Final Report: A longitudinal assessment study of human exposure to pesticides due to variations of dietary consumption patterns

EPA Grant Number: R832244
Title: A longitudinal assessment study of human exposure to pesticides due to variations of dietary consumption patterns
Investigators: Sarnat, Jeremy , Lu, Chensheng (Alex)
Institution: Emory University
EPA Project Officer: Klieforth, Barbara I
Project Period: February 1, 2005 through January 31, 2009
Project Amount: $1,883,248
RFA: Aggregate Exposure Assessment: Longitudinal Surveys of Human Exposure - Related Behavior (2003) RFA Text |  Recipients Lists
Research Category: Health , Health Effects

Objective:

The primary objective of this study is to determine how variations in diets contribute to pesticide exposure longitudinally among individuals living in metro Atlanta, GA, area stratified by age and ethnic background. A secondary objective is to develop and pilot a novel survey device to record and transmit dietary consumption data from study participants remotely.

Summary/Accomplishments (Outputs/Outcomes):

The first deliverable outcome from this study is the establishment of a stratified probability-sampled cohort (Metro Atlanta Cohort, MAC) of 500 individuals based on gender, age and ethnicity using U.S. Census 2000 data, who lived in Fulton, Gwinnett or DeKalb counties in the state of Georgia. The participants in this cohort would agree to participate in this longitudinal study, if they were selected. We then randomly selected 60 of the 500 individuals from the cohort to participate in the research study. The MAC cohort identification and recruitment was done by the A.L. Burruss Institute of Public Service at Kennesaw State University in Kennesaw, GA. Of the 60 individuals confirmed to participate in the study, 53 individuals actually attended the training sessions, signed consent forms, and agreed to participate in the study.
 
In each study month, participants choose a study week (6 consecutive days beginning on a Sunday) in which to record their daily dietary consumption (including both the types and quantity of food) via the Internet Data Logger (iDL, see full description in section 2) and to collect the first and last urine voids of the day. At the participant’s convenience, one day of their study week is chosen as their “duplicate diet day.” On this day ONLY, if the participant consumes any food or drink item that is derived from fruits or vegetables, the participant collects duplicate portions of these items. At the end of the longitudinal sample collection, seven of the 53 participants have withdrawn from the study. Among those seven participants, three moved out of the study area and four withdrew for personal reasons. We ended this study with 46 participants.
 
We have collected 988 composite food samples throughout the 12-month sampling period, and analyzed for pesticide residues using the analytical method that is published in the Journal of AOAC (see Publication #4). This multi-residue method for the analysis of OPs and pyrethroid pesticides in fresh produce was developed aiming at levels down to 1.0 µg/kg (ppb) using a modification of the QuEChERS (quick, easy, cheap, effective, rugged, and safe) procedure. This analytical method was used in the analysis of all food samples collected in this study.
 
The second deliverable outcome from this study is the development of the Internet Data Logger (iDL). Because diet has been considered as the major exposure pathway for pesticides, we have developed a Web-based questionnaire system, the internet Data Logger (iDL), in order to facilitate the collection of detailed self-recording of standardized daily dietary consumption in a longitudinal manner. An iDL prototype optimized for hand-held devices was first tested in the ongoing Children’s Pesticide Exposure Study (CPES) in Atlanta, GA, in which 15 consecutive days of dietary consumption information were recorded by 11 children or their parents and transmitted to a server via broadband wireless internet connection, and later improved to be used in this study. Participants spent an average of 4 minutes to enter a meal into iDL and approximately 75% of meals were entered into iDL on the same day of consumption. The development of iDL represents a novel and pioneering tool, which integrates dietary data collection, transmission, and management in a real-time and automated manner. iDL provides the needed flexibility and mobility for research focused on collecting not only dietary consumption data but also other time-sensitive behavior data. We have demonstrated that iDL can be deployed to collect long-term dietary consumption information in a population-based study, though future modifications/enhancements will undoubtedly improve its usability and application. The details of the iDL protocol can be found in Publication #1.
 
