Concentrations of dialkyl phosphate metabolites of organophosphorus pesticides in the U.S. population.We report population-based concentrations, stratified by age, sex, and racial/ethnic groups, of dialkyl phosphate (DAP (Directory Access Protocol) A protocol used to gain access to an X.500 directory listing. See LDAP.) metabolites of multiple organophosphorus pesticides. We measured dimethylphosphate (DMP), dimethylthiophosphate (DMTP), dimethyldithiophosphate (DMDTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP) concentrations in 1,949 urine samples collected in U.S. residents 6-59 years of age during 1999 and 2000 as a part of the ongoing National Health and Nutrition Examination Survey (NHANES). We detected each DAP metabolite in more than 50% of the samples, with DEP being detected most frequently (71%) at a limit of detection of 0.2 [micro]g/L. The geometric means for the metabolites detected in more than 60% of the samples were 1.85 [micro]g/L for DMTP and 1.04 [micro]g/L for DEP. The 95th percentiles for each metabolite were DMP, 13 [micro]g/L; DMTP, 46 [micro]g/L; DMDTP, 19 [micro]g/L; DEP, 13 [micro]g/L; DETP, 2.2 [micro]g/L; and DEDTP, 0.87 [micro]g/L. We determined the molar sums of the dimethyl-containing and diethyl-containing metabolites; their geometric mean concentrations were 49.4 and 10.5 nmol/L, respectively, and their 95th percentiles were 583 and 108 nmol/L, respectively. These data are also presented as creatinine creatinine /cre·at·i·nine/ (kre-at´i-nin) an anhydride of creatine, the end product of phosphocreatine metabolism; measurements of its rate of urinary excretion are used as diagnostic indicators of kidney function and muscle mass. cre·at·i·nine (kr-adjusted concentrations. Multivariate analyses showed concentrations of DAPs in children 6-11 years of age that were consistently significantly higher than in adults and often higher than in adolescents. Although the concentrations between sexes and among racial/ethnic groups varied, no significant differences were observed. These data will be important in evaluating the impact of organophosphorus pesticide exposure in the U.S. population and the effectiveness of regulatory actions. Key words: biologic monitoring, dialkyl phosphate, general population, organophosphate, organophosphorus, reference range, urine. Environ Health Perspect 112:186-200 (2004). doi:10.1289/ehp.6503 available via http://dx.doi.org/[Online 4 November 2003] ********** Organophosphorus (OP) pesticides are among the most widely used pesticides in the United States and are used in both agricultural and residential settings. Approximately 40 OP pesticides are registered with the U.S. Environmental Protection Agency (U.S. EPA) for use in the United States (U.S. EPA 2003). Examples of commonly used OP pesticides are chlorpyrifos (Dursban), diazinon (Dianon), azinphos methyl (Guthion), and oxydemetonmethyl (Metasystox-R). OP pesticides are popular because of their broad spectrum of applications and potent toxicity to insects, their relative inexpensive costs, and their decreased likelihood for pest resistance (Karalliedde et al. 2001). According to U.S. EPA sales data, OP pesticides account for about half of all insecticides used in the United States. About 80 million pounds of OP pesticides are used annually in the United States, with 75% of their use in agriculture (U.S. EPA 1991). Crops on approximately 38 million acres of farmland are treated annually with OP insecticides (U.S. EPA 1991). A smaller percentage of the total OP use has been in residential settings. Whitmore et al. (2003) found that nearly half of U.S. households with a child younger than 5 years of age had a pesticide stored within a child's reach. In outdoor settings in contact with light and water, OP pesticides degrade relatively rapidly. However, when used indoors or as a part of structural treatments, these compounds can remain stable for much longer periods (Fenske et al. 2000) and can remain potentially available for repeated exposure for both adults and children. Most OP pesticides have the same general structure (Figure 1), a common mode of action as an insecticide, and a common mode of acute toxicity in humans and other animals (Mileson et al. 1998). In vivo, these pesticides are potent inhibitors of the enzyme acetyl cholinesterase (AChE), which breaks down the neurotransmitter acetylcholine. More specifically, the hydroxyl group of a serine residue in the active site of AChE chemically reacts with the OP pesticide or its metabolically activated form to chemically bind the enzyme and prevent it from performing its natural function. In most instances, the original enzyme may be regenerated via a simple hydrolysis, similar to its regeneration after breaking down acetylcholine. [FIGURE 1 OMITTED] Most OP pesticides are composed of a phosphate (or phosphorothioate or phosphorodithioate) moiety that, in most cases, is O, O-dialkyl substituted, where the alkyl groups are usually dimethyl or diethyl, and an organic group (Figure 1). For example, diazinon is composed of an O, O-diethyl phosphorothioate to which a 2-isopropyl-4-methyl-6-hydroxypyrimidinyl group is attached. Once entering the body, OPs can be enzymatically converted to their oxon form, which then reacts with available cholinesterase. The oxon also can be enzymatically or spontaneously hydrolyzed to form a dialkyl phosphate (DAP) metabolite and the organic group moiety. In the case of diazinon, diethylphosphate (DEP) and 2-isopropyl-4-methyl-6-hydroxypyrimidine (IMPY) may be formed. If the pesticide is not converted to its oxen form, it can undergo hydrolysis to its organic group metabolite and dialkylthionate metabolites (i.e., dialkylthiophosphate and/or dialkyldithiophosphate). For diazinon, these metabolites are diethylthiophosphate (DETP) and IMPY. These metabolites and/or their glucuronide or sulfate conjugates are excreted in urine. After the National Research Council's 1993 report, which focused on dietary pesticide exposure among infants and children, the advantages of using OP pesticides were scrutinized because of the potential consequences of childhood exposures. Consequently, the passage of the Food Quality Protection Act (FQPA) of 1996 required the U.S. EPA to reassess all pesticide residue tolerances on food and, in this reassessment, to give special consideration to potential cumulative and aggregate exposures to children. OP pesticides were the first class of pesticides for which tolerances were reassessed because of their common mode of toxicity, widespread use, and unknown long-term health effects (U.S. EPA 2003). Because of increasing concern about the safety of these pesticides to children, many OP pesticide uses, such as residential use of chlorpyrifos and diazinon, are being eliminated. Because exposure to OP pesticides occurs typically by multiple routes and the dominant routes of exposure for individuals vary, quantification of OP exposure is not a trivial process. Therefore, in many epidemiologic studies, markers of exposure in biologic samples have been measured to estimate the absorbed dose (Aprea et al. 1996; Curl et al. 2002; Loewenherz et al. 1997; Lu et al. 2001; Mills and Zahm 2001; Whyatt and Barr 2001). One of the most common ways to assess OP pesticide dose is quantifying six common urinary DAP metabolites. These measurements may provide information on class exposure to OP pesticides or exposure to the DAP itself that may be present in the environment as a breakdown product of OP pesticides (environmental DAP). Although no published studies have documented the environmental presence or biologic absorption of environmental DAPs or their contribution to urinary DAP concentrations in humans, researchers widely recognize their potential contributions to urinary levels largely based on data demonstrating similar environmental exposures, absorption, and excretion for more selective OP metabolites (Barr et al. 2002; Curl et al. 2003a; Krieger et al. 2003; Wilson et al. 2003). In addition, the potential health effects resulting from exposure to environmental DAPs have not been evaluated. Although the DAP measurements provide no specific information about the pesticide to which one was exposed and they may potentially represent exposure to the pesticide itself and/or its environmental degradate, urinary DAP metabolites still provide useful information about cumulative exposure to OP pesticides as a class because about 75% of the U.S. EPA-registered OP pesticides form one to three of these six DAP metabolites. However, these concentrations are often difficult to interpret because reference concentrations are not available. We report DAP metabolite concentrations in urine samples collected in 1999 and 2000 from approximately 2,000 persons 6-59 years of age from the U.S. general population. Specifically, we report urinary concentrations of dimethylphosphate (DMP), DEP, dimethylthiophosphate (DMTP), DETP, dimethyldithiophosphate (DMDTP), and diethyldithiophosphate (DEDTP). The data we report are representative of the civilian, noninstitutionalized U.S. population and are stratified by age, sex, and race/ethnicity. Materials and Methods Study design. The National Health and Nutrition Examination Survey (NHANES), conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC), is designed to measure the health and nutrition status of the civilian noninstitutionalized U.S. population (CDC 2003a). In 1999, NHANES became a continuous survey, fielded on an ongoing basis. Each year of data collection is based on a representative sample covering all ages of the civilian noninstitutionalized population. Data files are released for public use in 2-year groupings (cycles). National population estimates for DAPs as well as estimates for the three largest racial/ethnic subgroups in the U.S. population (non-Hispanic white, non-Hispanic black, and Mexican American) are derived from the first 2-year cycle of the survey, NHANES 1999-2000. The sampling scheme for NHANES is based on a complex multistage area probability design, which includes selection of primary sampling units (counties), household segments within the counties, and finally sample persons from selected households. In 1999 and 2000, persons 12-19 years of age and [greater than or equal to] 60 years of age, non-Hispanic blacks, and Mexican Americans were oversampled. Low-income white Americans were oversampled in 2000. In addition, in 1999 and 2000, most women who indicated that they were pregnant in the screening interview were selected into the sample to increase the sample size for pregnant women. Data were collected through a household interview and a standardized physical examination, which was conducted in a mobile examination center. Urine specimens were collected from each participant [greater than or equal to] 6 years of age during one of three daily scheduled examination periods (i.e., morning, afternoon, and early evening). Sociodemographic information and medical histories of the survey participant and the family were collected during the household interview. NHANES 1999-2000 was conducted in 26 locations throughout the United States and included examinations of 9,282 persons. For the DAP metabolites, measurements were conducted on a subset of participants that were selected based on a random one-half sample of children 6-11 years of age in 1999 and 2000, a random one-quarter sample of people 12-59 years of age in 1999, and a random one-third sample of people 12-59 years of age in 2000. Because the subset was a random selection from the entire set, the representativeness of the survey was maintained. Laboratory methods. During the physical examinations, "spot" or "grab" urine specimens were collected from participants, aliquoted, and stored cold (2-4[degrees]C) or frozen until shipment. Urinary creatinine concentrations were determined using an automated colorimetric method based on a modified Jaffe reaction (Jaffe 1886) on a Beckman Synchron AS/ASTRA clinical analyzer (Beckman Instruments, Inc., Brea, CA) at the Fairview University Medical Center, Minneapolis, Minnesota. Samples collected for OP pesticide measurements were shipped on dry ice to the CDC's National Center for Environmental Health. Urine samples were analyzed for DAP metabolites of OP pesticides using the method of Bravo et al. (2002). Briefly, 4 mL of urine was spiked with an isotopically labeled internal standard mixture and concentrated to dryness using an azeotropic codistillation with acetonitrile acetonitrile /ac·e·to·ni·trile/ (as?e-to-ni´tril) a colorless liquid with an etherlike odor used as an extractant, solvent, and intermediate; ingestion or inhalation yields cyanide as a metabolic product.. The residue was dissolved in acetonitrile, and the DAPs were derivatized to their respective chloropropyl esters using 1-chloro-3-iodopropane and potassium carbonate. The solution containing the chloropropyl esters was concentrated and then analyzed using gas chromatography-positive chemical ionization-tandem mass spectrometry. The DAP metabolites were quantified using isotope-dilution calibration. Metabolite concentrations were adjusted using creatinine concentrations to correct for variable urine dilutions in the "spot" urine samples. Quality control materials were analyzed in parallel with unknown samples. Data were not reported for sample runs in which the quality control materials failed to meet the specifications outlined in the Westgard multirules (Westgard 2002). Both laboratories and methods were certified according to guidelines set forth in the Clinical Laboratory Improvement Amendment (1988). Covariates. Age was reported at the time of the household interview as the age in years at the last birthday. Age categories used in our statistical analyses were 6-11 years, 12-19 years, and 20-59 years. A composite racial/ethnic variable based on self-reported race and ethnicity was created to define three major racial/ethnic groups: non-Hispanic black, non-Hispanic white, and Mexican American. Individuals from other racial/ethnic groups were included in the total estimates reported in this publication; however, no separate demographic breakdown was provided. Traditionally, creatinine concentrations have been used to adjust spot urine samples for variable dilution caused by the different hydration states of the sample donor. Because age group, sex, and race/ethnicity all affect the creatinine concentrations in the urine, creatinine adjustment in diverse populations would not be valid for comparisons of DAP concentrations among the demographic groups. To overcome this limitation and thereby allow for an appropriate comparison of DAP concentrations among the demographic groups, creatinine was also used as a covariate in statistical models. By using this model for DAP concentration comparisons, we appropriately corrected for covariate effects on the creatinine concentrations while eliminating the variability caused by urine dilution of spot samples. Statistical analysis. Survey-specific sample weights tailored to suit the random subset were used in statistical analyses. Parametric statistics were performed only on analytes for which the frequency of detection was greater than or equal to 60%. Geometric means (GMs), least-squares geometric means (LSGMs), and percentiles of urinary DAP concentrations were calculated using SAS software release 8 (SAS Institute, Cary, NC) and SUDAAN software release 7.5.6 (Research Triangle Institute, Research Triangle Park, NC). LSGMs are GMs that have been calculated using an analysis of covariance. The analytic limits of detection (LODs; defined as three times the standard deviation at zero concentration) were 0.58 [micro]g/L for DMP, 0.18 [micro]g/L for DMTP, 0.08 [micro]g/L for DMDTP, 0.2 [micro]g/L for DEP, 0.09 [micro]g/L for DETP, and 0.05 [micro]g/L for DEDTP. For concentrations below the LODs, a value equal to the LOD divided by the square root of 2 was used (Hornung and Reed 1990). For the statistical analyses of summed metabolite concentrations, the individual metabolite concentrations in units of micrograms per liter or micrograms per gram creatinine were converted to their nanomolar units using the general formula (analyte