Annals of Occupational Hygiene Advance Access originally published online on April 21, 2005
Annals of Occupational Hygiene 2005 49(6):511-519; doi:10.1093/annhyg/mei013
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© 2005 British Occupational Hygiene Society Published by Oxford University Press
Original Article |
Variability in Dust Exposure in a Cement Factory in Tanzania
1 Centre for International Health, Faculty of Medicine, University of Bergen, Armauer Hansens Hus, N-5021 Bergen, Norway; 2 Section for Occupational Medicine, Institute of Public Health and Primary Health Care, University of Bergen, Kalfarvei 31, N-5018 Bergen, Norway; 3 Department of Environmental Health, University of Washington, P.O. Box 357234, Seattle, WA 98195-7234, USA
* Author to whom correspondence should be addressed. Tel: +47-55-58-6100; fax: +47-55-58-6105; e-mail: jmwaiselage{at}yahoo.com
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Dust exposure levels were studied in a cement factory in Dar es Salaam, Tanzania, as part of an epidemiological study assessing chronic respiratory health effects. One hundred and twenty personal ‘total’ dust samples were collected from 80 randomly selected workers from eight a priori occupational groups (OGs) based on work areas using a 37 mm Millipore sampler. The between-group, within-group and within-worker variances were determined to assess the contrast in exposure level between the OGs and to estimate the attenuation and standard error of the theoretical exposure–response slope. Using mixed-effect model estimates, the probability of overexposure relative to the occupational exposure limit (OEL) was assessed for each OG. The geometric means of total dust exposure were higher in the cranes (38.64 mg m–3), packing (21.30 mg m–3) and crusher (13.48 mg m–3) than in the cement mill (3.23 mg m–3), kiln (2.87 mg m–3), raw mill (1.85 mg m–3), maintenance (1.16 mg m–3) and administration (0.29 mg m–3). The a priori grouping scheme seems to be an efficient scheme because of the high contrast in exposure level between the OGs (0.78) and minimal attenuation of the theoretical exposure–response slope (1.0%). When using the reduced mixed-effect model, the probabilities of overexposure (
) relative to the OEL of 10 mg m–3 for total cement dust were higher in the crane (96%), packing (88%) and crusher (73%) than in the cement mill (16%), kiln (14%), raw mill (5%), maintenance (2%) and administration (0.01%).
Keywords: cement dust • exposure • exposure assessment • variance components
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Assessing workplace exposure is important not only for evaluating health risks but also for reducing exposure through workable control measures. In epidemiological studies, the validity of the association between exposure and health effects is essential. This relationship may be biased by variability in exposure and misclassification of workers. The extent to which exposure varies depends on many factors; some are related to the agent itself, but most are linked to work content, tasks performed, and production and environmental characteristics (Kromhout et al., 1993
; Rappaport et al., 1993; Kromhout, 2002). In order to estimate and avoid this possible bias, exposure variability and proper classification of workers has become an important topic in occupational epidemiology (Goldberg and Hemon, 1993; Vinzents et al., 2001).
Occupational sampling strategies do not usually include measuring the entire workforce, primarily because of logistical constraints of time and cost (Sauleau et al., 2003; Loomis and Kromhout, 2004). Thus, for practical reasons, a group-based strategy is preferred in most cases, as they tend to be logistically less demanding than individual-based strategies (Loomis and Kromhout, 2004). In a group-based strategy, representative measurements are collected on some individuals in the occupational group (OG), and the average exposure is estimated and assigned to all group members (Seixas and Sheppard, 1996; Nieuwenhuijsen, 1997). The variability in exposure between exposure groups can be evaluated and can assist in the assessment of different grouping schemes (Symanski et al., 1996; Vinzents et al., 2001). Variability in exposure from day to day and between workers comprising an OG can be used to assess the probabilities of overexposure and exceedance relative to the occupational exposure limits (OELs) (Rappaport et al., 1993, 1995), homogeneity in exposure levels (Rappaport et al., 1995, 1999) and to classify workers into similar exposure groups (Mulhausen and Damiano, 1998).
