Erik Tielemans

Publications of Erik Tielemans

• Stoffenmanager Nano Version 1.0: A Web-Based Tool for Risk Prioritization of Airborne Manufactured Nano Objects.

  Authors: Birgit Van Duuren-Stuurman, Stefan R Vink, Koen J M Verbist, Henri G A Heussen, Derk H Brouwer, Dinant E D Kroese, Maikel F J Van Niftrik, Erik Tielemans, Wouter Fransman

  The Annals of occupational hygiene. 01/2012;

  Stoffenmanager Nano (version 1.0) is a risk-banding tool developed for employers and employees to prioritize health risks occurring as a result of exposure to manufactured nano objects (MNOs) for aStoffenmanager Nano (version 1.0) is a risk-banding tool developed for employers and employees to prioritize health risks occurring as a result of exposure to manufactured nano objects (MNOs) for a broad range of worker scenarios and to assist implementation of control measures to reduce exposure levels. In order to prioritize the health risks, the Stoffenmanager Nano combines the available hazard information of a substance with a qualitative estimate of potential for inhalation exposure. The development of the Stoffenmanager Nano started with a review of the available literature on control banding. Input parameters for the hazard assessment of MNOs were selected based on the availability of these parameters in, for instance, Safety Data Sheets or product information sheets. The conceptual exposure model described by Schneider et al. (2011) was used as the starting point for exposure banding. During the development of the Stoffenmanager Nano tool, the precautionary principle was applied to deal with the uncertainty regarding hazard and exposure assessment of MNOs. Subsequently, the model was converted into an online tool (http://nano.stoffenmanager.nl), tested, and reviewed by a number of companies. In this paper, we describe the Stoffenmanager Nano. This tool offers a practical approach for risk prioritization in exposure situations where quantitative risk assessment is currently not possible. Updates of this first version are anticipated as more data become available in the future.

• Harmonization of measurement strategies for exposure to manufactured nano-objects; report of a workshop.

  Authors: Derk Brouwer, Markus Berges, Mohammed Abbas Virji, Wouter Fransman, Dhimiter Bello, Laura Hodson, Stefan Gabriel, Erik Tielemans

  The Annals of occupational hygiene. 12/2011; 56(1):1-9.

  The present paper summarizes the outcome of the discussions at the First International Scientific Workshop on Harmonization of Strategies to Measure and Analyze Exposure to (Manufactured)The present paper summarizes the outcome of the discussions at the First International Scientific Workshop on Harmonization of Strategies to Measure and Analyze Exposure to (Manufactured) Nano-objects in Workplace Air that was organized and hosted by the Netherlands Organization for Applied Scientific Research (TNO) and the Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA) (Zeist, The Netherlands, December 2010). It reflects the discussions by 25 international participants in the area of occupational (nano) exposure assessment from Europe, USA, Japan, and Korea on nano-specific issues related to the three identified topics: (i) measurement strategies; (ii) analyzing, evaluating, and reporting of exposure data; and (iii) core information for (exposure) data storage. Preliminary recommendations were achieved with respect to (i) a multimetric approach to exposure assessment, a minimal set of data to be collected, and basic data analysis and reporting as well as (ii) a minimum set of contextual information to be collected and reported. Other issues that have been identified and are of great interest include (i) the need for guidance on statistical approaches to analyze time-series data and on electron microscopy analysis and its reporting and (ii) the need for and possible structure of a (joint) database to store and merge data. To make progress in the process of harmonization, it was concluded that achieving agreement among researchers on the preliminary recommendations of the workshop is urgent.

• Use of the MEGA Exposure Database for the Validation of the Stoffenmanager Model.

  Authors: Dorothea Koppisch, Jody Schinkel, Stefan Gabriel, Wouter Fransman, Erik Tielemans

  The Annals of occupational hygiene. 11/2011;

