Kumagai and his colleges [1] have reported that incinerator workers
employed at intermittently burning incineration plants were not
necessarily exposed to high concentrations of polychlorinated dibenzo-p-
dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). The authors
conclusions were based on concentrations of PCDDs and PCDFs in serum
samples of the workers.
I have deep concerns regarding the st...
Kumagai and his colleges [1] have reported that incinerator workers
employed at intermittently burning incineration plants were not
necessarily exposed to high concentrations of polychlorinated dibenzo-p-
dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). The authors
conclusions were based on concentrations of PCDDs and PCDFs in serum
samples of the workers.
I have deep concerns regarding the study methodology and results which do
not consider the accumulation of PCDDs and PCDFs in the adipose tissue.
PCDDs and PCDFs are organochlorines with different degrees and positions
of chlorination, which determine their persistence and toxicity. They are
lipophilic and difficult to metabolise, and any environmental exposure of
living organisms to them results in their accumulation and persistence in
fat tissues.[2]
Meanwhile, it is feasible to use blood sera to obtain and analyse PCDDs
and PCDFs. Adipose tissue organochlorines levels have been regarded as a
preferred indicator of human exposure. Levels in adipose tissue are known
to be higher and more representative of the cumulative internal exposure.
[2,3]
Previously, Archibeque-Engle et al.[4] did not find significant
relationship between serum concentrations and tissue residues for
organochlorines compounds. Based on the lack of correlation between
adipose tissue and serum, as well as an absence of some compound residues
in serum, the authors emphasized that adipose tissue should be analysed in
addition to serum.
Finally, I would like to acknowledge the authors for such original subject
study, which enable us to raise the profile of and discuss new hypotheses
in environmental and occupational health.
References
(1) Kumagai S, Koda S, Miyakita T, Ueno M. Polychlorinated dibenzo-p-dioxin
and dibenzofuran concentrations in serum samples of workers at
intermittently burning municipal waste incinerators in Japan. Occup
Environ Med 2002;59(6):362-8.
(2) Angulo R, Martinez P, Jodral ML. PCB Congeners transferred by human
milk, with an estimate of their daily intake. Food and Chemical Toxicology
1999;37:11081-8.
(3) Lopez-Carrillo L, Torres-Sanchez L, Lopez-Cervantes M, Blair A, Cebrian
ME, Uribe M. The adipose tissue to serum dichlorodiphenyldichloroethane
(DDE) ratio: some methodological considerations. Environ Res
1999;81(2):142-5.
(4) Archibeque-Engle SL, Tessari JD, Winn DT, Keefe TJ, Nett TM, Zheng T.
Comparison of organochlorine pesticide and polychlorinated biphenyl
residues in human breast adipose tissue and serum. J Toxicol Environ
Health 1997;52(4):285-93.
We thank Drs Schwartz and Seeber, as well as their colleagues, for the commentaries on our paper “Neurobehavioral Testing in Workers Occupationally Exposed to Lead: Systematic Reviewand Meta-Analysis of Publications”[1] and would like to respond to their criticisms.
Response to specific points made by Schwartz et al.:
(i) “No evaluation of the quality of the evidence from available stu...
We thank Drs Schwartz and Seeber, as well as their colleagues, for the commentaries on our paper “Neurobehavioral Testing in Workers Occupationally Exposed to Lead: Systematic Reviewand Meta-Analysis of Publications”[1] and would like to respond to their criticisms.
Response to specific points made by Schwartz et al.:
(i) “No evaluation of the quality of the evidence from available studies based on study design and analytic method.” Our article first reviews the individual studies to assess their quality,
summarises findings in Table 1 and only then presents the results of a meta-analysis. In our methods section, we specifically discuss the criteria for assessing the quality of the individual studies. These included: a) evaluation of pre-exposure status; b) adjustment for age; c) adjustment for other occupational exposures; d) adjustment for alcohol use; e) adjustment for socio-economic confounding factors such as income level, education, etc.; and f) use of blinding procedures.
(ii) “Data were combined from poorly done studies with data from welldone studies.” Table 1 clearly shows that no study satisfied all of the above criteria
for quality. As Schwartz et al. did not provide criteria to distinguish a “poorly done” from a “well done” study, we re-analysed the data based on five studies that adjusted results for age, education, and alcohol use
and, therefore, in our opinion can be considered relatively well-designed. These five studies (Baker et al.,[2] Campara et al.,[3] Chia et al.,[4] Maizlish et al.,[5] and Williamson and Teo[6]) contained sufficient information to conduct a meta-analysis for only three tests: Santa Ana preferred hand, Santa Ana non-preferred hand, and Digit Symbol. The results were as follows:
For the Santa Ana preferred hand test, the effect size changed from non-significant negative to non-significant positive.
For the Santa Ana
non-preferred hand the result changed slightly towards the null and remained statistically non-significant. For the Digit Symbol test, the result changed away from the null and remained statistically significant in the fixed effects model, but changed slightly towards the null and was
no longer statistically significant in the two random effects models. (See table)
(iii) “Inclusion of studies that did not control for age and education.” Although adjustment for age and education is undoubtedly
important, Schwartz et al. do not provide evidence that these are “the two most important predictors.” One could certainly argue that alcohol use, or the presence of pre-existing neuropsychiatric conditions would also act
as powerful confounders. Our review indicated that the 22 studies had non-overlapping strengths and limitations and further inclusion or exclusion based on quality appeared to be a matter of judgment. Nevertheless, we accepted the Schwartz et al. argument and re-analysed the data based on the 13 studies that adjusted for age and education. The results indicated that, as opposed to our original findings (based on all 22 studies), none of the tests showed a statistically significant difference in all three models. (See table)
(iv) “No adjustment for age, education, or lead dose differences across studies.”
This criticism appears to be somewhat theoretical, as the data did not allow such adjustment. Inclusion of only those studies that adjusted for age and education in part addresses this issue with no apparent impact on the overall conclusions.
