The paper by Harrison et al.[1] and the accompanying editorial by
Cherrie [2] address the important issue of personal exposure assessment (of
air pollutants) in environmental epidemiology. After reading both papers
we would like to make some comments with regard to the design, conduct and
statistical analysis of the study by Harrison et al. and at the same time
answer the question raised by...
The paper by Harrison et al.[1] and the accompanying editorial by
Cherrie [2] address the important issue of personal exposure assessment (of
air pollutants) in environmental epidemiology. After reading both papers
we would like to make some comments with regard to the design, conduct and
statistical analysis of the study by Harrison et al. and at the same time
answer the question raised by Cherrie in his editorial.
Coming from the occupational exposure assessment arena it is
interesting to see that our environmental colleagues are still relying on
to a large extent on static (micro-environmental) sampling and even rely
on shadowing to represent personal exposure. The latter brought back
memories of old occupational hygiene textbooks with pictures of
technicians standing with a sampling probe in the breathing zone of a
worker (clearly hindered while carrying out his work task). It is
interesting to note that Dr Cherrie´s very relevant earlier work [3] on
whether wearing sampling pumps affects exposure (it hardly did) was not
mentioned in both papers.
The paper by Harrison et al.[1] clearly states as one of its goals to
answer the question "Does modelling through the use of microenvironment
measurements and activity diaries produce reliable estimates of personal
exposure to air pollutants". However in the only setting where personal
exposures were actually measured (Phase 1, volunteers; with regard to
Phase 2 we do not think that shadowing results can be seen as equivalent
to personal measured exposure) it is hard to grasp from both Figure 1 and
Table 2 which exposure was actually modelled (1-hour averages, 2-3 day
averages) and how (a formula was only provided for measurements within the
susceptible groups).
When comparing direct personal measurements for CO and PM10 with the
modelled results, the authors exclude all data which are not directly
comparable, i.e. when the volunteer spent most of their time out of house,
and all the data for smokers. It is therefore not surprising that good
correlations were found between personal and static measurement results.
Why were smokers excluded? Was their measured CO exposure representing a
different kind of CO leading to a different health effect? We know that
excluding smokers or people with unventilated gas heaters is common
practice in the statistical analyses of environmental exposures, but this
would only make sense if we were expecting different risks from the same
exposure originating from different sources.
In Figure 1 the authors present 120 comparable data points for 11
individuals and given the repeated nature of the sampling these data
points cannot be seen as statistically independent. Putting a simple
regression line through these points is therefore not correct and
application of a mixed model would have been more appropriate. Besides
that, when estimating environmental exposure for instance for a panel
study, we are interested in the full range of exposures both in the
temporal and spatial sense (not only for the room with the static
sampler). However, Harrison et al. conclude, "...modelled personal exposure
is unable to reflect the variability of measured personal exposures
occasioned by the spread of concentrations within given
microenvironments."
Both Cherrie and Harrison et al. claim that micro-environmental
sampling would be a good alternative for direct personal exposure
measurements that supposedly are "costly and time consuming". However, the
costs for sampling micro environments in a general population study will
be far greater if we want to measure all the micro environments people end
up in (for instance in Table 1 seven environments are indicated and most
of them will most likely be different for each study participant). In
addition, it will be practically impossible to measure some of these
environments as the authors point out. In their study, it was not possible
to collect data for all appropriate microenvironments even for a
comparatively small number of subjects.
Recently, a very insightful paper was presented at the X2001
conference in Gothenburg. Seixas et al.[4] showed that in a study to assess
noise exposure, a task-based methodology (analogous to micro-environmental
sampling in occupational exposure assessment) could only account for 30%
of variability in daily exposures. They even considered this estimate
somewhat optimistic since their estimated noise exposures were derived
from the same data on which the daily average exposures were estimated. In
addition they clearly pointed out that using simple task-based averages
that artificially compress exposure variability resulted in a very
substantial negative bias in the estimated daily exposure.
In our opinion, we should aim to collect personal exposure
measurements when estimating exposure for epidemiological studies. We
agree that smaller and lighter sampling instruments will need to be
developed, as was suggested by Cherrie in his editorial. Recent studies in
both the occupational and environmental arena have shown that study
subjects are capable to carry out personal measurements themselves (and by
doing so, cutting out the costs of the technician).[5-9] In all these
studies but one [7] far more than 100 personal measurements were generated,
which shows that studies of this size are not exceptional as was suggested
in the editorial by Cherrie.
