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Recent eLetters

Displaying 1-10 letters out of 188 published

  1. Mesothelioma Risk From Chrysotile

    We welcome the appearance of this new analysis of asbestos related mortality which constitutes an important addition to the available evidence. We note that the lung cancer risk from this data highlighted by the authors and based on their internal analyses gives an identical risk factor to the one suggested as the 'best estimate' in our earlier meta- analysis (1): a relative risk of 1.102 per 100 f/ml.yr translates almost exactly to an excess over expected of 0.1% per f/ml.yr.

    The risk of mesothelioma derived from these new data is higher by a factor of 10 than that which emerged from our meta-analysis. The following table shows these new data (labelled N. Carolina) along with the chrysotile data used in our analysis.

    The generally small numbers mean that all the estimates are subject to substantial statistical error. The largest single set of observations is that derived from the Canadian mines, and this gives a low and (statistically) reasonably precise estimate of about 0.001. The remaining observations are statistically consistent (P=0.075); though mainly due to their imprecision, rather than to the similarity of the estimates. The statistical consistency is somewhat improved by also removing the Italian mines (Balangero) cohort (P=0.10). The mean risk taken across the remaining cohorts is 0.0070 with a confidence limit running from 0.0038 to 0.013.

    Combining the two mining cohorts gives a joint estimate of 0.00096 (95% CI 0.00069, 0.0013).

    The estimate from the latest study is based on eight cases. Assuming Poisson variability the underlying risk could correspond to between 4 and 16 cases. Up to three of the observed cases may be due to amosite exposure in plant 3, but it could also be argued that some mesothelioma cases may have been missed during the period prior to the introduction of ICD 10.

    An estimate of 0.007% per f/ml.yr still places the risk of mesothelioma from chrysotile at least an order of magnitude lower than the risk we estimate for the amphiboles fibres (0.5 for crocidolite, 0.1 for amosite). As we argued in our original paper, if the risk from chrysotile is indeed substantially lower than from the other fibre types then the level of risk observed in cohorts with mixed exposure provides an upper limit to the true risk for chrysotile on its own. In our meta-analysis four of the mixed fibre cohorts had mesothelioma risk estimates around or below the 0.01 level. In the largest of these (Ferodo) there is a strong indication that 11 of the 13 mesothelioma deaths were due to crocidolite exposure. Since the overall risk for this cohort was 0.014, the implied chrysotile risk in this setting (friction products) would be well below 0.01.

    These new results certainly strengthen the case for the proposition that the per fibre risk of mesothelioma from chrysotile in textile plants is greater than it is in the mines. Whether this differential also applies in other settings is not clear from the evidence above: the absence of mesothelioma deaths in the New Orleans and Connecticut cohorts is statistically consistent with a risk of 0.01 though, obviously, more consistent with the mines estimate of 0.001.

    John Hodgson Andrew Darnton

    Statistics Branch (Epidemiology Group) Health and Safety Executive Redgrave Court (S4.3) Merton Road Bootle L20 7HS United Kingdom Tel: 0151 951 4566 (fax 4703)

    1. JT Hodgson, A Darnton. The quantitative risks of mesothelioma and lung cancer in relation to asbestos exposure. Ann. occup. Hyg., Vol. 44, No. 8, pp. 565–601

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  2. Response to e-letter

    We welcome the comments on our systematic review on factors associated with the Work Ability Index (WAI) with regard to the practical implications of the WAI instrument. After reading the review, the author of the e-letter concludes that ‘the WAI should be used with caution outside samples of people with musculoskeletal disorders and that more robust psychometric data be produced in other groups’. The intended message of the review is that the WAI is a useful tool in the field of employability of (older) workers, and that various work-related and individual factors play a role in someone’s workability. Our review was restricted to those factors that are not incorporated in the work ability index itself and, thus, we have not investigated health complaints, such as musculoskeletal disorders, as determinants and also refrained from analyzing in which occupational populations the use of the work ability index may be warranted. We agree with Nicholas Glozier that the work ability concept is complex and needs further study. Since the work ability index is a summary score over different dimensions, caution is required in drawing conclusions on a decreased WAI score without further diagnosis of reasons for a decreased WAI and underlying mechanisms. Previous studies have shown that the WAI is a useful tool among workers in physically demanding professions[1] as well as among mentally demanding professions[2] to analyze factors at population level that influence employability of workers and, thus, may be considered for addressing in interventions.

