Recent eLetters
Displaying 1-10 letters out of 208 published
-
Occupational Dermatitis
Submit responseIt is good to see some scientific rigour applied in this important area. It is interesting to note however that there is no definition of occupational dermatitis. It is a reportable and prescribed disease in the UK, and can cause major impact on workers who suffer from it, but the question is whether healthcare workers who have perhaps a period of dry skin managed with ease, should be regarded has suffering from an occupational disease. The answer to such a question is important to the context of this paper and to the subject as a whole. The title of the paper is on 'management' therefore relates to those who have the condition, but there are of course in addition, major issues of risk reduction and control, which must run in parallel. While the paper makes mention of sensitisation in its background section, this important group does not feature in the review. In its later sections the term occupational dermatitis, is often reduced just to 'dermatitis'. Does this mean that the recommendations apply equally to workers with non occupational skin problems, such as psoriasis or eczema, both in the pre-employment and in service situations?
Conflict of Interest:
None declared
-
Response to "Health benefits of traffic-related air pollution reduction in different socioeconomic groups: the effect of low-emission zoning in Rome." Cesaroni et al. 69:133-139 doi:10.1136/oem.2010.063750
Submit responseDear Editor,
Cesaroni et al make an assessment of the health benefits of a traffic management scheme in Rome based on changes in vehicle emissions and associated chronic risk factors(1). The authors estimate that a combination of the policy intervention and unrelated fleet changes caused a 38% reduction in the annual mean exposure of NO2 and a 29% reduction of PM10 within the 'railway ring' restricted zone between 2001 and 2005. The majority of this decrease was unrelated to the intervention, however, NO2 reductions specifically driven by the policy, were translated to 1387 years of life gained per 100,000 residents.
We strongly believe that such statements based solely on modelled and hence theoretical decreases in pollution require validation using empirical data. Measurements from the European Environment Agency's air quality database(2) show that measured annual mean NO2 concentrations within the 'railway ring' zone actually increased between 2001 and 2005 (80 ug/m3 to 82 ug/m3 at roadside site IT0946A and 39 ug/m3 to 41 ug/m3 at background site IT0953A). It is therefore evident that the assumptions used in the analysis did not reflect real world conditions.
Similarly, in studying the impacts of the London Congestion Charging Scheme, Kelly et al, found little evidence of a beneficial effect on monitored concentrations of NO2 and PM10, despite a large and sustained reduction in vehicle numbers(3). This was attributed to the relatively small area of the zone and an increase in the proportion of the vehicle fleet using diesel engines. It is also now widely accepted that the Euro emission standards are not delivering the predicted reductions in NOX(4).
While theoretical estimations of the health benefits of policy interventions are welcome, care should be taken to validate these estimates with empirical measurements wherever possible as man and machine rarely behave as predicted.
References:
1 Cesaroni G, Boogaard H, Jonkers S, Porta D, Badaloni C, Cattani G, Forastiere F, Hoek G. Health benefits of traffic-related air pollution reduction in different socioeconomic groups: the effect of low-emission zoning in Rome. Occup Environ Med. 2012;69(2):133-9.
2 http://www.eea.europa.eu/themes/air/airbase, accessed 08-mar-2012.
3 Kelly F.J., Anderson H.R., Armstrong B., Atkinson R, Barratt B., Beevers S.D, Derwent D., Green D., Mudway I., Wilkinson P., 2011. The Impact of the Congestion Charging Scheme on Air Quality in London. Research Report Number 155. Health Effects Institute, Boston, MA, USA. April 2011. Available from http://pubs.healtheffects.org/types.php?type=1.
4 Carslaw D.C., Beevers S.D., Westmoreland E., Williams W., Tate J., Murrells T., Stedman J., Li Y., Grice S., Kent A., Tsagatakis I., 2011. Trends in NOX and NO2 emissions and ambient measurements in the UK. Report for Defra, March 2011. Available from http://uk-air.defra.gov.uk/library/reports?report_id=645.Conflict of Interest:
None declared
-
Response to "The effect of high temperatures on cause-specific mortality in England and Wales." Gasparrini et al. 69:56-61 doi:10.1136/oem.2010.059782
Submit responseDear Editor,
High temperatures and mortality - even more relevant in desert environments.