(v) “Reliance on exposed v. control comparisons” rather than “only including studies that reported beta coefficients for the blood lead v.
test score relation, or adjusting for mean blood lead levels in exposed and non-exposed groups.” As noted in the abstract and in the methods section, we defined low to
moderately exposed populations as those whose central tendency for blood lead concentration was less than 70mg/dl. We used the same definition of exposure as the previously published meta-analysis by Meyer-Baron and Seeber[7] to find out if the results of our two studies were reproducible.The direct comparison of the two analyses in the discussion section was important in explaining our position with regards to meta-analysis as a research technique. We do agree that other approaches such as those proposed by Schwartz and colleagues could be informative. We were
surprised to read the following statement: “The authors conclude that blood lead levels, that are described as “moderate” in one location in the manuscript and “low” in another, are not associated with neurobehavioral test scores.” We believe this statement misrepresents our conclusions listed on page 222.[1]
(vi) “Reliance on a small number of unspecified studies for effect estimates. Table 2 of the study reports the number of studies that were combined to derive effect estimates, but does not specify which studies were combined.” The originally submitted version of the article included tables with information on each individual study. However, following the reviewers’ comments, and at the request of the editor, we had to shorten the manuscript substantially. We will make this information available upon
request.
With respect to the omission from our meta-analysis of the recent article by Schwartz et al.,[8] we have to point out that our manuscript
was submitted for publication in December 2000, while the Schwartz et al. study appeared in press in May 2001. The other two studies cited in their letter did not meet our inclusion criteria.
We have not had an opportunity to evaluate the association between cumulative exposure to lead and neurobehavioral testing results. However,
we did note that the 2001 article by Schwartz et al.,8 found no association
between tibia lead levels and test scores.
Response to Seeber: Although Dr Seeber agrees with our conclusion about the need for prospective studies he states that “the repeated information on cross-sectional studies should also be accepted as source for conclusions on (neurobehavioral) effects due to exposures” and that meta-analyses are one approach to search such summarizing information.”
After having reviewed the results of five meta-analyses on the subject (two presented in the recent Seeber and Meyer Baron article,[9] our paper,[1] and the two additional re-analyses presented here) we found five different sets of results with no evidence of consistency to qualify these results as “repeated”. Therefore, we have to adhere to our original conclusions.
References
(1) Goodman M, LaVerda N, Clarke C, Foster ED, Iannuzzi J, Mandel J. Neurobehavioural testing in workers occupationally exposed to lead: systematic review and meta-analysis of publications. Occup Env Med
2002;59:217-23.
(2) Baker EL, Feldman RG, White RA, Harley JP, Niles CA, Dinse GE, Berkey CS. Occupational lead neurotoxicity: a behavioral and electrophysiological evaluation. Study design and year one results. Br J
Ind Med 1984;41:352-61.
(3) Campara P, D’Andrea F, Micciolo R, Savonitto C, Tansella M, Zimmerman-Tansella C. Psychological performance of workers with blood-lead concentration below the current threshold limit value. Int Arch Occup Environ Health 1984;53:233-46.
(4) Chia S-E, Chia H-P, Ong C-N, Jeyaratnam J. Cumulative blood lead levels and neurobehavioral test performance. Neurotoxicology 1997;18:793-804.
(5) Maizlish N, Parra G, Feo O. Neurobehavioral evaluation of Venezuelan workers exposed to inorganic lead. Occup Environ Med 1995;52:408-14.
(6) Williamson A, Teo R. Neurobehavioral effects of occupational exposure to lead. Br J Ind Med 1986;43:374-80.
(7) Meyer-Baron M, Seeber A. A meta-analysis for neurobehavioral results due to occupational lead exposure with blood lead concentrations
<70 µg/ml. Arch Toxicol 2000;73:510-8.
(8) Schwartz BS, Lee BK, Lee GS, Stewart WF, Lee SS, Hwang KY, Ahn KD, Kim YB, Bolla KI, Simon D, Parsons PJ, Todd AC. Associations of blood lead, dimercaptosuccinic acid-chelatable lead, and tibia lead with neurobehavioral test scores in South Korean lead workers. Am J Epidemiol 2001 Mar 1;153(5):453-64.
(9) Seeber A, Meyer-Baron M, Schäper M. A summary of two meta-
analyses on neurobehavioural effects due to lead exposure. Arch Toxicol2002;76:137-45.