concentration/molecular weight of analyte) x 1,000, giving final concentrations in units of nanomoles per liter or nanomoles per gram creatinine, respectively. SUDAAN incorporates the NHANES sampling weights and adjusts for the complex sample design of the survey. Sample weights take into account nonresponse and the unequal probabilities of selection, resulting from the cluster design and the planned oversampling of certain subgroups. The LSGMs for each demographic group were corrected for effects of all covariates, including creatinine. Differences in LSGMs among demographic groups were considered significant when p < 0.05 and nominally or marginally significant when p > 0.05 but < 0.1. Results Our data included 1,949 valid concentrations for each DAP in urine samples collected during 1999 and 2000. The distribution of the DAP metabolites in the NHANES samples analyzed are presented in Table 1. These values are presented as volume-based concentrations to allow for comparisons with similar data in the literature. The creatinine-adjusted concentrations are shown in Table 2. The volume-based and creatinine-adjusted GMs for each demographic group are shown graphically in Figure 2. DEP was detected with the highest frequency in about 70% of the samples tested; however, DMTP was detected in the highest concentrations. Concentrations of DEP and DETP in individual samples were highly correlated (r = 0.66, p < 0.0001), suggesting they were derived from a common source, such as chlorpyrifos or diazinon. No other DAPs were correlated. [FIGURE 2 OMITTED] The LSGMs for each demographic group are shown in Table 3. For all analytes, children 6-11 years of age had higher concentrations, even after correcting for all covariates including creatinine. Children 6-11 years of age had a significantly higher LSGM concentration of DEP than did adults (p = 0.008) but only marginally significantly higher concentration than did adolescents (p = 0.07). Children had a significantly higher LSGM concentration of DMTP than did adults (p = 0.015), but the difference between values for children and adolescents was not significant. All DAPs were detected more frequently in Mexican Americans and non-Hispanic blacks than in non-Hispanic whites, although the differences were not significant. Mexican Americans had higher concentrations of DEP and DEDTP, whereas non-Hispanic blacks had higher concentrations of DMP and DETP. Mexican Americans and non-Hispanic whites had higher concentrations of DMTP than did non-Hispanic blacks, and all groups had similar concentrations of DMDTP. The maximum concentrations observed for the DAPs were more frequently seen in Mexican Americans. None of the differences observed among the racial/ethnic groups was significant. Because the methyl-containing metabolites are derived from O, O-dimethyl-substituted OP pesticides such as azinphos-methyl and malathion, their concentrations were converted to molar equivalents and summed to produce one composite dimethyl alkylphosphate (DMAP) concentration for each person. A similar conversion and summation was performed for the ethyl-containing metabolites [diethyl alkylphosphate (DEAP) composite]. The distributions of the composite DMAP and DEAP concentrations in the NHANES samples analyzed are presented in Table 4. These values are presented as volume-based molar concentrations to allow for comparisons with similar data in the literature. The creatinine-adjusted concentrations are shown in Table 5. The volume-based and creatinine-adjusted GMs for each demographic group are shown graphically in Figure 3. The LSGMs are given in Table 3. [FIGURE 3 OMITTED] Children 6-11 years of age had significantly higher concentrations of both DMAP and DEAP than did adults (both p < 0.007). Although these concentrations were also higher than for adolescents, the differences were not significant for DMAP (p = 0.26) and only marginally significant for DEAP (p = 0.06). Adolescents had higher concentrations of DMAP than did adults, but the difference was only marginally significant (p = 0.08). The total DAP concentrations in children and adolescents were also significantly greater than in adults (p < 0.0001). Although we report only the DAP concentrations, four "selective" metabolites of OP pesticides were also measured in the same samples. These selective metabolites are derived from the organic portion of the pesticide that is unique to a specific OP pesticide or diethyl/ dimethyl congener pair. The selective metabolites we measured and their parent pesticides are listed in Table 6. Although the distribution data will be reported elsewhere (Barr et al. Unpublished data), we used a Pearson correlation analysis to examine the correlation of the concentrations of these selective pesticides with their corresponding DAP metabolites. The results of our analyses are shown in Table 6. Concentrations of 3,5,6-trichloro-2-pyridinol, a selective metabolite of chlorpyrifos and chlorpyrifos-methyl, were significantly correlated with both DEP (r = 0.22, p < 0.0001) and DETP (r = 0.29, p < 0.0001) concentrations. Likewise, concentrations of IMPY, a selective metabolite of diazinon, were significantly correlated with both DEP (r = 0.27, p < 0.0001) and DETP (r = 0.38, p < 0.0001) concentrations. Other significant, albeit weak, correlations were seen among the other metabolites tested. Similar correlations were observed among the selective metabolites and the composite DEAP and DMAP variables. Discussion We report concentrations of DAPs in the U.S. population using several different formats to allow these data to be more easily compared with existing data in the literature. We found that concentrations of the DAPs among the various demographic subgroups had subtle, nonsignificant differences, except for children 6-11 years of age, who had concentrations consistently significantly higher than in adults and sometimes significantly higher than in adolescents. We have reported these data both as volume-based concentrations and as creatinine-adjusted concentrations, to attempt to correct for the variability in urine dilution among the "spot" samples. However, the demographic covariates we evaluated also may affect the urinary concentrations of creatinine, thus increasing the variability of the data instead of reducing it. For example, a child 6-11 years of age is likely to have a lower concentration of creatinine than would an adult; therefore, a DAP concentration in the child may be overcorrected when adjusting for creatinine, producing a DAP concentration that is falsely elevated compared with that of an adult with a similar exposure and uptake. However, this same adjusted measurement may be more indicative of the size-related dose of the child, assuming that a urinary creatinine concentration could be used as a reasonable surrogate for body weight because it is proportional to lean muscle mass. For these reasons, the creatinine-adjusted results should be evaluated with caution. We have studied the effect of demographic covariates on creatinine in detail; these results will be published separately (Barr et al. Unpublished data). For our statistical analyses to evaluate significant differences in exposures among the subpopulations, we included creatinine as a covariate to correct for the effects of the demographic variables on creatinine. Therefore, the differences we report for children represent real differences in exposure, not false differences produced by creatinine overcorrection. These differences are likely because of increased opportunities for exposure based on their dietary and physical behaviors (Eskenazi et al. 1999; National Research Council 1993). Although urinary DAPs have been measured for almost 30 years to evaluate both occupational and incidental exposures (Table 7), our data are the first population-based reference data reported for the United States. These data were first released in summary format in the CDC's Second National Report on Human Exposure to Environmental Chemicals in January 2003 (CDC 2003b). We observed higher frequencies of detection (Table 8) and higher GMs in 1999, the first year (CDC 2001) of the 2-year NHANES cycle than in the combined 1999-2000 data that we report. Because of the small sample size and the small number of primary sampling units included in any one year of NHANES, there is a high level of variation in annual estimates. We did not formally evaluate the statistical significance of trends in DAP metabolites over this time period, but differences are unlikely to be statistically significant. Data from additional NHANES cycles are required to determine whether exposure levels have declined. These DAPs also were measured in urine samples collected in NHANES II (1976-1980). These data were never released publicly because of laboratory quality control issues that were not resolved (Schober S. Personal communication), but the NHANES II frequency of detection information and mean concentration of the detectable values were reported by Griffith and Duncan (1985). Those data are not directly comparable with the data we report here because the analytical technology used for those analyses was not sufficiently sensitive to detect these metabolites in more than 12% of the samples tested (Murphy et al. 1983). The mean DAP concentrations for the detectable samples in NHANES II ranged from 40 to 110 [micro]g/L, concentrations well in excess of the 95th percentiles for all of the analytes we report, except DMTP. General population DAP data have been reported for European populations in Italy (Aprea et al. 1996, 2000) and Germany (Hardt and Angerer 2000; Heudorf and Angerer 2001; Figure 4). The Italian adult data were derived from a sample size that was only about 6% (n = 124) of the number of samples we report. They reported frequencies of detection ranging from 7% for DEDTP to 99% for DMTP (LODs ~1 [micro]g/L). Our frequencies of detection were much higher for DEDTP (55%; LOD = 0.05 [micro]g/L) and much lower for DMTP (59%; LOD = 0.18 [micro]g/L). Other DAP metabolites were detected much less frequently as well. The GMs of the Italian population ranged from 13.7 (DEDTP) to 70.7 (DMTP) nmol/g creatinine, which are equivalent to 2.5-10 [micro]g/g creatinine. Our GMs ranged from less than the LOD to 2.95 [micro]g/g creatinine in certain demographic subgroups. In addition, one study (Aprea et al. 2000) measured concentrations of DAPs in children 6-7 years of age in a nonagricultural region of Italy. DAP metabolites were detected in 12% (DEDTP) to 96% (DMP) of the samples tested. The GMs ranged from 7.7 (DEDTP) to 117 (DMP) nmol/g creatinine, which are equivalent to 1.4-14.7 [micro]g/g creatinine. DAPs were detected much less frequently in our population of children (59-74%) for all analytes except DMDTP, DETP, and DEDTP. Aprea et al. (2000) found that the DAP concentrations of the children in their study were significantly greater than those of an adult reference population in Italy (Aprea et al. 1996). Our results are consistent with this finding. The German population data were determined on a small population subset (n = 54; Hardt and Angerer 2000). Their frequencies of detection (LODs = 1-5 [micro]g/L) ranged from 2 to 100%, with DMTP being the most frequently detected, and the median concentrations ranged from < 1 [micro]g/L for DETP and DEDTP to 30 [micro]g/L for DMP. Our median concentrations were typically [less than or equal to] 1 [micro]g/L except for DMTP, which ranged from 1.9 to 4.2 [micro]g/L. The German median for DMTP was 22 [micro]g/L. DAPs in urine samples from 1,146 Germans living in former U.S. Air Force housing in Germany were detected with frequency similar to that in our population, except for DMDTP and DEDTP (Heudorf and Angerer 2001). Both the GMs and the distribution percentiles were significantly higher in the German population than in ours for each age group evaluated. For example, the 95th percentile DMTP concentrations for the German population ranged from 51 to 334 [micro]g/g creatinine for the various age groups, whereas ours ranged from 47 to 66 [micro]g/g creatinine. Other DAP data generated from reference populations in exposure studies, mostly in Washington State (Loewenherz et al. 1997; Lu et al. 2000, 2001), have been reported. Concentrations of DAPs found in reference children from these exposure studies were generally comparable with the DAP concentrations of children in our population-based data, expressed either as individual DAP metabolites or as summed DMAP and DEAP concentrations; however, our data on children were usually slightly lower. The differences among our NHANES DAP data and other reported reference values, including the German and Italian data, may be caused by a variety of factors. First, our data were derived from samples that represent a geographically and culturally diverse population. An equal proportion of males and females were sampled, and the participants represented a wide age range. Although age, race/ethnicity, and sex were considered covariates in our analysis and were appropriately accounted for, geographic diversity was not. The geographic area in which the participants lived certainly would have some impact on the DAP concentrations. Second, our data were derived from a large enough sample population to appropriately characterize background DAP concentrations by minimizing the spikes in data associated with overt pesticide exposures. The reference data to which we have compared the NHANES data were all derived from small, likely more homogeneous, populations. Third, the analytic methodology should be considered when comparing the results. Our data were generated using analytic methodology that is highly selective, allowing us to minimize the "false positive" samples, and highly sensitive, allowing us to detect very low levels. In general, other reference data were generated using less selective methodology with LODs that were higher. Given the differences in LODs among methods where general population DAP concentrations were evaluated, we would have expected to detect DAPs more frequently in the U.S. population. However, we observed much lower detection frequencies, which can likely be explained by the factors we mention here. Fourth, the distribution of our data was generated by substituting concentrations less than the LOD with an imputed value equal to the LOD divided by the square root of 2. Other reference data were generated using censored data, zero, or unspecified methods for treatment of data less than the LOD. Finally, the differences could be due to population or subpopulation differences in OP pesticide use or seasonal variations. DAP metabolites have also been measured to assess exposure to OP pesticides in a variety of nonoccupational exposure studies. The concentrations and primary findings from these studies are outlined in Table 7. Most nonoccupational studies took place in Washington State (Curl et al. 2002; Fenske et al. 2000; Loewenherz et al. 1997; Lu et al. 2000, 2001), California (Mills and Zahm 2001), and Arizona (O'Rourke et al. 2000) and report similar findings: Children who lived near farmland or had a parent who was a farmer had higher DAP concentrations than did both reference children in the studies and our population-based reference concentrations for children. Many occupational exposure studies have also been reported. Shafik et al. (1973) found concentrations of DEP and DETP as high as 2,400 and 1,600 [micro]g/L, respectively, in workers formulating O, O-diethyl-substituted OP pesticides, such as phorate. Florida citrus sprayers and harvesters using both O, O-dimethyl-substituted and O, O-diethyl-substituted pesticides had urinary concentrations of DAPs ranging from 6 to 410 [micro]g/L (Griffith and Duncan 1985). Another study on a similar exposure group reported DAP concentrations as high as 3,200 [micro]g/L (Duncan and Griffith 1985). Fenske and Leffingwell (1989) reported DMTP and DMDTP concentrations approaching 700 [micro]g/L in a malathion applicator ap·pli·ca·tor (  p l -k in Washington State. Sprayers and leaf
thinners in Tuscany vineyards in Italy had DMP and DMTP concentrations
as high as 600 and 175 [micro]g/L, respectively (Aprea et al. 1997).
