In their reply to me (Weill et al, 2005), I stand reproved for
ignorance and partisanship ("...more interested in the "adversarial
spectrum than the science!"). Modesty precludes me from protesting the
first, but I affirm that I have never been funded by industry or by unions
to write opinions or conduct research on their behalf, nor have I been
paid to assist them in litigation or to support or conte...
In their reply to me (Weill et al, 2005), I stand reproved for
ignorance and partisanship ("...more interested in the "adversarial
spectrum than the science!"). Modesty precludes me from protesting the
first, but I affirm that I have never been funded by industry or by unions
to write opinions or conduct research on their behalf, nor have I been
paid to assist them in litigation or to support or contest proposals to
alter an asbestos hygiene standard.
I would take issue on their interpretation of Wagner's inhalation
experiments, which are not so clear cut and dried in relation to the
development of malignant mesothelioma. In fact, Wagner was persuaded by
his early experimental studies in South Africa, that crocidolite and
Amosite should be considered as hazardous as chrysotile. In later years he
certainly became more kindly disposed towards chrysotile and testified
accordingly at conferences and in depositions on behalf of industry.
Defenders of chrysotile contend that it must be safer than
amphiboles, pleading the alternative that the shape of its fibres renders
it less respirable, and that anyway it is rapidly cleared from the lung
parenchyma (though what this has to do with disease of the pleura is not
apparent). For all this, chrysotile fibres are found in the lung
parenchyma in Man in substantial quantities, long after exposure has
ceased, and after mixed asbestos dust exposure chrysotile is commonly
found juxtapleurally in cases of malignant mesothelioma. The insistence of
chrysotile's protagonists that it is the amphibole in the parenchyma that
is the causal agent rather than the chrysotile near the tumour site, is
that an example of Weill et al's "adversarial spectrum" or "science"?
Weill et al speak of asbestos associated cancers as "...a problem
that with proper control of exposure, will slowly disappear...". In 1906
and at regular intervals subsequently, proper control of exposure was
deemed to to have been exerted so that future generations of physicians
would never see a case of asbestosis. Well regrettably they have , lots
of them as well as lots of bronchial carcinomas and malignant
mesotheliomas. WHO, IPCS, and EU among others, are not persuaded that the
phrase, "the safe use of asbestos" is other than an oxymoron when employed
in Developed Countries let alone in the Third World.
The authors ask despairingly, "..if there will ever come a time when
any good news about asbestos related health effects is welcomed by all who
profess to have worker health as their primary motivation". In the past
good news about asbestos related health effects has ncluded: assurance
from government and industry that Canada's miners and millers were in
robust good health well into their 70s ; that asbestos exposure protected
against pulmonary tuberculosis; that Richard Doll's claim for a causal
association between lung cancer excess and asbestos exposure could not be
corroborated; that asbestos diseases were relegated to history. The World
Trade Organization, Commissioners, who have never been perceived to be
antipathetic to the interests of commerce, have not opposed an EU
Directive that on health grounds will apply a virtual total ban on the use
of chrysotile. For now, the resultant surplus chrysotile mined is being
marketed freely in the Third World, but the United Nations Environment
Programme's Rotterdam Convention may yet require Prior Informed Consent
for this. By all means discount the opinions of hypocrites who profess to
have worker health as their primary motivation, but do the decisions of
IPCS, WTO, and UN, represent good or bad news?
As it had been discussed in the study[1], selection bias may affect
the validity of the result. In this case there would be selection bias, if
the response rate in the survey associated with occupation, and the
distribution of occupation among controls did not reflect that among the
general population. However, if the response rate was independent from
occupations, health status, other lifestyle, se...
As it had been discussed in the study[1], selection bias may affect
the validity of the result. In this case there would be selection bias, if
the response rate in the survey associated with occupation, and the
distribution of occupation among controls did not reflect that among the
general population. However, if the response rate was independent from
occupations, health status, other lifestyle, selection bias may not exist
regardless the response rate. An addition survey only requires information
on occupation, sex and age might be able to evaluate the strength of
selection bias among the controls. Or it would be great if there were any
comparable official statistic .
Reference
1. Mester, B., et al., Occupation and malignant lymphoma: a
population based case control study in Germany. Occup Environ Med, 2006.
63(1): p.17-26.
This article is presenting both the applied question and the
statistical methods used in a very well organised and excellent way.
