HEALTH BENEFITS OF FISH CONSUMPTION

Fish and shellfish contain protein, long-chain omega-3 fatty acids, vitamins, minerals and trace elements such as calcium and magnesium (Tacon & Metian, Reference Tacon and Metian2013). Seafood has the highest concentration of long-chain omega-3 polyunsaturated fatty acids (PUFAs), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), of any foods (Tacon & Metian, Reference Tacon and Metian2013). EPA and DHA show beneficial associations with cardiovascular phenotypes including blood pressure (Campbell et al., Reference Campbell, Dickinson, Critchley, Ford and Bradburn2013), vascular endothelial function (Xin et al., Reference Xin, Wei and Li2012), arterial stiffness (Pase et al., Reference Pase, Grima and Sarris2011) and heart rate variability (Xin et al., Reference Xin, Wei and Li2013). Fish or fish oil intake is also associated with decreased weight and waist circumference (Bender et al., Reference Bender, Portmann, Heg, Hofmann, Zwahlen and Egger2014). Possible impacts of EPA and DHA on cholesterol in humans are unclear. Among persons with diabetes, fish oil supplementation may be associated with lower triglycerides and lower levels of very low density lipoprotein (VLDL) cholesterol, but with higher levels of low density lipoprotein (LDL) cholesterol (Hartweg et al., Reference Hartweg, Perera, Montori, Dinneen, Neil and Farmer2008). In dialysis patients, there are also associations of fish oil supplements with lower triglycerides, but also higher high density lipoprotein (HDL) cholesterol, and no association with LDL cholesterol (Zhu et al., Reference Zhu, Dong, Du, Zhang, Chen, Hu and Hu2014). However, the relationship of EPA and DHA to hard cardiovascular endpoints is less clear. A pooled meta-analysis of 68,680 fish oil supplement clinical trial participants, many of whom (more than half of the trials) had pre-existing cardiovascular disease and were being followed for a second event, did not show evidence for lower risk of mortality (from any cause), cardiac death, myocardial infarction or stroke (Rizos et al., Reference Rizos, Ntzani, Bika, Kostapanos and Elisaf2012). In contrast, many observational studies report a decrease in cardiovascular disease and all-cause mortality with higher fish oil intake (Wang et al., Reference Wang, Harris, Chung, Lichtenstein, Balk, Kupelnick, Jordan and Lau2006). The discrepancy between the clinical trial and the observational study results may reflect differences in study populations, or may suggest that another nutrient in fish (or an interacting cofactor in fish) is responsible for some of the cardiovascular benefits attributed to fish oils.

In addition to their possible relevance for cardiometabolic diseases, EPA and DHA fatty acids also may be associated with many other health outcomes. For example, observational studies suggest a lower risk of breast cancer with higher exposure (Zheng et al., Reference Zheng, Hu, Zhao, Yang and Li2013). DHA is essential for ophthalmological and neurological development (Uauy et al., Reference Uauy, Hoffman, Peirano, Birch and Birch2001; Janssen & Kiliaan, Reference Janssen and Kiliaan2014) and fish oil supplements may be associated with cognitive development among infants (Jiao et al., Reference Jiao, Li, Chu, Zeng, Yang and Zhu2014). Among women who previously had delivered a pre-term baby, fish oil supplements appeared to be associated with longer latency and greater weight at birth of the child but did not appear to be associated with differences in risk of another pre-term birth (Saccone & Berghella, Reference Saccone and Berghella2015).

Selenium, present in marine biota including fish and mussels (Outzen et al., Reference Outzen, Tjønneland, Larsen, Andersen, Christensen, Overvad and Olsen2015), has biological effects that are dose-dependent: at low doses, selenium is an essential nutrient used in selenoproteins such as glutathione peroxidase (Barceloux, Reference Barceloux1999), but at higher doses, selenium might be toxic to a range of animals including humans (Barceloux, Reference Barceloux1999; Hoffman, Reference Hoffman2002; Lemly, Reference Lemly2002; Adams et al., Reference Adams, Brix, Edwards, Tear, DeForest and Fairbrother2003; Ackerman & Eagles-Smith, Reference Ackerman and Eagles-Smith2009; Rigby et al., Reference Rigby, Deng, Grieb, Teh and Hung2010; Hladun et al., Reference Hladun, Kaftanoglu, Parker, Tran and Trumble2013; Thomas & Janz, Reference Thomas and Janz2014), although the dose-response of selenium toxicity differs across animal species (Ackerman & Eagles-Smith, Reference Ackerman and Eagles-Smith2009). In humans, the health effects of selenium (total selenium and selenium species) are controversial, with ongoing research into possible elevations or decreases in risk of various health outcomes according to selenium intake (Sabino et al., Reference Sabino, Stranges and Strazzullo2013). A recent Cochrane review (a comprehensive review in medical sciences that aims to summarize published and unpublished data on a topic) of selenium and cancer prevention found heterogeneous studies furnishing no overall evidence that selenium reduces cancer risk (Vinceti et al., Reference Vinceti, Dennert, Crespi, Zwahlen, Brinkman, Zeegers, Horneber, D'Amico and Del Giovane2014).

