Identifying populations potentially exposed to agricultural pesticides using remote sensing and a Geographic Information System

Evaluating the accuracy of satellite-based methods to estimate residential proximity to agricultural crops

BACKGROUND

Epidemiologic investigations increasingly employ remote sensing data to estimate residential proximity to agriculture as a means of approximating individual-level pesticide exposure. Few studies have examined the accuracy of these methods and the implications for exposure misclassification.

OBJECTIVES

Compare metrics of residential proximity to agricultural land between a groundtruth approach and commonly-used satellite-based estimates.

METHODS

We inspected 349 fields and identified crops in current production within a 0.5 km radius of 40 residences in Idaho. We calculated the distance from each home to the nearest agricultural field and the total acreage of agricultural fields within a 0.5 km buffer. We compared these groundtruth estimates to satellite-derived estimates from three widely used datasets: CropScape, the National Land Cover Database (NLCD), and Landsat imagery (using Normalized Difference Vegetation Index thresholds).

RESULTS

We found poor to moderate agreement between the classification of individuals living within 0.5 km of an agricultural field between the groundtruth method and the comparison datasets (53.1-77.6%). All satellite-derived estimates overestimated the acreage of agricultural land within 0.5 km of each home (average = 82.8-148.9%). Using two satellite-derived datasets in conjunction resulted in substantial improvements; specifically, combining CropScape or NLCD with Landsat imagery had the highest percent agreement with the groundtruth data (92.8-93.8% agreement).

SIGNIFICANCE

Residential proximity to agriculture is frequently used as a proxy for pesticide exposure in epidemiologic investigations, and remote sensing-derived datasets are often the only practical means of identifying cultivated land. We found that estimates of agricultural proximity obtained from commonly-used satellite-based datasets are likely to result in exposure misclassification. We propose a novel approach that capitalizes on the complementary strengths of different sources of satellite imagery, and suggest the combined use of one dataset with high temporal resolution (e.g., Landsat imagery) in conjunction with a second dataset that delineates agricultural land use (e.g., CropScape or NLCD).

Modeling historic environmental pollutant exposures and non-Hodgkin lymphoma risk

Environmental exposures to chemicals are suspected risk factors for non-Hodgkin lymphoma (NHL), but few studies have assessed historic environmental risk factors. In this study, we estimated the associations between NHL and 1) historic environmental pollutant emissions from the Risk Screening Environmental Indicators (RSEI) model, which uses a database from the Environmental Protection Agency of toxic release emissions to air, water, and land, and 2) chemical mixtures measured in house dust (groups of PCBs, PAHs, and two mixtures of pesticides) for study participants enrolled in the NCI-SEER population-based case-control study (1998-2000) at four SEER centers - Detroit, Iowa, Los Angeles County, and Seattle. We assigned 11 years of annual temporally-varying historic environmental exposure scores by intersecting residential locations from participants' residential histories with a fine grid from the RSEI model and by performing inverse distance weighting between facilities releasing specific carcinogenic chemicals and residential locations for spatially-precise exposure assignments. We used Bayesian index low-rank kriging multiple membership models to identify important lag times for RSEI scores, cumulative effects of RSEI scores, and specific carcinogenic chemical releases into the environment. We found a significant positive association between RSEI scores and NHL at the maximum time lag of 11 years (OR = 1.17, 95% CI (1.06, 1.32)) and a significant cumulative RSEI score effect (OR = 1.30, 95% CI (1.02, 1.84)) for long-term residents in Detroit, where benzene and trichloroethylene were the most important chemicals driving this association. Additionally, we identified significant inverse associations for two study centers and time lags that did not persist in cumulative exposure models. Large weights for dichloromethane and pentachlorophenol in models of cumulative exposure also support evidence for their association with NHL risk. These results underscore the importance of considering historic and cumulative environmental exposures and using residential histories for diseases with long latency periods such as NHL.

An integrated host-microbiome response to atrazine exposure mediates toxicity in Drosophila

The gut microbiome produces vitamins, nutrients, and neurotransmitters, and helps to modulate the host immune system-and also plays a major role in the metabolism of many exogenous compounds, including drugs and chemical toxicants. However, the extent to which specific microbial species or communities modulate hazard upon exposure to chemicals remains largely opaque. Focusing on the effects of collateral dietary exposure to the widely used herbicide atrazine, we applied integrated omics and phenotypic screening to assess the role of the gut microbiome in modulating host resilience in Drosophila melanogaster. Transcriptional and metabolic responses to these compounds are sex-specific and depend strongly on the presence of the commensal microbiome. Sequencing the genomes of all abundant microbes in the fly gut revealed an enzymatic pathway responsible for atrazine detoxification unique to Acetobacter tropicalis. We find that Acetobacter tropicalis alone, in gnotobiotic animals, is sufficient to rescue increased atrazine toxicity to wild-type, conventionally reared levels. This work points toward the derivation of biotic strategies to improve host resilience to environmental chemical exposures, and illustrates the power of integrative omics to identify pathways responsible for adverse health outcomes.

Association between Pesticides in House Dust and Residential Proximity to Farmland in a Rural Region of Taiwan

Pesticide drift was reported in many international studies, but rarely studied in Taiwan. We conducted a study in a rural region of Taiwan to examine the associations between pesticides in house dust and nearby agricultural areas using geographic information system (GIS). A questionnaire regarding home characteristics and pesticide use, and indoor and outdoor dust samples were collected from 47 rural homes. Dust samples were analyzed for six pesticides, and agricultural land data for GIS analysis were retrieved from a national website. All but prallethrin were frequently detected from indoor dust samples (>50%), and the maximum concentrations were all below 1000 ng/g. Detection frequencies and concentrations of pesticides in outdoor dust samples were even lower than that in indoor dust samples. Only "work involving pesticides" in the questionnaire was significantly associated with four pesticides in house dust (p < 0.05). Carbofuran and tetramethrin in house dust were significantly correlated with rice cultivation area at certain buffer distances (ρ > 0.33, p < 0.05), and chlorpyrifos was found to be associated with abandoned cultivation area, suggesting the occurrence of pesticide drift. Despite the low levels of pesticides in house dust, residents in the rural region should be cautious of pesticide drift from nearby active or abandoned farmlands.