Though, I have some comments on the use of the words risk, effect and
predictor as these imply a casual relationship and make us believe that we
model the development of neck pain.
The data in the article is longitudinal and in the analysis the
authors are using this...
This article is presenting both the applied question and the
statistical methods used in a very well organised and excellent way.
Though, I have some comments on the use of the words risk, effect and
predictor as these imply a casual relationship and make us believe that we
model the development of neck pain.
The data in the article is longitudinal and in the analysis the
authors are using this. In the marginal model all repeated measures of
“current neck pain” are included and time is in the model. In the
transition model “current neck pain” is modelled and “neck pain previous
year” is included in the model. These are interesting and valuable models
that gives more information on the association of interest than a cross-
sectional study would, but it is not the same as modelling risk or
incidence.
The two models used and the analysis of them is correct as long as
one sees that they are not models of the risk of developing neck pain.
This fact is not clearly put forward either in this article or in texts
about analysis of longitudinal ordinal data. The fact that the data is
longitudinal ensures us that there is more information than data from a
cross-sectional study can give. Note though that the fact that the data is
longitudinal does not automatically imply that it is possible to analyse
cause and effect or to analyse the risk of developing neck pain.
The marginal model in the article models the prevalence of neck pain
using all the information in the repeated measures, time trend etc. The
transition model is modelling the prevalence of neck pain and all the
explanatory variables are adjusted for “previous neck pain”. That is the
OR, for example of “mental stress”, is the OR for having neck pain now,
averaged over all possible values of “previous neck pain”. Note though
that this is not the same as modelling the development of neck pain, in
other words the risk of getting neck pain. In the transition model one
interaction is included, “previous neck pain” and “hand above shoulder”.
This means that for the specific explanatory variable “hands above
shoulder” one can talk about the effect on moving from severe to mild neck
pain (developing neck pain) or the other way around due to “hands above
shoulder”.
The topic of analysing longitudinal ordinal data as an alternative to
dichotomising variables and analysing them traditionally is very
interesting and needs further discussions. There are statistical models
and methods available, but to realise what we model is of great
importance.
I want to thank the authors for a nice article and for introducing
these models in the area of occupational medicine. I look forward to
further discussions and developments in the methodological area of
longitudinal ordinal data.
We appreciate Dr. Kromhout’s comments regarding our article “Air
samples versus biomarkers for epidemiology”[1] and are pleased that he
supports our recommendation that both air samples and biomarkers be
collected whenever possible. Kromhout raises three points in his letter.
First, he suggests that our conclusion that biomarkers tend to be better
surrogates for exposures than air samples might have b...
We appreciate Dr. Kromhout’s comments regarding our article “Air
samples versus biomarkers for epidemiology”[1] and are pleased that he
supports our recommendation that both air samples and biomarkers be
collected whenever possible. Kromhout raises three points in his letter.
First, he suggests that our conclusion that biomarkers tend to be better
surrogates for exposures than air samples might have been biased by our
inclusion of some data from studies that contained only biomarker
measurements. Second, he questions our comparisons of air measurements
and biomarkers in situations where sample sizes differ between the two
types of data. And finally, Kromhout argues that because variance ratios
(values of lambda) are relative measures, they should not be the sole
criteria for choosing between air and biological measurements in an
epidemiology study. We will respond to each of these points in turn.
We agree that it is best to compare environmental and biomarker data
that were collected concurrently from the same subjects. Indeed, as we
indicated, we made every effort to do so and were successful in 36 of the
47 biomarker datasets (77%) listed in table 1. We have no reason to
believe, as Kromhout suggests, that the remaining 11 biomarker datasets
were less representative of biomarker measurements than those with
concurrent air measurements. But, even if we restrict our analyses to
datasets with concurrent air and biological measurements, 62% of these
datasets had lambda ratios less than one (median=0.46, p.755, par. 2),
indicating that a typical biomarker should be a less biasing surrogate for
exposure in an epidemiology study than a typical air measurement. This
was the main conclusion of our analyses. Although sample sizes were small
for stratified comparisons, we also observed that lambda ratios for metals
were significantly smaller than one (Figure 5B), while those for pesticide
exposures were significantly greater than one. Although Kromhout
concluded from the latter result that air measurements would be favoured
for pesticides, we cautioned that a lambda ratio greater than one could
also result from multiple routes of pesticide exposure including
inhalation, dermal contact, and ingestion; if this were the case, then
biomarkers would be preferred for pesticide exposures as well.
