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

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<middle dot>day-1. Notably, 6.7% of participants exhibited Hg levels that exceeded the oral reference dose (RfD) of 0.1 mu g<middle dot>kg-1 bw<middle dot>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 mu g<middle dot>g-1 (with two outlier values of 16.96 and 54.07 mu g<middle dot>g-1). The Hg levels in 86.85% of the population surpassed the reference value of 1 mu g<middle dot>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.