Meta-analysis results using two alternative inclusion criteria:(1) five studies that adjusted for age, educational level, and alcohol consumption (age, ed, alc); (2) 13 studies that adjusted for age and educational level (age, ed)
Meta-analysis results using two alternative inclusion criteria:(1) five studies that adjusted for age, educational level, and alcohol consumption (age, ed, alc); (2) 13 studies that adjusted for age and educational level (age, ed)
Test
Fixed-effects
Weighted random-effects
Unweighted random effects
K
Effect size
95% CI
K0
Effect size
95% CI
Effect size
95% CI
Santa Ana Preferred – age, ed, alc
4
0.074
-0.134
0.282
0.103
-0.235
0.441
0.102
-0.227
0.431
Santa Ana Preferred - age, ed
7
-0.060
-0.226
0.106
-0.058
-0.304
0.188
-0.058
-0.306
0.190
Santa Ana Non-Preferred Hand – age, ed, alc
4
-0.096
-0.304
0.112
--
--
--
--
--
--
Santa Ana Non-Preferred Hand – age, ed
5
-0.066
-0.257
0.125
--
--
--
--
--
--
Santa Ana Both Hands – age, ed
4
0.117
-0.119
0.352
0.121
-0.188
0.430
0.121
-0.182
0.423
Block Design Test – age, ed
8
-0.081
-0.228
0.067
-0.155
-0.378
0.068
-0.134
-0.326
0.059
Digit Symbol – age, ed, alc
6
-0.319
-0.530
-0.108
7
-0.315
-0.847
0.218
-0.314
-0.823
0.195
Digit Symbol – age, ed
9
-0.041
-0.178
0.096
-0.240
-0.631
0.152
-0.236
-0.598
0.126
D2-Speed – age, ed
4
0.169
-0.101
0.438
0.178
-0.114
0.469
0.175
-0.110
0.460
Similarities – age, ed
6
-0.088
-0.247
0.071
-0.174
-0.464
0.116
-0.181
-0.493
0.130
Benton Visual Retention – age, ed
3
-0.042
-0.244
0.159
--
--
--
-0.037
-0.293
0.218
Paired Associates – age, ed*
5
-0.156
-0.295
-0.017
4
-0.233
-0.665
0.199
-0.233
-0.696
0.231
Paired Associates– age, ed
8
-0.219
-0.412
-0.026
3
-0.238
-0.667
0.192
-0.237
-0.659
0.184
Visual Reproduction – age, ed*
4
-0.158
-0.312
-0.003
2
--
--
--
--
--
--
Visual Reproduction – age, ed
11
-0.210
-0.367
-0.052
9
--
--
--
--
--
--
Digit Span Forward – age, ed
4
-0.033
-0.237
0.172
--
--
--
--
--
--
Digit Span Score – age, ed
5
-0.040
-0.221
0.141
-0.207
-0.602
0.188
-0.238
-0.712
0.236
Simple reaction time Preferred Hand – age, ed
10
-0.148
-0.250
-0.046
-0.036
-0.261
0.189
-0.052
-0.240
0.135
Simple reaction time Preferred Hand – age, ed*
5
0.141
-0.040
0.323
0.134
-0.105
0.373
0.136
-0.079
0.350
Picture Completion – age, ed
4
-0.129
-0.308
0.049
-0.275
-0.701
0.151
-0.295
-0.823
0.232
Grooved Pegboard Dominant – age, ed
3
0.245
0.073
0.417
2
0.217
-0.304
0.738
0.209
-0.435
0.854
Results were adjusted for the lowest reliability coefficient reported in the literature; otherwise reliability coefficients were set equal to 1.0 * = Results for multiple strata within one study were combined; otherwise all strata entered separately. -- = Random-effect model reduced to a fixed effect model. Bold print indicates statistically significant results. K = Number of studies (strata). K0 = Fail-safe N.
NOTE: Table for Re: Critique of Goodman et al.: lead and neurobehavioral test scores in adults by Michael Goodman et al.
Access E-letter
Whether or not low-to-modest levels of exposure to lead have a
detrimental effect on cognition is an important issue given the growing
attention, for example, in the United States, that has recently been paid
towards potentially revising downward the levels of lead exposure allowed
in the workplace. Thus, we read with interest the meta-analysis of
studies on this topic that appeared in this journal by...
Whether or not low-to-modest levels of exposure to lead have a
detrimental effect on cognition is an important issue given the growing
attention, for example, in the United States, that has recently been paid
towards potentially revising downward the levels of lead exposure allowed
in the workplace. Thus, we read with interest the meta-analysis of
studies on this topic that appeared in this journal by Goodman et al. [1]
Unfortunately, we believe that the authors’ conclusions are not valid. Specifically, the authors state that
“the data available to date are inconsistent and are unable to provide
adequate information on the neurobehavioral effects of exposure to
moderate blood concentrations of lead.” We found no direct support for
this conclusion in the publication. Moreover, numerous flaws in their
method limit any specific inferences that can be made. In general, we
found that the meta-analysis combined evidence from studies of widely
varying quality and did not account for significant confounding within and
between studies. Given these and other flaws, it was predictable that the
authors did not find an association between blood lead levels and
neurobehavioral test scores.
Specific concerns that we had with the methods include:
(i) The
authors offer no evaluation of the quality of the evidence from available
studies based on study design and analytic method.
(ii) The authors combine
data from poorly done studies with data from well done studies, clouding
any effects that is observable from the better conducted studies.
(iii)
Although age and education adjustment within studies is assessed, six
studies were included that did not adjust for age and another three
studies did not adjust for education. These are the two most well
established predictors of neurobehavioral test scores and the most
important potentially confounding variables.
(iv) Even among the remaining
studies that did adjust for age and education, the authors do not address
the confounding in the meta-analysis that is caused by variation in age
and education across study populations.
(v) The authors’ main effect
measure is an exposed v. control comparison. Among the options that could
have been pursued, this is the effect measure with the lowest power. It
is unable to assess a dose-effect relation, and it is also the one most
prone to selection bias.
(vi) Relatively few of the 22 studies listed in
Table 2 contribute to the estimate of the effect size for each
neurobehavioral outcome. Moreover, the authors do not state which studies
contributed to the effect estimate.
It is important to note that several recent studies, all published
before this article was accepted for publication, reported that blood lead
was associated with neurobehavioral test scores in multiple cognitive
domains. One study of 803 Korean lead workers is the largest study
reported to date and observed consistent associations of blood lead with
test scores in the domains of executive abilities, manual dexterity, and
peripheral motor strength at blood lead levels as low as 18 µg/dL. [2] In another study
of former organolead manufacturing workers, tibia lead was associated with
test scores at cross-section [3] and with longitudinal declines in test scores.[4] These findings suggest that lead may have
both short-term and progressive influences on neurobehavioral performance.
We elaborate on our main concerns, below.
(i) No evaluation of the quality of the evidence available from
studies, and (ii) data were combined from poorly done studies with data from
well done studies. It is traditional in meta-analysis to establish a
priori criteria for what defines acceptable evidence from studies. The
authors only had three inclusion criteria, none of which refer to the
quality of the study designs, analytic method, adjustment for confounding,
evaluation of bias in selection of exposed and non-exposed subjects, and
other such methodologic factors. There is apparently no consideration for
this arguably single most important step in meta-analysis. The meta-analytic results could simply reflect wide heterogeneity in the quality of
the evidence that was combined. This factor alone could account for the
overall conclusion of no association.