Assessment of residential exposures to agricultural pesticides: A scoping review

The assessment of residential exposure to agricultural pesticides is a major issue for public health, regulatory and management purposes. In recent years, research into this field has developed considerably. The purpose of this scoping review is to provide an overview of scientific literature characterizing residential exposure to agricultural pesticides and to identify potential gaps in this research area. This work was conducted according to the JBI and PRISMA guidelines. Three databases were consulted. At least two experts selected the eligible studies. Our scoping review enabled us to identify 151 articles published between 1988 and 2019 dealing with the assessment of residential exposure to agricultural pesticides. Of these, 98 (64.9%) were epidemiological studies investigating possible links between pesticide exposure and the onset of adverse health effects, principally cancers and reproductive outcomes. They predominantly used Geographic Information Systems and sometimes surveys or interviews to calculate surrogate exposure metrics, the most common being the amounts of pesticides applied or the surface area of crops around the dwelling. Twenty-six (17.2%) were observational measurement studies conducted to quantify levels of pesticide exposure and identify their possible determinants. These studies assessed exposure by measuring pesticides in biological and environmental matrices, mostly in urines and house dust. Finally, we found only eight publications (5.3%) that quantified the risk to human health due to residential exposure for management purposes, in which exposure was mainly determined using probabilistic models. Pesticide exposure appears to be largely correlated with the spatial organization of agriculture activities in a territory. The determinants and routes of exposure remain to be explored to improve the conduct of epidemiological and risk assessment studies and to help prevent future exposures. Improvement could be expected from small-scale studies combining different methods of exposure assessment.

Applications of Space Technologies to Global Health: Scoping Review

Background

Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health.

Objective

The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges.

Methods

We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified.

Results

A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use.

Conclusions

Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

Relative Contributions of Agricultural Drift, Para-Occupational, and Residential Use Exposure Pathways to House Dust Pesticide Concentrations: Meta-Regression of Published Data

BACKGROUND

Increased pesticide concentrations in house dust in agricultural areas have been attributed to several exposure pathways, including agricultural drift, para-occupational, and residential use.

OBJECTIVE

To guide future exposure assessment efforts, we quantified relative contributions of these pathways using meta-regression models of published data on dust pesticide concentrations.

METHODS

From studies in North American agricultural areas published from 1995 to 2015, we abstracted dust pesticide concentrations reported as summary statistics [e.g., geometric means (GM)]. We analyzed these data using mixed-effects meta-regression models that weighted each summary statistic by its inverse variance. Dependent variables were either the log-transformed GM (drift) or the log-transformed ratio of GMs from two groups (para-occupational, residential use).

RESULTS

For the drift pathway, predicted GMs decreased sharply and nonlinearly, with GMs 64% lower in homes 250 m versus 23 m from fields (interquartile range of published data) based on 52 statistics from seven studies. For the para-occupational pathway, GMs were 2.3 times higher [95% confidence interval (CI): 1.5, 3.3; 15 statistics, five studies] in homes of farmers who applied pesticides more recently or frequently versus less recently or frequently. For the residential use pathway, GMs were 1.3 (95% CI: 1.1, 1.4) and 1.5 (95% CI: 1.2, 1.9) times higher in treated versus untreated homes, when the probability that a pesticide was used for the pest treatment was 1-19% and ≥ 20%, respectively (88 statistics, five studies).

CONCLUSION

Our quantification of the relative contributions of pesticide exposure pathways in agricultural populations could improve exposure assessments in epidemiologic studies. The meta-regression models can be updated when additional data become available. Citation: Deziel NC, Beane Freeman LE, Graubard BI, Jones RR, Hoppin JA, Thomas K, Hines CJ, Blair A, Sandler DP, Chen H, Lubin JH, Andreotti G, Alavanja MC, Friesen MC. 2017. Relative contributions of agricultural drift, para-occupational, and residential use exposure pathways to house dust pesticide concentrations: meta-regression of published data. Environ Health Perspect 125:296-305; http://dx.doi.org/10.1289/EHP426.

Passive exposure to agricultural pesticides and risk of childhood leukemia in an Italian community

BACKGROUND

Exposure to pesticides has been suggested as a risk factor for childhood leukemia, but definitive evidence on this relation and the specific pesticides involved is still not clear.

OBJECTIVE

We carried out a population-based case-control study in a Northern Italy community to assess the possible relation between passive exposure to agricultural pesticides and risk of acute childhood leukemia.

METHODS

We assessed passive pesticide exposure of 111 childhood leukemia cases and 444 matched controls by determining density and type of agricultural land use within a 100-m radius buffer around children's homes. We focused on four common crop types, arable, orchard, vineyard and vegetable, characterized by the use of specific pesticides that are potentially involved in childhood induced leukemia. The use of these pesticides was validated within the present study. We computed the odds ratios (OR) of the disease and their 95% confidence intervals (CI) according to type and density of crops around the children's homes, also taking into account traffic pollution and high-voltage power line magnetic field exposure.

RESULTS

Childhood leukemia risk did not increase in relation with any of the crop types with the exception of arable crops, characterized by the use of 2.4-D, MCPA, glyphosate, dicamba, triazine and cypermethrin. The very few children (n=11) residing close to arable crops had an OR for childhood leukemia of 2.04 (95% CI 0.50-8.35), and such excess risk was further enhanced among children aged <5 years.

CONCLUSIONS

Despite the null association with most crop types and the statistical imprecision of the estimates, the increased leukemia risk among children residing close to arable crops indicates the need to further investigate the involvement in disease etiology of passive exposure to herbicides and pyrethroids, though such exposure is unlikely to play a role in the vast majority of cases.

Agricultural crop exposure and risk of childhood cancer: new findings from a case-control study in Spain

Background

Childhood cancer is the main cause of disease-related death in children in Spain. Although little is known about the etiology, environmental factors are potential explanations for a fraction of the cases. Previous studies have shown pesticides to be associated with childhood cancer. The difficulty of collecting personal environmental exposure data is an important limitation; this lack of information about pesticides motivates the development of new methods to subrogate this exposure. We developed a crop exposure index based on geographic information to study the relationship between exposure to different types of crops and risk of childhood tumors.

Methods

We conducted a population-based case–control study of childhood cancer covering 3350 cases and 20,365 controls in two Spanish regions. We used CORINE Land Cover to obtain data about agricultural land use. We created a 1 km buffer around every child and calculated the percentage of crop surface within the buffer (Global Crop Index) for total crops and for individual types of crops. We fitted mixed multiple unconditional logistic regression models by diagnostic group.

Results

We found excess of risk among children living in the proximity of crops. For total crops our results showed excesses of risk for almost all diagnostic groups and increasing risk with increasing crop index value. Analyses by region and individual type of crop also showed excess of risk.

Conclusion

The results suggest that living in the proximity of cultivated land could be a risk factor for several types of cancer in children.

Pesticide exposure and hepatocellular carcinoma risk: A case-control study using a geographic information system (GIS) to link SEER-Medicare and California pesticide data

BACKGROUND

Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is associated with low survival. U.S. studies examining self-reported pesticide exposure in relation to HCC have demonstrated inconclusive results. We aimed to clarify the association between pesticide exposure and HCC by implementing a novel data linkage between Surveillance, Epidemiology, and End Results (SEER)-Medicare and California Pesticide Use Report (PUR) data using a geographic information system (GIS).