    [1] Alavinia SM, van Duivenbooden C, Burdorf A. Influence of work- related factors and individual characteristics on work ability among Dutch construction workers. Scand J Work Environ Health. 2007 Oct;33(5):351-7.

    [2] van den Berg TI, Alavinia SM, Bredt FJ, Lindeboom D, Elders LA, Burdorf A. The influence of psychosocial factors at work and life style on health and work ability among professional workers. Int Arch Occup Environ Health. 2008 Aug;81(8):1029-36.

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  3. What is the extent of ability in workabilty?

    The systematic review of factors associated with the Work Ability Index raises significant questions about this measure. The paper repeats the assertion that "the bases for work ability are health and functional capacity, but work ability is also determined by professional knowledge and competence (skills), values, attitudes, and motivation, and work itself." Certainly clinicians are constantly asked to assess the health and functional components of an individual's work related problems and help with this aspect of assessment is welcome. However, as table 6 succinctly demonstrates, the WAI shows consistent null associations with three of the four health and functional capacity constructs - cardiorespiratory fitness, "mental performance" and poor balance. Whilst some of these may reflect type 2 errors in the initial studies from the ORs quoted in the table this is concerning if the WAI is to be used across a range of health conditions. The results of intervention studies, which appear to be detected as positive only in those interventions with physical function components, may reflect a lack of responsiveness of the instrument to other interventions targetting improvements in, for example, mental health. In summary this review suggests that the WAI should be used with caution outside samples of people with musculoskeletal disorders and that more robust psychometric data be produced in other groups.

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  4. Response to Swaen et al.

    Response to Swaen et al.

    Authors Craig Steinmaus1, 2 Allan H Smith1 Martyn T Smith1

    Authors affiliations 1. School of Public Health, University of California, Berkeley, University Hall, Berkeley, CA 94720-7360, USA 2. Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, 1515 Clay St., Oakland, CA 94612

    Corresponding author Craig Steinmaus, School of Public Health, University of California, Berkeley, University Hall, Berkeley, CA 94720-7360, USA e-mail: craigs@berkeley.edu

    Sir, The differences in methods between our meta-analysis and that of Swaen et al. did not “vastly alter” our most important finding or change our overall conclusion.1,2 Our major conclusion was that evidence of an association between benzene and non-Hodgkin lymphoma (NHL) could be found when analyses were focused on results from highly exposed workers and were appropriately adjusted for the healthy worker effect. In their analysis of high exposure benzene studies, Swaen et al. implemented a series of differences in the data used from the studies compared to our own. But despite the fact that every single one of their major changes resulted in a lowering of the summary relative risk, Swaen et al. also found a statistically significant elevated relative risk in the high exposure studies (RR = 1.33 (95% CI, 1.02-1.74)), just as we did. Even after they adjusted for heterogeneity, the relative risk remained statistically significant if correctly estimated. The one-sided p-value after this adjustment can be estimated from their confidence interval to be 0.03. Since our a priori hypothesis was that benzene increases, not decreases, the risk of NHL, a one-tailed p-value is clearly most appropriate here.

    The Swaen et al. use of the all-cancer standardized mortality ratio (SMR) to adjust for the healthy worker effect assumes that benzene or any of the other agents that the benzene-exposed workers are exposed to will not cause any other cancer type. However, benzene is a well known cause of leukemia and risks of this cancer were elevated in many of the studies used in our meta-analyses. Relative risks of other cancers such as lung cancer and mesothelioma were also elevated in some of the studies, probably due to co-exposures like asbestos that can commonly occur with benzene. Because of these increases in other cancers, the use of the all- cancer SMR probably biased the Swaen et al. summary relative risks towards the null. Without this bias, the Swaen et al. summary relative risks would have been higher than they reported and even more similar to our results than they already are. In any case, as we noted above, using different data and different methods, Swaen et al. have produced additional evidence that benzene increases the overall risk of non-Hodgkin lymphoma in the available studies to date in a manner which is unlikely to be due to chance.

