Scholarlink

<p>Mercury (Hg) is a highly toxic heavy metal that presents a notable and worldwide threat to human health and the environment. The most direct method to evaluate the potential effects on human health due to Hg exposure is to monitor biological samples. When biological samples are limited, predictive models are valuable tools to estimate levels of Hg exposure. In this study, fish consumption data was used to compare two toxicokinetic models to predict Hg exposure in a coastal population in northwestern Mexico. To calculate daily Hg intake, 15 children, 42 women, and 18 men were surveyed regarding their fish consumption habits. The data were analyzed using deterministic and probabilistic models, and the results were validated by comparing them with the Hg levels in their hair. Fish consumption varied from 46 to 219&#xa0;g·day<sup>−1</sup>. Notably, 6.7% of participants exhibited Hg levels that exceeded the oral reference dose (RfD) of 0.1&#xa0;μg·kg<sup>−1</sup> bw·day<sup>−1</sup> and were thus considered to be at risk of adverse health effects. The average Hg concentration in hair among the sampled groups ranged from 1.59 to 4.42&#xa0;μg·g<sup>−1</sup> (with two outlier values of 16.96 and 54.07&#xa0;μg·g<sup>−1</sup>). The Hg levels in 86.85% of the population surpassed the reference value of 1&#xa0;μg·g<sup>−1</sup>. The predictions generated by the deterministic and probabilistic models based on the ingestion rate (<i>CRj</i>) closely mirrored the actual Hg levels in hair. We highlight the importance of mathematical models to predict the body burden of Hg, particularly when sampling resources are limited.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Dietary mercury exposure through fish consumption in a coastal community in northwestern Mexico: a comparison of toxicokinetic models

  • 期刊论文

  • 发表日期：

    2025年2月13日

查看全文
  • Nydia Zamora-Arellano,
  • Jorge Ruelas-Inzunza,
  • Pamela Spanopoulos-Zarco,
  • Miguel Betancourt-Lozano

摘要

Mercury (Hg) is a highly toxic heavy metal that presents a notable and worldwide threat to human health and the environment. The most direct method to evaluate the potential effects on human health due to Hg exposure is to monitor biological samples. When biological samples are limited, predictive models are valuable tools to estimate levels of Hg exposure. In this study, fish consumption data was used to compare two toxicokinetic models to predict Hg exposure in a coastal population in northwestern Mexico. To calculate daily Hg intake, 15 children, 42 women, and 18 men were surveyed regarding their fish consumption habits. The data were analyzed using deterministic and probabilistic models, and the results were validated by comparing them with the Hg levels in their hair. Fish consumption varied from 46 to 219 g·day−1. Notably, 6.7% of participants exhibited Hg levels that exceeded the oral reference dose (RfD) of 0.1 μg·kg−1 bw·day−1 and were thus considered to be at risk of adverse health effects. The average Hg concentration in hair among the sampled groups ranged from 1.59 to 4.42 μg·g−1 (with two outlier values of 16.96 and 54.07 μg·g−1). The Hg levels in 86.85% of the population surpassed the reference value of 1 μg·g−1. The predictions generated by the deterministic and probabilistic models based on the ingestion rate (CRj) closely mirrored the actual Hg levels in hair. We highlight the importance of mathematical models to predict the body burden of Hg, particularly when sampling resources are limited.