METHODS

Controls were frequency-matched to HCC cases diagnosed between 2000 and 2009 in California by year, age, race, sex, and duration of residence in California. Potential confounders were extracted from Medicare claims. From 1974 to 2008, pounds (1 pound represents 0.45 kg) of applied organophosphate, organochlorine, and carbamate pesticides provided in PURs were aggregated to the ZIP Code level using area weighting in a GIS. ZIP Code exposure estimates were linked to subjects using Medicare-provided ZIP Codes to calculate pesticide exposure. Agricultural residents were defined as living in ZIP Codes with a majority area intersecting agricultural land cover according to the 1992, 2001, and 2006 National Land Cover Database (NLCD) rasters. Multivariable conditional logistic regression was used to estimate the association between pesticide exposure and HCC.

RESULTS

Among California residents of agriculturally intensive areas, previous annual ZIP Code-level exposure to over 14.53 kg/km(2) of organochlorine pesticides (75(th) percentile among controls) was associated with an increased risk of HCC after adjusting for liver disease and diabetes (adjusted odds ratio [OR] 1.87, 95% confidence interval [CI] 1.17, 2.99; p=0.0085). ZIP Code-level organochlorines were significantly associated with an increased risk of HCC among males (adjusted OR 2.76, 95% CI 1.58, 4.82; p=0.0004), but not associated with HCC among females (adjusted OR 0.83, 95% CI 0.35, 1.93; p=0.6600) (interaction p=0.0075).

CONCLUSIONS

This is the first epidemiologic study to use GIS-based exposure estimates to study pesticide exposure and HCC. Our results suggest that organochlorine pesticides are associated with an increase in HCC risk among males but not females.

Linking pesticides and human health: a geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.

An evaluation of metrics for assessing maternal exposure to agricultural pesticides

We evaluate the use of three different exposure metrics to estimate maternal agricultural pesticide exposure during pregnancy. Using a geographic information system-based method of pesticide exposure estimation, we combine data on crop density and specific pesticide application amounts/dates to create the three exposure metrics. For illustration purposes, we create each metric for a North Carolina cohort of pregnant women, 2003-2005, and analyze the risk of congenital anomaly development with a focus on metric comparisons. Based on the results, and the need to balance data collection efforts/computational efficiency with accuracy, the metric which estimates total chemical exposure using application dates based on crop-specific earliest planting and latest harvesting information is preferred. Benefits and drawbacks of each metric are discussed and recommendations for extending the analysis to other states are provided.

Studying the impact of early life exposures to pesticides on the risk of testicular germ cell tumors during adulthood (TESTIS project): study protocol

BACKGROUND

The incidence of testicular germ cell tumors (TGCT), the most common cancer in men aged 15 to 45 years, has doubled over the last 30 years in developed countries. Reasons remain unclear but a role of environmental factors, especially during critical periods of development, is strongly suspected. Reliable data on environmental exposure during this critical time period are sparse. Little is known on whether it could be a combined effect of early and later-life exposures.

METHODS/DESIGN

Our research aims to study the association between TGCT risk and pesticide exposures (domestic, occupational and environmental) during critical time periods of development and combined early and later-life exposures. The study design, developed during a 2-year pilot study, is a multicenter case-control study of 500 cases (ascertained through histology) and 1000 fertile/fecund controls recruited through 21 French 'Centres d'Etude et de Conservation des Œufs et de Sperme humain' (CECOS). Trained professional interviewers interview the subjects and their mothers by phone. Using a geographic information system developed and tested for application in this study design, environmental pesticides exposure assessment is based on life-time residential history. Occupational pesticides exposures are assessed by an industrial hygienist based on parents' occupations and tasks. Exposures during the prenatal period, early childhood and puberty are focused. A blood sample is collected from each participant to assess genetic polymorphisms known to be associated with TGCT risk, as well as to explore gene-environment interactions.

DISCUSSION

The results of our study will contribute to better understanding the causes of TGCT and the rapid increase of its incidence. We explore the effect of combined early and later-life pesticides exposure from multiple sources, as well as potential gene-environment interactions that have until now been rarely studied for TGCT. Our design allows future pooled studies and the bio-bank allows additional genetic or toxicological analyses.

Factors associated with self-reported symptoms of acute pesticide poisoning among farmers in northwestern Jamaica

Pesticide poisoning is a major public health concern in developing countries. The authors conducted a population survey among farmers in 3 parishes of northwestern Jamaica to determine the occurrence of acute pesticide poisoning and to identify factors associated with pesticide poisoning. Approximately 16% of 359 farmers who participated in the study reported 1 or more incidents of acute pesticide poisoning within the last 2 years. Only 25% of the farmers reported ever receiving training in pesticide handling or safety. The majority (68%) of farmers who reported pesticide poisoning never sought medical attention for poisoning. The factors found to be associated with pesticide poisoning in this study indicate that implementation of specific intervention strategies and education of farmers is needed in order to improve safe handling, use, and disposal of pesticides and reduce incidents of acute pesticide poisoning.

Using Landsat satellite data to support pesticide exposure assessment in California

BACKGROUND

The recent U.S. Geological Survey policy offering Landsat satellite data at no cost provides researchers new opportunities to explore relationships between environment and health. The purpose of this study was to examine the potential for using Landsat satellite data to support pesticide exposure assessment in California.

METHODS AND RESULTS

We collected a dense time series of 24 Landsat 5 and 7 images spanning the year 2000 for an agricultural region in Fresno County. We intersected the Landsat time series with the California Department of Water Resources (CDWR) land use map and selected field samples to define the phenological characteristics of 17 major crop types or crop groups. We found the frequent overpass of Landsat enabled detection of crop field conditions (e.g., bare soil, vegetated) over most of the year. However, images were limited during the winter months due to cloud cover. Many samples designated as single-cropped in the CDWR map had phenological patterns that represented multi-cropped or non-cropped fields, indicating they may have been misclassified.

CONCLUSIONS

We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

Assessment of a pesticide exposure intensity algorithm in the agricultural health study

The accuracy of the exposure assessment is a critical factor in epidemiological investigations of pesticide exposures and health in agricultural populations. However, few studies have been conducted to evaluate questionnaire-based exposure metrics. The Agricultural Health Study (AHS) is a prospective cohort study of pesticide applicators who provided detailed questionnaire information on their use of specific pesticides. A field study was conducted for a subset of the applicators enrolled in the AHS to assess a pesticide exposure algorithm through comparison of algorithm intensity scores with measured exposures. Pre- and post-application urinary biomarker measurements were made for 2,4-D (n=69) and chlorpyrifos (n=17) applicators. Dermal patch, hand wipe, and personal air samples were also collected. Intensity scores were calculated using information from technician observations and an interviewer-administered questionnaire. Correlations between observer and questionnaire intensity scores were high (Spearman's r=0.92 and 0.84 for 2,4-D and chlorpyrifos, respectively). Intensity scores from questionnaires for individual applications were significantly correlated with post-application urinary concentrations for both 2,4-D (r=0.42, P<0.001) and chlorpyrifos (r=0.53, P=0.035) applicators. Significant correlations were also found between intensity scores and estimated hand loading, estimated body loading, and air concentrations for 2,4-D applicators (r-values 0.28-0.50, P-values<0.025). Correlations between intensity scores and dermal and air measures were generally lower for chlorpyrifos applicators using granular products. A linear regression model indicated that the algorithm factors for individual applications explained 24% of the variability in post-application urinary 2,4-D concentration, which increased to 60% when the pre-application urine concentration was included. The results of the measurements support the use of the algorithm for estimating questionnaire-based exposure intensities in the AHS for liquid pesticide products. Refinement of the algorithm may be possible using the results from this and other measurement studies.

