The association between biomarker-based exposure estimates for phthalates and demographic factors in a human reference population
The association between biomarker-based exposure estimates for phthalates and demographic factors in a human reference population
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DOI：
10.1289/ehp.02110405
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发表时间：
2002-04-01
影响因子：
10.4
通讯作者：
Portier, CJ
中科院分区：
文献类型：
--
作者：
Koo, JW;Parham, F;Portier, CJ
由于各种原因，使用生物标志物对环境暴露的总体估计可能很难获得，包括检测限度问题、关键地层采样不足、暴露和采样之间的时间、个体之间的差异、个人内部的差异以及发现和解释给定生物标志物的能力。在本文中，我们将统计似然、加权抽样和回归方法应用于生物标志物数据的分析。用这些方法分析了Blount等人报道的七种邻苯二甲酸酯的尿代谢物。在邻苯二甲酸盐数据的情况下，我们假设潜在的模型是对数正态分布，分布的平均值被定义为可能影响个体邻苯二甲酸盐水平的许多人口统计学变量的函数。人口统计变量包括年龄、性别、种族、居住地、家庭收入和教育水平。我们进行了两个分析：一个是非加权分析，其中邻苯二甲酸盐的分布是根据这些分布的平均值作为人口变量的函数来估计的；另一个是对总体人口的加权预测，其中根据人口变量在美国总体人口中的出现频率为人口子集分配了权重。我们使用统计测试来确定是否有任何人口统计学变量影响平均邻苯二甲酸盐水平。只受过高中教育的人比受过高中以上教育的人邻苯二甲酸二丁酯水平更高。在抽样前一个月家庭收入低于1,500美元和/或只受过高中教育的受试者，n-Buryl水平较高。邻苯二甲酸苄酯水平高于其他基团。邻苯二甲酸二(2-乙基己基)酯在男性和/或城市人口和/或家庭月收入低于1,500美元的人中较高。我们的发现表明，邻苯二甲酸盐的暴露和/或代谢可能存在显著的人口统计学差异，人类暴露于邻苯二甲酸盐的健康风险评估应考虑不同的潜在风险群体。
Population-based estimates of environmental exposures using biomarkers can be difficult to obtain for a variety of reasons, including problems with limits of detection, undersampling of key strata, time between exposure and sampling, variation across individuals, variation within individuals, and the ability to find and interpret a given biomarker. In this article, we apply statistical likelihoods, weighted sampling, and regression methods for censored data to the analysis of biomarker data. Urinary metabolites for seven phthalates, reported by Blount et al., are analyzed using these methods. In the case of the phthalates data, we assumed the underlying model to be a log-normal distribution with the mean of the distribution defined as a function of a number of demographic variables that might affect phthalate levels in individuals. Included as demographic variables were age, sex, ethnicity, residency, family income, and education level. We conducted two analyses: an unweighted analysis where phthalate distributions were estimated with changes in the means of these distributions as a function of demographic variables, and a weighted prediction for the general population in which weights were assigned for a subset of the population depending on the frequency of their demographic variables in the general U.S. population. We used statistical tests to determine whether any of the demographic variables affected mean phthalate levels. Individuals with only a high school education had higher levels of di-n-butyl phthalate than individuals with education beyond high school. Subjects who had family income less than $1,500 in the month before sampling and/or only high school education had higher levels of n-buryl. benzyl phthalate levels than other groupings. Di(2-ethylhexyl) phthalate was higher in males and/or in urban populations and/or in people who had family income less than $1,500 per month. Our findings suggest that there may be significant demographic variations in exposure and/or metabolism of phthalates and that health-risk assessments for phthalate exposure in humans should consider different potential risk groups.