Cement factories have different stages in their production processes (Alvear-Galindo et al., 1999; Prodan and Bachofen, 1999), where dust exposure among the workers is likely to vary. Epidemiological studies indicate that workers exposed to cement dust, which is an irritant to the respiratory airways, have an increased risk of suffering from acute across-workshift reduction in ventilatory function (Ali et al., 1998; Mwaiselage et al., 2002) and chronic respiratory symptoms accompanied by impairment of ventilatory function (Yang et al., 1996; Noor et al., 2000; Al-Neaimi et al., 2001). Exposure to cement dust has recently been associated with laryngeal cancer (Diertz et al., 2004) and respiratory cancer (Smailyte et al., 2004). A review of cement studies has indicated that cement workers might be exposed to dust levels ranging 11–230 mg m–3 for total dust and 2–46 mg m–3 for respirable dust (Fairhurst et al., 1997). However, previous studies in cement factories have not assessed the variability in exposure among different groups of workers and the potential for misclassification of exposures.
This study was part of an epidemiological cross-sectional survey to assess chronic respiratory health effects among workers in a cement factory in Tanzania. The major aims of the present study were to assess the levels of personal total dust exposure, to determine the efficiency of the a priori grouping scheme for the planned epidemiological study and to assess the probability of overexposure relative to the OEL.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Settings
The study was conducted at a Portland cement factory in Dar es Salaam, Tanzania, between June and August 2002. The factory started production in 1965. It currently employs
300 workers and produces 500 000 tons of cement annually. The factory has nine major departments: corporate, production, maintenance, personnel, accounts, business, transport, procurement and quality assurance.
Methods of manufacture
The raw materials used in the production of cement are limestone (>80% calcium carbonate), red soil (>50% silicates) and gypsum (>60% calcium sulfate). The main processes and operations carried out during cement manufacture are crushing, raw milling, calcination (pyroprocessing) in a rotary kiln, cement milling, crane operations and packing. The main method for prevention of dust exposure available at the work areas is the use of personal respiratory protective equipment (resembling half-face mask type P1), although it was observed that the workers did not wear them regularly. No noticeable specific control measures, such as local exhaust ventilation, wet dust suppression or any dust reducing techniques, were found in the work areas. The job categories, tasks and working conditions in the different work areas in the cement factory are described in Table 1.
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Work area identification and allocation of workers
The OGs representing the respective work areas were a priori selected, based on description assigned administratively by the factory management. In the production department the workers were assigned into six OGs: crusher, crane, raw mill, kiln, cement mill and packing. Workers from the maintenance department (mechanics, electricians, civil and carpentry) constituted one OG and workers in the administration block (accounts, business, personnel and quality-assurance departments) were considered as one OG. Workers from the corporate, transport and procurement departments were excluded from the study.
Dust sampling strategy
One hundred and twenty (80 initial and 40 repeated) ‘total’ dust samples were planned to be collected from the factory. Preliminary data for respirable dust levels from an earlier survey in the factory (Mwaiselage et al., 2002) was used for allocating 80 ‘total’ dust samples into the eight a priori OGs by a stratified random sampling plan as described by Cochran (1997). The preliminary respirable dust exposure data (number of samples, arithmetic mean in mg m–3, standard deviation) were collected from the crusher (7, 19.3, 24.9), crane (7, 12.8, 3.7), kiln (4, 1.5, 1.1), packing (6, 7.9, 6.6), maintenance (3, 1.1, 4.6) and administration (2, 0.8, 1.6). Raw mill and cement mill sections were not sampled, but due to similarity in working conditions, these sections were estimated to have similar dust exposure as the kiln section. Total dust exposure was also assessed during the preliminary survey but only in few numbers and was therefore inadequate to make necessary calculations. The average ratio of respirable dust to total dust was 0.40. The allocation of the 80 initial total dust samples into the eight a priori OGs using stratified random sampling was based on the following expression:
 | (1) |
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Dust sampling methods
One hundred and twenty full-shift personal measurement of total dust in the breathing zones of the randomly selected 80 workers was performed during the 8 h morning shift. Of the workers 40 were randomly re-selected for repeated measurement conducted at an interval of 2–4 weeks. The sampling time for the dust measurement ranged from 387 to 463 min with arithmetic mean (SD) of 436.0 (16.4) min. The total dust samples were collected on cellulose acetate filter paper with 0.8 µm pore size, placed in 37 mm closed-faced Millipore cassettes (Millipore Corporation, Bedford, MA), connected to a side-kick sampling pump (SKC Ltd., London, UK), using a flow rate of 2 l min–1. This Millipore sampler has been shown to be less efficient in collecting large particles than laid down in the International Standard Organisation (ISO) inhalable dust definition (Kenny et al., 1997
), but it has the advantages of being readily available and able to protect the filter. Furthermore, in Norway, the closed-faced Millipore sampler is normally used for sampling ‘total’ aerosol and to compare with the recommended limit values (Bråtveit et al., 2004). For simplicity, we refer to the samples as ‘total dust’ samples. The sampling pumps were calibrated before sampling using a rotameter. No dust sample was regarded invalid since the pumps did not stop during sampling and no change of >5% in the flow rate between pre- and post-sampling flow rate occurred. The collected dust samples were sealed in plastic bags and transported in a protective suitcase to Norway for analysis at X-lab AS, Bergen, Norway. This laboratory has passed the intercalibration testing, run by the Norwegian Institute of Occupational Health in Oslo. During transportation, it is possible that small amounts of dust might have fallen from the filter into the wall of the Millipore cassette. Thus, we can not completely exclude the possibility of underestimation of the dust levels. The Millipore filters were weighed on a microbalance (Mettler AT 261), with a detection limit of 0.01 mg m–3 before and after sampling. None of the samples was found to be below the limit of detection. Six field blanks, which were randomly collected during sampling, were all found to be below the limit of detection. We compared the results from the exposure monitoring using the current Norwegian OEL for 8 h total dust exposure of 10 mg m–3 (Norwegian Directorate of Labour Inspection, 2003).