These studies all report concentrations well in excess of the reference
concentrations we have established. However, some of the concentrations
are similar to the maximum concentrations we observed, especially for
DMTP, indicating some similar high-end exposures in our population.Several incidents of nonfatal OP pesticide poisonings have been reported in which urinary DAP was measured. Davies and Peterson (1997) reported cases in which the concentrations of DEP and DETP were as high as 7,800 and 1,500 [micro]g/L, respectively, for parathion poisoning and 30,000 and 30,000 [micro]g/L, respectively, for chlorpyrifos poisoning. Bradway and Shafik (1977) reported a nonfatal malathion poisoning case in which the DMP, DMTP, and DMDTP urinary concentrations were 50,000, 96,000, and 20,000 [micro]g/L, respectively. We had a maximum concentration for DMTP in our population that was similar to these poisoning cases; health and occupation data for this individual have not yet been evaluated. Conclusions We report the first U.S. population-based reference data for DAP metabolites of OP pesticides; these data are stratified by age, sex, and race/ethnicity. We found that concentrations of the DAPs among the various demographic subgroups had subtle, nonsignificant differences, except for children 6-11 years of age, who had concentrations consistently significantly higher than did adults and sometimes significantly higher than did adolescents. Sex and race/ethnicity did not significantly affect DAP concentrations. Our data indicate that most of the U.S. population have some exposure to OP pesticides; however, the concentrations we report are much lower than those of other reference populations in the literature. These data will serve many purposes in environmental public health primarily to help minimize or prevent any adverse health outcome that may result from exposure to these pesticides. To help accomplish this, these data will have many specific uses. They will be used as reference range values by physicians and public health officials for comparing urinary levels of these metabolites to potentially exposed persons or populations to assess their relative exposure status. They will be used by risk assessors for modeling to estimate the intake (e.g., daily) and compare with regulated doses, such as the U.S. EPA's reference dose and the Food and Drug Administration's acceptable daily intake. These data will be used in many disciplines in environmental public health to track trends in exposure over time and to determine the effectiveness of public health efforts, including legislation such as the FQPA, to reduce exposures for all Americans, but particularly for certain vulnerable or sensitive subgroups, such as children. These data also will help prioritize research gaps and needs for relating human exposures and adverse health outcomes; they will be used for comparing human urinary levels with urinary levels found in dosed animals that have exhibited adverse health outcomes. In summary, these data serve as U.S. landmark data that will be used in many ways, including those mentioned above.
Table 1. Weighted quantiles of urinary DAP concentrations
([micro]g/L) in the NHANES 1999-2000 study population.
Analyte/ Detection
demographic category No. frequency (%) GM
DMP
All (a) 1,949 53 NC
6-11 years of age 471 63 NC
12-19 years of age 664 50 NC
20-59 years of age 814 52 NC
Males 952 53 NC
Females 997 54 NC
Non-Hispanic whites 594 49 NC
Non-Hispanic blacks 509 62 NC
Mexican Americans 672 59 NC
DMTP
All (a) 1,949 64 1.82
(1.43-2.32)
6-11 years of age 471 69 2.72
(1.85-4.01)
12-19 years of age 664 67 2.53
(1.72-3.63)
20-59 years of age 814 63 1.59
(1.25-2.03)
Males 952 66 2.10
(1.58-2.78)
Females 997 62 1.59
(1.2-2.11)
Non-Hispanic whites 594 64 1.77
(1.30-2.39)
Non-Hispanic blacks 509 68 2.13
(1.38-3.28)
Mexican Americans 672 63 1.79
(1.11-2.90)
DMDTP
All (a) 1,949 53 NC
6-11 years of age 471 63 NC
12-19 years of age 664 51 NC
20-59 years of age 814 48 NC
Males 952 53 NC
Females 997 53 NC
Non-Hispanic whites 594 50 NC
Non-Hispanic blacks 509 56 NC
Mexican Americans 672 53 NC
DEP
All (a) 1,949 71 1.03
(0.76-1.40)
6-11 years of age 471 74 1.32
(0.85-2.05)
12-19 years of age 664 73 1.21
(0.85-1.72)
20-59 years of age 814 69 0.955
(0.70-1.30)
Males 952 72 1.11
(0.81-1.54)
Females 997 69 0.954
(0.69-1.32)
Non-Hispanic whites 594 68 0.98
(0.67-1.44)
Non-Hispanic blacks 509 82 1.56
(1.23-1.98)
Mexican Americans 672 74 1.22
(0.87-1.71)
DETP
All (a) 1,949 53 NC
6-11 years of age 471 59 NC
12-19 years of age 664 46 NC
20-59 years of age 814 54 NC
Males 952 57 NC
Females 997 50 NC
Non-Hispanic whites 594 51 NC
Non-Hispanic blacks 509 64 NC
Mexican Americans 672 58 NC
DEDTP
All (a) 1,949 56 NC
6-11 years of age 471 60 NC
12-19 years of age 664 50 NC
20-59 years of age 814 56 NC
Males 952 57 NC
Females 997 54 NC
Non-Hispanic whites 594 53 NC
Non-Hispanic blacks 509 61 NC
Mexican Americans 672 66 NC
Percentile of distribution
Analyte/
demographic category 25th 50th 75th
DMP
All (a) < LOD 0.74 2.80
(< LOD-1.30) (2.10-3.90)
6-11 years of age < LOD 1.00 4.40
(0.59-2.00) (2.90-6.80)
12-19 years of age < LOD 0.65 3.80
(< LOD-1.50) (2.40-5.50)
20-59 years of age < LOD 0.68 2.60
(< LOD-1.20) (1.80-3.60)
Males < LOD 0.65 2.80
(< LOD-1.20) (2.10-4.10)
Females < LOD 0.78 2.80
(< LOD-1.40) (2.00-4.00)
Non-Hispanic whites < LOD < LOD 2.90
(1.80-4.20) (5.50-9.60)
Non-Hispanic blacks < LOD 0.98 3.60
(0.65-1.30) (2.40-5.50)
Mexican Americans < LOD 1.00 3.80
(< LOD-1.60) (2.70-4.70)
DMTP
All (a) < LOD 2.70 10.0
(1.50-3.80) (8.00-16.0)
6-11 years of age < LOD 4.10 20.0
(2.30-7.60) (13.0-30.0)
12-19 years of age < LOD 3.60 16.0
(1.70-6.00) (8.80-24.0)
20-59 years of age < LOD 2.20 9.10
(1.10-3.40) (7.10-13.0)
Males < LOD 3.40 13.0
(2.40-4.50) (8.50-20.0)
Females < LOD 2.00 9.70
(0.72-3.30) (6.70-16.0)
Non-Hispanic whites < LOD 2.60 10.0
(1.10-4.00) (7.00-17.0)
Non-Hispanic blacks < LOD 3.60 11.0
(1.60-5.60) (8.30-18.0)
Mexican Americans < LOD 2.00 10.0
(0.60-4.30) (6.60-16.0)
DMDTP
All (a) < LOD < LOD 2.30
(1.40-3.60)
6-11 years of age < LOD < LOD 4.30
(2.50-6.90)
12-19 years of age < LOD < LOD 2.20
(1.30-4.50)
20-59 years of age < LOD < LOD 2.10
(1.10-3.10)
Males < LOD < LOD 2.30
(1.30-4.30)
Females < LOD < LOD 2.10
(1.30-3.20)
Non-Hispanic whites < LOD < LOD 2.00
(0.850-370)
Non-Hispanic blacks < LOD < LOD 3.20
(1.70-6.50)
Mexican Americans < LOD < LOD 1.80
(1.20-2.30)
DEP
All (a) < LOD 1.20 3.10
(0.80-1.50) (2.40-4.60)
6-11 years of age < LOD 1.40 4.50
(0.99-2.10) (2.30-0.50)
12-19 years of age < LOD 1.30 3.70
(1.00-1.90) (2.40-5.40)
20-59 years of age < LOD 1.00 3.00
(0.73-1.40) (2.10-4.40)
Males < LOD 1.10 3.80
(0.85-1.40) (2.50-4.90)
Females < LOD 1.10 2.90
(0.73-1.50) (2.10-4.40)
Non-Hispanic whites < LOD 1.10 3.30
(0.58-1.50) (2.30-4.90)
Non-Hispanic blacks < LOD 1.60 4.20
(1.30-1.80) (2.90-5.80)
Mexican Americans < LOD 1.10 4.10
(0.84-1.50) (2.60-6.40)
DETP
All (a) < LOD 0.49 0.76
(< LOD-0.62) (0.66-0.91)
6-11 years of age < LOD 0.59 0.90
(< LOD-0.72) (0.73-1.20)
12-19 years of age < LOD 0.21 0.78
(< LOD-0.64) (0.63-1.20)
20-59 years of age < LOD 0.480 0.74
(< LOD-0.59) (0.63-0.91)
Males < LOD 0.50 0.79
(< LOD-0.630) (0.70-1.00)
Females < LOD < LOD 0.72
(0.600-0.910)
Non-Hispanic whites < LOD 0.16 0.73
(< LOD-0.63) (0.60-1.00)
Non-Hispanic blacks < LOD 0.56 0.81
(< LOD-0.670) (0.69-1.20)
Mexican Americans < LOD 0.56 0.84
(< LOD-0.70) (0.74-0.98)
DEDTP
All (a) < LOD 0.08 0.20
(< LOD-0.11) (0.15-0.29)
6-11 years of age < LOD 0.08 0.19
(< LOD-0.11) (0.15-0.24)
12-19 years of age < LOD 0.08 0.26
(< LOD-0.11) (0.12-0.35)
20-59 years of age < LOD 0.08 0.21
(< LOD-0.11) (0.13-0.29)
Males < LOD 0.09 0.22
(< LOD-0.10) (0.16-0.29)
Females < LOD 0.08 0.19
(< LOD-0.10) (0.11-0.30)
Non-Hispanic whites < LOD 0.08 0.19
(< LOD-0.12) (0.12-0.28)
Non-Hispanic blacks < LOD 0.09 0.27
(< LOD-0.11) (0.18-0.33)
Mexican Americans < LOD 0.10 0.31
(0.07-0.15) (0.23-0.39)
Percentile of
distribution
Analyte/
demographic category 90th 95th
DMP
All (a) 7.90 13.0
(5.90-9.50) (9.50-21.0)
6-11 years of age 10.0 21.0
(6.60-18.0) (10.0-41.0)
12-19 years of age 9.90 22.0
(6.10-18.0) (12.0-29.0)
20-59 years of age 6.50 9.70
(5.2-8.8) (8.50-16.0)
Males 7.90 18.0
(5.90-10.0) (9.00-25.0)
Females 7.60 10.0
(5.40-9.50) (8.50-15.0)
Non-Hispanic whites 7.90 10.0
(8.90-21.0)
Non-Hispanic blacks 8.90 21.0
(6.50-15.0) (12.0-24.0)
Mexican Americans 9.50 15.0
(6.80-13.0) (10.0-23.0)
DMTP
All (a) 38.0 46.0
(21.0-38.0) (38.0-60.0)
6-11 years of age 40.0 62.0
(38.0-54.0) (38.0-110)
12-19 years of age 37.0 69.0
(21.0-38.0) (39.0-190)
20-59 years of age 38.0 38.0
(18.0-38.0) (38.0-48.0)
Males 38.0 41.0
(17.0-38.0) (38.0-62.0)
Females 38.0 52.0
(19.0-38.0) (38.0-120)
Non-Hispanic whites 37.0 45.0
(15.0-38.0) (38.0-62.0)
Non-Hispanic blacks 37.0 39.0
(25.0-38.0) (38.0-88.0)
Mexican Americans 38.0 130.0
(26.0-79.0) (41.0-230)
DMDTP
All (a) 12.0 19.0
(5.40-17.0) (17.0-37.0)
6-11 years of age 16.0 32.0
(5.90-18.0) (18.0-38.0)
12-19 years of age 12.0 19.0
(6.20-17.0) (12.0-52.0)
20-59 years of age 10.0 16.0
(4.20-17.0) (6.30-19.0)
Males 16.0 18.0
(5.80-17.0) (17.0-32.0)
Females 10.0 20.0
(4.50-17.0) (13.0-40.0)
Non-Hispanic whites 13.0 18.0
(4.20-17.0) (16.0-40.0)
Non-Hispanic blacks 14.0 18.0
(7.0-18.0) (17.0-39.0)
Mexican Americans 5.70 12.0
(4.00-9.70) (6.80-17.0)
DEP
All (a) 7.50 13.0
(5.20-11.0) (8.00-21.0)
6-11 years of age 10.0 15.0
(4.80-16.0) (11.0-27.0)
12-19 years of age 7.90 20.0
(4.20-23.0) (8.00-27.0)
20-59 years of age 7.20 10.0
(4.90-10.0) (6.90-19.0)
Males 8.00 18.0
(5.00-19.00) (7.40-27.0)
Females 7.50 11.0
(4.90-10.0) (7.70-14.0)
Non-Hispanic whites 7.60 14.0
(4.80-14.0) (7.90-23.0)
Non-Hispanic blacks 10.0 18.0
(6.20-16.0) (10.0-26-0)
Mexican Americans 11.00 17.0
(6.90-13.0) (12.0-23.0)
DETP
All (a) 1.30 2.20
(1.20-1.60) (1.70-2.80)
6-11 years of age 1.70 3.13
(1.30-2.40) (1.70-5.00)
12-19 years of age 1.40 2.20
(1.20-1.90) (1.60-3.10)
20-59 years of age 1.30 2.00
(0.99-1.50) (1.50-2.80)
Males 1.40 2.70
(1.20-1.90) (1.90-4.10)
Females 1.24 1.70
(0.950-1.50) (1.30-2.70)
Non-Hispanic whites 1.30 1.80
(0.980-1.50) (1.50-2.80)
Non-Hispanic blacks 1.80 3.50
(1.24-3.30) (1.80-4.80)
Mexican Americans 1.40 2.20
(1.10-1.90) (1.90-2.90)
DEDTP
All (a) 0.47 0.87
(0.39-0.63) (0.65-1.00)
6-11 years of age 0.43 0.85
(0.30-0.55) (0.49-1.00)
12-19 years of age 0.64 0.90
(0.36-0.86) (0.68-1.30)
20-59 years of age 0.45 0.90
(0.36-0.62) (0.61-1.10)
Males 0.47 0.87
(0.36-0.66) (0.65-1.10)
Females 0.45 0.85
(0.35-0.69) (0.46-1.40)
Non-Hispanic whites 0.42 0.87
(0.32-0.68) (0.51-1.10)
Non-Hispanic blacks 0.56 0.85
(0.42-0.82) (0.65-1.20)
Mexican Americans 0.65 1.1
(0.49-1.00) (0.63-1.70)
Abbreviations: GM, geometric mean; LOD, limit of detection; NC,
not calculated because proportion of results below the LOD was
too high to provide reliable result; NE, could not be reliably
estimated. Upper and lower 95th confidence intervals of each
quantile are shown in parentheses; these data are shown as
total population data and divided into demographic subgroups
based on race/ethnicity, sex, and age.