Regarding the issue of sample sizes, Kromhout suggests that the variance
components estimated in our study might have been influenced by the
relative numbers of air and biomarker measurements in our database. His
argument is based upon previous work, which indicated that the within-
subject variance components, estimated from air measurements of workplace
exposures, tended to be greater when sample sizes were greater than 10
measurements than when they were less than 10 measurements’.[2] In fact,
the median number of repeated observations from a given subject in our
database was three for both biomarkers (range: 2-30) and air measurements
(range: 2-37). So, different sample sizes were unlikely to have
influenced our results. We also note that the variance components
estimated in our study were obtained after adjustment for fixed time
effects, whereas those from Kromhout’s study were not.[2] Because sample
sizes tend to be positively associated with the duration of a study,
larger numbers of measurements tend to suggest longer periods of
observation which can introduce trends and seasonal effects into the data.
Indeed, in our study we identified significant fixed effects of time in
about 1⁄2 of the sets of biomarker measurements and about 1/3 of the sets of
air measurements. We reported in our paper that ignoring such fixed time
effects tended to increase the estimated within-person variance component
and to decrease the estimated between-person variance component,
consistent with the earlier work of Symanski et al.[3]
Concerning the relative nature of the variance ratio (lambda), we agree
that it should not be the sole criterion used to choose between air and
biological measurements. As we indicated on p.758 of our paper, “…the
optimal measure of exposure for an epidemiology study depends not only on
variance ratios of the air and biomarker measurements (smaller is better),
but also on projected sample sizes (larger is better), based on practical
considerations and costs, and knowledge of the dominant route of exposure
(if multiple routes, biomarkers are preferred).”
Finally, Kromhout questioned the numbers of datasets we used for
various analyses and noted a discrepancy regarding the numbers of datasets
referred to in Figures 4C and 5C. His confusion may have resulted from
the fact that some studies reported multiple biomarkers for a given air
exposure (e.g., reference 24, appendices B and D) and, occasionally, two
types of air exposure for a given biomarker (e.g., ref 26, appendices B
and D). Thus, 43 datasets generated 64 estimates of lambda for biomarkers
(Figure 4) and generated 54 lambda ratios (Figure 5). While rechecking
our files, we found that one set of blood lead measurements had been coded
as an intermediate-term biomarker for the estimate of lambda (Figure 4C)
and as a long-term biomarker for the estimate of the lambda ratio (Figure
5C). We also discovered that an asterisk (indicating statistical
significance) had been inadvertently deleted from Figure 5B under the bar
‘Metal’. We apologize for any confusion this may have caused.
Sincerely,
S.M. Rappaport, Ph.D.
Yu-Sheng Lin, Ph.D.
Lawrence L. Kupper, Ph.D.
School of Public Health
University of North Carolina
Chapel Hill, NC 27599-7431
U.S.A.
References
1. Lin YS, Kupper LL, Rappaport SM. Air samples versus biomarkers for
epidemiology. Occup Environ Med. 2005 Nov;62(11):750-60.
2. Kromhout H, Symanski E, Rappaport SM. A comprehensive evaluation of
within- and between-worker components of occupational exposure to chemical
agents. Ann Occup Hyg. 1993;37(3):253-70.
3. Symanski E, Kupper LL, Kromhout H, Rappaport SM. An investigation of
systematic changes in occupational exposure. Am Ind Hyg Assoc J.
1996;57(8):724-35.
Sir, the recent paper by Lin et al.[1] in the November issue of the
journal was a thought provoking piece of work. In their paper the authors
try to prove the theoretically derived hypothesis that biomarkers of
exposure have smaller variance ratios and would typically provide less
biased surrogates of exposure compared to air measurements. Although I
entirely agree with the theoretical part of this s...
Sir, the recent paper by Lin et al.[1] in the November issue of the
journal was a thought provoking piece of work. In their paper the authors
try to prove the theoretically derived hypothesis that biomarkers of
exposure have smaller variance ratios and would typically provide less
biased surrogates of exposure compared to air measurements. Although I
entirely agree with the theoretical part of this scientific discussion, I
do not think the data presented in their paper actually support the
notion.
