Characterizing exposures to nonpersistent pesticides during pregnancy and early childhood in the national children's study: a review of monitoring and measurement methodologies.
Pesticide use is widespread in the United States. A billion pounds or more of conventional pesticides are used annually, and 85% of households store at least one pesticide in their homes (Adgate et al. 2000; Kiely et al. 2004). Approximately 78% of conventional pesticide use is for agriculture, 10% is used in the home and garden, and the remainder is for government, commercial building, and industrial use. Recent biologic monitoring studies indicate that pesticide exposures are ubiquitous, including among women of childbearing age, pregnant women, children, and fetuses (Adgate et al. 2001; Barr et al. 2004; Berkowitz et al. 2003; Bradman et al. 2003; Lu et al. 2000; Whyatt and Barr 2001; Whyatt et al. 2003). To test the hypothesis that exposures to nonpersistent pesticides in utero and postnatally increase the risk of poor performance on neurobehavioral and cognitive examinations, the National Children's Study (NCS) will need to characterize exposures to a broad array of pesticides. The Exposure to Chemical Agents and Development and Behavior 2002 Interworking Group to the NCS, for example, has recommended that this hypothesis focus on current-use neurotoxic insecticides, including organophosphates (OPs), carbamates, pyrethroids, and nicotinoids, and additionally consider other current-use pesticides.
Exposure assessment will be challenging. Nonpersistent pesticides do not accumulate in the body and are generally excreted within hours and days, often via water-soluble metabolites in urine. Biologic exposure markers tend to reflect low-level, transient exposures that are highly variable. Further, the pesticides often degrade rapidly in the ambient environment. Although persistence in the indoor environment appears longer (Gurunathan et al. 1998; Lewis et al. 1994; Whyatt et al. 2004a), indoor levels can be highly variable depending on use patterns. Pesticide exposures can also vary by season (Berkowitz et al. 2003; Whyatt et al. 2003), and exposures can occur through multiple pathways and routes. Diet may be a significant source for some children (Clayton et al. 2003). Dermal exposure and non-intentional ingestion as well as inhalation may all be important routes for pesticides used in the home (Clayton et al. 2003; Fenske et al. 1990; Gurunathan et al. 1998; Lewis et al. 1994; Pang et al. 2002; Whitmore et al. 1994; Whyatt et al. 2003). In addition, effects of the pesticides may depend on the developmental stage when exposure occurs (Slotkin 1999). Experimental data for OPs indicate that the developing brain could be vulnerable to exposures from early embryonic life into childhood (Eskenazi et al. 1999; Garcia et al. 2003; Slotkin 1999). Thus, sampling to characterize exposure will need to be intensive and multimedia and will require repeat assessments during pregnancy and early childhood. A combination of environmental and biologic monitoring, as well as collection of questionnaire data, will likely be involved.
Tables 1 and 2 present the sampling framework proposed by the Exposure to Chemical Agents Working Group of the NCS for assessing exposures to nonpersistent pesticides. Details on the NCS and the role of the Exposure to Chemical Agents Work Group are provided in the accompanying article by Needham et al. (2005). A review of monitoring and measurement methods for assessing pesticide exposure is detailed below. Barr et al. (2005a) provide an additional overview of biologic monitoring.
Biomonitoring has the advantage over environmental monitoring of providing integrating dosimeters summing exposures from all routes and may more accurately reflect the dose to the target tissue. However, biologic half-lives of nonpersistent pesticides are short, and, thus, biomarkers generally provide only transient dosimeters. Therefore, repeat sampling designs will be necessary to characterize exposure.
Urinary monitoring. The measurement of pesticide metabolites in urine offers advantages over other potential exposure biomarkers. Urine is easy and noninvasive to collect, and laboratory methods are available to measure many different pesticide- and class-specific metabolites. Collection from adults is straightforward, and pediatric urine bags can be used with very young children. In one study approximately 90% of 6-month-old infants provided samples during assessments (Fenske et al. 2005). However, urine is an unregulated body fluid and varies from void to void in volume and in the concentration of endogenous and exogenous chemicals (Barr et al. 2005b; Wessels et al. 2003). This may not be true for very young children (e.g., < 12 months) because they feed and urinate frequently, but variability in urinary dilution has not been evaluated for this age group. Creatinine adjustment of urinary metabolites has been the standard method for accounting for urine dilution. However, urinary creatinine levels vary by age, sex, race/ethnicity, and body mass index (Barr et al. 2005b). Adjustments of urinary pesticide levels by creatinine may not be appropriate, therefore, in pregnant women and children. A recent study suggests that for multiple regression analyses in health outcome studies, the analyte concentration unadjusted for creatinine should be included in the model, with urinary creatinine added as a separate independent variable (Barr et al. 2005b).
Spot urine samples are easiest to collect, but no studies have assessed whether single or serial spot urine samples can be used to classify daily or chronic pesticide exposures. Several recent studies indicate that pesticide metabolites in children's spot urine samples exhibit high intraindividual variability (Adgate et al. 2001; Koch et al. 2002). In addition, analyses have not been conducted to evaluate whether 24-hr urine samples can be used to classify chronic exposures. It is important to note that a number of urinary validation studies are under way and should be published within the next 2 years. One recent study suggests that first morning void samples may more accurately represent total daily exposure (Kissel et al. 2005). Existing literature evaluating spot versus 24-hr urine samples for nutrients, renal function measures, and some toxicants is mixed (Boeniger et al. 1993; Chitalia et al. 2001; Evans et al. 2000; Hinwood et al. 2002; Kawasaki et al. 1982; Kieler et al. 2003; Lee et al. 1996; Luft et al. 1983; Neithardt et al. 2002; Tsai et al. 1991; Woods et al. 1998).
An additional concern that has recently been raised about urinary biomarkers is that the metabolites in urine may reflect exposure to the metabolites themselves in the environment rather than to the parent compound (Duggan et al. 2003; Wilson et al. 2003). For example, 3,5,6-trichloro-2-pyridinol (TCPy), the specific metabolite for chlorpyrifos, and several dialkyl phosphates, the class-specific metabolites for many OPs, have been found in food samples (Lu et al. 2005; Wilson et al. 2003).
Blood monitoring. Blood monitoring has advantages over urinary measurements in that the parent compound, instead of a metabolite, can be directly monitored (Barr et al. 2002). Pesticide concentrations in blood may more accurately reflect the absorbed dose and the dose available to the target tissue because the measured dose has not yet been eliminated from the body. Whyatt et al. (2004b) recently showed a significant inverse association between chlorpyrifos levels in umbilical cord blood and both birth weight and length, whereas no association was seen between chlorpyrifos in maternal personal air samples measured during pregnancy and either parameter of fetal growth. These results suggest that the biomarker may better reflect exposure from all routes and the amount of insecticides absorbed by the mother as well as the amount of the absorbed dose that has been transferred to the developing fetus (Fenske et al. 2005). Further, unlike urinary levels, no corrections for dilution are necessary when quantifying contaminate levels in blood (Barr et al. 2002). Additionally, it has recently been hypothesized that blood levels may provide a better dosimeter than urinary levels for steady-state exposures (Needham 2005). However, this hypothesis has yet to be validated. The Centers for Disease Control and Prevention (CDC) has developed a sensitive and accurate analytical method for quantifying 29 contemporary-use pesticides in human serum or plasma (Barr et al. 2002). However, laboratory methods are not available for many OPs and other pesticides in blood, including many without specific- or class-specific metabolites in urine. Finally, blood is invasive to collect, although collection can be timed to coincide with medically scheduled blood collections, such as during the pregnancy glucose tolerance test (at 26 weeks gestational age), delivery, and during 12- and 24-month lead screens (Eskenazi et al. 2003; Fenske et al. 2005).
