This carefully conducted study (1) points at the kidney as a
potential target of toxicity of phenoxy acids in a chronic occupational
exposure.
This is biologically plausible as the phenoxy acids are inhibitors of
chloride channels in renal tubular cells (2) which leads to alterations in
the excretion of urinary electrolytes (3).
Thus, it is entirely possible that the chronic dysfun...
This carefully conducted study (1) points at the kidney as a
potential target of toxicity of phenoxy acids in a chronic occupational
exposure.
This is biologically plausible as the phenoxy acids are inhibitors of
chloride channels in renal tubular cells (2) which leads to alterations in
the excretion of urinary electrolytes (3).
Thus, it is entirely possible that the chronic dysfunction can lead
to renal problems.
1 Boers D, Portengen L,Bas Bueno-de-Mesquita H, et al. Cause-specific
mortality of Dutch chlorophenoxy herbicide manufacturing workers. Occup
Environ Med 2010; 67: 24-31
2 Savolainen H. New uses for old urine tests. Brit J Ind Med 1989;
46: 361-363
3 Manninen A, Kangas J, Klen T, Savolainen H. Exposure of Finnish
farm workers to phenoxy acid herbicides. Arch Environ Contam Toxicol 1986;
15: 107-111
Laney, et al. [1] provide important and compelling insight to
potential causes of the unexpected occurrence of progressive massive
fibrosis among underground coal miners in some areas of the U.S. Based on
the occurrence of “r” opacities in these films, exposure to quartz is the
likely cause. This conclusion is supported by an exposure assessment that
shows elevated exposure to quartz dust in area...
Laney, et al. [1] provide important and compelling insight to
potential causes of the unexpected occurrence of progressive massive
fibrosis among underground coal miners in some areas of the U.S. Based on
the occurrence of “r” opacities in these films, exposure to quartz is the
likely cause. This conclusion is supported by an exposure assessment that
shows elevated exposure to quartz dust in area mines.[2] However, there
is an increase in the prevalence of CWP that extends beyond these areas
and that includes CWP in lower categories [3] and that may have different
causes.
Laney et al.[1] suggest that an increase in hours worked may
contribute to the increase in the prevalence of CWP. I agree. More
important, data to support this suggestion exist. Mine operators report
to MSHA hours worked and average number of workers per quarter [4]. From
these reports, one can easily calculate hours worked per miner. Based on
these data, annual hours worked per underground miner increased from an
average of about 1700 hours per year in 1982 to about 2200 hours per year
in 2006, an increase of nearly 30%. These measures, and measures of dust
concentration, are available for each mine since the early 1970’s. They
could and should be combined to revise estimates of miners’ exposure in
relation to the occurrence of CWP and thereby evaluate this suggestion.
Clearly, a complete understanding of exposure is important for preventing
CWP. Laney et al. [1] have identified an important cause. And as they
suggest, there is more to do.
James L. Weeks, ScD, CIH
Industrial Hygiene Consultant to the United Mine Workers of America
1. Laney AS, Petsonk EL and Attfield MD. Pneumoconiosis among
underground bituminous coal miners in the United States: Is silicosis
becoming more frequent? Occ Enviro Med. Published online 22 Sep 2009.
2. Pollock DE, Potts JD and Joy GJ. Investigation into dust exposure
and mining practices in the Southern Appalachian Region. (ND) (October
28,2009). (http://www.cdc.gov/niosh/mining/pubs/pdfs/iidea.pdf)
3. National Institute for Occupational Safety and Health. Work-
related lung disease surveillance report 2007. (October 28, 2009).
(http://www.cdc.gov/niosh/docs/2008-143/)
We welcome the appearance of this new analysis of asbestos related
mortality which constitutes an important addition to the available
evidence. We note that the lung cancer risk from this data highlighted by
the authors and based on their internal analyses gives an identical risk
factor to the one suggested as the 'best estimate' in our earlier meta-
analysis (1): a relative risk of 1.102 per 100 f/ml.yr translates almost...
