Bioaccumulation and health risk assessment of trace metal contamination in the musculature of the trahira fish (Hoplias malabaricus) from two neotropical rivers in southeastern Brazil

Fish are an important source of nutrition for humans, as their meat contains high amounts of proteins, fatty acids, vitamins, and essential metals [1]. In Brazil, an average of 4.7 kg of fish is consumed per capita/year. Southeast Brazil is the region that consumes the least amount of fish meat in the country, with fish meat representing 6.1 % of the population’s diet, of which, 23 % represents consumption from outside home. In addition, the rural areas consume 34.4 % more fish than the population living in urban areas of the country [2].

Brazil has an immense hydrographic structure, with the most extensive river network in the world, and having the greatest hydrological potential on the planet, which directly reflects in the complexity of structuring aquatic animal communities, where fish represent enormous diversity, with approximately 2500 species [3]. Due to the great diversity of hydrographic basins and of fish species, fishery (both industrial and artisanal) in Brazil is an important economic tool [4], which places the country in the fourth position in the ranking of the largest fishing countries in Latin America [5]. Artisanal fishing plays a fundamental role in Brazil fish production, being responsible for more than 50 % of landings [6] and can be divided into three categories: 1) professional artisanal fishing, focusing on commercialization, 2) subsistence artisanal fishing, supplying food for the fishermen and their families and 3) amateur/sport fishing, practiced only as tourism or leisure, and the fish cannot be commercialized [7].

Fishing activities develop over time, and there is also an increase in the anthropic pressure exerted on aquatic environments, both lotic and lentic. In Brazil, the unrestrained increase, diffusion, and little importance for environmental causes of other economic activities, such as the agricultural industry, for example, has caused irreparable damage, leading to the contamination of water bodies, including the organisms that lives in these environments [8], [9], [10].

Among the countless pollutants that reach water bodies, trace metals are extremely problematic because they can be very toxic even at lowest concentrations in the aqueous state [11]. Agricultural activities, and discharges of industrial and domestic sewage are the main sources of contamination in both lentic and lotic environments. In water, non-reactive or non-toxic forms of certain metals can be transformed into reactive or toxic forms, which in turn can directly affect life in water [11], being bioaccumulated or biomagnified trough food web, including fish. Since fish are at the top of the food chain, they can accumulate higher amounts of metals in their tissues, and this in turn becomes a public health problem, since humans can feed on contaminated tissue, leading to intoxication [12]. In this sense, detection techniques in environmental samples are extremely important in these types of studies and in order to obtain accurate results that reflect the real state of the environment even at the lowest levels of disturbance [13], [14], [15], [16].

Hoplias malabaricus (Bloch, 1794) (Characiformes: Herythrinidae) is a freshwater, carnivore, and top food chain predator. It occurs throughout South and Central America, especially in lentic environments. It is a fish well adapted to waters with high turbidity and low oxygen availability [17]. This fish has a highly appreciated and high-quality meat, which makes it very popular in fishing activities. It is estimated that up to 9 tons of fish of this genus are caught per year [18]. In this study, we aimed to evaluate the concentrations of trace metals in the muscle tissue of H. malabaricus and in the water of two rivers where this species occurs, the Jacaré-Pepira and Jacaré-Guaçú rivers, in southeastern Brazil, and to analyze if there is a risk of contamination by consumption by humans through the hazard coefficient.

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