HAZARDS OF MERCURY

Although seafood provides important nutritional benefits, there may also be hazards from contaminants such as mercury. Neurological impacts of high methylmercury exposure were described in mass poisoning events in Minamata Bay, Japan (Harada, Reference Harada1995) from consumption of seafood contaminated by effluent from a chlor-alkali facility. ‘Minamata disease’ was characterized by deficits in sensation, vision, hearing, coordination (ataxia) and other problems associated with neurological function (Eto et al., Reference Eto, Takizawa, Akagi, Haraguchi, Asano, Takahata and Tokunaga1999; Uchino et al., Reference Uchino, Hirano, Satoh, Arimura, Nakagawa and Wakamiya2005). Children who had high in utero exposures suffered many neurotoxic effects including cerebral palsy, mental retardation, sensorimotor dysfunction and low birth weight (Chapman & Chan, Reference Chapman and Chan2000; Karagas et al., Reference Karagas, Choi, Oken, Horvat, Schoeny, Kamai, Cowell, Grandjean and Korrick2012). At lower doses, the neurological effects of methylmercury are less clear (Axelrad et al., Reference Axelrad, Bellinger, Ryan and Woodruff2007; Karagas et al., Reference Karagas, Choi, Oken, Horvat, Schoeny, Kamai, Cowell, Grandjean and Korrick2012).

Neurodevelopmental toxicity of mercury

Methylmercury neurotoxicity from consumption of seafood has been the focus of birth cohorts in the Faroe Islands, Seychelles and elsewhere (Table 1). In the Faroe Islands, where much of the mercury was acquired from consumption of marine mammals contaminated by organochlorines, there was an inverse association between mercury in cord blood and children's performance on developmental tests (Grandjean et al., Reference Grandjean, Weihe, Burse, Needham, Storr-Hansen, Heinzow, Debes, Murata, Simonsen, Ellefsen, Budtz-Jørgensen, Keiding and White2001, Reference Grandjean, Weihe, Debes, Choi and Budtz-Jørgensen2014). However, in the Seychelles, where much of the mercury was from fish, overall associations between foetal exposure to mercury and neurodevelopmental impairments were generally not observed (Carocci et al., Reference Carocci, Rovito, Sinicropi and Genchi2014). However, at 9 years of age there appeared to be possible differences in fine motor function at higher levels of mercury exposure (Davidson et al., Reference Davidson, Myers, Weiss, Shamleye and Cox2006; van Wijngaarden et al., Reference van Wijngaarden, Beck, Shamlaye, Cernichiari, Davidson, Myers and Clarkson2006; Mergler et al., Reference Mergler, Anderson, Chan, Mahaffey, Murray, Sakamoto and Stern2007), and evidence for interactions between fatty acids and mercury for cognitive processes (Strain et al., Reference Strain, McAfee, van Wijngaarden, Thurston, Mulhern, McSorley, Watson, Love, Smith, Yost, Harrington, Shamlaye, Henderson, Myers and Davidson2015). Emerging research suggests that genetic polymorphisms and epigenetic processes may account for some of the inter-individual variations of health effects given exposures (reviewed in Basu et al., Reference Basu, Goodrich and Head2014). A recent systematic review examined the associations between exposure to methylmercury from seafood consumption and developmental neurotoxicity from 164 studies in 43 countries and found that mercury might be impacting the health of Arctic and riverine populations near gold mining sites, and might also be relevant for public health in highly populated coastal regions (Sheehan et al., Reference Sheehan, Burke, Navas-Acien, Breysse, McGready and Fox2014).

Table 1.

Major cohort studies examining early-life methylmercury (MeHg) and total mercury (Hg) exposure and neurodevelopment in children. IQR, inter-quartile range (25th to 75th percentile).