Your editorial on exposure to high ambient temperatures and mortality is timely [1]. The Gasparrini et al.[2] paper on ambient air temperatures and mortality in temperate England and Wales provides further support for population-level preventive measures to reduce the likelihood of adverse health effects from elevated environmental temperatures.
The risk of heat-related illness and death is especially relevant to desert environments, such as in the United Arab Emirates (UAE), where summer temperatures can often exceed 50 degrees Celsius. In recent years, the risk of morbidity and mortality from heat exposure was compounded when the holy month of Ramadan coincided with summer in the Middle East. During Ramadan, Muslims abstain from consuming fluids or food during daylight hours. Additional risk factors for these workers are prolonged day shifts, strenuous outdoor manual work and inadequate rest breaks. Muslim workers constitute a majority of the expatriate workforce in several Middle Eastern countries. Preventive measures to reduce the likelihood of morbidity and/or mortality in this group are particularly pertinent over the next few years when Ramadan will again fall during summer. In the UAE, the Health Authority of Abu Dhabi developed a "Safety in the Heat" campaign which distributed educational materials in five different languages to over 800,000 outdoor workers focusing on self-monitoring hydration status using urine colour, adequate hydration before and after fasting, and self-pacing strategies whilst performing physical activity [3]. An environmental early warning system could be developed using a composite index of thermal stress incorporating several environmental parameters (i.e. dry bulb temperature, wet bulb temperature, wind speed and radiant heat). Another index is the Thermal Work Limit [4] which is a good indicator of heat stress in outdoor workers and would be a useful addendum to the Department of Health's Heatwave environmental monitoring plan [5].
1. Ebi KL. High temperatures and cause-specific mortality. Occup Environ Med 2012;69:3-4.
2. Gasparrini A, Armstrong B, Kovats S, Wilkinson P. The effect of high temperatures on cause-specific mortality in England and Wales. Occup Environ Med 2012;69:56-61.
3. Joubert D, Thomsen J, Harrison O. Safety in the Heat: A Comprehensive Program for Prevention of Heat Illness Among Workers in Abu Dhabi, United Arab Emirates, Am J Public Hlth 2011;101(3):395-398.
4. Brake DJ, Bates GP. Limiting metabolic rate (Thermal Work Limit) as an Index of Thermal Stress. App Occup Environ Hyg 2002;17(3):176-186.
5. Department of Health. Heatwave: Plan for England - Protecting Health and Reducing Harm From Extreme Heat and Heatwave. London: Department of Health, 2009.
Conflict of Interest:
None declared
-
Analyses of cadmium and kidney function in lead workers were adjusted for lead
Submit responseWe thank Dr. Kawada for his interest in our manuscript entitled "Associations of low-level urine cadmium with kidney function in lead workers."[1] As discussed in the methods and shown in the footnotes to Tables 3 and 4 in the manuscript, we adjusted for blood and tibia lead. We have presented lead analyses in this cohort in multiple past publications[2-8] so, in order to focus on the unique cadmium associations and comply with space considerations, we did not show the lead regression coefficients. Multiple linear regression was used in the analysis.
References:
1 Weaver VM, Kim NS, Jaar BG et al. Associations of low-level urine cadmium with kidney function in lead workers. Occup Environ Med 2011;68:250-256. doi:oem.2010.056077 [pii] 10.1136/oem.2010.056077 [doi] [published Online First 2010/10/27].
2 Weaver VM, Lee BK, Ahn KD et al. Associations of lead biomarkers with renal function in Korean lead workers. Occup Environ Med 2003;60:551- 62. 2003/07/29].
3 Weaver VM, Schwartz BS, Ahn KD et al. Associations of renal function with polymorphisms in the delta-aminolevulinic acid dehydratase, vitamin D receptor, and nitric oxide synthase genes in Korean lead workers. Environ Health Perspect 2003;111:1613-9. 2003/10/07].