The question that was raised by Cherrie "How important is personal
exposure assessment in the epidemiology of air pollution?" can only be
answered with a firm "Very important", if we want to capture the full
range of personal exposures experienced in the general environment. In
addition, given the relatively low concentrations in the general
environment we will need to measure these accurately. Micro-environmental
monitoring and consequent modelling based on diaries will not provide
sufficient resolution and accuracy.
Hans Kromhout1,2 Martie van Tongeren3
1. Environmental and Occupational Health Division, Institute for Risk
Assessment Sciences, Utrecht University, PO Box 80176, 3508 TD Utrecht,
The Netherlands
2. Research Unit Respiratory and Environmental Health, Municipal
Institute of Medical Research, Barcelona, Spain
3. Centre for Occupational and Environmental Health, School of
Epidemiology and Health Sciences, The University of Manchester,
Manchester, United Kingdom
References
(1) Harrison RM, Thornton CA, Lawrence RG, et al. Personal exposure
monitoring of particulate matter, nitrogen dioxide and carbon monoxide,
including susceptible groups. Occup Environ Med 2002;59: 671–9.
(2) Cherrie JW. How important is personal exposure assessment in the
epidemiology of air pollutants? Occup Environ Med 2002;59:653-54.
(3) Cherrie JW, Lynch G, Bord BS, Heathfield P, Cowie H, Robertson A.
Does the wearing of sampling pumps affect exposure? Ann Occup Hyg
1994;38:827-38.
(4) Seixas N, Sheppard L, Neitzel R. Comparison of task-based and full
-shift strategies for noise exposure assessment in the construction
industry. Arbete och Hälsa 2001; 10:51-3.
(5) Kromhout H, Loomis DP, Mihlan GJ, Peipins LA, Kleckner RC, Iriye
R, Savitz DA. Assessment and grouping of occupational magnetic field
exposure in five electric utility companies. Scand J Work Environ Health
1995;21:43-50.
(6) Egeghy PP, Tornero-Velez R, Rappaport SM. Environmental and
biological monitoring of benzene during self-service automobile refueling.
Environ Health Perspect 2000;108:1195-202.
(7) Tielemans E, Heederik D, Burdorf A, Vermeulen R, Veulemans H,
Kromhout H, Hartog K. Assessment of occupational exposures in a general
population: comparison of different methods. Occup Environ Med 1999;56:145
-51.
(8) Rijnders E, Janssen NAH, Vliet PHN van, B. Brunekreef. Personal
and outdoor nitrogen dioxide concentrations in relation to degree of
urbanization and traffic density. Environ Health Perspect 2001;109:411-7.
(9) Liljelind IE, Rappaport SM, Levin JO, et al. Comparison of self-
assessment and expert assessment of occupational exposure to chemicals.
Scand J Work Environ Health 2001;27:311–7.
In commenting on our paper published recently in OEM,[1] Kromhout
and van Tongeren admonish us for paying insufficient attention to the
earlier literature on occupational pollutant exposures. Whilst no doubt
an element of their criticism is justified, we feel that the exposure
situation for the general public is sufficiently different that it should
not be assumed that findings in the occupational...
In commenting on our paper published recently in OEM,[1] Kromhout
and van Tongeren admonish us for paying insufficient attention to the
earlier literature on occupational pollutant exposures. Whilst no doubt
an element of their criticism is justified, we feel that the exposure
situation for the general public is sufficiently different that it should
not be assumed that findings in the occupational environment can
necessarily be extrapolated to environmental exposures of the general
public. A large component of environmental exposure arises from diffuse
sources and may therefore be very spatially homogeneous at locations such
as peoples’ homes which are often relatively remote from outdoor pollution
sources.
There has been some controversy in the literature regarding the
extent to which measurements at fixed central urban background monitoring
locations can reflect the exposures of large urban populations who spend
much of their time indoors at locations relatively remote from the
monitoring station [e.g. 2,3]. It has been typical to find that for an
individual, daily personal exposures correlate with concentrations at the
monitoring station, whilst if data are pooled from many individuals, the
exposures appear to be uncorrelated with ambient air data.[4,5] This
finding suggests that the diffuse background as represented by the central
urban monitor does account for a substantial proportion of variance in the
exposure of an individual and this conclusion is supportive of causality
in the time series epidemiological studies, which would appear implausible
if the monitoring data were unrelated to human exposures. The finding of
our paper that microenvironment measurements do, in general, well
represent individual personal exposures in that microenvironment
(excepting for the personal cloud of PM10) is far from self-evident from
much of the earlier literature and is a useful addition to knowledge. The
fact that cigarette smokers were outliers in the regression analysis shows
not unexpectedly that they generate strong local concentration gradients
and would therefore need to be treated differently in any modelling of
personal exposures. In the absence of such local sources of pollution,
our study supports the concept that were sufficient microenvironment
measurement data available, it would be perfectly feasible to model
personal exposures with some degree of reliability.