  OBJECTIVES: This paper explores the usefulness of the exposure database MEGA for model validation and evaluates the capability of two Stoffenmanager model equations (i.e. handling of powders/granulesOBJECTIVES: This paper explores the usefulness of the exposure database MEGA for model validation and evaluates the capability of two Stoffenmanager model equations (i.e. handling of powders/granules and machining) to estimate workers exposure to inhalable dust. METHODS: For the task groups, 'handling of powders and granules' (handling) and 'machining of wood and stone' (machining) measurements were selected from MEGA and grouped in scenarios depending on task, product, and control measures. The predictive capability of the model was tested by calculating the relative bias of the single measurements and the correlation between geometric means (GMs) for scenarios. The conservatism of the model was evaluated by checking if the percentage of measurement values above the 90th percentile estimate was ≤10%. RESULTS: From 22 596 personal measurements on inhalable dust within MEGA, 390 could be selected for handling and 1133 for machining. The relative bias for the task groups was -25 and 68%, respectively, the percentage of measurements with a higher result than the estimated 90th percentile 11 and 7%. Correlations on a scenario level were good for both model equations as well for the GM (handling: r(s) = 0.90, n = 15 scenarios; machining: r(s) = 0.84, n = 22 scenarios) as for the 90th percentile (handling: r(s) = 0.79; machining: r(s) = 0.76). CONCLUSIONS: The MEGA database could be used for model validation, although the presented analyses have learned that improvements in the database are necessary for modelling purposes in the future. For a substantial amount of data, contextual information on exposure determinants in addition to basic core information is stored in this database. The relative low bias, the good correlation, and the level of conservatism of the tested model show that the Stoffenmanager can be regarded as a useful Tier 1 model for the Registration, Evaluation, Authorisation and Restriction of Chemicals legislation.

• Advanced REACH Tool: development and application of the substance emission potential modifying factor.

  Authors: Martie van Tongeren, Wouter Fransman, Sally Spankie, Martin Tischer, Derk Brouwer, Jody Schinkel, John W Cherrie, Erik Tielemans

  The Annals of occupational hygiene. 11/2011; 55(9):980-8.

  The Advanced REACH Tool (ART) is an exposure assessment tool that combines mechanistically modelled inhalation exposure estimates with available exposure data using a Bayesian approach. TheThe Advanced REACH Tool (ART) is an exposure assessment tool that combines mechanistically modelled inhalation exposure estimates with available exposure data using a Bayesian approach. The mechanistic model is based on nine independent principal modifying factors (MF). One of these MF is the substance emission potential, which addresses the intrinsic substance properties as determinants of the emission from a source. This paper describes the current knowledge and evidence on intrinsic characteristics of solids and liquids that determine the potential for their release into workplace air. The principal factor determining the release of aerosols from handling or processing powdered, granular, or pelletized materials is the dustiness of the material, as well as the weight fraction of the substance of interest in the powder and the moisture content. The partial vapour pressure is the main intrinsic factor determining the substance emission potential for emission of vapours. For generation of mist, the substance emission potential is determined by the viscosity of the liquid as well as the weight fraction of the substance of interest in the liquid. Within ART release of vapours is considered for substances with a partial vapour pressure at the process temperature of 10 Pa or more, while mist formation is considered for substances with a vapour pressure ≤ 10 Pa. Relative multipliers are assigned for most of the intrinsic factors, with the exception of the weight fraction and the vapour pressure, which is applied as a continuous variable in the estimation of the substance emission potential. Currently, estimation of substance emission potential is not available for fumes, fibres, and gases. The substance emission potential takes account of the latest thinking on emissions of dusts, mists, and vapours and in our view provides a good balance between theory and pragmatism. Expanding the knowledge base on substance emission potential will improve the predictive power of occupational exposure models and thereby the accuracy and precision of the exposure estimates.

• Revisiting the effect of room size and general ventilation on the relationship between near- and far-field air concentrations.

  Authors: John W Cherrie, Laura Maccalman, Wouter Fransman, Erik Tielemans, Martin Tischer, Martie Van Tongeren

  The Annals of occupational hygiene. 11/2011; 55(9):1006-15.

