Wouter Fransman
Utrecht University
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Epidemiology | 2007
Wouter Fransman; N. Roeleveld; S.J.M. Peelen; W. de Kort; Hans Kromhout; Dick Heederik
Background: Nurses and other hospital workers are exposed to antineoplastic drugs during daily activities. Previous studies suggest that antineoplastic drugs at occupational exposure levels may be toxic to reproduction, but these studies are not consistent or conclusive. Methods: Self-administered questionnaires were completed by 4393 exposed and nonexposed nurses employed between 1990 and 1997 (79% response). Questions were asked about pregnancy outcome, work-related exposures, and lifestyle. Exposure to antineoplastic drugs was estimated using task-based dermal exposure measurements and self-reported task frequencies. Time to pregnancy was modeled using survival analysis, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for other reproductive outcomes using multiple logistic regression analysis. Associations were further explored by nonparametric regression modeling. Results: Nurses highly exposed to antineoplastic drugs took longer to conceive than referent nurses (adjusted hazard ratio = 0.8; CI = 0.6–0.9). Exposure to antineoplastic drugs was associated with premature delivery (OR per unit increase in ln[exposure] = 1.08; CI = 1.00–1.17) and low birth weight (OR per unit increase in ln[exposure] = 1.11; 1.01–1.21). Penalized smoothed spline plots corroborated these log-linear relations. Spontaneous abortion, stillbirth, congenital anomalies, and sex of offspring appeared not to be related to exposure to antineoplastic drugs. Conclusion: Antineoplastic drugs may reduce fertility and increase poor neonatal outcomes among occupationally exposed oncology nurses.
Annals of Occupational Hygiene | 2012
Derk H. Brouwer; Markus Berges; Mohammed Abbas Virji; Wouter Fransman; Dhimiter Bello; Laura Hodson; Stefan Gabriel; Erik Tielemans
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.
Journal of Exposure Science and Environmental Epidemiology | 2011
Thomas Schneider; Derk H. Brouwer; Ismo K. Koponen; Keld Alstrup Jensen; Wouter Fransman; Birgit van Duuren-Stuurman; Martie van Tongeren; Erik Tielemans
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 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.
Annals of Occupational Hygiene | 2012
Birgit van Duuren-Stuurman; Stefan R. Vink; Koen Verbist; Henri Heussen; Derk H. Brouwer; Dinant E. D. Kroese; Maikel F. J. Van niftrik; Erik Tielemans; Wouter Fransman
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 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.
Annals of Occupational Hygiene | 2011
Erik Tielemans; Nick Warren; Wouter Fransman; Martie van Tongeren; Kevin McNally; Martin Tischer; Peter Ritchie; Hans Kromhout; Jody Schinkel; Thomas Schneider; John W. Cherrie
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 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.
Annals of Occupational Hygiene | 2008
Wouter Fransman; Jody Schinkel; Tim Meijster; Joop J. van Hemmen; Erik Tielemans; Henk Goede
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 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.
Journal of Environmental Monitoring | 2011
Jody Schinkel; Nicholas Warren; Wouter Fransman; Martie van Tongeren; Patricia McDonnell; Eef Voogd; John W. Cherrie; Martin Tischer; Hans Kromhout; Erik Tielemans
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 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.
Occupational and Environmental Medicine | 2010
Jody Schinkel; Wouter Fransman; Henri Heussen; Hans Kromhout; Hans Marquart; Erik Tielemans
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 between scenarios which are of concern and those which are not. The Stoffenmanager is mentioned as a 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 “handling of volatile liquids” (n=72). Results The relative bias of the four algorithms ranged between −9% and −77% with a precision of approximately 1.7. The 90th percentile estimate of one out of four 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 into one dataset (n=952) used for calibrating the adapted Stoffenmanager algorithms. This new calibration resulted in new exposure algorithms for the four scenarios. Conclusions The Stoffenmanager is capable of discriminating among exposure levels mainly between scenarios in different companies. The 90th 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.
Annals of Occupational Hygiene | 2011
John W. Cherrie; Laura MacCalman; Wouter Fransman; Erik Tielemans; Martin Tischer; Martie van Tongeren
OBJECTIVES 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 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.
Annals of Occupational Hygiene | 2015
Cindy Bekker; Eelco Kuijpers; Derk H. Brouwer; Roel Vermeulen; Wouter Fransman
BACKGROUND Occupational exposure to manufactured nano-objects and their agglomerates, and aggregates (NOAA) has been described in several workplace air monitoring studies. However, data pooling for general conclusions and exposure estimates are hampered by limited exposure data across the occupational life cycle of NOAA and a lack in comparability between the methods of collecting and analysing the data. By applying a consistent method of collecting and analysing the workplace exposure data, this study aimed to provide information about the occupational NOAA exposure levels across various life cycle stages of NOAA in the Netherlands which can also be used for multi-purpose use. METHODS Personal/near field task-based exposure data was collected using a multi-source exposure assessment method collecting real time particle number concentration, particle size distribution (PSD), filter-based samples for morphological, and elemental analysis and detailed contextual information. A decision logic was followed allowing a consistent and objective way of analysing the exposure data. RESULTS In total, 46 measurement surveys were conducted at 15 companies covering 18 different exposure situations across various occupational life cycle stages of NOAA. Highest activity-effect levels were found during replacement of big bags (<1000-76000 # cm(-3)), mixing/dumping of powders manually (<1000-52000 # cm(-3)) and mechanically (<1000-100000 # cm(-3)), and spraying of liquid (2000-800000 # cm(-3)) showing a high variability between and within the various exposure situations. In general, a limited change in PSD was found during the activity compared to the background. CONCLUSIONS This broad-scale exposure study gives a comprehensive overview of the NOAA exposure situations in the Netherlands and an indication of the levels of occupational exposure to NOAA across various life cycle of NOAA. The collected workplace exposure data and contextual information will serve as basis for future pooling of data and modelling of worker exposure.