    References 1. Steinmaus C, Smith AH, Jones RM, Smith MT. Meta-analysis of benzene exposure and non-Hodgkin lymphoma: biases could mask an important association. Occup Environ Med 2008; 65:371-8. 2. Swaen GMH, Tsai SP, Burns C. Meta-analysis on benzene exposure and non Hodgkin lymphoma (Letter to Editor). Occup Environ Med:TBD

    Copyright The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive license (or non- exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article to be published in Occupational and Environmental Medicine editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our license.

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  5. Meta-analysis on benzene exposure and non Hodgkin lymphoma

    Meta-analysis on benzene exposure and non Hodgkin lymphoma

    June 30 2009

    Gerard M H Swaen1 Shan P. Tsai2 Carol Burns1

    1 Department of Epidemiology, The Dow Chemical Company, Midland, Michigan USA. 2 Shell Health, Shell Oil Company, Houston Texas, USA.

    Corresponding Author: Gerard M H Swaen, The Dow Chemical Company, P.O. Box 444, 4530 AK Terneuzen, The Netherlands 31-(0)43-3626042. E- mail: gswaen@dow.com

    Key words: benzene, non Hodgkin lymphoma, epidemiology, meta- analysis, occupation, risk

    Sir, A recent meta-analysis on benzene exposure and non Hodgkin lymphoma (NHL) concluded that the reviewed epidemiological studies provide “new evidence that benzene causes NHL.” 1 The meta-analysis conducted by Steinmaus et al differed from the others in several aspects. Firstly, it selected subgroups with the highest putative exposure to avoid dilution. Secondly, cohort studies were adjusted for the Healthy Worker Effect (HWE) by considering the NHL deaths as cases and all other deaths as controls. A HWE for cancer endpoints is small if any, compared to non cancer endpoints.2. The results from a meta-analysis of 150 occupational cohort studies suggest that HWE adjustment may artificially inflate the true RR for cancer endpoints. 3 Thirdly, outdated cohort study results were used instead of more recent updates. Fourthly, Steinmaus et al did not consistently apply their own selection criteria. We have re-analyzed the Steinmaus et al meta-analysis by precisely applying their inclusion and exclusion criteria. These include selecting the highest exposure category relative risk (RR), selecting cancer incidence versus mortality data and we used the most recent results from cohort updates whenever available. To maintain consistency, we adjusted the RR estimates for the HWE by using the all cancer SMR of the selected sub cohort instead of the all mortality SMR. Herein we present only a summary table of results. Additional comparative tables are available upon request.

    There were 16 case-control studies included in the Steinmaus et al. review. We excluded the study by Dryver since it provided no odds ratio (OR) for benzene exclusively. For the Fabbro-Peray et al. study, Steinmaus et al selected the OR of those with over 810 days of exposure. However, we used the subcategory with exposure duration of over 15 years since it represents the group with longer exposure. For the study by Schnatter et al the OR for the highest intensity was 0 and Steinmaus et al selected the OR for the second highest exposure intensity group. We combined the highest and the second highest exposure intensity groups (OR=0.49 95% CI: 0.10-2.32). The revised meta-OR for the 15 case-control studies was 1.17 (95% CI 0.96 – 1.44) (see Table 1).

    For the six non refinery cohort studies, we observed inconsistencies in the authors’ use of the selection sequence. For the Bloemen study, the longest duration RR was used by Steinmaus et al. although RRs by cumulative exposure were given. We combined the two cumulative exposure categories into one category of 28.3+ ppm-years (SMR=0.63 95% CI: 0.08- 2.28). For the Rinsky study, we selected the RR for men (1.00), assuming that the men were higher exposed, since the jobs with benzene exposure were generally done by men. Lastly, for Wong et al. the RR for highest cumulative exposure was replaced with that for highest intensity exposure. The revised meta-RR for these non-refinery studies was 1.13 (95% CI: 0.80- 1.61) and a meta-RR of 1.05 (95% CI: 0.75-1.47) after adjusting for the HWE.