(iii) Inclusion of studies that did not control for age and education.
Age and education are the two most important predictors of neurobehavioral
test scores in working populations. In the absence of adjustment for
these confounders there should be convincing evidence that the two groups
being compared were equivalent in age and education. Eight of the
included studies did not adjust for age and/or education. The authors
offer no explanation for why these studies should be included in the meta-
analysis.
(iv) No adjustment for age, education, or lead dose differences across
studies. By not adjusting for age and education differences across
studies, the authors make an implicit assumption that age and education do
not modify the relation between blood lead and neurobehavioral test
scores. This may or may not be true. In the meta-analysis, the authors
also implicitly assume a fixed difference in blood lead levels between
exposed and non-exposed groups. Table 1 clearly indicates that this
assumption does not hold.
(v) Reliance on exposed v. control comparisons. This is a weak test
and a test that is not germane to the conclusions that the authors make.
The authors conclude that blood lead levels, that are described as
“moderate” in one location in the manuscript and “low” in another, are not
associated with neurobehavioral test scores. All studies included exposed
workers with a range of blood lead levels, from very low to high. More
appropriate approaches could have been considered, for example, only
including studies that reported beta coefficients for the blood lead v.
test score relation, or adjusting for mean blood lead levels in exposed
and non-exposed groups.
(vi) Reliance on a small number of unspecified studies for effect
estimates. Table 2 of the study reports the number of studies that were
combined to derive effect estimates, but does not specify which studies
were combined. This omission does not allow the reader to determine
whether solid evidence was combined with more questionable evidence, or to
evaluate whether any of the issues described above were germane to the
effect estimates reported.
Two more concerns exist regarding the author’s treatment of the issue
of cumulative v. on-going lead exposure as well as the identification of
the source of funding for this study. In their introduction, the authors
quote the review by Balbus-Kornfeld et al. [5] which noted that “the current
scientific evidence is flawed because of inadequate estimation of
cumulative exposure to or absorption of lead…” but fail to acknowledge
this issue in the interpretation of their own meta-analysis. In fact, as
has been widely reported in the literature, methods are now available to
non-invasively measure bone lead levels as a reliable and accurate measure
of cumulative lead dose. Several studies (such as Payton et al.[6], Stewart et al.[3], and Schwartz et
al.[4]) suggest that cumulative lead exposure is a very important
biological marker that may be related to cognitive decrements not
predicted by blood lead levels. With regards to funding, the authors note
that they are mainly from Exponent Health Group in Alexandria, Virginia
and Menlo Park, California; however, they fail to describe what motivated
the study or sources of funding for the study. We believe this
information would be of interest to scientists and policy-makers engaged
in work on this topic.
References
(1) M Goodman, N LaVerda, C Clarke, E D Foster, J Iannuzzi, J Mandel. Neurobehavioural testing in workers occupationally exposed to lead: systematic review and meta-analysis of publications. Occup Environ Med 2002;59: 217-23.
(2) Schwartz BS, Lee BK, Lee GS, Stewart WF, Lee SS, Hwang KY, Ahn KD, Kim YB, Bolla KI, Simon D, Parsons PJ, Todd AC. Associations of blood lead, dimercaptosuccinic acid-chelatable lead, and tibia lead with neurobehavioral test scores in South Korean lead workers. Am J Epidemiol 2001;153:453-64.
(3) Stewart WF, Schwartz BS, Simon D, Bolla KI, Todd AC, Links J. Neurobehavioral function and tibial and chelatable lead levels in 543 former organolead workers. Neurology 1999;52:1610-7.
(4) Schwartz BS, Stewart WF, Bolla KI, Simon PD, Bandeen-Roche K, Gordon PB, Links JM, Todd AC. Past adult lead exposure is associated with longitudinal decline in cognitive function. Neurology2000;55:1144-50.
(5) Balbus-Kornfeld JM, Stewart W, Bolla KI, et al. Cumulative exposure to inorganic lead and neurobehavioral test performance in adults: an epidemiological review. Occup Environ Med 1995;52:2–12.
(6) Payton M, Riggs KM, Spiro A 3rd, Weiss ST, Hu H. Relations of bone and blood lead to cognitive function: the VA Normative Aging Study. Neurotoxicol Teratol 1998 Jan-Feb;20(1):19-27
Brian S. Schwartz, MD, MS
Professor and Director
Division of Occupational and Environmental Health
Johns Hopkins Bloomberg School of Public Health
Walter Stewart, PhD, MPH
Adjunct Professor
Department of Epidemiology
Johns Hopkins Bloomberg School of Public Health
Howard Hu, MD, ScD, MPH, MS
Associate Professor and Director
Occupational/Environmental Medicine
Department of Environmental Health
Harvard School of Public Health
The article of Dr Goodman and co-workers on "Neurobehavioral testing
in workers occupationally exposed to lead…." [1] covers an interesting
approach with a surprising main message: "None of the individual studies
is conclusive or adequate in providing information on the subclinical
neurobehavioral effects …". Such sentence astonishes a reader since the
studies used were selected from established journals...
The article of Dr Goodman and co-workers on "Neurobehavioral testing
in workers occupationally exposed to lead…." [1] covers an interesting
approach with a surprising main message: "None of the individual studies
is conclusive or adequate in providing information on the subclinical
neurobehavioral effects …". Such sentence astonishes a reader since the
studies used were selected from established journals.
A long section of the discussion deals with an article of Meyer-Baron
and Seeber,[2] the beforehand published meta-analysis on the topic. We
agree that prospective studies are the best basis to receive a stable
knowledge about exposure effects, also in neurobehavioural studies.
However, the repeated information on cross sectional studies should also
be accepted as source for conclusions on (neurobehavioral) effects due to
exposures. Meta-analyses are one approach to search such summarizing
information.