Other biologic monitoring. Laboratory methods are also under development for pesticides in saliva, meconium, and amniotic fluid, although validated methods are available for only a few compounds. Pesticides in saliva should reflect blood plasma levels (depending on the protein-binding capacity) and therefore recent exposure (Lu et al. 1997, 1998). Current saliva collection methods, which use a cotton sponge, could pose a choking hazard to very young children. Meconium, the first bowel void of the newborn, is a concentrated mixture of swallowed amniotic fluid, cells, bile, and other materials and likely accumulates in the third trimester. Measurement of pesticides in meconium could provide an integrated dosimeter for assessment of fetal exposure in the third trimester (Whyatt and Barr 2001). However, this hypothesis has not been validated. Measurement of pesticide metabolites in amniotic fluid is feasible (Bradman et al. 2003), but amniocentesis poses risks to the fetus and therefore can be conducted only when medically indicated. Thus, population-wide sampling is not possible.
Few data are available on levels of nonpersistent pesticides in breast milk. Many nonpersistent pesticides are soluble in water and therefore may partition to the water fraction of breast milk. Furthermore, the log of the octanol--water coefficient (log [K.sub.ow])--a measure of fat solubility--suggests that some nonpersistent OPs such as malathion (log [K.sub.ow] = 4.5) could partition into the lipid fraction of breast milk. Parathion, malathion, fenchlorphos, and chlorpyrifos have been detected in breast milk in studies from central Asia and India (Lederman 1996; Sanghi et al. 2003). Fonofos and diazinon have been detected in cows' milk or butter fat after acute exposure (Cook and Carson 1985; Spradbery and Tozer 1996). These data suggest that OP and possibly other nonpersistent pesticides may be found in breast milk, although available data are extremely limited. The CDC and the Center for Children's Environmental Health at the University of California, Berkeley, are conducting a study to develop laboratory methods to measure nonpersistent pesticides in human breast milk. Results for several OPs, carbamates, pyrethroids, phthalates, fungicides, and dicarboximides are promising. Numerous research studies indicate that persistent organic pollutants [e.g., 1,1,1-trichloro-2-(o-chlorophenyl)-2,2(p-chlorophenyl)ethane (DDT), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers] bioaccumulate in fat and are transferred to breast milk, thereby exposing breast-feeding infants (Landrigan et al. 2002).
Measurements of pesticides in environmental media can be used to augment biomonitoring and, additionally, can provide information about routes of exposure. In cases when no biomarker is available, the environmental measure may provide the only dosimeter of exposure. For example, no laboratory methods are available for measuring either the parent compound or chemical-specific metabolite of the OP oxydemeton methyl in biologic media.
Air monitoring. Many pesticides are semi-volatile (Lewis 2001; Lewis et al. 2001) and are readily detectable in indoor and personal air samples. These include the OPs and carbamate insecticides; many of the older organochlorine compounds; herbicides such as alachlor, atrazine, 2,4-dichlorophenoxyacetic acid (2,4-D) and dicamba; and several fungicides (e.g., folpet and o-phenylphenol) (Geno et al. 1995; Hsu et al. 1988). The pyrethroids are less volatile, and some of the newer insecticides (e.g., abamectin) are basically nonvolatile. Air sampling may thus not be the best protocol for these less volatile compounds; however, both semi- and nonvolatile pesticides can be resuspended into air on particles by human and pet activity (Lewis et al. 2001; Nishioka et al. 1999, 2001). Pesticides can reach indoor air as a result of volatilization off of treated surfaces within the home or from pesticides tracked into the house from outdoor uses or from occupational take-home exposures (Lewis et al. 2001; Lu et al. 2000; Nishioka et al. 2001; Simcox et al. 1995). There have been numerous prior studies of pesticide levels in indoor air (Clayton et al. 2003; Esteban et al. 1996; Fenske et al. 1990; Lewis et al. 1994, 2001; Pang et al. 2002; Whitmore et al. 1994) and personal air (Clayton et al. 2003; Whitmore et al. 1994; Whyatt et al. 2002, 2003). Indoor air sampling has been conducted over hours to weeks at flow rates ranging from 0.5 to 4 L/min. Sampler height needs to be considered, as pesticide air concentrations may vary with height, being greatest near the floor after indoor application (Fenske et al. 1991; Lewis et al. 1994). Because of participant burden, personal air samples have generally been collected over shorter time periods (24-48 hr) at the higher flow rates (e.g., 4 L/min). However, a recent study collected 6-day integrated average personal air samples at a flow rate of 1.25 L/min from 74 children in Minnesota (Clayton et al. 2003; Quackenboss et al. 2000). Pesticide detection limits depend on the analytical technique and amount of air sampled but are generally in the low nanogram per cubic meter range (Clayton et al. 2003; Whitmore et al. 1994; Whyatt et al. 2003).
Prior studies have shown that inhalation exposure to semivolatile pesticides in indoor air can be substantial and may be a primary route of exposure after residential use among homes using insecticides (Fenske et al. 1990; Whitmore et al. 1994; Whyatt et al. 2002, 2003). However, for any given pesticide/ exposure scenario, the primary route of exposure (inhalation vs. ingestion or dermal) will depend both on use patterns and on the volatility of the pesticides. For example, an aggregate exposure assessment of chlorpyrifos found that inhalation exposures accounted for approximately 85% of total daily dose (Pang et al. 2002). Similarly, results from the U.S. Environmental Protection Agency (EPA) Nonoccupational Pesticide Exposure Study indicate that 85% of the total daily exposure of adults to airborne pesticides is from breathing air inside the home (Whitmore et al. 1994). By contrast, a recent assessment of children's exposure to chlorpyrifos, diazinon, malathion, and atrazine determined that ingestion rather than inhalation was the dominant route (Clayton et al. 2003). Indoor air pesticides levels have been shown to be considerably higher than outdoor air levels.
Dust monitoring. Several researchers have concluded that the majority of household pesticides are better detected by dust sampling than by air sampling (Butte and Heinzow 2002; Fenske et al. 2002b; Roberts et al. 1991; Whitmore et al. 1994). Multiple organic chemicals (both persistent and nonpersistent) can be measured in a single house dust sample, and samples without detectable pesticides are rare. For example, laboratory methods are available for measuring pesticides (both semivolatile and nonvolatile), PCBs and other organochlorine compounds, dioxin, dibenzofurans, polycydic aromatic hydrocarbons, and phthalates in house dust (Butte and Heinzow 2002; Chuang et al. 1995; Lewis et al. 1999; Moate et al. 2002; Rudel et al. 2003). Studies designed to characterize children's exposure to pesticides indicate that the largest number of pesticides and the highest concentrations are found in household dust compared with air, soil, and food (Lewis et al. 1994; Simcox et al. 1995). Finally, whereas air levels of semivolatile pesticides decline rapidly after use, residues are more constant in house dust and can still be detected for months or years after use (Lewis et al. 1994; Roinestad et al. 1993; Rudel et al. 2003). Because of hand-to-mouth activities, house dust may be a significant pesticide exposure pathway for young children.
Most prior studies have collected a sample of house dust from carpets or rugs with the high-volume, small-surface HVS-3 sampler (Cascade Stamp Sampling Systems, Bend, OR) (Lewis et al. 1994; Roberts and Dickey 1995; Simcox et al. 1995). Dust has also been collected using other vacuuming devices (Thompson et al. 2003), and several studies have sampled noncarpeted areas, although dust loading levels are much lower. In all cases, the protocols are labor intensive because they require that the sample be collected by the study team. Studies have also collected dust samples by asking the participants themselves to save the bag from a vacuum cleaner (Roinestad et al. 1993). Colt et al. (1998) compared levels of pesticides and other compounds in dust obtained from used vacuum cleaner bags with those collected by the HVS-3 among 15 homes and found reasonably comparable results. This approach has the advantage of relatively low cost of sample collection. However, disadvantages include the fact that participation is limited to those subjects who own a vacuum cleaner. Further, although the protocol allows determination of contaminant concentrations per gram of dust, pesticide loading (amount of pesticide/floor area) cannot be assessed.
A limitation of dust sampling is that the timing of application is not known, and levels in the dust may reflect use months to years before the sampling. Also, dust on hard surfaces may be readily available to transfer to children's skin and result in nondietary ingestion or dermal exposures, whereas dust lodged deeply in carpets may not be available to children. Carpet dust and dust from other surfaces may function as a reservoir for household pesticide contamination, recontaminating surfaces and air after cleaning depending on the physical and chemical properties ("fugacity") of the specific compounds. Additionally, studies on the inter-relationships of environmental and personal exposures can be difficult to interpret.
