Bibliography Tag: 2 4 d

Bohnenblust et al., 2016

Bohnenblust, E. W., Vaudo, A. D., Egan, J. F., Mortensen, D. A., & Tooker, J. F.; “Effects of the herbicide dicamba on nontarget plants and pollinator visitation;” Environmental Toxicology and Chemistry, 2016, 35(1), 144-151; DOI: 10.1002/etc.3169.


Nearly 80% of all pesticides applied to row crops are herbicides, and these applications pose potentially significant ecotoxicological risks to nontarget plants and associated pollinators. In response to the widespread occurrence of weed species resistant to glyphosate, biotechnology companies have developed crops resistant to the synthetic-auxin herbicides dicamba and 2,4-dichlorophenoxyacetic acid (2,4-D); and once commercialized, adoption of these crops is likely to change herbicide-use patterns. Despite current limited use, dicamba and 2,4-D are often responsible for injury to nontarget plants; but effects of these herbicides on insect communities are poorly understood. To understand the influence of dicamba on pollinators, the authors applied several sublethal, drift-level rates of dicamba to alfalfa (Medicago sativa L.) and Eupatorium perfoliatum L. and evaluated plant flowering and floral visitation by pollinators. The authors found that dicamba doses simulating particle drift (≈1% of the field application rate) delayed onset of flowering and reduced the number of flowers of each plant species; however, plants that did flower produced similar-quality pollen in terms of protein concentrations. Further, plants affected by particle drift rates were visited less often by pollinators. Because plants exposed to sublethal levels of dicamba may produce fewer floral resources and be less frequently visited by pollinators, use of dicamba or other synthetic-auxin herbicides with widespread planting of herbicide-resistant crops will need to be carefully stewarded to prevent potential disturbances of plant and beneficial insect communities in agricultural landscapes. FULL TEXT

Rydz et al., 2020

Rydz, C. E., Larsen, K., & Peters, C. E.; “Estimating Exposure to Three Commonly Used, Potentially Carcinogenic Pesticides (Chlorolathonil, 2,4-D, and Glyphosate) Among Agricultural Workers in Canada;” Annals of Work Exposures and Health, 2020; DOI: 10.1093/annweh/wxaa109.


OBJECTIVES: Certain pesticides have been associated with adverse health outcomes including cancer and reproductive harms. However, little is known about the prevalence of occupational pesticide exposure among agricultural workers in Canada. The purpose of this study was to estimate the prevalence and likelihood of occupational exposure to pesticides in Canada’s agricultural industry, using three commonly used, potentially carcinogenic pesticides [chlorothalonil, 2,4-dichlorophenoxyacetic acid (2,4-D), and glyphosate] as an example.

METHODS: Estimates were calculated using the Canadian Census of Population and the Census of Agriculture. The number of workers and the proportion of farms applying ‘herbicides’ or ‘fungicides’ by farm type was estimated using survey data from the Census of Agriculture. These values were multiplied to yield the potential number of workers at risk of exposure. Likelihood of exposure (i.e. exposed, probably exposed, and possibly exposed) was then qualitatively assigned using information on crop type, primary expected tasks, crop production practices, and residue transfer data. Additional agricultural workers who are at risk of exposure but not captured by the Census of Agriculture were identified using the 2016 Census of Population.

RESULTS: An estimated range of 37 700-55 800 workers (11-13% of agricultural workers) were exposed to glyphosate in Canada while 30 800-43 600 workers (9-11%) and 9000-14 100 (2.9-3.2%) were exposed to 2,4-D and chlorothalonil, respectively. Approximately 70-75% of workers at risk of exposure were considered probably or possibly exposed to any of the pesticides. Glyphosate exposure was most common among workers in oilseed (29% of oilseed farm workers exposed) and dry pea/bean farms (28%), along with those providing support activities for farms (31%). 2,4-D exposure was most common in corn (28%), other grain (28%), and soybean farms (27%), while chlorothalonil exposure was more likely among greenhouse, nursery, and floriculture workers (42%), workers on farms (28%, for occupations not captured by the Census of Agriculture, specifically), and those providing support activities for farms (20%). Regional variations broadly reflected differences in farm types by province.

CONCLUSIONS: This study estimated the prevalence of occupational exposure to three pesticides in Canada. Seasonal and temporary agricultural workers, which were captured by the Census of Agriculture, contributed to many additionally exposed workers. A large percent of the workers who were considered at risk of exposure were considered probably or possibly exposed, indicating a need for enhanced data collection and availability on pesticide use data in Canada. The study’s methods can be applied to estimate workers’ exposures to other pesticides within the agricultural industry.