I would like to raise three issues to support my case. First, in
order to proof the hypothesis one would have to compare concurrently
collected environmental and biological data gathered from the same
individuals during the same time period. The main analysis presented in
the paper by Lin et al.1 does not fulfil this criterion, because as the
authors pointed out datasets were added with biomarker data only. These
added datasets might not have been representative for the other situations
considered and as the authors point out might be from exposure situations,
which favours biomonitoring a priori (exposure with a long residential
half-life). When we restrict ourselves to the data presented in Figure 5
we see no statistically significant difference in variance ratios between
the two measures of exposure except for pesticides, but these exposure
situations remarkably show variance ratios that favour air measurements.
There is also a puzzling issue when one compares table 3, figure 4 and
figure 5. From figure 4 one learns that 64 lambda values could be
estimated for biomarker measurement datasets and 43 for air measurement
datasets. One would expect that when the authors fall back to exposure
settings where both measurements were performed, they would present
results for 43 datasets. However, in figure 5 results are presented for 54
datasets. It becomes even more puzzling when one considers table 3 where
33 air measurement datasets and 46 biomarker measurement datasets are
mentioned. In addition, comparing figure 4c with 5c it is remarkable that
the number of datasets with biomarkers with intermediate residence time
increases from 17 to 18. Unless the residence time of the biomarkers was
recoded this would have been impossible.
The second issue that might have biased the presented results is the
unequal number of both monitored workers and occasions. From table 1 and
Appendices A and B it is clear that in most situations more air samples
were collected than biomarker samples. As was shown earlier[2], when the
number of observations increases (more individuals measured on more
occasions covering a larger area of possible conditions) the estimated
between- and within-worker variance components have a tendency to increase
as well. So if one does not restrict the datasets to the same individuals
measured over the same period, comparing variance ratios of air and
biomarker data becomes problematic. From the Appendices it looks like that
in most cases the data collection covered the same period, but not
necessarily the same individuals (see for instance reference 24 in
Appendix B, where 249 airborne styrene measurements were performed on 48
individuals during a period of 2-3 months, while 146 blood styrene
measurements were taken from 29 individuals in a period of 3-4 months).
The third issue I would like to raise is the comparison of
environmental versus occupational exposures. Based on the presented fold
ranges and lambda values the authors claim “biomonitoring may be more
advantageous in environmental settings than in occupational settings”.
Here the authors appear to forget that fold ranges and lambda’s are by
definition of a relative nature. A fold range of 100 at nanogram level
might be biologically totally irrelevant, while a fold range of 2 around a
level where biological effects can be expected, might be relevant to study
in an epidemiological setting. When we studied a group of pig farmers in
The Netherlands3 their between-farmer fold range in average air exposure
to endotoxins was very low (bwR95=4.1) and the variance ratio such that
we could expect heavily biased exposure response relations (λ= 4.7).
Nevertheless even within a group so uniformly exposed meaningful exposure-
response relations could be discerned by applying an innovative exposure
assessment method where measurement results were modelled and exposure
predicted based on diary information.
Finally, I would like to comment and I am convinced that the authors
will fully agree, that one should not choose between air sampling and
biomonitoring, but one should perform both whenever possible. Not only
because more data is needed to prove the case for biomonitoring (for which
currently data is insufficient), but also air and dermal measurements are
a necessity in order to link (internal) exposure to possibilities for
hazard control. Prevention of occupational and environmental exposures
before they reach harmful concentrations will continue to be our first
priority in the field of occupational and environmental health.
References:
1. Lin YS, Kupper LL, Rappaport SM. Air samples versus biomarkers for
epidemiology. Occupational and Environmental Medicine 2005; 62:750-60.
2. Kromhout H, Symanski E, Rappaport SM. A comprehensive evaluation of
within- and between-worker components of occupational exposure to chemical
agents. the Annals of Occupational Hygiene 1993; 37:253-270.
3. Preller L, Kromhout H, Heederik D, Tielen MJM. Modeling long-term
average exposure in occupational exposure-response analysis. Scandinavian
Journal of Work Environment and Health 1995; 21:504-12.
We have read the study on respiratory disease and cardiovascular
morbidity by Koskela and coworkers with great interest.[1] They found no
obvious effect of direct dust exposure on ischaemic heart disease (IHD)
among granite workers and workers in metal industry such as foundry
workers and iron foundry workers in Finland. Furthermore, there was a weak
association between dust exposure and chronic bronc...