4 Weaver VM, Jaar BG, Schwartz BS et al. Associations among lead dose biomarkers, uric acid, and renal function in Korean lead workers. Environ Health Perspect 2005;113:36-42. 2005/01/01].
5 Weaver VM, Lee BK, Todd AC et al. Associations of patella lead and other lead biomarkers with renal function in lead workers. J Occup Environ Med 2005;47:235-43. doi:00043764-200503000-00005 [pii] [published Online First 2005/03/12].
6 Weaver VM, Schwartz BS, Jaar BG et al. Associations of uric acid with polymorphisms in the delta-aminolevulinic acid dehydratase, vitamin D receptor, and nitric oxide synthase genes in Korean lead workers. Environ Health Perspect 2005;113:1509-15. 2005/11/03].
7 Weaver VM, Lee BK, Todd AC et al. Effect modification by delta- aminolevulinic acid dehydratase, vitamin D receptor, and nitric oxide synthase gene polymorphisms on associations between patella lead and renal function in lead workers. Environ Res 2006;102:61-9. doi:S0013- 9351(06)00002-8 [pii] 10.1016/j.envres.2006.01.001 [doi] [published Online First 2006/02/21].
8 Weaver VM, Griswold M, Todd AC et al. Longitudinal associations between lead dose and renal function in lead workers. Environ Res 2009;109:101-7. doi:S0013-9351(08)00215-6 [pii] 10.1016/j.envres.2008.09.005 [doi] [published Online First 2008/11/29].
Conflict of Interest:
None declared
-
Response to "Does self-reported computer work add biologically relevant information beyond that of objectively recorded computer work?"
Submit responseWe appreciate the careful reading of our editorial [1] by Drs. Mikkelsen and Andersen. We regret our omission of the one published NUDATA study available at the time our editorial was submitted [2]. That study reported significant associations between mouse usage time collected with memory resident software and both, acute neck pain and acute shoulder pain, among 2146 technical assistants. However, because i) median mouse usage time was 5.2 hours/week and median keyboard usage time was 0.9 hours/week, and ii) rates of moderate or greater musculoskeletal pain were very low among the participating computer users, we are concerned about the generalizability of the observed associations to workers with greater mouse and keyboard use.
Regarding differences in associations with musculoskeletal disorders (MSDs) observed across studies using self-reported estimates of computer use versus memory resident software documentation of computer use, we made no argument that one was correct and the other was incorrect. Rather, we raised the concern that these two exposure assessment methods capture different (but not totally unrelated) aspects of computer use relevant to MSD risk. The absence of perfect correlation between self-reported estimates of computer use and memory resident software documentation of computer use may be due to error in self report, differences in the kind of exposure information captured, or both. The claims of methodological objectivity and validity presented by Mikkelsen and Andersen do not address this fundamental question. We continue to believe, as noted in our editorial, that a better understanding of the attributes of work captured by self report and by computer registration software will clarify what appear to be inconsistent results reported by studies using them.
1. Gerr F, Fethke N. Ascertaining computer use in studies of musculoskeletal outcomes among computer workers: differences between self- report and computer registration software. Occup Environ Med 2011; 68: 465 -66.
2. Andersen JH, Harhoff M, Grimstrup S, et al. Computer mouse use predicts acute pain but not prolonged or chronic pain in the neck and shoulder. Occup Environ Med 2008;65 :126-31.
Conflict of Interest:
None declared
-
Does self-reported computer work add biologically relevant information beyond that of objectively recorded computer work?