We welcome the appearance of this new analysis of asbestos related
mortality which constitutes an important addition to the available
evidence. We note that the lung cancer risk from this data highlighted by
the authors and based on their internal analyses gives an identical risk
factor to the one suggested as the 'best estimate' in our earlier meta-
analysis (1): a relative risk of 1.102 per 100 f/ml.yr translates almost
exactly to an excess over expected of 0.1% per f/ml.yr.
The risk of mesothelioma derived from these new data is higher by a
factor of 10 than that which emerged from our meta-analysis. The following
table shows these new data (labelled N. Carolina) along with the
chrysotile data used in our analysis.
The generally small numbers mean that all the estimates are subject
to substantial statistical error. The largest single set of observations
is that derived from the Canadian mines, and this gives a low and
(statistically) reasonably precise estimate of about 0.001. The remaining
observations are statistically consistent (P=0.075); though mainly due to
their imprecision, rather than to the similarity of the estimates. The
statistical consistency is somewhat improved by also removing the Italian
mines (Balangero) cohort (P=0.10). The mean risk taken across the
remaining cohorts is 0.0070 with a confidence limit running from 0.0038 to
0.013.
Combining the two mining cohorts gives a joint estimate of 0.00096
(95% CI
0.00069, 0.0013).
The estimate from the latest study is based on eight cases. Assuming
Poisson variability the underlying risk could correspond to between 4 and
16 cases. Up to three of the observed cases may be due to amosite
exposure in plant 3, but it could also be argued that some mesothelioma
cases may have been missed during the period prior to the introduction of
ICD 10.
An estimate of 0.007% per f/ml.yr still places the risk of
mesothelioma from chrysotile at least an order of magnitude lower than the
risk we estimate for the amphiboles fibres (0.5 for crocidolite, 0.1 for
amosite). As we argued in our original paper, if the risk from chrysotile
is indeed substantially lower than from the other fibre types then the
level of risk observed in cohorts with mixed exposure provides an upper
limit to the true risk for chrysotile on its own. In our meta-analysis
four of the mixed fibre cohorts had mesothelioma risk estimates around or
below the 0.01 level. In the largest of these (Ferodo) there is a strong
indication that 11 of the 13 mesothelioma deaths were due to crocidolite
exposure. Since the overall risk for this cohort was 0.014, the implied
chrysotile risk in this setting (friction products) would be well below
0.01.
These new results certainly strengthen the case for the proposition
that the per fibre risk of mesothelioma from chrysotile in textile plants
is greater than it is in the mines. Whether this differential also
applies in other settings is not clear from the evidence above: the
absence of mesothelioma deaths in the New Orleans and Connecticut cohorts
is statistically consistent with a risk of 0.01 though, obviously, more
consistent with the mines estimate of 0.001.
John Hodgson
Andrew Darnton
Statistics Branch (Epidemiology Group)
Health and Safety Executive
Redgrave Court (S4.3)
Merton Road
Bootle L20 7HS
United Kingdom
Tel: 0151 951 4566 (fax 4703)
1. JT Hodgson, A Darnton. The quantitative risks of mesothelioma
and lung cancer in relation to asbestos exposure. Ann. occup. Hyg., Vol.
44, No. 8, pp. 565–601
We welcome the comments on our systematic review on factors
associated with the Work Ability Index (WAI) with regard to the practical
implications of the WAI instrument.
After reading the review, the author of the e-letter concludes that ‘the
WAI should be used with caution outside samples of people with
musculoskeletal disorders and that more robust psychometric data be
produced in other groups’. The intended message o...
We welcome the comments on our systematic review on factors
associated with the Work Ability Index (WAI) with regard to the practical
implications of the WAI instrument.