Wipe samples. Initial attempts to look at direct child exposures have included the use of hand wipes to collect pesticides directly from children's hands. These methods include wiping the child's hand with sterile gauze dressing pads that have been moistened with propanol or asking the child to place his/her hand in a bag containing propanol (Bradman et al. 1997; Geno et al. 1996; Lioy et al. 2000). Gordon et al. (1999) found excellent correlations between chlorpyrifos in indoor air and corresponding dermal wipes but poor correlations between chlorpyrifos in dust and dermal wipes. Another study reported a weak association between concentrations of OP pesticides in house dust, loadings in house dust, and concentration on hands, hand surface area, and urinary levels of OP metabolites (Shalat et al. 2003). However, hand loadings of OP pesticides were more strongly associated with urinary OP metabolite levels. This finding suggests that on a cross-sectional basis, pesticides on hands may be more strongly correlated with exposure biomarkers. On a longitudinal basis, however, the dust measure may provide better classification of potential and actual exposure. Dust wipe samples have also been collected using the Edwards and Lioy (EL) press sampler and the Lioy, Wainman, and Weisel (LWW) surface wipe sampler (Lioy et al. 2000). The EL sampler has been designed to collect surface concentrations of dust and pesticides that are representative of those adhering to the human hand (Edwards and Lioy 1999). A significant correlation was seen between chlorpyrifos levels in EL surface and carpet samplers (Lioy et al. 2000). The LWW sampler has been used to obtained dust samples from smooth surfaces in the home (Lioy et al. 2000). A protocol that is currently being validated involves mailing study participants an alcohol wipe with instruction for wiping dust on the top of a specified doorframe. The sample is then placed in a Ziploc bag and mailed back to the study team. Advantages include low cost of sample collection and low participant burden. However, research is currently ongoing to determine detection limits and detection frequencies using this method. Other techniques include use of clothing dosimeters such as cotton gloves, union suits, and socks, as well as alternative surface wipe techniques, to quantify exposures (Fenske 1993; Lewis 2005).
Dietary sampling. Diet is a potentially significant pathway of exposure to pesticides for children (Clayton et al. 2003; Fenske et al. 2002a; National Academy of Sciences 1993). Numerous studies have detected OP and organochlorine insecticides and herbicides in food, including chlorpyrifos, malathion, dichlorodiphenyldichloroethylene (DDE), diazinon, and atrazine (Clayton et al. 2003; Macintosh et al. 2001; Pang et al. 2002). Market-basket surveys by the U.S. Department of Agriculture (USDA) indicate that most food types contain some pesticide residues (USDA 2002). For example, 65 and 82% of conventionally grown vegetables and fresh fruits tested by the USDA Pesticide Data Program (PDP) from 1994 through 1999 contained one or more pesticide residues (Baker et al. 2002). However, pesticide concentrations vary significantly across foods (Gunderson 1995). Low detection frequencies, combined with highly variable individual diets, make it difficult to estimate individual dietary exposures using food consumption questionnaires (Macintosh et al. 2001). Instead, studies have generally estimated dietary exposures by measuring pesticides in duplicate diet samples, in which study participants prepare and collect duplicate portions of all foods and beverages consumed (Quackenboss et al. 2000; Wilson et al. 2004). These studies are considered the gold standard; however, they are extremely time intensive and costly and place substantial burdens on participants. Duplicate diet studies may also underestimate dietary exposure if study designs do not account for contamination of foods from indoor sources, such as handling of food by children who also contact contaminated surfaces or dust (Melnyk et al. 2000). Finally, duplicate diet studies are valid for the period over which the samples were collected (e.g., 24 hr) but may not reflect chronic exposures. Laboratory methods for food often require extensive cleanup steps to address fatty and nonfatty foods. Some researchers recommend that acidic foods (e.g., fruit) be collected separately from nonacidic foods (e.g., bread), potentially increasing participant burden and the possibility of error.
Questionnaire-based evaluations have also been used to assess dietary exposures. The key questions that these methods address are how much and what types of food are being eaten and what are the pesticide levels in these foods when eaten (after preparation and handling). Questionnaire methods including 24-hr food recall and food-frequency questionnaires, and diaries can be used to estimate the types and amounts of food individuals are eating. This information can then be linked to national food pesticide residue data (e.g., California Department of Pesticide Regulation 2005a; USDA 2005) to estimate the range of individual exposures. Finally, questionnaires can also be used to classify food consumption patterns that relate to exposure (and nutrition). Examples include the timing of the transition in young children from liquid to solid foods (at 4-6 months) and the consequent increase in consumption of potentially contaminated grains or produce. Before 4-6 months, virtually all dietary exposures, if present, will be due to contamination of formula (powder or water) and possibly breast milk (discussed above).
Infant formula. Several studies have investigated pesticide contamination in milk- or soy-based infant formula. In the United States, Gelardi and Mountford (1993) reviewed tests on 2,043 milk-derived samples and 1,141 soy-derived samples by formula manufacturers. Thirty-four target pesticides included OPs, carbamates, herbicides, and several fungicides (National Academy of Sciences 1993) (persistent organic pollutants were not included). No detectable results were reported. All detection limits were < 1.0 ppm, with most detection limits < 0.005 ppm. We did not find any U.S. studies funded by nonindustry sources. In Canada, Newsome et al. (2000) tested six composite milk-based and six composite soy-based formula samples for a wide array of pesticides, including OPs, carbamates, herbicides, and persistent organic compounds (i.e., DDT, etc.). The sampling scheme was designed to represent the Canadian infant diet. No pesticides were detected in these composite samples. Studies in New Zealand, India, and Spain report positive detections for several pesticides, including DDT and derivatives, hexachlorobenzene, hexachlorocyclohexane, heptachlor, aldrin, endrin, azinphos-methyl, pirimiphosmethyl, dimethoate, and malathion. Overall, these studies suggest that pesticide contamination in infant formula in North American and other developed countries is low and unlikely to be a major source of infant exposure.
Drinking water. Drinking water may also be a source of pesticide exposure, particularly in agricultural communities. In the late 1980s the U.S. EPA undertook a nationwide survey of pesticide contamination in groundwater (Nadakavukaren 2000). The study found that 14% of all public and private drinking-water well samples had measurable levels of at least one pesticide. Subsequent analyses showed that nearly one-third of rural wells sampled had pesticide contamination, with aldicarb and the herbicides atrazine and alachlor being the most widespread. Agricultural pesticide use was the main source (Nadakavukaren 2000). The PDP recently initiated monitoring of finished waters at drinking water treatment plants in New York and California states as a pilot program for a nationally representative drinking water assessment program (USDA 2001). New York and California were initially chosen because they represent diverse climate, geology, and land use and are highly populated. In the near future, monitoring sites will be expanded to include Texas, Kansas, and Colorado. The PDP screens for more than 150 pesticides and metabolites, with detection limits in the part-per-trillion range; 297 samples were tested in 2001, the most recent year with published data. Overall, "positive detections were reported in 145 (40%) of the samples"; the detects were primarily of widely used herbicides. Atrazine or its metabolites were detected in 42-60% of the samples tested (concentration range = 5 500 ppt). Simazine was detected in 15% of samples (concentration range = 13-93 ppt). Metolachlor, metolachlor ethanesulfonic acid, or metolachlor oxanilic acid (OA) was detected in 10-50% of samples, with concentrations ranging up to 4,420 ppt (OA). Alachlor or metabolites were detected in 4% of samples. Detection frequencies for other compounds were all below 1%, including bentazon, diazinon, malaoxon, metribuzin, or propanil.
