No abstract

A urine contaminant concentration per se has uncertain meaning for human health because of dilution by hydration. However, the estimation of the health-related daily intake dose of pollutant (mg/kg/day) that equilibrates with a spot urinary concentration of a pesticide residue or metabolite, or other analyte, can be made using creatinine-corrected toxicant levels (mg analyte/mg creatinine) multiplied by an estimate of the subjects' expected creatinine excretion rates (mg creatinine/kg/day). The objective was to develop a set of equations predicting a person's expected daily creatinine excretion (mg/kg) as a function of age, gender, race and morphometry, from birth to old age. We review the creatinine excretion literature where infants, children and adults provided 24 h total urine samples for creatinine analysis. Equations are developed for infants (r3 years), children (3-18 years) and adults (Z18 years) that match at 3 and 18 years. A series of equations that estimate daily creatinine excretion (mg/day) are developed that are piecewise continuous from birth through infancy through adolescence and through adulthood for males and females, and Black and White races. Complicating factors such as diet, health status and obesity are discussed. We propose that these equations, with caveat, can now be used with measured urine concentrations to consistently estimate the corresponding equilibrium intake doses of toxicants at ages from birth to 92 years for the healthy non-obese. We recommend that this system of equations be considered for future development and reporting of applied doses in mg/kg/day of pollutants and toxicants that are measured in urine samples, as in the National Health and Nutrition Examination Survey.

This paper discusses the legal and scientific reasons for separating personal exposure to PM into ambient and nonambient components. It then demonstrates by several examples how well-established models and data typically obtained in exposure field studies can be used to estimate both individual and community average exposure to ambient-generated PM (ambient PM outdoors plus ambient PM that has infiltrated indoors), indoor-gener- IMPLICATIONSExposure analysts historically have sought to determine the total personal exposure to PM of all types in all environments. The lack of correlation between this parameter and ambient PM concentration has been considered an impediment to epidemiologic studies seeking to find an association between ambient PM concentrations and health outcomes. For community, time-series epidemiology, it is necessary only that the community average personal exposure to ambient-generated PM be correlated with the ambient PM concentration. If everyone spent the same amount of time outside and in each microenvironment each day, and the air exchange rate and any forced-air ventilation that resulted in particle removal was a constant, and PM concentrations were uniform across the community, a high correlation would be expected between the PM concentration measured by a community-based PM monitor and the personal exposure of each individual to ambient-generated PM. Also, a high correlation would be expected between ambient concentration and the exposure surrogate of interest in epidemiology, the community average personal exposure to ambient-generated PM. For short-term panel studies, time-series should be determined for all classes of PM. For cohort studies of long-term effects, consideration must be given to the influence of possible variations in exposures to nonambient-generated PM because of differences among cities in time-location patterns (fractions of time spent outdoors), average air exchange rates, and average concentrations of indoor-generated and personal activity PM.

Kitchen-area 22-h gravimetric PM2.5 and passive diffusion stain-tube carbon monoxide (CO) concentrations were measured in homes with open fire and improved wood cookstoves in two studies. In the first study (Guat-2), which also studied homes with gas cookstoves, three samples were collected per stove condition from each of three test houses. In the second study (Guat-3), one sample was collected per house from 15 open fire and 25 improved-stove houses. CO personal samples were also taken for mother and child in both studies. Spearman correlation coefficients (R) between kitchen-area CO and PM2.5 levels in homes using open fires or impoved wood cookstoves were high ranging from 0.92 (Guat-2) to 0.94 (Guat-3), as were those between the personal samples for mother and child ranging from 0.85 (Guat-3) to 0.96 (Guat-2). In general, the correlations were lower for less-polluted conditions. The study found that CO is a good proxy for PM2.5 in homes using open fires or planchas (improved wood cookstove with chimney) but not under gas stove use conditions. It also determined that mother personal CO is a good proxy for child's (under 2 years of age) personal CO and that area CO measurements are not strongly representative of personal CO measurements. These results generally support the use of Draeger CO passive diffusion tubes as a proxy for PM2.5 in such cases where a single type of emission source is the predominant source for CO and PM2.5.