Taking into account that the extended study selection in the article
of Goodman et al. may lead to different results we do not agree with
several arguments. For example, they refer to the bias problem, the
exposure range, the interpretation in terms of age-related changes, and
the results for the Digit Symbol test. On these problems an exchange of
opinions has been published in Archives of Toxicology.[3, 4] Without
making reference to this discussion, several arguments and conclusions
were presented again. They are identical with the main conclusions in an
anonymous "expert opinion" for the German Battery Association. [5]
From our point of view it makes no sense to repeat the same details
of argumentation for a second time. However, we believe that the readers
of your journal should be informed that conclusions of the article of
Goodman et al. have been discussed at other places. In the meantime an
additional article on the subject has been published.[6] In this article
the data of the original "expert opinion" – the basis of the article in
Occupational and Environmental Medicine – and the data of our first meta-analysis were
comparatively evaluated. We hope that the critical readers of your journal
pick up the full information on the matter. Thereupon they may draw their
own conclusions regarding meta-analyses of neurobehavioral effects due to
occupational exposure to inorganic lead.
References
(1) M Goodman, N LaVerda, C Clarke, E D Foster, J Iannuzzi, J Mandel. Neurobehavioural testing in workers occupationally exposed to lead:
systematic review and meta-analysis of publications. Occup Env Med 2002;59:217-23.
(2) Meyer-Baron M, Seeber A. A meta-analysis for neurobehavioural
results due to occupational lead exposure with blood lead concentrations <_70 xb5g="xb5g" _100="_100" ml.="ml." i="i"/>Arch Toxicol 2001;73:510-8.
(3) Meyer-Baron M, Seeber A. Letter to the editor. Arch Toxicol 2001;75:441-2.
(4) Goodman M, LaVerda N, Mandel J. Letter to the editor. Arch
Toxicol 2001;75:439-40.
(5) Exponent (September 2000): Neurobehavioral testing in workers
occupationally exposed to lead: systematic review and meta-analysis of the
published literature. Prepared for German Battery Association, central
association of electrical engineering and electronics industry. Doc.
No:SF29294.000 A0F00900. Menlo Park: Exponent.
(6) Seeber A, Meyer-Baron M, Schäper M. A summary of two meta-
analyses on neurobehavioural effects due to lead exposure. Arch Toxicol 2002;76:137-45.
We appreciate dr Wijngaarden´s interest in our report and his
suggestion for understanding the differences in risk. Dr Wijngaarden
suggests that difference in unemployment rate between electricians and
glassworker and wood workers could be an explanation.
We have no data on employment status at time of death and can
therefore not test this hypothesis. However, if employment status is an...
We appreciate dr Wijngaarden´s interest in our report and his
suggestion for understanding the differences in risk. Dr Wijngaarden
suggests that difference in unemployment rate between electricians and
glassworker and wood workers could be an explanation.
We have no data on employment status at time of death and can
therefore not test this hypothesis. However, if employment status is an
important predictor, this could explain some of the difference as the wood
workers had a different employment than the other groups. Electricians and
glass workers have had permanent positions since a long time, while wood
workers had an employment for a certain object, e.g. a house before 1990s.
When the object was finished he had to find another employer. Today, most
construction workers have permanent positions in Sweden.
In our search of literature to understand differences in suicide
rates between occupations we found little knowledge. This might be an
important area of research in the future.
We read the report by Hollund et al[1] with great interest. We agree
that there is limited information about the prevalence of airway symptoms
caused by highly reactive chemicals in hairdressing salons. In this well designed study, authors focused on age as a risk factor and observed an
increased prevalence of respiratory symptoms among the oldest and youngest
hairdressers and observed more symptoms among...
We read the report by Hollund et al[1] with great interest. We agree
that there is limited information about the prevalence of airway symptoms
caused by highly reactive chemicals in hairdressing salons. In this well designed study, authors focused on age as a risk factor and observed an
increased prevalence of respiratory symptoms among the oldest and youngest
hairdressers and observed more symptoms among hairdressers over 40 years
of age.
Work intensity, work duration, working conditions, and job titles
(master, and fellow hairdresser) should also be considered as risk factors
for occupational asthma and respiratory symptoms. With the exception of
work intensity, these features have been reported as risk factors in
previous studies [2-4]. Work intensity is an objective parameter for
evaluating occupational exposures. In our study, we calculated work
intensity from the average number of chemical applications (bleaching,
dye, and permanent wave)per week and observed a 3.6 times higher risk of
occupational asthma among hairdressers with high work intensity (95% CI =
1.2-10.9) with a significant trend (X² for trend: 4.9, p: 0.027)[5].
However, we did not observe any excess by work duration, which probably is
a result of the healthy-worker effect. Hollund et al. stated that the
older hairdressers had more customers than the younger ones, which may be
an evidence of higher occupational exposures. If they had used work
intensity as more objective criteria than age, they might have prevented
possible misclassifications by age.
Working conditions of hairdressers and exposures depend on country
and regional variability, which might also affect study results. In the
United States and United Kingdom, the term “hairdressers” is inclusive,
denoting women’s hairdressers and barbers for man [6]. In Turkey however,
the term addresses women’s hair salons only. Most of the studies on
hairdressers have been published from Nordic and industrialized countries
[7-11]. Studies from developing countries will help to describe the extent
of occupational health problems among hairdressers and to identify
etiologic factors.
References
(1) Hollund BE, Moen BE, Lygre SH et al. Prevalence of airway
symptoms among hairdressers in Bergen, Norway. Occup Environ Med 2001;
58:780-785.
(2) Blainey AD, Ollier S, Cundell D et al. Occupational asthma in a
hairdressing salon. Thorax 1986; 41:42-50.
(3) Parra FM, Igea JM, Quirce S et al. Occupational asthma in a
hairdresser caused by persulphate salts. Allergy 1992; 47:656-660.
(4) Schwaiblmair M, Vogelmeier C, Fruhmann G. Occupational asthma in
hairdressers: results of inhalation tests with bleaching powder. Int Arch
Occup Environ Health 1997; 70:419-423.