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

Agricultural pesticides and risk of childhood cancers

Agricultural pesticide applications have the potential for significant drift beyond the target spray area and may result in exposure to non-farming residents in surrounding communities. Using geographic information system (GIS) methods, 1778 childhood cancer cases and 1802 controls born in Texas between 1990 and 1998 were assigned probable agricultural pesticide exposure based on proximity of birth residence to crop fields. Multivariate modeling was used to estimate odds ratios and 95% confidence intervals for selected cancers. For most childhood cancers, we found no evidence of elevated risk associated with residential proximity at birth to cropland. There was an overall pattern of increased risk for germ-cell tumors but the odds ratios were based on few number of exposed cases. There was also some indication of increased risk for non-Hodgkin lymphoma (NHL) and Burkitt lymphoma, but point estimates were imprecise and not statistically significant. Previous studies have assessed pesticide exposure primarily based on parental occupational history or household use, while our focus was on agricultural pesticides and so may represent a different array of chemical agents occurring at lower doses.

Spatial modeling of personalized exposure dynamics: the case of pesticide use in small-scale agricultural production landscapes of the developing world

Background

Pesticide poisoning is a global health issue with the largest impacts in the developing countries where residential and small-scale agricultural areas are often integrated and pesticides sprayed manually. To reduce health risks from pesticide exposure approaches for personalized exposure assessment (PEA) are needed. We present a conceptual framework to develop a spatial individual-based model (IBM) prototype for assessing potential exposure of farm-workers conducting small-scale agricultural production, which accounts for a considerable portion of global food crop production. Our approach accounts for dynamics in the contaminant distributions in the environment, as well as patterns of movement and activities performed on an individual level under different safety scenarios. We demonstrate a first prototype using data from a study area in a rural part of Colombia, South America.

Results

Different safety scenarios of PEA were run by including weighting schemes for activities performed under different safety conditions. We examined the sensitivity of individual exposure estimates to varying patterns of pesticide application and varying individual patterns of movement. This resulted in a considerable variation in estimates of magnitude, frequency and duration of exposure over the model runs for each individual as well as between individuals. These findings indicate the influence of patterns of pesticide application, individual spatial patterns of movement as well as safety conditions on personalized exposure in the agricultural production landscape that is the focus of our research.

Conclusion

This approach represents a conceptual framework for developing individual based models to carry out PEA in small-scale agricultural settings in the developing world based on individual patterns of movement, safety conditions, and dynamic contaminant distributions.

The results of our analysis indicate our prototype model is sufficiently sensitive to differentiate and quantify the influence of individual patterns of movement and decision-based pesticide management activities on potential exposure. This approach represents a framework for further understanding the contribution of agricultural pesticide use to exposure in the small-scale agricultural production landscape of many developing countries, and could be useful to evaluate public health intervention strategies to reduce risks to farm-workers and their families. Further research is needed to fully develop an operational version of the model.

Using satellite derived land cover information for a multi-temporal study of self-reported recall of proximity to farmland

Exposure misclassification is a major concern in epidemiologic studies. The potential for misclassification becomes even more problematic when participants are asked to recall historical information. Yet, historical information is important in cancer studies, where latency is long and causative exposures may have occurred years or even decades prior to diagnosis. Even though self-reported proximity to farmland is a commonly used exposure measure, the accuracy of recall is seldom, if ever validated. Geographic Information Systems (GISs) and land cover information derived from satellite imagery can allow researchers to assess the accuracy of this exposure measure, and to quantify the extent and importance of exposure misclassification. As part of a bladder cancer case-control study in Michigan, participants were asked whether they lived on a farm, or within a distance of 1/4, 1/4-1, 1-5, or >5 miles from farmland for each residence over their lifespan. Responses from 531 participants over two time periods--1978 and 2001--were investigated. Self reported proximity to farmland was compared to a "gold standard" derived from Michigan land cover files for the same time periods. Logistic regression and other statistical measures including sensitivity, specificity, and percentage matching were evaluated. In comparing self-reported and land cover-derived proximity to farmland, cases exhibited better agreement than controls in 2001 (adjusted OR=1.74; 95% CI=1.01, 2.99) and worse agreement in 1978, although not significantly (adjusted OR=0.74; 95% CI=0.47, 1.16). When comparing 2001 with 1978, both cases and controls showed better agreement in 2001, but only cases showed a significant difference (adjusted OR=2.36; 95% CI=1.33, 4.18). These differences in agreement may be influenced by differences in educational attainment between cases and controls, although adjustment for education did not diminish the association. Gender, age, number of years at residence, and geocoding accuracy did not influence agreement between the proximity approaches. This study suggests that proximity measures taken from satellite-derived land cover imagery may be useful for assessing proximity to farmland, and it raises some concerns about the use of self-reported proximity to farmland in exposure assessments.

A GIS-based method for household recruitment in a prospective pesticide exposure study

BACKGROUND

Recent advances in GIS technology and remote sensing have provided new opportunities to collect ecologic data on agricultural pesticide exposure. Many pesticide studies have used historical or records-based data on crops and their associated pesticide applications to estimate exposure by measuring residential proximity to agricultural fields. Very few of these studies collected environmental and biological samples from study participants. One of the reasons for this is the cost of identifying participants who reside near study fields and analyzing samples obtained from them. In this paper, we present a cost-effective, GIS-based method for crop field selection and household recruitment in a prospective pesticide exposure study in a remote location. For the most part, our multi-phased approach was carried out in a research facility, but involved two brief episodes of fieldwork for ground truthing purposes. This method was developed for a larger study designed to examine the validity of indirect pesticide exposure estimates by comparing measured exposures in household dust, water and urine with records-based estimates that use crop location, residential proximity and pesticide application data. The study focused on the pesticide atrazine, a broadleaf herbicide used in corn production and one of the most widely-used pesticides in the U.S.

RESULTS

We successfully used a combination of remotely-sensed data, GIS-based methods and fieldwork to select study fields and recruit participants in Illinois, a state with high corn production and heavy atrazine use. Our several-step process consisted of the identification of potential study fields and residential areas using aerial photography; verification of crop patterns and land use via site visits; development of a GIS-based algorithm to define recruitment areas around crop fields; acquisition of geocoded household-level data within each recruitment area from a commercial vendor; and confirmation of final participant household locations via ground truthing. The use of these procedures resulted in a sufficient sample of participants from 14 recruitment areas in seven Illinois counties.

