Assessing spatial fluctuations, temporal variability, and measurement error in estimated levels of disinfection by-products in tap water: implications for exposure assessment.
Assessing spatial fluctuations, temporal variability, and measurement error in estimated levels of disinfection by-products in tap water: implications for exposure assessment.
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发表时间：
2004
影响因子：
4.9
通讯作者：
E. Symanski;D. Savitz;P. Singer
中科院分区：
文献类型：
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作者：
E. Symanski;D. Savitz;P. Singer
目的：为了评估空间波动，时间变异性，以及由于在日常监测自来水样品和在同一分配系统内的家庭收集的水样中的消毒副产品水平的采样和分析的误差，用于暴露评估研究。方法应用混合效应模型来量化季节效应和三卤甲烷（THM）水平在家庭或地点之间相对于任何给定地点的季节内随时间变化的程度。在一项单独的分析中，还量化了由于采样和分析产生的测量误差而导致的总变异的比例。结果夏季THM水平高于其他季节。在两组THM测量之间观察到家庭内和家庭间变异成分的相对幅度差异，由于常规监测数据季节内差异导致的变异比例较大，由于暴露评估研究数据不同地点差异导致的变异比例较大。产生这种差异的原因可能是选择取样地点的战略不同，以及收集数据的时间不同。除溴二氯甲烷外，取样和分析造成的测量误差仅占THM水平总变化的一小部分。结论：在流行病学研究中，常规监测数据在分配暴露量方面的效用有限，因为这些数据可能无法代表整个分销系统中消毒副产品水平的空间变异性大小。测量误差在三卤甲烷水平的总变化中所占的比例相对较小，这表明随着时间的推移收集更多的样本，在每个采样地点收集较少的重复样本更有效，可能会改善对家庭暴露的估计。
AIMS To assess spatial fluctuations, temporal variability, and errors due to sampling and analysis in levels of disinfection by-products in routine monitoring tap water samples and in water samples collected in households within the same distribution system for an exposure assessment study. METHODS Mixed effects models were applied to quantify seasonal effects and the degree to which trihalomethane (THM) levels vary among households or locations relative to variation over time within seasons for any given location. In a separate analysis, the proportion of total variation due to measurement error arising from sampling and analysis was also quantified. RESULTS THM levels were higher in the summer relative to other seasons. Differences in the relative magnitude of the intra- and inter-household components of variation were observed between the two sets of THM measurements, with a greater proportion of the variation due to differences within seasons for the routine monitoring data and a greater proportion of the variation due to differences across locations for the exposure assessment study data. Such differences likely arose due to differences in the strategies used to select sites for sampling and in the time periods over which the data were collected. With the exception of bromodichloromethane, measurement errors due to sampling and analysis contributed a small proportion of the total variation in THM levels. CONCLUSIONS The utility of routine monitoring data in assigning exposure in epidemiological studies is limited because such data may not represent the magnitude of spatial variability in levels of disinfection by-products across the distribution system. Measurement error contributes a relatively small proportion to the total variation in THM levels, which suggests that gathering a greater number of samples over time with fewer replicates collected at each sampling location is more efficient and would likely yield improved estimates of household exposure.