    In the meta-analysis of the refinery studies, as per the recommendations of Steinmaus et al., cancer incidence data were selected if both incidence and mortality were reported. There were two refineries included in the 1993 study published by Tsai, et al, and the combined results were used instead of selecting only one of the refineries. Additionally, we used the combined results from maintenance and process workers for the study conducted at the Beaumont refinery by Wong since it is unclear that process workers were more exposed. We selected results based on the longer duration of work for the study by Pukkala et al, following the Steinmaus et al. hierarchy. We used the updated data for the following refinery studies (Sorahan, Thomas and Tsai et al, 1996) 4 5 6. In the update by Tsai and colleagues NHL was listed as one of the specific disease categories, replacing reticulosarcoma used in the 1996 paper. We selected the updated RR although the longest duration of employment was shorter. 7 The revised meta-RR for the 21 refinery studies was 1.00 (95% CI: 0.89-1.12) and 1.06 (95% CI: 0.95-1.18) after adjusting for the HWE. All the models gave similar results and we only present those of the fixed model.

    All of the meta-RRs calculated in the re-analysis were less than those reported by Steinmaus et al and most were close to unity. The only meta-RR that remained statistically significant was that for the high exposure non refinery studies, consisting of four cohort studies and nine case-control studies (meta-RR of 1.33, 95% CI: 1.02-1.74), for which exposure was largely based on self-reported data. The statistical significance of this meta-RR was lost after adjustment for the heterogeneity effect (95% CI: 0.99-1.80).

    The re-analysis shows that the differences of the applied analytical methods and relative risks selected can vastly alter the overall meta- relative risk. The re-analyzed evidence provides little if any support for an association between benzene exposure and NHL.

    Gerard M H Swaen1, Shan P. Tsai2 Carol Burns1. 1 Department of Epidemiology, The Dow Chemical Company, Midland, Michigan USA.

    2 Shell Health, Shell Oil Company, Houston Texas, USA.

    Table 1 Summary results of the meta-analysis on benzene exposure and NHL and for refinery workers and NHL, comparing the results by Steinmaus et al to our findings (fixed models, other models gave similar results)).

    N RR as in Steinmaus RR in the re-analysis Benzene and NHL

    All studies 22 1.22 (1.03-1.46) 1.16 (0.97-1.38)

    Case control studies 16 1.23 (1.00-1.50) 1.17 (0.96-1.44)

    Cohort studies 6 1.21 (0.86-1.71) 1.13 (0.80-1.61)

    All high exposure studies 13 1.49 (1.15-1.92) 1.33 (1.02-1.74)1

    HWE adjusted cohort studies 6 1.22 (0.89-1.67 1.05 (0.75-1.47) Refinery work and NHL

    All studies 21 1.21 (1.06-1.38) 1.00 (0.89-1.12)

    High exposure studies 14 1.30 (1.04-1.62) 1.07 (0.87-1.31)

    HWE adjusted all studies 21 1.42 (1.25-1.62) 1.06 (0.95-1.18)

    HWE adjusted high exposure studies 14 1.51 (1.22-1.88) 1.20 (0.99- 1.47) 1 statistical significance was lost after adjustment for heterogeneity (95% CI: 0.99-1.80)

    References

    1. Steinmaus C, Smith AH, Jones RM, Smith MT. Meta-analysis of benzene exposure and non-Hodgkin lymphoma: biases could mask an important association. Occup Environ Med 2008;65(6):371-8.

    2. Li CY, Sung FC. A review of the healthy worker effect in occupational epidemiology. Occup Med (Lond) 1999;49(4):225-9.

    3. Greenberg RS, Mandel JS, Pastides H, Britton NL, Rudenko L, Starr TB. A meta-analysis of cohort studies describing mortality and cancer incidence among chemical workers in the United States and western Europe. Epidemiology 2001;12(6):727-40.