The California Department of Pesticide Regulation monitors surface and well waters statewide. Diazinon, dimethoate, chlorpyrifos, carbaryl, DDE, DDT, diuron, and oxamyl have been detected in surface water (concentration range = 0.1-2.8 [micro]g/L), and 1,2-dichloropropane, 2,4-D, atrazine, dibromochloropropane, ethylene dibromide, heptachlor, simazine, bromacil, diuron, and hexazinone in well waters (California Department of Pesticide Regulation 2005b). Overall, detection frequencies are low (9%, with ultimately 0.5% verified in 2001). Melnyk et al. (1997) tested drinking water in Iowa and North Carolina for 32 pesticides, including OPs, carbamates, herbicides, and organochlorines; none were detected. Zaki et al. (1982) reported aldicarb in 52% of groundwater samples collected in Suffolk County, New York (concentration range up to > 75 [micro]g/L). Little or no pesticides were found in municipal drinking water in the Nonoccupational Pesticide Exposure Study (Whitmore et al. 1994). In summary, available data suggest that widespread contamination of drinking water by herbicides may contribute to chronic exposures in some parts of the United States. Although other compounds have been detected in surface and well waters, available data suggest that contamination is limited to isolated communities or households and does not result in population-wide exposures. Although the core NCS hypotheses do not focus on nonpersistent herbicides, laboratory methods for measuring herbicides in biologic samples are available for future studies of archived material.
Questionnaire Data and Ecologic Analyses
It is unlikely that questionnaires alone will prove adequate data for pesticide exposure classification (Sexton et al. 2003). However, questionnaires can provide an important supplement to environmental and biologic monitoring. For example, results from ongoing studies by the Children's Environmental Health Centers funded by the U.S. EPA and National Institute of Environmental Health Sciences have found that questionnaires are able to provide information about residential use habits but are rarely able to obtain more detailed information on specific chemicals (Fenske et al. 2005). In preliminary analyses of questionnaires administered by the Columbia Center for Children's Environmental Health, women provided a pesticide product name for fewer than half the pest control methods reported to be used in the home during pregnancy and, in particular, were rarely able to identify the pesticide products used by an exterminator (Fenske et al. 2005). Further, pesticide products can have the same brand name but contain different active ingredients, further complicating use of questionnaire data in pesticide exposure assessment. A visual inspection of active ingredients in pesticide products in the home can be used to supplement questionnaire data. Questionnaires can also provide information about exposure-related events in a household that would not be captured by biomonitoring. For example, a short-term exposure related to a single pesticide application, such as a "bomb" fumigant, may not result in a detectable exposure in a biologic sample collected several weeks later. Finally, questionnaires can provide basic information about milestones in child behavior that explain changes in exposure, such as the transition to solid foods noted above or the onset of crawling and walking that may lead to increased dermal contact with their environment.
Geographic information systems (GIS) provide a tool to evaluate information on pesticide use or landscape features to classify exposure. For GIS analyses, pesticide use reporting (PUR) data must be geographically coded. Several states compile data on agricultural pesticide use. In California 100% of all agricultural pesticide use is reported to the state and geocoded to one-square-mile sections based on the Public Lands Survey System (PLSS). In several epidemiologic studies, researchers have then linked these data to residential addresses to classify exposure based on the amount of nearby pesticide use (Bell et al. 2001; Gunier et al. 2001; Reynolds et al. 2002, 2004). In a case-control study of stillbirths, Ihrig et al. (1998) linked residential address to geographically based estimates of arsenic exposure from an agricultural chemical manufacturing facility. This approach could be a model for nested case-control studies within the NCS. Other researchers have used GIS and land-use data to classify residential proximity to croplands as an exposure metric (Ward et al. 2000a, 2000b; Xiang et al. 2000).
Classifying pesticide exposure using these types of ecologic analyses has many limitations. For example, nearby pesticide use does not necessarily result in exposure, and if it does, exposure may vary depending on proximity to a given application (which can vary greatly within a PLSS section), weather conditions, daily activity patterns, and so forth. In a simulation study of exposure misclassification and bias using PUR data, Rull and Ritz (2003) found that accounting for nearby cropping patterns, seasonality, mobility, and other factors was necessary to improve the "spatiotemporal resolution of pesticide exposure models." Researchers in Washington State have found higher pesticide levels in house dust and urinary metabolite levels in children for households living close to fields compared with those living farther away (Lu et al. 2000; Simcox et al. 1995). Other researchers have not found these relationships (Royster et al. 2002). Differences in crop (orchard vs. row crop), pesticide application methods, climate, sampling methods, etc., could explain these findings. Clearly, additional studies are needed to determine whether ecologic exposure measurements are valid for large-scale epidemiologic studies.
Quantifying exposure to nonpersistent pesticides in the NCS will be challenging (Needham et al. 2005). Exposures are likely to be variable, can occur simultaneously from multiple routes (dietary and nonintentional ingestion, inhalation, and dermal absorption), and can vary dramatically within a particular group or across populations depending on use patterns. These circumstances will require intensive sampling and a repeat-measurement design and will likely necessitate use of a combination of both environmental and biologic monitoring supported by questionnaire information. Ozkaynak et al. (2005) provide an overview of the steps necessary in selecting appropriate exposure assessment methods in the NCS. The framework presented in Tables 1 and 2 outlines assessment methods specific for characterizing pesticide exposures for a longitudinal epidemiologic study of neurodevelopmental outcomes in children. Experimental evidence indicates that the window of susceptibility for neurotoxic pesticides is likely during nervous system development (Slotkin 1999). Thus, the prenatal and early postnatal periods are the key critical life stages during which pesticide exposure must be carefully assessed. The initial step in selecting the exposure assessment methods will include an evaluation of whether the exposure at the critical life stage can be reliably estimated using questionnaire data alone or another indirect low-cost, low-burden measure of exposure. In most instances these measurements alone will not provide reliable dosimeters for pesticide exposures and will need to be supplemented by other methods. However, the survey instruments will be useful to assess household information directly related to pesticide exposures, including household practices such as home pesticide use, food consumption trends, address changes, and so forth. Where feasible, GIS and other ecologic methods should be used. At the very least, the latitude and longitude coordinates of each home should be determined for future studies of pesticides or other environmental exposures. It is also important that questionnaires and other indirect exposure measurements be validated against more direct measures (e.g., biologic or environmental monitoring).
In selecting the direct measurements, the researcher must decide whether to collect a biologic or an environmental sample, or some combination of both. Given the complexity of assessing exposure to nonpersistent pesticides, it is likely that both environmental and biologic sampling will be needed for many compounds. It is important to realize, however, that although efforts to assess children's pesticide exposures have increased dramatically in the last decade, most exposure assessment methods are not fully validated for use in an epidemiologic study. Despite these limitations, a strong case can be made for collecting biologic and environmental samples to characterize children's exposure for the NCS. Tables 1 and 2 include the primary media we believe should be collected to assess pesticide exposure: a) urine from mothers and children, b) maternal and child blood with blood collection linked to scheduled medical tests, c) cord blood, and d) air and/or house dust or wipe samples. Meconium, breast milk, and saliva should also be collected and stored for future use. Validation studies are currently in progress that will provide key information about pesticide exposure assessment methods (Bradman et al. 2003; Fenske et al. 2005; Kieszak et al. 2002; Kissel et al. 2005; Whyatt and Barr 2001; Whyatt et al. 2003). Additionally, several birth cohort studies have successfully used blood and urinary metabolite exposure markers to assess relationships between nonpersistent pesticide exposure and adverse health outcomes in newborns (Berkowitz et al. 2004; Eskenazi et al. 2004; Whyatt et al. 2004b). In some cases the findings of these studies are not consistent. However, these studies have demonstrated the feasibility of collecting environmental and biologic samples, including blood and urine, for large cohort studies. Finally, each project has also stored a variety of samples that will ultimately allow replication of each study and direct assessment of key criteria necessary to judge causal relationships. Planning for the NCS should be forward-looking and include resources to bank a variety of sample types to ensure that new or improved laboratory methods can be applied when they become available. Other exposure assessment methods should be considered for specialized exposure or health outcome studies that involve a subset of participants. These methods could include measuring pesticides in duplicate diet or breast milk samples, or other media (reviewed above). Information from new validation studies should be continuously monitored to improve exposure assessment protocols for this long-term prospective study. For example, exploratory studies of semipermeable membranes that absorb pesticides or wipe and settled dust-sampling techniques may provide less expensive strategies to assess exposure (Robertson et al. 2003). Participant incentives should also be carefully chosen to maintain retention and encourage cooperation. For example, some participants could be provided with vacuum samplers to collect house dust. Participant burden will be a key factor to consider when choosing exposure assessment methods. Initial pilot studies for the NCS should determine what is feasible for participants and tailor protocols to accommodate participant needs. Recent birth cohort studies have implemented protocols approximating the sampling framework presented in Tables 1 and 2. These efforts, however, require intensive staff time to collect the information and samples and to maintain retention. They also require a major time commitment by participants and are logistically challenging, especially when different visit types (e.g., prenatal, delivery, child) with different women are occurring simultaneously.