(a) All population data, including those individuals not grouped
into one of the three composite race/ethnicity categories, are
presented.
Table 2. Weighted quantiles of creatinine-adjusted urinary DAP
concentrations ([micro]g/g creatinine) in the NHANES 1999-2000
study population.
Analyte/ Detection
demographic category No. frequency (%) GM
DMP
All (a) 1,949 53 NC
6-11 years of age 471 63 NC
12-19 years of age 664 50 NC
20-59 years of age 814 52 NC
Males 952 53 NC
Females 997 54 NC
Non-Hispanic whites 594 49 NC
Non-Hispanic blacks 509 62 NC
Mexican Americans 672 59 NC
DMTP
All (a) 1,949 64 1.64
(1.27-2.10)
6-11 years of age 471 69 2.95
(2.00-4.34)
12-19 years of age 664 67 1.71
(1.13-2.59)
20-59 years of age 814 63 1.47
(1.14-1.90)
Males 952 66 1.61
(1.19-2.18)
Females 997 62 1.66
(1.24-2.21)
Non-Hispanic whites 594 64 1.68
(1.21-2.32)
Non-Hispanic blacks 509 68 1.45
(0.95-2.23)
Mexican Americans 672 63 1.60
(0.962-2.67)
DMDTP
All (a) 1,949 53 NC
6-11 years of age 471 63 NC
12-19 years of age 664 51 NC
20-59 years of age 814 48 NC
Males 952 53 NC
Females 997 53 NC
Non-Hispanic whites 594 50 NC
Non-Hispanic blacks 509 56 NC
Mexican Americans 672 53 NC
DEP
All (a) 1,949 71 0.93
(0.69-1.25)
6-11 years of age 471 74 1.43
(0.94-2.17)
12-19 years of age 664 73 0.76
(0.55-1.05)
20-59 years of age 814 69 0.90
(0.67-1.23)
Males 952 72 0.86
(0.63-1.17)
Females 997 69 1.00
(0.73-1.37)
Non-Hispanic whites 594 68 0.94
(0.65-1.37)
Non-Hispanic blacks 509 82 1.06
(0.84-1.35)
Mexican Americans 672 74 1.08
(0.74-1.58)
DETP
All (a) 1,949 53 NC
6-11 years of age 471 59 NC
12-19 years of age 664 46 NC
20-59 years of age 814 54 NC
Males 952 57 NC
Females 997 50 NC
Non-Hispanic whites 594 51 NC
Non-Hispanic blacks 509 64 NC
Mexican Americans 672 58 NC
DEDTP
All (a) 1,949 56 NC
6-11 years of age 471 60 NC
12-19 years of age 664 51 NC
20-59 years of age 814 56 NC
Males 952 57 NC
Females 997 54 NC
Non-Hispanic whites 594 53 NC
Non-Hispanic blacks 509 61 NC
Mexican Americans 672 66 NC
Percentile of distribution
Analyte/
demographic category 25th 50th 75th
DMP
All (a) < LOD 0.81 2.93
(0.59-1.11) (2.12-3.86)
6-11 years of age < LOD 1.38 4.48
(0.89-2.38) (2.63-8.20)
12-19 years of age < LOD 0.59 2.27
(0.45-0.95) (1.67-2.91)
20-59 years of age < LOD 0.76 2.87
(0.56-1.11) (1.91-3.92)
Males < LOD 0.62 2.38
(0.45-0.89) (1.78-3.23)
Females < LOD 1.00 3.53
(0.68-1.50) (2.35-5.00)
Non-Hispanic whites < LOD < LOD 3.15
(2.03-4.26)
Non-Hispanic blacks < LOD 0.69 2.67
(0.53-1.06) (1.78-3.87)
Mexican Americans < LOD 1.06 3.68
(0.72-1.47) (2.77-4.67)
DMTP
All (a) < LOD 2.12 9.57
(1.38-3.11) (6.67-15.1)
6-11 years of age < LOD 5.25 18.7
(2.50-7.03) (11.6-31.5)
12-19 years of age < LOD 2.14 13.4
(1.22-4.13) (7.01-21.0)
20-59 years of age < LOD 1.90 8.09
(1.00-2.83) (5.58-12.4)
Males < LOD 2.28 9.27
(1.42-3.35) (6.43-15.4)
Females < LOD 2.01 10.0
(0.92-3.11) (6.20-17.5)
Non-Hispanic whites < LOD 2.20 9.27
(1.17-3.42) (5.96-16.9)
Non-Hispanic blacks < LOD 1.75 8.21
(1.01-3.38) (4.65-12.4)
Mexican Americans < LOD 1.83 10.4
(0.74-3.75) (5.93-17.1)
DMDTP
All (a) < LOD < L0D 1.86
(1.04-3.25)
6-11 years of age < LOD < LOD 4.07
(2.34-7.00)
12-19 years of age < LOD < LOD 1.52
(0.64-3.37)
20-59 years of age < LOD < LOD 1.71
(0.92-2.82)
Males < LOD < LOD 1.64
(0.87-3.45)
Females < LOD < LOD 1.99
(1.00-3.67)
Non-Hispanic whites < LOD < LOD 1.75
(0.85-4.00)
Non-Hispanic blacks < LOD < LOD 2.39
(1.18-4.53)
Mexican Americans < LOD < LOD 1.35
(0.97-1.99)
DEP
All (a) < LOD 0.92 2.73
(0.63-1.28) (1.89-4.29)
6-11 years of age < LOD 1.47 3.94
(1.02-2.41) (2.39-8.15)
12-19 years of age < LOD 0.79 2.29
(0.62-1.13) (1.40-3.42)
20-59 years of age < LOD 0.86 2.63
(0.58-1.18) (1.71-4.38)
Males < LOD 0.81 2.61
(0.59-1.19) (1.76-4.13)
Females < LOD 0.96 2.80
(0.64-1.45) (1.89-4.72)
Non-Hispanic whites < LOD 0.90 2.82
(0.51-1.48) (1.75-5.33)
Non-Hispanic blacks < LOD 1.17 2.55
(0.83-1.53) (2.13-3.24)
Mexican Americans < LOD 1.05 3.78
(0.74-1.57) (2.29-5.79)
DETP
All (a) < LOD 0.25 0.71
(0.10-0.42) (0.51-0.96)
6-11 years of age < LOD 0.47 1.08
(0.15-0.83) (0.83-1.30)
12-19 years of age < LOD 0.18 0.51
(0.06-0.33) (0.34-0.76)
20-59 years of age < LOD 0.25 0.69
(0.10-0.41) (0.47-0.96)
Males < LOD 0.27 0.67
(0.10-0.42) (0.52-0.81)
Females < LOD < LOD 0.79
(0.45-1.20)
Non-Hispanic whites < LOD 0.23 0.71
(0.08-0.46) (0.46-1.05)
Non-Hispanic blacks < LOD 0.30 0.72
(0.15-0.46) (0.54-0.84)
Mexican Americans < LOD 0.34 0.83
(0.10-0.57) (0.57-1.13)
DEDTP
All (a) < LOD 0.07 0.20
(0.06-0.11) (0.15-0.26)
6-11 years of age < LOD 0.10 0.19
(0.07-0.13) (0.15-0.25)
12-19 years of age < LOD 0.05 0.17
(0.04-0.07) (0.10-0.22)
20-59 years of age < LOD 0.08 0.21
(0.06-0.11) (0.15-0.29)
Males < LOD 0.07 0.19
(0.05-0.10) (0.14-0.22)
Females <LOD 0.09 0.22
(0.06-0.12) (0.16-0.32)
Non-Hispanic whites < LOD 0.07 0.20
(0.05-0.11) (0.14-0.29)
Non-Hispanic blacks < LOD 0.07 0.18
(0.05-0.10) (0.13-0.22)
Mexican Americans < LOD 0.09 0.30
(0.07-0.15) (0.19-0.41)
Percentile of
distribution
Analyte/
demographic category 90th 95th
DMP
All (a) 8.46 16.1
(6.74-11.2) (12.1-19.5)
6-11 years of age 15.9 21.7
(7.65-21.7) (16.7-45.1)
12-19 years of age 7.70 14.5
(4.16-13.8) (7.78-35.3)
20-59 years of age 8.11 14.6
(5.45-10.6) (10.1-17.6)
Males 7.58 15.2
(4.64-11.6) (9.74-19.5)
Females 9.12 16.4
(7.59-12.2) (10.4-21.4)
Non-Hispanic whites 8.73 15.8
(6.12-12.8) (10.2-19.7)
Non-Hispanic blacks 7.07 13.9
(4.77-11.5) (9.61-19.5)
Mexican Americans 9.41 15.9
(7.24-12.2) (12.7-23.2)
DMTP
All (a) 32.0 51.0
(23.9-40.4) (39.0-71.1)
6-11 years of age 45.2 65.9
(32.1-60.3) (50.7-100)
12-19 years of age 36.0 61.5
(25.1-51.4) (37.1-179)
20-59 years of age 27.0 47.4
(20.6-37.1) (34.2-70.1)
Males 28.9 41.1
(20.5-37.6) (32.0-57.1)
Females 34.5 69.5
(25.4-47.4) (41.7-118)
Non-Hispanic whites 32.5 54.4
(21.3-49.4) (39.2-74.7)
Non-Hispanic blacks 25.5 52.1
(17.9-38.8) (25.55-97.6)
Mexican Americans 37.0 112
(22.8-63.1) (39.2-207)
DMDTP
All (a) 10.1 21.7
(5.63-16.6) (13.8-30.8)
6-11 years of age 16.2 30.8
(9.25-27.0) (20.2-38.9)
12-19 years of age 9.42 18.5
(4.02-16.8) (8.76-44.8)
20-59 years of age 8.46 19.2
(4.96-16.6) (9.82-35.2)
Males 11.0 17.8
(5.32-16.6) (10.1-34.2)
Females 9.30 27.0
(5.41-21.5) (9.82-47.5)
Non-Hispanic whites 11.3 21.5
(4.79-20.2) (12.8-30.8)
Non-Hispanic blacks 9.41 17.8
(5.11-16.6) (11.6-36.0)
Mexican Americans 6.55 16.7
(4.10-11.6) (6.94-34.2)
DEP
All (a) 7.94 12.1
(4.90-11.7) (8.75-17.5)
6-11 years of age 10.3 16.2
(4.55-20.6) (10.5-32.7)
12-19 years of age 5.38 12.3
(2.89-12.3) (4.87-23.8)
20-59 years of age 7.37 12.1
(4.60-11.3) (8.57-15.7)
Males 7.69 12.2
(4.55-11.7) (8.00-21.6)
Females 8.00 12.1
(4.90-11.7) (8.10-17.5)
Non-Hispanic whites 8.46 12.6
(4.95-13.3) (8.89-19.6)
Non-Hispanic blacks 5.98 11.7
(4.22-8.93) (6.62-19.4)
Mexican Americans 9.84 15.6
(6.57-14.4) (10.3-19.3)
DETP
All (a) 1.70 2.64
(1.21-2.17) (2.12-2.96)
6-11 years of age 1.73 2.45
(1.44-2.36) (1.88-5.42)
12-19 years of age 1.07 1.97
(0.78-1.53) (1.07-3.92)
20-59 years of age 1.79 2.75
(1.18-2.32) (2.12-3.06)
Males 1.34 2.66
(1.08-2.18) (1.56-3.23)
Females 1.89 2.52
(1.22-2.33) (2.08-2.96)
Non-Hispanic whites 1.88 2.58
(1.20-2.36) (2.12-2.96)
Non-Hispanic blacks 1.35 2.89
(0.90-2.89) (1.35-5.13)
Mexican Americans 1.69 2.71
(1.30-2.16) (1.86-3.55)
DEDTP
All (a) 0.55 0.86
(0.41-0.69) (0.69-1.13)
6-11 years of age 0.57 1.03
(0.39-0.77) (0.60-1.57)
12-19 years of age 0.44 0.73
(0.23-0.73) (0.39-0.95)
20-59 years of age 0.55 0.86
(0.38-0.71) (0.67-1.16)
Males 0.42 0.72
(0.32-0.52) (0.49-0.94)
Females 0.67 0.89
(0.41-0.86) (0.71-1.38)
Non-Hispanic whites 0.55 0.88
(0.39-0.73) (0.65-1.16)
Non-Hispanic blacks 0.45 0.69
(0.28-0.68) (0.48-1.07)
Mexican Americans 0.81 1.16
(0.52-1.00) (0.86-2.66)
Abbreviations: GM, geometric mean; LOD, limit of detection; NC,
not calculated because proportion of results below the LOD was
too high to provide reliable result; NE, could not be reliably
estimated. Upper and lower 95th confidence intervals of each
quantile are shown in parentheses; these data are shown as
total population data and divided into demographic subgroups
based on race/ethnicity, sex, and age.