The third deliverable outcome from this study is the collection of 4,032 personal-day dietary consumption data from the study. Since characterizing dietary consumption patterns is critical to dietary pesticide exposure assessment, we used those daily dietary consumption data to compare consumption patterns between adults (age 18-60) in the Metro Atlanta Cohort (MAC), a longitudinal study of pesticide exposure among Atlanta residents, and U.S. National Health and Nutrition Examination Survey (NHANES) adults (Publication #7). We focused on foods commonly eaten by U.S. adults and foods likely to contain OP and pyrethroid pesticide residues. MAC participants provided consumption data for 6 days per month for 1 year using a Web-based data collection tool. We defined “percent eaters” as the percent of participants who reported eating a particular food in 24 hours. We computed the NHANES weighted percent eaters and 95% confidence limits (CLs) using the 24-hr dietary recall data. We calculated the MAC percent eaters for each sampling day and the percent of days this number fell below, within, or above the NHANES 95% CLs. We also re-sampled the MAC percent eaters across sampling days to explore whether the resulting distribution resembled the NHANES estimate, and used the Kruskal-Wallis Test to evaluate whether season affected the number of MAC eaters of a particular food on a given sampling day. In general, across all sampling days, a greater proportion of MAC participants reported eating banana, broccoli, cream, grapes, lettuce, onion, peach, pear, peas, strawberries, string beans and tomatoes than the national estimate, while the proportion of apple, spinach, catsup and white bread/roll eaters was similar and the proportion of milk drinkers lower. Season predicted the number of MAC peach and strawberry eaters but not other foods. The data illustrate how a higher proportion of Atlanta adults may eat certain foods (e.g., peaches in summer or strawberries in spring) than the national average depending on season or other factors. An exposure assessment that ignored this difference could underestimate dietary pesticide intakes.
 
Prior to this analysis, we recognized that different study designs and their respective sampling methodology utilized to estimate food consumption patterns may significantly alter the parameter estimates and the variability in the values obtained. We then conducted a study to investigate the impacts of study design on overall estimates of dietary intake by applying the temporal sampling characteristics used in cross-sectional approaches, as in The Continuing Survey of Food for Intakes by Individuals (CSFII), to food consumption data collected in a longitudinal manner via a bootstrap sampling technique (Publication #2). We examined the precision of time-averaged dietary intake estimates under various sampling schemes and explored the contribution of seasonality toward the dietary patterns. A comparison between the estimates of food consumption obtained from the bootstrap replicates and the longitudinal study estimates indicate that variability is significantly decreased when employing a longitudinal study design. Moreover, both between and within-subject variability decreases when individuals are followed over an increasing number of days. Finally, within the longitudinal study cohort, we observed a seasonal component to dietary intake for fruits and grains. Our findings suggest that longitudinal dietary surveys offer substantial improvements for exposure assessment compared to a standard cross-sectional design.
 
The fourth deliverable outcome from this study is a new finding using specific gravity, which reflects the solute concentrations in the urine, instead of urinary creatinine levels to correct the variations of urinary outputs (Publication #3). We compared the appropriateness of urinary creatinine and urinary specific gravity as factors for correcting morning and evening spot urine samples collected from the study participants for a total of 41 days in four different seasons in two linear mixed-effects models fitting with age, sex, season and sample collection time (morning/evening) as predictors with specific gravity and creatinine as dependent variables. Specific gravity was significantly associated with the sample collection time (p < 0.001) with morning samples higher than evening samples. Creatinine was significantly associated with season (p < 0.05), sample collection time (p < 0.0001), and age (p < 0.0001). Creatinine levels were higher during the summer compared to the other seasons, higher in the morning compared to the evening, and higher with increases in participant’s age. Therefore, we concluded that by normalizing the spot urine samples using creatinine would inadvertently introduce bias to the data analysis. Whereas using specific gravity to correct for variable urinary output would be more robust. Additionally, measuring specific gravity is relatively easy, does not require the use of chemicals, and the results are available instantaneously.
 
