Ann. occup. Hyg., Vol. 48, No. 3, pp. 285-297, 2004
© 2004 British Occupational Hygiene Society
Published by Oxford University Press
Patterns of Dermal Exposure to Hazardous Substances in European Union Workplaces
1 Health & Safety Executive, Magdalen House, Stanley Precinct, Bootle L20 3QZ, UK; 2 Health and Safety Laboratory, Broad Lane, Sheffield S3 7HQ, UK; 3 National Institute for Occupational Safety and Hygiene, Autopista de San Pablo s/n, PO Box 3037, 41080 Sevilla, Spain; 4 National Institute for Working Life, Programme for Chemical Exposure Assessment, PO Box 7654, SE-907 13 Umeå, Sweden; 5 Division of Environmental and Occupational Health, Institute for Risk Assessment Sciences, Utrecht University, PO Box 80176, Utrecht, The Netherlands; 6 TNO Nutrition and Food Research, Department of Chemical Exposure Assessment, PO Box 360, Zeist, The Netherlands; 7 Institute of Occupational Medicine, Research Park North, Riccarton, Edinburgh EH14 4AP, UK; 8 Kuopio Regional Institute of Occupational Health, PO Box 93, FIN-70701 Kuopio, Finland
Received 14 July 2003; in final form 23 December 2003
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
Workplace dermal exposure assessment is a complex task that aims to understand the dynamic interaction between the skin and the hazardous substances present in the surrounding environment. A European project known as RISKOFDERM gathered dermal exposure data in 85 workplaces (industrial and other types) in five countries in Europe. In order to optimize data collection and to develop a representative picture of dermal exposure, scenarios (tasks made up of a series of activities) were grouped together into dermal exposure operation units (DEOs). The allocation of scenarios to relevant DEOs was achieved on the basis of similarities of exposure routes, tasks and professional judgement. Sampling and quantification procedures were based on the approaches recommended by the OECD protocol. The laboratories involved in the analysis of the samples participated in quality assurance programmes. This exercise resulted in 419 body measurements and 437 measurements on hands expressed in terms of formulation (product) in use. Exposures for a given scenario varied by several orders of magnitude. The extent and patterns of exposure were found to be dependent on various exposure determinants, including inter- and intra-scenario variations. Hands were found to be the most contaminated parts of the body. Exposure patterns for liquid and solid contaminants were different. On the basis of the analysis of the data presented here, the averaged results (median and 95th percentile) for a given DEO unit should not be used as a representative measure of dermal exposure for all scenarios within that DEO without taking the exposure determinants into account. However, the data could be used to develop an exposure matrix (indicative exposure distributions) for different types of scenario and workplace, using determinants of exposure and a Bayesian approach to integrating expert opinion.
Keywords: dermal exposure; dip coating; hazardous substances; manual dispersion; patch sampling; skin; spray dispersion
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
Following the growing realization of the importance of dermal exposure during the 1980s and 1990s, a dermal exposure assessment project (RISKOFDERM, 1999) was funded by the European Union 5th Framework Programme. One of its purposes was to determine the patterns of dermal exposure to hazardous substances used in a variety of workplaces in the European Union. The main purpose of the exposure data was to aid the development of predictive dermal exposure models for exposure predictions (Marquart et al., 2003; van Hemmen et al., 2003) that would in turn be used in a ‘Toolkit’ to aid dermal exposure risk assessment and control, especially for small and medium sized enterprises (Oppl et al., 2003).
This paper summarizes the results of the dermal exposure surveys and explores (i) the relationship between work scenarios and exposure patterns and (ii) whether the measurements obtained can be used to assess exposure levels for comparable scenarios. A more detailed statistical treatment of factors contributing to the variability in dermal exposures is presented elsewhere in this issue (Kromhout et al., 2004).
|
DERMAL EXPOSURE |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
Dermal exposure may be defined as the amount of chemical substance contacted by the outer layer of the skin and being available for dermal uptake (Environmental Protection Agency, 1996) and/or for producing an effect on the surface of the skin. But the interaction of the skin with the surrounding environment and contaminants is influenced by many factors. The contact is non-uniform, multidirectional and multicompartmental and these present a great challenge in determining and interpreting dermal exposure. The complications are illustrated in the conceptual model proposed by Schneider et al. (1999). In this model, dermal exposure normally occurs by one or more of three pathways:
- direct contact, including immersion—the skin comes into direct contact with the contaminants;
deposition—aerosolized contaminants impact or settle on the skin;
surface contact—the skin comes into contact with contaminated surfaces.
