E. Tielemans

Pesticide exposure and decreased fertilisation rates in vitro

The effect of paternal occupational exposures on fertilising ability was investigated in 836 couples who sought in-vitro fertilisation treatment. Fertilisation rates were significantly decreased for couples with paternal pesticide exposure.

Paternal occupational exposures and embryo implantation rates after IVF

OBJECTIVEnTo investigate any influence of paternal occupational exposures on implantation rates after IVF.nnnDESIGNnCohort study of couples who sought IVF treatment.nnnSETTINGnUniversity Hospital Utrecht, The Netherlands.nnnPATIENT(S)nThe study population was composed of 726 couples pursuing IVF treatment.nnnINTERVENTION(S)nOnly the earliest IVF treatment cycle with ET was selected for the analysis. All couples filled in a generic questionnaire on lifestyle factors and details about their occupation. In addition, more detailed exposure information was obtained for pesticides with use of job-specific questionnaires and a subsequent telephone interview.nnnMAIN OUTCOME MEASURE(S)nThe implantation rate was defined as the number of gestational sacs seen with ultrasound at 6-7 weeks of pregnancy, divided by the number of embryos replaced.nnnRESULT(S)nA significantly reduced implantation rate was seen among couples with male partners working in occupations with presumably high levels of organic solvent exposure. Conversely, paternal pesticide exposure was significantly associated with an increased implantation rate. Paternal exposures to metal dust or fumes and welding fumes were not related to the probability of implantation.nnnCONCLUSION(S)nThe findings suggested that paternal organic solvent exposure decreased the implantation rate among couples undergoing IVF-ET treatment.

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

Objectives 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 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. Methods 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. Results Implementation of a covenant intervention program resulted in a net benefit of €16u2008848u2008546 over 20u2005years for a population of 10u2008000 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 €44u2008659u2008352. The costs of the interventions could not be calculated. Conclusion 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.

Exposure profiles of pesticides among greenhouse workers: Implications for epidemiological studies

The aim of this study was to assess exposure to pesticides for a longitudinal epidemiological study on adverse reproduction effects among greenhouse workers. Detailed information on pesticide use among greenhouse workers was obtained on a monthly basis through self-administered questionnaires and subsequent workplace surveys. Questionnaires were filled in for a whole year. Dermal exposure rankings were developed for each task using the observational method Dermal Exposure Assessment Method (DREAM). Exposure scores were calculated for each worker for each month during the year, taking into account frequency, duration and exposure intensity for each task. A total number of 116 different active ingredients were used in the population, whereas a mean number of 15 active ingredients were applied per greenhouse. DREAM observations provided insight into the exposure intensity of 12 application techniques and three mixing and loading activities. Relatively high DREAM scores were obtained for scattering, fogging, dusting, and mixing and loading of powders. Observations with DREAM indicated that application with a horizontal ground-boom, motor driven boom, and bulb shower resulted in low dermal exposure. Exposure scores showed substantial variation between workers and over the year. It can be concluded that exposure variation between- and within greenhouses is very large, both in terms of chemical composition and exposure intensity. This may be a significant contributor to the inconsistent results of studies evaluating health effects of pesticide exposure.

A probabilistic assessment of the impact of interventions on oncology nurses' exposure to antineoplastic agents.

Objective: The main goal was to investigate the potential of a probabilistic approach for exposure assessment and use this information to evaluate the impact of a complex of policy actions/interventions on dermal exposure to antineoplastic agents among oncology nurses. The central theme of this study was to make optimal use of existing data, supplemented only with limited additional information from a questionnaire survey. Methods: A task based exposure model was used to estimate dermal exposure of the hands among oncology nurses in non-academic hospitals in the Netherlands. Monte Carlo simulation was used to integrate information from available (exposure) studies and generate exposure distributions for the total population of oncology nurses in both pre- and post-intervention situation. Graphs and descriptive statistics of the simulated exposure distributions were used to evaluate trends in population exposure. Results: The inventory showed that important intervention occurred in the preparation and administering of antineoplastic agents and in the handling of urine. Hardly any changes were identified in de nursing tasks. The use of gloves seemed to have decreased for a number of tasks. The results of the analysis show that the interventions did not affect the median exposure. However frequencies of occurrence of individuals with very high and very low total dermal exposures decreased substantially in the post-intervention situation. Analysis of the effect of pregnancy showed that pregnancy is very unlikely to influence exposure or any of the key input variables. Conclusions: The present study shows that the probabilistic approach adds valuable information to deterministic exposure assessment, especially when extrapolating data on a subpopulation to populations of individuals at large. The results show that the identified changes in the past decade in Dutch non-academic hospitals resulted in changes in the exposure distribution of antineoplastic agents among oncology nurses.

Application of a dynamic population-based model for evaluation of exposure reduction strategies in the baking industry

Recently a dynamic population model was developed that simulates a population of bakery workers longitudinally through time and tracks the development of work-related sensitisation and respiratory symptoms in each worker. Input for this model comes from cross-sectional and longitudinal epidemiological studies which allowed estimation of exposure response relationships and disease transition probabilities This model allows us to study the development of diseases and transitions between disease states over time in relation to determinants of disease including flour dust and/or allergen exposure. Furthermore it enables more realistic modelling of the health impact of different intervention strategies at the workplace (e.g. changes in exposure may take several years to impact on ill-health and often occur as a gradual trend). A large dataset of individual full-shift exposure measurements and real-time exposure measurements were used to obtain detailed insight into the effectiveness of control measures and other determinants of exposure. Given this information a population wide reduction of the median exposure with 50% was evaluated in this paper.