Adgate JL, Barr DB, Clayton CA, Eberly LE, Freeman NC, Lioy PJ, et al. 2001. Measurement of children's exposure to pesticides: analysis of urinary metabolite levels in a probability-based sample. Environ Health Perspect 109:583-590.
Adgate JL, Kukewski A, Stroebel C, Shubat PJ, Morrell S, Quackenboss JJ, et al. 2000. Pesticide storage and use patterns in Minnesota households with children. J Expo Anal Environ Epidemiol 10:159-167.
Baker BP, Benbrook CM, Groth E III, Lutz Benbrook K. 2002. Pesticide residues in conventional, integrated pest management (IPM)-grown and organic foods: insights from three US data sets. Food Addit Contam 19:427-446.
Barr DB, Barr JR, Maggio VL, Whitehead RD, Sadowski MA, Whyatt RM, et al. 2002. A multi-analytic method for the quantification of contemporary pesticides in human serum and plasma using high resolution mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci Appl 778: 99-111.
Barr DB, Bravo R, Weerasekera G, Caltabiano LM, Whiteheard RD, Olsson AO, et al. 2004. Concentrations of diakyl phosphate metabolites of organophosphorus pesticides in the U.S. population. Environ Health Perspect 112:106-200.
Barr DB, Wang RY, Needham LL. 2005. Biological monitoring of exposure to environmental chemicals throughout the life stages: requirements and issues for consideration for the National Children's Study. Environ Health Perspect 113(8):1083-1001.
Barr DB, Wilder LC, Caudill SP, Gonzalez AJ, Needham LL, Pirkle JL. 2005b. Urinary creatinine concentrations in the U.S. populations: implications for urinary biologic monitoring measurements. Environ Health Perspect 113:102-200.
Bell EM, Hertz-Piccioto I, Beaumont JJ. 2001. A case-control study of pesticides and fetal death due to congenital anomalies. Epidemiology 12:148-156.
Berkowitz GS, Obel J, Deych E, Lapinski R, Godbold J, Liu Z, et al. 2003. Exposure to indoor pesticides during pregnancy in a multiethnic, urban cohort. Environ Health Perspect 111:79-84.
Berkowitz GS, Wetmur JB, Birman-Deych E, Obel J, Lapinski RH, Godbold JH, et al. 2004. In utero pesticide exposure, maternal paraoxonase activity, and head circumference. Environ Health Perspect 112:388-391.
Boeniger MF, Lowry LK, Rosenberg J. 1993. Interpretation of urine results used to assess chemical exposure with emphasis on creatinine adjustments: a review. Am Ind Hyg Assoc J 54:615-627.
Bradman A, Barr DB, Claus Henn BG, Drumheller T, Curry C, Eskenazi B. 2003. Measurement of pesticides and other toxicants in amniotic fluid as a potential biomarker of prenatal exposure: a validation study. Environ Health Perspect 111:1782-1789.
Bradman MA, Harnly ME, Draper W, Seidel S, Teran S, Wakeham D, et al. 1997. Pesticide exposures to children from California's Central Valley: results of a pilot study. J Expo Anal Environ Epidemiol 7:217-234.
Butte W, Heinzow B. 2002. Pollutants in house dust as indicators of indoor contamination. Rev Environ Contain Toxicol 175:1-46.
California Department of Pesticide Regulation. 2005a. Residue Monitoring Program. Available: http://www.cdpr.ca.gov/ docs/pstrsmon/rsmonmnu.htm#resimon/ [accessed 3 March 2005].
California Department of Pesticide Regulation. 2005b. Environmental Monitoring Branch. Available: http://www.cdpr.ca.gov/docs/empm/ehap.htm [accessed 3 March 2005].
Chitalia VC, Kothari J, Wells EJ, Livesey JH, Robson RA, Searle M, et al. 2001. Cost-benefit analysis and prediction of 24-hour proteinuria from the spot urine protein-creatinine ratio. Clin Nephrol 55:436-447.
Chuang JC, Callahan PJ, Katona V, Menton RG, Lewsi RG, Wilson NK. 1995. Monitoring methods for polycyclic aromatic hydrocarbons and their distribution in house dust and track-in soil. Environ Sci Technol 29:494-500.
Clayton AC, Pellizzari ED, Whitmore RW, Quackenboss JJ, Adgate J, Sefton K. 2003. Distributions, associations, and partial aggregate exposure of pesticides and polynuclear aromatic hydrocarbons in the Minnesota Children's Pesticide Exposure Study (MNCPES). J Expo Anal Environ Epidemiol 13:100-111.
Colt JS, Zahm SH, Camann DE, Hartge P. 1998. Comparison of pesticides and other compounds in carpet dust samples collected from used vacuum cleaner bags and from a high-volume surface sampler. Environ Health Perspect 109:721-724.
Cook WO, Carson TL. 1985. Fonofos toxicosis and milk residues in dairy cattle. Vet Hum Toxicol 28:281-282.
Duggan A, Charnley D, Chen W, Chukwudebe A, Hawk R, Krieger RI, et al. 2003. Di-atkyl phosphate biomonitoring data: assessing cumulative exposure to organophosphate pesticides. Regul Toxicol Pharmacol 37:382-395.
Edwards RD, Lioy PJ. 1999. The EL sampler: a press sampler for the quantitative estimation of dermal exposure to pesticides in housedust. J Expo Anal Environ Epidemiol 9:521-529.
Eskenazi B, Bradman A, Castorina R. 1999. Exposures of children to organophosphate pesticides and their potential adverse health effects. Environ Health Perspect 107:409-419.
Eskenazi B, Bradman A, Gladstone E, Jaramillo S, Birth K, Holland N. 2003. CHAMACOS, a longitudinal birth cohort study: lessons from the fields. J Children's Health 1:3-27.
Eskenazi B, Harley K, Bradman A, Weltzien E, Jewell NP, Barr DB, et al. 2004. Association of in utero organophosphate pesticide exposure end fetal growth and length of gestation in an agricultural population. Environ Health Perspect 112:1116-1124.
Esteban E, Rubin C, Hill R, Olson D, Pearce K. 1996. Association between indoor residential contamination with methyl parathion and urinary para-nitrophenol. J Expo Anal Environ Epidemiol 6:375-387.
Evans W, Lensmeyer JP, Kirby RS, Malnory ME, Broekhuizen FF. 2000. Two-hour urine collection for evaluating renal function correlates with 24-hour urine collection in pregnant patients. J Matern Fetal Med 9:233-237.
Fenske RA. 1993. Dermal exposure assessment techniques. Ann Occup Hyg 37:686-706.
Fenske RA, Black KG, Elkner KP, Lee CL, Methner MM, Soto R. 1990. Potential exposure and health risks of infants following indoor pesticide applications. Am J Public Health 80:689-693.
Fenske RA, Bradman A, Whyatt RM, Wolff M, Barr DB. 2005. Assessment of children's pesticide exposure: critical sampling and analytical issues for future studies. Environ Health Perspect doi:10.1289/ehp.7674 [Online 24 June 2005].
Fenske RA, Curry PB, Wandelmaier F, Ritter L. 1991. Development of dermal and respiratory sampling procedures for human exposure to pesticides in indoor environments. J Expo Anal Environ Epidemiol 1:11-30.
Fenske RA, Kedan G, Lu C, Fisker-Andersen JA, Curl CL. 2002a. Assessment of organophosphorous pesticide exposures in the diets of preschool children in Washington State. J Expo Anal Environ Epidemiol 12:21-28.