Kromhout and van Tongeren advocate the use of personal exposure
measurements in environmental epidemiological studies. In doing so, they
fail to acknowledge the magnitude of such studies. For example, in the
large North American cohort studies, 8111 subjects were recruited in the
Harvard Six Cities Study and over one million in the American Cancer
Society Study. Were it possible to reconstruct the exposure environments
of those individuals, even in a rather general way from time activity
diaries, a considerable refinement would have been achieved. Even in
panel studies, which typically recruit a far smaller number of
individuals, the subjects are frequently drawn from susceptible groups and
therefore not willing to be encumbered with troublesome and heavy sampling
equipment. It must be remembered that concentrations in environmental
samples are typically orders of magnitude lower than in occupational
samples, therefore requiring higher flow rates (hence bigger pumps) and
longer sampling intervals. In some instances it may be possible to use
passive samplers such as diffusion tubes and badges, but these are
typically rather imprecise and are available only for a very limited range
of pollutants.
In summary, therefore, whilst the measurement of personal exposure in
environmental epidemiology is highly desirable, it is in reality very
unlikely to be practicable in most studies. Thus, our study of the
feasibility of reconstructing exposures from microenvironment data is well
justified and has thrown useful light on the problem, for example, in
illustrating the lower exposures of members of certain of our susceptible
groups.
Roy M. Harrison, Rob P. Kinnersley, Royston G. Lawrence
University of Birmingham
Jon G. Ayres
University of Aberdeen
David Mark
Health & Safety Laboratory
References
(1) R.M. Harrison,
C.A. Thornton, R.G. Lawrence, D. Mark, R.P. Kinnersley and J.G. Ayres. Personal exposure monitoring of particulate matter, nitrogen
dioxide and carbon monoxide, including susceptible groups. Occup. Environ.
Med., 59, 671-679 (2002).
(2) C.H. Linaker, A.J. Chauthan, H.M. Inskip,
S.T. Holgate, D. Coggon. Personal exposures of children to nitrogen dioxide relative to
concentrations in outdoor air. Occup. Environ. Med., 57, 472-176 (2000).
(3) D. Mark, S.L. Upton, C.P. Lyons, R. Appleby, E.J. Dyment, W.D.
Griffith and A.A. Fox. Personal exposure measurements of the general public to atmospheric
particles. Ann. Occup. Hyg., 41, Suppl 1, 700-706 (1997).
(4) N.A.H. Janssen, G. Hoek, B. Brunekreef, H. Harssema, I. Mensink and A.
Zuidhof. Personal sampling of particles in adults: Relation among personal,
indoor and outdoor air concentrations. Am. J. of Epidemiol., 147, 537-547 (1998).
(5) L. Wallace. Correlations of personal exposure to particles with outdoor air
measurements: A review of recent studies. Aerosol Sci. & Technol., 32, 15-25 (2000).
Editor,
Rushton's recent article on the reporting of occupational and environmental research raises a number of useful points that all researchers would do well to remember when writing up epidemiological findings for publication. Without expressly intending to do so, however, the article also emphasizes the hazards of establishing formal criteria or
checklists for the evaluation of scientific work. Good epi...
Editor,
Rushton's recent article on the reporting of occupational and environmental research raises a number of useful points that all researchers would do well to remember when writing up epidemiological findings for publication. Without expressly intending to do so, however, the article also emphasizes the hazards of establishing formal criteria or
checklists for the evaluation of scientific work. Good epidemiological practices certainly exist, but one of the pitfalls inherent in attempts to codify them is that, by their nature, lists of the features of "good"
research tend to impose a "one size fits all" standard, which - like clothing of the same description - fits nothing particularly well.
The prospect of developing formal guidelines for reporting analyses based on multivariable models illustrates the difficulties. Science involves many kinds of activities, but the significant advances come about through the creative application of human intellect, rather than by rote
repetition of the familiar. Like other aspects of science, epidemiological data analysis blends attention to factual detail with creativity, intuition, judgement and even aesthetics. From the initial choice of model
form to the final specification of covariates and interaction terms, there may be many reasonable ways to model a given data set. Researchers should
be at liberty to analyze their data according to their individual scientific insights. In subsequent evaluations of methods and results, reviewers likewise should be encouraged to apply their scientific judgement, rather than following a recipe.
