Bibliography Tag: pesticide exposure

Bibliography Index

Curwin et al., 2007

Curwin, Brian D., Hein, Misty J., Sanderson, Wayne T., Striley, Cynthia, Heederik, Dick, Kromhout, Hans, Reynolds, Stephen J., & Alavanja, Michael C.; “Pesticide dose estimates for children of Iowa farmers and non-farmers;” Environmental Research, 2007, 105, 307-315; DOI: 10.1016/j.envres.2007.06.001.

ABSTRACT:

Farm children have the potential to be exposed to pesticides. Biological monitoring is often employed to assess this exposure; however, the significance of the exposure is uncertain unless doses are estimated. In the spring and summer of 2001, 118 children (66 farm, 52 non-farm) of Iowa farm and non-farm households were recruited to participate in a study investigating potential take-home pesticide exposure. Each child provided an evening and morning urine sample at two visits spaced approximately 1 month apart, with the first sample collection taken within a few days after pesticide application. Estimated doses were calculated for atrazine, metolachlor, chlorpyrifos, and glyphosate from urinary metabolite concentrations derived from the spot urine samples and compared to EPA reference doses. For all pesticides except glyphosate, the doses from farm children were higher than doses from the non-farm children. The difference was statistically significant for atrazine (p<0.0001) but only marginally significant for chlorpyrifos and metolachlor (p=0.07 and 0.1, respectively). Among farm children, geometric mean doses were higher for children on farms where a particular pesticide was applied compared to farms where that pesticide was not applied for all pesticides except glyphosate; results were significant for atrazine (p=0.030) and metolachlor (p=0.042), and marginally significant for chlorpyrifos (p=0.057). The highest estimated doses for atrazine, chlorpyrifos, metolachlor, and glyphosate were 0.085, 1.96, 3.16, and 0.34 μg/kg/day, respectively. None of the doses exceeded any of the EPA reference values for atrazine, metolachlor, and glyphosate; however, all of the doses for chlorpyrifos exceeded the EPA chronic population adjusted reference value. Doses were similar for male and female children. A trend of decreasing dose with increasing age was observed for chlorpyrifos. 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.

ABSTRACT:

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.

ABSTRACT:

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

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.

ABSTRACT:

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.

ABSTRACT:

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

Thomas et al., 2010

Thomas, K. W., Dosemeci, M., Hoppin, J. A., Sheldon, L. S., Croghan, C. W., Gordon, S. M., Jones, M. L., Reynolds, S. J., Raymer, J. H., Akland, G. G., Lynch, C. F., Knott, C. E., Sandler, D. P., Blair, A. E., & Alavanja, M. C.; “Urinary biomarker, dermal, and air measurement results for 2,4-D and chlorpyrifos farm applicators in the Agricultural Health Study;” Journal of Exposure Science and Environmental Epidemiology, 2010, 20(2), 119-134; DOI: 10.1038/jes.2009.6.

ABSTRACT:

A subset of private pesticide applicators in the Agricultural Health Study (AHS) epidemiological cohort was monitored around the time of their agricultural use of 2,4-dichlorophenoxyacetic acid (2,4-D) and O,O-diethyl-O-3,5,6-trichloro-2-pyridyl phosphorothioate (chlorpyrifos) to assess exposure levels and potential determinants of exposure. Measurements included pre- and post-application urine samples, and patch, hand wipe, and personal air samples. Boom spray or hand spray application methods were used by applicators for 2,4-D products. Chlorpyrifos products were applied using spray applications and in-furrow application of granular products. Geometric mean (GM) values for 69 2,4-D applicators were 7.8 and 25 microg/l in pre- and post-application urine, respectively (P<0.05 for difference); 0.39 mg for estimated hand loading; 2.9 mg for estimated body loading; and 0.37 microg/m(3) for concentration in personal air. Significant correlations were found between all media for 2,4-D. GM values for 17 chlorpyrifos applicators were 11 microg/l in both pre- and post-application urine for the 3,5,6-trichloro-2-pyridinol metabolite, 0.28 mg for body loading, and 0.49 microg/m(3) for air concentration. Only 53% of the chlorpyrifos applicators had measurable hand loading results; their median hand loading being 0.02 mg. Factors associated with differences in 2,4-D measurements included application method and glove use, and, for hand spray applicators, use of adjuvants, equipment repair, duration of use, and contact with treated vegetation. Spray applications of liquid chlorpyrifos products were associated with higher measurements than in-furrow granular product applications. This study provides information on exposures and possible exposure determinants for several application methods commonly used by farmers in the cohort and will provide information to assess and refine exposure classification in the AHS. Results may also be of use in pesticide safety education for reducing exposures to pesticide applicators. FULL TEXT

