期刊
ANNALS OF OCCUPATIONAL HYGIENE
卷 55, 期 6, 页码 620-633出版社
OXFORD UNIV PRESS
DOI: 10.1093/annhyg/mer008
关键词
agriculture; captan; dermal exposure-pesticides; determinants of exposure; exposure assessment-mixed models; orchards; pesticide exposure; variance components
资金
- National Institute for Occupational Safety and Health
- National Institutes of Health, National Cancer Institute [Z01-CP010119]
- National Institute of Environmental Health Sciences [Z01-ES049030]
Methods: External exposure metrics included personal air, hand rinse, and dermal patch samples collected from each applicator on 2 days in 2002-2003. A 24-h urine sample was also collected. Exposure determinants were identified for each external metric using multiple linear regression models via the NLMIXED procedure in SAS. The AHS algorithm was adjusted, consistent with the identified determinants. Mixed-effect models were used to evaluate the correlation between the adjusted and unadjusted algorithm and urinary captan metabolite levels. Results: Consistent determinants of captan exposure were a measure of application size (kilogram of captan sprayed or application method), wearing chemical-resistant (CR) gloves and/or a coverall/suit, repairing spray equipment, and product formulation. Application by airblast was associated with a 4- to 5-fold increase in exposure as compared to hand spray. Exposure reduction to the hands, right thigh, and left forearm from wearing CR gloves averaged similar to 80%, to the right and left thighs and right forearm from wearing a coverall/suit by similar to 70%. Applicators using wettable powder formulations had significantly higher air, thigh, and forearm exposures than those using liquid formulations. Application method weights in the AHS algorithm were adjusted to nine for airblast and two for hand spray; protective equipment reduction factors were adjusted to 0.2 (CR gloves), 0.3 (coverall/suit), and 0.1 (both). Conclusions: Adjustment of application method, CR glove, and coverall weights in the AHS algorithm based on our exposure determinant findings substantially improved the correlation between the AHS algorithm and urinary metabolite levels.
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