Statistical analysis
The statistical analysis was performed on log-transformed data due to the lognormal distribution of the exposure data. Two-way nested random-effects model was used to estimate variance components of between-group, within-group and within-worker as described by Kromhout and Heederik (1995). In the random effects model, the OG and the worker identity were treated as random effects, and the model is given as
 | (2) |
i is the random effect owing to the ith group; ßij is the random effect of the jth worker in the ith group; 
ijk is the random error of the ith group jth worker exposure on the kth day. The between-group (bgS2), within-group (wgS2) and within-worker (wwS2) variances were estimated by the model.
Contrast () in mean exposure levels between the OGs was calculated as described by Kromhout and Heederik (1995): Contrast () = bgS2/(bgS2 + wgS2). The value of contrast lies between 0 and 1, and a value of 1 is reached if each OG constitute a unique exposure. If the value approaches 0, the OGs can not be distinguished with regard to exposure (Kromhout and Heederik, 1995).
Attenuation and standard error (SE) of the observed exposure–response slope was assessed as described by van Tongeren et al. (1997) and Tielemans et al. (1998). The ratio of observed to true slope was estimated by
 | (3) |
 | (4) |
; Tielemans et al., 1998). Using equations (3) and (4), k was set at 2, because the overall mean of repeated measurement for each worker was 1.5 and was rounded to 2. Furthermore, the number of workers in each OG (n) was approximated to be 10 because the overall number of workers was 80 from the eight OGs. The efficiency of the grouping scheme was assessed in terms of high contrast in exposure level, minimal attenuation of exposure–response slope and small SE of the slope.
Mixed-effect model was also applied to the dataset, whereby the occupational group was introduced as a fixed effect and the worker identity was introduced as a random effect. The mixed-effect model equation is the same as the random-effect model (2), but it differs in its specification of OG as fixed effects, and thus it can investigate the fixed effect of the OG upon exposure (Rappaport et al., 1999; van Tongeren et al., 2000; Weaver et al., 2001). The model is given as
 | (5) |
i,...,g = fixed effects of the ith OG...gth OG. Where Xijk represents the exposure level on the kth day for the jth worker in the ith group; Yijk is the natural logarithm of the individual measurements Xijk.
When applying mixed-effect model to our data, three alternative variance structures were evaluated. The full model: bwS2 and wwS2 were assumed to be distinct for all groups. The partly reduced model: bwS2 was assumed to be distinct for each group and wwS2 common for all groups. The reduced model: bwS2 and wwS2 were both assumed to be common for all groups. Likelihood ratio test was applied at a significance level of 0.05 to compare the reduced model and the partly reduced models to the full model (Rappaport et al., 1999). The bwS2 and wwS2 were used to estimate the probability of overexposure () relative to the OEL as described by Rappaport et al. (1999); van Tongeren et al. (2000); and Weaver et al. (2001):
 | (6) |
{x} denotes the probability that a standard normal deviate falls below the value x; µyi represents the fixed mean (logged) exposure for the ith group; µxij = mean exposure of randomly-selected jth worker in the ith group and 
representing the long-term mean exposure for the ith group, where tS2 = wwS2 + bwS2.