(5) Akpinar-Elci M, Cimrin AH, Elci OC. Prevalence and risk factors of
occupational asthma among hairdressers in Turkey. J Occup Environ Med
2002; (accepted for publication).
(6) Occupational exposures of hairdressers and barbers and personal use
of hair colorants; some hair dyes, cosmetic colorants, industrial
dyestuffs and aromatic amines. IARC monographs on evaluation of
carcinogenic risks to human 1993; 57:43-66.
(7) Leino T, Tammilehto L, Luukkonen R et al. Self-reported respiratory
symptoms and diseases among hairdressers. Occup Environ Med 1997; 54:452-
455.
(8) Leino T, Tammilehto L, Paakkulainen H et al. Occurrence of asthma and
chronic bronchitis among female hairdressers. A questionnaire study. J
Occup Environ Med 1997; 39:534-539.
(9) Leino T, Tammilehto L, Hytonen M et al. Occupational skin and
respiratory diseases among hairdressers. Scand J Work Environ Health 1998;
24:398-406.
(10) Leino T, Tuomi K, Paakkulainen H et al. Health reasons for leaving
the profession as determined among Finnish hairdressers in 1980-1995. Int
Arch Occup Environ Health 1999; 72:56-59.
(11) Hollund BE, Moen BE. Chemical exposure in hairdresser salons: effect
of local exhaust ventilation. Ann Occup Hyg 1998; 42:277-282.
Järvholm and Stenberg [1] evaluated suicide mortality rates among
electricians ("exposed to electromagnetic fields (EMFs)") and glass and
woodworkers ("unexposed to EMFs") in the Swedish construction industry.
Standard mortality rates were lower for the two job groups as compared to
the Swedish general population. This is likely due to the healthy worker
effect. The internal cohort analysis showed...
Järvholm and Stenberg [1] evaluated suicide mortality rates among
electricians ("exposed to electromagnetic fields (EMFs)") and glass and
woodworkers ("unexposed to EMFs") in the Swedish construction industry.
Standard mortality rates were lower for the two job groups as compared to
the Swedish general population. This is likely due to the healthy worker
effect. The internal cohort analysis showed that electricians had a lower
suicide mortality rate than glass and woodworkers.
As the authors rightfully point out, these results should not be seen
as evidence against the association between exposure to EMFs and suicide,
in particular because no quantitative estimates of exposure were obtained
to directly evaluate this association. Jarvholm and Stenberg cited a small
measurement survey in the Swedish construction industry, which indicated
that exposure levels were low and comparable between the two occupational
groups. Therefore, one would not expect to see an EMF-mediated increase in
suicide risk among electricians as compared to glass and woodworkers, if
an association between EMF exposure and suicide truly exists.
Järvholm and Stenberg suggested that the difference in suicide rate
between the two job groups was unlikely to be due to differences in
socioeconomic factors, but they did not provide an alternative
explanation. One possible explanation may be a healthy survivor worker
effect related to employment status (e.g., at time of death) within this
cohort. That is, active workers may be more physically and mentally fit
than those who left the industry or are unemployed, and may therefore be
at lower risk of committing suicide [2]. A large body of literature
suggests that unemployment and suicide are positively related [3,4], and
being out of work was positively associated with suicide in the electric
utility industry [2]. Since cessation of work also leads to cessation of
work-related exposures, employment status may be an important potential
confounder (or perhaps effect modifier) for the association between work-related exposures and suicide. The lower suicide rate among electricians
as compared to glass and wood workers may be explained by a larger
proportion of glass and wood workers with an inactive employment status at
the time of death.
Although it is unlikely that consideration of employment status, if
possible, would greatly alter the conclusions reached by Järvholm and
Stenberg [1], it would be informative to see its influence on the rate
ratio.
References:
(1) Jarvholm B, Stenberg A. Suicide mortality among electricians in the
Swedish construction industry
Occup Environ Med 2002; 59: 199-200.
(2) van Wijngaarden E, Savitz DA, Kleckner RC, Cai J, Loomis D. Exposure
to electromagnetic fields and suicide among electric utility workers: A
nested case-control study. Occup Environ Med 2000;57:258-263.
(3)Dooley D, Fielding J, Levi L. Health and unemployment. Annu Rev Public
Health 1996;17:449-465.
(4)Kposowa AJ. Suicide mortality in the United States: differentials by
industrial and occupational groups. Am J Ind Med 1999;36:645-652.
Ernst and Fugh-Berman (Occup Environ Med 2002; 59: 140-144) state
that an estimated 42% of Americans and 20-65% of Europeans are using some
form of complementary and alternative medicine (CAM). Unable to find
reliable data on non-industrialised countries, however, they speculate
that the use of CAM in these countries 'may be ubiquitous'.[1] Indeed,
little is known about CAM usage in non-western countries ev...
Ernst and Fugh-Berman (Occup Environ Med 2002; 59: 140-144) state
that an estimated 42% of Americans and 20-65% of Europeans are using some
form of complementary and alternative medicine (CAM). Unable to find
reliable data on non-industrialised countries, however, they speculate
that the use of CAM in these countries 'may be ubiquitous'.[1] Indeed,
little is known about CAM usage in non-western countries even though some
1500 articles on CAM find their way into indexed journals annually.[2]
Readers may therefore be interested to know that a recently completed
interviewer-administered household survey (468 respondents, selection by 2
-stage random sampling) in a housing estate in Singapore, where
Conventional Western Medicine (CWM) is mainstream, revealed that 75% of
respondents had used at least one form of CAM in the past 12 months.[3] The
most common variety was Traditional Chinese Medicine (TCM, 88%) followed
by Malay Jambu (7%) and Ayurvedic Medicine (3%). Among the users of both
CAM and CWM, 74% did not discuss their use of CAM with their CWM
practitioners, a finding that is consistent with studies elsewhere.[4,5]
Singapore's population of 4 million comprises a culturally diverse
mix of Chinese (77%), Malays (14%) Indians (8%) and Others (1%). The use
of TCM is popular, even among the non-Chinese. In 1994, a government
review committee recommended the accreditation of TCM training programmes,
registration of TCM practitioners by a self-regulatory body, and the
establishment of a Chinese Proprietary Medicines Listing Unit in the
Ministry of Health.[6] From 1 January 2004, only registered persons with
valid practising certificates issued by the Traditional Chinese Medicine
Practitioners Board will be allowed to practice. This is similar to the
approach taken by Hong Kong[7] and Taiwan[8] where the popularity of TCM on
the one hand, and concern for patient safety on the other, have
necessitated regulation through a system of registration and licensing.