  In 1999, Cherrie carried out a series of mathematical simulations to investigate dispersion of pollutants through two indoor zones: the near-field (NF) and the far-field (FF). The results of theseIn 1999, Cherrie carried out a series of mathematical simulations to investigate dispersion of pollutants through two indoor zones: the near-field (NF) and the far-field (FF). The results of these simulations were used to derive modifying factors for use in exposure modeling. However, in the original simulations, no account was taken of deposition on surfaces, either from sedimentation of aerosols or other mechanisms or the potential effects of intermittent or short duration sources. These factors may affect pollutant dispersion, particularly the relationship between NF and FF levels. The Advanced REACH Tool (ART) is based on a two-zone dispersion paradigm. Further simulations have been carried out to help ensure that the ART realistically reflects pollutant dispersion. Pollutant dispersion has been simulated using a two-compartment well-mixed box model to represent the NF and the FF. Simulations were repeated for a range of room sizes and ventilation conditions. Intermittent sources (e.g. batch processes) were simulated by having the source active for 1 h followed by a 1-h gap, while short duration work emissions were set to last for 10 min, 30 min, 1 h, or 4 h, within the working day. Deposition was modeled by adding an equivalent air exchange rate based on published research data. Simulations were undertaken for non-volatile, monodisperse aerosols of aerodynamic diameter: 0.3, 1, 3, 10, 30, and 100 μm and the results were then interpreted in terms of typical polydisperse industrial aerosols. Room size and general ventilation strongly influenced dispersion from the NF to the FF as Cherrie had originally found. When varying the duration of the simulation, the biggest difference from continuous work was seen in small poorly ventilated rooms, with the ratio of the NF to FF concentration for 1-h work in the smallest room and lowest air exchange rate being a fifth of that calculated for continuous work. For large rooms and high general ventilation rates, the duration of the activity made little difference to dispersion. The results suggest that for the purposes of dispersion intermittent batch work is equivalent to continuous work. For typical simulated poly-disperse aerosols, the main effect of aerosol deposition was to reduce the predicted high concentrations compared to vapours when working in confined spaces. Both short duration of source emissions and deposition of aerosols have an important effect on dispersion, and the results from this study have been reflected in the ART model.

• Advanced Reach Tool (ART): development of the mechanistic model.

  Authors: Wouter Fransman, Martie Van Tongeren, John W Cherrie, Martin Tischer, Thomas Schneider, Jody Schinkel, Hans Kromhout, Nick Warren, Henk Goede, Erik Tielemans

  The Annals of occupational hygiene. 11/2011; 55(9):957-79.

  This paper describes the development of the mechanistic model within a collaborative project, referred to as the Advanced REACH Tool (ART) project, to develop a tool to model inhalation exposure forThis paper describes the development of the mechanistic model within a collaborative project, referred to as the Advanced REACH Tool (ART) project, to develop a tool to model inhalation exposure for workers sharing similar operational conditions across different industries and locations in Europe. The ART mechanistic model is based on a conceptual framework that adopts a source receptor approach, which describes the transport of a contaminant from the source to the receptor and defines seven independent principal modifying factors: substance emission potential, activity emission potential, localized controls, segregation, personal enclosure, surface contamination, and dispersion. ART currently differentiates between three different exposure types: vapours, mists, and dust (fumes, fibres, and gases are presently excluded). Various sources were used to assign numerical values to the multipliers to each modifying factor. The evidence used to underpin this assessment procedure was based on chemical and physical laws. In addition, empirical data obtained from literature were used. Where this was not possible, expert elicitation was applied for the assessment procedure. Multipliers for all modifying factors were peer reviewed by leading experts from industry, research institutes, and public authorities across the globe. In addition, several workshops with experts were organized to discuss the proposed exposure multipliers. The mechanistic model is a central part of the ART tool and with advancing knowledge on exposure, determinants will require updates and refinements on a continuous basis, such as the effect of worker behaviour on personal exposure, 'best practice' values that describe the maximum achievable effectiveness of control measures, the intrinsic emission potential of various solid objects (e.g. metal, glass, plastics, etc.), and extending the applicability domain to certain types of exposures (e.g. gas, fume, and fibre exposure).

• Advanced REACH Tool (ART): overview of version 1.0 and research needs.

  Authors: Erik Tielemans, Nick Warren, Wouter Fransman, Martie Van Tongeren, Kevin McNally, Martin Tischer, Peter Ritchie, Hans Kromhout, Jody Schinkel, Thomas Schneider, John W Cherrie

  The Annals of occupational hygiene. 11/2011; 55(9):949-56.

  This paper provides an outline of the Advanced REACH Tool (ART) version 1.0 and a discussion of how it could be further developed. ART is a higher tier exposure assessment tool that combinesThis paper provides an outline of the Advanced REACH Tool (ART) version 1.0 and a discussion of how it could be further developed. ART is a higher tier exposure assessment tool that combines mechanistically modelled inhalation exposure predictions with available exposure data using a Bayesian approach. ART assesses exposure for scenarios across different plants and sites. Estimates are provided for different percentiles of the exposure distribution and confidence intervals around the estimate. It also produces exposure estimates in the absence of data, but uncertainty of the estimates will decrease when results of exposure measurements are included. The tool has been calibrated using a broad range of exposure data and provides estimates for exposure to vapours, mists, and dusts. ART has a robust and stable conceptual basis but will be refined in the future and should therefore be considered an evolving system. High-priority areas for future research are identified in this paper and include the integration of partially analogous measurement series, inclusion of company and site-specific assessments, user decision strategies linked to ART predictions, evaluation of validity and reliability of ART, exploring the possibilities for incorporating the dermal route and integration of ART predictions with tools for modelling internal dose. ART is initially developed in the scope of REACH but is equally useful for exposure assessment in other areas.