Fenske RA, Lu C, Barr D, Needham L. 2002b. Children's exposure to chlorpyrifos and parathion in an agricultural community in central Washington State. Environ Health Perspect 110:549-553.
Garcia SJ, Seidler FJ, Slotkin TA. 2003. Developmental neurotoxicity elicited by prenatal or postnatal chlorpyrifos exposure: effects on neurospecific proteins indicate changing vulnerabilities. Environ Health Perspect 111:297-304.
Gelardi RC, Mountford MK. 1993. Infant formulas: evidence of the absence of pesticide residues. Regul Toxicol Pharmacol 17:181-192.
Geno PW, Camann DE, Harding HJ, Villalobos K, Lewis RG. 1996. Handwipe sampling and analysis procedure for the measurement of dermal contact with pesticides. Arch Environ Contam Toxicol 30:132-138.
Geno PW, Majumdar TK, Camann DE, Bond AE. 1995. A multiresidue GC/MS method for the determination of pesticides in environmental media. In: Measurement of Toxic and Related Air Pollutants (Tuerst RG, Jauanty RKM, eds). Pittsburgh, PA:Air and Waste Management Association, 531-541.
Gordon SM, Callahan PJ, Nishioka MG, Brinkman MC, O'Rourke MK, Lebowitz MD, et al. 1999. Residential environmental measurements in the national human exposure assessment survey (NHEXAS) pilot study in Arizona: preliminary results for pesticides and VOCs. J Expo Anal Environ Epidemiol 9:456-470.
Gunderson E. 1995. FDA Total Diet Study, July 198G-April 1991, dietary intakes of pesticides, selected elements, and other chemicals. J AOAC Int 78:1353-1363.
Gunier RB, Harnly ME, Reynolds P, Hertz A, Von Behren J. 2001. Agricultural pesticide use in California: pesticide prioritization, use densities, and population distributions for a childhood cancer study. Environ Health Perspect 109:1071-1078.
Gurunathan S, Robson M, Freeman N, Buckley B, Roy A, Meyer A, et al. 1998. Accumulation of chlorpyrifos on residential surfaces and toys accessible to children. Environ Health Perspect 106:9-16.
Hinwood AL, Sim MR, de Klerk N, Drummer O, Gerostamoulos J, Bastone EB. 2002. Are 24-hour urine samples and creatinine adjustment required for analysis of inorganic arsenic in urine in population studies? Environ Res 88:219-224.
Hsu JP, Wheeler HG, Camann DE, Schattenberg HJ, Lewis RG, Bond AE. 1988. Analytical methods for detection of non-occupational exposure to pesticides. J Chromatogr Sci 26:181-189.
Ihrig MM, Shalat SL, Baynes C. 1998. A hospital-based case-control study of stillbirths and environmental exposure to arsenic using an atmospheric dispersion model linked to a geographical information system. Epidemiology 9:290-294.
Kawasaki T, Ueno M, Uezono K, Kawazoe N, Nakamuta S, Ueda K, et al. 1982. Average urinary excretion of sodium in 24 hours can be estimated from a spot-urine specimen. Jpn Circ J 46:948-953.
Kieler H, Zettergren T, Svensson H, Dickman PW, Larsson A. 2003. Assessing urinary albumin excretion in pre-eclamptic women: which sample to use? Br J Obstet Gynaecol 110:12-17.
Kiely T, Donaldson D, Grube A. 2004. Pesticides Industry Sales and Usage 2000 and 2001 Market Estimates. Washington, DC:U.S. Environmental Protection Agency, Office of Pesticide Programs. Available: http:/www.epa.gove/oppbead1/pestsales/index.htm [accessed 10 February 2005].
Kieszak SM, Naeher LP, Rubin CS, Needham LL, Backer L, Barr D, McGeehin M. 2002. Investigation of the relation between self-reported food consumption and household chemical exposures with urinary levels of selected nonpersistent pesticides. J Expo Anal Environ Epidemiol 12:404-408.
Kissel JC, Curl CL, Kedan D, Lu C, Griffith W, Barr DB, et al. 2005. Comparison of organophosphorus pesticide metabolite levels in single and multiple daily urine samples collected from preschool children in Washington State. J Expo Anal Environ Epidemiol 15(2):164-171.
Koch D, Lu C, Fisker-Andersen J, Jolley L, Fenske RA. 2002. Temporal association of children's pesticide exposure and agricultural spraying: report of a longitudinal biological monitoring study. Environ Health Perspect 110:829-833.
Landrigan PJ, Sonawane B, Mattison D, McCally M, Garg A. 2002. Chemical contaminants in breast milk and their impacts on children's health: an overview. Environ Health Perspect 110:A313-A315.
Lederman SA. 1996. Environmental contaminants in breast milk from the central Asian republics. Reprod Toxicol 10:93-104.
Lee E, Park HK, Kim HJ. 1996. Adjustment of urinary mercury in health risk assessment of mercury. J Korean Med Sci 11:319-325.
Lewis RD. 2001. Pesticides. In: Indoor Air Quality (Spengler JD, Samet JM, McCarthy JF, eds). New York:McGraw Hill, 35.1-35.21.
Lewis RG. 2005. Residential post-application exposure monitoring. In: Occupational and Incidental Residential Exposure Assessment (Franklin CA, Worgan JP, eds). Sussex, UK:John Wiley & Sons, 71-128.
Lewis RG, Fortmann RC, Camann DE. 1994. Evaluation of methods for monitoring potential exposure of small children to pesticides in the residential environment. Arch Environ Contain Toxicol 26:37-46.
Lewis RG, Fortune CR, Blanchard FT, Camann DE. 2001. Movement and desposition of two organophosphorus pesticides within a residence after interior and exterior applications. J Air Waste Manag Assoc 51:339-351.
Lewis RG, Fortune CR, Willis RD, Camann DE, Antley JT. 1999. Distribution of pesticides and polycyclic aromatic hydrocarbons in house dust as a function of particle size. Environ Health Perspect 107:721-726.
Lioy PJ, Edwards RD, Freeman N, Gurunathan S, Pellizzari E, Adgate JL, et al. 2000. House dust levels of selected insecticides and a herbicide measured by the EL and LWW samplers and comparisons to hand rinses and urine metabolites. J Expo Anal Environ Epidemiol 10:327-340.
Lu C, Anderson LC, Fenske RA. 1997. Determination of atrazine levels in whole saliva and plasma in rats: potential of salivary monitoring for occupational exposure. J Toxicol Environ Health 50:101-111.
Lu C, Anderson LC, Morgan MS, Fenske RA. 1998. Salivary concentrations of atrazine reflect free atrazine plasma levels in rats. J Toxicol Environ Health 53:283-292.
Lu C, Bravo R, Caltabiano LM, Irish RM, Weerasekera G, Barr DB. 2005. The presence of dialkylphosphates in fresh fruit juices: implications for organophosphate pesticide exposure and risk assessments. J Toxicol Environ Health 68(3):209-227.
Lu C, Fenske RA, Simcox NJ, Kalman D. 2000. Pesticide exposure of children in an agricultural community: evidence of household proximity to farmland and take home exposure pathways. Environ Res 84:290-332.
Luft FC, Sloan RS, Fineberg NS, Free AH. 1983. The utility of overnight urine collections in assessing compliance with a low sodium intake diet. JAMA 249:1764-1768.
MacIntosh DL, Kabiru CW, Ryan PB. 2001. Longitudinal investigation of dietary exposure to selected pesticides. Environ Health Perspect 109:145-150.
Melnyk LJ, Berry MR, Sheldon LS. 1997. Dietary exposure from pesticide application on farms in the Agricultural Health Pilot Study. J Expo Anal Environ Epidemiol 7:61-80.
Melnyk LJ, Berry MR, Sheldon LS, Freeman NC, Pellizzari ED, Kinman RN. 2000. Dietary exposure of children in lead-laden environments. J Expo Anal Environ Epidemiol 10:723-733.
Moate TF, Furia M, Curl C, Muniz JF, Yu J, Fensko RA. 2002. Size exclusion chromatographic cleanup for GC/MS determination of organophosphorus pesticide residues in household and vehicle dust. J AOAC Int 85(1):36-43.