Hoppin et al., 2002

Hoppin, Jane A., Umbach, David M, London, Stephanie J., Alavanja, Michael, & Sandler, Dale P.; “Chemical Predictors of Wheeze among Farmer Pesticide Applicators in the Agricultural Health Study;” American Journal of Respiratory and Critical Care Medicine, 2002, 165, 683-689; DOI: 10.1164/rccm.2106074.

ABSTRACT:

Pesticides may contribute to respiratory symptoms among farmers. Using the Agricultural Health Study, a large cohort of certified pesticide applicators in Iowa and North Carolina, we explored the association between wheeze and pesticide use in the past year. Self-administered questionnaires contained items on 40 currently used pesticides and pesticide application practices. A total of 20,468 applicators, ranging in age from 16 to 88 years, provided complete information; 19% reported wheezing in the past year. Logistic regression models controlling for age, state, smoking, and history of asthma or atopy were used to evaluate associations between individual pesticides and wheeze. Among pesticides suspected to contribute to wheeze, paraquat, three organophosphates (parathion, malathion, and chlorpyrifos), and one thiocarbamate (S-ethyl-dipropylthiocarbamate [EPTC]) had elevated odds ratios (OR). Parathion had the highest OR (1.5, 95% confidence interval [CI] 1.0, 2.2).

Chlorpyrifos, EPTC, paraquat, and parathion demonstrated significant dose–response trends. The herbicides, atrazine and alachlor, but not 2,4-D, were associated with wheeze. Atrazine had a significant dose–response trend with participants applying atrazine more than 20 days/year having an OR of 1.5 (95% CI 1.2,1.9). Inclusion of crops and animals into these models did not significantly alter the observed OR. These associations, though small, suggest an independent role for specific pesticides in respiratory symptoms of farmers. FULL TEXT

Dosemeci et al., 2002

Dosemeci, M., Alavanja, M. C., Rowland, A. S., Mage, D., Zahm, S. H., Rothman, N., Lubin, J. H., Hoppin, J. A., Sandler, D. P., & Blair, A.; “A quantitative approach for estimating exposure to pesticides in the Agricultural Health Study;” Annals of Occupational Hygiene, 2002, 46(2), 245-260; DOI: 10.1093/annhyg/mef011.

ABSTRACT:

We developed a quantitative method to estimate long-term chemical-specific pesticide exposures in a large prospective cohort study of more than 58000 pesticide applicators in North Carolina and Iowa. An enrollment questionnaire was administered to applicators to collect basic time- and intensity-related information on pesticide exposure such as mixing condition, duration and frequency of application, application methods and personal protective equipment used. In addition, a detailed take-home questionnaire was administered to collect further intensity-related exposure information such as maintenance or repair of mixing and application equipment, work practices and personal hygiene. More than 40% of the enrolled applicators responded to this detailed take-home questionnaire. Two algorithms were developed to identify applicators’ exposure scenarios using information from the enrollment and take-home questionnaires separately in the calculation of subject-specific intensity of exposure score to individual pesticides. The ‘general algorithm’ used four basic variables (i.e. mixing status, application method, equipment repair status and personal protective equipment use) from the enrollment questionnaire and measurement data from the published pesticide exposure literature to calculate estimated intensity of exposure to individual pesticides for each applicator. The ‘detailed’ algorithm was based on variables in the general algorithm plus additional exposure information from the take-home questionnaire, including types of mixing system used (i.e. enclosed or open), having a tractor with enclosed cab and/or charcoal filter, frequency of washing equipment after application, frequency of replacing old gloves, personal hygiene and changing clothes after a spill. Weighting factors applied in both algorithms were estimated using measurement data from the published pesticide exposure literature and professional judgment. For each study subject, chemical-specific lifetime cumulative pesticide exposure levels were derived by combining intensity of pesticide exposure as calculated by the two algorithms independently and duration/frequency of pesticide use from the questionnaire. Distributions of duration, intensity and cumulative exposure levels of 2,4-D and chlorpyrifos are presented by state, gender, age group and applicator type (i.e. farmer or commercial applicator) for the entire enrollment cohort and for the sub-cohort of applicators who responded to the take-home questionnaire. The distribution patterns of all basic exposure indices (i.e. intensity, duration and cumulative exposure to 2,4-D and chlorpyrifos) by state, gender, age and applicator type were almost identical in two study populations, indicating that the take-home questionnaire sub-cohort of applicators is representative of the entire cohort in terms of exposure. FULL TEXT