Due to the attenuating abilities associated with personal protective equipment (PPE) and clothing ensembles, two descriptors of dermal exposure patterns are used in the scientific literature to describe and measure dermal exposure (Chester and Hart, 1986; Health & Safety Executive, 1999; Phillips and Garrod, 2001).
- Potential dermal exposure (PDE) is an estimate of the amount of contaminant landing on the outside of the work wear or PPE and on the exposed surfaces of the skin.
- Actual dermal exposure (ADE) is an estimate of the amount of contaminant actually reaching the outer layer of the skin, which includes exposed skin surfaces. It takes account of the attenuation characteristics of workwear and PPE.
- Actual dermal exposure (ADE) is an estimate of the amount of contaminant actually reaching the outer layer of the skin, which includes exposed skin surfaces. It takes account of the attenuation characteristics of workwear and PPE.
|
MATERIALS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
Partners
The exposure surveys were conducted in five countries (Finland, Spain, Sweden, The Netherlands and the UK) by seven research institutions: Kuopio Regional Institute of Occupational Health (KRIOH) (Mäkinen and Linnainmaa, 2004a,b, personal communication); National Institute for Occupational Safety and Hygiene (INSHT) (Delgado et al., 2004); National Institute for Working Life (NIWL) (Eriksson and Wiklund, 2004; Eriksson et al., 2004); TNO Nutrition and Food Research (TNO) (Gijsbers et al., 2004); University of Utrecht (UU) (Fransman et al., 2004); Health and Safety Laboratory (HSL) (Roff et al., 2004a,b) and Institute of Occupational Medicine (IOM) (Hughson and Aitken, 2004).
Tasks, Scenarios and Industrial Sectors
The survey results were intended to provide a generic approach for predicting and assessing dermal exposure when a given scenario is undertaken. As it was impossible to survey all scenarios, the first step was to group scenarios that were considered similar in nature and that were likely to give rise to exposure mainly by the same pathway or from similar combinations of more than one pathway. This was to aid the development of predictive dermal exposure models that used determinants specific to those pathways and the development of the risk assessment toolkit described in several papers in one issue (Goede et al., 2003; Marquart et al., 2003; Oppl et al., 2003; Schuhmacher-Wolz et al., 2003; van Hemmen et al., 2003; Warren et al., 2003). The grouping of scenarios was done on the basis of similarities of exposure routes, tasks, professional experience and judgement. The groups developed were termed dermal exposure operation units (DEOs). The DEOs and the scenarios encompassed within each DEO are detailed in Appendix Table A1. The qualities desirable of any scenario and DEO were that dermal exposure should be: observable, measurable, attributable to the task within the scenario and applicable to many industries (van Hemmen et al., 2003). To ensure coverage, it was agreed between partners that at least two scenarios should be selected for workplace exposure assessment in each DEO. The selection of a particular scenario was dependent on partner preference subject to the constraints of ensuring coverage. It was important for the modelling that the targeted scenarios should be carried out in isolation and not ‘tainted’ with other tasks that might also give rise to measurable levels of dermal exposure. The requirement to stop sampling whenever a change of scenario took place often led to short exposure times and this caused more not detecteds (NDs) than was anticipated. Because of the difficulties involved in identifying suitable worksites it was necessary to substitute certain scenarios by others within the same DEO. For each scenario studied, the partners were expected to collect 30 ADE or PDE samples for hands and 30 PDE samples for body. Each partner was to target one large (>100 employees) enterprise and two medium or small ones. Wherever possible, the sites were visited on a maximum of two occasions to sample the same workers. This was to allow intra-subject variability to be estimated and to prevent over-reliance on individuals within the data set. However, this was not always possible, especially at small firms, either because the same scenarios were not performed on the second visit due to fluctuating workload or were not performed by the same people.
|
The scenarios, substances monitored, partners involved and the industrial sectors visited during the survey are summarized in Appendix Table A2. Over 270 subjects were monitored (some of them several times) at 85 worksites (industrial and other types). This exercise resulted in 490 body measurements and 537 measurements on hands. These break down into potential and actual dermal exposure measurements in terms of formulations or analytes, as set down in Appendix Table A2.
|
Sampling methods
The data reported here were obtained by using either ‘surrogate skin’ methods (Fenske, 1993), in which gloves and patches or whole body suits were used as sample collection media, or by using ‘removal’ methods, of washing or wiping the skin. Chemicals recovered from the collection media were subjected to suitable assay.