We have read the study on respiratory disease and cardiovascular
morbidity by Koskela and coworkers with great interest.[1] They found no
obvious effect of direct dust exposure on ischaemic heart disease (IHD)
among granite workers and workers in metal industry such as foundry
workers and iron foundry workers in Finland. Furthermore, there was a weak
association between dust exposure and chronic bronchitis and
pneumoconiosis, respectively, among granite workers. However, there was an
association between chronic bronchitis and IHD among granite workers and
iron foundry workers.
We want to make one comment regarding a possible bias towards unity-
effect by the inclusion of non-exposed workers.
The study by Koskela et al. comprises six cohorts. Three of these
cohorts consist of 1000 iron foundry workers, 1000 metal product workers
and 1000 electrical workers, respectively. The subjects selected into the
cohorts were 400 current and 400 former male workers with the longest
duration of employment and a further 200 with the shortest duration of
employment.
A possible association between air pollutants and IHD may have a
similar mechanism as the association between smoking and IHD. Smoking more
than 25 cigarettes per day is estimated to double the risk of IHD compared
with non-smokers. This risk decreases after quitting smoking and becomes
closer to the risk of non-smokers.[2] Thus, former dust exposed workers
followed for 16 years may ultimately have a risk similar to non-exposed
workers.
Consequently, the findings of the study by Koskela and coworkers may
underestimate the relation between dust exposure and the occurrence of
IHD. We certainly agree with our Finnish colleagues that efforts to
prevent IHD should both include the prevention of respiratory diseases and
the control of dust exposure.
We do not have any competing interest regarding this letter.
References:
1. Koskela R-S, Mutanen P, Sorsa J-A, Klockars M. Respiratory disease
and cardiovascular morbidity. Occup Environ Med 2005; 62: 650-655.
2. Doll R, Peto R, Wheatley K, Gray R, Sutherland I. Mortality in
relation to smoking: 40 years’ observations on male British doctors. BMJ
1994; 309: 901-911.
Bengt Sjögren, MD, PhD
Work Environment Toxicology
Institute of Environmental Medicine
Karolinska Institutet
P.O. Box 210
SE-171 77 Stockholm
Sweden
Tel: 46 8 524 822 29
Fax: 46 8 31 41 24
E-mail: Bengt.Sjogren@ki.se
Carl-Göran Ohlson, MD, PhD
Department of Occupational and Environmental Medicine
Örebro University Hospital
SE-701 85 Örebro
Sweden
Tel.: +46 19 6022468
Fax.: +46 19 120404
E-mail: carl-goran.ohlson@orebroll.se
We read with interest the article by Sorahan et al., “Cancer risks in a historical UK cohort of
benzene exposed workers” [1]. We note that the authors showed an increased SMR and SRR for
lung cancer among this group. They comment that “there was evidence of increased mortality
for lung and lip cancers and for ANLL, and increased morbidity for lung and pleural cancers.
There is no reason to suspect that benze...
We read with interest the article by Sorahan et al., “Cancer risks in a historical UK cohort of
benzene exposed workers” [1]. We note that the authors showed an increased SMR and SRR for
lung cancer among this group. They comment that “there was evidence of increased mortality
for lung and lip cancers and for ANLL, and increased morbidity for lung and pleural cancers.
There is no reason to suspect that benzene is responsible for the increased lung and pleural
cancer risks in this study.” The authors then go on to point out that it is likely that some
members of the cohort were exposed to other lung carcinogens. However, we feel that if this
was a likely explanation for the observed excess, then the SMR for lung cancer would probably
have been heterogeneously distributed among the industries studied, the risk being elevated only
in those industries with known exposures to lung carcinogens. This does not seem to have been
the case. Further , confounding by cigarette smoking seems unlikely because the SMR for some
other tobacco-related causes are not significantly elevated (e.g. non-maliganant diseases of the
respiratory system).
There have been two papers based on a Chinese cohort of benzene exposed workers [2,3], which
are relevant to this issue. The first of these, showed an RR for lung cancer of 2.31 among
exposed non-smokers, and while 95% confidence intervals were not reported the authors did
state this was statistically significant [2]. The second reported a relative risk for lung cancer of
1.4 (95% CI 1.0-2.0) among benzene exposed males [3]. Therefore, we think it is important to
recognize that while the excess described in this paper may be due to exposure to other
carcinogens, it is also possible that we are seeing accumulating evidence of an association
between benzene exposure and lung cancer.