    4. Sorahan T. Mortality of UK oil refinery and petroleum distribution workers, 1951-2003. Occup Med (Lond) 2007;57(3):177-85.

    5. Dement JM, Hensley L, Kieding S, Lipscomb H. Proportionate mortality among union members employed at three Texas refineries. Am J Ind Med 1998;33(4):327-40.>

    6. Tsai SP, Ahmed FS, Wendt JK, Foster DE, Donnelly RP, Strawmyer TR. A 56-year mortality follow-up of Texas petroleum refinery and chemical employees, 1948-2003. J Occup Environ Med 2007;49(5):557-67.

    7. Tsai SP, Chen VW, Fox EE, Wendt JK, Cheng Wu X, Foster DE, et al. Cancer incidence among refinery and petrochemical employees in Louisiana, 1983-1999. Ann Epidemiol 2004;14(9):722-30.

    Licence Statement: The Corresponding author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence on a worldwide basis to the BMJ Publishing Group Ltd to permit this article (if accepted) to be published in OEM and any other BMJPGL products and sublicences such use and exploit all subsidiary rights, as set out in our licence

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  6. Regarding Mortality among British asbestos workers undergoing regular medical examinations

    Letter to the editor

    Mortality among British asbestos workers undergoing regular medical examinations (1971-2005). Occup Environ Med 2009; 66: 487-95.

    Bengt Sjögren, MD, PhD Work Environment Toxicology Institute of Environmental Medicine Karolinska Institutet P.O. Box 210 SE-171 77 Stockholm Sweden Tel +46 8 524 822 29 Fax +46 8 31 41 24 E-mail Bengt.Sjogren@ki.se

    Anne-Helen Harding and coworkers1 presented mortality data from 98117 asbestos-exposed workers and increased mortality due to ischaemic heart disease (IHD), SMR 1.40 (95% CI 1.36-1.44). There are good arguments for further scrutinizing this observation.

    Today it is rather established that inhalation of urban air pollutants are associated with increases in mortality and morbidity due to cardiovascular disease. This was observed in short-term, cohort and intervention studies and effects were seen at low concentrations.2

    Whether inhalation of asbestos fibers can cause IHD is today an unsolved question. Some studies show a relationship between asbestos exposure and IHD.

    A cohort of 3072 white male textile workers exposed to chrysotile was followed through 2001. An increased risk of ischemic heart disease was observed (SMR 1.20, 95%CI 1.10 – 1.32).3

    A cohort of about 11000 men employed in the chrysotile mines and mills of Quebec was followed until 1988. IHD was more common among those exposed to 300 or more million particles per cubic foot x years (SMR 1.24) compared with those exposed to less than 30 (SMR 0.92).4

    Non-smoking patients with asbestosis were compared with healthy controls. The asbestosis patients had significantly increased serum levels of inflammatory markers.5 During the last decade these markers of inflammation have emerged as risk factors for IHD. A general hypothesis about exposure to inhaled air pollutants and the occurrence of IHD can be expressed in the following way. Inhalation of particles will create a low grade inflammation associated with an increase in plasma fibrinogen and other blood clotting agents. A higher concentration of these agents will increase the likelihood for blood clotting and thereby the risk for myocardial infarction and IHD. 2

    I hope these arguments will encourage Harding and coworkers to further explore the relationship between asbestos exposure and the occurrence of IHD in internal analysis.

    Literature

    1. Harding A-H, Darnton A, Wegerdt J, McElvenny D. Mortality among British asbestos workers undergoing regular medical examinations (1971-2005). Occup Environ Med 2009; 66: 487-95.

    2. Sjögren B. Occupational exposure to air pollutants, inflammation and ischemic heart disease, Editorial. Scand J Work Environ Health 2004;30:421-423.

    3. Hein MJ, Stayner LT, Lehman E, Dement JM. Follow-up study of chrysotile textile workers: cohort mortality and exposure-response. Occup Environ Med 2007; 64: 616-625.

