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

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.

Regulation of adipose tissue inflammation and systemic metabolism in murine obesity by polymer implants loaded with lentiviral vectors encoding human interleukin‐4

“…Each experimental arm (sham, empty implant, hIL‐4 implant) included eight mice before the exclusion of outliers. Statistical outliers were determined using the boxplot method previously described (Mandić‐Rajčević et al, 2019). Using this method, numerical data were first graphically analyzed, and outliers were determined as data points that were located outside 1.5 times the interquartile range above the upper quartile and below the lower quartile.…”

Establishing health-based biological exposure limits for pesticides: A proof of principle study using mancozeb

“…The low exposure/risk introduces an unavoidable degree of uncertainty in the calculation, due to extrapolating the trend of exposure and excretion over two orders of magnitude. The assessment of the internal dose from available body deposition data relied on dealing with several sources of variability that include different deposition in the body areas, different duration of pesticide permanence on the skin, and a generic number for skin absorption coefficient (Mandić-Rajčević and Colosio, 2019;Mandic-Rajcevic et al, 2019;SANCO, 2009). Technical improvements in each of these aspects will increase the accuracy of the approach and the assessment.…”

“…To improve the assessment of mancozeb deposition on the skin and the estimate of the absorbed dose, we examined the analytical results to identify and treat outliers. Outliers that could influence the estimate of the skin dose were identified and treated using the modified Z score according to our previously proposed and published procedure (Mandić-Rajčević and Colosio, 2019;Mandic-Rajcevic et al, 2019). This processing improved the correlation…”

Custom Outlier Detection for Electrical Energy Consumption Data Applied in Case of Demand Response in Block of Buildings

“…The same can be observed in the mathematical model of the median absolute deviation (MAD) [ 57 , 58 ] where the limitations are given by the threshold values from the median value. The threshold value chosen for Interquartile range (IQR) method testing is 1.5 [ 59 ] and for median is 3. The advantage of using the IQR and median absolute deviation (MAD) models is more related with ‘tracking’ and maintaining a permeant control spread that will identify the extreme values for most of the cases.…”