After reading the review, the author of the e-letter concludes that ‘the
WAI should be used with caution outside samples of people with
musculoskeletal disorders and that more robust psychometric data be
produced in other groups’. The intended message of the review is that the
WAI is a useful tool in the field of employability of (older) workers, and
that various work-related and individual factors play a role in someone’s
workability. Our review was restricted to those factors that are not
incorporated in the work ability index itself and, thus, we have not
investigated health complaints, such as musculoskeletal disorders, as
determinants and also refrained from analyzing in which occupational
populations the use of the work ability index may be warranted. We agree
with Nicholas Glozier that the work ability concept is complex and needs
further study. Since the work ability index is a summary score over
different dimensions, caution is required in drawing conclusions on a
decreased WAI score without further diagnosis of reasons for a decreased
WAI and underlying mechanisms. Previous studies have shown that the WAI is
a useful tool among workers in physically demanding professions[1] as well
as among mentally demanding professions[2] to analyze factors at
population level that influence employability of workers and, thus, may be
considered for addressing in interventions.
[1] Alavinia SM, van Duivenbooden C, Burdorf A. Influence of work-
related factors and individual characteristics on work ability among Dutch
construction workers. Scand J Work Environ Health. 2007 Oct;33(5):351-7.
[2] van den Berg TI, Alavinia SM, Bredt FJ, Lindeboom D, Elders LA,
Burdorf A. The influence of psychosocial factors at work and life style on
health and work ability among professional workers. Int Arch Occup Environ
Health. 2008 Aug;81(8):1029-36.
The systematic review of factors associated with the Work Ability
Index raises significant questions about this measure. The paper repeats
the assertion that "the bases for work ability are health and functional
capacity, but work ability is also determined by professional knowledge
and competence (skills), values, attitudes, and motivation, and work
itself." Certainly clinicians are constantly asked to assess the health...
The systematic review of factors associated with the Work Ability
Index raises significant questions about this measure. The paper repeats
the assertion that "the bases for work ability are health and functional
capacity, but work ability is also determined by professional knowledge
and competence (skills), values, attitudes, and motivation, and work
itself." Certainly clinicians are constantly asked to assess the health
and functional components of an individual's work related problems and
help with this aspect of assessment is welcome. However, as table 6
succinctly demonstrates, the WAI shows consistent null associations with
three of the four health and functional capacity constructs -
cardiorespiratory fitness, "mental performance" and poor balance. Whilst
some of these may reflect type 2 errors in the initial studies from the
ORs quoted in the table this is concerning if the WAI is to be used across
a range of health conditions. The results of intervention studies, which
appear to be detected as positive only in those interventions with
physical function components, may reflect a lack of responsiveness of the
instrument to other interventions targetting improvements in, for example,
mental health. In summary this review suggests that the WAI should be used
with caution outside samples of people with musculoskeletal disorders and
that more robust psychometric data be produced in other groups.
The comment by the authors about the computer code IREP used by
NIOSH, namely: “IREP includes a DDREF, which lowers the probability of
causation [PC] for low-dose-rate exposures,” has the potential to be
misinterpreted. IREP contains two discrete DDREF distributions, one for
most solid cancers and another, more restricted, distribution for thyroid
and female breast cancers. The first mentioned, with values of DDREF
rang...
The comment by the authors about the computer code IREP used by
NIOSH, namely: “IREP includes a DDREF, which lowers the probability of
causation [PC] for low-dose-rate exposures,” has the potential to be
misinterpreted. IREP contains two discrete DDREF distributions, one for
most solid cancers and another, more restricted, distribution for thyroid
and female breast cancers. The first mentioned, with values of DDREF
ranging from 0.5 to 5, is most comparable to the inverse of the risk ratio
calculated by Jacob et al.
The IREP-based PC depends on the value selected from this
distribution. To be correct, the PC is never lowered by the DDREF for any
U.S. radiation worker whose claim for compensation is evaluated using
IREP. This is because the 99th percentile of PC is used in making
compensation decisions, unlike the U.K. compensation scheme in which the
50th percentile estimate is used.