For patch sampling, as a general rule, eleven 10 x 10 cm patches (effective sampling area) were located on the body following the recommendations in the OECD Guidance Document (OECD, 1997). The surface areas of the body represented by each patch were standardized to represent an 80th percentile man, taken from Table A1 of the Guidance Document. The total body area was 18 720 cm2 and the hand areas 410 cm2 each. Whole body suits were of flash-spun polypropylene and analysed either by sectioning (cutting out suitable sized patches), by non-destructive analysis or by solvent extraction of the entire suit. Wipes and washes were limited to hands and foreheads.
Thin cotton sampling gloves worn beneath chemical protective gloves were used to measure ADE. Alternatively, ADE was measured by hand washing. PDE was measured using cotton gloves or charcoal patches over the protective gloves. Sampling of bare (unprotected) skin by any method counted as both ADE and PDE for that area. Sampling methodologies and analytical techniques are described in detail in the individual partners’ papers and are summarized in Appendix Table A3. The analytes themselves are listed in Appendix Table A1.
|
All the laboratories involved in the analytical work were subject to quality assurance schemes. In accordance with the OECD Guidance Document, all of the sampling media were subjected to storage stability tests (unless stability was already known) and analysis for background levels to estimate detection limits. For in-field validation, field blank samples were collected. Field spiked samples were prepared wherever practical.
Recovery efficiencies were determined in the laboratory by spiking known amounts of either the analyte or the commercial formulation of interest onto the various sampling media and subjecting them to the same extraction and assay as the field samples. Low and high levels of spikes tested whether recovery efficiency was dose-dependent.
Limit of detection (LOD)
All results were corrected for background using laboratory blank samples. LOD was defined as the mean plus three times the arithmetic standard deviation of the laboratory blanks (Keith et al., 1983). Where no blank signal was obtained, LOD was set to the instrument detection limit, which is three times the baseline noise of the instrument. Where a sample was determined to be ND, i.e. <LOD, a value of LOD was assigned. Some patch locations were assumed to be ND and were not measured during the main study to reduce analytical costs. These assumptions were based on pilot studies where measurements had been taken, all of which proved to be ND. The decision to assume ND or not was taken case-by-case by the field teams using their professional judgement. For example, during a small-scale handling task, the back was assumed ND. In some cases, the assumption was used to improve the accuracy of the OECD patch extrapolation method, where contamination was local. For example, in a handling study, a patch normally representing the entire upper leg was assumed to be ND on the rear half and as per the measured patch sample on the front half. Absence of the coloured contaminant on the white overall confirmed the assumption. The results were weighted to represent half of the standard surface area of the body location as LOD and half as the patch sample to yield a more accurate result.
Limit of quantification (LOQ)
LOQ was defined as the mean plus 10 times the standard deviation of the blank samples (Keith et al., 1983). Where no blank signal was obtained, LOQ was set using other methods, e.g. 3.3 times the instrument detection limit or the lowest calibration point. For the remainder of this paper, results were assigned as LOD if ND or as the measured value if <LOQ. A body result consisting of multiple patches could contain elements of all three outcomes, >LOQ, <LOQ or ND.
Units of dermal exposure
Dermal exposure measurement results may be presented in many ways. The units of measurement used may depend on user preference and the end uses of the data. In this paper exposure measurements are described as µg formulation/cm2/h. These units allow comparison of measurements taken for different sampling times (assuming a linear contamination rate) and different constituents (analytes) present in the given formulations. This provides information on the amount of generic formulation landing on a unit area of the skin or clothing per hour. This approach is consistent with those recommended in the OECD guidelines (OECD, 1997). As the exposure ranges are so wide and variable, all measurements are rounded to two significant figures.
|
RESULTS AND DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
To take account of the concerns expressed by Vermeulen et al. (2000) that standardized exposure assessment strategies are lacking because of problems concerning quantification and interpretation of dermal exposure data, it should be borne in mind that when designing and conducting dermal exposure surveys of this magnitude consistent sampling and analytical methods must be used. In this survey it was not possible to enforce rigorous controls towards uniform approaches for several reasons, which included the following: (i) the way PDE and ADE are defined; (ii) the techniques for dermal exposure sampling are still developing and are not mature, for example the selection of pad materials and positioning of pads; and (iii) the varied nature of the analytes, cost of analysis, work situations and work clothing regimes. Although a unified approach would help to improve consistency which could help towards improving the data set, no one methodology was suitable for all analytes or all work situations studied in this survey. We believe that the lessons learned in this study will help future developments in dermal exposure monitoring.