Givens et al., 2017

Givens, Wade A., Shaw, David R., Johnson, William G., Weller, Stephen C., Young, Bryan G., Wilson, Robert G., Owen, Micheal D. K., & Jordan, David; “A Grower Survey of Herbicide Use Patterns in Glyphosate-Resistant Cropping Systems;” Weed Technology, 2017, 23(1), 156-161; DOI: 10.1614/wt-08-039.1.


A telephone survey was conducted with growers in Iowa, Illinois, Indiana, Nebraska, Mississippi, and North Carolina to discern the utilization of the glyphosate-resistant (GR) trait in crop rotations, weed pressure, tillage practices, herbicide use, and perception of GR weeds. This paper focuses on survey results regarding herbicide decisions made during the 2005 cropping season. Less than 20% of the respondents made fall herbicide applications. The most frequently used herbicides for fall applications were 2,4-D and glyphosate, and these herbicides were also the most frequently used for preplant burndown weed control in the spring. Atrazine and acetochlor were frequently used in rotations containing GR corn. As expected, crop rotations using a GR crop had a high percentage of respondents that made one to three POST applications of glyphosate per year. GR corn, GR cotton, and non-GR crops had the highest percentage of growers applying nonglyphosate herbicides during the 2005 growing season. A crop rotation containing GR soybean had the greatest negative impact on non-glyphosate use. Overall, glyphosate use has continued to increase, with concomitant decreases in utilization of other herbicides. FULL TEXT

Griffin et al., 1997

Griffin, R. J., Godfrey, V. B., Kim, Y. C., & Burka, L. T.; “Sex-dependent differences in the disposition of 2,4-dichlorophenoxyacetic acid in Sprague-Dawley rats, B6C3F1 mice, and Syrian hamsters;” Drug Metabolism and Disposition, 1997, 25(9), 1065-1071.


2,4-Dichlorophenoxyacetic acid (2,4-D), a widely used broadleaf herbicide, is under investigation in a study of peroxisome proliferators. To supplement that study, male and female rats, mice, and hamsters were dosed with 14C-2,4-D orally at 5 and 200 mg/kg and tissue distributions were determined. Blood, liver, kidney, muscle, skin, fat, brain, testes, and ovaries were examined. At early time points tissues from female rats consistently contained higher amounts of radioactivity than did corresponding tissues from males (up to 9 times). By 72 hr, tissue levels were equivalent and males and females had excreted equal amounts of radioactivity. This sex difference was absent in mice. In hamsters, males had higher tissue levels than females. Taurine, glycine, and glucuronide conjugates of 2,4-D were excreted along with parent. Metabolite profiles differed between species qualitatively and quantitatively; however, differences between sexes were minimal. Plasma elimination curves were generated in male and female rats after iv and oral administration. Kinetic analysis revealed significant differences in elimination and exposure parameters consistent with a greater ability to clear 2,4-D by male rats relative to females. This suggests that at equivalent doses, female rats are exposed to higher concentrations of 2,4-D for a longer time than males and may be more susceptible to 2,4-D-induced toxicity. These sex-dependent variations in the clearance of 2,4-D in rats and hamsters may indicate a need for sex-specific models to accurately assess human health risks. FULL TEXT

Thomas et al., 2010b

Thomas, K. W., Dosemeci, M., Coble, J. B., Hoppin, J. A., Sheldon, L. S., Chapa, G., Croghan, C. W., Jones, P. A., Knott, C. E., Lynch, C. F., Sandler, D. P., Blair, A. E., & Alavanja, M. C.; “Assessment of a pesticide exposure intensity algorithm in the agricultural health study;” Journal of Exposure Analysis and Environmental Epidemiology, 2010, 20(6), 559-569; DOI: 10.1038/jes.2009.54.


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. FULL TEXT

Curwin et al., 2002

Curwin, B., Sanderson, W., Reynolds, S., Hein, M., & Alavanja, M.; “Pesticide use and practices in an Iowa farm family pesticide exposure study;” Journal of Agricultural Safety and Health, 2002, 8(4), 423-433; DOI: 10.13031/2013.10222.