In the U.S., values from the lower end of the DDREF distribution
(i.e., <1, which corresponds to a risk ratio >1 in the authors’
parlance) drive PC estimates at the 99th percentile. Thus, the effective
“risk ratio” produced by the DDREF in IREP as it is currently used in
making compensation decisions is influenced by values greater than 1,
which is consistent with current uncertainties in DDREF. This differs from
the approach used in the U.K., which does currently not allow for risk
ratios greater than 1. [jrt@senes.com]
Authors
Craig Steinmaus1, 2
Allan H Smith1
Martyn T Smith1
Authors affiliations
1. School of Public Health, University of California, Berkeley, University
Hall, Berkeley, CA 94720-7360, USA
2. Office of Environmental Health Hazard Assessment, California
Environmental Protection Agency, 1515 Clay St., Oakland, CA 94612
Corresponding author
Craig Steinmaus, School of Publ...
Authors
Craig Steinmaus1, 2
Allan H Smith1
Martyn T Smith1
Authors affiliations
1. School of Public Health, University of California, Berkeley, University
Hall, Berkeley, CA 94720-7360, USA
2. Office of Environmental Health Hazard Assessment, California
Environmental Protection Agency, 1515 Clay St., Oakland, CA 94612
Corresponding author
Craig Steinmaus, School of Public Health, University of California,
Berkeley, University Hall, Berkeley, CA 94720-7360, USA e-mail:
craigs@berkeley.edu
Sir,
The differences in methods between our meta-analysis and that of Swaen et
al. did not “vastly alter” our most important finding or change our
overall conclusion.1,2 Our major conclusion was that evidence of an
association between benzene and non-Hodgkin lymphoma (NHL) could be found
when analyses were focused on results from highly exposed workers and were
appropriately adjusted for the healthy worker effect. In their analysis of
high exposure benzene studies, Swaen et al. implemented a series of
differences in the data used from the studies compared to our own. But
despite the fact that every single one of their major changes resulted in
a lowering of the summary relative risk, Swaen et al. also found a
statistically significant elevated relative risk in the high exposure
studies (RR = 1.33 (95% CI, 1.02-1.74)), just as we did. Even after they
adjusted for heterogeneity, the relative risk remained statistically
significant if correctly estimated. The one-sided p-value after this
adjustment can be estimated from their confidence interval to be 0.03.
Since our a priori hypothesis was that benzene increases, not decreases,
the risk of NHL, a one-tailed p-value is clearly most appropriate here.
The Swaen et al. use of the all-cancer standardized mortality ratio
(SMR) to adjust for the healthy worker effect assumes that benzene or any
of the other agents that the benzene-exposed workers are exposed to will
not cause any other cancer type. However, benzene is a well known cause of
leukemia and risks of this cancer were elevated in many of the studies
used in our meta-analyses. Relative risks of other cancers such as lung
cancer and mesothelioma were also elevated in some of the studies,
probably due to co-exposures like asbestos that can commonly occur with
benzene. Because of these increases in other cancers, the use of the all-
cancer SMR probably biased the Swaen et al. summary relative risks towards
the null. Without this bias, the Swaen et al. summary relative risks would
have been higher than they reported and even more similar to our results
than they already are. In any case, as we noted above, using different
data and different methods, Swaen et al. have produced additional evidence
that benzene increases the overall risk of non-Hodgkin lymphoma in the
available studies to date in a manner which is unlikely to be due to
chance.
References
1. Steinmaus C, Smith AH, Jones RM, Smith MT. Meta-analysis of benzene
exposure and non-Hodgkin lymphoma: biases could mask an important
association. Occup Environ Med 2008; 65:371-8.