• Classification of occupational activities for assessment of inhalation exposure.

  Authors: Hans Marquart, Thomas Schneider, Henk Goede, Martin Tischer, Jody Schinkel, Nick Warren, Wouter Fransman, Suzanne Spaan, Martie Van Tongeren, Hans Kromhout, Erik Tielemans, John W Cherrie

  The Annals of occupational hygiene. 09/2011; 55(9):989-1005.

  There is a large variety of activities in workplaces that can lead to emission of substances. Coding systems based on determinants of emission have so far not been developed. In this paper, a systemThere is a large variety of activities in workplaces that can lead to emission of substances. Coding systems based on determinants of emission have so far not been developed. In this paper, a system of Activity Classes and Activity Subclasses is proposed for categorizing activities involving chemical use. Activity Classes share their so-called 'emission generation mechanisms' and physical state of the product handled and the underlying determinants of emission. A number of (industrial) stakeholders actively participated in testing and fine-tuning the system. With the help of these stakeholders, it was found to be relatively easy to allocate a large number of activities to the Activity Classes and Activity Subclasses. The system facilitates a more structured classification of activities in exposure databases, a structured analysis of the analogy of exposure activities, and a transparent quantification of the activity emission potential in (new) exposure assessment models. The first use of the system is in the Advanced REACH Tool.

• Cost-benefit analysis in occupational health: a comparison of intervention scenarios for occupational asthma and rhinitis among bakery workers.

  Authors: Tim Meijster, Birgit van Duuren-Stuurman, Dick Heederik, Remko Houba, Ernst Koningsveld, Nicholas Warren, Erik Tielemans

  Occupational and environmental medicine. 05/2011; 68(10):739-45.

  Use of cost-benefit analysis in occupational health increases insight into the intervention strategy that maximises the cost-benefit ratio. This study presents a methodological framework identifyingUse of cost-benefit analysis in occupational health increases insight into the intervention strategy that maximises the cost-benefit ratio. This study presents a methodological framework identifying the most important elements of a cost-benefit analysis for occupational health settings. One of the main aims of the methodology is to evaluate cost-benefit ratios for different stakeholders (employers, employees and society). The developed methodology was applied to two intervention strategies focused on reducing respiratory diseases. A cost-benefit framework was developed and used to set up a calculation spreadsheet containing the inputs and algorithms required to calculate the costs and benefits for all cost elements. Inputs from a large variety of sources were used to calculate total costs, total benefits, net costs and the benefit-to-costs ratio for both intervention scenarios. Implementation of a covenant intervention program resulted in a net benefit of €16 848 546 over 20 years for a population of 10 000 workers. Implementation was cost-effective for all stakeholders. For a health surveillance scenario, total benefits resulting from a decreased disease burden were estimated to be €44 659 352. The costs of the interventions could not be calculated. This study provides important insights for developing effective intervention strategies in the field of occupational medicine. Use of a model based approach enables investigation of those parameters most likely to impact on the effectiveness and costs of interventions for work related diseases. Our case study highlights the importance of considering different perspectives (of employers, society and employees) in assessing and sharing the costs and benefits of interventions.

• Conceptual model for assessment of inhalation exposure to manufactured nanoparticles.

  Authors: Thomas Schneider, Derk Henri Brouwer, Ismo Kalevi Koponen, Keld Alstrup Jensen, Wouter Fransman, Birgit Van Duuren-Stuurman, Martie Van Tongeren, Erik Tielemans

  Journal of exposure science & environmental epidemiology. 03/2011; 21(5):450-63.