On the other hand, it is very costly and time consuming to obtain dermal exposure measurements. In this study the cost of obtaining a single measurement (for body and hands) amounted to >1000 euros. In addition, there is an urgent need to reduce dermal exposure to chemicals (Health and Safety Commission, 2001; Rycroft et al., 2001). Exposure information is also needed for policy development and control systems assessment. Therefore, it is necessary to utilize the data obtained in this study judiciously by recognizing its limitations and by making sure that the use of the data will not compromise the safety of individuals.
In order to compare dermal exposure patterns within and between DEOs and scenarios, only results that relate to formulations are used in the rest of this paper. Some of the results obtained as analytes were not convertible to formulation either due to lack of details about the product or to evaporation of the product/analyte from the sampling medium or to multiple sources of analyte (those sources not forming part of the scenario monitored). The distribution of measurements obtained were strongly skewed (Fig. 1). Analysis of the data is based on the assumption of log normality, although median values are compared wherever possible. Differences between medians and geometric means (GMs) in the tables indicate departure from log normality.
|
Potential exposure of the body
To determine the extent of potential dermal exposure of the body (excluding hands) a subset of 418 samples was used. The remainder were either unsuitable as explained above or missing because some measurements were confined to the hands only. Of the 418 samples, 79 (18.9%) were ND. DEO 1 (handling objects) contains the most NDs, at 45%, and DEO 4 (spray dispersion) the fewest, at 1%. This information indicates that in many exposure situations body areas are not subjected to significant exposure. The potential body dermal exposure ranged from 0.0006 to 6800 µg/cm2/h. Table 1 summarizes the potential dermal exposures (body) in the six DEO units.
|
In general, GSDs reported in Table 1 are much larger than those reported in the literature of single studies from a specified scenario in one industrial sector. In this study different industrial sectors and scenarios with a wider range of GMs contributed to the DEOs. The GSD for DEO 1 is 26 and this appears to be weighted by the loading scenario (1.8, see Table 3).
|
Other factors may also contribute to the potential for the creation of subsets within a DEO. These include variations in work practices employed within and between industrial sectors, even though the scenario studied was the same, and may also include attributes associated with sampling and analytical methodologies. A detailed statistical treatment of some of the factors contributing to the variability in dermal exposure is described by Kromhout et al. (2004). The analysis of all factors affecting exposure within DEOs is beyond the scope of either this paper or that of Kromhout et al. and is the ongoing task of the exposure modellers. The DEOs themselves do not necessarily account for differences in dermal exposures, but some differences between DEOs are apparent. The GMs obtained for DEO 1 (handling objects) and DEO 2 (manual dispersion) are 10 and 280 µg/cm2/h, respectively, and these two DEOs differ significantly from one another (P = 3 x 10–7 using pooled variance t-test). The GMs for DEO 2 (manual dispersion without hand-held tools, 280 µg/cm2/h) and DEO 3 (manual dispersion with hand-held tools, 250 µg/cm2/h) are not significantly different (P = 0.71 using pooled variance t-test). Thus, the use of hand-held tools appears to have little impact on body exposure, but is more likely to affect hand exposure (discussed later).
The median and GM values for spray dispersion (DEO 4) are 78 and 80 µg/cm2/h, respectively. These values differ from those obtained in comparable single studies reported elsewhere (Garrod et al., 1998, median = 630, GM = 1020; Phillips and Garrod, 2001, median = 330), but the GSD values reported are similar here (DEO 4, GSD = 4.2) and in those studies (Brouwer et al., 2000, GSD = 3.8; Garrod et al., 1998, GSD = 4.5). The measured exposure ranges varied by many orders of magnitude in all studies.
Table 2 provides a comparison of body exposure results to liquid and solid contaminants. This comparison was only possible for DEOs 1, 4 and 6, the other DEOs containing only liquid formulations. In DEO 1 the variation in median exposure levels between liquid and solid contaminants is 
170 times, for DEO 4 it is twice and for DEO 6 it is 10 times. GM values were significantly different, and varied by 48 times (P = 3 x 10–6), 2 times (P = 0.013) and 9 times (P = 3 x 10–6), respectively. These results show that dermal exposure patterns may be different for liquid and solid contaminants. These differences might be explained by determinants of exposure (Marquart et al., 2003).
|
Table 3 shows the distribution statistics for the body for different scenarios as obtained by the respective partners. Exposure levels for scenarios within a given DEO unit vary by orders of magnitude.