Residents of Iowa were enrolled in a study investigating differences in pesticide contamination and exposure factors between 25 farm homes and 25 non-farm homes. The target pesticides investigated were atrazine, metolachlor, acetochlor, alachlor, 2,4-D, glyphosate, and chlorpyrifos; all were applied to either corn or soybean crops. A questionnaire was administered to all participants to determine residential pesticide use in and around the home. In addition, a questionnaire was administered to the farmers to determine the agricultural pesticides they used on the farm and their application practices. Non-agricultural pesticides were used more in and around farm homes than non-farm homes. Atrazine was the agricultural pesticide used most by farmers. Most farmers applied pesticides themselves but only 10 (59%) used tractors with enclosed cabs, and they typically wore little personal protective equipment (PPE). On almost every farm, more than one agricultural pesticide was applied. Corn was grown by 23 (92%) farmers and soybeans by 12 (48%) farmers. Of these, 10 (40%) grew both soybeans and corn, with only 2 (8%) growing only soybeans and 13 (52%) growing only corn. The majority of farmers changed from their work clothes and shoes in the home, and when they changed outside or in the garage, they usually brought their clothes and shoes inside. Applying pesticides using tractors with open cabs, not wearing PPE, and changing from work clothes in the home may increase pesticide exposure and contamination. Almost half of the 66 farm children less than 16 years of age were engaged in some form of farm chores, with 6 (9%) potentially directly exposed to pesticides, while only 2 (4%) of the 52 non-farm children less than 16 years of age had farm chores, and none were directly exposed to pesticides. Farm homes may be contaminated with pesticides in several ways, resulting in potentially more contamination than non-farm homes, and farm children may be directly exposed to pesticides through farm chores involving pesticides. In addition to providing a description of pesticide use, the data presented here will be useful in evaluating potential contributing factors to household pesticide contamination and family exposure. FULL TEXT

Coble et al., 2011

Coble, J., Thomas, K. W., Hines, C. J., Hoppin, J. A., Dosemeci, M., Curwin, B., Lubin, J. H., Beane Freeman, L. E., Blair, A., Sandler, D. P., & Alavanja, M. C.; “An updated algorithm for estimation of pesticide exposure intensity in the agricultural health study;” International Journal of Environmental Research and Public Health, 2011, 8(12), 4608-4622; DOI: 10.3390/ijerph8124608.


An algorithm developed to estimate pesticide exposure intensity for use in epidemiologic analyses was revised based on data from two exposure monitoring studies. In the first study, we estimated relative exposure intensity based on the results of measurements taken during the application of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) (n = 88) and the insecticide chlorpyrifos (n = 17). Modifications to the algorithm weighting factors were based on geometric means (GM) of post-application urine concentrations for applicators grouped by application method and use of chemically-resistant (CR) gloves. Measurement data from a second study were also used to evaluate relative exposure levels associated with airblast as compared to hand spray application methods. Algorithm modifications included an increase in the exposure reduction factor for use of CR gloves from 40% to 60%, an increase in the application method weight for boom spray relative to in-furrow and for air blast relative to hand spray, and a decrease in the weight for mixing relative to the new weights assigned for application methods. The weighting factors for the revised algorithm now incorporate exposure measurements taken on Agricultural Health Study (AHS) participants for the application methods and personal protective equipment (PPE) commonly reported by study participants. FULL TEXT

Blair et al., 2011

Blair, A., Thomas, K., Coble, J., Sandler, D. P., Hines, C. J., Lynch, C. F., Knott, C., Purdue, M. P., Zahm, S. H., Alavanja, M. C., Dosemeci, M., Kamel, F., Hoppin, J. A., Freeman, L. B., & Lubin, J. H.; “Impact of pesticide exposure misclassification on estimates of relative risks in the Agricultural Health Study;” Occupational and Environmental Medicine, 2011, 68(7), 537-541; DOI: 10.1136/oem.2010.059469.


BACKGROUND: The Agricultural Health Study (AHS) is a prospective study of licensed pesticide applicators and their spouses in Iowa and North Carolina. We evaluate the impact of occupational pesticide exposure misclassification on relative risks using data from the cohort and the AHS Pesticide Exposure Study (AHS/PES).

METHODS: We assessed the impact of exposure misclassification on relative risks using the range of correlation coefficients observed between measured post-application urinary levels of 2,4-dichlorophenoxyacetic acid (2,4-D) and a chlorpyrifos metabolite and exposure estimates based on an algorithm from 83 AHS pesticide applications.

RESULTS: Correlations between urinary levels of 2,4-D and a chlorpyrifos metabolite and algorithm estimated intensity scores were about 0.4 for 2,4-D (n=64), 0.8 for liquid chlorpyrifos (n=4) and 0.6 for granular chlorpyrifos (n=12). Correlations of urinary levels with kilograms of active ingredient used, duration of application, or number of acres treated were lower and ranged from -0.36 to 0.19. These findings indicate that a priori expert-derived algorithm scores were more closely related to measured urinary levels than individual exposure determinants evaluated here. Estimates of potential bias in relative risks based on the correlations from the AHS/PES indicate that non-differential misclassification of exposure using the algorithm would bias estimates towards the null, but less than that from individual exposure determinants.

