Decision trees for evaluating skin and respiratory sensitizing potential of chemicals in accordance with European regulations.

Guidance for determining the sensitizing potential of chemicals is available in EC Regulation No. 1272/2008 Classification, Labeling, and Packaging of Substances; REACH guidance from the European Chemicals Agency; and the United Nations Globally Harmonized System (GHS). We created decision trees for evaluating potential skin and respiratory sensitizers. Our approach (1) brings all the regulatory information into one brief document, providing a step-by-step method to evaluate evidence that individual chemicals or mixtures have sensitizing potential; (2) provides an efficient, uniform approach that promotes consistency when evaluations are done by different reviewers; (3) provides a standard way to convey the rationale and information used to classify chemicals. We applied this approach to more than 50 chemicals distributed among 11 evaluators with varying expertise. Evaluators found the decision trees easy to use and recipients (product stewards) of the analyses found that the resulting documentation was consistent across users and met their regulatory needs. Our approach allows for transparency, process management (e.g., documentation, change management, version control), as well as consistency in chemical hazard assessment for REACH, EC Regulation No. 1272/2008 Classification, Labeling, and Packaging of Substances and the GHS.

Drinking water contribution to aggregate perchlorate intake of reproductive-age women in the United States estimated by dietary intake simulation and analysis of urinary excretion data.

Estimates of perchlorate intake by the US population can be derived from either urinary excretion data or through simulation of dietary intake. Estimates from surveys of urinary excretion (NHANES) are subject to substantial uncertainty owing to the small numbers of subjects for which data are currently available. In addition, current excretion estimates are derived from "spot" urine samples and include a component of short-term (intra-day) variability that may give biased estimates of the variability in average daily intakes. Previous dietary estimates have generally not included any contribution from drinking water, owing to a lack of data related to perchlorate concentrations in water supplies. In this paper, we derive simulation (Monte Carlo) estimates of dietary perchlorate intake distributions for reproductive-age women, which include explicit contributions from drinking water, and compare them to estimates based on urinary excretion. Perchlorate concentrations in water were estimated based on measurements from the US Environmental Protection Agency's UCMR1 database, and from other regional studies of perchlorate contamination. We find that including the drinking water contributions in the dietary simulations yields increases in the population's geometric mean perchlorate intake of 3-8 percent, with a conservative maximum of about 24 percent, compared to intakes estimated based on food intake alone. The intake distributions estimated from dietary and water consumption were found to be very similar to estimates based on creatinine-adjusted perchlorate excretion data from the NHANES, except for having lower population variability. When the dietary simulation data were adjusted to include a contribution from short-term variability similar to that in the "spot" urine samples, the variability in the NHANES and diet-derived estimates were found to be very similar. Our analyses indicate that a reasonable upper-bound estimate for the 95th percentile perchlorate intake among women of reproductive age in the US is on the order of 1.5 x 10(-4) mg/kg/day.

Modeling framework for human exposure assessment.

We are at the dawn of a new era of quantitative consumer exposure and risk assessment of chemicals driven by regulatory mandates. This remarkable development also signals the beginning of a dramatic resurgence in the need for and development of human exposure models. This paper presents some of the philosophical background underlying exposure modeling in the context of human health risk assessment. The basic types of and structure of inhalation exposure models are discussed, as well as the research needed to move us forward into this exciting new period of development.

Tracking health and the environment: a pilot test of environmental public health indicators.

Examining the relationship between health outcomes and environmental exposures requires summary measures, or indicators. To advance the use of indicators, the Johns Hopkins Center for Excellence in Environmental Public Health Tracking piloted three pairs of indicators: 1) air toxics and leukemia in New Jersey, 2) mercury emissions and fish advisories in the United States, and 3) urban sprawl and obesity in New Jersey. These analyses illustrate the feasibility of creating environmental hazard, exposure, and health outcome indicators, examining their temporal and geographic trends, and identifying their temporal and geographic relationships. They also show the importance of including appropriate caveats with the findings. The authors' investigations demonstrate how existing environmental health data can be used to create meaningful indicator measures to further the understanding of environment-related diseases and to help prioritize and guide interventions. Indicators are the foundation of environmental public health tracking, and increased use and development of them are necessary for the establishment of a nationwide tracking network capable of linking environmental exposures and health outcomes.