Division of Environmental Health and Risk Management, School of Geography, Earth, and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom.
Environ Health Perspect. 2009 Oct;117(10):1571-9. doi: 10.1289/ehp.0900561. Epub 2009 Jun 23.
Direct measurement of exposure to volatile organic compounds (VOCs) via personal monitoring is the most accurate exposure assessment method available. However, its wide-scale application to evaluating exposures at the population level is prohibitive in terms of both cost and time. Consequently, indirect measurements via a combination of microenvironment concentrations and personal activity diaries represent a potentially useful alternative.
The aim of this study was to optimize a model of personal exposures (PEs) based on microenvironment concentrations and time/activity diaries and to compare modeled with measured exposures in an independent data set.
VOC PEs and a range of microenvironment concentrations were collected with active samplers and sorbent tubes. Data were supplemented with information collected through questionnaires. Seven models were tested to predict PE to VOCs in 75% (n = 370) of the measured PE data set, whereas the other 25% (n = 120) was used for validation purposes.
The best model able to predict PE with independence of measurements was based upon stratified microenvironment concentrations, lifestyle factors, and individual-level activities. The proposed model accounts for 40-85% of the variance for individual VOCs and was validated for almost all VOCs, showing normalized mean bias and mean fractional bias below 25% and predicting 60% of the values within a factor of 2.
The models proposed identify the most important non-weather-related variables for VOC exposures; highlight the effect of personal activities, use of solvents, and exposure to environmental tobacco smoke on PE levels; and may assist in the development of specific models for other locations.
通过个人监测直接测量挥发性有机化合物（VOC）暴露量是目前最准确的暴露评估方法。然而，由于成本和时间的限制，将其广泛应用于评估人群水平的暴露量是不可行的。因此，通过微环境浓度和个人活动日记的组合进行间接测量是一种潜在的有用替代方法。
本研究的目的是优化基于微环境浓度和时间/活动日记的个人暴露模型，并在独立数据集上比较模型预测的暴露量与实测暴露量。
使用主动采样器和吸附管采集 VOC 个人暴露量（PE）和一系列微环境浓度数据，并通过问卷调查收集补充信息。测试了 7 种模型，以预测 75%（n=370）实测 PE 数据集的 VOC 暴露量，而其余 25%（n=120）用于验证目的。
能够独立于测量预测 PE 的最佳模型是基于分层微环境浓度、生活方式因素和个体活动的模型。所提出的模型可以解释个体 VOC 暴露量的 40-85%的方差，并且对几乎所有 VOC 进行了验证，归一化平均偏差和平均分数偏差均低于 25%，并预测了 60%的个体值在 2 倍以内。
所提出的模型确定了 VOC 暴露的最重要的非天气相关变量；强调了个人活动、溶剂使用和环境烟草烟雾暴露对 PE 水平的影响；并可能有助于为其他地点开发特定模型。