The opportunity cost involved in demonstrating compliance with guidelines for good practice may also be considerable, as Rushton suggests. Between the growing fear of litigation and mounting demands for accountability, especially in the United States, epidemiologists may
soon spend more time documenting adherence to protocol than doing science.
My particular fear, however, is that guidelines will be used to assail sound research on the grounds that it fails to comply with supposed standards of good science. The misuse of Bradford Hill's ideas about causality illustrates the danger. Hill intended his suggestions as an aid
to researchers, not as evaluative standards for critics; he wrote: "I do not believe...that we can usefully lay down some hard-and-fact rules of evidence that must be obeyed before we accept cause and effect. None of my nine viewpoints ... can be required as a sine qua non. What they can do, with greater or less strength, is help us to make up our minds on the fundamental question." [1] Yet, Hill's ideas are frequently presented as criteria that must be fulfilled for a study's evidence to be accepted.[2]
The involvement of such obviously self-interested groups as the Chemical Manufacturers Association in promoting "good epidemiological practices" makes the potential misuse of guidelines to suppress good research seem all too likely.
I do not mean to suggest that all epidemiological research should be published or accepted at face value, far from it. There will always be a need for review to ensure the quality of published work and to protect the public from policies based on unsound science. I am convinced, however,
that peer review coupled with the opportunity for criticism and debate in the open literature provide the best pathway to this goal. In contrast with standardized criteria, these processes allow multiple, independent readers' perspectives concerning the methodological quality, and the substantive importance of research to be heard. As a result, they reduce
the chances that unconventional but valuable views will be suppressed or that an interested group could gain control over the process for their own purposes.
References
1. Hill AB. The environment and disease: association or causation? Proc R Soc Med 1965;58:295-300.
2. Gamble JF. PM2.5 and mortality in long-term prospective cohort studies: cause-effect or statistical association? Environ Health Perspect 1998;106:535-549.
“Job strain” may be associated with unhealthy diet pattern, which
usually includes high sodium intake—a major risk factor of hypertension.
Moreover, high sodium intake is always associated with high fat and high
energy intake, and further associated with high BMI level.
Therefore, it would be interesting to see whether there is any
association between “Job constraints” and overweight among th...
“Job strain” may be associated with unhealthy diet pattern, which
usually includes high sodium intake—a major risk factor of hypertension.
Moreover, high sodium intake is always associated with high fat and high
energy intake, and further associated with high BMI level.
Therefore, it would be interesting to see whether there is any
association between “Job constraints” and overweight among the subjects in
this study.[1]
Reference
1. Radi, S., et al., Job constraints and arterial hypertension:
different effects in men and women: the IHPAF II case control study. Occup
Environ Med, 2005. 62(10): p. 711-7.
Dr Loomis draws attention to the potential dangers of the rigid use
of checklists and guidelines to judge occupational and environmental
research. I agree with these sentiments, in particular the concerns about
the increasing number of papers that use compliance with these guidelines
as a justification for conclusions regarding causality. There is, however,
one rapidly expanding area of research that...
Dr Loomis draws attention to the potential dangers of the rigid use
of checklists and guidelines to judge occupational and environmental
research. I agree with these sentiments, in particular the concerns about
the increasing number of papers that use compliance with these guidelines
as a justification for conclusions regarding causality. There is, however,
one rapidly expanding area of research that would benefit from the
development of minimum standards for presentation of results. This is the
field of epidemiological meta-analysis, in which data are generally
abstracted from published papers. Difficulties can arise in deriving a
common set of definitions for variables. For example, in a meta-analysis
of oral contraceptive use and breast cancer risk,[1] 42 different
categorisations of duration of oral contraceptive use were published in
the 24 papers analysed for this variable. Debate within the scientific
community is needed to decide categorisations that are most useful.
Editors could then encourage authors either to use these in their papers
or at least be prepared to make them available on request.
Reference
1. Rushton L, Jones DR. Oral contraceptive use and breast cancer
risk: a meta-analysis of variations with age at diagnosis, parity and
total duration of oral contraceptive use. Br J Obs Gyn 1992;99:239-246.
We thank Mr. Wenbin Liang for comments on our paper.
The first part of the comments concerned criticism on our Figure 1
and handling of exposure data. Our
Figure 1 is a schematic drawing. It was aimed only to portray how the
explanatory variables precede the response variables in our two-stage
model. The purpose of our study was not to investigate does "dust exposure
increase the risk of IHD a...