Nadakavukaren A. 2000. Pest and pesticides. In: Our Global Environment: A Health Perspective. Prospect Heights, IL: Waveland Press, 269-316.
National Academy of Sciences. 1993. Pesticides in the Diets of Infants and Children. Washington, DC:National Academy Press.
Needham LL. 2005. Assessing exposure to organophosphorous pesticides by biomonitoring in epidemiologic studies of birth outcomes. Environ Health Perspect 113:494-498.
Needham LL, Ozkaynak H, Whyatt RM, Barr DB, Wang RY, Naeher L, et al. 2005. Exposure assessment in the National Children's Study: Introduction. Environ Health Perspect 113(8):1076-1082.
Neithardt AB, Dooley SL, Borensztajn J. 2002. Prediction of 24-hour protein excretion in pregnancy with a single voided urine protein-to-creatinine ratio. Am J Obstet Gynecol 186:883-886.
Newsome WH, Doucet J, Davies D, Sun WF. 2000. Pesticide residues in the Canadian Market Basket Survey--1992 to 1996. Food Addit Contam 17:847-854.
Nishioka MG, Burkholder HM, Brinkman MC, Lewis RG. 1999. Distribution of 2,4-dichlorophenoxyacetic acid in floor dust throughout homes following homeowner and commercial lawn applications: quantitative effects of children, pets, and shoes. Environ Sci Technol 33:1359-1365.
Nishioka MG, Lewis RG, Brinkman MC, Burkholder HM, Hines CE. 2001. Distribution of 2,4-D in air and on surfaces inside residences after lawn application: comparing exposure estimates from various media for young children. Environ Health Perspect 109:1185-1191.
Ozkaynak H, Whyatt R, Needham LL, Akland G, Quackenboss J. 2005. Exposure assessment implications for design and implementation of the National Children's Study. Environ Health Perspect 113(8):1108-1115.
Pang Y, MacIntosh DL, Camann DE, Ryan PB. 2002. Analysis of aggregate exposure to chlorpyrifos in the NHEXAS-Maryland investigation. Environ Health Perspect 110:235-240.
Quackenboss JJ, Pellizzari ED, Shubat P, Whitmore RW, Adgate JL, Thomas KW, et al. 2000. Design strategy for assessing multi-pathyway exposure for children: the Minesota Children's Pesticide Exposure Study (MNCPES). J Expo Anal Environ Epidemiol 10:145-158.
Reynolds P, Hurley SE, Goldberg DE, Yerabati S, Gunier RB, Hertz A, et al. 2004. Residential proximity to agricultural pesticide use and incidence of breast cancer in the California Teachers Study cohort. Environ Res 96:206-218.
Reynolds P, Von Behren J, Gunier RB, Goldberg DE, Hertz A, Harnly ME. 2002. Childhood cancer and agricultural pesticide use: an ecologic study in California. Environ Health Perspect 110:319-324.
Roberts JW, Budd WT, Ruby MG, Bond AE, Lewis RG, Wiener RW, et al. 1991. Development and filed testing of a high volume sampler for pesticides and toxics in dust. J Expo Anal Environ Epidemiol 1:143-155.
Roberts JW, Dickey P. 1995. Exposure of children to pollutants in house dust and indoor air. Rev Environ Contam Toxicol 143:59-78.
Robertson GL, Hern SC, Rogers KR. 2003. Method studies for the National Children's Study: semipermeable membrane divide (SPMD) [Abstract]. Presented at the National Children's Study Assembly Meeting, 17 December 2003, Atlanta, GA. Available: http://oaspub.epa.gov/eims/xmlreport.display?deid = 75562&z_chk = 2895#top [accessed 3 March 2005].
Roinestad KS, Louis JB, Rosen JD. 1993. Determination of pesticides in indoor air and dust. J AOAC Int 76:1121-1126.
Royster MO, Hilborn ED, Barr D, Carry CL, Rhoney 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 12:433-40.
Rudel RA, Camann DE, Spengler JD, Korn LR, Brody JG. 2003. Phthalates, alkylphenols, pesticides, polybrominated diphenyl ethers, and other endocrine-disrupting compounds in indoor air and dust. Environ Sci Technol 37:4543-4553.
Rull RP, Ritz B. 2003. Historical pesticide exposure in California using pesticide use reports and land-use surveys: an assessment of misclassification error and bias. Environ Health Perspect 111:1582-1589.
Sanghi R, Pillar MK, Jayalekshmi TR, Nair A. 2003. Organochlorine and organophosphorous pesticide residues in breastmilk from Bhopal, Madhya Pradesh, India. Hum Exp Toxicol 22:73-76.
Sexton K, Adgate JL, Eberly LE, Clayton A, Whitmore RW, Pellizzari ED. 2003. Predicting children's short-term exposure to pesticides: results of a questionnaire screening approach. Environ Health Perspect 111:123-128.
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.
Simcox NJ, Fenske RA, Wolz SA, Lee IC, Kalman DA. 1995. Pesticides in household dust and soil: exposure pathways for children of agricultural families. Environ Health Perspect 103:1126-1134.
Slotkin SM. 1999. Developmental cholinotoxicants: nicotine and chlorpyrifos. Environ Health Perspect 107:71-79.
Spradbery JP, Tozer RS. 1996. The efficacy of diazinon impregnated ear tags against buffalo fly and resulting weight gains and diazinon residues in meat and milk. Aust Vet J 73(1):6-10.
Thompson B, Coronado GD, Grossman JE, Puschel K, Solomon CC, Islas I, et al. 2003. Pesticide take-home pathway among children of agricultural workers: study design, methods, and baseline findings. J Occup Environ Med 45:42-53.
Tsai TJ, Chen YM, Hsieh BS, Chen WY. 1991. Comparison between spot urine and overnight urine in the estimation of 24-hour excretion of urine protein, sodium and kallikrein. J Formos Med Assoc 90:755-759.
USDA. 2001. Finished Drinking Water Monitoring Survey. U.S. Department of Agriculture. Available:http://www.ams.usda.gov/science/pdp/water.htm [accessed 3 March 2005].
USDA. 2002. Pesticide Data Program, Summary Calendar Year 2002. Washington, DC:U.S. Department of Agriculture, Agricultural Marketing Service.
USDA. 2005. Pesticide Data Program. U.S. Department of Agriculture. Available: http://www.ams.usda.gov/science/pdp/ [accessed 3 March 2005].
Ward MH, Nuckols JR, Weigel SJ, Maxwell SK, Cantor KP, Miller RS. 2000a. Identifying populations potentially exposed to agricultural pesticides using remote sensing and Geographic Information System. Environ Health Perspect 108:5-12.
Ward MH, Nuckols JR, Weigel SJ, Maxwell SK, Cantor KP, Miller RS. 2000b. Geographic information systems. A new tool in environmental epidemiology [Abstract]. Ann Epidemiol 10:477.
Wessels D, Barr DB, Mendola P. 2003. Use of biomarkers to indicate exposure of children to organophosphate pesticides: implications for a longitudinal study of children's environmental health. Environ Health Perspect 111:1939-1946.
Whitmore R, Immerman FW, Camann DE, Bond AE, Lewis RG, Schaum JL 1994. Non-occupational exposures to pesticides for residents of two U.S. cities. Arch Environ Contam Toxicol 26:47-59.
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 103:417-420.
Whyatt RM, Barr DB, Camann DE, Kinney PL, Barr JR, Andrews HF, et al. 2003. Contemporary-use pesticides in personal air samples during pregnancy and blood samples at delivery among urban minority mothers and newborns. Environ Health Perspect 111:749-756.
Whyatt RM, Camann DE, Cosme Y, Borjas M, Barr DB. 2004a. Persistence of chlorpyrifos and diazinon in the indoor environment following U.S. regulatory action to ban residential use [Abstract]. Presented at the International Society for Exposure Analysis Annual Meeting, 17-21 October 2004, Philadelphia, Pennsylvania.
Whyatt RM, Camann DE, Kinney PL, Reyes A, Ramirez J, Dietrich J, et al. 2002. Pesticide exposure during pregnancy among minority women residing in northern Manhattan and the South Bronx. Environ Health Perspect 110:507-514.