CONCLUSION

One of the challenges in pesticide research is the identification and recruitment of study participants, which is time consuming and costly, especially when the study site is in a remote location. We have demonstrated how GIS-based processes can be used to recruit participants, increase efficiency and enhance accuracy. The method that we used ultimately made it possible to collect biological samples from a specific demographic group within strictly defined exposure areas, with little advance knowledge of the location or population.

Linkage of the California Pesticide Use Reporting Database with spatial land use data for exposure assessment

BACKGROUND

The State of California maintains a comprehensive Pesticide Use Reporting Database (CPUR). The California Department of Water Resources (CDWR) maps all crops in agricultural counties in California about once every 5 years.

OBJECTIVE

We integrated crop maps with CPUR to more accurately locate where pesticides are applied and evaluated the effects for exposure assessment.

METHODS

We mapped 577 residences and used the CPUR and CDWR data to compute two exposure metrics based on putative pesticide use within a 500-m buffer. For the CPUR metric, we assigned pesticide exposure to the residence proportionally for all square-mile Sections that intersected the buffer. For the CDWR metric, we linked CPUR crop-specific pesticide use to crops mapped within the buffer and assigned pesticide exposure. We compared the metrics for six pesticides: simazine, trifluralin (herbicides), dicofol, propargite (insecticides), methyl bromide, and metam sodium (fumigants).

RESULTS

For all six pesticides we found good agreement (88-98%) as to whether the pesticide use was predicted. When we restricted the analysis to residences with reported pesticide use in Sections within 500 m, agreement was greatly reduced (35-58%). The CPUR metric estimates of pesticide use within 500 m were significantly higher than the CDWR metric for all six pesticides.

CONCLUSIONS

Our findings may have important implications for exposure classification in epidemiologic studies of agricultural pesticide use using CPUR. There is a need to conduct environmental and biological measurements to ascertain which, if any, of these metrics best represent exposure.

The crossroads of GIS and health information: a workshop on developing a research agenda to improve cancer control

Cancer control researchers seek to reduce the burden of cancer by studying interventions, their impact in defined populations, and the means by which they can be better used. The first step in cancer control is identifying where the cancer burden is elevated, which suggests locations where interventions are needed. Geographic information systems (GIS) and other spatial analytic methods provide such a solution and thus can play a major role in cancer control. This report presents findings from a workshop held June 16-17, 2005, to bring together experts and stakeholders to address current issues in GIScience and cancer control. A broad range of areas of expertise and interest was represented, including epidemiology, geography, statistics, environmental health, social science, cancer control, cancer registry operations, and cancer advocacy. The goals of this workshop were to build consensus on important policy and research questions, identify roadblocks to future progress in this field, and provide recommendations to overcome these roadblocks.

Agricultural pesticide use and hypospadias in eastern Arkansas

INTRODUCTION

We assessed the relationship between hypospadias and proximity to agricultural pesticide applications using a GIS-based exposure method.

METHODS

We obtained information for 354 cases of hypospadias born between 1998 and 2002 in eastern Arkansas; 727 controls were selected from birth certificates. We classified exposure on pounds of pesticides (estimated by crop type) applied or persisting within 500 m of each subject's home during gestational weeks 6 to 16. We restricted our analyses to 38 pesticides with some evidence of reproductive, developmental, estrogenic, and/or antiandrogenic effects. We estimated timing of pesticide applications using crop phenology and published records.

RESULTS

Gestational age at birth [odds ratio (OR) = 0.91; 95% confidence interval (CI), 0.83-0.99], parity (OR = 0.79; 95% CI, 0.65-0.95), and delaying prenatal care until the third trimester (OR = 4.04; 95% CI, 1.46-11.23) were significantly associated with hypospadias. Risk of hypospadias increased by 8% for every 0.05-pound increase in estimated exposure to diclofop-methyl use (OR = 1.08; 95% CI, 1.01-1.15). Pesticide applications in aggregate (OR = 0.82; 95% CI, 0.70-0.96) and applications of alachlor (OR = 0.56; 95% CI, 0.35-0.89) and permethrin (OR = 0.37; 95% CI, 0.16-0.86) were negatively associated with hypospadias.

CONCLUSIONS

Except for diclofop-methyl, we did not find evidence that estimated exposure to pesticides known to have reproductive, developmental, or endocrine-disrupting effects increases risk of hypospadias. Further research on the potential effects of exposure to diclofop-methyl is recommended.

Individual lifetime exposure to inorganic arsenic using a space-time information system

OBJECTIVES

A space-time information system (STIS) based method is introduced for calculating individual-level estimates of inorganic arsenic exposure over the adult life-course. STIS enables visualization and analysis of space-time data, overcoming some of the constraints inherent to spatial-only Geographic Information System software. The power of this new methodology is demonstrated using data from southeastern Michigan where 8% of the population is exposed to arsenic >10 microg/l (the World Health Organization guideline) in home drinking water.

METHODS

Participants (N=440) are members of a control group in a population-based bladder cancer case-control study in southeastern Michigan and were recruited by phone using random digit dialing. Water samples were collected and analyzed for arsenic at current residence and participants were required to answer questions concerning lifetime mobility history and dietary habits. Inorganic arsenic concentrations were estimated at past residences and workplaces, and in select foods. Fluid and food consumption data were integrated with mobility histories and arsenic concentrations to calculate continuous estimates of inorganic arsenic intake over the adult life-course.

RESULTS

Estimates of continuous arsenic exposure are displayed, making use of both participant age and calendar year as measures of time. Results illustrate considerable temporal variability in individual-level exposure, with 26% of the participants experiencing a change in drinking water arsenic concentration of at least +/-10 microg/l over their adult lives. The average cumulative intake over the adult life-course ranges from 2.53 x 10(4)-1.30 x 10(5) microg, depending on the selected exposure metric.

CONCLUSIONS

The STIS-based exposure assessment method allows for flexible inclusion of different parameters or alternative formulations of those parameters, thus enabling the calculation of different exposure metrics. This flexibility is particularly useful when additional exposure routes are considered, input datasets are updated, or when a scientific consensus does not exist regarding the proper formulation of the exposure metric. These results demonstrate the potential of STIS as a useful tool for calculating continuous estimates of adult lifetime exposure to arsenic or other environmental contaminants for application in exposure and risk assessment.

Potential residential exposure to toxics release inventory chemicals during pregnancy and childhood brain cancer

BACKGROUND

Although the susceptibility of the developing fetus to various chemical exposures is well documented, the role of environmental chemicals in childhood brain cancer etiology is not well understood.

OBJECTIVES

We aimed to evaluate whether mothers of childhood brain cancer cases had greater potential residential exposure to Toxics Release Inventory (TRI) chemicals than control mothers during pregnancy.