2. Swaen GMH, Tsai SP, Burns C. Meta-analysis on benzene exposure and non
Hodgkin lymphoma (Letter to Editor). Occup Environ Med:TBD
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and does grant on behalf of all authors, an exclusive license (or non-
exclusive for government employees) on a worldwide basis to the BMJ
Publishing Group Ltd and its Licensees to permit this article to be
published in Occupational and Environmental Medicine editions and any
other BMJPGL products to exploit all subsidiary rights, as set out in our
license.
Meta-analysis on benzene exposure and non Hodgkin lymphoma
June 30 2009
Gerard M H Swaen1
Shan P. Tsai2
Carol Burns1
1 Department of Epidemiology, The Dow Chemical Company, Midland,
Michigan USA.
2 Shell Health, Shell Oil Company, Houston Texas, USA.
Corresponding Author: Gerard M H Swaen, The Dow Chemical Company,
P.O. Box 444, 4530 AK Terneuzen, The Netherlands 31-(0)43-3626042. E-
mail: gswaen@dow.com
Sir,
A recent meta-analysis on benzene exposure and non Hodgkin lymphoma (NHL)
concluded that the reviewed epidemiological studies provide “new evidence
that benzene causes NHL.” 1 The meta-analysis conducted by Steinmaus et al
differed from the others in several aspects. Firstly, it selected
subgroups with the highest putative exposure to avoid dilution. Secondly,
cohort studies were adjusted for the Healthy Worker Effect (HWE) by
considering the NHL deaths as cases and all other deaths as controls. A
HWE for cancer endpoints is small if any, compared to non cancer
endpoints.2. The results from a meta-analysis of 150 occupational cohort
studies suggest that HWE adjustment may artificially inflate the true RR
for cancer endpoints. 3 Thirdly, outdated cohort study results were used
instead of more recent updates. Fourthly, Steinmaus et al did not
consistently apply their own selection criteria.
We have re-analyzed the Steinmaus et al meta-analysis by precisely
applying their inclusion and exclusion criteria. These include selecting
the highest exposure category relative risk (RR), selecting cancer
incidence versus mortality data and we used the most recent results from
cohort updates whenever available. To maintain consistency, we adjusted
the RR estimates for the HWE by using the all cancer SMR of the selected
sub cohort instead of the all mortality SMR. Herein we present only a
summary table of results. Additional comparative tables are available
upon request.
There were 16 case-control studies included in the Steinmaus et al.
review. We excluded the study by Dryver since it provided no odds ratio
(OR) for benzene exclusively. For the Fabbro-Peray et al. study,
Steinmaus et al selected the OR of those with over 810 days of exposure.
However, we used the subcategory with exposure duration of over 15 years
since it represents the group with longer exposure. For the study by
Schnatter et al the OR for the highest intensity was 0 and Steinmaus et al
selected the OR for the second highest exposure intensity group. We
combined the highest and the second highest exposure intensity groups
(OR=0.49 95% CI: 0.10-2.32). The revised meta-OR for the 15 case-control
studies was 1.17 (95% CI 0.96 – 1.44) (see Table 1).
For the six non refinery cohort studies, we observed inconsistencies
in the authors’ use of the selection sequence. For the Bloemen study, the
longest duration RR was used by Steinmaus et al. although RRs by
cumulative exposure were given. We combined the two cumulative exposure
categories into one category of 28.3+ ppm-years (SMR=0.63 95% CI: 0.08-
2.28). For the Rinsky study, we selected the RR for men (1.00), assuming
that the men were higher exposed, since the jobs with benzene exposure
were generally done by men. Lastly, for Wong et al. the RR for highest
cumulative exposure was replaced with that for highest intensity exposure.
The revised meta-RR for these non-refinery studies was 1.13 (95% CI: 0.80-
1.61) and a meta-RR of 1.05 (95% CI: 0.75-1.47) after adjusting for the
HWE.