We thank Mr. Wenbin Liang for comments on our paper.
The first part of the comments concerned criticism on our Figure 1
and handling of exposure data. Our
Figure 1 is a schematic drawing. It was aimed only to portray how the
explanatory variables precede the response variables in our two-stage
model. The purpose of our study was not to investigate does "dust exposure
increase the risk of IHD among patients who already had respiratory
diseases". Therefore, the figure was not intended to express that
question. The aim of our study was concentrated on the intermediate role
of the respiratory diseases in the association of dust exposure with IHD.
To predict IHD with the two-stage model we first used respiratory diseases
and dust exposure as explanatory variables. Second, we studied respiratory
diseases as response variables. The respiratory disease and exposure
variables were time dependent in the model predicting IHD just due to the
importance of the timing.
All the cohort members have been followed up until the end of the
whole follow-up period. Although the workers had moved to other jobs,
e.g., to those of lower dust exposure, they remained in our cohort.
Lifelong occupational histories (including confounding exposures) were
collected via questionnaires. In the model, cumulative exposure to dust
was considered until the diagnosis date of ischaemic heart disease (IHD)
regardless of the diagnosis date of any respiratory disease. In the model
where respiratory diseases were predicted, exposure was considered only
until the occurrence of each respiratory disease.
Changing out of dusty jobs does not remove the effect of earlier dust
exposure on IHD as well as on respiratory diseases, because both of these
diseases have developed as disease processes and are continuously
developing. The date of diagnosis is just one time point during the
development. In addition, some of the workers with a respiratory disease
had continued working in their dusty jobs.
Workers with a respiratory disease may have an increased risk to get
IHD due to an additional dust exposure after the respiratory disease
diagnosis. However, it is important to remember that those workers who
don't yet have a diagnosis but who are under the process to develop a
respiratory disease may have the same increased risk. Thus, it is more
reasonable to use the cumulative dust exposure up to the date of IHD
diagnosis. Further, if we had analyzed the exposure data only including
dust exposure after the diagnosis of a respiratory disease, the resulted
effect of dust exposure on IHD would have been small.
The most important reason for the observed small effect of dust
exposure on IHD seemed to be homogeneity in the exposure variable. This
has been thoroughly discussed in our article.
The second part of the comments concerned smoking. It is well known
that smoking is a great risk factor for both respiratory disease and IHD.
The following data on smoking were collected via questionnaires: age when
started to smoke and age when stopped, current smoking (amount of
cigarettes per day), lifelong smoking (amount of cigarettes per day,
smoking years). The comparison of the different smoking variables (tables
and models) showed that the classified variable lifelong smoking was the
most suitable for this material. Further, we have not reported any results
on the effect of interaction between smoking and respiratory diseases on
incidence of IHD. Of course we studied in the models interaction between
smoking and dust exposure as well as interaction between smoking and
different respiratory diseases but these interactions seemed to be non-
significant.
Chronic hand vibration exposure is now a well-described cause of
Raynaud's phenomenon. According to Palmer et al, it is estimated that
220,000 cases of Raynaud's phenomenon are attributable to vibration
exposure in Great Britain.[1] These epidemiological data, based on a
questionnaire, are considered reasonably accurate.[2] About 4.2 million
workers are exposed to hand transmitted vibration but the real...
Chronic hand vibration exposure is now a well-described cause of
Raynaud's phenomenon. According to Palmer et al, it is estimated that
220,000 cases of Raynaud's phenomenon are attributable to vibration
exposure in Great Britain.[1] These epidemiological data, based on a
questionnaire, are considered reasonably accurate.[2] About 4.2 million
workers are exposed to hand transmitted vibration but the real health and
economic impact is unknown.[3] More precise clinical data are therefore
necessary before implementing a large preventive program.
The hand-arm vibration syndrome encompass a wide range of disorders being
responsible for digital blanching and paresthesias.[4] Different vascular
problems such as a pure vasospastic phenomenon, a digital organic
microangiopathy or an occlusive arterial thrombosis can be observed. A
diffuse vibration neuropathy with mechanical skin receptors involvement or
a carpal tunnel syndrome are also often associated.[5] The relationship
between these neurovascular disorders is not clear but autonomic
dysfunction in carpal tunnel syndrome can induce a Raynaud's phenomenon
which is curable with surgery.[6] The prognosis of these neurovascular
troubles is dependant on the underlying trouble and cannot be evaluated
with a simple questionnaire. As no single test can reliably stage the
vascular and neurological component, the use of a battery of tests is
necessary. Digital capillaroscopy and plethysmography with nerve
conduction studies are recommended as the basic tests. Cold provocation
tests are effective for grading a pure vasospastic Raynaud's phenomenon
but is less reliable in other forms of vibration-induced white finger
explaining why this test is not always well correlated with the vascular
symptoms.[7][8] Doppler and duplex studies are useful to assess the
severity of an occlusive arterial disease.