METHODS

We included 382 brain cancer cases diagnosed at < 10 years of age from 1993 through 1997 who were identified from four statewide cancer registries. One-to-one matched controls were selected by random-digit dialing. Computer-assisted telephone interviews were conducted. Using residential history of mothers during pregnancy, we measured proximity to TRI facilities and exposure index, including mass and chemicals released. We calculated odds ratios (ORs) and 95% confidence intervals (CIs) using conditional logistic regression to estimate brain cancer risk associated with TRI chemicals.

RESULTS

Increased risk was observed for mothers living within 1 mi of a TRI facility (OR = 1.66 ; 95% CI, 1.11-2.48) and living within 1 mi of a facility releasing carcinogens (OR = 1.72 ; 95% CI, 1.05-2.82) for having children diagnosed with brain cancer before 5 years of age, compared to living > 1 mi from a facility. Taking into account the mass and toxicity of chemical releases, we found a nonsignificant increase in risk (OR = 1.25 ; 95% CI, 0.67-2.34) comparing those with the lowest versus highest exposure index.

CONCLUSIONS

Risk of childhood brain cancers may be associated with living near a TRI facility ; however, this is an exploratory study and further studies are needed.

Proximity to crops and residential exposure to agricultural herbicides in iowa

Rural residents can be exposed to agricultural pesticides through the proximity of their homes to crop fields. Previously, we developed a method to create historical crop maps using a geographic information system. The aim of the present study was to determine whether crop maps are useful for predicting levels of crop herbicides in carpet dust samples from residences. From homes of participants in a case-control study of non-Hodgkin lymphoma in Iowa (1998-2000), we collected vacuum cleaner dust and measured 14 herbicides with high use on corn and soybeans in Iowa. Of 112 homes, 58% of residences had crops within 500 m of their home, an intermediate distance for primary drift from aerial and ground applications. Detection rates for herbicides ranged from 0% for metribuzin and cyanazine to 95% for 2,4-dichlorophenoxyacetic acid. Six herbicides used almost exclusively in agriculture were detected in 28% of homes. Detections and concentrations were highest in homes with an active farmer. Increasing acreage of corn and soybean fields within 750 m of homes was associated with significantly elevated odds of detecting agricultural herbicides compared with homes with no crops within 750 m (adjusted odds ratio per 10 acres = 1.06; 95% confidence interval, 1.02-1.11). Herbicide concentrations also increased significantly with increasing acreage within 750 m. We evaluated the distance of crop fields from the home at < 100, 101-250, 251-500, and 501-750 m. Including the crop buffer distance parameters in the model did not significantly improve the fit compared with a model with total acres within 750 m. Our results indicate that crop maps may be a useful method for estimating levels of herbicides in homes from nearby crop fields.

Characterizing exposures to nonpersistent pesticides during pregnancy and early childhood in the National Children's Study: a review of monitoring and measurement methodologies

The National Children's Study is a proposed longitudinal cohort study to evaluate the relationships between children's health and the environment. Enrollment is estimated to begin in September 2005, and 100,000 children will be followed from preconception or early pregnancy until adulthood. Among multiple health outcomes, the study is proposing to investigate whether pre- and/or postnatal exposures to nonpersistent pesticides increase the risk of poor performance on neurobehavioral and cognitive exams during infancy and early childhood. Characterization of exposures will be challenging. Nonpersistent pesticides include many chemicals with biologic half-lives on the order of hours or days. Exposures can occur through multiple pathways (e.g., food and residential or agriculture pesticide use) and by multiple routes (inhalation, ingestion, dermal). Effects may depend on the developmental stage when exposure occurs. Sequential sampling is likely to be required and may involve a combination of environmental and biologic monitoring as well as collection of questionnaire data. In this article we review measurements that can be used to characterize exposures. These include biologic markers, personal and indoor air sampling techniques, collection of dust, surface and dermal wipe samples, and dietary assessment tools. Criteria for sample selection will necessitate evaluation of the time frame of exposure captured by the measurement in relationship to critical windows of susceptibility, the cost and validity of the measurements, participant burden, and variability in exposure routes across populations and at different age periods.

Assessing spatio-temporal variability of risk surfaces using residential history data in a case control study of breast cancer

BACKGROUND: Most analyses of spatial clustering of disease have been based on either residence at the time of diagnosis or current residence. An underlying assumption in these analyses is that residence can be used as a proxy for environmental exposure. However, exposures earlier in life and not just those in the most recent period may be of significance. In breast cancer, there is accumulating evidence that early life exposures may contribute to risk. We explored spatio-temporal patterns of risk surfaces using data on lifetime residential history in a case control study of breast cancer, and identified elevated areas of risk and areas potentially having more exposure opportunities, defined as risk surfaces in this study. This approach may be more relevant in understanding the environmental etiology of breast cancer, since lifetime cumulative exposures or exposures at critical times may be more strongly associated with risk for breast cancer than exposures from the recent period. RESULTS: A GIS-based exploratory spatial analysis was applied, and spatio-temporal variability of those risk surfaces was evaluated using the standardized difference in density surfaces between cases and controls. The significance of the resulting risk surfaces was tested and reported as p-values. These surfaces were compared for premenopausal and postmenopausal women, and were obtained for each decade, from the 1940s to 1990s. We found strong evidence of clustering of lifetime residence for premenopausal women (for cases relative to controls), and a less strong suggestion of such clustering for postmenopausal women, and identified a substantial degree of temporal variability of the risk surfaces. CONCLUSION: We were able to pinpoint geographic areas with higher risk through exploratory spatial analyses, and to assess temporal variability of the risk surfaces, thus providing a working hypothesis on breast cancer and environmental exposures. Geographic areas with higher case densities need further epidemiologic investigation for potential relationships between lifetime environmental exposures and breast cancer risk. Examination of lifetime residential history provided additional information on geographic areas associated with higher risk; limiting exploration of chronic disease clustering to current residence may neglect important relationships between location and disease.

Current practices in spatial analysis of cancer data: data characteristics and data sources for geographic studies of cancer

The use of spatially referenced data in cancer studies is gaining in prominence, fueled by the development and availability of spatial analytic tools and the broadening recognition of the linkages between geography and health. We provide an overview of some of the unique characteristics of spatial data, followed by an account of the major types and sources of data used in the spatial analysis of cancer, including data from cancer registries, population data, health surveys, environmental data, and remote sensing data. We cite numerous examples of recent studies that have used these data, with a focus on etiological research.

Visualization and exploratory analysis of epidemiologic data using a novel space time information system

Background

Recent years have seen an expansion in the use of Geographic Information Systems (GIS) in environmental health research. In this field GIS can be used to detect disease clustering, to analyze access to hospital emergency care, to predict environmental outbreaks, and to estimate exposure to toxic compounds. Despite these advances the inability of GIS to properly handle temporal information is increasingly recognised as a significant constraint. The effective representation and visualization of both spatial and temporal dimensions therefore is expected to significantly enhance our ability to undertake environmental health research using time-referenced geospatial data. Especially for diseases with long latency periods (such as cancer) the ability to represent, quantify and model individual exposure through time is a critical component of risk estimation. In response to this need a STIS – a Space Time Information System has been developed to visualize and analyze objects simultaneously through space and time.