IQR, inter-quartile range (25th and 75th percentiles of distribution).

CONCENTRATIONS OF EPA + DHA

Variability up to 128-fold has been documented in EPA and DHA levels across fish species (Gladyshev et al., Reference Gladyshev, Sushchik and Makhutova2013). EPA and DHA contents in aquatic animals depend on both taxonomic and ecological factors (Makhutova et al., Reference Makhutova, Sushchik, Gladyshev, Ageev, Pryanichnikova and Kalachova2011; Gladyshev et al., Reference Gladyshev, Lepskaya, Sushchik, Makhutova, Kalachova, Malyshevskaya and Markevich2012b; Lau et al., Reference Lau, Vrede, Pickova and Goedkoop2012); other factors such as an anthropogenic pollution (Gladyshev et al., Reference Gladyshev, Anishchenko, Sushchnik, Kalacheva, Gribovskaya and Ageev2012a) may also be important. Research on the possible impacts of fish health status on fish fatty acid content is limited, but suggests the relationships may be complex and organism-specific. In a recent experiment with cultured puffer fish (Fugu rubripes) with or without Trichodina infection, flat fish (Paralichthys olivaceus) with or without streptococcus infection, yellowtail (Seriola quinqueradiata) with or without jaundice, and amberjack (Seriola purpurascens) with or without Photobacterium damselae sp. piscicida, there was not a significant difference by fish disease status in the overall fish fatty acid composition in fish livers; however, liver DHA was significantly higher in the diseased fish than healthy fish for flat fish, yellowtail and amberjack (Tanaka et al., Reference Tanaka, Shigeta, Sugiura, Hatate and Matsushita2014). There is also growing interest in how oxidative stress in fish may affect fish lipids (Tanaka & Nakamura, Reference Tanaka and Nakamura2012; Tanaka et al., Reference Tanaka, Shigeta, Sugiura, Hatate and Matsushita2014).

One objective for our review is to summarize data on EPA and DHA across fish populations. To identify EPA and DHA content of diverse marine fish species, including anadromous fish, we queried Web of Science, Core Collection on 2 October 2014 for ‘fatty acid AND content AND fish AND marine’ (Table 2). Unfortunately, most studies report EPA and DHA as per cent of total fatty acids, and do not provide quantitative information on contents of these PUFA in mass units per fish portion (Gladyshev et al., Reference Gladyshev, Sushchik, Gubanenko, Demirchieva and Kalachova2007, Reference Gladyshev, Lepskaya, Sushchik, Makhutova, Kalachova, Malyshevskaya and Markevich2012b; Huynh & Kitts, Reference Huynh and Kitts2009). In this manuscript, we review data from 10 studies reporting direct measurements of EPA and DHA contents in wild fish biomass obtained using internal standards in chromatography (using capillary columns) over two recent decades. These had slightly different methodologies. For small fish, less than 35 cm (e.g. sardine or capelin), the fish were analysed whole (Huynh & Kitts, Reference Huynh and Kitts2009). Larger fish species (e.g. salmon) were sampled by dissecting muscle tissue (filets without skin), usually under dorsal fin (e.g. Gladyshev et al., Reference Gladyshev, Sushchik, Gubanenko, Demirchieva and Kalachova2006, Reference Gladyshev, Sushchik, Gubanenko, Demirchieva and Kalachova2007, Reference Gladyshev, Lepskaya, Sushchik, Makhutova, Kalachova, Malyshevskaya and Markevich2012b; Huynh & Kitts, Reference Huynh and Kitts2009; Kitson et al., Reference Kitson, Patterson, Izadi and Stark2009; Abd Aziz et al., Reference Abd Aziz, Azlan, Ismail, Alinafiah and Razman2013; Sahari et al., Reference Sahari, Farahani, Soleimanian and Javadi2014). In some studies (Chuang et al., Reference Chuang, Bulbul, Wen, Glew and Ayaz2012) ventral muscles were sampled. In other studies both small and large fish were taken whole, e.g. ground and homogenized (Castro-Gonzalez et al., Reference Castro-Gonzalez, Maafs-Rodriguez, Silencio-Barrita, Galindo-Gomez and Perez-Gil2013). Some authors did not report the sampling in detail (Garcia-Moreno et al., Reference Garcia-Moreno, Perez-Galvez, Morales-Medina, Guadix and Guadix2013).

Table 2.

