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验证在挪威大陆架上的石油开采平台上开发的适用于整个轮班时间的苯暴露经验模型。

Validation of a full-shift benzene exposure empirical model developed for work on offshore petroleum installations on the Norwegian continental shelf.

机构信息

Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.

Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.

出版信息

J Occup Environ Hyg. 2023 Oct;20(10):460-467. doi: 10.1080/15459624.2023.2242416. Epub 2023 Sep 8.

Abstract

Workers on offshore petroleum installations might be exposed to benzene, a carcinogenic agent. Recently, a full-shift benzene exposure model was developed based on personal measurements. This study aimed to validate this exposure model by using datasets not included in the model. The exposure model was validated against an internal dataset of measurements from offshore installations owned by the same company that provided data for the model, and an external dataset from installations owned by another company. We used Tobit regression to estimate GM (geometric mean) benzene exposure overall and for individual job groups. Bias, relative bias, precision, and correlation were estimated to evaluate the agreement between measured exposures and the levels predicted by the model. Overall, the model overestimated exposure when compared to the predicted exposure level to the internal dataset with a factor of 1.7, a relative bias of 73%, a precision of 0.6, a correlation coefficient of 0.72 ( = 0.019), while the Lin's Concordance Correlation Coefficient (CCC) was 0.53. The model underestimated exposure when compared to the external dataset with a factor of about 2, with a relative bias of -45%, a precision of 1.2, a correlation coefficient of 0.31 ( = 0.544), and a Lin's CCC of 0.25. The exposure model overestimated benzene exposure in the internal validation dataset, while the precision and the correlation between the measured and predicted exposure levels were high. Differences in measurement strategies could be one of the reasons for the discrepancy. The exposure model agreed less with the external dataset.

摘要

海上石油设施的工人可能会接触到苯,这是一种致癌物质。最近,根据个人测量结果开发了一种全班次苯暴露模型。本研究旨在使用未包含在模型中的数据集来验证该暴露模型。该暴露模型通过与内部数据集进行了验证,该数据集来自提供模型数据的同一家公司拥有的海上设施的测量结果,还与另一家公司拥有的设施的外部数据集进行了验证。我们使用 Tobit 回归来估计 GM(几何平均值)苯暴露总体水平和各个工作群体的暴露水平。偏差、相对偏差、精度和相关性用于评估测量暴露值与模型预测值之间的一致性。总的来说,与内部数据集相比,模型高估了暴露水平,预测值与实际值的比值为 1.7,相对偏差为 73%,精度为 0.6,相关系数为 0.72(=0.019),而林氏一致性相关系数(CCC)为 0.53。与外部数据集相比,模型低估了暴露水平,预测值与实际值的比值约为 2,相对偏差为-45%,精度为 1.2,相关系数为 0.31(=0.544),林氏 CCC 为 0.25。暴露模型对内部分数据集的苯暴露进行了高估,而测量值和预测值之间的精度和相关性较高。测量策略的差异可能是造成这种差异的原因之一。该暴露模型与外部数据集的一致性较差。

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