Results

In this paper we present a "first use" of a STIS in a case-control study of the relationship between arsenic exposure and bladder cancer in south eastern Michigan. Individual arsenic exposure is reconstructed by incorporating spatiotemporal data including residential mobility and drinking water habits. The unique contribution of the STIS is its ability to visualize and analyze residential histories over different temporal scales. Participant information is viewed and statistically analyzed using dynamic views in which values of an attribute change through time. These views include tables, graphs (such as histograms and scatterplots), and maps. In addition, these views can be linked and synchronized for complex data exploration using cartographic brushing, statistical brushing, and animation.

Conclusion

The STIS provides new and powerful ways to visualize and analyze how individual exposure and associated environmental variables change through time. We expect to see innovative space-time methods being utilized in future environmental health research now that the successful "first use" of a STIS in exposure reconstruction has been accomplished.

Using geographic information systems for exposure assessment in environmental epidemiology studies

Geographic information systems (GIS) are being used with increasing frequency in environmental epidemiology studies. Reported applications include locating the study population by geocoding addresses (assigning mapping coordinates), using proximity analysis of contaminant source as a surrogate for exposure, and integrating environmental monitoring data into the analysis of the health outcomes. Although most of these studies have been ecologic in design, some have used GIS in estimating environmental levels of a contaminant at the individual level and to design exposure metrics for use in epidemiologic studies. In this article we discuss fundamentals of three scientific disciplines instrumental to using GIS in exposure assessment for epidemiologic studies: geospatial science, environmental science, and epidemiology. We also explore how a GIS can be used to accomplish several steps in the exposure assessment process. These steps include defining the study population, identifying source and potential routes of exposure, estimating environmental levels of target contaminants, and estimating personal exposures. We present and discuss examples for the first three steps. We discuss potential use of GIS and global positioning systems (GPS) in the last step. On the basis of our findings, we conclude that the use of GIS in exposure assessment for environmental epidemiology studies is not only feasible but can enhance the understanding of the association between contaminants in our environment and disease.

Breast cancer risk and historical exposure to pesticides from wide-area applications assessed with GIS

Pesticides are of interest in etiologic studies of breast cancer because many mimic estrogen, a known breast cancer risk factor, or cause mammary tumors in animals, but most previous studies have been limited by using one-time tissue measurements of residues of only a few pesticides long banned in the United States. As an alternative method to assess historical exposures to banned and current-use pesticides, we used geographic information system (GIS) technology in a population-based case-control study of 1,165 women residing in Cape Cod, Massachusetts, who were diagnosed with breast cancer in 1988-1995 and 1,006 controls. We assessed exposures dating back to 1948 (when DDT was first used there) from pesticides applied for tree pests (e.g., gypsy moths), cranberry bogs, other agriculture, and mosquito control on wetlands. We found no overall pattern of association between pesticide use and breast cancer. We found modest increases in risk associated with aerial application of persistent pesticides on cranberry bogs and less persistent pesticides applied for tree pests or agriculture. Adjusted odds ratios for these exposures were 1.8 or lower, and, with a few exceptions, confidence intervals did not exclude the null. The study is limited by uncertainty about locations of home addresses (particularly before 1980) and unrecorded tree pest and mosquito control events as well as lack of information about exposures during years when women in the study lived off Cape Cod and about women with potentially important early life exposures on Cape Cod who were not included because they moved away.

Historical pesticide exposure in California using pesticide use reports and land-use surveys: an assessment of misclassification error and bias

We used California's Pesticide Use Report (PUR) and land-use survey data to conduct a simulation study evaluating the potential consequences of misclassifying residential exposure from proximity to agricultural pesticide application in health effect studies. We developed a geographic model linking the PUR with crop location data from land-use surveys to assess the impact of exposure misclassification from simpler exposure models based solely on PUR or land-use data. We simulated the random selection of population controls recruited into a hypothetical case-control study within an agricultural region. Using residential parcel data, we derived annual exposure prevalences, sensitivity, and specificity for five pesticides and relied on the PUR plus land-use model as the "gold standard." Based on these estimates, we calculated the attenuation of prespecified true odds ratios (ORs), assuming nondifferential exposure misclassification. True ORs were severely attenuated a) when residential exposure status was based on a larger geographic area yielding higher sensitivity but low specificity for exposure, in contrast to relying on a smaller area and increasing specificity; b) for less frequently applied pesticides; and c) with increasing mobility of residents among the study population. Considerable effect estimate attenuation also occurred when we used residential distance to crops as a proxy for pesticide exposure. Finally, exposure classifications based on annual instead of seasonal summaries of PUR resulted in highly attenuated ORs, especially during seasons when applications of specific pesticides were unlikely to occur. These results underscore the importance of increasing the spatiotemporal resolution of pesticide exposure models to minimize misclassification.

The role of genetic polymorphisms in environmental health

Interest is increasing in the role of variations in the human genome (polymorphisms) in modifying the effect of exposures to environmental health hazards (often referred to as gene-environment interaction), which render some individuals or groups in the population more or less likely to develop disease after exposure. This review is intended for an audience of environmental health practitioners and students and is designed to raise awareness about this rapidly growing field of research by presenting established and novel examples of gene-environment interaction that illustrate the major theme of effect modification. Current data gaps are identified and discussed to illustrate limitations of past research and the need for the application of more robust methods in future research projects. Two primary benefits of incorporating genetics into the existing environmental health research framework are illustrated: a) the ability to detect different levels of risk within the population, and b) greater understanding of etiologic mechanisms. Both offer opportunities for developing new methods of disease prevention. Finally, we describe a basic framework for researchers interested in pursuing health effects research that incorporates genetic polymorphisms.

Environmental pollutants and breast cancer

Breast cancer is the most common cancer in women and the leading cause of cancer death among women 35-54 years of age. Rising incidence, increased risk among migrants to higher risk regions, and poor prediction of individual risk have prompted a search for additional modifiable factors. Risk factors for breast cancer include reproductive characteristics associated with estrogen and other hormones, pharmaceutical hormones, and activities such as alcohol use and lack of exercise that affect hormone levels. As a result, investigation of hormonally active compounds in commercial products and pollution is a priority. Compounds that cause mammary tumors in animals are additional priorities. Animal models provide insight into possible mechanisms for effects of environmental pollutants on breast cancer and identify chemical exposures to target in epidemiologic studies. Although few epidemiologic studies have been conducted for chemical exposures, occupational studies show associations between breast cancer and exposure to certain organic solvents and polycyclic aromatic hydrocarbons (PAHs). Population-based studies have been limited to a few organochlorine compounds and PAHs and have been mostly negative. A variety of challenges in studies of breast cancer and the environment may have contributed to negative findings. Lack of exposure assessment tools and few hypothesis-generating toxicologic studies limit the scope of epidemiologic studies. Issues of timing with respect to latency and periods of breast vulnerability, and individual differences in susceptibility pose other challenges. Substantial work is needed in exposure assessment, toxicology, and susceptibility before we can expect a pay-off from large epidemiologic studies of breast cancer and environment.

