Freni S C, Phillips D L
Center for Environmental Health, Centers for Disease Control, Atlanta, GA 30333.
Environ Health Perspect. 1987 Oct;74:211-21. doi: 10.1289/ehp.8774211.
For a proper analysis of the potentially causal relationship between exposure to volatile organic chemicals (VOCs) in drinking water and health events, it is essential to know T1, the time when exposure started, and C = f(T), which is the change of the VOC concentration C as a function of time T and the total accumulated exposure (TAE) to VOCs to which an individual was exposed. In the typical situation of incidentally detected pollution of groundwater, no such information is available. This paper describes the development of a method for estimating T1, C = f(T), and TAE as part of an epidemiologic study of the health effects of VOC contamination of an aquifer serving public and private wells. Pooled test results of city wells, tested periodically since 1981, provided the data base for developing a statistical model for estimating C = f(T). This model was then applied to private wells, for which the data of only one water sample were available, to retrospectively estimate their T1. The best-fitting model was a multiple linear regression equation consisting of the natural logarithm of the VOC concentration as the response variable, with the time of sampling, the distance of the wells from the source (expressed as coordinates), the well depth, and the well capacity as determinants. The TAE was calculated by integrating the area under the time-concentration curve.
为了正确分析饮用水中挥发性有机化合物(VOCs)暴露与健康事件之间潜在的因果关系,了解暴露开始的时间T1以及C = f(T)(即VOC浓度C随时间T的变化以及个体所暴露的VOCs的总累积暴露量(TAE))至关重要。在偶然检测到地下水污染的典型情况下,此类信息无法获取。本文描述了一种估计T1、C = f(T)和TAE的方法的开发过程,该方法是对为公共和私人水井供水的含水层中VOC污染对健康影响的流行病学研究的一部分。自1981年以来定期检测的城市水井的汇总测试结果为开发估计C = f(T)的统计模型提供了数据库。然后将该模型应用于仅有一个水样数据的私人水井,以回顾性估计它们的T1。最佳拟合模型是一个多元线性回归方程,以VOC浓度的自然对数作为响应变量,采样时间、水井到污染源的距离(以坐标表示)、水井深度和水井容量作为决定因素。TAE通过对时间 - 浓度曲线下的面积进行积分来计算。