Submit responseIn a recent editorial Gerr et al.[1] discuss computer work and musculoskeletal outcomes based on self-reported exposure versus objective recordings using computer software. They state that only one small study (n=27) using objective recordings was published before a large study by Ijmker et al.[2], published in the same issue as the editorial. They failed to consider the results of two NUDATA papers based on more than 2000 study participants, one of them published in the OEM[3]. The results of the study of Ijmker et al. and the NUDATA studies consistently indicate that sustained or severe pain outcomes were not related to objective computer work recordings. The editorial argues that the results of the study of Ijmker et al does not invalidate the much larger literature in which self-reported computer use was associated with musculoskeletal symptoms. The main argument seems to be that objective recordings do not capture the relevant exposures, e.g. holding the hands over the keyboard without keying and that different cut points for such non-activity periods may invalidate the objective recordings. However, objective software-based computer work recordings are in very good accordance with other objective measures like video- recordings, and much better than self-reported exposure. Furthermore, within reasonable limits, different cut-off values for non-activity periods do not change these relations or computer times very much. This is consistent evidence from several studies and not from "preliminary investigations", as stated in the editorial. Finally, exposure times based on different cut off's are highly correlated, and their relation to musculoskeletal outcomes will not vary much with different cut-offs [4]. Contrary to the editorial, we find it very unlikely that retrospective self-reports about computer use during several months should capture biologically important aspects of computer work which are not captured by a validated objective method, which prospectively collects exact computer use data on a daily basis.
References
1. Gerr F, Fethke N. Ascertaining computer use in studies of musculoskeletal outcomes among computer workers: differences between self- report and computer registration software. Occup Environ Med 2011; 68: 465 -66
2. IJmker S, Huysmans MA, van der Beek AJ, et al. Software-recorded and self-reported duration of computer use in relation to the onset of severe arm-wrist-hand pain and neck-shoulder pain. Occup Environ Med 2011; 68: 502-9
3. Andersen JH, Harhoff M, Grimstrup S, et al. Computer mouse use predicts acute pain but not prolonged or chronic pain in the neck and shoulder. Occup Environ Med 2008;65 :126-31.
4. Mikkelsen S, Lassen CF, Vilstrup I, et al. Does computer use affect the incidence of distal arm pain? A one-year prospective study using objective measures of computer use. Int Arch Occup Environ Health 2011 May 24 [Epub ahead of print]
Conflict of Interest:
None declared
-
Re:Analysis of job strain effects
Submit responseWe thank Dr. Mikkelsen and colleagues for their constructive comments on our paper. Our responses to their three major questions are listed below.
1) Why did we present various formulations of job strain?
The five formulations of job strain have been commonly reported in the literature. Often, authors chose one or two formulations and thus would not know if their results were consistent across different formulations. In our study, with the encouragement of an OEM peer reviewer, we presented results for all five formulations so that readers can compare the results both across different formulations and with previous job strain studies. We agree with Mikkelsen et al. that four of the five formulations of job strain we examined could be the result of the effect of job control only. As shown in Table 3, job demands was not significantly associated with IMT whereas job control was.
2) Why did we not show the main effect coefficients for job demands and control as we showed the coefficient for the multiplicative term in Table 4?
When a multiplicative term is included in a regression model, the main effects of the interacted variables have a more complex interpretation;1 that is, the coefficients represent the magnitude of effect for each variable when the other is 0. We showed the main effects of the two variables in Table 3, which represent the magnitude of each variable's effect when the other is controlled for. For the sake of brevity, we did not show the coefficients for demands and control after the multiplicative term was included in the model. This was explained in the footnote for Table 4.
3) Why did we illustrate the interaction in dichotomous terms (Figure 1) and ignored that high job demands were protective?
Figure 1 is an illustration of the interaction, which could have been constructed using the mean+1SD as "high" and the mean-1SD as "low" or other ways. We used the median split again for the sake of simplicity and also because it is a commonly used approach in the job strain literature. We do recognize that the demand-control model was only partially supported in our study; that is, job control was protective only for those who reported high job demands. Overall, job demands did not have a significant association with IMT, as shown in Table 3. The following paragraph is our discussion on this finding from an earlier draft. Unfortunately, this paragraph was excluded from the final version because of the word limit.
Contrary to the demand-control model's prediction,2 we did not find significant associations between IMT and job demands. The Cardiovascular Risk in Young Finns Study also failed to find the same significant association.3 The majority of CVD studies have found positive associations between job demands and CVD,4 but Belki? et al.4 identified five studies that reported an inverse association between psychological job demands and CVD.5-9 In the MESA cohort, of which about 30% were immigrants, the job demands scale had acceptable scale reliability among U.S.-born participants but not among immigrants (Cronbach's alpha = 0.75 for U.S.-born, ranged from 0.45 to 0.65 for immigrants, depending on the language used in data collection10). Limitations in the measure of job demands used in heterogeneous samples like ours may have limited our ability to detect associations of job demands with IMT.