    4. McDonald JC, Liddell FDK, Dufresne A, McDonald AC. The 1891-1920 birth cohort of Quebec chrysotile miners and millers: mortality 1976-88. Br J Ind Med 1993;50:1073-1081.

    5. Lehtonen H, Oksa P, Lehtimäki L, et al. Increased alveolar nitric oxide concentration and high levels of leukotriene B4 and 8-isoprostane in exhaled breath condensate in patients with asbestosis. Thorax 2007; 62: 602-607.

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  7. Sinonasal Cancer and the Glassware Industry

    Sinonasal Cancer and the Glassware Industry.

    Pere Sanz-Gallén, Santiago Nogué, Eva Muñoz and Francisco Sabater*

    Clinical Toxicology Unit and *Otorhinolaryngology Service. Hospital Clínic. Barcelona

    Sir,

    The case-control study by D' Errico et al (1) on occupational risk factors for sinonasal cancer concludes that exposure to arsenic is one such factor and suggests more cases should be reported, as there are only two studies at present (2,3). We contribute a new case of a worker in the glassware industry, in order to reinforce the relationship between sinonasal cancer and occupational exposure to arsenic.

    A middle-aged, non-smoking patient was diagnosed more than a decade previously with squamous cell carcinoma affecting the left maxilla. The initial computed tomography (CT) scan had shown a lesion occupying the space of the left maxillary sinus that had destroyed the bone structure of the left maxilla and invaded the soft facial tissue and the pterygopalatine fossa. A CT scan more than a decade later after surgery and radiotherapy shows changes in the nasal fossa and left maxillary sinus, with a fibrotic mass of scar tissue.

    The patient worked in the glassware industry for over twenty years. The main materials forming the mix introduced in the glass furnace were silica, sodium carbonate, potassium carbonate, zinc oxide and lead oxide. The dyes, which represented 0.1% of the mixture, included cadmium sulphide and oxides of cobalt, copper, chromium, manganese and nickel. One per cent of arsenic trioxide was added to the mixture to increase the transparency of the glass. An onsite workplace study showed environmental levels of chromium and nickel <3 µg/m3, but levels of arsenic of 85 µg/m3 (Threshold Limit Value: 10 µg/m3).

    Although chromium and nickel oxides, known sinonasal carcinogens, are used in the glassware industry, the environmental levels found were very low. However, the levels of arsenic were very high, in agreement with the study by Battista et al in various glassware companies (3). Therefore, arsenic trioxide should be replaced by other metals and preventive measures should be introduced to minimize the health risks of workers exposed to these substances in the workplace.

    References

    1. d'Errico A, Pasian S, Baratti A, Zanelli R, Alfonzo S, Gilardi L et al. A case-control study on occupational risk factors for sino-nasal cancer. Occup Environ Med. Publish Ahead of Print, January 19, 2009

    2. Roth F. Uber den bronchialkrebs arsengeschadigter winzer. Virchows Arch Pathol Anat 1958;331: 119-137.

    3. Battista G, Bartoli D, Iaia TE, Dini F, Fiumalbi C, Ciglioli S et al. Art glassware and sinonasal cancer: report of three cases. Am J Ind Med 1996; 30: 31-35.

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  8. Biological monitoring of wood dust exposure

    Dear Editor,

    This informative article on the occupational wood dust exposure in Italy requests a monitoring method for received personal doses. Such a method exists exploiting samples obtained by nasal lavage (1). It is based on the the chemical analysis for wood polyphenols. Although they are species specific they are good quantitative indicators of hardwood dust particles coarse enough to be retained in the nasal passages.

    The wood tannins can also be analysed in the suspended dust in the work room air. This provides the advantage that it gives an idea of current dusts and previous materials which may not have been properly cleaned away (2).