Workers using hand-held vibrating tools are also exposed to diverse
environmental and occupational factors accounting for the wide clinical
spectra of the disease. Epidemiological studies have pointed out that the
prevalence of vibration-induced white finger is very wide, ranging from 0-
5% in warm climate to 80-100% in northern climate.[9] In the pure
vasospastic Raynaud's phenomenon, cold exposure is probably the most
important triggering factor and cold protection the most effective
preventive measure. In the case of digital blanching associated with
carpal tunnel syndrome, other ergonomic factors such as repetitive
forceful use of the hands are likely to play a dominant role and a
workplace ergonomic modification is indicated.[10] Hypothenar hammer
syndrome is a another frequent cause of digital blanching in mechanics and
carpenters requiring prevention of repetitive hand trauma.[11][12] For the
digital organic microangiopathy and the diffuse vibration neuropathy,
vibration exposure is the only identified factor and suppression of the
exposition is essential. In consequences, a detailed and precise clinical
diagnosis with objective tests is important to determine the real cause of
the vascular symptoms. The impact of vibration exposure on health will be
more precisely evaluated and prevention will be more effective.
1. Palmer KT, Griffin MJ, Syddall H, et al. Prevalence of Raynaud's
phenomenon in Great Britain and its relation to hand transmitted
vibration: a national postal survey. Occup Environ Med 2000;57:448-52.
2. Palmer KT, Haward B, Griffin MJ, et al. Validity of self reported
occupational exposures to hand transmitted and whole body vibration. Occup
Environ Med 2000;57:237-41.
3. Palmer KT, Griffin MJ, Bendall H, et al. Prevalence and pattern of
occupational exposure to hand transmitted vibration in Great Britain:
findings from a national survey. Occup Environ Med 2000;57:218-28.
4. Noel B. Pathophysiology and classification of the vibration white
finger. Int Arch Occup Environ Health 2000;73:150-5.
5. Stromberg T, Dahlin LB, Rosen I, et al. Neurophysiological findings in
vibration-exposed male workers. J Hand Surg [Br] 1999;24:203-9.
6. Verghese J, Galanopoulou AS, Herskovitz S. Autonomic dysfunction in
idiopathic carpal tunnel syndrome. Muscle Nerve 2000;23:1209-13.
7. McLafferty RB, Edwards JM, Ferris BL, et al. Raynaud's syndrome in
workers who use vibrating pneumatic air knives. J Vasc Surg 1999;30:1-7.
8. McGeoch KL, Gilmour WH. Cross sectional study of a workforce exposed to
hand-arm vibration: with objective tests and the Stockholm workshop
scales. Occup Environ Med 2000;57:35-42.
9. Bovenzi M. Exposure-response relationship in the hand-arm vibration
syndrome: an overview of current epidemiology research. Int Arch Occup
Environ Health 1998;71:509-19.
10. Gemne G. Diagnostics of hand-arm system disorders in workers who use
vibrating tools. Occup Environ Med 1997;54:90-5.
11. Little JM, Ferguson DA. The incidence of the hypothenar hammer
syndrome. Arch Surg 1972;105:684-5.
12. Ferris BL, Taylor LM Jr, Oyama K, et al. Hypothenar hammer syndrome:
proposed etiology. J Vasc Surg 2000 Jan;31:104-13.
The recent article by Vyas, et al.[1] raises some concerns to which I
would be grateful if they could respond.
1) In the abstract one of the objectives is stated as finding the
nature and incidence of symptoms experienced by a large sample of hospital
endoscopy nurses. The study design is cross-sectional and used an adapted
version of the MRC questionnaire for respiratory symptoms. This study
design normally re...
The recent article by Vyas, et al.[1] raises some concerns to which I
would be grateful if they could respond.
1) In the abstract one of the objectives is stated as finding the
nature and incidence of symptoms experienced by a large sample of hospital
endoscopy nurses. The study design is cross-sectional and used an adapted
version of the MRC questionnaire for respiratory symptoms. This study
design normally records disease prevalence rather than incidence.[2] It
would be helpful to know if the questionnaire sought information on new
symptoms in a given time period in the past, or the presence of symptoms.
