Interpreting NHANES biomonitoring data, cadmium
Interpreting NHANES biomonitoring data, cadmium
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DOI：
10.1016/j.toxlet.2010.04.022
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发表时间：
2010-09-15
影响因子：
3.5
通讯作者：
Fowler, Bruce A.
中科院分区：
文献类型：
--
作者：
Ruiz, Patricia;Mumtaz, Moiz;Fowler, Bruce A.
镉(Cd)自然存在于环境中，一般人主要通过饮食接触。慢性镉暴露是一个公共卫生问题，因为镉是一种已知的致癌物质；它在体内积累并导致肾脏损害。国家健康和营养检查调查(NHANES)测量了尿镉；2003-2004年NHANES调查周期在第四次关于人类接触环境化学品的国家报告中报告了2257名6岁及6岁以上的人的估计数字。作为翻译研究的一部分，为了使健康风险评估人员能够访问计算机化的模型，我们用伯克利麦当娜模拟语言重新编码了一个镉模型。这个模型被我们的计算毒理学实验室用来预测尿镉的排泄量。该模型很好地模拟了6岁至60岁以上的NHANES测量数据。在6-11岁的儿童中观察到尿镉排泄量的异常增加，然后持续单调地增加到70岁。在早期的研究中也观察到了这一点，这些研究可能与生命阶段有关，并可能是在这一生命阶段发生的解剖和生理变化的作用。在所有年龄组中，女性的尿镉排泄量大约是男性的两倍。该模型描述了镉在人体内的累积性质，并适应了在一生中观察到的暴露/摄取的变化。这样的模型可能对解释生物监测数据和风险评估有用。爱思唯尔爱尔兰有限公司出版。
Cadmium (Cd) occurs naturally in the environment and the general population's exposure to it is predominantly through diet. Chronic Cd exposure is a public health concern because Cd is a known carcinogen; it accumulates in the body and causes kidney damage. The National Health and Nutritional Examination Survey (NHANES) has measured urinary Cd; the 2003-2004 NHANES survey cycle reported estimates for 2257 persons aged 6 years and older in the Fourth National Report on Human Exposure to Environmental Chemicals. As part of translational research to make computerized models accessible to health risk assessors we re-coded a cadmium model in Berkeley Madonna simulation language. This model was used in our computational toxicology laboratory to predict the urinary excretion of cadmium. The model simulated the NHANES-measured data very well from ages 6 to 60+ years. An unusual increase in Cd urinary excretion was observed among 6-11-year-olds, followed by a continuous monotonic rise into the seventh decade of life. This observation was also made in earlier studies that could be life stage-related and a function of anatomical and phsysiological changes occurring during this period of life. Urinary excretion of Cd was approximately twofold higher among females than males in all age groups. The model describes Cd's cumulative nature in humans and accommodates the observed variation in exposure/uptake over the course of a lifetime. Such models may be useful for interpreting biomonitoring data and risk assessment. Published by Elsevier Ireland Ltd.