In DEO 1 two sets of results obtained for the same scenario (1.6 maintenance and servicing) are different (P = 6 x 10–10), although there are only four results for one study so far. Similarly, the data sets obtained for the filling (1.10) and mixing (1.14) scenarios vary by many orders of magnitude. For example, potential dermal exposure resulting from the mixing (1.14) scenario undertaken in a ship repair (paint mixing) situation is different from those obtained during the mixing of a cancer treatment drug, due to scale, handling practices and the stringency of control measures in place (see Table 3). The median and 95th percentile values obtained for the mixing of anti-fouling paints are 350 and 1700 µg/cm2/h, respectively, and these compare reasonably with other reported values of 160 and 800 µg/cm2/h (Phillips and Garrod, 2001).
In DEO 3 the median value (21 µg/cm2/h) obtained for the pouring (3.1) scenario of a biocide or a cancer treatment drug in hospitals is less than that obtained by Cattani et al. (2001) of 200 µg/cm2/h. However, it should be noted that in our study pouring was assessed whilst decanting urine in a hospital environment, while in the Cattani et al. (2001) study chloropyrofos was poured from a container into a mixing vessel in situ at construction sites. Pouring and spreading (3.2) produced similar exposures, but rolling (3.4) produced higher exposures.
In DEO 4 the three spray painting (4.2) scenarios appear to produce significantly different GMs (P = 0.001) and it would not be practical to use the ‘averages’ of the data for exposure prediction for all types of spray painting situations unless exposure determinants, (such as application pressure, distance of the gun to the object/operator, viscosity, particle size, etc.) are taken into account through modelling.
In DEO 5 (dip coating) two sets of data were obtained for the electroplating (5.1) scenario and they show remarkable differences that may also be due to workplace factors but may be attributable to sampling methodology. The data available for DEO 5 were all from electroplating and are not adequate to assess the applicability of the data to the other scenarios within it (Appendix Table A1).
In DEO 6 (mechanical treatment of solids) the median values for two sets of results for the machining (6.2) scenario differ by 5.5 times, whereas the GMs differ by only 2 times, indicating a poor fit to the log normal distribution. The GM results from grinding (6.6) are lower than from the machining (6.2) scenario (P = 3 x 10–6).
On the basis of the results presented, the median for a given DEO unit may not be used as a representative measure of dermal exposure for all scenarios within that DEO. Similarly, the 95th percentile value for the respective DEO may not be used as the worst case prediction for all scenarios within it. However, the usability of the data can be enhanced by an exposure matrix (indicative exposure distribution based on scenario/workplace) such as that proposed by Phillips and Garrod (2001) or by predictive modelling as proposed in the RISKOFDERM project (Marquart et al., 2003).
Potential hand exposure
Potential hand exposure levels for different DEO units are summarized in Table 4. In this case a subset of 375 samples contributes to the data. The percentage of NDs is 3.2%. This is much lower than those observed for body (18.9%) and shows that hands get contaminated almost all of the time. In general, the extent of contamination of hands is much greater than the body and the exposure levels ranged from 0.0005 to 300 000 µg/cm2/h. Visual perusal of the data in Table 4 indicates that each DEO unit has its own exposure pattern. As expected, work involving manual dispersion (DEO 2) caused high exposures (median = 130 000 µg/cm2/h) resulting from the significant potential for direct contact with contaminants. DEO 2 also shows a weighting to the high end of the distribution, indicating a poor fit to the log normal distribution, possibly caused by complete saturation of the sampling gloves. Dip coating (DEO 5) appears to cause considerably lower exposure to hands. It should be noted that the scenario involved was electroplating (5.1) and the items being plated were dipped using mechanical means, thereby reducing the potential for hand/body exposures. Consequently, the variation in exposure between hands and body are small. For example, the median value for hands is 0.43 µg/cm2/h and for the body it is 1.4 µg/cm2/h.
|
In general, scenarios in DEO 3 (manual dispersion with hand-held tools), when compared with those in DEO2 (manual dispersion), should reflect reduced potential for direct contact with contaminants. This fact is clearly reflected in the results obtained.
Table 5 shows the breakdown by solid and liquid contaminants on hands. The patterns match those found for the body. In DEO 1 hands were a factor of 7.5 times higher for liquids than solids, much less than the factor of 170 times found for the body. For DEO 4 solids and liquids were very similar for hands (1 times) and only a factor of twice for the body. The contamination route for DEO 4 is via deposition from the air, which settles on hands and body alike.
|
Variations in potential exposure of hands for different scenarios within DEO units are presented in Table 6. In DEO 1 median exposures for scenarios ranged from 1.4 to 62 000 µg/cm2/h and many of these values differ significantly from the median value for the DEO as a whole (870 µg/cm2/h). In the case of DEO 3 median values varied between 61 and 1300 µg/cm2/h and in DEO 4 it varied from 190 to 2800 µg/cm2/h. The potential exposure of hands when handling cancer-causing drugs (maintenance and servicing; mixing and pouring) is very different from those obtained for industrial activities, but there are few data so far to enable proper comparison.
|
The potential influences of exposure determinants are clearly seen from the results obtained for spray painting. The data obtained for spray painting of anti-fouling paint (median = 2800, GM = 2800 µg/cm2/h) is different from that obtained for powder coating (median = 400, GM = 970 µg/cm2/h). Similarly, spray painting of motor vehicles produced a very different set of data (median = 190, GM = 160 µg/cm2/h).