Content of eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids (mg g⁻¹, wet weight) in various wild fish species, their types of habitat (H1: p, pelagic, bp, benthopelagic, d, demersal; H2: c, cold waters, t, temperate waters; w, warm waters) and size (cm). Orders and species are ranged by EPA + DHA content values.

The resulting data set includes 63 fish species across 11 orders (Table 2). Since PUFA contents in aquatic animals are known to depend on both phylogenetic and ecological factors (Makhutova et al., Reference Makhutova, Sushchik, Gladyshev, Ageev, Pryanichnikova and Kalachova2011; Gladyshev et al., Reference Gladyshev, Lepskaya, Sushchik, Makhutova, Kalachova, Malyshevskaya and Markevich2012b; Lau et al., Reference Lau, Vrede, Pickova and Goedkoop2012), fish species were organized by their EPA and DHA values within taxonomic orders. Putative effects of ecological (habitat) factors were taken into account by dividing the fish species into pelagic, benthopelagic and demersal, as well as by category of water temperature of their habitat, i.e. cold-water, temperate and warm-water (tropical) species. Common size of the fish species was used as a proxy of their trophic level, although this is an imperfect surrogate.

Values of EPA + DHA concentration in the 63 fish species varied from 25.60 mg g⁻¹ (sardine Sardinops sagax, order Clupeiformes) to 0.04 mg g⁻¹ (spotted weakfish Cynoscion nebulosus, order Perciformes) (Table 2). Clupeiformes had the highest median and maximum values of EPA + DHA contents, followed by Salmoniformes, while Perciformes, Scorpaeniformes and Gadiformes and miscellaneous had nearly similar median values (Figure 1). Nevertheless, ranges of values for EPA + DHA content of all orders overlapped in minimum values (Figure 1, Table 2). Thus, all orders, including Clupeiformes, have species with comparatively low content of EPA and DHA.

Fig. 1.

Contents of eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA) in fish orders: minimum, maximum and median values and quartiles. Number of species, N: order Clupeiformes, N = 9; order Salmoniformes, N = 3; order Perciformes, N = 36; order Scorpaeniformes, N = 3; order Gadiformes, N = 4; miscellaneous (orders Osmeriformes, Pleuronectiformes, Siluriformes, Mugiliformes, Beloniformes and Myliobatiformes), N = 8.

Interpretation of these results may be complicated by measurement error introduced by differing methods used for fish sampling and analysis, but some broad patterns in the data are interesting. Analysis of published EPA + DHA values found no statistically significant effect of type of habitat (pelagic, benthopelagic and demersal), or temperature of habitat, or their interaction on the PUFA content in fish. To visualize the results of ANOVA, a two-dimensional graph of the PUFA content in the groups of species was created (Figure 2). Since EPA + DHA contents in benthopelagic species overlapped completely with those of pelagic and demersal species, they were not included in the depicted groups. In addition, there were only six cold water species amongst pelagic, benthopelagic and demersal, which were joined in one group. The graph illustrates that EPA and DHA values of all the groups, pelagic temperate water, pelagic warm water, demersal temperate water, demersal warm water and cold water species, overlapped nearly completely.

Fig. 2.

Areas of eicosapentaenoic acid (EPA) vs docosahexaenoic acid (DHA) A levels in fish species from diverse habitats: pelagic warm water species (number of species, N = 17, violet), pelagic temperate water species (N = 10, black), demersal warm water species (N = 15, green), demersal temperate water species (N = 10, blue) and cold water species (N = 6, red).