(a) All population data, including those individuals not grouped
into one of the three composite race/ethnicity categories, are
presented.
Table 3. LSGMs (95% CIs) of urinary DAP metabolites among
demographic groups.
DMTP DEP
Category Demographic group ([micro]g/L) ([micro]g/L)
Age 6-11 years of age 3.08 * 1.73 *
(children) (1.90-4.97) (1.06-2.83)
12-19 years of age 2.07 1.06
(adolescents) (1.35-3.17) (0.73-1.55)
20-59 years of age 1.59 1.00
(adults) (1.16-2.16) (0.74-1.37)
Sex Males 2.00 1.08
(1.44-2.78) (0.79-1.49)
Females 1.57 1.07
(1.11-2.22) (0.77-1.48)
Race/ethnicity Non-Hispanic whites 1.78 1.03
(1.25-2.53) (0.73-1.47)
Non-Hispanic blacks 1.79 1.25
(1.155-2.79) (0.98-1.60)
Mexican Americans 1.69 1.16
(1.02-2.80) (0.80-1.70)
Category Demographic group DMAP (nmol/L) REAP (nmol/L)
Age 6-11 years of age 72.8 * 17.4 *
(children) (54.3-97.5) (11.1-27.3)
12-19 years of age 56.9 11.0
(adolescents) (40.2-80.7) (7.6-15.9)
20-59 years of age 42.1 10.0
(adults) (33.6-52.8) (7.5-13.2)
Sex Males 50.6 10.8
(40.0-64.2) (8.0-14.5)
Females 42.9 10.7
(33.8-54.3) (8.0-14.3)
Race/ethnicity Non-Hispanic whites 45.2 10.4
(35.3-57.8) (7.5-14.3)
Non-Hispanic blacks 53.0 12.0
(38.8-72.6) (9.3-15.5)
Mexican Americans 50.1 12.2
(36.8-68.3) (8.6-17.2)
Category Demographic group DAP (nmol/L)
Age 6-11 years of age 109.6 *
(children) (83.3-144.3)
12-19 years of age 89.3 *
(adolescents) (65.2-122.2)
20-59 years of age 66.9
(adults) (54.3-82.5)
Sex Males 79.1
(62.6-9.99)
Females 68.2
(55.9-83.3)
Race/ethnicity Non-Hispanic whites 70.9
(56.4-89.1)
Non-Hispanic blacks 83.0
(65.6-105.0)
Mexican Americans 82.7
(62.1-110.2)
LSGMs were adjusted for age, sex, race/ethnicity, and concentrations
of serum cotinine and urinary creatinine. LSGMs were calculated for
metabolites with detection frequencies of [greater than or equal to]
60%.
* Significantly different from adults at 0.05.
Table 4. Weighted quantiles of composite DMAP and DEAP concentrations
(nmol/L) in the NHANES 1999-2000 study population.
Analyte/ Detection
demographic category No. frequency(%) GM
DAP
All (a) 1,949 94 76.3
(65.0-89.6)
6-11 years of age 471 96 101
(80.7-126)
12-19 years of age 664 94 96.5
(73.6-127)
20-59 years of age 814 92 69.4
(58.5-82.4)
Males 952 94 82.9
(67.5-101.8)
Females 997 93 70.4
(60.0-82.6)
Non-Hispanic whites 594 92 72.8
(59.0-90.0)
Non-Hispanic blacks 509 96 96.3
(79.1-117)
Mexican Americans 672 93 84.1
(65.0-109)
DMAP
All (a) 1,949 84 49.4
(41.7-58.5)
6-11 years of age 471 87 70.3
(55.6-88.8)
12-19 years of age 664 84 63.0
(46.8-84.7)
20-59 years of age 814 82 44.3
(36.9-53.1)
Males 952 84 53.1
(43.2-65.2)
Females 997 84 46.0
(38.2-55.5)
Non-Hispanic whites 594 82 47.3
(37.9-59.0)
Non-Hispanic blacks 509 86 59.6
(44.9-79.0)
Mexican Americans 672 84 52.1
(39.1-69.4)
DEAP
All (a) 1,949 77 10.5
(7.93-13.9)
6-11 years of age 471 80 13.2
(8.80-19.8)
12-19 years of age 664 82 11.8
(8.4-16.6)
20-59 years of age 814 76 9.85
(7.46-13.0)
Males 952 80 11.5
(8.60-15.4)
Females 997 77 9.56
(710-12.8)
Non-Hispanic whites 594 76 9.96
(7.03-14.1)
Non-Hispanic blacks 509 83 15.2
(12.1-19.2)
Mexican Americans 672 81 12.5
(9.10-17.1)
Percentile of distribution
Analyte/
demographic category 10th 25th 50th
DAP
All (a) 8.65 31.1 81.7
(6.00-15.2) (24.0-40.0) (65.5-98.9)
6-11 years of age 10.6 40.3 113
(6.00-22.0) (26.5-61.0) (78.2-152)
12-19 years of age 12.9 36.0 93.2
(6.50-21.9) (28.0-50.2) (64.3-135)
20-59 years of age 7.36 26.6 75.3
(6.00-12.8) (20.0-39.6) (60.3-92.5)
Males 11.2 35.7 87.1
(6.40-19.4) (26.4-47.0) (65.4-110)
Females 6.46 25.0 76.2
(6.00-12.5) (19.6-36.0) (61.6-92.3)
Non-Hispanic whites 6.51 27.5 76.2
(6.00-12.4) (19.4-41.0) (60.7-107)
Non-Hispanic blacks 18.1 43.4 105
(12.0-26.8) (32.0-56.8) (78.1-123)
Mexican Americans 10.5 32.2 81.7
(6.00-20.7) (24.4-43.0) (59.7-114)
DMAP
All (a) 4.47 13.2 54.5
(4.20-4.55) (7.60-19.5) (42.2-68.8)
6-11 years of age 4.47 23.4 90.6
(4.20-4.55) (11.8-39.0) (64.9-112)
12-19 years of age 4.55 18.1 62.2
(4.20-4.55) (11.6-28.0) (41.2-103)
20-59 years of age 4.55 11.8 48.3
(4.20-4.55) (6.10-18.4) (37.4-62.4)
Males 4.55 17.2 59.1
(4.20-4.55) (11.6-24.0) (45.1-74.5)
Females 4.55 11.0 46.8
(4.20-4.55) (4.80-18.0) (37.7-68.7)
Non-Hispanic whites 4.15 11.6 54.0
(4.20-4.55) (5.4-21.9) (38.4-70.2)
Non-Hispanic blacks 4.55 22.3 71.9
(4.20-4.55) (10.0-37) (50.3-96.3)
Mexican Americans 4.15 15.6 48.0
(4.20-4.55) (7.10-24.6) (38.6-72.0)
DEAP
All (a) < LOD 2.30 12.3
(1.50-7.20) (9.9-15.6)
6-11 years of age < LOD 4.70 15.6
(1.50-11.7) (12.3-21.4)
12-19 years of age < LOD 3.23 12.9
(1.48-8.34) (10.3-16.8)
20-59 years of age < LOD 1.80 11.6
(1.48-6.10) (9.12-14.4)
Males < LOD 2.96 12.4
(1.48-7.70) (10.0-16.6)
Females < LOD < LOD 11.9
(9.00-15.5)
Non-Hispanic whites < LOD < LOD 12.0
(7.80-16.5)
Non-Hispanic blacks < LOD 9.0 15.7
(3.23-11.2) (12.5-19.0)
Mexican Americans < LOD 3.82 13.9
(1.48-9.18) (10.9-17.3)
Percentile of distribution
Analyte/
demographic category 75th 90th 95th
DAP
All (a) 202 399 651
(168-270) (357-475) (516-911)
6-11 years of age 287 507 832
(218-350) (410-623) (599-1,230)
12-19 years of age 268 541 1,130
(175-320) (362-1,000) (563-2,180)
20-59 years of age 188 380 552
(144-233) (294-416) (411-798)
Males 239 400 648
(164-288) (332-520) (486-930)
Females 190.0 387 692
(152-227) (300-454) (428-971)
Non-Hispanic whites 202 386 651
(151-273) (314-494) (471-932)
Non-Hispanic blacks 233 417 692
(171-278) (330-623) (481-911)
Mexican Americans 215 479 1,250
(172-264) (347-798) (532-1,930)
DMAP
All (a) 159 377 583
(123-216) (290-403) (441-725)
6-11 years of age 270 460 679
(174-308) (338-515) (493-1,080)
12-19 years of age 224 472 1,120
(139-271) (320-911) (498-2,140)
20-59 years of age 137 331 426
(102-181) (271-378) (379-623)
Males 179 377 552
(117-271) (288-419) (378-725)
Females 149 375 638
(116-179) (274-414) (401-937)
Non-Hispanic whites 153 366 568
(112-237) (273-409) (394-783)
Non-Hispanic blacks 195 379 623
(121-268) (292-469) (421-812)
Mexican Americans 155 403 1,230
(124-189) (271-748) (455-1,920)
DEAP
All (a) 28.3 64.7 108
(22.0-36.6) (42.9-84.7) (73.4-147)
6-11 years of age 35.9 87.5 136
(21.2-60.3) (51.3-121) (87.2-200)
12-19 years of age 30.5 84.4 161
(19.1-45.1) (39.5-164) (64.4-185)
20-59 years of age 27.0 59.0 88.0
(20.5-34.1) (41.8-78.5) (65.9-137)
Males 31.9 68.9 147
(22.0-39.7) (46.4-137) (73.4-186)
Females 25.5 58.4 80.1
(19.1-34.0) (41.7-77.1) (70.6-104)
Non-Hispanic whites 28.0 65.1 109
(19.2-39.9) (41.7-105) (70.6-161)
Non-Hispanic blacks 36.6 77.8 126
(29.2-44.1) (50.5-113) (78.5-186)
Mexican Americans 33.5 83.9 126
(23.1-48.6) (58.4-102) (95.8-178)
NE, could not be reliably estimated. To determine the composite
concentrations, the dialkylphosphate concentrations were converted
to their molar equivalents and then summed. Upper and lower 95th
confidence intervals of each quantile are shown in parentheses;
these data are shown as total population data and divided into
demographic subgroups based on race/ethnicity, sex, and age.
(a) All population data, including those individuals not grouped
into one of the three composite race/ethnicity categories, are
presented.
Table 5. Weighted quantiles of creatinine-adjusted composite DMAP
and DEAP concentrations (nmol/L) in the NHANES 1999-2000 study
population.