  As workplace air measurements of manufactured nanoparticles are relatively expensive to conduct, models can be helpful for a first tier assessment of exposure. A conceptual model was developed toAs workplace air measurements of manufactured nanoparticles are relatively expensive to conduct, models can be helpful for a first tier assessment of exposure. A conceptual model was developed to give a framework for such models. The basis for the model is an analysis of the fate and underlying mechanisms of nanoparticles emitted by a source during transport to a receptor. Four source domains are distinguished; that is, production, handling of bulk product, dispersion of ready-to-use nanoproducts, fracturing and abrasion of end products. These domains represent different generation mechanisms that determine particle emission characteristics; for example, emission rate, particle size distribution, and source location. During transport, homogeneous coagulation, scavenging, and surface deposition will determine the fate of the particles and cause changes in both particle size distributions and number concentrations. The degree of impact of these processes will be determined by a variety of factors including the concentration and size mode of the emitted nanoparticles and background aerosols, source to receptor distance, and ventilation characteristics. The second part of the paper focuses on to what extent the conceptual model could be fit into an existing mechanistic predictive model for ''conventional'' exposures. The model should be seen as a framework for characterization of exposure to (manufactured) nanoparticles and future exposure modeling.

• Advanced REACH Tool (ART): calibration of the mechanistic model.

  Authors: Jody Schinkel, Nicholas Warren, Wouter Fransman, Martie van Tongeren, Patricia McDonnell, Eef Voogd, John W Cherrie, Martin Tischer, Hans Kromhout, Erik Tielemans

  Journal of environmental monitoring : JEM. 03/2011; 13(5):1374-82.

  The mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper areThe mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper are threefold: to study whether the mechanistic model scores are accurately ranked in relation to exposure measurements; to enable the mechanistic model to estimate actual exposure levels rather than relative scores; and to provide a method of quantifying model uncertainty. Stringent data quality guidelines were applied to the collated data. Linear mixed effects models were used to evaluate the association between relative ART model scores and measurements. A random scenario and company component of variance were introduced to reflect the model uncertainty. Stratified analyses were conducted for different forms of exposure (abrasive dust, dust, vapours and mists). In total more than 2000 good quality measurements were available for the calibration of the mechanistic model. The calibration showed that after calibration the mechanistic model of ART was able to estimate geometric mean (GM) exposure levels with 90% confidence for a given scenario to lie within a factor between two and six of the measured GM depending upon the form of exposure.

• What is the best strategy to reduce the burden of occupational asthma and allergy in bakers?

  Authors: Tim Meijster, Nick Warren, Dick Heederik, Erik Tielemans

  Occupational and environmental medicine. 03/2011; 68(3):176-82.

  Insight into the effectiveness of intervention strategies will help realise a decrease in the occupational disease burden from (allergic) respiratory diseases in the bakery population. To use aInsight into the effectiveness of intervention strategies will help realise a decrease in the occupational disease burden from (allergic) respiratory diseases in the bakery population. To use a simulation model to assess the impact of different intervention strategies on the disease burden of the bakery population over time. A recently developed dynamic population based model was used to prospectively evaluate the impact on disease burden resulting from different intervention strategies. We distinguished interventions based on exposure reductions for flour dust and fungal α-amylase, health surveillance combined with reduction in exposure, and pre-employment screening. The impact of most interventions on disease burden was limited, generally less than 50% for lower respiratory symptoms and disabling occupational asthma. Only the rigorous health surveillance strategy, identifying workers who are sensitised or report upper respiratory symptoms and decreasing their individual exposures by 90% shortly after diagnosis, resulted in a decrease of almost 60% in disease burden after 20 years. This study demonstrates that different intervention strategies have substantially different impacts on the burden of disease. The time window during which changes occur differs considerably between strategies. This information can assist policy makers in their choice of intervention and gives guidance for achievable reductions in disease burden.

• Variability of biomarkers in volunteer studies: The biological component.

  Authors: Suzanne Spaan, Wouter Fransman, Nick Warren, Richard Cotton, John Cocker, Erik Tielemans

  Toxicology letters. 10/2010; 198(2):144-51.