This analysis of available data did not identify a strong predictor for EPA and DHA contents in fish. Temperature, for example, had limited impact: the contents of EPA + DHA in three pelagic planktivorous Clupeiformes with nearly identical sizes: sardine Sardinops sagax from temperate waters, shad Hilsa macrura from warm waters and herring Clupea harengus from cold waters were all similar (Table 2). Moths et al. (Reference Moths, Dellinger, Holub, Ripley, McGraw and Kinnunen2013) analysed freshwater fish from the Great Lakes as well as 99 other species from freshwater and marine systems documented in seven other studies. As in this study, Moths et al. (Reference Moths, Dellinger, Holub, Ripley, McGraw and Kinnunen2013) found that for marine systems, there was no relationship between latitude and omega-3 fatty acid composition of fish. However, in temperate climates, marine fish had higher omega-3/6 ratios than freshwater fish and for freshwater fish alone, there were higher omega-3 fatty acids in temperate fish as compared with tropical fish. While this study was based on relatively few datasets and many different species, it suggests some interesting patterns. For marine zooplankton, Kattner & Hagen (Reference Kattner, Hagen, Arts, Kainz and Brett2009) did not find significant differences in latitudinal distribution of EPA and DHA levels. Since zooplankton are the main food of these three planktivorous fish species from different latitudes, Kattner & Hagen's (Reference Kattner, Hagen, Arts, Kainz and Brett2009) findings for zooplankton are consistent with those for the planktivorous fish. Thus, more specific characteristics of diverse aquatic ecosystems, such as levels of primary production of PUFA and the efficiency of their transfer through trophic chains (Gladyshev et al., Reference Gladyshev, Sushchik, Anishchenko, Makhutova, Kolmakov, Kalachova, Kolmakova and Dubovskaya2011), are likely to be contributing factors for EPA and DHA content of given fish species. In these large meta-analyses, many environmental and fish specific variables may obscure the potential effects of individual environmental factors such as temperature or trophic level, or pharmacokinetic compartment differences of lipids across fish tissues. More research directed to effects of fish phylogenetics, ecological niche, type of habitat, food quality and other possible determinants is needed to be able to predict EPA and DHA contents, particularly in marine fish.

Studies of fish from field sampling, particularly with heterogeneous methodology, are not conducive to investigating the mechanistic sources of difference between populations living in different environmental settings. In contrast to the analysis of metadata for fish fatty acids above, experimental laboratory studies suggest that fatty acid concentrations in plankton and fish may be influenced in part by the food and temperature environments to which they are exposed. Numerous studies have shown that EPA and PUFAs increase in cells grown at lower temperatures and saturated fatty acids decrease (Thompson et al., Reference Thompson, Guo, Harrison and Whyte1992; Jiang & Gao, Reference Jiang and Gao2004; Fuschino et al., Reference Fuschino, Guschina, Dobson, Yan, Harwood and Arts2011; Teoh et al., Reference Teoh, Phang and Chu2013). In addition, some fish either naturally occurring or cultured have higher concentrations of fatty acids when grown in colder temperatures. Fish need to adjust membrane fluidity for metabolic function in fluctuating temperatures (homeoviscous adaptation) and they do this by changing the concentrations and composition of individual fatty acids and sterols in cell membranes (Sinensky, Reference Sinensky1974; Snyder et al., Reference Snyder, Schregel and Wei2012). Several experimental studies show differences in fatty acid concentrations in fish exposed to different temperatures. Experiments with juvenile Atlantic salmon at two temperatures (14 and 19°C) found that n-3, n-5 and total fatty acids were higher in fish raised in colder water (Arts et al., Reference Arts, Palmer, Skiftesvik, Jokinen and Browman2012). Another study on cultured Atlantic salmon found that the temperature effect was dependent on the type of oil in their food; temperature effects were more pronounced in fish fed copepod oil diets than fish oil diets (Bogevik et al., Reference Bogevik, Henderson, Mundheim, Olsen and Tocher2011). Another study found the digestibility of the lipids in Atlantic salmon to increase with increasing rearing temperatures suggesting that while colder temperatures may favour higher fatty acid concentrations, they may be less digestible than at warmer temperatures (Huguet et al., Reference Huguet, Norambuena, Emery, Hermon and Turchini2015). Laurel et al. (Reference Laurel, Copeman and Parrish2012) found that lower temperatures also favoured increases in unsaturated fatty acids in newly hatched Pacific cod larvae but relative amounts of essential fatty acids did not change with temperature. Similarly, n-3 and n-6 fatty acids decreased with increased temperatures in eggs and larvae of the marine fish, Inimicus japonicas (Wen et al., Reference Wen, Huang, Chen and Feng2013). Thus, there are a range of experimental studies supporting the role of temperature and potentially diet determining fatty acid composition in aquatic plankton and fish. They suggest that colder temperatures result in higher amounts and differing quality of fatty acids. However, the disparity between patterns observed in experimental and field-based studies should be further investigated.

VARIABILITY IN FISH MERCURY CONCENTRATIONS

One of the major challenges in managing human exposure to mercury from fish consumption is that fish mercury concentrations are highly variable. Numerous studies have measured broad differences in mercury content across different finfish and shellfish taxa (Sunderland, Reference Sunderland2007; Karimi et al., Reference Karimi, Fitzgerald and Fisher2012). A recent review estimated that mercury content within a given taxon can also be highly variable, ranging from 0.3–2.4 orders of magnitude, depending on the taxon (Karimi et al., Reference Karimi, Fitzgerald and Fisher2012). This variability poses a challenge to estimating mercury exposure from seafood consumption, and makes it difficult to quantify the risk associated with consuming specific fish taxa.