The fifth deliverable outcome from this study is the development of the physiologically-based pharmacokinetic (PBPK) models (Publication #6). We recognized that, despite the availability of pesticide exposure data, the link between exposure and the absorbed dose has yet to be clearly established due to the inability of converting exposure measurements to the dose matrices, and therefore, hinders the progress of assessing OP-related health effects. Therefore, we conducted a pilot study to evaluate the use of a PBPK model for applying aggregate exposure inputs and estimating absorbed dose consistent with using OP urinary biomarkers. We established a PBPK model to allow data input for three concurrent exposure scenarios; bolus ingestion for meals, inhalation and rate ingestion for non-dietary oral exposures and the model outcomes were used to interpret urinary levels of 3,5,6-trichloro-2-pyridinol (TCPY), the specific metabolite for chlorpyrifos. We found that a majority of the model simulations grossly underestimate children’s aggregate exposures to chlorpyrifos. The inability of the PBPK model to interpret urinary TCPY biomarker data is likely due to the misrepresentation of the dietary exposure as measured in the 24-hour duplicate diets. However, when the exposure scenario involved dietary ingestion of chlorpyrifos, as measured in the 24-hour duplicate diets, the PBPK/ERDEM seems to predict the exposure reasonably well. Since it is likely that people are being exposed to multiple OPs simultaneously and predominantly through dietary intake, effort should be devoted to improve the dietary OP pesticide assessment for PBPK application, as well as the quality of biomarker data so the absorbed OP pesticide dose can be estimated using an inverse pharmacokinetic approach.
 
In parallel to the PBPK model development, we have illustrated the development of a simple pharmacokinetic (SPK) model aiming to estimate the absorbed chlorpyrifos doses using urinary biomarker data, 3,5,6-trichlorpyridinol as the model input. The effectiveness of the SPK model in the pesticide risk assessment was evaluated by comparing dose estimates using different urinary composite data. The dose estimates results from the first morning voids appeared to be lower then but not significantly different to those using before bedtime, lunch or dinner voids. We found similar trends for dose estimates using three different urinary composite data. However, the dose estimates using the SPK model for individuals were significantly higher than those from the conventional PBPK modeling using aggregate environmental measurements of chlorpyrifos as the model inputs. The use of urinary data in the SPK model intuitively provided a plausible alternative to the conventional PBPK model in reconstructing the absorbed chlorpyrifos dose. A manuscript (Publication #8) describing this work has just been accepted (December 2011) for publication in the Journal of Toxicology.
 
These two PBPK models will be useful tools in future data analysis once the urinary biomarker data are available.
 
The last deliverable outcome from this study at present is our continuing collaboration with EPA scientists (Drs. Zartarian V. Xue J. and McCurdy T.) from ORD/NERL in supporting their work on the SHEDS residential and dietary modeling development. Our current plan is to share the data that we have collected from the MAC study and to support the Office of Research and Development/National Exposure Research Laboratory's effort in developing the SHEDS’ residential pesticide exposure model. The SHEDS model development is being subjected to the EPA Scientific Advisory Panel review since June 2010.
 
Since the MAC study is the first undertaking to investigate the relationship between dietary consumption pattern and the total pesticide exposures in the longitudinal manner and at the population-level, we are generating a great number of samples and data that merit further analyses. Our ongoing efforts to further analyzing samples/data collected from the MAC study will contribute significantly to the dietary pesticide exposure and risk assessment. Those efforts include:
  1. The analysis of urinary biomarkers for OP and pyrethroid pesticides. We have collected approximately 7,200 spot urine samples from the MAC study and are in the process of analyzing the composite urine samples at Emory University, led by Dr. Dana Barr. Those urinary biomarker data will be critical not only to validate the accuracy of estimated dietary pesticide intakes but also to be used for calculating absorbed pesticide dose in the pharmacokinetic model as well. We anticipate completing the laboratory activities by 2012.
  2. In parallel to the development of PBPK model, we are developing a deterministic model for estimating dietary pesticide intakes based on the consumption and pesticide residues in/on the foods. This work is the extension of the work that is included in the Publication #7. A manuscript is currently being reviewed by the internal reviewers before the submission to a peer-review journal.

Conclusions:

The most significant outcome from this study is that longitudinal dietary surveys offer substantial improvements for dietary pesticide exposure assessment compared to the standard cross-sectional design. The data illustrated that a higher proportion of Atlanta adults may eat certain foods (e.g., peaches in summer or strawberries in spring) than the national average, depending on season or other factors, which has significant implication for dietary pesticide intakes. This is because most of the seasonal fresh produce often contain pesticide residues. The longitudinal dataset would allow us to calculate the within and between-subject variations that are essential for making sound statistical inferences. The Internet Data Logger (iDL) has made the collection of longitudinal dietary consumption data in the population-based studies possible.
 
