Drift Comparisons Between Aerial and Ground Orchard Application

Maccollom, G. B.; Currier, William W.; Baumann, G. L.

doi:10.1093/jee/79.2.459

Cited by 23 publications

(19 citation statements)

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“…Employing our GIS-based system, we combined PUR data, land use maps, and geocoded address information [26, 28] to produce estimates of pesticide exposure within a 500-m radius buffer around participants’ occupational and residential addresses as suggested in previous literature [29–31]. A technical discussion of our GIS-based approach is provided elsewhere, here we briefly summarize the data sources and exposure modeling process [26].…”

Section: Methodsmentioning

confidence: 99%

Parkinson’s disease risk from ambient exposure to pesticides

et al. 2011

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Due to the heavy and expanding agricultural use of neurotoxic pesticides suspected to affect dopaminergic neurons, it is imperative to closely examine the role of pesticides in the development of Parkinson’s disease (PD). We focus our investigation on pesticide use in California’s heavily agricultural central valley by utilizing a unique pesticide use reporting system. From 2001 to 2007, we enrolled 362 incident PD cases and 341 controls living in the Central Valley of California. Employing our geographic information system model, we estimated ambient exposures to the pesticides ziram, maneb, and paraquat at work places and residences from 1974 to 1999. At workplaces, combined exposure to ziram, maneb, and paraquat increased risk of PD three-fold (OR: 3.09; 95% CI: 1.69, 5.64) and combined exposure to ziram and paraquat, excluding maneb exposure, was associated with a 80% increase in risk (OR:1.82; 95% CI: 1.03, 3.21). Risk estimates for ambient workplace exposure were greater than for exposures at residences and were especially high for younger onset PD patients and when exposed in both locations. Our study is the first to implicate ziram in PD etiology. Combined ambient exposure to ziram and paraquat as well as combined ambient exposure to maneb and paraquat at both workplaces and residences increased PD risk substantially. Those exposed to ziram, maneb, and paraquat together experienced the greatest increase in PD risk. Our results suggest that pesticides affecting different mechanisms that contribute to dopaminergic neuron death may act together to increase the risk of PD considerably.

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Section: Methodsmentioning

confidence: 99%

Parkinson’s disease risk from ambient exposure to pesticides

et al. 2011

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“…proximity to pesticides at distances < 1 mi (1,609 m). Yet some dispersion studies suggest that pesticides are measurable only at considerably smaller distances of ≤ 500 m from the application site (Chester and Ward 1984;Frost and Ware 1970;MacCollom et al 1986;Woods et al 2001). Thus, exposure misclassification may occur if the drift range of an applied pesticide is considerably less than one 1 mi.…”

Section: Historical Pesticide Exposure In California Using Pesticide mentioning

confidence: 99%

“…Pesticides applied from the air or ground have been observed to drift from their intended treatment sites, with measurable concentrations detected in the air and in plants and animals several hundred meters away (Chester and Ward 1984;Currier et al 1982;Frost and Ware 1970;MacCollom et al 1986;Woods et al 2001). Herbicides transported downwind can cause unintended damage to crops (Byass and Lake 1977), and acute pesticide poisonings have been observed in communities downwind from agricultural fields after applications (Ames et al 1993).…”

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confidence: 99%

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

Rull

Ritz

2003

Environ Health Perspect

103

102

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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.

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“…Pesticides applied from the air or ground may drift from their intended treatment sites, such that there are measurable concentrations of pesticides detected in the air, in plants, and in animals up to several hundred meters from application sites. [25][26][27][28] Thus, alternative methods of estimating exposures in rural communities are sorely needed, but accurate exposure assessment may be particularly challenging. Geographic Information System (GIS)-based methods of assessing exposures to pesticides have become popular in recent years and may prove to be an effective solution to this problem.…”

Section: Introductionmentioning

confidence: 99%

Geographic Model and Biomarker‐Derived Measures of Pesticide Exposure and Parkinson's Disease

Ritz

Costello

2006

Annals of the New York Academy of Sciences

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For more than two decades, reports have suggested that pesticides and herbicides may be an etiologic factor in idiopathic Parkinson's disease (PD). To date, no clear associations with any specific pesticide have been demonstrated from epidemiological studies perhaps, in part, because methods of reliably estimating exposures are lacking. We tested the validity of a Geographic Information Systems (GIS)-based exposure assessment model that estimates potential environmental exposures at residences from pesticide applications to agricultural crops based on California Pesticide Use Reports (PUR). Using lipid-adjusted dichlorodiphenyldichloroethylene (DDE) serum levels as the "gold standard" for pesticide exposure, we conducted a validation study in a sample taken from an ongoing, population-based case-control study of PD in Central California. Residential, occupational, and other risk factor data were collected for 22 cases and 24 controls from Kern county, California. Environmental GIS-PUR-based organochlorine (OC) estimates were derived for each subject and compared to lipid-adjusted DDE serum levels. Relying on a linear regression model, we predicted log-transformed lipid-adjusted DDE serum levels. GIS-PUR-derived OC measure, body mass index, age, gender, mixing and loading pesticides by hand, and using pesticides in the home, together explained 47% of the DDE serum level variance (adjusted r 2 = 0.47). The specificity of using our environmental GIS-PUR-derived OC measures to identify those with high-serum DDE levels was reasonably good (87%). Our environmental GIS-PUR-based approach appears to provide a valid model for assessing residential exposures to agricultural pesticides.

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Drift Comparisons Between Aerial and Ground Orchard Application

Cited by 23 publications

References 0 publications

Parkinson’s disease risk from ambient exposure to pesticides

Parkinson’s disease risk from ambient exposure to pesticides

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

Geographic Model and Biomarker‐Derived Measures of Pesticide Exposure and Parkinson's Disease

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