Alavanja et al., 1996

Alavanja, M. C., Sandler, D. P., McMaster, S. B., Zahm, S. H., McDonnell, C. J., Lynch, C. F., Pennybacker, M., Rothman, N., Dosemeci, M., Bond, A. E., & Blair, A.; “The Agricultural Health Study;” Environmental Health Perspectives, 1996, 104(4), 362-369; DOI: 10.1289/ehp.96104362.

ABSTRACT:

The Agricultural Health Study, a large prospective cohort study has been initiated in North Carolina and Iowa. The objectives of this study are to: 1) identify and quantify cancer risks among men, women, whites, and minorities associated with direct exposure to pesticides and other agricultural agents; 2) evaluate noncancer health risks including neurotoxicity reproductive effects, immunologic effects, nonmalignant respiratory disease, kidney disease, and growth and development among children; 3) evaluate disease risks among spouses and children of farmers that may arise from direct contact with pesticides and agricultural chemicals used in the home lawns and gardens, and from indirect contact, such as spray drift, laundering work clothes, or contaminated food or water; 4) assess current and past occupational and nonoccupational agricultural exposures using periodic interviews and environmental and biologic monitoring; 5) study the relationship between agricultural exposures, biomarkers of exposure, biologic effect, and genetic susceptibility factors relevant to carcinogenesis; and 6) identify and quantify cancer and other disease risks associated with lifestyle factors such as diet, cooking practices, physical activity, smoking and alcohol consumption, and hair dye use. In the first year of a 3-year enrollment period, 26,235 people have been enrolled in the study, including 19,776 registered pesticide applicators and 6,459 spouses of registered farmer applicators. It is estimated that when the total cohort is assembled in 1997 it will include approximately 75,000 adult study subjects. Farmers, the largest group of registered pesticide applicators comprise 77% of the target population enrolled in the study. This experience compares favorably with enrollment rates of previous prospective studies. FULL TEXT

Pardo et al., 2020

Pardo, L. A., Beane Freeman, L. E., Lerro, C. C., Andreotti, G., Hofmann, J. N., Parks, C. G., Sandler, D. P., Lubin, J. H., Blair, A., & Koutros, S.; “Pesticide exposure and risk of aggressive prostate cancer among private pesticide applicators;” Environmental Health, 2020, 19(1), 30; DOI: 10.1186/s12940-020-00583-0. https://www.ncbi.nlm.nih.gov/pubmed/32138787.

ABSTRACT:

BACKGROUND: Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men in developed countries; however, little is known about modifiable risk factors. Some studies have implicated organochlorine and organophosphate insecticides as risk factors (particularly the organodithioate class) and risk of clinically significant PCa subtypes. However, few studies have evaluated other pesticides. We used data from the Agricultural Health Study, a large prospective cohort of pesticide applicators in North Carolina and Iowa, to extend our previous work and evaluate 39 additional pesticides and aggressive PCa.

METHODS: We used Cox proportional hazards models, with age as the time scale, to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between ever use of individual pesticides and 883 cases of aggressive PCa (distant stage, poorly differentiated grade, Gleason score >/= 7, or fatal prostate cancer) diagnosed between 1993 and 2015. All models adjusted for birth year, state, family history of PCa, race, and smoking status. We conducted exposure-response analyses for pesticides with reported lifetime years of use.

RESULTS: There was an increased aggressive PCa risk among ever users of the organodithioate insecticide dimethoate (n = 54 exposed cases, HR = 1.37, 95% CI = 1.04, 1.80) compared to never users. We observed an inverse association between aggressive PCa and the herbicide triclopyr (n = 35 exposed cases, HR = 0.68, 95% CI = 0.48, 0.95), with the strongest inverse association for those reporting durations of use above the median (>/= 4 years; n = 13 exposed cases, HR=0.44, 95% CI=0.26, 0.77).

CONCLUSION: Few additional pesticides were associated with prostate cancer risk after evaluation of extended data from this large cohort of private pesticide applicators.

FULL TEXT

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