  Biological monitoring has become one of the methods to measure exposure, with the advantage that it gives information about the concentration of a substance that actually enters the body and reflectsBiological monitoring has become one of the methods to measure exposure, with the advantage that it gives information about the concentration of a substance that actually enters the body and reflects the inter-individual differences in uptake and metabolic variation. However, limited information is available on inter- and intra-individual variability of biomarkers. The aim of this study was to gather information about the biological component of inter-individual variation in biomarkers using results from volunteer studies. Open literature and other (internal) sources were searched to find human volunteer studies utilizing biological monitoring. Ultimately 41 studies were included in our analysis, with a total of 6747 observations for one or more biomarkers from 223 volunteers. The data from these studies were grouped on the basis of study, substance under investigation, exposure route, biological matrix, exposure duration, dose and number of exposure events to obtain 278 homogeneous groups (strata) for statistical analysis. Variability was assessed in two ways. Firstly, estimates of biomarker half-life were calculated for each individual, thereby allowing the estimation of inter-individual variability in half-lives within the homogeneous groups. Secondly, variation in biomarker concentrations at a given time point was estimated. For estimated half-lives the GSDs ranged from 1.0 to 6.8. The variability in estimated half-lives did not differ much for the different types of substances. For concentrations at a given time point the average GSDs within strata ranged from 1.0 to 5.6. Again, variability did not differ much for different groups (e.g., type of substance). The median variability component was 0.11 (range 0-3.0). In conclusion, volunteer studies enable the estimation of both variation in half-lives and variation in biomarker levels in the well-defined homogeneous groups. Comparison of our results with other studies indicates that variation due to biological differences within and between people is quite substantial in homogeneous exposure groups. The relative contribution of this biological component to the total variation will be smaller when variance components are estimated in less homogeneous groups, such as those in occupational and environmental settings.

• Stoffenmanager exposure model: company-specific exposure assessments using a Bayesian methodology.

  Authors: Peter van de Ven, Wouter Fransman, Jody Schinkel, Carina Rubingh, Nicholas Warren, Erik Tielemans

  Journal of occupational and environmental hygiene. 04/2010; 7(4):216-23.

  The web-based tool "Stoffenmanager" was initially developed to assist small- and medium-sized enterprises in the Netherlands to make qualitative risk assessments and to provide advice on control atThe web-based tool "Stoffenmanager" was initially developed to assist small- and medium-sized enterprises in the Netherlands to make qualitative risk assessments and to provide advice on control at the workplace. The tool uses a mechanistic model to arrive at a "Stoffenmanager score" for exposure. In a recent study it was shown that variability in exposure measurements given a certain Stoffenmanager score is still substantial. This article discusses an extension to the tool that uses a Bayesian methodology for quantitative workplace/scenario-specific exposure assessment. This methodology allows for real exposure data observed in the company of interest to be combined with the prior estimate (based on the Stoffenmanager model). The output of the tool is a company-specific assessment of exposure levels for a scenario for which data is available. The Bayesian approach provides a transparent way of synthesizing different types of information and is especially preferred in situations where available data is sparse, as is often the case in small- and medium sized-enterprises. Real-world examples as well as simulation studies were used to assess how different parameters such as sample size, difference between prior and data, uncertainty in prior, and variance in the data affect the eventual posterior distribution of a Bayesian exposure assessment.

• A dynamic population-based model for the development of work related respiratory health effects amongst bakery workers.

  Authors: Nick Warren, Tim Meijster, Dick Heederik, Erik Tielemans

  Occupational and environmental medicine. 10/2009;

  OBJECTIVES: This paper presents a dynamic population-based model for the development of sensitisation and respiratory symptoms in bakery workers. The model simulates a population of individualOBJECTIVES: This paper presents a dynamic population-based model for the development of sensitisation and respiratory symptoms in bakery workers. The model simulates a population of individual workers longitudinally and tracks the development of work-related sensitisation and respiratory symptoms in each worker. METHODS: The model has three components: a multi-stage disease model describing the development of sensitisation and respiratory symptoms in each worker over time; an exposure model describing occupational exposure to flour dust and allergens; and a basic population model describing the length of a worker's career in the bakery sector and the influx of new workers. Each worker's disease state is modelled independently using a discrete time Markov Chain, updated yearly using each individual's simulated exposure. A Bayesian analysis of data from a recent epidemiological study provided estimates of the yearly transition probabilities between disease states. RESULTS: For non-atopic/non-sensitised workers the estimated probabilities of developing moderate (upper respiratory) symptoms and progression to severe (lower respiratory) symptoms are 0.4% (95% C.I. 0.3%-0.5%) and 1.1% (95% C.I. 0.6%-1.9%) per mg/m3/year flour dust respectively and approximately twice these for atopic workers. The model predicts that 36% (95% C.I. 26%-46%) of workers with severe symptoms are sensitised to wheat and 22% (95% C.I. 12%-37%) to amylase. The predicted mean latency period for respiratory symptoms was 10.3 years (95% C.I. 8.3-12.3). CONCLUSIONS: Whilst the model provides a valuable population level representation of the mechanisms contributing to respiratory diseases in bakers, it was primarily developed for use in quantitative Health Impact Assessment. Future research will use the model to evaluate a range of workplace interventions, including achievable reductions in exposure and health surveillance. The general methodology is applicable to other diseases such as Chronic Obstructive Pulmonary Disease (COPD), Silicosis and Musculoskeletal Disorders and could be particularly valuable for forecasting changes in long latency diseases.