References
1 Sorahan T, Kinlen LJ, Doll R. Cancer risks in a historical UK cohort of benzene exposed
workers. Occupational and Environmental Medicine 2005; 62:231-236.
2 Yin SN, Li GL, Tain FD, et al. A retrospective cohort study of leukemia and other
cancers in benzene workers. Environmental Health Perspectives 1989; 82:207-13.
3 Yin SN, Haze RB, Linet MS, et al. A cohort study of cancer among benzene exposed
workers in China: Overall results. American Journal of Industrial Medicine 1996;
29:227-35.
We thank Helen C Francis for the interest in our article
“Mould/dampness exposure at home is associated with respiratory disorders
in Italian children and adolescents: the SIDRIA-2 Study” [1] and we
appreciate her comments reported in the letter “The validity of self-
reported measures of mould/dampness”, 21 September, 2005.
We think it is difficult to compare our findings with those of Tavernier
and co...
We thank Helen C Francis for the interest in our article
“Mould/dampness exposure at home is associated with respiratory disorders
in Italian children and adolescents: the SIDRIA-2 Study” [1] and we
appreciate her comments reported in the letter “The validity of self-
reported measures of mould/dampness”, 21 September, 2005.
We think it is difficult to compare our findings with those of Tavernier
and colleagues [2] for the following reasons:
1. that study regards a relatively little (n=200) sample of subjects,
aged 4 to 17 years, whereas we studied thousands of children and
adolescents, separately;
2. that study regards current exposure, whereas we compared the
effects of current and early exposure.
In addition, as regard the current exposure, the findings by
Tavernier and colleagues do not seem to disagree with our results. We also
did not find a significant association between asthma and current
exposure, among the adolescents, and the association was not so strong, as
indicated by 95%CI (1.00-1.93), among the children.
It is not surprising to find controversial results in the literature.
Although some studies showed a poor concordance between self-reported
dampness and objective measures [2, 3], other authors confirmed the
validity of questionnaires. For instance, Belanger et al report that “the
association of reported mold and wheeze was confirmed by measured levels
of fungi and wheeze, suggesting that reports of mold were not biased”[4].
The fact that some studies suggest “an almost complete disagreement
between self-reported dampness, visual inspection by a trained
investigator and measurement using an industrial dampmeter” might even
suggest that objective measurements are not completely reliable. As we
reported in our article, although studies that objectively assess exposure
would be desirable, there are problems with accurate air sampling [5]. The
measurements currently used might not accurately represent the variability
of concentration over time, because the measurement periods are too short
and the variability in repeated measures is elevated over a very short
period of time. Thus, both self-report and direct measurement would be
desirable. However, our study focused on the comparison between possible
effects by current or by early exposure and, obviously, early exposure
assessment could only be assessed through the questionnaire.
References
1. Simoni M, Lombardi E, Berti G et al. Mould/dampness exposure at
home is associated with respiratory disorders in Italian children and
adolescents: the SIDRIA-2 study. Occup Environ Med 2005; 62:616-622.
2. Tavernier GO, Fletcher GD, Frencis HC et al. Endotoxin exposure in
asthmatic children and matched healthy controls: results of IPEADAM study.
Indoor Air 2005; 15 suppl 10:25-32.
3. Dales RE, Miller D, Mc Mullen ED. Indoor air quality and health:
validity and determinats of reported home dampness and moulds. Int J
Epidemiol 1997; 26:120-125.
4. Belanger K, Beckett W, Triche E, et al. Symptoms of wheeze and
persistent cough in the first year of life: association with indoor
allergens, air contaminants, and maternal history of asthma. Am J
Epidemiol 2003;158:195-202.
5. Douwes J, Pearce N. Is indoor mold exposure a risk factor for
asthma? Am J Epidemiol 2003;158:203-6.
The interesting results of Delphi study (OEM 2005; 62: 406-413)
underline the increasing importance of a specific training for physicians
involved in the prevention of accidents and other work-related disorders
and diseases. Although EU countries have similar legislation concerning
activities and individual prevention on the workplace, training curricula
for doctors involved in the health activities...