    References

    1 Mämmelä P, Tuomainen A, Vartiainen T, Lindroos L, Kangas J, Savolainen H. Biological monitoring of wood dust exposure in nasal lavage by high-performance liquid chromatography. J environ Monit, 2002; 4: 187- 189

    2 Bianco M-A, Savolainen H. Woodworkers´ exposure to tannins. J appl Toxicol, 1994; 14: 293-295

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  9. Respiratory disease by diisocyanate exposure

    Dear Editor,

    As described in this investigation only a minority workers with an occupational asthma due to a diisocyanate exposure have specific IgE antibodies towards the monomers (1).

    Therefore, it is likely the host factors play an important role (2). However, their significance may not be so firm so as to be used as predictors of a disease. The concept is, however, important in the workers´ compensation cases if only those with specific antibodies or positive provocation test results outside the work place are accepted as valid cases.

    1 Savolainen H. New mechanistic model for organic diisocyanate- induced respiratory disease. Schweiz Med Wochenschr 1999; 129: 465-7.

    2 Berode M, Jost M, Ruegger M, Savolainen H. Host factors in occupational diisocyanate asthma: a Swiss longitudinal study. Int Arch Occup Environ Health 2005; 158-163.

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  10. Comments on Koppelaar et al

    Comments on Koppelaar et al, 'Determinants of implementation of primary preventive interventions on patient handling in healthcare: a systematic review'. OEM 2009;66:353-360

    Koppelaar et al put forward an interesting view on implementation in their article. They state that the results of interventions will depend not only on the effectiveness of the intervention itself but also on appropriate implementation in the actual work situation. However, the term implementation and the use of the supportive reference by Groll and Grimshaw are not used in their proper context here. The idea is that once an intervention has been shown to be effective, it should be implemented into health care, meaning that it should be used in 100% of the situations in which it is appropriate. Koppelaar et al confuse this with the actual process of the intervention in an evaluative trial. I think that these are two different processes with different determinants. Since there is no evidence of effectiveness of interventions that aim at preventing adverse health effects of handling patients by healthcare workers, these interventions should not be implemented in practice. If one would like to improve these types of interventions in research projects, there should be a clear idea of how the intervention works. Based on these ideas a maximum powerful intervention can be developed and evaluated. Once proven effective, the intervention should be implemented in health care. Also in their review the majority of the studies cited does not have a statistically significant positive outcome, neither is there a relation with the outcome of the study and the 'barriers and facilitators' for implementation.

    Moreover, we would like to point out that the review does not deserve the adjective systematic. The inclusion criteria are unclear because there is no definition of the study designs to be included. Arbitrarily, qualitative studies are excluded. The search is limited only to Medline and Web of Science and it is unclear why important databases such as Embase, Cinahl and OSHrom are not searched. There is language bias because only studies written in English are included. Especially for implementation, one could expect to find studies to be published in national languages. Even though it is an objective to assess the influence of barriers and facilitators on the effectiveness of interventions, there are no methods or results for this objective. The lack of an assessment of study quality in combination with the inclusion of any study type makes that the reader has no idea what the validity of the results of the included studies is. The authors acknowledge this as a limitation of their study in the discussion section. However, in my view, all these problems together make it impossible to interpret the results of the review.

    "The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive license (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Occupational and Environmental Medicine editions and any other BMJPG products to exploit all subsidiary rights, as set out in our licence

    Jos Verbeek, MD PhD Finnish Institute of Occupational Health Cochrane Occupational Health Field Kuopio Finland

    1. E Koppelaar, J J Knibbe, H S Miedema, A Burdorf. Determinants of implementation of primary preventive interventions on patient handling in healthcare: a systematic review. Occup Environ Med 2009;66:353–360. 2. Grol R, Grimshaw J. From best evidence to best practice: effective implementation of change in patients’ care. Lancet 2003;362:1225-29. 3. Campbell M, Fitzpatrick R, Haines A, Kinmonth A, Sandercock P, Spiegelhalter D, Tyrer P. Framework for design and evaluation of complex interventions to improve health. BMJ 2000;321:694–6 4. Moher D, Tetzlaff J, Tricco AC, Sampson M, Altman DG. Epidemiology and reporting characteristics of systematic reviews. PLoS Med 4(3);2007:e78. doi:10.1371/journal.pmed.0040078

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