• Cross-validation and refinement of the Stoffenmanager as a first tier exposure assessment tool for REACH.

  Authors: Jody Schinkel, Wouter Fransman, Henri Heussen, Hans Kromhout, Hans Marquart, Erik Tielemans

  Occupational and environmental medicine. 09/2009;

  OBJECTIVES: For regulatory risk assessment under REACH a tiered approach is proposed in which the first tier models should provide a conservative exposure estimate that can discriminate betweenOBJECTIVES: For regulatory risk assessment under REACH a tiered approach is proposed in which the first tier models should provide a conservative exposure estimate that can discriminate between scenarios of concern and those which are not. The Stoffenmanager is mentioned as first tier approach in the REACH guidance. In an attempt to investigate the validity of the Stoffenmanager algorithms a cross-validation study was performed. METHODS: Exposure estimates using the Stoffenmanager algorithms were compared with exposure measurement results (n=254). Correlations between observed and predicted exposures, bias and precision were calculated. Stratified analyses were performed for the scenarios "handling of powders and granules" (n=82), "handling solids resulting in comminuting" (n=60), "handling of low-volatile liquids" (n=40) and for "handling of volatile liquids" (n=72). RESULTS: The relative bias of the 4 algorithms ranged between -9% and -77% with a precision of approximately 1.7. The 90-percentile estimate of 1 out of 4 algorithms was not conservative enough. Based on these statistics and analyses of residual plots the underlying algorithm was adapted. Subsequently, the calibration and the cross-validation dataset were merged to one dataset (n=952) used for calibrating the adapted Stoffenmanager algorithms. This new calibration resulted in new exposure algorithms for the 4 scenarios. CONCLUSIONS: The Stoffenmanager is capable of discriminating among exposure levels mainly between scenarios in different companies. The 90-percentile estimates of the Stoffenmanager are verified to be sufficiently conservative. Therefore, the Stoffenmanager could be a useful Tier 1 exposure assessment tool for REACH.

• Effect of an intervention aimed at reducing the risk of allergic respiratory disease in bakers: change in flour dust and fungal alpha-amylase levels.

  Authors: Tim Meijster, Erik Tielemans, Dick J J Heederik

  Occupational and environmental medicine. 05/2009;

  Introduction: We evaluated the effect on exposure of an intervention program, which focussed on risk education and providing information on good work practices. This intervention program was enrolledIntroduction: We evaluated the effect on exposure of an intervention program, which focussed on risk education and providing information on good work practices. This intervention program was enrolled as part of a Dutch covenant in the flour processing industry (industrial bakeries, flour mills, ingredient producers). METHODS: Data from several measurement surveys collected pre- and post-intervention were used to evaluate changes in exposure over time. All datasets contained personal measurements analysed for flour dust and fungal alpha-amylase contents and contextual information was available on process characteristics, work practice, and use of control measures. RESULTS: Changes in exposure over time varied substantially between sectors and jobs. For bakeries a modest downward annual trend of -2% was found for flour dust and -8% for amylase. For flour mills the annual trend for flour dust was -12%, no significant trend was observed for amylase. For ingredient producers results were generally non significant but indicated a reduction in flour dust exposure and increase in fungal alpha-amylase exposure. Modest increase in use of control measures and proper work practices were reported in most sectors, especially the use of LEV and decreased use of compressed air. CONCLUSIONS: The magnitude of the observed reductions in exposure levels indicate that the sector-wide intervention strategy implemented during the covenant period had a limited overall effect. This indicates that a more rigorous approach is needed to substantially decrease the exposure levels to flour dust and related allergens and respectively the prevalence of associated occupational diseases.

• Conceptual Model for Assessment of Inhalation Exposure: Defining Modifying Factors.