Correlation between potential hand and body exposure is shown in Fig. 2 by DEO. It shows reasonable correlations for DEOs 1, 3, 4 and 6, but none for DEOs 2 or 5. DEO 2 was a wiping task in which gloves may have been saturated. Figure 2 shows that a plateau was reached in the DEO 2 hand exposures. DEO 5 was dip coating, where high levels of automation were used. Figure 2 shows results from only one study which produced very low results and therefore a lack of correlation for DEO 5 could be due to relatively high noise. There was no data in terms of formulation for DEO 6, but one study reported in terms of analyte, and this is shown in Fig. 2.
|
Comparison of body areas
Hands are the most contaminated parts of the body for all DEOs. The degree of contamination of other parts of the body varied with the scenario undertaken and probably depends upon the physical conditions that prevailed for the job. During a small-scale filling (1.10) exposure of the forearms were 10 times higher than the rest of the body, although the hands were 250 times higher still. During the mixing/diluting task (1.14), exposure of the legs was 7 times higher than the rest of the body, but exposure of the hands was 60 times higher still. For the wiping task (2.2), exposure of the right forearm was 3 times higher than the rest of the body, but the hands were 500 times higher still, and exposure of the right hand was twice that of the left. In contrast DEO 3, dispersing with a hand-held tool, exposures were found to be even over the body. Spray dispersion also caused even exposures over the body for large-scale tasks that included spraying above head (ship repair). Small-scale spray dispersion (painting car body) caused higher exposure to the legs, where the spraying remained below waist height (for most of the time). For dip coating using waist-high baths (DEO 5) exposure of the hands and legs were three times higher than the rest of the body, indicating that subjects leaned over the baths.
|
CONCLUSIONS |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
On the basis of the analysis of the data presented here, the averaged results (median and 95th percentile) for a given DEO unit should not be used as a representative measure of dermal exposure for all scenarios within that DEO without taking the exposure determinants into account.
There are various options for using the data in quantitative risk assessments. These include the following: (i) only use results obtained from a particular scenario/workplace (e.g. brushing overhead indoors) to assess dermal exposure for similar situations. Guidelines for selecting scenarios are given in the current Technical Guidance Document (ECB, 2003) and the RISKOFDERM data will extend the selection. (ii) Further improve the exposure matrix (indicative distributions) proposed by Phillips and Garrod (2001), taking account of determinants of exposure and using a Bayesian approach to integrating expert opinion. (iii) Develop predictive models that take account of exposure determinants. The last approach has been adopted by RISKOFDERM.
The major problems in dermal exposure measurements seem to be the multidirectional and multicompartmental nature of dermal exposure, further influenced by human factors, substances used, work activities, equipment used and so on. Exposure data for a given scenario is likely to vary by many orders of magnitude and this situation has to be accepted when carrying out workplace measurements, but variability should be kept to a minimum. The data obtained and the practical issues involved in obtaining dermal exposure measurements suggest that a balance should be struck between directing efforts towards dermal exposure control and actual dermal exposure measurement. Where there is a need to assess dose, biological monitoring may be a better measure.
|
APPENDICES |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
Table A1 lists DEO units and relevant scenarios. Table A2 is a summary of the sampling survey details. Table A3 is a summary of the partners’ analytical methods.
Acknowledgements—The authors are indebted to the many participating colleagues in the partner institutions. This paper would not have been written without their work, help and support. This study was facilitated by the RISKOFDERM project supported by European Commission Contract QLK4-CT-1999-01107 and the institutions referred to in the body of the paper.
|
FOOTNOTES |
|---|
* Author to whom correspondence should be addressed. Tel: +44-151-951-3318; fax: +44-151-951-3595; e-mail: bob.rajan{at}hse.gsi.gov.uk
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONDERMAL EXPOSUREMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSAPPENDICESREFERENCES |
|---|
Brouwer DH, Lansink CM, Cherrie JW, van Hemmen JJ. (2000) Assessment of dermal exposure during airless spray painting using a quantitative visualisation technique. Ann Occup Hyg; 44: 543–50.