The interesting results of Delphi study (OEM 2005; 62: 406-413)
underline the increasing importance of a specific training for physicians
involved in the prevention of accidents and other work-related disorders
and diseases. Although EU countries have similar legislation concerning
activities and individual prevention on the workplace, training curricula
for doctors involved in the health activities are variable in different
countries. In Italy for instance a legislation approved by the Italian
Parliament in 2001 has extended to specialists in Hygiene and preventive
medicine and in Forensic medicine (“medicina legale”) the licence to
practice health surveillance in the workplace (become “competent” doctor
or “medico competente”), an undertaking so far reserved to specialists in
Occupational medicine.[2,3]
Occupational Medicine training was mainly oriented in the past
decades to clinical occupational medicine only which, though important,
does not give a full response to the needs for expertise in a preventive
workplace-oriented occupational health service, as underlined also in a
recent WHO report.[4]
The post-graduate training for specialists in Hygiene and preventive
medicine is mainly oriented to environmental hygiene and environmental
health, management, communication, health education, epidemiology and
medical statistics.[2]
The curriculum of the specialist in Forensic medicine is oriented to
health legislation, legal obligations of physicians and health personnel,
writing reports about health problems other than more specific training in
forensic medicine.[3]
Although the extension to the two new specialities was not well
accepted by the specialists in Occupational medicine[5], it seems that
the recent results of the Delphi study[1,6], as well as other
recommendations[4,7], stress the importance of the latter two post-
graduate curricula. In fact, according to customer opinions, the four most
important areas of competency of occupational physicians are law, hazards,
fitness and communication. For the training in these competencies the
present curricula in Hygiene and preventive medicine and in Forensic
medicine seem appropriate for the training of the “competent” doctor in
Italy. An additional analysis of the results, which took into
consideration the specific competencies required by the Occupational
physician, show that the activities which obtained the highest scores were
much more present in the curricula of the two post-graduated programmes
(Hygiene and Forensic medicine) introduced in 2001: applying legal and
other ethical requirements for confidentiality (score of 4.48 in Delphi
study); being well informed about acts, regulations, codes of practice
(4.36); identifying the occupational needs (4.25); understanding the
differences between work related and environmental related diseases
(4.11); assessing the work environment and evaluating risks (4.11).
In conclusion the results of Delphi study applied to training
programmes and continuing professional education in Italy indicate that
the most profitable way for the implementation of curricula for
Occupational physicians (“competent” doctors) is the co-operation between
the scientific associations of Occupational medicine, Hygiene and
preventive medicine and Forensic medicine. This in order to adopt common
initiatives to better match the modern training needs of trade unions,
companies and workers and to create in a short time a cadre of
appropriately skilled doctors.
Carlo Signorelli, PhD
Full Professor of Hygiene
University of Parma
Dept. of Public Health
Via Volturno, 39 – 43100 PARMA
References
1. Reetoo KN, Harrington JM, Macdonald EB. Required competencies of
occupational physicians: a Delphi survey of UK customer. Occup Environ Med
2005; 62: 406-413.
2. Carreri V, Signorelli C, Marinelli P, Fara GM, Boccia A. New
opportunities to improve occupational health in Italy. Lancet 2002; 360:
723.
3. Tomassini A. New opportunities to improve occupational health in
Italy. Lancet. 2002 Aug 31;360(9334):723-4.
4. WHO. Global Strategy on Occupational Health for All.
Recommendation of the Second Meeting of the WHO Collaborating Centres in
Occupational Health, Beijing, China, 11-14 October 1994.
5. Manno M, , Mutti A, Apostoli P, Bartolucci B, Franchini I.
Occupational medicine at stake in Italy. Lancet. 2002;359: 1865.
6. Macdonald EB. Ritchie KA, Murrey KJ, Gilmpur WH. Requirements for
occupational training in Europe: a Delphi study. Occup Environ Med 2000;
57: 98-105.
7. Turner S, Hobson J, D’Auria D, Beach J. Continuing professional
development of occupational medicine practitioners: a needs assessment.
Occupational Medicine 2004; 54: 14-20.
I was not against figure 1. Instead, I was concerning the second
scenario in figure 1: people who had respiratory diseases would have a higher
rate of IHD if they kept exposure to dust—there might be an interaction
between respiratory diseases and dust exposure after. In the discussion of
the paper it states that “The direct independent effect of dust exposu...