What about mainland China, the home of TCM and whose teeming millions
account for one-fifth of humanity? In a recently concluded interviewer-
administered household survey involving 3730 respondents (selection by
multi-stage cluster sampling) from three provinces and including urban and
rural residents, 31% said they trusted TCM more than CWM, and 74% said
they preferred to consult a doctor who practises both TCM and CWM.[9]
Given its global popularity despite the lack of a solid evidence
base, CAM certainly deserves more attention than it is presently getting.
M K Lim
Associate Professor
Department of Community, Occupational and Family Medicine
Faculty of Medicine
National University of Singapore
MD3, 16 Medical Drive
Singapore 117597
References
(1) Ernst E and Fugh-Berman A. Complementary and alternative medicine:
what is it all about? Occup Environ Med 2002; 59: 140-144
(2) Barnes J et al. Articles on complementary medicine in the mainstream
medical literature. Archives of International Medicine, 1999;159:1721-1725
(3) Lim MK et al (unpublished data)
(4) Eisenberg D et al. Unconventional medicine in the United States. New
England Journal of Medcine, 1993. 328:246-252.
(5) Oldendick R et al. Population-based survey of complementary and
alternative medicine usage, patient satisfaction, and physician
involvement. South Carolina Complementary Medicine Program Baseline
Research Team. South Medical Journal, 2000, 93 (4), 375-81.
(6) Lim MK Health care systems in transition. II. Singapore, Part I. An
overview of health care systems in Singapore. Journal of Public Health
Medicine 20, no. 1 (March 1998) : 16-22
(7) Hong Kong SAR Government Website. Chinese Medicine. Available at:
http//www.info.gov.hk/info/tcm.htm updated 2002.
(8) Chi C, Lee JW, Lai JS, Chen CY., Chang SK, Chen SC. The practice of
Chinese Medicine in Taiwan. Social Science & Medicine, 1996, Vol.
43(9):1329-1348.
(9) Lim MK et al (unpublished data)
Mortality from cardiovascular diseases and exposure to inorganic
mercury
Bengt Sjögren1, Jonas Holme2, Bjørn Hilt2
1) Toxicology and Risk Assessment
Swedish National Institute for Working Life
SE-112 79 Stockholm
Sweden
Tel 46 8 730 93 40
Fax 46 8 730 33 12
Email Bengt.Sjogren@niwl.se
2) Department of Occupational Medicine
University Hospital of Trondheim
N-7006 Trondheim
Norway
Dear Editor
Paolo Boffetta and his coworkers presented a comprehensive cohort
study comprising of 6784 male and 265 female workers from four mercury mines
and mills in Spain, Slovenia, Italy, and the Ukraine.[1] The expected number
of deaths were derived from the national rates specific for sex, age, and
calender period. Slovenia was the only country with an increased mortality
of ischaemic heart disease among men (SMR 1.66, 95% CI 1.35-2.02). In the
Slovenian mine, dust measurements showed concentrations between 30 and 70
mg/m3 with 10% to 35% free silica in the 1960s, and about 40 mg/m3 in the
1970s. An increased mortality from pneumoconiosis was present in all
countries. Mortality from ischaemic heart disease was positively
correlated with duration of employment but not with cumulative exposure to
mercury. Smoking habits was an unlikely confounder as mortality from
diseases strongly asssociated with tobacco smoking – such as bronchitis,
emphysema, and asthma – was not increased and mortality from lung cancer
showed only a small increase (SMR 1.19). The purpose of this letter is to
further discuss a possible relationship between silica exposure and
ischaemic heart disease (IHD).
A recently published study comprised 4 626 industrial sand workers
exposed to crystalline silica.[2] The study showed a higher standardized
mortality ratio regarding IHD (SMR 1.22, 95% CI 1.09 - 1.36). Smoking
might hypothetically be responsible for 2-4% of this increase.
A Swedish case-control study comprised 26847 men with myocardial
infarctions and for each case two controls were selected from the study
base through random sampling, stratified by age, county, and socioeconomic
group. The second highest risk was found among stonecutters and carvers RR
1.9 (95% CI 1.1 - 3.4). This high risk could not be explained by
differences in smoking habits.[3]
A cohort consisted of 597 miners from North Karelia in Finland
employed for at least three years in a copper mine or a zinc mine.[4] The
excess mortality was mainly due to IHD; 44 were observed, the expected
number was 22.1 based on the general male population, and the North
Karelian expected number was 31.2 (p<_0.05. p="p"/> A cohort of 3971 white South-African gold miners was followed from
the beginning of 1970. Most of the miners worked that year and the age of
the workers was 39-54 years. The participants of the study were followed
for nine years. A case-referent analysis was conducted comprising the
miners who had had at least 85% of their service in gold mines. Ten years
of underground mining was associated with a risk ratio of 1.5 (p=0.004)
regarding IHD after adjustment for smoking, blood pressure, and body mass
index.[5]
A large cohort comprised 68 241 miners as well as pottery workers
from south central China.[6] The participants were employed between 1972
and 1974 and followed until 1989. There was an increased mortality due to
IHD (SMR 1.25, 95% CI 1.05-1.45). Smoking habits was unlikely responsible
for this risk as the mortality from lung cancer was lower than expected
(SMR 0.8, 95% CI 0.7-0.9). There was no significant trend regarding
mortality due to IHD when medium and high dust exposed workers (RR 1.16)
were compared with low dust exposed workers (RR 0.65). Silicotics had not
an increased mortality due to IHD (RR 1.1, 95% CI 0.7-1.8).