We developed a quantitative method to estimate long-term chemical-specific pesticide exposures in a large prospective cohort study of more than 58000 pesticide applicators in North Carolina and Iowa. An enrollment questionnaire was administered to applicators to collect basic time- and intensity-related information on pesticide exposure such as mixing condition, duration and frequency of application, application methods and personal protective equipment used. In addition, a detailed take-home questionnaire was administered to collect further intensity-related exposure information such as maintenance or repair of mixing and application equipment, work practices and personal hygiene. More than 40% of the enrolled applicators responded to this detailed take-home questionnaire. Two algorithms were developed to identify applicators' exposure scenarios using information from the enrollment and take-home questionnaires separately in the calculation of subject-specific intensity of exposure score to individual pesticides. The 'general algorithm' used four basic variables (i.e. mixing status, application method, equipment repair status and personal protective equipment use) from the enrollment questionnaire and measurement data from the published pesticide exposure literature to calculate estimated intensity of exposure to individual pesticides for each applicator. The 'detailed' algorithm was based on variables in the general algorithm plus additional exposure information from the take-home questionnaire, including types of mixing system used (i.e. enclosed or open), having a tractor with enclosed cab and/or charcoal filter, frequency of washing equipment after application, frequency of replacing old gloves, personal hygiene and changing clothes after a spill. Weighting factors applied in both algorithms were estimated using measurement data from the published pesticide exposure literature and professional judgment. For each study subject, chemical-specific lifetime cumulative pesticide exposure levels were derived by combining intensity of pesticide exposure as calculated by the two algorithms independently and duration/frequency of pesticide use from the questionnaire. Distributions of duration, intensity and cumulative exposure levels of 2,4-D and chlorpyrifos are presented by state, gender, age group and applicator type (i.e. farmer or commercial applicator) for the entire enrollment cohort and for the sub-cohort of applicators who responded to the take-home questionnaire. The distribution patterns of all basic exposure indices (i.e. intensity, duration and cumulative exposure to 2,4-D and chlorpyrifos) by state, gender, age and applicator type were almost identical in two study populations, indicating that the take-home questionnaire sub-cohort of applicators is representative of the entire cohort in terms of exposure.

No abstract

The Third National Health and Nutrition Examination Survey (NHANES-III) of the Centers for Disease Control and Prevention (CDC) recorded data on the urinary concentrations of 12 chemicals (analytes), which were either pesticides or their metabolites, that represent exposure to certain pesticides, in urine samples collected from 1988 to 1994 from a cohort of 978 volunteer subjects, aged 20-59 years. We have used each subject's urinary creatinine concentration and their individual daily creatinine excretion rate (g/day) computed from their age, gender, height and weight, to estimate their daily excretion rate in mg analyte/kg/day. We discuss the mechanisms of excretion of the analytes and certain assumptions needed to compute the equivalent daily dietary intake (mg/kg/day) of the most likely parent pesticide compounds for each excreted analyte. We used literature data on the average amount of parent compound ingested per unit amount of the analyte excreted in the urine, and compared these estimated daily intakes to the US EPA's reference dose (RfD) values for each of those parent pesticides. A Johnson S B distribution (four-parameter lognormal) was fit to these data to estimate the national distribution of exclusive exposures to these 12 parent compounds. Only three such pesticides had a few predicted values above their RfD (lindane 1.6%; 2,4-dichlorophenol 1.3%; chlorpyrifos 0.02%). Given the possibility of a subject's dietary intake of a pesticide's metabolites incorporated into treated food, our results show that few, if any, individuals in the general US population aged 20-59 years and not employed in pesticide application were likely to have exceeded the USEPA RfD for these parent compounds during the years studied.

This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless "attenuation factor" between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM10 measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities. Using a fixed 24-hr attenuation factor as a first approximation derived from regression analysis for the respondents, the distributions of nonambient PM10 personal exposures were obtained for each city. Although the mean ambient PM10 concentrations in the three cities varied from 27.9 micrograms/m3 in Toronto to 60.9 micrograms/m3 in Phillipsburg to 94.1 micrograms/m3 in Riverside, the mean nonambient components of personal exposures were found to be closer: 52.6 micrograms/m3 in Toronto; 52.4 micrograms/m3 in Phillipsburg; and 59.2 micrograms/m3 in Riverside. The three frequency distributions of the nonambient components of exposure also were similar in shape, giving support to the hypothesis that nonambient concentrations are similar across different cities and populations. These results indicate that, if the ambient concentrations were completely controlled and set to zero in all three cities, the median of the remaining personal exposures to PM10 would range from 32.0 micrograms/m3 (Toronto) to 34.4 micrograms/m3 (Phillipsburg) to 48.8 micrograms/m3 (Riverside). The highest-exposed 30% of the population in the three cities would still be exposed to 24-hr average PM10 concentrations of 47-74 micrograms/m3; the highest 20% would be exposed to concentrations of 56-92 micrograms/m3; the highest 10% to concentrations of 88-131 micrograms/m3; and the highest 5% to 133-175 micrograms/m3, due only to indoor sources and activities. The distribution for the difference between personal exposures and indoor concentrations, or the "personal cloud," also was similar in the three cities, with a mean of 30-35 micrograms/m3, suggesting that the personal cloud accounts for more than half of the nonambient component of PM10 personal exposure in the three cities. Using ...