Cattani M, Cena K, Edwards J, Pisaniello D. (2001) Potential dermal and inhalation exposure to chlorpyrifos in Australian pesticide workers. Ann Occup Hyg; 45: 299–308.
Chester G, Hart TB. (1986) Biological monitoring of a herbicide applied through backpack and vehicle spraying. Toxicol Lett; 33: 137–49.[CrossRef][ISI][Medline]
Delgado P, Porcel J, Abril I, Torres N, Teran A, Zugasti A. (2004) Potential dermal exposure during the painting process in car body repair shops. Ann Occup Hyg; 48: 229–236.
ECB. (2003) Technical guidance document on risk assessment in support of Commission Directive 93/67/EEC on risk assessment for new notified substances; Commission Regulation (EC) no. 1488/94 on risk assessment for existing substances; Directive 98/8/EC of the European Parliament and of the Council concerning the placing of biocidal products on the market. Part I. EUR 20418 EN/1. European Commission. Joint Research Centre. ISPRA, Italy: European Chemical Bureau.
Environmental Protection Agency. (1996) Occupational dermal exposure assessment—a review of methodologies and field data (68-D2-0157, WA) no. 2-50. Washington, DC: Environmental Protection Agency.
Eriksson K, Wiklund L. (2004) Dermal exposure to styrene in the fibreglass reinforcement plastics industry. Ann Occup Hyg; 48: 203–208.
Eriksson K, Wiklund L, Larsson C. (2004) Dermal exposure to terpenic resin acids in Swedish carpentries and sawmills. Ann Occup Hyg; 48: 267–275.
Fenske RA. (1993) Dermal exposure assessment techniques. Ann Occup Hyg; 37: 687–706.
Fransman W, Vermeulen R, Kromhout H. (2004) Dermal exposure to cyclophosphamide in Dutch hospitals: a pilot study. Ann Occup Hyg; 48: 237–244.
Garrod ANI, Rimmer DA, Robertshaw L, Jones T. (1998) Occupational exposure through spraying remedial pesticides. Ann Occup Hyg; 42: 159–65.
Gijsbers HJ, Tielemans E, Brouwer DH, van Hemmen JJ. (2004) Dermal exposure during filling, loading and brushing with products containing 2-(2-butoxyethoxy)ethanol. Ann Occup Hyg; 48: 219–227.
Goede HA, Tijssen SCHA, Schipper HJ, et al. (2003) Classification of dermal exposure modifiers and assignment of values for a risk assessment toolkit. Ann Occup Hyg; 47: 609–18.
Health & Safety Executive. (1999) Dermal exposure to non-agricultural pesticides, EH7/43. Sudbury: HSE Books. ISBN 07176 1718 1.
Health and Safety Commission. (2001) Health and safety statistics 2000/01. Sudbury: HSE Books. ISBN 01716 2110 3.
Hughson GW, Aitken RJ. (2004) Determination of the variability of dermal exposures during mixing, spraying and wiping activities. Ann Occup Hyg; 48: 245–255.
Keith L, Crummett W, Deegan J, Libby R, Taylor J, Wentler G. (1983) Principles of environmental analysis. Anal Chem; 55: 2210–8.[CrossRef]
Kromhout H, Fransman W, Vermeulen R, Roff M. (2004) Variability of task-based dermal exposure measurements from a variety of workplaces. Ann Occup Hyg; 48: 187–196.
Mäkinen M, Linnainmaa M. (2004a) Dermal exposure to chromium in electroplating. Ann Occup Hyg; 48: 277–283.
Mäkinen M, Linnainmaa M. (2004b) Dermal exposure to chromium in the grinding of stainless and acid proof steel. Ann Occup Hyg; 48: 197–202.
Marquart H, Brouwer DH, Gijsbers JHJ, Links IHM, Warren N, van Hemmen JJ. (2003) Determinants of dermal exposure relevant for exposure modelling in regulatory risk assessment. Ann Occup Hyg; 47: 599–608.
OECD. (1997) Environmental health and safety publications series on testing and assessment no. 9: Guidance document for the conduct of studies of occupational exposure to pesticides during agricultural application, OCDE/GD(97) 148. Paris: OECD.
Oppl R, Kalberlah F, Evans PG, van Hemmen JJ. (2003) A toolkit for dermal risk assessment and management: an overview. Ann Occup Hyg; 47: 641–52.
Phillips, AP and Garrod, ANI. (2001) Assessment of dermal exposure—empirical and indicative distributions. Appl Occup Environ Hyg; 16: 323–8.[Medline]
RISKOFDERM. (1999) Contract number QLK4-CT-1999-01107, 5th Framework Programme of the European Union. Luxemburg: European Commission.
