Bibliography Tag: agricultural health study

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