Analyte/ Detection
demographic category No. frequency (%) GM
DAP
All (a) 1,949 94 68.5
(57.98-80.92)
6-11 years of age 471 96 109
(88.7-134.1)
12-19 years of age 664 94 65.1
(48.96-86.67)
20-59 years of age 814 92 64.1
(53.33-77.06)
Males 952 94 63.7
(51.1-79.3)
Females 997 93 73.6
(62.2-87.0)
Non-Hispanic whites 594 92 69.2
(55.4-86.5)
Non-Hispanic blacks 509 96 65.9
(54.2-80.1)
Mexican Americans 672 93 75.3
(56.4-100)
DMAP
All (a) 1,949 84 44.3
(37.2-52.8)
6-11 years of age 471 87 76.1
(61.0-94.9)
12-19 years of age 664 84 42.5
(30.9-58.5)
20-59 years of age 814 82 40.9
(33.9-49.4)
Males 952 84 40.8
(32.7-50.9)
Females 997 84 48.1
(39.7-58.3)
Non-Hispanic whites 594 82 44.9
(35.5-56.8)
Non-Hispanic blacks 509 86 40.75
(31.3-53.1)
Mexican Americans 672 84 46.6
(34.1-63.6)
DEAP
All (a) 1,949 77 14.7
(11.0-19.6)
6-11 years of age 471 80 21.5
(15.9-29.0)
12-19 years of age 664 82 10.7
(8.16-14.1)
20-59 years of age 814 76 14.0
(11.0-17.7)
Males 952 80 12.8
(9.98-16.4)
Females 997 77 15.7
(12.3-20.1)
Non-Hispanic whites 594 76 14.7
(11.0-19.6)
Non-Hispanic blacks 509 83 13.9
(11.5-16.8)
Mexican Americans 672 81 15.5
(11.6-20.6)
Percentile of distribution
Analyte/
demographic category 10th 25th 50th
DAP
All (a) 10.0 25.9 70.9
(8.10-12.5) (19.0-34.6) (55.5-84.6)
6-11 years of age 14.9 41.3 116
(10.8-24.2) (28.4-63.2) (95.1-159)
12-19 years of age 9.42 22.0 57.1
(7.90-13.5) (15.0-33.0) (40.0-87.0)
20-59 years of age 9.42 23.9 67.8
(7.5-11.9) (17.5-34.2) (51.3-81.0)
Males 10.2 23.8 64.1
(8.20-12.6) (17.0-35.0) (51.0-82.2)
Females 9.99 27.3 78.3
(7.80-12.6) (18.8-35.9) (59.7-92.8)
Non-Hispanic whites 9.67 25.3 74.2
(7.50-12.3) (16.7-38.2) (54.8-94.2)
Non-Hispanic blacks 13.7 23.8 62.5
(10.5-17.3) (19.1-31.0) (49.2-76.3)
Mexican Americans 10.0 29.5 75.1
(6.33-18.2) (22.1-39.7) (57.1-97.8)
DMAP
All (a) 4.14 13.5 43.4
(3.30-5.50) (9.50-19.8) (36.4-56.3)
6-11 years of age 5.60 26.5 91.0
(4.40-11.1) (16.4-46.6) (67.4-109)
12-19 years of age 3.92 10.4 36.7
(2.80-6.40) (7.10-19.0) (27.8-58.9)
20-59 years of age 3.64 12.9 41.1
(3.20-5.50) (8.40-19.6) (33.8-50.3)
Males 3.73 13.3 40.4
(3.30-5.10) (9.10-18.9) (34.7-63.0)
Females 4.24 14.4 47.3
(3.50-6.10) (9.30-22.7) (36.3-61.1)
Non-Hispanic whites 3.79 13.8 44.2
(3.20-5.50) (8.60-23.3) (35.8-60.4)
Non-Hispanic blacks 5.00 13.6 42.5
(3.20-7.50) (9.00-22.3) (30.9-57.3)
Mexican Americans 4.14 16.1 41.9
(2.50-7.00) (8.90-23.3) (35.6-57.5)
DEAP
All (a) 1.33 3.44 8.82
(1.20-1.80) (2.30-4.91) (6.81-11.9)
6-11 years of age 1.65 5.92 14.9
(1.21-3.66) (2.52-10.7) (10.7-22.4)
12-19 years of age 1.28 3.20 7.55
(1.06-1.81) (1.83-4.35) (6.01-10.2)
20-59 years of age 1.30 3.28 8.42
(1.16-1.82) (2.22-4.78) (6.41-11.5)
Males 1.26 3.12 8.42
(1.10-1.46) (1.91-4.62) (6.78-11.7)
Females 1.63 3.68 9.15
(1.26-2.21) (2.62-5.28) (6.72-13.4)
Non-Hispanic whites 1.30 3.20 8.60
(1.11-1.82) (2.20-4.88) (5.90-13.6)
Non-Hispanic blacks 1.59 4.48 10.8
(1.16-3.02) (3.72-6.44) (8.05-13.7)
Mexican Americans 1.32 3.89 10.6
(1.05-2.12) (2.28-6.78) (7.81-15.8)
Percentile of distribution
Analyte/
demographic category 75th 90th 95th
DAP
All (a) 189 405 748
(152-223) (310-493) (536-1,000)
6-11 years of age 283 574 979
(205-351) (364-905) (609-1,240)
12-19 years of age 170 432 1,120
(115-227) (252-880) (500-1,470)
20-59 years of age 176 352 611
(139-217) (281-471) (412-1,000)
Males 177 352 611
(135-222) (269-452) (409-981)
Females 204 438 912
(157-240) (342-566) (538-1,120)
Non-Hispanic whites 197 405 713
(146-246) (288-566) (475-1,030)
Non-Hispanic blacks 148 336 656
(115-217) (259-540) (423-854)
Mexican Americans 180 453 1,130
(137-261) (290-912) (512-1,460)
DMAP
All (a) 153 337 601
(118-184) (272-408) (414-923)
6-11 years of age 243 494 753
(169-316) (326-683) (499-1,060)
12-19 years of age 139 418 961
(103-191) (226-762) (425-1,430)
20-59 years of age 143 312 522
(95.7-173) (238-403) (352-822)
Males 144 295 472
(103-182) (237-403) (362-692)
Females 163 393 768
(114-206) (312-534) (494-1,110)
Non-Hispanic whites 159 337 581
(105-196) (249-454) (402-964)
Non-Hispanic blacks 122 318 536
(86.6-193) (232-472) (328-713)
Mexican Americans 140 410 1,120
(100-187) (241-758) (446-1,460)
DEAP
All (a) 24.0 66.9 97.7
(16.3-35.3) (43.4-85.5) (80.7-120)
6-11 years of age 34.4 85.4 128
(21.1-54.6) (56.0-113) (91.8-213)
12-19 years of age 19.6 47.1 112
(11.9-27.4) (26.1-110) (44.2-194)
20-59 years of age 23.0 65.5 94.3
(15.4-36.3) (43.1-85.3) (77.4-120)
Males 23.0 68.0 104
(16.3-34.0) (40.9-86.3) (80.0-129)
Females 24.5 65.6 96.4
(15.8-38.0) (43.1-88.4) (69.8-139)
Non-Hispanic whites 26.1 73.9 108
(15.4-43.1) (43.1-97.2) (85.3-139)
Non-Hispanic blacks 22.8 48.6 84.5
(17.8-28.1) (35.4-70.2) (57.0-153)
Mexican Americans 31.9 75.5 110
(20.9-47.9) (58.5-100) (75.5-145)
NE, could not be reliably estimated. To determine the composite
concentrations, the DAP concentrations were converted to their
molar equivalents and then summed. Upper and lower 95th confidence
intervals of each quantile are shown in parentheses; these data
are shown as total population data and divided into demographic
subgroups based on race/ethnicity, sex, and age.
(a) All population data, including those individuals not grouped
into one of the three composite race/ethnicity categories, are
presented.
Table 6. Pearson correlation coefficients of DAP metabolites of OP
pesticides with selective OP metabolites.
TCPY
(chlorpyrifos,
chlorpyrifos-
methyl) IMPY (diazinon)
Metabolite r-Value p-Value r-Value p-Value
DMP 0.11 0.007 ND ND
DMTP 0.12 0.0101 ND ND
DEP 0.22 < 0.0001 0.27 < 0.0001
DETP 0.29 < 0.0001 0.38 < 0.0001
DEAP 0.25 < 0.0001 0.29 < 0.0001
DMAP 0.114 0.009 ND ND
PNP (a)
(parathion,
MAL (malathion) methyl parathion)
Metabolite r-Value p-Value r-Value p-Value
DMP 0.10 0.0138 0.16 0.014
DMTP 0.16 < 0.0001 0.09 0.015
DEP ND ND 0.27 < 0.0001
DETP ND ND 0.27 0.0003
DEAP ND ND 0.27 < 0.0001
DMAP 0.14 0.0004 0.064 0.114
Abbreviations: MAL, malathion dicarboxylic acid; ND, not determined;
PNP, para-nitrophenol; TCPY, 3,5,6-trichloropyridinol. The parent
pesticides for each selective metabolite are listed below the
metabolite. All analyses were weighted and used log-transformed data.
(a) PNP can also be derived from exposure to pesticides such as EPN
(0-ethyl-4- 0-nitro phenyl phenylphasphonothioate) and other
nonpesticide sources such as 4-aminophenol.
Table 7. DAP concentrations in reported studies. Concentrations
shown are mean values unless otherwise indicated; median values
shown in parentheses.
Study Study population No.
Incidental or community-based measures
Griffith and Duncan General U.S. 6,894
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 124
Loewenherz et al. 1997 Reference children 33
(0-6 years, WA
State)
Applicator children 127
Children living 51
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in 110
farm families
Aprea et al. 2000 (b) Italian children 195
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period 28
Control period 6
Hardt and Angerer 2000 German adults 54
Lu et al. 2000 (e) Reference children 14
(central WA)
Applicator children 49
Farm children 13
0'Rourke et al. 2000 (d) U.S.-Mexico border 121
CDC 2001 (b) General U.S- 703
(NHANES 1999)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age 309
6-13 years of age 294
14-19 years of age 59
[greater than or equal 484
to] 20 years of age
Lu et al. 2001 Children (2-5 years 110
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers 18
Farm children 9
Curl et al. 2002 (b) Agricultural workers 213
Workers' children 211
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months 44
(26/child)
Nonspray months 44
(26/child)
Royster et al. 2002 Toddlers in 15
agricultural
region of CA
2nd visit 17
Castorina et al. 2003 Pregnant women 1,365
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 18
years of age;
WA State)
Regular diet (2-6 21
years of age;
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 41
Mexico border
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide 6
formulators
Nonexposed 6
Duncan and Griffith Citrus sprayers 332
1985 (h) Citrus harvesters 265
Griffith and Duncan 1985 Citrus sprayers 332
Citrus harvesters 264
Franklin et al. 1986 (i) Canadian applicators 23
Guthion-dosed 10
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator 1
1989 (j)
Drevenkar et al. Orchard sprayers 97
1991 (c)
Aprea et al. 1994 Controls 99
(b,c,k)
Applicator women 19
with rubber gloves
and masks
Applicator women 28
with waterproof
cotton gloves and
masks
Applicator women 28
with cotton gloves
and masks
Applicator women 54
with cotton gloves
Men with no 13
protective wear
Takamiya 1994 Pest control 2 DMP
operators 4 DEP
Aprea et al. 1997 (b,c) Vineyard sprayers 9
Vineyard leaf thinners 2
Controls 46
Aprea et al. 1999 (b) Greenhouse workers
Basal 5
Reentry day 2 5
Reentry day 4 5
Reentry day 6 5
Controls 21
Cocker et al. 2002 (c,l) Controls 463
Occupational 917
exposures
Lin et al. 2002 (m) Farmers 4
preexposure
Farmers 4
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion 1
poisoning
Richter et al. 1992 Residents of 4
diazinon-
contaminated home
After cleanup 4
Davies and Peterson 1997 Parathion poisoning 1
Chlorovrifos ooisonino 1
Study Study population DMP
Incidental or community-based measures
Griffith and Duncan General U.S. 50 [micro]g/L
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 12 [micro]g/g
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in NA
farm families
Aprea et al. 2000 (b) Italian children 15 [micro]g/g
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period 250 [micro]g/L
Control period 250 [micro]g/L
Hardt and Angerer 2000 German adults (30 [micro]g/L)
Lu et al. 2000 (e) Reference children NA
(central WA)
Applicator children NA
Farm children NA
0'Rourke et al. 2000 (d) U.S.-Mexico border 25%
> 25 [micro]g/L
CDC 2001 (b) General U.S- 1.84 [micro]g/L
(NHANES 1999) (1.67)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age 63 [micro]g/g
(27)
6-13 years of age 35 [micro]g/g
(16)
14-19 years of age 24 [micro]g/g
(17)
[greater than or equal 28 [micro]g/g
to] 20 years of age (16)
Lu et al. 2001 Children (2-5 years NA
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers 8 [micro]g/L
Farm children 8 [micro]g/L
Curl et al. 2002 (b) Agricultural workers NA
Workers' children NA
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months NA
Nonspray months NA
Royster et al. 2002 Toddlers in 26.6 [micro]g/L
agricultural (6.63)
region of CA
2nd visit 30.1 [micro]g/L
(8.13)
(8.14)
Castorina et al. 2003 Pregnant women (1.7 [micro]g/L)
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 1.1 [micro]g/L
years of age; (0.6)
WA State)
Regular diet (2-6 1.9 [micro]g/L
years of age; (0.6)
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 22 [micro]g/g
Mexico border (10)
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide 20 [micro]g/L
formulators
Nonexposed 30 [micro]g/L
Duncan and Griffith Citrus sprayers 170 [micro]g/L
1985 (h) Citrus harvesters 1,650 [micro]g/L
Griffith and Duncan 1985 Citrus sprayers 160 [micro]g/L
Citrus harvesters 390 [micro]g/L
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator NA
1989 (j)
Drevenkar et al. Orchard sprayers NA
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control 99,000 [micro]g/g
operators
Aprea et al. 1997 (b,c) Vineyard sprayers 23 [micro]g/g
Vineyard leaf thinners 13 [micro]g/g
Controls 5 [micro]g/g
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls NA
Occupational NA
exposures
Lin et al. 2002 (m) Farmers NA
preexposure
Farmers NA
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion 50,000 [micro]g/L
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning NA
Chlorovrifos ooisonino NA
Study Study population DMTP
Incidental or community-based measures
Griffith and Duncan General U.S. 60 [micro]g/L
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 16 [micro]g/g
Loewenherz et al. 1997 Reference children 18 [micro]g/L
(0-6 years, WA (< 15 [micro]g/L)
State)
Applicator children 39 [micro]g/L
(15 [micro]g/L)
Children living 28 [micro]g/L
< 200 ft of orchard 53 [micro]g/L
Azaroff 1999 (d) Nonfieldworkers in NA
farm families
Aprea et al. 2000 (b) Italian children 15 [micro]g/g
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period 430 [micro]g/L
Control period 50 [micro]g/L
Hardt and Angerer 2000 German adults (22 [micro]g/L)
Lu et al. 2000 (e) Reference children 20 [micro]g/L
(central WA) (5 [micro]g/L)
Applicator children 40 [micro]g/L
Farm children 30 [micro]g/L
0'Rourke et al. 2000 (d) U.S.-Mexico border 26%
> 25 [micro]g/L
CDC 2001 (b) General U.S- 2.61 [micro]g/L
(NHANES 1999) (3.80)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age 77 [micro]g/g
(29)
6-13 years of age 37 [micro]g/g
(15)
14-19 years of age 18 [micro]g/g
(14)
[greater than or equal 37 [micro]g/g
to] 20 years of age (14)
Lu et al. 2001 Children (2-5 years NA
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers 13 [micro]g/L
Farm children 14 [micro]g/L
Curl et al. 2002 (b) Agricultural workers NA
Workers' children NA
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months NA
Nonspray months NA
Royster et al. 2002 Toddlers in NA
agricultural
region of CA
2nd visit NA
(3.2)
Castorina et al. 2003 Pregnant women (6.2 [micro]g/L)
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 4.3 [micro]g/L
years of age; (2.8)
WA State)
Regular diet (2-6 41 [micro]g/L
