Modeled estimates of chlorpyrifos exposure and dose for the Minnesota and Arizona NHEXAS populations.

This paper presents a probabilistic, multimedia, multipathway exposure model and assessment for chlorpyrifos developed as part of the National Human Exposure Assessment Survey (NHEXAS). The model was constructed using available information prior to completion of the NHEXAS study. It simulates the distribution of daily aggregate and pathway-specific chlorpyrifos absorbed dose in the general population of the State of Arizona (AZ) and in children aged 3-12 years residing in Minneapolis-St. Paul, Minnesota (MSP). Pathways included were inhalation of indoor and outdoor air, dietary ingestion, non-dietary ingestion of dust and soil, and dermal contact with dust and soil. Probability distributions for model input parameters were derived from the available literature, and input values were chosen to represent chlorpyrifos concentrations and demographics in AZ and MSP to the extent possible. When the NHEXAS AZ and MSP data become available, they can be compared to the distributions derived in this and other prototype modeling assessments to test the adequacy of this pre-NHEXAS model assessment. Although pathway-specific absorbed dose estimates differed between AZ and MSP due to differences in model inputs between simulated adults and children, the aggregate model results and general findings for simulated AZ and MSP populations were similar. The major route of chlorpyrifos intake was food ingestion, followed by indoor air inhalation. Two-stage Monte Carlo simulation was used to derive estimates of both inter-individual variability and uncertainty in the estimated distributions. The variability in the model results reflects the difference in activity patterns, exposure factors, and concentrations contacted by individuals during their daily activities. Based on the coefficient of variation, indoor air inhalation and dust ingestion were most variable relative to the mean, primarily because of variability in concentrations due to use or no-use of pesticides. Uncertainty analyses indicated a factor of 10-30 for uncertainty of model predictions of 10th, 50th, and 90th percentiles. The greatest source of uncertainty in the model stems from the definition of no household pesticide use as no use in the past year. Because chlorpyrifos persists in the residential environment for longer than a year, the modeled estimates are likely to be low. More information on pesticide usage and environmental concentrations measured at different post-application times is needed to refine and evaluate this and other pesticide exposure models.

A longitudinal investigation of solid-food based dietary exposure to selected elements.

As part of a longitudinal investigation of environmental exposures to selected chemical contaminants, the National Human Exposure Assessment Survey (NHEXAS), food consumption and duplicate diet samples were obtained in each of six sampling cycles from up to 80 individuals in Maryland during 1995-1996. Duplicate diet samples were weighed and analyzed for arsenic, cadmium, chromium and lead and were used to derive average daily intakes of each element. Mean log-transformed concentrations of arsenic and cadmium in duplicate diet samples and derived intakes of chromium were found to vary significantly among sampling cycles. Repeated observations of dietary exposure metrics from the same individual over time were highly variable. The results suggest that distributions of dietary exposure to arsenic and cadmium do vary for a population within a 1-year period, while those for chromium and lead do not. This may result in single measurements of exposure being sufficient to characterize population variability for these latter two elements. However, even for those elements not displaying statistically significant temporal variability for the population, a single dietary exposure measurement may still not be sufficient to characterize accurately chronic dietary exposure levels for individuals.

A longitudinal investigation of selected pesticide metabolites in urine.

As part of a longitudinal investigation of environmental exposures to selected chemical contaminants, concentrations of the pesticide metabolites 1-naphthol (INAP), 3,5,6-trichloro-2-pyridinol (TCPY), malathion dicarboxylic acid (MDA), and atrazine mercapturate (AM) were measured in repeated samples obtained from 80 individuals in Maryland during 1995-1996. Up to six urine samples were collected from each individual at intervals of approximately 8 weeks over a 1-year period (i.e., one sample per participant in each of six cycles). INAP (median=4.2 microg/l and 3.3 microg/g creatinine) and TCPY (median=5.3 microg/l and 4.6. microg/g creatinine) were present in over 80% of the samples, while MDA and AM were detected infrequently (6.6% and <1% of samples, respectively). Geometric mean (GM) concentrations of INAP in urine did not vary significantly among sampling cycles. In contrast, GM concentrations of TCPY were significantly greater in samples collected during the spring and summer of 1996 than in the preceding fall and winter. Repeated measurements of INAP and TCPY from the same individual over time were highly variable. The average range of INAP and TCPY concentrations from the same individual were approximately 200% and 50% greater than the respective population mean levels. Geometric mean (GM) TCPY concentrations differed significantly between Caucasian (n=42, GM=5.7 microg/g creatinine) and African-American (n=11, GM=4.0 microg/g) participants and among education levels, but were not significantly different among groups classified by gender, age, or household income. In future research, environmental measurements of the parent compounds and questionnaire data collected concurrently with the biomarker data will be used to characterize the determinants of variability in the urinary pesticide metabolite levels.

Temporal variability of microenvironmental time budgets in Maryland.

Information on human time-activity patterns is often required to interpret environmental exposure data fully and to implement exposure assessment models. Data on short-term time-activity patterns for individuals, such as 1-day measurements, are relatively abundant. The reliability of such data for use in chronic exposure (e.g., 1 or more years) assessments performed for evaluation of health risks is not well understood. As part of the NHEXAS-Maryland investigation, daily time budget data for seven microenvironments were collected from 80 people during as many as six 1-week Cycles over a 12-month period. The data were summarized and analyzed statistically by sampling Cycle, day of week, and individual to characterize long-term average microenvironmental time budgets and to identify their determinants. Median times spent in transit, indoors at home, outside at home, indoors at work or school, outdoors at work or school, indoors at other locations, and outdoors at other locations were found to vary significantly, although not substantively in many cases, by time of year (i.e., Cycle), by day of week, and by individuals. Time budgets for most of the microenvironments also exhibited significant variability by gender, age group, education level, annual household income, and work status. The results indicate that short-term (e.g., 1-day) measures of microenvironmental time budgets for individuals are unlikely to be representative of their long-term patterns. Thus, health risk or epidemiological assessments performed for a population mean or specific quantile may be relatively insensitive to when time budget data were collected. However, the accuracy of such assessments performed for individuals is likely to be greatly improved by collection of time budget data from numerous points in time.

Estimating long-term exposures from short-term measurements.

Many health problems are related to chronic exposure of individuals to pollutants in the environment. The level of exposure of a specified population is typically represented by the mean level of exposure of the population, the variation in exposure between individuals within the population, and levels of exposure for selected percentiles of the population, such as the 50th and 98th percentiles. However, the day-to-day level of exposure for individuals varies, and direct measurement of total exposure for long periods of time is impractical. The problem is to estimate the quantities listed above using incomplete sampling of the time period of interest. This paper looks at the effect of using estimates of long-term exposure for individuals on estimating the exposure distribution of the population. A simple and apparently robust estimate for the upper percentiles of the exposure distribution is proposed. Problems related to estimating an individual's long-term exposure, including sample size, are also discussed. The length of time defined as long-term in this paper is one year; however, the results are generalizable to any period of time desired.