Numerous studies have shown that body size, age, trophic level and food source of fish are related to concentrations of methylmercury and the per cent of total mercury that is methylmercury (Chen et al., Reference Chen, Dionne, Mayes, Ward, Sturup and Jackson2009; Piraino & Taylor, Reference Piraino and Taylor2009). Across species, body size can be more strongly correlated with mercury concentration than trophic level (Karimi et al., Reference Karimi, Frisk and Fisher2013). In general, larger fish across and within species have higher concentrations of methylmercury because larger fish eat higher trophic level prey and are older and have had a longer time to accumulate mercury (Cossa et al., Reference Cossa, Harmelin-Vivien, Mellon-Duval, Loizeau, Averty, Crochet, Chou and Cadiou2012; Storelli and Barone, Reference Storelli and Barone2013). However, some studies have found that mercury concentration is more strongly correlated with age than length or weight (Braune, Reference Braune1987; Burger & Gochfeld, Reference Burger and Gochfeld2011). For example, the size of Bluefin tuna is not related to mercury concentration (Burger & Gochfeld, Reference Burger and Gochfeld2011) and Atlantic herring in the Arctic show relationships at 3–5 years of age but a decrease at 1–2 years of age due to growth dilution (Braune, Reference Braune1987). While there are clear positive relationships between total mercury and fish size and fish age, there is still variability in total mercury concentrations that is not explained by those two variables as well as the presence of interspecific and intraspecific variability (Tremain & Adams, Reference Tremain and Adams2012). Some of this unexplained variability likely comes from the food source and geographic range of the fish. Fish that have more pelagic than benthic food sources appear to bioaccumulate higher concentrations of mercury (Power et al., Reference Power, Klein, Guiguer and Kwan2002; Chen et al., Reference Chen, Dionne, Mayes, Ward, Sturup and Jackson2009; Karimi et al., Reference Karimi, Frisk and Fisher2013). Not surprisingly, fish that are exposed to higher water and sediment concentrations also have higher tissue concentrations of mercury (Lowery & Garrett, Reference Lowery and Garrett2005; Chen et al., Reference Chen, Dionne, Mayes, Ward, Sturup and Jackson2009; Gehrke et al., Reference Gehrke, Blum and Marvin-DiPasquale2011; Taylor et al., Reference Taylor, Linehan, Murray and Prell2012; Chen et al., Reference Chen, Lai, Chen, Hsu, Hung and Chen2014). However, levels of mercury may vary between similar species in a small geographic area and by tissue within a fish (Bank et al., Reference Bank, Chesney, Shine, Maage and Senn2007). A recent study also suggests increases in methylmercury bioaccumulation in fish experiencing warmer temperatures (Dijkstra et al., Reference Dijkstra, Buckman, Ward, Evans, Dionne and Chen2013). Overall, these studies show that fish size, age, trophic level, food source and geographic region each influence fish mercury content, with no strict rules for which of these factors explains the largest portion of mercury variability. While agencies such as the Food and Drug Administration (FDA) in the USA monitor mercury in marine fish consumed by humans, they do not report fish sizes or geographic location, both of which are extremely important when looking at mercury bioaccumulation.