SPSS version 11.5 for Windows (SPSS Inc., Chicago, IL, 2001) was used for the analysis. Due to the unbalanced nature of the data, all model parameters were estimated using restricted maximum likelihood (REML) method (Searle et al., 1992).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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The cranes, packing and crusher had higher geometric mean total dust exposure than the cement mill, kiln, raw mill, maintenance and administration block (Table 2). Comparison of the measurements to the OEL shows that 39.2% of the dust samples exceeded the OEL of 10 mg m–3 for total dust. The highest fractions of samples exceeding the OEL were in the crane (91.7%), crusher (84.6%) and packing (76.5%) (Table 2).
The results of the two-way random effect model are given in Table 3. The largest contribution to the total variability was from the between-group variance (68.7%), followed by within-group variance (19.0%) and within-worker variance (12.3%). The contrast in exposure between the OGs was as high as 0.78, implying that the a priori grouping scheme is an efficient scheme in distinguishing the OGs with regard to exposure.
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The ratio of observed/true slope of the exposure–response relationship was 0.99 and when the true exposure–response slope is set at –0.10, the observed slope was estimated to be –0.099 (Table 3). This indicates an attenuation of 1.0% (i.e., 1 – ß*/ß = 0.01) of the true slope. These findings indicate that the a priori grouping scheme is an efficient scheme in examining exposure–response relationship.
Based on the mixed-effect model, the likelihood ratio test results showed that the variance components under the full model did not differ from those under the partly reduced model [–2(LR – LF) = 8.13; 
, P > 0.05] or under the reduced model [–2(LMR – LF) = 16.8; 
; P > 0.05]. This implied that the variance components of bwS2 and wwS2 might be pooled across the OGs. However, based on the full model, the within-worker (day-to-day) variability was higher in the crane and kiln than in the other OGs (Table 4).
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The probability of overexposure (
) relative to OEL using the reduced model estimates was higher in the crane, packing and crusher than in the cement mill, kiln, raw mill, maintenance and administration (Table 4). The results of overexposure based on the full and partly reduced models are shown for comparison purposes, and in all the models workers in the crane, packing and crusher had higher probabilities of overexposure than workers in the cement mill, kiln, raw mill, maintenance and administration. |
DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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The measured total dust levels were highest in the crane, crusher and packing sections. This is in accordance with a previous study (Alvear-Galindo et al., 1999
), reporting that workers in the crusher and packing areas subjectively reported higher dust exposure than workers in the kiln, cement mill and maintenance areas. In our study, 39% of the total dust samples exceeded the OEL of 10 mg m–3 for total cement dust, and all of them occurred in the crusher, crane and packing areas. The workers in these areas are routinely in closer contact with the dust-emitting machinery for a prolonged period of time. In the present study, the measured total dust exposure in the production areas varied from 0.21 to 229.23 mg m–3 (GM: 10.6 mg m–3). Our results exceed the total dust levels in the USA ranging from 0.01 to 78.61 mg m–3 (GM: 2.9 mg m–3; Abrons et al., 1988) and in Norway ranging 0.4–53.7 mg m–3 (AM: 7.4 mg m–3; Fell et al., 2003). Cement industries in the developed countries are more efficient in dust control measures using methods such as: enclosure of dust-emitting machinery, conveyor belts and its transfer points; improved general mechanical ventilation in the work areas; local exhaust ventilation from the crusher and packing machinery; replacement of pneumatic packing machine with automatic impeller driven packing machine; wet dust suppression during cleaning activities; greater diligence in maintenance of machinery to prevent dust release; regular use of high quality personal protective respiratory equipment and influencing workers behaviour by training and education (Fairhurst et al., 1997). These methods were lacking in the presently studied cement factory. In Malaysia (Noor et al., 2000), mean total dust level of 8.52 mg m–3 was reported to cause impaired lung function and increased prevalence of respiratory symptoms among the cement workers. Thus, the high values of total dust levels found in the work areas of the presently studied cement factory poses an increased risk for the workers in developing respiratory health effects.
To our knowledge, this is the first published study of assessing total dust exposure variability in the cement industry, and shows the usefulness of categorization of workers into exposure groups. In this context, it was essential to know how efficient the a priori grouping scheme was in terms of contrast in exposure level (Kromhout and Heederik, 1995; van Tongeren et al., 1997). A high exposure contrast was found when using the a priori grouping scheme, indicating that clearly distinguishable levels of exposure are obtained by the scheme. In our study, collection of a higher number of repeated samples from all job categories would enable the estimation of variance components in all job categories, and alternative grouping strategy could have been evaluated. However, since the number of workers in many job categories were small, it seemed beneficial to combine the job categories rather than to increase the number of repeated measurements (Kromhout et al., 1993).