In the meta-analysis of the refinery studies, as per the
recommendations of Steinmaus et al., cancer incidence data were selected
if both incidence and mortality were reported. There were two refineries
included in the 1993 study published by Tsai, et al, and the combined
results were used instead of selecting only one of the refineries.
Additionally, we used the combined results from maintenance and process
workers for the study conducted at the Beaumont refinery by Wong since it
is unclear that process workers were more exposed. We selected results
based on the longer duration of work for the study by Pukkala et al,
following the Steinmaus et al. hierarchy. We used the updated data for
the following refinery studies (Sorahan, Thomas and Tsai et al, 1996) 4
5 6. In the update by Tsai and colleagues NHL was listed as one of the
specific disease categories, replacing reticulosarcoma used in the 1996
paper. We selected the updated RR although the longest duration of
employment was shorter. 7 The revised meta-RR for the 21 refinery studies
was 1.00 (95% CI: 0.89-1.12) and 1.06 (95% CI: 0.95-1.18) after adjusting
for the HWE. All the models gave similar results and we only present those
of the fixed model.
All of the meta-RRs calculated in the re-analysis were less than
those reported by Steinmaus et al and most were close to unity. The only
meta-RR that remained statistically significant was that for the high
exposure non refinery studies, consisting of four cohort studies and nine
case-control studies (meta-RR of 1.33, 95% CI: 1.02-1.74), for which
exposure was largely based on self-reported data. The statistical
significance of this meta-RR was lost after adjustment for the
heterogeneity effect (95% CI: 0.99-1.80).
The re-analysis shows that the differences of the applied analytical
methods and relative risks selected can vastly alter the overall meta-
relative risk. The re-analyzed evidence provides little if any support for
an association between benzene exposure and NHL.
Gerard M H Swaen1, Shan P. Tsai2 Carol Burns1. 1 Department of
Epidemiology, The Dow Chemical Company, Midland, Michigan USA.
2 Shell Health, Shell Oil Company, Houston Texas, USA.
Table 1 Summary results of the meta-analysis on benzene exposure and
NHL and for refinery workers and NHL, comparing the results by Steinmaus
et al to our findings (fixed models, other models gave similar results)).
N RR as in Steinmaus RR in the re-analysis
Benzene and NHL
All studies 22 1.22 (1.03-1.46) 1.16 (0.97-1.38)
Case control studies 16 1.23 (1.00-1.50) 1.17 (0.96-1.44)
All high exposure studies 13 1.49 (1.15-1.92) 1.33 (1.02-1.74)1
HWE adjusted cohort studies 6 1.22 (0.89-1.67 1.05 (0.75-1.47)
Refinery work and NHL
All studies 21 1.21 (1.06-1.38) 1.00 (0.89-1.12)
High exposure studies 14 1.30 (1.04-1.62) 1.07 (0.87-1.31)
HWE adjusted all studies 21 1.42 (1.25-1.62) 1.06 (0.95-1.18)
HWE adjusted high exposure studies 14 1.51 (1.22-1.88) 1.20 (0.99-
1.47)
1 statistical significance was lost after adjustment for heterogeneity
(95% CI: 0.99-1.80)
References
1. Steinmaus C, Smith AH, Jones RM, Smith MT. Meta-analysis of
benzene exposure and non-Hodgkin lymphoma: biases could mask an important
association. Occup Environ Med 2008;65(6):371-8.
2. Li CY, Sung FC. A review of the healthy worker effect in
occupational epidemiology. Occup Med (Lond) 1999;49(4):225-9.
3. Greenberg RS, Mandel JS, Pastides H, Britton NL, Rudenko L, Starr
TB. A meta-analysis of cohort studies describing mortality and cancer
incidence among chemical workers in the United States and western Europe.
Epidemiology 2001;12(6):727-40.
4. Sorahan T. Mortality of UK oil refinery and petroleum distribution
workers, 1951-2003. Occup Med (Lond) 2007;57(3):177-85.