I was not against figure 1. Instead, I was concerning the second
scenario in figure 1: people who had respiratory diseases would have a higher
rate of IHD if they kept exposure to dust—there might be an interaction
between respiratory diseases and dust exposure after. In the discussion of
the paper it states that “The direct independent effect of dust exposure
on IHD and other CVDs was small”, but many people who had been diagnosis
for respiratory diseases would be removed from the dust exposure job (I am
sorry that I express it as “cohort” in the last letter). Thus most
people who already had been diagnosed for respiratory disease, were not
exposed to dust exposure after they had been diagnosed, even the
“cumulative exposure to dust was considered until the diagnosis date of
ischaemic heart disease (IHD)” .
However as the reply showed that "the exposure data only including
dust exposure after the diagnosis of a respiratory disease," had a small
effect, my question is answered.
I thank the authors so much to give more detail on the information on
smoking. Eletter is a great way to reduce the information lost which is
due to limited space in paper journals. Would it be appropriate to
encourage authors to add more detail on journal websites?
Dear Editor,
In their reply to me (Weill et al, 2005), I stand reproved for ignorance and partisanship ("...more interested in the "adversarial spectrum than the science!"). Modesty precludes me from protesting the first, but I affirm that I have never been funded by industry or by unions to write opinions or conduct research on their behalf, nor have I been paid to assist them in litigation or to support or conte...
Dear Editor,
As it had been discussed in the study[1], selection bias may affect the validity of the result. In this case there would be selection bias, if the response rate in the survey associated with occupation, and the distribution of occupation among controls did not reflect that among the general population. However, if the response rate was independent from occupations, health status, other lifestyle, se...
Dear Editor,
This article is presenting both the applied question and the statistical methods used in a very well organised and excellent way. Though, I have some comments on the use of the words risk, effect and predictor as these imply a casual relationship and make us believe that we model the development of neck pain.
The data in the article is longitudinal and in the analysis the authors are using this...
The Editor,
We appreciate Dr. Kromhout’s comments regarding our article “Air samples versus biomarkers for epidemiology”[1] and are pleased that he supports our recommendation that both air samples and biomarkers be collected whenever possible. Kromhout raises three points in his letter. First, he suggests that our conclusion that biomarkers tend to be better surrogates for exposures than air samples might have b...
Dear Editor,
Sir, the recent paper by Lin et al.[1] in the November issue of the journal was a thought provoking piece of work. In their paper the authors try to prove the theoretically derived hypothesis that biomarkers of exposure have smaller variance ratios and would typically provide less biased surrogates of exposure compared to air measurements. Although I entirely agree with the theoretical part of this s...
Dear Editor,
We have read the study on respiratory disease and cardiovascular morbidity by Koskela and coworkers with great interest.[1] They found no obvious effect of direct dust exposure on ischaemic heart disease (IHD) among granite workers and workers in metal industry such as foundry workers and iron foundry workers in Finland. Furthermore, there was a weak association between dust exposure and chronic bronc...
Dear Editor
We read with interest the article by Sorahan et al., “Cancer risks in a historical UK cohort of benzene exposed workers” [1]. We note that the authors showed an increased SMR and SRR for lung cancer among this group. They comment that “there was evidence of increased mortality for lung and lip cancers and for ANLL, and increased morbidity for lung and pleural cancers. There is no reason to suspect that benze...
Dear Editor
We thank Helen C Francis for the interest in our article “Mould/dampness exposure at home is associated with respiratory disorders in Italian children and adolescents: the SIDRIA-2 Study” [1] and we appreciate her comments reported in the letter “The validity of self- reported measures of mould/dampness”, 21 September, 2005. We think it is difficult to compare our findings with those of Tavernier and co...
Dear Editor,
The interesting results of Delphi study (OEM 2005; 62: 406-413) underline the increasing importance of a specific training for physicians involved in the prevention of accidents and other work-related disorders and diseases. Although EU countries have similar legislation concerning activities and individual prevention on the workplace, training curricula for doctors involved in the health activities...
Dear Editor,
I thank the authors for they reply.
I was not against figure 1. Instead, I was concerning the second scenario in figure 1: people who had respiratory diseases would have a higher rate of IHD if they kept exposure to dust—there might be an interaction between respiratory diseases and dust exposure after. In the discussion of the paper it states that “The direct independent effect of dust exposu...
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