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Exposure Intensity Revisited

Mage, David

doi: 10.1097/01.ede.0000221661.75598.59
Letters to the Editor: Letters
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To the Editor:

Acquavella et al1 evaluated an exposure-intensity algorithm I coauthored.2 The algorithm’s purpose was to predict the relative intensity of pesticide exposures in relation to possible health effects for which the best measure of exposure intensity is the resulting systemic dosage of pesticide in micrograms per kilogram per day, the units of EPA’s reference dosage (RfD).3,4 The authors1 recognized that actual absorbed doses of pesticides “are not subject to variation due to the hydration [fluid intake] status of study subjects” and actually used them previously.5 Yet, they chose here to ignore this observation and instead used urine concentrations in parts per billion, claiming that “with a few exceptions, the results [not presented] were similar.”

A more correct procedure, as originally intended, is to collect total urine in the immediately preceding 24 hours with last void just before the first handling–mixing–loading on the application day. The biologic half-life of the measured pesticide analyte then can be used to estimate the biologic-residual amount that would be excreted over the next 96 hours with zero additional exposure. In the 24 hours spanning the entire application activities, and in 3 following 24-hour periods, all voids are collected. The 96-hour pesticide mass collected can then be corrected by subtraction of the estimated zero-exposure residual mass. If the farmer made another application before 96 hours had passed, the urine collection would be truncated with the last void taken purposefully immediately before that application, and the missing end mass would be estimated.

However, Acquavella and colleagues1 analyzed only the 24-hour urine concentrations of the application day for glyphosate and the next day for 2,4-D and chlorpyrifos. Even if all farmers had a single identical bolus exposure at t = 0, they would all have variable amounts excreted in the next 2 24-hour periods.6 Given that the farmers were all exposed at unknown times ranging from first handling to last clean up, the different exposure patterns would lead to an even greater variable fraction of their total exposure excreted in these 2 fixed 24-hour periods. This would not be such a problem if the total corrected mass, collected in the last 96 hours, was used for analysis.

In conclusion, the authors could have provided a more meaningful evaluation of our exposure-intensity algorithm if they had removed these sources of variance by correcting the total analyte mass collected for residual exposure and divided by the applicator’s body mass.

David Mage

Philadelphia, PA

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1. Acquavella JF, Alexander BH, Mandel JS, et al. Exposure misclassification in studies of agricultural pesticides: insights from biomonitoring. Epidemiology. 2006;17:69–74.
2. Dosemeci M, Alavanja MC, Rowland AS, et al. A quantitative approach for estimating exposure to pesticides in the Agricultural Health Study. Ann Occup Hyg. 2002;46:245–260.
3. Zhao Q, Dourson M, Gadagbui B. A review of the reference dose for chlorpyrifos. Regul Toxicol Pharmacol. 2005; Dec 13 [Epub ahead of print].
4. Mage DT, Allen RH, Gondy G, et al. Estimating pesticide dose from urinary pesticide concentration data by creatinine correction in the Third National Health and Nutrition Examination Survey (NHANES-III). J Expo Anal Environ Epidemiol. 2004;14:457–465.
5. Acquavella JF, Alexander BH, Mandel JS, et al. Glyphosate biomonitoring for farmers and their families: results from the Farm Family Exposure Study. Environ Health Perspect. 2004;112:321–326.
6. Nolan RJ, Rick DL, Freshour NL, et al. Chlorpyrifos: pharmacokinetics in human volunteers. Toxicol Appl Pharmacol. 1984;73:8–15.
© 2006 Lippincott Williams & Wilkins, Inc.