A geographic information system for characterizing exposure to Agent Orange and other herbicides in Vietnam

Between 1961 and 1971, U.S. military forces dispersed more than 19 million gallons of phenoxy and other herbicidal agents in the Republic of Vietnam, including more than 12 million gallons of dioxin-contaminated Agent Orange, yet only comparatively limited epidemiologic and environmental research has been carried out on the distribution and health effects of this contamination. As part of a response to a National Academy of Sciences' request for development of exposure methodologies for carrying out epidemiologic research, a conceptual framework for estimating exposure opportunity to herbicides and a geographic information system (GIS) have been developed. The GIS is based on a relational database system that integrates extensive data resources on dispersal of herbicides (e.g., HERBS records of Ranch Hand aircraft flight paths, gallonage, and chemical agent), locations of military units and bases, dynamic movement of combat troops in Vietnam, and locations of civilian population centers. The GIS can provide a variety of proximity counts for exposure to 9,141 herbicide application missions. In addition, the GIS can be used to generate a quantitative exposure opportunity index that accounts for quantity of herbicide sprayed, distance, and environmental decay of a toxic factor such as dioxin, and is flexible enough to permit substitution of other mathematical exposure models by the user. The GIS thus provides a basis for estimation of herbicide exposure for use in large-scale epidemiologic studies. To facilitate widespread use of the GIS, a user-friendly software package was developed to permit researchers to assign exposure opportunity indexes to troops, locations, or individuals.

Time-location analysis for exposure assessment studies of children using a novel global positioning system instrument

Global positioning system (GPS) technology is used widely for business and leisure activities and offers promise for human time-location studies to evaluate potential exposure to environmental contaminants. In this article we describe the development of a novel GPS instrument suitable for tracking the movements of young children. Eleven children in the Seattle area (2-8 years old) wore custom-designed data-logging GPS units integrated into clothing. Location data were transferred into geographic information systems software for map overlay, visualization, and tabular analysis. Data were grouped into five location categories (in vehicle, inside house, inside school, inside business, and outside) to determine time spent and percentage reception in each location. Additional experiments focused on spatial resolution, reception efficiency in typical environments, and sources of signal interference. Significant signal interference occurred only inside concrete/steel-frame buildings and inside a power substation. The GPS instruments provided adequate spatial resolution (typically about 2-3 m outdoors and 4-5 m indoors) to locate subjects within distinct microenvironments and distinguish a variety of human activities. Reception experiments showed that location could be tracked outside, proximal to buildings, and inside some buildings. Specific location information could identify movement in a single room inside a home, on a playground, or along a fence line. The instrument, worn in a vest or in bib overalls, was accepted by children and parents. Durability of the wiring was improved early in the study to correct breakage problems. The use of GPS technology offers a new level of accuracy for direct quantification of time-location activity patterns in exposure assessment studies.

Effects of chloro-s-triazine herbicides and metabolites on aromatase activity in various human cell lines and on vitellogenin production in male carp hepatocytes

We investigated a potential mechanism for the estrogenic properties of three chloro-s-triazine herbicides and six metabolites in vitro in several cell systems. We determined effects on human aromatase (CYP19), the enzyme that converts androgens to estrogens, in H295R (adrenocortical carcinoma), JEG-3 (placental choriocarcinoma), and MCF-7 (breast cancer) cells; we determined effects on estrogen receptor-mediated induction of vitellogenin in primary hepatocyte cultures of adult male carp (Cyprinus carpio). In addition to atrazine, simazine, and propazine, two metabolites--atrazine-desethyl and atrazine-desisopropyl--induced aromatase activity in H295R cells concentration-dependently (0.3-30 microM) and with potencies similar to those of the parent triazines. After a 24-hr exposure to 30 microM of the triazines, an apparent maximum induction of about 2- to 2.5-fold was achieved. The induction responses were confirmed by similar increases in CYP19 mRNA levels, determined by reverse-transcriptase polymerase chain reaction. In JEG-3 cells, where basal aromatase expression is about 15-fold greater than in H295R cells, the induction responses were similar but less pronounced; aromatase expression in MCF-7 cells was neither detectable nor inducible under our culture conditions. The fully dealkylated metabolite atrazine-desethyl-desisopropyl and the three hydroxylated metabolites (2-OH-atrazine-desethyl, -desisopropyl, and -desethyl-desisopropyl) did not induce aromatase activity. None of the triazine herbicides nor their metabolites induced vitellogenin production in male carp hepatocytes; nor did they antagonize the induction of vitellogenin by 100 nM (EC(50) 17beta-estradiol. These findings together with other reports indicate that the estrogenic effects associated with the triazine herbicides in vivo are not estrogen receptor-mediated, but may be explained partly by their ability to induce aromatase in vitro.

Agricultural pesticide use in California: pesticide prioritization, use densities, and population distributions for a childhood cancer study

Several studies have suggested an association between childhood cancer and pesticide exposure. California leads the nation in agricultural pesticide use. A mandatory reporting system for all agricultural pesticide use in the state provides information on the active ingredient, amount used, and location. We calculated pesticide use density to quantify agricultural pesticide use in California block groups for a childhood cancer study. Pesticides with similar toxicologic properties (probable carcinogens, possible carcinogens, genotoxic compounds, and developmental or reproductive toxicants) were grouped together for this analysis. To prioritize pesticides, we weighted pesticide use by the carcinogenic and exposure potential of each compound. The top-ranking individual pesticides were propargite, methyl bromide, and trifluralin. We used a geographic information system to calculate pesticide use density in pounds per square mile of total land area for all United States census-block groups in the state. Most block groups (77%) averaged less than 1 pound per square mile of use for 1991-1994 for pesticides classified as probable human carcinogens. However, at the high end of use density (> 90th percentile), there were 493 block groups with more than 569 pounds per square mile. Approximately 170,000 children under 15 years of age were living in these block groups in 1990. The distribution of agricultural pesticide use and number of potentially exposed children suggests that pesticide use density would be of value for a study of childhood cancer.

Farming from a new perspective: remote sensing comes down to earth

Farmers strive to increase the yield of their fields by adding nutrients and water to the land, and using pesticides to control insects and disease. In addition to bountiful harvests, the results of their endeavors may include elevated amounts of fertilizers in surface waters and aquifers and potential risk to themselves and their neighbors from exposure to pesticides. Precision agriculture is the use of modern information technologies such as geographic information systems, the global positioning system, and remote sensing from the air to reduce the environmental effects of these chemicals while enhancing the productivity of farming. By combining crop yield maps with soil survey maps and remote sensing output, farmers can identify areas that need more or less fertilizer, water, or pesticide.