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农业健康研究中果园农药施用者的克菌丹暴露情况及农药暴露算法评估

Captan exposure and evaluation of a pesticide exposure algorithm among orchard pesticide applicators in the Agricultural Health Study.

作者信息

Hines Cynthia J, Deddens James A, Jaycox Larry B, Andrews Ronnee N, Striley Cynthia A F, Alavanja Michael C R

机构信息

National Institute for Occupational Safety and Health, 4676 Columbia Parkway R-14, Cincinnati, OH 45226, USA.

出版信息

Ann Occup Hyg. 2008 Apr;52(3):153-66. doi: 10.1093/annhyg/men001. Epub 2008 Mar 6.

Abstract

Pesticide exposure assessment in the Agricultural Health Study (AHS) has relied upon two exposure metrics: lifetime exposure days and intensity-weighted lifetime exposure days, the latter incorporating an intensity score computed from a questionnaire-based algorithm. We evaluated this algorithm using actual fungicide exposure measurements from AHS private orchard applicators. Captan was selected as a marker of fungicide exposure. Seventy-four applicators from North Carolina and Iowa growing apples and/or peaches were sampled on 2 days they applied captan in 2002 and 2003. Personal air, hand rinse, 10 dermal patches, a pre-application first-morning urine and a subsequent 24-h urine sample were collected from each applicator per day. Environmental samples were analyzed for captan, and urine samples were analyzed for cis-1,2,3,6-tetrahydrophthalimide (THPI). Task and personal protective equipment information needed to compute an individual's algorithm score was also collected. Differences in analyte detection frequency were tested in a repeated logistic regression model. Mixed-effects models using maximum-likelihood estimation were employed to estimate geometric mean exposures and to evaluate the measured exposure data against the algorithm. In general, captan and THPI were detected significantly more frequently in environmental and urine samples collected from applicators who used air blast sprayers as compared to those who hand sprayed. The AHS pesticide exposure intensity algorithm, while significantly or marginally predictive of thigh and forearm captan exposure, respectively, did not predict air, hand rinse or urinary THPI exposures. The algorithm's lack of fit with some exposure measures among orchard fungicide applicators may be due in part to the assignment of equal exposure weights to air blast and hand spray application methods in the current algorithm. Some modification of the algorithm is suggested by these results.

摘要

农业健康研究(AHS)中的农药暴露评估依赖于两个暴露指标:终生暴露天数和强度加权终生暴露天数,后者纳入了根据基于问卷的算法计算得出的强度得分。我们使用AHS私人果园施药者的实际杀菌剂暴露测量值对该算法进行了评估。克菌丹被选为杀菌剂暴露的标志物。2002年和2003年,从北卡罗来纳州和爱荷华州种植苹果和/或桃子的74名施药者中抽取样本,在他们施用克菌丹的两天进行采样。每天从每个施药者收集个人空气样本、手部冲洗样本、10个皮肤贴片样本、施药前第一个晨尿样本以及随后的24小时尿液样本。对环境样本进行克菌丹分析,对尿液样本进行顺式-1,2,3,6-四氢邻苯二甲酰亚胺(THPI)分析。还收集了计算个人算法得分所需的任务和个人防护设备信息。在重复逻辑回归模型中测试分析物检测频率的差异。采用使用最大似然估计的混合效应模型来估计几何平均暴露量,并根据该算法评估实测暴露数据。总体而言,与手动喷雾者相比,在使用气力喷雾器的施药者收集的环境和尿液样本中,克菌丹和THPI的检测频率显著更高。AHS农药暴露强度算法虽然分别对大腿和前臂克菌丹暴露有显著或边际预测能力,但并未预测空气、手部冲洗或尿液中THPI的暴露情况。该算法在果园杀菌剂施药者中与某些暴露测量值不匹配,部分原因可能是当前算法对气力喷雾和手动喷雾施用方法赋予了相等的暴露权重。这些结果提示对该算法进行一些修改。

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