The attenuation of the theoretical exposure–response slope was minimal (1.0%). Similarly, the SE of the theoretically attenuated slope was small and comparable to those obtained in other studies, such as 0.0296 for exposure group scheme in carbon black exposure (van Tongeren et al., 1997) and 0.03 for job category scheme in flour dust exposure (Houba et al., 1997). This suggested that the a priori grouping scheme is an appropriate strategy for obtaining a relatively unbiased exposure–response slope. However, previous studies have generally shown that more precise estimates of exposure–response relationship are obtained with an individual-based strategy because of a much smaller SE of the observed slope (van Tongeren et al., 1997; Tielemans et al., 1998). In our study individual-based strategy was not an option in examining exposure–response relationship as only a few workers from the study population were assessed for dust exposure. Care should be taken in the interpretation of the observed results since assumptions of equal number of measurements per worker and equal number of workers per group were not met. These assumptions are seldom met in the real world, but have been used in several previous studies probably resulting in some inaccuracy (van Tongeren et al., 1997; Tielemans et al., 1998; Tjoe Nij et al., 2004). Furthermore, the equations used are based on a situation in which the health outcome only depends on one exposure factor. This is not the case as respiratory disorders also depend on other factors such as age, smoking, etc. (van Tongeren et al., 1997).
Based on the full model, it was observed that the between-worker variance was relatively greater than within-worker variance for four of the eight OGs, probably due to the presence of different job categories within these OGs performing different tasks. In the OGs where the workers in the different job categories perform more or less similar tasks, the between-worker variability was lower than or equal to within-worker variability (crane, raw mill, kiln and cement mill). Outdoor activity, intermittent processes and mobility of worker has been reported to be associated with high day-to-day (within-worker) variability (Rappaport et al., 1993; Kromhout, 2002). In our study, relatively high within-worker variability was observed in the crane and kiln. In the crane, this could be due to the outdoor location of the work area and the intermittent operation of the overhead cranes, which is dependent on material re-arrangement and the mills requirement. In the kiln, it could be the result of a high mobility of the workers between the control room and the outdoor-located rotary kiln.
The likelihood ratio test suggested that it was reasonable to pool the within- and between-worker variances across the OGs, as there was no advantage in assuming heterogeneity in the between-worker and within-worker variances across the OGs. These findings indicate that the OGs share common levels of variability. However, the day-to-day variation in exposure level might have been underestimated because of the short interval of 2–4 weeks between repeated measurement. It is true that the operating machinery, work environment, processes, climatic conditions and dust sampling technique did not change during this short period. However, the underestimation of the ‘true’ within-worker variance is likely to be small for the majority of the workers because they perform similar tasks more or less every day.
The crusher, packing and crane had high probabilities of overexposure relative to the OEL (10 mg m–3) for total dust independent of the model applied. For the raw mill, maintenance and administration, the probability of overexposure was <10%, a level that has been used as an indicator of acceptable probability of overexposure (Rappaport et al., 1995; van Tongeren, 2000). However, for cement mill and kiln, the probability of overexposure were >10% when using the reduced model and <10% for the other two models. Because workers in the crane, crusher, packing and to a small extent in the cement mill and kiln had high probabilities of overexposure, necessary control measures need to be taken.
In conclusion, this study has demonstrated that exposure to cement dust in the factory has considerable variability. The a priori grouping by eight OGs representing the work area was found to be an efficient grouping scheme with regard to high contrast in exposure level between the work areas, minimal attenuation of exposure–response slope and small SE of the slope. Workers in the crane, packing and crusher were highly overexposed to total cement dust relative to OEL, irrespective of the mixed-model applied.
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ACKNOWLEDGEMENTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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We thank the workers and management of the Tanzania Portland Cement Company for co-operation. We also thank Mr Simon Lupatu, safety officer for the technical assistance during data collection at the factory. The Norwegian State Education Loan Fund (Lånekassen), Norwegian Council of Universities Committee for Development Research and Education (NUFU) and the Section for Occupational Medicine, University of Bergen supported this project.
Received July 2, 2004; in final form February 26, 2005
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S. H. D. MAMUYA, M. BRATVEIT, J. MWAISELAGE, and B. E. MOEN Variability of Exposure and Estimation of Cumulative Exposure in a Manually Operated Coal Mine Ann. Hyg., October 1, 2006; 50(7): 737 - 745. [Abstract] [Full Text] [PDF]
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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]
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