Roff M, Bagon DA, Chambers H, Dilworth EM, Warren N. (2004a) Dermal exposure to dry powder spray paints using PXRF and the method of Dirichlet tesselations. Ann Occup Hyg; 48: 257–265.
Roff M, Bagon DA, Chambers H, Dilworth EM, Warren N. (2004b) Dermal exposure to electroplating fluids and metalworking fluids in the UK. Ann Occup Hyg; 48: 209–217.
Rycroft RJG, Menne T, Frosch PJ, Lepoittevin JP. (Eds) (2001) Textbook of contact dermatitis, 3rd edn. Berlin: Springer Verlag.
Schneider T, Vermeulen R, Brouwer DH, Cherrie JW, Kromhout H, Fogh CL. (1999) Conceptual model for assessment of dermal exposure. Occup Environ Med; 56: 65–773.
Schuhmacher-Wolz U, Kalberlah F, Oppl R, van Hemmen JJ. (2003) A toolkit for dermal risk assessment: toxicological approach for hazard classification. Ann Occup Hyg; 47: 641–52.
van Hemmen JJ, Auffarth J, Evans PG, Rajan-Sithamparanadarajah R, Marquart H, Oppl R. (2003) RISKOFDERM: risk assessment of occupational dermal exposure to chemicals. An introduction to a series of papers on the development of the toolkit. Ann Occup Hyg; 47: 595–8.
Vermeulen R, Heideman J, Bos RP, Kromhout, H. (2000) Identification of dermal exposure pathways in the rubber manufacturing industry. Ann Occup Hyg; 44: 533–41.
Warren N, Goede HA, Tijssen SCHA, Oppl R, Schipper HJ, van Hemmen JJ. (2003) Deriving default dermal exposure values for use in a risk assessment toolkit for small and medium-sized enterprises. Ann Occup Hyg; 47: 619–27.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  P. Boogaard Biomonitoring as a tool in the human health risk characterization of dermal exposure Human and Experimental Toxicology, April 1, 2008; 27(4): 297 - 305. [Abstract] [PDF]
|
|
|
|
 |
|
 T. OGDEN Annals of Occupational Hygiene at Volume 50: Many Achievements, a Few Mistakes, and an Interesting Future Ann. Hyg., November 1, 2006; 50(8): 751 - 764. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. MARQUART, N. D. WARREN, J. LAITINEN, and J. J. VAN HEMMEN Default Values for Assessment of Potential Dermal Exposure of the Hands to Industrial Chemicals in the Scope of Regulatory Risk Assessments Ann. Hyg., July 1, 2006; 50(5): 469 - 489. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. D. WARREN, H. MARQUART, Y. CHRISTOPHER, J. LAITINEN, and J. J. VAN HEMMEN Task-based Dermal Exposure Models for Regulatory Risk Assessment Ann. Hyg., July 1, 2006; 50(5): 491 - 503. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. SYMANSKI, S. MABERTI, and W. CHAN A Meta-Analytic Approach for Characterizing the Within-Worker and Between-Worker Sources of Variation in Occupational Exposure Ann. Hyg., June 1, 2006; 50(4): 343 - 357. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. CRAUSTE-MANCIET, P. J. M. SESSINK, S. FERRARI, J.-Y. JOMIER, and D. BROSSARD Environmental Contamination with Cytotoxic Drugs in Healthcare Using Positive Air Pressure Isolators Ann. Hyg., October 1, 2005; 49(7): 619 - 628. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. KROMHOUT, W. FRANSMAN, R. VERMEULEN, M. ROFF, and J. J. VAN HEMMEN Variability of Task-based Dermal Exposure Measurements from a Variety of Workplaces Ann. Hyg., April 1, 2004; 48(3): 187 - 196. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. ROFF, D. A. BAGON, H. CHAMBERS, E. M. DILWORTH, and N. WARREN Dermal Exposure to Electroplating Fluids and Metalworking Fluids in the UK Ann. Hyg., April 1, 2004; 48(3): 209 - 217. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. W. HUGHSON and R. J. AITKEN Determination of Dermal Exposures During Mixing, Spraying and Wiping Activities Ann. Hyg., April 1, 2004; 48(3): 245 - 255. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. ROFF, D. A. BAGON, H. CHAMBERS, E. M. DILWORTH, and N. WARREN Dermal Exposure to Dry Powder Spray Paints Using PXRF and the Method of Dirichlet Tesselations Ann. Hyg., April 1, 2004; 48(3): 257 - 265. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||