5. Dement JM, Hensley L, Kieding S, Lipscomb H. Proportionate
mortality among union members employed at three Texas refineries. Am J Ind
Med 1998;33(4):327-40.>
6. Tsai SP, Ahmed FS, Wendt JK, Foster DE, Donnelly RP, Strawmyer TR.
A 56-year mortality follow-up of Texas petroleum refinery and chemical
employees, 1948-2003. J Occup Environ Med 2007;49(5):557-67.
7. Tsai SP, Chen VW, Fox EE, Wendt JK, Cheng Wu X, Foster DE, et al.
Cancer incidence among refinery and petrochemical employees in Louisiana,
1983-1999. Ann Epidemiol 2004;14(9):722-30.
Licence Statement:
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and does grant on behalf of all authors, an exclusive licence on a
worldwide basis to the BMJ Publishing Group Ltd to permit this article (if
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sublicences such use and exploit all subsidiary rights, as set out in our
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Mortality among British asbestos workers undergoing regular medical examinations (1971-2005). Occup Environ Med 2009; 66: 487-95.
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
Mortality among British asbestos workers undergoing regular medical examinations (1971-2005). Occup Environ Med 2009; 66: 487-95.
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
Anne-Helen Harding and coworkers1 presented mortality data from 98117 asbestos-exposed workers and increased mortality due to ischaemic heart disease (IHD), SMR 1.40 (95% CI 1.36-1.44). There are good arguments for further scrutinizing this observation.
Today it is rather established that inhalation of urban air pollutants are associated with increases in mortality and morbidity due to cardiovascular disease. This was observed in short-term, cohort and intervention studies and effects were seen at low concentrations.2
Whether inhalation of asbestos fibers can cause IHD is today an unsolved question. Some studies show a relationship between asbestos exposure and IHD.
A cohort of 3072 white male textile workers exposed to chrysotile was followed through 2001. An increased risk of ischemic heart disease was observed (SMR 1.20, 95%CI 1.10 – 1.32).3
A cohort of about 11000 men employed in the chrysotile mines and mills of Quebec was followed until 1988. IHD was more common among those exposed to 300 or more million particles per cubic foot x years (SMR 1.24) compared with those exposed to less than 30 (SMR 0.92).4
Non-smoking patients with asbestosis were compared with healthy controls. The asbestosis patients had significantly increased serum levels of inflammatory markers.5 During the last decade these markers of inflammation have emerged as risk factors for IHD. A general hypothesis about exposure to inhaled air pollutants and the occurrence of IHD can be expressed in the following way. Inhalation of particles will create a low grade inflammation associated with an increase in plasma fibrinogen and other blood clotting agents. A higher concentration of these agents will increase the likelihood for blood clotting and thereby the risk for myocardial infarction and IHD. 2
I hope these arguments will encourage Harding and coworkers to further explore the relationship between asbestos exposure and the occurrence of IHD in internal analysis.
Literature
1. Harding A-H, Darnton A, Wegerdt J, McElvenny D. Mortality among British asbestos workers undergoing regular medical examinations (1971-2005). Occup Environ Med 2009; 66: 487-95.
2. Sjögren B. Occupational exposure to air pollutants, inflammation and ischemic heart disease, Editorial. Scand J Work Environ Health 2004;30:421-423.
3. Hein MJ, Stayner LT, Lehman E, Dement JM. Follow-up study of chrysotile textile workers: cohort mortality and exposure-response. Occup Environ Med 2007; 64: 616-625.
4. McDonald JC, Liddell FDK, Dufresne A, McDonald AC. The 1891-1920 birth cohort of Quebec chrysotile miners and millers: mortality 1976-88. Br J Ind Med 1993;50:1073-1081.
5. Lehtonen H, Oksa P, Lehtimäki L, et al. Increased alveolar nitric oxide concentration and high levels of leukotriene B4 and 8-isoprostane in exhaled breath condensate in patients with asbestosis. Thorax 2007; 62: 602-607.