years of age; (14)
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 6 [micro]g/g
Mexico border (0)
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide 60 [micro]g/L
formulators
Nonexposed 120 [micro]g/L
Duncan and Griffith Citrus sprayers 100 [micro]g/L
1985 (h) Citrus harvesters 500 [micro]g/L
Griffith and Duncan 1985 Citrus sprayers 80 [micro]g/L
Citrus harvesters 150 [micro]g/L
Franklin et al. 1986 (i) Canadian applicators 146 [micro]g/L
Guthion-dosed 72 [micro]g/L
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator 550 [micro]g/L
1989 (j)
Drevenkar et al. Orchard sprayers (111 [micro]g/g)
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control NA
operators
Aprea et al. 1997 (b,c) Vineyard sprayers 32 [micro]g/g
Vineyard leaf thinners 59 [micro]g/g
Controls 14 [micro]g/g
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls NA
Occupational NA
exposures
Lin et al. 2002 (m) Farmers 32 [micro]g/L
preexposure
Farmers 77 [micro]g/L
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion 96,000 [micro]g/L
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning NA
Chlorovrifos ooisonino NA
Study Study population DMDTP
Incidental or community-based measures
Griffith and Duncan General U.S. 50 [micro]g/L
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 5 [micro]g/g
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in NA
farm families
Aprea et al. 2000 (b) Italian children 2 [micro]g/g
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period 60 [micro]g/L
Control period NA
Hardt and Angerer 2000 German adults (1 [micro]g/L)
Lu et al. 2000 (e) Reference children 3 [micro]g/L
(central WA) (0 [micro]g/L)
Applicator children 5 [micro]g/L
Farm children 2 [micro]g/L
0'Rourke et al. 2000 (d) U.S.-Mexico border 3% > [micro]g/L
> 25 [micro]g/L
CDC 2001 (b) General U.S- 0.51 [micro]g/L
(NHANES 1999) (0.60)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age 5 [micro]g/g
6-13 years of age 3 [micro]g/g
14-19 years of age 0.7 [micro]g/g
(3)
[greater than or equal 2 [micro]g/g
to] 20 years of age
Lu et al. 2001 Children (2-5 years NA
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers < 8 [micro]g/L
Farm children < 8 [micro]g/L
Curl et al. 2002 (b) Agricultural workers NA
Workers' children NA
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months NA
Nonspray months NA
Royster et al. 2002 Toddlers in NA
agricultural
region of CA
2nd visit NA
Castorina et al. 2003 Pregnant women (0.5 [micro]g/L)
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 0.8 [micro]g/L
years of age; (0.7)
WA State)
Regular diet (2-6 4.8 [micro]g/L
years of age; (2.1)
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 0.05 [micro]g/g
Mexico border (0)
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide < 20 [micro]g/L
formulators
Nonexposed < 20 [micro]g/L
Duncan and Griffith Citrus sprayers 150 [micro]g/L
1985 (h) Citrus harvesters 600 [micro]g/L
Griffith and Duncan 1985 Citrus sprayers 110 [micro]g/L
Citrus harvesters 250 [micro]g/L
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator 630 [micro]g/L
1989 (j)
Drevenkar et al. Orchard sprayers (145 [micro]g/g)
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control NA
operators
Aprea et al. 1997 (b,c) Vineyard sprayers NA
Vineyard leaf thinners NA
Controls NA
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls NA
Occupational NA
exposures
Lin et al. 2002 (m) Farmers 27 [micro]g/L
preexposure
Farmers 164 [micro]g/L
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion 20,000 [micro]g/L
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning NA
Chlorovrifos ooisonino NA
Study Study population DEP
Incidental or community-based measures
Griffith and Duncan General U.S. 40 [micro]g/L
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 6 [micro]g/g
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in NA
farm families
Aprea et al. 2000 (b) Italian children 5 [micro]g/g
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period NA
Control period NA
Hardt and Angerer 2000 German adults (4 [micro]g/L)
Lu et al. 2000 (e) Reference children NA
(central WA)
Applicator children NA
Farm children NA
0'Rourke et al. 2000 (d) U.S.-Mexico border 5%
> 25 [micro]g/L
CDC 2001 (b) General U.S- 2.6 [micro]g/L
(NHANES 1999) (1.85)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age 8 [micro]g/g
(5)
6-13 years of age 5 [micro]g/g
(3)
14-19 years of age 4 [micro]g/g
[greater than or equal 4 [micro]g/g
to] 20 years of age (2)
Lu et al. 2001 Children (2-5 years NA
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers < 8 [micro]g/L
Farm children < 8 [micro]g/L
Curl et al. 2002 (b) Agricultural workers NA
Workers' children NA
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months NA
Nonspray months NA
Royster et al. 2002 Toddlers in 4.9 [micro]g/L
agricultural (2.69)
region of CA
2nd visit 3.8 [micro]g/L
Castorina et al. 2003 Pregnant women (1 [micro]g/L)
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 1.0 [micro]g/L
years of age; (0.7)
WA State)
Regular diet (2-6 0.8 [micro]g/L
years of age; (0.7)
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 14 [micro]g/g
Mexico border (3)
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide 50 [micro]g/L
formulators
Nonexposed 1,200 [micro]g/L
Duncan and Griffith Citrus sprayers 350 [micro]g/L
1985 (h) Citrus harvesters 650 [micro]g/L
Griffith and Duncan 1985 Citrus sprayers 410 [micro]g/L
Citrus harvesters 90 [micro]g/L
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator NA
1989 (j)
Drevenkar et al. Orchard sprayers NA
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control 97,000 [micro]g/g
operators
Aprea et al. 1997 (b,c) Vineyard sprayers NA
Vineyard leaf thinners NA
Controls NA
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls NA
Occupational NA
exposures
Lin et al. 2002 (m) Farmers NA
preexposure
Farmers NA
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion NA
poisoning
Richter et al. 1992 Residents of 31, 000 pg/L
diazinon-
contaminated home
After cleanup < 10 [micro]g/L
Davies and Peterson 1997 Parathion poisoning 7,800 [micro]g/L
Chlorovrifos ooisonino 30,000 [micro]g/L
Study Study population DETP
Incidental or community-based measures
Griffith and Duncan General U.S. 40 [micro]g/L
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 5 [micro]g/g
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in NA
farm families
Aprea et al. 2000 (b) Italian children 3 [micro]g/g
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period 90 [micro]g/L
Control period 30 [micro]g/L
Hardt and Angerer 2000 German adults (< 3 [micro]g/L)
Lu et al. 2000 (e) Reference children NA
(central WA)
Applicator children NA
Farm children NA
0'Rourke et al. 2000 (d) U.S.-Mexico border < 25 [micro]g/L
CDC 2001 (b) General U.S- 0.8 [micro]g/L
(NHANES 1999) (0.70)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age 4 [micro]g/g
6-13 years of age 2 [micro]g/g
14-19 years of age 1 [micro]g/g
[greater than or equal 1 [micro]g/g
to] 20 years of age
Lu et al. 2001 Children (2-5 years NA
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers 8 [micro]g/L
Farm children 6 [micro]g/L
Curl et al. 2002 (b) Agricultural workers NA
Workers' children NA
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months NA
Nonspray months NA
Royster et al. 2002 Toddlers in NA
agricultural
region of CA
2nd visit NA
Castorina et al. 2003 Pregnant women (0.9 [micro]g/L)
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 2.7 [micro]g/L
years of age; (2.0)
WA State)
Regular diet (2-6 4.0 [micro]g/L
years of age; (3.0)
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 12 [micro]g/g
Mexico border (8)
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide 5 [micro]g/L
formulators
Nonexposed 900 [micro]g/L
Duncan and Griffith Citrus sprayers 250 [micro]g/L
1985 (h) Citrus harvesters 75 [micro]g/L
Griffith and Duncan 1985 Citrus sprayers 370 [micro]g/L
Citrus harvesters 70 [micro]g/L
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator NA
1989 (j)
Drevenkar et al. Orchard sprayers NA
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control NA
operators
Aprea et al. 1997 (b,c) Vineyard sprayers NA
Vineyard leaf thinners NA
Controls NA
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls NA
Occupational NA
exposures
Lin et al. 2002 (m) Farmers 52 [micro]g/L
preexposure
Farmers 54 [micro]g/L
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion NA
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning 1,500 [micro]g/L
Chlorovrifos ooisonino 30,000 [micro]g/L
Study Study population DEDTP
Incidental or community-based measures
Griffith and Duncan General U.S. 110 [micro]g/L
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults 3 [micro]g/g
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in NA
farm families
Aprea et al. 2000 (b) Italian children 1 [micro]g/g
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period 110 [micro]g/L
Control period 50 [micro]g/L
Hardt and Angerer 2000 German adults (< 3 [micro]g/L)
Lu et al. 2000 (e) Reference children NA
(central WA)
Applicator children NA
Farm children NA
0'Rourke et al. 2000 (d) U.S.-Mexico border < 25 [micro]g/L
CDC 2001 (b) General U.S- 0.19 [micro]g/L
(NHANES 1999) (0.14)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age < 1 [micro]g/g
6-13 years of age < 1 [micro]g/g
14-19 years of age 1 [micro]g/g
[greater than or equal 1 [micro]g/g
to] 20 years of age
Lu et al. 2001 Children (2-5 years NA
of age, Seattle, WA)
Mills and Zahm 2001 Adult farmworkers < 8 [micro]g/L
Farm children < 8 [micro]g/L
Curl et al. 2002 (b) Agricultural workers NA
Workers' children NA
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months NA
Nonspray months NA
Royster et al. 2002 Toddlers in NA
agricultural
region of CA
2nd visit NA
Castorina et al. 2003 Pregnant women (0 [micro]g/L)
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 NA
years of age;
WA State)
Regular diet (2-6 NA
years of age;
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- 1 [micro]g/g
Mexico border (0)
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide < 20 [micro]g/L
formulators
Nonexposed < 20 [micro]g/L
Duncan and Griffith Citrus sprayers 250 [micro]g/L
1985 (h) Citrus harvesters 60 [micro]g/L
Griffith and Duncan 1985 Citrus sprayers 240 [micro]g/L
Citrus harvesters 60 [micro]g/L
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator NA
1989 (j)
Drevenkar et al. Orchard sprayers NA
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control NA
operators
Aprea et al. 1997 (b,c) Vineyard sprayers NA
Vineyard leaf thinners NA
Controls NA
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls NA
Occupational NA
exposures
Lin et al. 2002 (m) Farmers NA
preexposure
Farmers NA
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion NA
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning NA
Chlorovrifos ooisonino NA
Study Study population DMAP
Incidental or community-based measures
Griffith and Duncan General U.S. NA
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults NA
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in 27%
farm families > 25 [micro]g/L
Aprea et al. 2000 (b) Italian children NA
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period NA
Control period NA
Hardt and Angerer 2000 German adults NA
Lu et al. 2000 (e) Reference children 60 mg/L
(central WA) (10 mg/L)
Applicator children NA
Farm children 70 mg/L
(50 mg/L)
0'Rourke et al. 2000 (d) U.S.-Mexico border NA
CDC 2001 (b) General U.S- NA
(NHANES 1999)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age NA
6-13 years of age NA
14-19 years of age NA
[greater than or equal NA
to] 20 years of age
Lu et al. 2001 Children (2-5 years 190
of age, Seattle, WA) nmol/L
(110)
Mills and Zahm 2001 Adult farmworkers NA
Farm children NA
Curl et al. 2002 (b) Agricultural workers 130
nmol/L
Workers' children 90
nmol/L
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months 96
nmol/L
(70)
Nonspray months 72
nmol/L
(60)
(61)
Royster et al. 2002 Toddlers in NA
agricultural
region of CA
2nd visit NA
Castorina et al. 2003 Pregnant women NA
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 40
years of age; nmol/L
WA State)
Regular diet (2-6 340
years of age; nmol/L
WA State) (170)
Shalat et al. 2003 (c,f) Children at U.S.- NA
Mexico border
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide NA
formulators
Nonexposed NA
Duncan and Griffith Citrus sprayers NA
1985 (h) Citrus harvesters NA
Griffith and Duncan 1985 Citrus sprayers NA
Citrus harvesters NA
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator NA
1989 (j)
Drevenkar et al. Orchard sprayers NA
1991 (c)
Aprea et al. 1994 Controls 145.4
(b,c,k) nmol/g
(143.1)
Applicator women 555.6
with rubber gloves nmol/g
and masks (768)
Applicator women 654.4
with waterproof nmol/g
cotton gloves and (611.5)
masks
Applicator women 326.3
with cotton gloves nmol/g
and masks (385.5)
Applicator women 614.0
with cotton gloves nmol/g
(657.5)
Men with no 3568.4
protective wear nmol/g
(3,227)
Takamiya 1994 Pest control NA
operators
Aprea et al. 1997 (b,c) Vineyard sprayers NA
Vineyard leaf thinners NA
Controls NA
Aprea et al. 1999 (b) Greenhouse workers
Basal 183
nmol/g
Reentry day 2 245
nmol/g
Reentry day 4 174
nmol/g
Reentry day 6 354
nmol/g
Controls 103
nmol/g
Cocker et al. 2002 (c,l) Controls 195 nmol/g
