Exploring Potential Human Health Risks Linked to Heavy Metal(Loid)s in Dietary Fishes: Utilizing Data-Driven and Computational Modelling Approaches.

Abstract

There are significant concerns about the risks to human health posed by metal(loid) contamination in dietary fishes in Bangladesh. Therefore, this study aimed to evaluate heavy metal(loid) contamination in fish and their associated health risks using published data from 2000 to 2022. Additionally, the safe limit of fish consumption was estimated using the target hazard quotient (THQ) followed by computational modelling and artificial neural networks (ANN). Results showed that freshwater and herbivorous fishes pose the least non-cancer risks, whereas saltwater and carnivorous fishes pose the highest non-cancer risks to Bangladeshi consumers. However, freshwater and omnivorous fish consumption pose the highest cancer risks compared to all studied metal(loid)s. In particular, among the heavy metal(loid)s, As, Cr, Hg, and Ni pose significant cancer and non-cancer risks to Bangladeshi consumers. On the contrary, the ANN and Decision tree regression (DTR) characterized the dataset, simulation model, or data testing condition, reaching 94.7% accuracy and allowing us to measure the safest fish consumption limit. The herbivorous fishes are less contaminated and allow greater consumption (175.09gday-1). Contrarily, the allowable intake rates of carnivorous and omnivorous fishes are 153.05 and 168.63gday-1, respectively. Besides, the safe consumption rate of saltwater fishes was 156.51gday-1, which was lower than freshwater (180.59gday-1) and euryhaline fishes (182.17gday-1). Therefore, this study will assist fish consumers in selecting less contaminated fish, ensuring safe consumption levels, and ultimately reducing health risks associated with metal(loid) contamination in fish.