Pere Sanz-Gallén, Santiago Nogué, Eva Muñoz and Francisco Sabater*
Clinical Toxicology Unit and *Otorhinolaryngology Service. Hospital Clínic. Barcelona
Sir,
The case-control study by D' Errico et al (1) on occupational risk factors for sinonasal cancer concludes that exposure to arsenic is one such factor and suggests more cases should be reported, as there...
Pere Sanz-Gallén, Santiago Nogué, Eva Muñoz and Francisco Sabater*
Clinical Toxicology Unit and *Otorhinolaryngology Service. Hospital Clínic. Barcelona
Sir,
The case-control study by D' Errico et al (1) on occupational risk factors for sinonasal cancer concludes that exposure to arsenic is one such factor and suggests more cases should be reported, as there are only two studies at present (2,3). We contribute a new case of a worker in the glassware industry, in order to reinforce the relationship between sinonasal cancer and occupational exposure to arsenic.
A middle-aged, non-smoking patient was diagnosed more than a decade previously with squamous cell carcinoma affecting the left maxilla. The initial computed tomography (CT) scan had shown a lesion occupying the space of the left maxillary sinus that had destroyed the bone structure of the left maxilla and invaded the soft facial tissue and the pterygopalatine fossa. A CT scan more than a decade later after surgery and radiotherapy shows changes in the nasal fossa and left maxillary sinus, with a fibrotic mass of scar tissue.
The patient worked in the glassware industry for over twenty years. The main materials forming the mix introduced in the glass furnace were silica, sodium carbonate, potassium carbonate, zinc oxide and lead oxide. The dyes, which represented 0.1% of the mixture, included cadmium sulphide and oxides of cobalt, copper, chromium, manganese and nickel. One per cent of arsenic trioxide was added to the mixture to increase the transparency of the glass. An onsite workplace study showed environmental levels of chromium and nickel <3 µg/m3, but levels of arsenic of 85 µg/m3 (Threshold Limit Value: 10 µg/m3).
Although chromium and nickel oxides, known sinonasal carcinogens, are used in the glassware industry, the environmental levels found were very low. However, the levels of arsenic were very high, in agreement with the study by Battista et al in various glassware companies (3). Therefore, arsenic trioxide should be replaced by other metals and preventive measures should be introduced to minimize the health risks of workers exposed to these substances in the workplace.
References
1. d'Errico A, Pasian S, Baratti A, Zanelli R, Alfonzo S, Gilardi L et al. A case-control study on occupational risk factors for sino-nasal cancer. Occup Environ Med. Publish Ahead of Print, January 19, 2009
2. Roth F. Uber den bronchialkrebs arsengeschadigter winzer. Virchows Arch Pathol Anat 1958;331: 119-137.
3. Battista G, Bartoli D, Iaia TE, Dini F, Fiumalbi C, Ciglioli S et al. Art glassware and sinonasal cancer: report of three cases. Am J Ind Med 1996; 30: 31-35.
Dear Editor,
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Authors Craig Steinmaus1, 2 Allan H Smith1 Martyn T Smith1
Authors affiliations 1. School of Public Health, University of California, Berkeley, University Hall, Berkeley, CA 94720-7360, USA 2. Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, 1515 Clay St., Oakland, CA 94612
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1 Department of Epidemiology, The Dow Chemical Company, Midland, Michigan USA. 2 Shell Health, Shell Oil Company, Houston Texas, USA.
Corresponding Author: Gerard M H Swaen, The Dow Chemical Company, P.O. Box 444, 4530 AK Terneuzen, The Netherlands 31-(0)43-3626042. E-...
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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
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Sir,
The case-control study by D' Errico et al (1) on occupational risk factors for sinonasal cancer concludes that exposure to arsenic is one such factor and suggests more cases should be reported, as there...
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