References:
1. Cohen J, Cohen P. Applied Multiple Regression: Correlation Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum, 1983.
2. Karasek RA. Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative Science Quarterly 1979;24:285-308.
3. Hinsta T, Kivim?ki M, Elovainio M, Vahtera J, Hintsanen M, Viikari JSA, et al. Is the association between job strain and carotid intima-media thickness attributable to pre-employment environmental and dispositional factors? The Cardiovascular Risk in Young Finns Study. Occupational and Environmental Medicine 2008;65:676-82.
4. Belki? KL, Landsbergis PA, Schnall P, Baker D. Is job strain a major source of cardiovascular disease risk? Scand. J. Work Environ. Health 2004;30(2):81-128.
5. Alterman T, Shekelle RB, Vernon SW, Burau KD. Decision latitude, psychologic demand, job strain and coronary heart disease in the Western Electric Study. American Journal of Epidemiology 1994;139:620-27.
6. Bobak M, Hertzman C, Skovoda Z, Marmot MG. Association between psychosocial factors at work and non-fatal myocardial infarction in a population based case-control study in Czech men. Epidemiology 1998;9:43- 47.
7. Hall EM, Johnson JV, Tsou TS. Women, occupation, and risk of cardiovascular morbidity and mortality. Occupational Medicine 1993;8:709- 19.
8. Johnson JV, Stewart W, Hall EM, Fredlund P, Theorell T. Long-term psychosocial work environment and cardiovascular mortality among Swedish men. American Journal of Public Health 1996;86:324-31.
9. Steenland K, Johnson JV, Nowlin S. A follow-up study of job strain and heart disease among males in the NHANES1 population. American Journal of Industrial Medicine 1997;31:256-59.
10. Fujishiro K, Landsbergis P, Diez Roux AV, Hinckley Stukovsky K, Shrager S, Baron S. Factorial invariance, scale reliability, and validity of the decision latitude and psychological demands scales for immigrant workers: The Multi-Ethnic Study of Atherosclerosis (MESA). Journal of Immigrant and Minority Health 2010;13:533-40.
Conflict of Interest:
None declared
-
Exposure to keyboard/mouse use = keystrokes + mouse clicks + POSTURE - a missing variable that cannot be overstated
Submit responseSelf-report of duration of computer use is usually overestimated. The search for a valid measure of exposure to keyboard/mouse use resulted in the development of a computer registration software. The use of this new software generated unexpected results when IJmker et al.1 found software- recorded computer use was not significantly associated with upper extremity/neck symptom onset while self-reported computer use was signficantly associated with symptoms in the neck/shoulder and arm/hand. What is captured in the self-report that is missing in the software- recorded duration of computer use? In the editorial by Gerr and Fethke2 reference is made to work by Homan and Armstrong3 that noted the potential negative effect of time spent with hands held over the keyboard but without keying. In our Medical-Ergonomic Program4 we refer to this position as the 'action ready' posture when the forearm(s) is in full pronation over the keyboard or mouse causing muscle activation of the forearm extensor muscles. This may lead to the development of painful trigger points in the forearm extensor muscles, a common area of complaints by computer users.4 Activities such as reading, talking, thinking etc. while using the computer are frequently accompanied by this 'action ready' posture. Time spent in these activities is included when self-reporting duration of computer use but would not be captured in computer registration software.
Other posture issues without keystrokes or mouse clicks involve the neck/shoulder area. Computer users have a habit of not sitting up straight against the back of the chair and carry their shoulders forward. This posture activates the muscles involved with scapulae stabilization and shortens the pectoralis minor4 resulting in painful trigger points in the overused muscles . Neck/shoulder muscles are also activated when mouse use is with the arm extended away from the body, when the monitor is too far away and the chin juts forward or when the keyboard is too high and the shoulders remain hiked to compensate. Maintenance of these postures with or without keystrokes and mouse clicks are an etiology for upper extremity symptoms that needs to be added to the exposure equation for computer use.