A general hypothesis about exposure to inhaled particles and the
occurrence of IHD can be expressed in the following way. Long term
inhalation of particles retained in the lungs will create a low grade
inflammation associated with an increase in plasma fibrinogen. The high
concentration of fibrinogen will increase the likelihood for blood
clotting and thereby the risk for myocardial infarction and IHD.[7,8] A high
concentration of fibrinogen in plasma is an established risk factor for
IHD.[9] An increased concentration of fibrinogen has been observed among
tunnel construction workers after a workshift with a dust exposure of less
than 2 mg/m3.[10] Thus dust exposure in general and silica exposure in
particular could be interesting to discuss in relation to ischaemic heart
disease in this study by Boffetta and coworkers.[1]
References
(1) Boffetta P, Sällsten G, Garcia-Gómez M, et al. Mortality from
cardiovascular diseases and exposure to inorganic mercury. Occup Environ
Med 2001; 58: 461-466.
(2) Steenland K, Sanderson W. Lung cancer among industrial sand
workers exposed to crystalline silica. Am J Epidemiol 2001;153:695-703.
(3) Hammar N, Alfredsson L, Smedberg M, Ahlbom A. Differences in the
incidence of myocardial infarction among occupational groups. Scand J Work
Environ Health 1992;18:178-185.
(4) Ahlman K, Koskela R-S, Kuikka P, et al. Mortality among sulfide
ore miners. Am J Ind Med 1991; 19: 603-617.
(5) Wyndham CH, Bezuidenhout BN, Greenacre MJ, Sluis-Cremer GK.
Mortality of middle aged white South African gold miners. Br J Ind Med
1986;43:677-684.
(6) Chen J, McLaughlin JK, Zhang J-Y, et al. Mortality among dust-
exposed Chinese mine and pottery workers. J Occup Med 1992; 34: 311-316.
(7) Seaton A, MacNee W, Donaldson K, Goddon D. Particulate air
pollution and acute health effects. Lancet 1995;345:176-178.
(8) Sjögren B. Occupational exposure to dust: inflammation and
ischaemic heart disease. Occup Environ Med 1997;54:466-469.
(9) Danesh J, Collins R, Appleby P, Peto R. Association of fibrinogen,
C-reactive protein, albumin, or leukocyte count with coronary heart
disease. JAMA 1998; 279: 1477-1482.
(10) Hilt B, Qvenild T, Holme J, et al. Increase in interleukin-6 and
fibrinogen after dust exposure in tunnel construction workers. Occup
Environ Med 2001 In press.
Dear Editor
Kumagai and his colleges [1] have reported that incinerator workers employed at intermittently burning incineration plants were not necessarily exposed to high concentrations of polychlorinated dibenzo-p- dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). The authors conclusions were based on concentrations of PCDDs and PCDFs in serum samples of the workers. I have deep concerns regarding the st...
Dear Editor
We thank Drs Schwartz and Seeber, as well as their colleagues, for the commentaries on our paper “Neurobehavioral Testing in Workers Occupationally Exposed to Lead: Systematic Reviewand Meta-Analysis of Publications”[1] and would like to respond to their criticisms.
Response to specific points made by Schwartz et al.:
(i) “No evaluation of the quality of the evidence from available stu...
Test...
Dear Editor
Whether or not low-to-modest levels of exposure to lead have a detrimental effect on cognition is an important issue given the growing attention, for example, in the United States, that has recently been paid towards potentially revising downward the levels of lead exposure allowed in the workplace. Thus, we read with interest the meta-analysis of studies on this topic that appeared in this journal by...
Dear Editor
The article of Dr Goodman and co-workers on "Neurobehavioral testing in workers occupationally exposed to lead…." [1] covers an interesting approach with a surprising main message: "None of the individual studies is conclusive or adequate in providing information on the subclinical neurobehavioral effects …". Such sentence astonishes a reader since the studies used were selected from established journals...
Dear Editor,
We appreciate dr Wijngaarden´s interest in our report and his suggestion for understanding the differences in risk. Dr Wijngaarden suggests that difference in unemployment rate between electricians and glassworker and wood workers could be an explanation.
We have no data on employment status at time of death and can therefore not test this hypothesis. However, if employment status is an...
Dear Editor
We read the report by Hollund et al[1] with great interest. We agree that there is limited information about the prevalence of airway symptoms caused by highly reactive chemicals in hairdressing salons. In this well designed study, authors focused on age as a risk factor and observed an increased prevalence of respiratory symptoms among the oldest and youngest hairdressers and observed more symptoms among...
Dear Editor,
Järvholm and Stenberg [1] evaluated suicide mortality rates among electricians ("exposed to electromagnetic fields (EMFs)") and glass and woodworkers ("unexposed to EMFs") in the Swedish construction industry. Standard mortality rates were lower for the two job groups as compared to the Swedish general population. This is likely due to the healthy worker effect. The internal cohort analysis showed...
Ernst and Fugh-Berman (Occup Environ Med 2002; 59: 140-144) state that an estimated 42% of Americans and 20-65% of Europeans are using some form of complementary and alternative medicine (CAM). Unable to find reliable data on non-industrialised countries, however, they speculate that the use of CAM in these countries 'may be ubiquitous'.[1] Indeed, little is known about CAM usage in non-western countries ev...
Letter to the editor
Mortality from cardiovascular diseases and exposure to inorganic mercury
Bengt Sjögren1, Jonas Holme2, Bjørn Hilt2
1) Toxicology and Risk Assessment Swedish National Institute for Working Life SE-112 79 Stockholm
Sweden Tel 46 8 730 93 40 Fax 46 8 730 33 12 Email Bengt.Sjogren@niwl.se
2) Department of Occupational Medicine University Hospital of Trondhe...
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