2) For the purposes of the study, work related symptoms (WRSs) of
contact dermatitis were defined as contact skin rash, which occurred when
working on the endoscopy unit and could not be attributed to known non-occupational agents. It is not clear what validation process was performed
prior to using this section of the questionnaire in the study. The authors
have indicated that 8 of the 13 subjects with a positive test to IgE
specific to latex had WRSs of dermatitis, and indicate this is non-significant. The authors definition of contact dermatitis would have
resulted in staff with contact urticaria answering positively to this
section. As such, the presence of IgE specific to latex could well be of
significance as staff would have used latex gloves.
3) Cross-sectional studies are enhanced by the inclusion of ex-employees. In this study only 18 of 68 ex-employees participated in this
study. All 18 were among 26 staff who had left within the past five years
for health reasons. As such a selection bias exists and the interpretation
of the frequency of WRSs in ex-employees should be cautious. In addition, it is noted that 8 of the 18 ex-employees continue to work as
nurses and may experience WRSs from circumstances related to current
workplaces rather than endoscopy suites. The absence of a control group of
nurses working in areas without exposure to glutaraldehyde would have been
of help in interpreting the results obtained.
References
1. A Vyas, C A C Pickering, L A Oldham, H C Francis, A M Fletcher, T Merrett, and R McL Niven.
Survey of symptoms, respiratory function, and immunology and their relation to glutaraldehyde and other
occupational exposures among endoscopy nursing staff
Occup Environ Med 2000;57:752-759
2. Last JM. A Dictionary of Epidemiology. Oxford: Oxford
University Press, 1995
We thank Dr. Seilkop for his comment and have, in essence, not much
to
add to it. The study by Shannon et al.[1] had obviously been overlooked
and the study by Arena et al.[2] was published after our deadline
for the inclusion of studies.
Dr. Seilkop´s Table has errors for the study by Andersson et al.[3]
The number of
pacreatic cancer deaths should be 2; relative risk should be 1.2; and
95% conf...
We thank Dr. Seilkop for his comment and have, in essence, not much
to
add to it. The study by Shannon et al.[1] had obviously been overlooked
and the study by Arena et al.[2] was published after our deadline
for the inclusion of studies.
Dr. Seilkop´s Table has errors for the study by Andersson et al.[3]
The number of
pacreatic cancer deaths should be 2; relative risk should be 1.2; and
95% confidence interval should be 0.1 - 4.5.
References
1. Shannon HS, Walsh C, Jadon N, et al. Mortality of 11,500 nickel
workers - extended follow up and relationship to environmental
conditions. Toxicol Ind Health 1991;7:277-94.
2. Arena VC, Sussman NB, Redmond CK, et al. Using alternative
comparison populations to assess occupation-related mortality risk. J
Occup Environ Med 1998;40:907-16.
3.Andersson VC, Elinder CG, Hogstedt C, et al. Mortality among
cadmium
and nickel-exposed workers in a Swedish battery factory. Current Topics
in Environmental and Toxicological Chemmistry 1985;399-408.
As victims of bullying and proponents of emotional intelligence in
the health profession we read with interest your article on workplace
bullying.[1]
Kavimaki et al[1] did not mentioned whether the responses were
anonymous. Identified responses may underestimate the incidence of
bullying in the cohort. Given that previous studies (mentioned by the
authors in the discussion) have shown a consid...
As victims of bullying and proponents of emotional intelligence in
the health profession we read with interest your article on workplace
bullying.[1]
Kavimaki et al[1] did not mentioned whether the responses were
anonymous. Identified responses may underestimate the incidence of
bullying in the cohort. Given that previous studies (mentioned by the
authors in the discussion) have shown a considerable percentage of victims
deciding to resign as a result of bullying, it is a pity that the article
by Kivimaki et al did not contain similar data. The other two issues that should have been included were the duration of being bullied, and how many
bullies are actually are aware that they are bullies. These can be addressed by asking
the question: Have you subjected your colleagues to such bullying
behaviour?
With doctors and nurses constituting 58% of the victims, we wonder
whether the authors could reanalyse their data to see whether there is a
higher incidence of bullying in the high stress specialities such as adult
intensive care and neonatal intensive care.[2] We would also like to
know whether the victims in their study were offered any counselling by
their institutions, and if so, the nature and impact of the counselling.