1. IJmker S, Huysmans MA, van der Beek AJ, et al. Software-recorder and self-reported duration of computer use in relation to the onset of severe arm-wrist-hand pain and neck-shoulder pain. Occup Environ Med 2011;68:502-209.
2. Gerr F and Fethke N. Ascertaining computer use in studies of musculoskeletal outcomes among computer workers: differences between self- report and computer registration software. Occup Environ Med 2011;68:465- 466.
3. Homan MM and Armstrong TJ. Evaluation of three methodologies for assessing work activity during computer use. AIHA J (Fairfax, VA) 2003;64:48-55.
4. Bleecker ML, Celio MA, Barnes SK. A medical-ergonomic program for symptomatic keyboard/mouse users. JOEM 2011;53:561-567.
Conflict of Interest:
None declared
-
Analysis of job strain effects
Submit responseFujishiro et al.1 recently published data on the association of job demands and control with carotid artery intima-media thickness (IMT). The joined effect of demands and control (strain) was analyzed by five different strain definitions: 1. a quadrant term (median splits of demands and control), 2. combinations of tertiles of demands and control, 3. an additive term (demands minus control) , 4. a quotient term (the ratio) and 5. a multiplicative term (the product).
The first three terms are linear combinations of demands and control, which are less informative than the corresponding linear combination based on regression analyses of the mutually adjusted effects of demands and control. The quotient term implies interaction between demands and control but does not examine if there is one, its size, form or statistical significance. An effect of any of the first four strain terms may be due to an effect of only one of the two factors. Why introduce a strain measure of the joined effect of demands and control, if it may only reflect the effect of one of these variables? A parsimonious and informative way to examine the joined effect of demands and control is regression analyses with demands, control and their multiplicative term included as covariates. The authors published the effects of the multiplicative term but not the main effects. These are needed to evaluate the form of any interaction. The authors only illustrate the form of the interaction by dichotomous combinations of demands and control. The authors interpret the interaction as confirmation of the job strain theory because high job control protected against thick IMT, especially among persons with high job demands. However, they overlook that high job demands also protected against thick IMT. The interaction effect as a whole was not in accordance with the job strain model.
References 1. Fujishiro K, Diez Roux AV, Landsbergis P, et al. Associations of occupation, job control and job demands with intima-media thickness: The Multi-Ethnic Study of Atherosclerosis (MESA). Occup Environ Med 2011;68:319-326.
Conflict of Interest:
None declared
-
A dose-response for asbestos
Submit responseThe article by Clin et al. (1) provides additional information for a dose-response relationship with asbestos and cancer. Information where a response curve changes effect as observed from background is critical in establishing a safe exposure limit (threshold -exposure/concentration- dose). Some investigators have reported this threshold is around 25 fiber/ml-years (2); although for some members of an exposed group this may be lower (3). However, a cumulative no-effect value does not provide information applicable for practical every day use when monitoring worker exposure.