In preparation of the availability of urinary biomarker data, we have developed several statistical models to further analyze the data for the purpose of estimating dietary pesticide intakes at the individuals, as well as the population levels. Two of the models are physiologically based pharmacokinetic approaches in which the absorbed pesticide doses could be estimated. The other deterministic model relies on dietary consumption patterns and pesticide residue data in order to simulate the absorbed pesticide doses. Either one of the approaches has been used sporadically; however, there is not yet an effort to compare the accuracy among those models. The data generated from the MAC study would allow accomplishing this work.
 
In conclusion, we have completed the MAC study fulfilling the study objectives, and generated fruitful datasets that would allow future analyses in relation to dietary consumption patterns and pesticide intakes at the population-based level.


Journal Articles on this Report : 9 Displayed | Download in RIS Format

Other project views: All 19 publications 9 publications in selected types All 9 journal articles
Type Citation Project Document Sources
Journal Article Givens ML, Lu C, Bartell SM, Pearson MA. Estimating dietary consumption patterns among children:a comparison between cross-sectional and longitudinal study designs. Environmental Research 2007;103(3):325-330. R832244 (Final)
R829364 (Final)
  • Abstract from PubMed
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  • Abstract: ScienceDirect-Abstract
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  • Journal Article Lu C, Pearson M, Renker S, Myerburg S, Farino C. A novel system for collecting longitudinal self-reported dietary consumption information:the internet data logger (iDL). Journal of Exposure Science and Environmental Epidemiology 2006;16(5):427-433. R832244 (Final)
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  • Abstract: Nature Publishing-Abstract
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  • Journal Article Lu C, Holbrook CM, Andres LM. The implications of using a physiologically based pharmacokinetic (PBPK) model for pesticide risk assessment. Environmental Health Perspectives 2010;118(1):125-130. R832244 (Final)
    R829364 (Final)
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  • Journal Article Lu C, Andres LM. Reconstructing organophosphorus pesticide doses using the reversed dosimetry approach in a simple physiologically-based pharmacokinetic model. Journal of Toxicology 2012;2012:131854, doi:10.1155/2012/131854. R832244 (Final)
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  • Abstract: Journal of Toxicology-Abstract
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  • Journal Article Pearson MA, Lu C, Schmotzer BJ, Waller LA, Riederer AM. Evaluation of physiological measures for correcting variation in urinary output: implications for assessing environmental chemical exposure in children. Journal of Exposure Science and Environmental Epidemiology 2009;19(3):336-342. R832244 (Final)
    R829364 (Final)
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  • Journal Article Riederer AM, Pearson MA, Lu C. Comparison of food consumption frequencies among NHANES and CPES children: implications for dietary pesticide exposure and risk assessment. Journal of Exposure Science and Environmental Epidemiology 2010;20(7):602-614. R832244 (Final)
    R829364 (Final)
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  • Journal Article Riederer AM, Pearson MA, Lu C. Dietary patterns among the Metro Atlanta Cohort:implications for population-based longitudinal dietary pesticide exposure and risk assessment. Journal of Exposure Science and Environmental Epidemiology 2011;21(2):142-149. R832244 (Final)
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  • Journal Article Riederer AM, Lu C. Measured versus simulated dietary pesticide intakes in children. Food Additives & Contaminants:Part A 2012;29(12):1922-1937. R832244 (Final)
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  • Journal Article Schenck F, Wong J, Lu C, Li J, Holcomb JR, Mitchell LM. Multiresidue analysis of 102 organophosphorus pesticides in produce at parts-per billion levels using a modified QuEChERS method and gas chromatography with pulsed flame photometric detection. Journal of AOAC International 2009;92(2):561-573. R832244 (Final)
    R829364 (Final)
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  • Supplemental Keywords:

    dietary consumption, iDL, longitudinal study, random subject recruitment, PBPK model, saliva, duplicate diets, Health, Scientific Discipline, ENVIRONMENTAL MANAGEMENT, HUMAN HEALTH, Environmental Chemistry, Health Risk Assessment, Exposure, Risk Assessments, Biochemistry, Biology, Risk Assessment, human activities, long term exposure, pesticides, micro environmental influences, food consumption habits, human exposure, dietary exposure, household study, exposure assessment

    Progress and Final Reports:

    Original Abstract
  • 2005
  • 2006
  • 2007