SELENIUM AND MERCURY CONCENTRATIONS IN FISH

There is a long-running interest in nutrient-toxicant interactions between mercury and selenium (Ganther et al., Reference Ganther, Goudie, Sunde, Kopicky, Wagner, Oh and Hoekstra1972). Although recent evidence suggests possible synergistic interactions between mercury and selenium for fish development (Penglase et al., Reference Penglase, Hamre and Ellingsen2014), the weight of evidence suggests antagonistic interactions in which selenium mediates mercury toxicokinetics (reviewed in Peterson et al., Reference Peterson, Ralston, Whanger, Oldfield and Mosher2009). Selenomethionine increases mercury elimination in zebrafish (Danio rerio) (Yamashita et al., Reference Yamashita, Yamashita, Suzuki, Kani, Mizusawa, Imamura, Takemoto, Hara, Hossain, Yabu and Touhata2013; Amlund et al., Reference Amlund, Lundebye, Boyle and Ellingsen2015), shrimp (Bjerregaard & Christensen, Reference Bjerregaard and Christensen2012) and goldfish (Carassius auratus) (Bjerregaard et al., Reference Bjerregaard, Fjordside, Hansen and Petrova2012); selenite, and seleno-cysteine also increased mercury elimination in goldfish and shrimp. In humans, dietary organic selenium can increase mercury elimination (Li et al., Reference Li, Dong, Chen, Li, Gao, Qu, Wang, Fu, Zhao and Chai2012). Ralston and colleagues report that selenium not only ameliorates the toxic effects of methylmercury by sequestering methylmercury and reducing its bioavailability to organisms, but mercury and selenium may also have physiologically important interactions mediated by other mechanisms (Ralston et al., Reference Ralston, Blackwell and Raymond2007; Ralston & Raymond, Reference Ralston and Raymond2010). Based on rat data, Ralston (Reference Ralston2008) suggests that where the selenium to mercury molar ratio exceeds 1:1, there is adequate selenium to counter mercury toxicity. However, this has not been clearly demonstrated in humans. In recent trout (Salmo trutta) studies in a Norwegian lake, the selenium to mercury molar ratio was a better predictor of trout metallothionein levels than was either selenium or mercury (Sørmo et al., Reference Sørmo, Ciesielski, Øverjordet, Lierhagen, Eggen, Berg and Jenssen2011). However, human studies and clinical trials for selenium demonstrate mixed and inconclusive results for cardiovascular effects of methylmercury and selenium (Mozaffarian, Reference Mozaffarian2009). It has been suggested that mercury cardiovascular toxicity may be modified by selenium intake (Cooper et al., Reference Cooper, Rader and Ralston2007; Khan & Wang, Reference Khan and Wang2009; Mozaffarian, Reference Mozaffarian2009). This might arise through selenium impacts on mercury kinetics (Huang et al., Reference Huang, Strathe, Fadel, Johnson, Lin, Liu and Hung2013) or through impacts on oxidative stress mediators of mercury toxicity (Kaneko & Ralston, Reference Kaneko and Ralston2007; Ralston et al., Reference Ralston, Blackwell and Raymond2007; Farina et al., Reference Farina, Aschner and Rocha2011; Alkazemi et al., Reference Alkazemi, Egeland, Roberts Ii, Chan and Kubow2013; Drescher et al., Reference Drescher, Dewailly, Diorio, Ouellet, Sidi, Abdous, Valera and Ayotte2014), although evidence for the oxidative stress mediation hypotheses is ambiguous (Belanger et al., Reference Belanger, Mirault, Dewailly, Berthiaume and Julien2008). Selenium-mercury interactions may also be relevant for neurodevelopmental outcomes (Choi et al., Reference Choi, Budtz-Jørgensen, Jørgensen, Steuerwald, Debes, Weihe and Grandjean2007).

In recent years due to the interest in selenium to mercury molar ratios, a number of studies have assessed mercury and selenium concentrations and the selenium to mercury molar ratios for a variety of fish species from field samples as well as fish purchased from supermarkets (Burger et al., Reference Burger, Stern and Gochfeld2005, Reference Burger, Gochfeld and Fote2013; Burger & Gochfeld, Reference Burger and Gochfeld2011, Reference Burger and Gochfeld2012; Gochfeld et al., Reference Gochfeld, Burger, Jeitner, Donio and Pittfield2012; Karimi et al., Reference Karimi, Frisk and Fisher2013, Reference Karimi, Fisher and Meliker2014). The relationship between body size and selenium to mercury molar ratios vary with species, tissues and geographic location. Selenium to mercury molar ratios decreased with size of fish for yellowfin tuna and windowpane flounder in Delaware Bay and a wide variety of species in the Aleutians (Burger & Gochfeld, Reference Burger and Gochfeld2011, Reference Burger and Gochfeld2012). Some individuals of most of the 15 species studied in the Aleutians had ratios less than 1.0, where older, larger, higher trophic level fish had the lowest ratios. This was the result of mercury concentrations increasing with fish size but selenium concentrations not increasing with size. While selenium to mercury molar ratios were negatively correlated with fish length for bluefish, the ratios were lower for white muscle tissue, the portion of the fish that humans consume. In a study of 19 species off the coast of New Jersey (USA), (Burger & Gochfeld, Reference Burger and Gochfeld2011) mercury and selenium were positively related for five species and negatively related for two species, and across all species, selenium had no consistent relationship with length. However, for most species tested across all of these studies, the ratios were greater than 1.0, although 20% of the striped bass caught by trawling off the New Jersey coast had molar ratios of less than 1.0 (Gochfeld et al., Reference Gochfeld, Burger, Jeitner, Donio and Pittfield2012).