Whyatt RW, Rauh V, Barr DB, Camann DE, Andrews HF, Garfinkel R, et al. 2004b. Prenatal insecticide exposures and birth weight and length among an urban minority cohort. Environ Health Perspect 112:1126-1132.
Wilson NK, Chuang JC, Iachan R, Lyu C, Gordon SM, Morgan MK, et al. 2004. Design and sampling methodology for a large study of preschool children's aggregate exposures to persistent organic pollutants in their everyday environments. J Expo Anal Environ Epidemiol 14:260-274.
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.
Woods JS, Martin MD, Leroux BG. 1998. Validity of spot urine samples as a surrogate measure of 24-hour porphyrin excretion rates. Evaluation of diurnal variations in porphyrin, mercury, and creatinine concentrations among subjects with very low occupational mercury exposure. J Occup Environ Med 40:1090-1101.
Xiang H, Nuckols JR, Stallones L. 2000. A geographic information assessment of birth weight and crop production patterns around mother's residence. Environ Res 82:160-167.
Zaki MH, Moran D, Harris D. 1982. Pesticides in groundwater: the aldicarb story in Suffolk County, NY. Am J Public Health 72:1391-1395.
Asa Bradman (1) and Robin M. Whyatt (2)
(1) Center for Children's Environmental Health Research, School of Public Health, University of California, Berkeley, California, USA;
(2) Columbia Center for Children's Environmental Health, Mailman School of Public Health, Columbia University, New York, New York, USA
This article is part of the mini-monograph "Assessing Exposures to Environmental Agents during the National Children's Study."
Address correspondence to R.M. Whyatt, Joseph L. Mailman School of Public Health, Columbia University, 60 Haven Ave., B-109, New York, NY 10032 USA. Telephone: (646) 459-9609. Fax: (646) 459-9610. E-mail: firstname.lastname@example.org
The authors have contributed equally to the work and are listed alphabetically.
We gratefully acknowledge R. Weldon for her review of pesticides in breast milk. We also thank other members of the Exposure to Chemical Agents Workgroup of the National Children's Study for their input and comments during the preparation of the manuscript.
The National Children's Study provided support for the preparation of the manuscript. A.B. was supported partly by the U.S. Environmental Protection Agency (U.S. EPA) grant R82679, National Institute of Environmental Health Sciences (NIEHS) grant POLES09605, and National Institute for Occupational Safety and Health grant RO1 OH07400. R.M.W was supported partly by NIEHS grants P50 ES09600, 5 RO1 ES08977, RO1 ES111158, and RO1 ES012468 and U.S. EPA grants R827027 and 8260901.
The authors declare they have no competing financial interests.
Received 19 November 2004; accepted 12 May 2005.
Table 1. Recommended preconception, pregnancy, and perinatal sample collection for nonpersistent pesticide analysis. Trimester Samples Preconception First Maternal urine, (a,b) [check] [check] Maternal blood (a,b) Cord blood (a,b) Meconium Colustrum/breast milk (a,e) Maternal saliva (a) [check] [check] Dietary assessment (e,f) Home/personal air sample (a,b,g) [check] Home composite dust/wipe (a,b,g) [check] Other home samples (b,g,h) Special studies Outdoor samples (b, i) Special studies Questionnaire (a) [check] [check] Ecologic analysis (e.g., GIS) (a) [check] [check] Trimester Samples Second Third Maternal urine, (a,b) [check] [check] Maternal blood (a,b) [check] (c,d) Cord blood (a,b) Meconium Colustrum/breast milk (a,e) Maternal saliva (a) [check] [check] Dietary assessment (e,f) [check] Home/personal air sample (a,b,g) [check] Home composite dust/wipe (a,b,g) [check] Other home samples (b,g,h) Special studies Outdoor samples (b, i) Special studies Questionnaire (a) [check] [check] Ecologic analysis (e.g., GIS) (a) [check] [check] Samples Perinatal period Maternal urine, (a,b) [check] Maternal blood (a,b) [check] (d) Cord blood (a,b) [check] (d) Meconium [check] Colustrum/breast milk (a,e) [check] Maternal saliva (a) [check] Dietary assessment (e,f) Home/personal air sample (a,b,g) Home composite dust/wipe (a,b,g) Other home samples (b,g,h) Special studies Outdoor samples (b, i) Special studies Questionnaire (a) [check] Ecologic analysis (e.g., GIS) (a) [check] [check], sample collection recommended. (a) Metrics that have been used in prior epidemiologic studies. (b) Media with existing laboratory methods for likely target pesticides (e.g., urine, dust, air, food). (c) Blood collection should coincide with glucose tolerance test. (d) Blood collection that is normal part of medical care. Blood samples crucial for paraoxonase status and acetylcholinesterase activity. (e) Metrics that are more experimental or costly. (f) Duplicate diet sampling, food frequency questionnaire, or other method (see text). (g) We recommend that air and/or composite dust or wipe samples be collected for each home lived in during pregnancy. Other environmental samples should be considered for special studies of selected participants. (h) For example, clothing dosimeters or hand wipes. (i) For example, ambient air samples in agricultural area (see text). Table 2. Recommended sample collection for nonpersistent pesticide analysis during early childhood. Months Samples 3 6 9 Urine (a,b,c) [check] [check] [check] Blood (a,c,d) Breast milk (a,e) [check] [check] [check] Saliva (e,f) Dietary assessment (e,g) [check] Home air sample (a,c,h) Each home/year Home dust or wipe samples (a,c,h) Each home/year Other home samples (c,h,i) Special studies Outdoor samples (c,j) Special studies Questionnaire (a) [check] Ecologic analysis (e.g., GIS) (a) [check] [check] [check] Months Years Samples 12 18 2 Urine (a,b,c) [check] [check] [check] Blood (a,c,d) [check] [check] Breast milk (a,e) [check] Saliva (e,f) [check] Dietary assessment (e,g) [check] [check] [check] Home air sample (a,c,h) Each home/year Home dust or wipe samples (a,c,h) Each home/year Other home samples (c,h,i) Special studies Outdoor samples (c,j) Special studies Questionnaire (a) [check] [check] [check] Ecologic analysis (e.g., GIS) (a) [check] [check] [check] Years Samples 3 4 5 Urine (a,b,c) [check] [check] [check] Blood (a,c,d) [check] Breast milk (a,e) Saliva (e,f) [check] [check] Dietary assessment (e,g) [check] [check] [check] Home air sample (a,c,h) Each home/year Home dust or wipe samples (a,c,h) Each home/year Other home samples (c,h,i) Special studies Outdoor samples (c,j) Special studies Questionnaire (a) [check] [check] [check] Ecologic analysis (e.g., GIS) (a) [check] [check] [check] [check], sample collection recommended. (a) Metrics that have been used in prior epidemiologic studies. (b) Pediatric urine bag or diaper sample for non-toilet-trained children. If not diaper, spot samples or multiple spots. Methods to measure pesticides in diapers under development. (c) Media with existing laboratory methods for likely target pesticides (e.g., urine, dust, air). (d) Blood collection at young ages should coincide with CDC-recommended lead screen at 12 and 24 months. Ongoing research has also established that blood collection at 4-5 years of age is feasible. (e) Metrics that are more experimental or costly. (f) Choking hazard for saliva collection for children younger than 3 years with current protocol. (g) Duplicate diet sampling, food frequency questionnaire, or other method (see text). (h) We recommend that air and/or composite dust or wipe samples be collected for each home lived in. Other environmental samples should be considered for special studies of selected participants. (i) For example, clothing dosimeter, hand wipe. (j) For example, ambient air samples in agricultural area (see text).
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||Research: Mini-Monograph|
|Author:||Whyatt, Robin M.|
|Publication:||Environmental Health Perspectives|
|Date:||Aug 1, 2005|
|Previous Article:||Biologic monitoring of exposure to environmental chemicals throughout the life stages: requirements and issues for consideration for the National...|
|Next Article:||Effects of environmental agents on the attainment of puberty: considerations when assessing exposure to environmental chemicals in the National...|