CONCLUSIONS: Although correlations between algorithm scores and urinary levels were quite good (ie, correlations between 0.4 and 0.8), exposure misclassification would still bias relative risk estimates in the AHS towards the null and diminish study power.


Curwin et al., 2005

Curwin, B. D., Hein, M. J., Sanderson, W. T., Nishioka, M. G., Reynolds, S. J., Ward, E. M., & Alavanja, M. C.; “Pesticide contamination inside farm and nonfarm homes;” Journal of Occupational and Environmental Hygiene, 2005, 2(7), 357-367; DOI: 10.1080/15459620591001606.


Twenty-five farm (F) households and 25 nonfarm (NF) households in Iowa were enrolled in a study investigating agricultural pesticide contamination inside homes. Air, surface wipe, and dust samples were collected. Samples from 39 homes (20 F and 19 NF) were analyzed for atrazine, metolachlor, acetochlor, alachlor, and chlorpyrifos. Samples from 11 homes (5 F and 6 NF) were analyzed for glyphosate and 2,4-Dichlorophenoxyac etic acid (2,4-D). Greater than 88% of the air and greater than 74% of the wipe samples were below the limit of detection (LOD). Among the air and wipe samples, chlorpyrifos was detected most frequently in homes. In the dust samples, all the pesticides were detected in greater than 50% of the samples except acetochlor and alachlor, which were detected in less than 30% of the samples. Pesticides in dust samples were detected more often in farm homes except 2,4-D, which was detected in 100% of the farm and nonfarm home samples. The average concentration in dust was higher in farm homes versus nonfarm homes for each pesticide. Further analysis of the data was limited to those pesticides with at least 50% of the dust samples above the LOD. All farms that sprayed a pesticide had higher levels of that pesticide in dust than both farms that did not spray that pesticide and nonfarms; however, only atrazine and metolachlor were significantly higher. The adjusted geometric mean pesticide concentration in dust for farms that sprayed a particular pesticide ranged from 94 to 1300 ng/g compared with 12 to 1000 ng/g for farms that did not spray a particular pesticide, and 2.4 to 320 ng/g for nonfarms. The distributions of the pesticides throughout the various rooms sampled suggest that the strictly agricultural herbicides atrazine and metolachlor are potentially being brought into the home on the farmer’s shoes and clothing. These herbicides are not applied in or around the home but they appear to be getting into the home para-occupationally. For agricultural pesticides, take-home exposure may be an important source of home contamination. FULL TEXT

Coble et al., 2005

Coble, J., Arbuckle, T., Lee, W., Alavanja, M., & Dosemeci, M.; “The validation of a pesticide exposure algorithm using biological monitoring results;” Journal of Occupational and Environmental Hygiene, 2005, 2(3), 194-201; DOI: 10.1080/15459620590923343.


A pesticide exposure algorithm was developed to calculate pesticide exposure intensity scores based on responses to questions about pesticide handling procedures and application methods in a self-administered questionnaire. The validity of the algorithm was evaluated through comparison of the algorithm scores with biological monitoring data from a study of 126 pesticide applicators who applied the herbicides MCPA or 2,4-D. The variability in the algorithm scores calculated for these applicators was due primarily to differences in their use of personal protective equipment (PPE). Rubber gloves were worn by 75% of applicators when mixing and 22% when applying pesticides, rubber boots were worn by 33% when mixing and 23% when applying, and goggles were worn by 33% and 17% of applicators when mixing and when applying, respectively. Only 2% of applicators wore all three types of PPE when both mixing and applying, and 15% wore none of these three types of PPE when either mixing or applying. Substantial variability was also observed in the concentrations of pesticides detected in the post application urine samples. The concentration of MCPA detected in urine samples collected on the second day after the application ranged from less than < 1.0 to 610 microg/L among 84 of the applicators who applied MCPA. The concentrations of 2,4-D detected in the urine samples ranged from less than < 1.0 to 514 microg/L among 41 of the applicators who applied 2,4-D. When categorized into three groups based on the algorithm scores, the geometric mean in the highest exposure group was 20 microg/L compared with 5 microg/L in the lowest exposure group for the MCPA applicators, and 29 microg/L in highest exposure group compared with 2 microg/L in the low exposure group for the 2,4-D applicators. A regression analysis detected statistically significant trends in the geometric mean of the urine concentrations across the exposure categories for both the 2,4-D and the MCPA applicators. The algorithm scores, based primarily on the use of PPE, appear to provide a reasonably valid measure of exposure intensity for these applicators, however, further studies are needed to generalize these results to other types of pesticides and application methods. FULL TEXT