Recent studies (4,5,6) have suggested levels of exposure where there was no excess increase in cancer, notably lung cancer and mesothelioma. This is especially noted for non-smokers where risk does not exceed unity (lung cancer), even for high asbestos exposure, while there is a significant increased risk for smokers and former smokers (6,7). Thus, it appears smoking is the primary contributor and confounder of disease for historical and current asbestos workers (6). Compounding this issue is the high number of smokers performing asbestos abatement work (approximately 60% or greater depending on the population observed even at the present time) (8,9). The high rate of smoking makes it difficult to estimate a threshold and subsequently establish an exposure value from this type of information. Certainly, for today's asbestos workers smoking constitutes their greatest risk (6,9,10). Recent studies with direct (4,5) and indirect (e.g. Job Exposure Matrix and Job Specific Modules) (6,11) exposure information do allow an estimate of a threshold exposure dose. Although, exposure can greatly vary over time (4), it appears even with mixed fiber exposure (chrysotile and amphibole) (5) a threshold of 1.0 f/ml-year is applicable, but at the upper range. If chrysotile alone is used in this estimate, it appears a higher value would be warranted (5). Taken together, with a safety margin to include a lower reported value in causation of asbestosis (about 23 f//ml - years) (11), a threshold of 0.8 f/ml-year would appear applicable (20 f/ml - years). From this, using a work time period of 25 years, which is not likely for asbestos workers in the United States, due to physical demands of the occupation and actual length of the "industry", allows suggestion for a threshold of 0.8 f/ml-Time Weighted Average. When present exposure levels are included in this evaluation (12), it is unlikely workers in developed nations will exceed a cumulative exposure of 20 or 25 fiber/ml-years. Comparison of this proposed threshold with data reported by Clin et al., for lung cancer and mesothelioma, with 25 years or less of exposure (table 1 in Clin et al.), provides support for this threshold value. However, any value will be controversial, especially in establishing a threshold.
References
1. Clin B, Morlais F, Launoy G, Guizard AV, Dubois B, Bouvier V, Desoubeaux N, Marquignon MF, Raffaelli C, Paris C, Galateau-Salle F, Guittet L, Letourneux M. Environ Occup Med 2011; First online March 15, 2011.
2. Lange JH. Emergence of a New Policy for Asbestos: A Result of the World Trade Center Tragedy. Indoor and Built Environment 2004; 12:21-33.
3. Pierce JS, McKinley MA, Paustenbach DJ, Finley BL. An evaluation of reported no-effect chrysotile asbestos exposures for lung cancer and mesothelioma. Crit Rev Toxicol. 2008;38:191-214.
4. Sichletidis L, Chloros D, Spyratos D, Haidich AB, Fourkiotou I, Kakoura M, Patakas D. Mortality from occupational exposure to relatively pure chrysotile: a 39-year study. Respiration. 2009;78:63-8.
5. Dodic Fikfak M, Kriebel D, Quinn MM, Eisen EA, Wegman DH. A case control study of lung cancer and exposure to chrysotile and amphibole at a slovenian asbestos-cement plant. Ann Occup Hyg. 2007 51:261-8.
6. Frost G. The joint effect of asbestos exposure and smoking on the risk of lung cancer mortality for asbestos workers (1971-2005). 2011; Health & Safety Executive (HSE); (http://www.hse.gov.uk/research/rrhtm/rr730.htm)
7. Frost G, Darnton A, Harding AH. The effect of smoking on the risk of lung cancer mortality for asbestos workers in Great Britain (1971- 2005). Ann Occup Hyg. 2011 55:239-47.
8. Frost G, Harding AH, Darnton A, McElvenny D, Morgan D. Occupational exposure to asbestos and mortality among asbestos removal workers: a Poisson regression analysis. Br J Cancer. 2008 99:822-9.
9. Lange JH, Mastrangelo G, Buja A. Smoking and alcohol use in asbestos abatement workers. Bull Environ Contam Toxicol 2006 77:338-42.
10. Harding A-H, Darnton A, Wegerdt J, McElvenny D. Mortality among British asbestos workers undergoing regular medical examinations (1971- 2005). Occup Environ Med 2009;66487-495.
11. Mastrangelo G, Ballarin MN, Bellini E, Bicciato F, Zannol F, Gioffr? F, Zedde A, Tessadri G, Fedeli U, Valentini F, Scoizzato L, Marangi G, Lange JH. Asbestos exposure and benign asbestos diseases in 772 formerly exposed workers: dose-response relationships. Am J Ind Med 2009 52:596-602.
12. Lange JH, Sites SL, Mastrangelo G, Thomulka KW. Exposure to airborne asbestos during abatement of ceiling material, window caulking, floor tile, and roofing material. Bull Environ Contam Toxicol 2006 77:718- 22.
Conflict of Interest:
None declared
This recent issue is free to all users to allow everyone the opportunity to see the full scope and typical content of
OEM.
View free sample issue >>
Don't forget to sign up for content alerts so you keep up to date with all the articles as they are published.
