercise induced dyspnea).”
The question of respirator use in the plants should have been
investigated. If respirators were used even by some employees, then any
association to the measured dust levels for those persons is no longer
I hope that the critical readers of your journal will decide based
upon the statistical significance of the data whether there is a basis for
stating that a relationship exists between exposure and effect in the soft
(1) T Kraus, A Pfahlberg, O Gefeller, H J Raithel, Respiratory
symptoms and diseases among workers in the soft tissue producing industry. Occup Environ Med 2002;59:830–835.
(2) Hothorn LA and Bretz F. Evaluation of Animal Carcinogenicity
Studies: Cochran-Armitage Trend Test vs. Multiple Contrast Tests.
Biometrics Journal 2000;42(5):553-567.
Jump to comment:
The paper by Kraus and colleagues in the December 2002 issue of Occupational and Environmental Medicine addresses the important issue of the relationship of personal exposure to possible effect in an industrial setting. After reading this paper I would like to make some comments with regard to the design, conduct and statistical analysis of the study.
In an area where exposure assessment...