(141)
Occupational 292 nmol/g
exposures (132)
Lin et al. 2002 (m) Farmers NA
preexposure
Farmers NA
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion NA
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning NA
Chlorovrifos ooisonino NA
Study Study population DEAP
Incidental or community-based measures
Griffith and Duncan General U.S. NA
1985 (a) (NHANES II:
1976-1980)
Aprea et al. 1996 (b,c) Italian adults NA
Loewenherz et al. 1997 Reference children NA
(0-6 years, WA
State)
Applicator children NA
Children living NA
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in 10%
farm families > 25 [micro]g/L
Aprea et al. 2000 (b) Italian children NA
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period NA
Control period NA
Hardt and Angerer 2000 German adults NA
Lu et al. 2000 (e) Reference children NA
(central WA)
Applicator children NA
Farm children NA
0'Rourke et al. 2000 (d) U.S.-Mexico border NA
CDC 2001 (b) General U.S.- NA
(NHANES 1999)
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age NA
6-13 years of age NA
14-19 years of age NA
[greater than or equal NA
to] 20 years of age
Lu et al. 2001 Children (2-5 years 50
of age, Seattle, WA) nmol/L
(40)
Mills and Zahm 2001 Adult farmworkers NA
Farm children NA
Curl et al. 2002 (b) Agricultural workers 60
nmol/L
Workers' children 60
nmol/L
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months 49
nmol/L
(40)
Nonspray months 35
nmol/L
(40)
Royster et al. 2002 Toddlers in NA
agricultural
region of CA
2nd visit NA
Castorina et al. 2003 Pregnant women NA
(Salinas, CA)
Curl et al. 2003b (b) Organic diet (2-6 20
years of age; nmol/L
WA State)
Regular diet (2-6 30
years of age; nmol/L
WA State) (20)
Shalat et al. 2003 (c,f) Children at U.S.- NA
Mexico border
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide NA
formulators
Nonexposed NA
Duncan and Griffith Citrus sprayers NA
1985 (h) Citrus harvesters NA
Griffith and Duncan 1985 Citrus sprayers NA
Citrus harvesters NA
Franklin et al. 1986 (i) Canadian applicators NA
Guthion-dosed NA
volunteers (dermal
500-6,000 [micro]g)
Fenske and Leffingwell Malathion applicator NA
1989 (j)
Drevenkar et al. Orchard sprayers NA
1991 (c)
Aprea et al. 1994 Controls NA
(b,c,k)
Applicator women NA
with rubber gloves
and masks
Applicator women NA
with waterproof
cotton gloves and
masks
Applicator women NA
with cotton gloves
and masks
Applicator women NA
with cotton gloves
Men with no NA
protective wear
Takamiya 1994 Pest control NA
operators
Aprea et al. 1997 (b,c) Vineyard sprayers NA
Vineyard leaf thinners NA
Controls NA
Aprea et al. 1999 (b) Greenhouse workers
Basal NA
Reentry day 2 NA
Reentry day 4 NA
Reentry day 6 NA
Controls NA
Cocker et al. 2002 (c,l) Controls
Occupational
exposures
Lin et al. 2002 (m) Farmers NA
preexposure
Farmers NA
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion NA
poisoning
Richter et al. 1992 Residents of NA
diazinon-
contaminated home
After cleanup NA
Davies and Peterson 1997 Parathion poisoning NA
Chlorovrifos ooisonino NA
Study Study population Findings
Incidental or community-based measures
Griffith and Duncan General U.S. Low frequency
1985 (a) (NHANES II: of detection
1976-1980)
Aprea et al. 1996 (b,c) Italian adults Frequent
detection
Loewenherz et al. 1997 Reference children Higher levels in
(0-6 years, WA applicator
State) children
Applicator children and children
living close
Children living to orchards
< 200 ft of orchard
Azaroff 1999 (d) Nonfieldworkers in Adult exposures
farm families associated
with child
exposures
Aprea et al. 2000 (b) Italian children Higher levels in
children
Garcia et al. 2000 (a) Adults and teenagers in rice-growing
region
Spray period No appreciable
Control period increase in
DAPS after
spraying; no
association of
DAPS with
symptoms
Hardt and Angerer 2000 German adults Frequent
detection
Lu et al. 2000 (e) Reference children Higher levels in
(central WA) applicator
Applicator children children
Farm children
0'Rourke et al. 2000 (d) U.S.-Mexico border Levels above a
reference
population
CDC 2001 (b) General U.S.- Frequent
(NHANES 1999) detection
Heudorf and Angerer 2001 Germans in former U.S. military
housing
0-5 years of age Higher levels in
children
6-13 years of age
14-19 years of age
[greater than or equal
to] 20 years of age
Lu et al. 2001 Children (2-5 years Residential
of age, Seattle, WA) pesticide use
associated
with DAPS
Mills and Zahm 2001 Adult farmworkers Infrequent
Farm children detection
Curl et al. 2002 (b) Agricultural workers Children of
farmers have
measureable
Workers' children DAP levels;
dust azinphos-
methyl levels
predictive of
urinary DAP
Koch et al. 2002 (b) Agricultural children 2-5 years of age
Spray months Increased DAP
levels during
spraying
months
Nonspray months
Royster et al. 2002 Toddlers in Proximity to
agricultural field not
region of CA associated
with DAPS
2nd visit
Castorina et al. 2003 Pregnant women Some calculated
(Salinas, CA) doses above
U.S. EPA
benchmark
dose/100
Curl et al. 2003b (b) Organic diet (2-6 Lower DMAP
years of age; levels with
WA State) organic diets
Regular diet (2-6
years of age;
WA State)
Shalat et al. 2003 (c,f) Children at U.S.- Higher levels
Mexico border
Occupational exposure measures
Shafik et al. 1973 (g) FL pesticide Differences in
formulators DAPS between
Nonexposed exposed and
nonexposed
Duncan and Griffith Citrus sprayers Measurable
1985 (h) Citrus harvesters levels
Griffith and Duncan 1985 Citrus sprayers More frequent
Citrus harvesters detection
among
sprayers,
higher levels
among
harvesters
Franklin et al. 1986 (i) Canadian applicators Metabolite
Guthion-dosed measurements
volunteers (dermal more reliable
500-6,000 [micro]g) and accurate
than dermal
patch
Fenske and Leffingwell Malathion applicator Measureable
1989 (j) levels
Drevenkar et al. Orchard sprayers DAP levels are
1991 (c) sensitive
indicators
of exposure
Aprea et al. 1994 Controls Applicators had
(b,c,k) increased DAP
levels; using
Applicator women no protective
with rubber gloves equipment
and masks increased
Applicator women levels
with waterproof
cotton gloves and
masks
Applicator women
with cotton gloves
and masks
Applicator women
with cotton gloves
Men with no
protective wear
Takamiya 1994 Pest control Daily
operators fluctuations
in levels
Aprea et al. 1997 (b,c) Vineyard sprayers Higher levels in
Vineyard leaf thinners vineyard
Controls sprayers and
thinners
Aprea et al. 1999 (b) Greenhouse workers
Basal No significant
difference in
Reentry day 2 DAPS among
workers in
Reentry day 4 days following
application or
Reentry day 6 between
Controls workers and
controls
Cocker et al. 2002 (c,l) Controls Nonoccupatio-
nally exposed
Occupational have
exposures measurable
levels,
differences
only in
distribution
tails
Lin et al. 2002 (m) Farmers Measurable
preexposure differences
Farmers after exposure
postexposure
Poisoning or contamination measures
Bradway and Shafik 1977 Nonfatal malathion High levels, no
poisoning death
Richter et al. 1992 Residents of Decontamination
diazinon- of home
contaminated home dramatically
After cleanup reduced DEP
levels
Davies and Peterson 1997 Parathion poisoning High levels
Chlorovrifos ooisonino
NA, not applicable. Concentrations shown are mean values unless
otherwise indicated; median concentrations are shown in parentheses,
when available. Units are either [micro]g/L or [micro]g/g creatinine
for individual metabolites and nmol/L or [micro]mol/g creatinine for
summed metabolites. Where noted, conversions to common units were
made.
(a) Mean value of detectable values. (b) GM. (c) Values presented in
citation converted to common units. (d) Only values given in citation
were percentages of values above analytic LODs. LODs are given in the
table as the value following the "<" sign. (e) Values expressed as
azinphos-methyl equivalents. (f) Values calculated from raw data.
(g) Values estimated from ranges given in citation. (h) Values
estimated from charts and/or graphs. (i) Values calculated from
total amounts excreted over 2 or 3 days assuming 1,000 mL urine
excreted per day. (j) Maximum value observed. (k) n represents
number of serial urine samples. Number of control subjects was 99,
and number of subjects for each exposure group was 2, 2, 2, 5, and
1, respectively. (l) Value given is a composite value summing all
DAP metabolites together. (m) Metabolite concentrations not
reported for all subjects.
Table 8. Frequencies of detection (%) of each DAP metabolite among
general population-based studies.
Study LOD Participants
Murphy et al. 1983 20 [micro]g/L NHANES II
(1976-1980)
5,976 adults
and children
Aprea et al. 1996 ~1 [micro]g/L 124 adults
(< 10 nmol/L)
Aprea et al. 2000 2-3 [micro]g/L 195 children
Hardt and Angerer 2000 1 [micro]g/L 54 adults
(5 [micro]g/L DMP)
Heudorf and Angerer 2001 1 [micro]g/L 1,146 adults,
(5 [micro]g/L DMP) adolescents,
and children
CDC 2001 (a) 0.01-0.58 [micro]g/L 703 adults,
adolescents,
and children
NHANES 1999-2000 0.01-0.58 [micro]g/L 1,949 adults,
adolescents,
and children
Study Country DMP DMTP DMDTP
Murphy et al. 1983 USA 12 6 < 1
Aprea et al. 1996 Italy 87 99 48
Aprea et al. 2000 Italy 96 94 34
Hardt and Angerer 2000 Germany 96 100 89
Heudorf and Angerer 2001 Germany 79 87 32
CDC 2001 (a) USA 83 84 72
NHANES 1999-2000 USA 53 64 53
Study DEP DETP DEDTP
Murphy et al. 1983 7 6 < 1
Aprea et al. 1996 82 73 7
Aprea et al. 2000 75 48 12
Hardt and Angerer 2000 94 46 2
Heudorf and Angerer 2001 78 45 2
CDC 2001 (a) 99 99 99
NHANES 1999-2000 71 53 56
(a) Nonweighted frequencies of detection.
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Committee on Pesticides in the Diets of Infants and Children. 1993. Pesticides in the Diets of Infants and Children. Washington, DC:National Academy Press. O'Rourke MK, Lizardi PS, Bogan SP, Freeman NC, Aguirre A, Saint CG. 2000. Pesticide exposure and creatinine variation among young children. J Expo Anal Environ Epidemiol 10:672-681. Richter ED, Kowalski M, Leventhal A, Grauer F, Marzouk J, Brenner S, et al. 1992. Illness and excretion of organophosphate metabolites four months after household pest extermination. Arch Environ Health 47:135-138. Royster MO, Hilborn ED, Barr D, Carty CL, Bhoney S, Walsh D. 2002. A pilot study of global positioning system/geographical information system measurement of residential proximity to agricultural fields and urinary organophosphate metabolite concentrations in toddlers. J Expo Anal Environ Epidemiol 12:433-440. Shafik T, Bradway DE, Enos HF, Yobs AR. 1973, Gas-liquid chromatographic analysis of alkyl phosphate metabolites in urine. J Agric Food Chem 21:625-629. Shalat SL, Donnelly KC, Freeman NC, Calvin JA, Ramesh S, Jimenez M, et al. 2003, Nondietary ingestion of pesticides by children in an agricultural community on the US/Mexico border: preliminary results. J Expo Anal Environ Epidemiol 13:42-50. Takamiya K. 1994. Monitoring of urinary alkyl phosphates in pest control operators exposed to various organophosphorus insecticides. Bull Environ Contain Toxicol 52:190-195. U.S. EPA. 1991. EPA's Pesticide Programs. Washington, DC:U.S. Environmental Protection Agency. --. 2003. Organophosphate Pesticides. Available: http://www.epa.gov/pesticides/op/[accessed 5 June 2003]. Westgard JO. 2002. Basic QC Practices: Training in Statistical Quality Control for Health Care Laboratories. Madison, WI:Westgard QC, Inc. Whitmore RW, Kelly JE, Reading PL, 2003. National Home and Garden Pesticide Survey: Final Report, Vol 1. RTI/5100. 17001F. Research Triangle Park, NC:Research Triangle Institute. Whyatt RM, Barr DB. 2001. Measurement of organophosphate metabolites in postpartum meconium as a potential biomarker of prenatal exposure: a validation study. Environ Health Perspect 109:417-420. Wilson NK, Chuang JC, Lyu C, Menton R, Morgan MK. 2003, Aggregate exposures of nine preschool children to persistent organic pollutants at day care and at home. J Expo Anal Environ Epidemiol 13:187-202. Dana B. Barr, (1) Roberto Bravo, (1) Gayanga Weerasekera, (1) Lisa M. Caltabiano, (1) Ralph D. Whitehead, Jr., (1) Anders O. Olsson, (1) Samuel P. Caudill, (1) Susan E. Schober, (2) James L. Pirkle, (1) Eric J. Sampson, (1) Richard J. Jackson, (1) and Larry L. Needham (1) (1) National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; (2) National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland, USA Address correspondence to D.B. Barr, Centers for Disease Control and Prevention, 4770 Buford Highway NE, Mailstop F-17, Atlanta, GA 30341 USA. Telephone: (770) 488-7886. Fax: (770) 488-0142. E-mail: dbarr@cdc.gov We thank the people at the National Center for Health Statistics (NCHS) and Westat who were responsible for planning and conducting the National Health and Nutrition Examination Study (NHANES), especially B. Lewis, C. Johnson, B. Lindstrom, A. Jeffries, and C. Humbertson. We thank E. Gunter and C. Pfeiffer for managing the National Center for Environmental Health's involvement in NHANES and for serving as liaisons with NCHS, and C. Fernandez for technical assistance. We also thank the Fairview University Medical Center for providing creatinine measurements. The authors declare they have no competing financial interests. Received 6 June 2003; accepted 4 November 2003. |
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