Emotional intelligence is defined by the five emotional quotients of
self awareness of feelings, emotional self regulation, self monitoring and
goal setting, empathy, and social and communication skills.[3] According
to Goleman, “The rules for work are changing, we’re being judged by a new
yardstick: not just how smart we are, or our expertise, but also how well
we handle ourselves and each other.”[4] Emotional intelligence is
considered more important than IQ in enabling people to function well in
society.[5] We would like to suggest that emotional intelligence, which
can be taught, can be an important solution to reducing the incidence of
bullying in the workplace.[6]
References:
1. Kivimaki M, Elovainio M, Vahtera J Workplace bullying and sickness absence in hospital staff. Occup Environ Med 2000;57:656-60
2. Rosenthal SL, Schmid KD, Black MM. Stress and coping in a NICU.
Res Nurs Health 1989;12:257-65
3. Goleman D. Emotional intelligence. Why it can matter more than IQ. London: Bloomsbury Publishing Plc, 1995
4. Goleman D. Working with Emotional Intelligence. London: Bloomsbury Publishing Plc, 1998
5. Goleman D. What makes a leader? Harv Bus Rev 1998;76:93-102
6. Koh TS, Koh THHG. Disruptive doctors: emotion based medicine is as important as evidence based medicine. MJA (in press)
Dear Editor
The paper by Harrison et al.[1] and the accompanying editorial by Cherrie [2] address the important issue of personal exposure assessment (of air pollutants) in environmental epidemiology. After reading both papers we would like to make some comments with regard to the design, conduct and statistical analysis of the study by Harrison et al. and at the same time answer the question raised by...
Dear Editor
In commenting on our paper published recently in OEM,[1] Kromhout and van Tongeren admonish us for paying insufficient attention to the earlier literature on occupational pollutant exposures. Whilst no doubt an element of their criticism is justified, we feel that the exposure situation for the general public is sufficiently different that it should not be assumed that findings in the occupational...
Editor,
Rushton's recent article on the reporting of occupational and environmental research raises a number of useful points that all researchers would do well to remember when writing up epidemiological findings for publication. Without expressly intending to do so, however, the article also emphasizes the hazards of establishing formal criteria or checklists for the evaluation of scientific work. Good epi...
Dear Editor,
“Job strain” may be associated with unhealthy diet pattern, which usually includes high sodium intake—a major risk factor of hypertension. Moreover, high sodium intake is always associated with high fat and high energy intake, and further associated with high BMI level.
Therefore, it would be interesting to see whether there is any association between “Job constraints” and overweight among th...
Dear Editor
Dr Loomis draws attention to the potential dangers of the rigid use of checklists and guidelines to judge occupational and environmental research. I agree with these sentiments, in particular the concerns about the increasing number of papers that use compliance with these guidelines as a justification for conclusions regarding causality. There is, however, one rapidly expanding area of research that...
Dear Editor,
We thank Mr. Wenbin Liang for comments on our paper.
The first part of the comments concerned criticism on our Figure 1 and handling of exposure data. Our Figure 1 is a schematic drawing. It was aimed only to portray how the explanatory variables precede the response variables in our two-stage model. The purpose of our study was not to investigate does "dust exposure increase the risk of IHD a...
Editor
Chronic hand vibration exposure is now a well-described cause of Raynaud's phenomenon. According to Palmer et al, it is estimated that 220,000 cases of Raynaud's phenomenon are attributable to vibration exposure in Great Britain.[1] These epidemiological data, based on a questionnaire, are considered reasonably accurate.[2] About 4.2 million workers are exposed to hand transmitted vibration but the real...
The recent article by Vyas, et al.[1] raises some concerns to which I would be grateful if they could respond.
1) In the abstract one of the objectives is stated as finding the nature and incidence of symptoms experienced by a large sample of hospital endoscopy nurses. The study design is cross-sectional and used an adapted version of the MRC questionnaire for respiratory symptoms. This study design normally re...
Editor
We thank Dr. Seilkop for his comment and have, in essence, not much to add to it. The study by Shannon et al.[1] had obviously been overlooked and the study by Arena et al.[2] was published after our deadline for the inclusion of studies.
Dr. Seilkop´s Table has errors for the study by Andersson et al.[3] The number of pacreatic cancer deaths should be 2; relative risk should be 1.2; and 95% conf...
Editor
As victims of bullying and proponents of emotional intelligence in the health profession we read with interest your article on workplace bullying.[1]
Kavimaki et al[1] did not mentioned whether the responses were anonymous. Identified responses may underestimate the incidence of bullying in the cohort. Given that previous studies (mentioned by the authors in the discussion) have shown a consid...
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