  Authors: Erik Tielemans, Thomas Schneider, Henk Goede, Martin Tischer, Nick Warren, Hans Kromhout, Martie van Tongeren, Joop Van Hemmen, John W Cherrie

  The Annals of occupational hygiene. 10/2008;

  The present paper proposes a source-receptor model to schematically describe inhalation exposure to help understand the complex processes leading to inhalation of hazardous substances. The modelThe present paper proposes a source-receptor model to schematically describe inhalation exposure to help understand the complex processes leading to inhalation of hazardous substances. The model considers a stepwise transfer of a contaminant from the source to the receptor. The conceptual model is constructed using three components, i.e. (i) the source, (ii) various transmission compartments and (iii) the receptor, and describes the contaminant's emission and its pattern of transport. Based on this conceptual model, a list of nine mutually independent principal modifying factors (MFs) is proposed: activity emission potential, substance emission potential, localized control, separation, segregation, dilution, worker behavior, surface contamination and respiratory protection. These MFs describe the exposure process at a high level of abstraction so that the model can be generically applicable. A list of exposure determinants underlying each of these principal MFs is proposed to describe the exposure process at a more detailed level. The presented conceptual model is developed in conjunction with an activity taxonomy as described in a separate paper. The proposed conceptual model and MFs should be seen as 'building blocks' for development of higher tier exposure models.

• Development and Evaluation of an Exposure Control Efficacy Library (ECEL).

  Authors: Wouter Fransman, Jody Schinkel, Tim Meijster, Joop Van Hemmen, Erik Tielemans, Henk Goede

  The Annals of occupational hygiene. 09/2008;

  OBJECTIVES: This paper describes the development and evaluation of an evidence database on the effectiveness of risk management measures (RMMs) to control inhalation exposure. This database isOBJECTIVES: This paper describes the development and evaluation of an evidence database on the effectiveness of risk management measures (RMMs) to control inhalation exposure. This database is referred to as Exposure Control Efficacy Library (ECEL). METHODS: A comprehensive review of scientific journals in the occupational hygiene field was undertaken. Efficacy values for RMMs in conjunction with contextual information on study design, sampling strategy and measurement type (among other parameters) were stored in an MS Access database. In total, 433 efficacy values for six RMM groups (i.e. enclosure, local exhaust ventilation, specialized ventilation, general ventilation, suppression techniques and separation of the worker) were collected from 90 peer-reviewed publications. These RMM categories were subdivided into more specific categories. RESULTS: Estimated average efficacy values ranged from 87% for specialized ventilation to 43% for general ventilation. Substantial variation in efficacy values was observed within RMM categories based on differences in selected covariables within each study (i.e. study design, sampling strategy, measurement type and others). More contrast in efficacy values was observed when evaluating more detailed subcategories. CONCLUSIONS: It is envisaged that ECEL will contribute to exposure modelling, but should be supplemented with expert opinion, preferably in a formal expert elicitation procedure. The work presented here should be considered as a first attempt to collate and analyse RMM efficacy values and inclusion of additional (unpublished) exposure data is highly warranted.

• Evaluation of Peak Exposures in the Dutch Flour Processing Industry: Implications for Intervention Strategies.

  Authors: Tim Meijster, Erik Tielemans, Jody Schinkel, Dick Heederik

  The Annals of occupational hygiene. 08/2008;

  OBJECTIVES: To effectively decrease occupational exposure to flour dust and related allergens, detailed information on exposure determinants and effectiveness of control measures is essential. InOBJECTIVES: To effectively decrease occupational exposure to flour dust and related allergens, detailed information on exposure determinants and effectiveness of control measures is essential. In this paper, we use personal real-time exposure measurements to get more insight into the relationship between specific work characteristics, including the use of control measures, and (peak) exposure to flour dust. The study has three objectives: (i) identify tasks and activities related to peak exposure, (ii) identify control measures and other important exposure determinants and (iii) assess the potential impact of these control measures on the (peak) exposure to flour dust. METHODS: A data set containing 82 real-time exposure measurements in combination with information from detailed observations was used to study the association between peak exposures and different tasks, activities and other determinants such as control measures. Descriptive statistics of peak exposure on job level were generated as well as information on contribution of task-specific peak exposures to time-weighted average (TWA) exposure levels. Finally, we evaluated the efficacy of a variety of control measures on task exposure by comparing exposure levels of groups of workers with and without controls. RESULTS: In workers included in this study, >75% of TWA exposure is directly associated with peak exposures during a limited set of well-defined tasks/activities. The impact of a single task on population TWA exposure is generally limited (<40%). Worker behavior seems an important determinant in effective exposure control for many tasks. CONCLUSIONS: Data from real-time measurements provide important detailed information with respect to exposure determinants and control measures, not obtainable from conventional measurement studies focusing at TWA exposure. This information is essential to perform prospective impact assessments of intervention strategies on the populations' exposure distribution.