New approaches to uncertainty analysis for use in aggregate and cumulative risk assessment of pesticides

Risk assessments for human exposures to plant protection products (PPPs) have traditionally focussed on single routes of exposure and single compounds. Extensions to estimate aggregate (multi-source) and cumulative (multi-compound) exposure from PPPs present many new challenges and additional uncertainties that should be addressed as part of risk analysis and decision-making. A general approach is outlined for identifying and classifying the relevant uncertainties and variabilities. The implementation of uncertainty analysis within the MCRA software, developed as part of the EU-funded ACROPOLIS project to address some of these uncertainties, is demonstrated. An example is presented for dietary and non-dietary exposures to the triazole class of compounds. This demonstrates the chaining of models, linking variability and uncertainty generated from an external model for bystander exposure with variability and uncertainty in MCRA dietary exposure assessments. A new method is also presented for combining pesticide usage survey information with limited residue monitoring data, to address non-detect uncertainty. The results show that incorporating usage information reduces uncertainty in parameters of the residue distribution but that in this case quantifying uncertainty is not a priority, at least for UK grown crops. A general discussion of alternative approaches to treat uncertainty, either quantitatively or qualitatively, is included

New approaches to uncertainty analysis for use in aggregate and cumulative risk assessment of pesticides

Risk assessments for human exposures to plant protection products (PPPs) have traditionally focussed on single routes of exposure and single compounds. Extensions to estimate aggregate (multi-source) and cumulative (multi-compound) exposure from PPPs present many new challenges and additional uncertainties that should be addressed as part of risk analysis and decision-making. A general approach is outlined for identifying and classifying the relevant uncertainties and variabilities. The implementation of uncertainty analysis within the MCRA software, developed as part of the EU-funded ACROPOLIS project to address some of these uncertainties, is demonstrated. An example is presented for dietary and non-dietary exposures to the triazole class of compounds. This demonstrates the chaining of models, linking variability and uncertainty generated from an external model for bystander exposure with variability and uncertainty in MCRA dietary exposure assessments. A new method is also presented for combining pesticide usage survey information with limited residue monitoring data, to address non-detect uncertainty. The results show that incorporating usage information reduces uncertainty in parameters of the residue distribution but that in this case quantifying uncertainty is not a priority, at least for UK grown crops. A general discussion of alternative approaches to treat uncertainty, either quantitatively or qualitatively, is included

A European model and case studies for aggregate exposure assessment of pesticides

Exposures to plant protection products (PPPs) are assessed using risk analysis methods to protect public health. Traditionally, single sources, such as food or individual occupational sources, have been addressed. In reality, individuals can be exposed simultaneously to multiple sources. Improved regulation therefore requires the development of new tools for estimating the population distribution of exposures aggregated within an individual. A new aggregate model is described, which allows individual users to include as much, or as little, information as is available or relevant for their particular scenario. Depending on the inputs provided by the user, the outputs can range from simple deterministic values through to probabilistic analyses including characterisations of variability and uncertainty. Exposures can be calculated for multiple compounds, routes and sources of exposure. The aggregate model links to the cumulative dietary exposure model developed in parallel and is implemented in the web-based software tool MCRA. Case studies are presented to illustrate the potential of this model, with inputs drawn from existing European data sources and models. These cover exposures to UK arable spray operators, Italian vineyard spray operators, Netherlands users of a consumer spray and UK bystanders/residents. The model could also be adapted to handle non-PPP compounds

Effects of decision aids for menorrhagia on treatment choices, health outcomes, and costs: a randomized controlled trial

CONTEXT Decision aids can increase patient involvement in treatment decision making. However, questions remain regarding their effects and cost implications. OBJECTIVE To evaluate the effects of information, with and without a structured preference elicitation interview, on treatment choices, health outcomes, and costs. DESIGN, SETTING AND PARTICIPANTS A randomized controlled trial with 2 years of follow-up. Between October 1996 and February 1998, 894 women with uncomplicated menorrhagia were recruited from 6 hospitals in southwest England. Women were randomized to the control group, information alone group (information), or information plus interview group (interview). INTERVENTIONS Women in both intervention groups were sent an information pack (a booklet and complementary videotape) 6 weeks before their specialist consultation. Immediately before their consultation, women in the interview group underwent structured interview, to clarify and elicit their preferences. MAIN OUTCOME MEASURES Self-reported health status was the main outcome; secondary outcomes included treatments received and costs. Cost analyses adopted a UK health service (payer) perspective, and were based on patient-reported resource use data and are reported in 1999-2000 US dollars. RESULTS The interventions had no consistent effect on health status. Hysterectomy rates were lower for women in the interview group (38%) (adjusted odds ratio [OR], 0.60; 95% confidence interval [CI], 0.38-0.96) than in the control group (48%) and women who received the information alone (48%) (adjusted OR, 0.52; 95% CI, 0.33-0.82). The interview group had lower mean costs ($1566) than the control group ($2751) (mean difference, $1184; 95$684-$2110) and the information group$2026 (mean difference, $461; 95$236-$696). CONCLUSIONS Neither intervention had an effect on health status. Providing women with information alone did not affect treatment choices; however, the addition of an interview to clarify values and elicit preferences had a significant effect on women's management and resulted in reduced costs