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农业农药施用者中异常值的识别方法及其对暴露评估的影响:一种建议方法及生物监测验证

Methods for the Identification of Outliers and Their Influence on Exposure Assessment in Agricultural Pesticide Applicators: A Proposed Approach and Validation Using Biological Monitoring.

作者信息

Mandić-Rajčević Stefan, Colosio Claudio

机构信息

Department of Health Sciences, University of Milan and International Centre for Rural Health of the Saints Paolo and Carlo Hospital, 20142 Milan, Italy.

出版信息

Toxics. 2019 Jul 12;7(3):37. doi: 10.3390/toxics7030037.

DOI:10.3390/toxics7030037
PMID:31336998
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6789726/
Abstract

The "patch" approach for skin exposure assessment can easily be combined with biological monitoring in real-life pesticide studies. Nevertheless, this approach is sensitive to outliers, with values markedly deviating from other members of the sample, which can result in a gross overestimation of exposure. This study aimed at developing methods for outlier identification and validating them while using biological monitoring. Twenty-seven workers applying mancozeb in Italian vineyards participated in this study. Their skin exposure was estimated while using the patch methodology, while ethylene-thiourea (ETU) was measured in the 24-h post-exposure urine as a biomarker of exposure. The outliers were detected using methods that were based on the multiplication of the median, the median absolute deviation, and boxplots. The detection rate varied between 2.3% and 17.3%. The estimated median skin exposure of 3.2 μg was reduced to 1.2 μg when the modified Z score was used. The highest reduction in the skin exposure was above 54 μg. The use of the modified Z score for outlier detection resulted in an increase in the correlation coefficient between the skin exposure and the urine ETU levels from 0.46 to 0.71, which suggested the validity of the approach. Future studies should standardize and improve the methods for pesticide exposure and risk assessment.

摘要

在实际的农药研究中,用于皮肤暴露评估的“贴片”方法可以很容易地与生物监测相结合。然而,这种方法对异常值很敏感,这些值明显偏离样本中的其他成员,这可能导致对暴露的严重高估。本研究旨在开发异常值识别方法,并在使用生物监测时对其进行验证。27名在意大利葡萄园施用代森锰锌的工人参与了这项研究。在使用贴片方法估算他们的皮肤暴露量的同时,将暴露后24小时尿液中的乙烯硫脲(ETU)作为暴露生物标志物进行测量。使用基于中位数乘法、中位数绝对偏差和箱线图的方法检测异常值。检测率在2.3%至17.3%之间变化。当使用修正Z分数时,估计的皮肤暴露中位数从3.2μg降至1.2μg。皮肤暴露量的最大降幅超过54μg。使用修正Z分数进行异常值检测导致皮肤暴露量与尿液ETU水平之间的相关系数从0.46增加到0.71,这表明该方法的有效性。未来的研究应规范和改进农药暴露和风险评估方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/84f478b4853e/toxics-07-00037-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/4e4aace50f09/toxics-07-00037-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/1e777a090256/toxics-07-00037-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/84f478b4853e/toxics-07-00037-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/4e4aace50f09/toxics-07-00037-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/1e777a090256/toxics-07-00037-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4a/6789726/84f478b4853e/toxics-07-00037-g003.jpg

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