In general, studies of selenium to mercury molar ratios have found that mercury concentrations were positively related to fish length and trophic level but selenium concentrations were not, and selenium to mercury molar ratios are more strongly related to mercury content than selenium content (Karimi et al., Reference Karimi, Frisk and Fisher2013). This reflects the fact that mercury more strongly accumulates in the body, and biomagnifies through the food chain compared with selenium (Karimi et al., Reference Karimi, Frisk and Fisher2013). These findings are consistent with lower efflux (loss) rates of methylmercury than selenium, because lower efflux rates lead to greater bioaccumulation over time as body size increases (Karimi et al., Reference Karimi, Fisher and Folt2010). However, bivalves (e.g. clams, mussels and oysters) are known to be relatively efficient selenium accumulators (Stewart et al., Reference Stewart, Luoma, Schlekat, Doblin and Hieb2004; Presser & Luoma, Reference Presser and Luoma2010), and have higher selenium concentrations than finfish (Karimi et al., Reference Karimi, Frisk and Fisher2013). It also appears that the mean selenium to mercury molar ratio declines with mean size of fish species and with individual fish size within a species. Both suggest that larger, predatory fish as well as the largest individuals of many species have lower selenium to mercury molar ratios and may not provide selenium protection against mercury toxicity for human seafood consumers (although selenium may be available in their diet from other sources). Moreover, smaller fish of a given species may provide greater protective benefits suggesting that those age classes that reside in more estuarine and coastal environments may present lower human health hazards (Burger et al., Reference Burger, Gochfeld and Fote2013). However, the variability of selenium to mercury molar ratios found within and across species makes it difficult to use this ratio in risk assessment, risk management and risk communication at the present time. Most governmental organizations that develop fish consumption advisories do not have the data on both mercury and selenium levels in individual fish which are necessary to determine the selenium to mercury molar ratio variation within and across species. It is difficult for risk assessors to develop advisories that are protective without an estimate of this variability.

FISH THAT OPTIMIZE POTENTIAL BENEFITS VS RISKS

Recent research is beginning to address the need to quantify the overall nutritional and toxicological value of different types of fish and shellfish based on concentrations of multiple nutrients and contaminants in edible tissues. A recent study found unique, relative concentrations of mercury, omega-3 fatty acids, and selenium, or mercury-nutrient signatures, across seafood taxa (Figure 3, Karimi et al., Reference Karimi, Fisher and Meliker2014). Specifically, salmon and forage fish (herring, anchovies and sardines) are high in EPA and DHA compared with other seafood (Figure 3). In contrast, predatory fish have higher mercury concentrations than lower trophic level fish but nutrient concentrations do not appear to differ as strongly by trophic level. Karimi et al. (Reference Karimi, Fisher and Meliker2014) found that these distinct mercury–nutrient signatures were reflected in the blood of seafood consumers based on their consumption habits. Most notably, consumers with a salmon-dominated diet had a high percentage of omega-3 fatty acids in their blood compared with other seafood consumers. Consumers who tended to eat top-predator fish had higher mercury, but similar nutrient concentrations in blood compared with consumers of lower trophic level seafood. These results suggest that consuming lower trophic level seafood can minimize the risk of mercury exposure without reducing the benefits of nutrient intake, and more broadly, demonstrate the value of examining nutrient and mercury exposure patterns simultaneously. Such research efforts are valuable in summarizing the largest signals among otherwise complex patterns of multiple nutrients and contaminants, but there is a need for a deeper understanding of these multivariate patterns at higher levels of taxonomic resolution. In some cases, the seafood categories used in this study include multiple species that share market names in order to compare mercury–nutrient signatures between edible seafood and seafood consumers. For example, salmon includes Atlantic salmon and multiple species of Pacific salmon, and tuna steak includes bigeye and yellowfin tuna (Karimi et al., Reference Karimi, Fisher and Meliker2014). Future studies that examine the composition of individual fish of the same species would complement these broader analyses by examining nutrient-contaminant patterns at greater taxonomic resolution, and in relation to ecological and environmental factors. In addition, better information on the taxonomic identity of market fish and shellfish would improve estimates of co-exposure to nutrients and contaminants in seafood consumers.

Fig. 3.

Canonical discriminant analyses testing for differences in mercury-nutrient signatures among seafood items (from Karimi et al., Reference Karimi, Fisher and Meliker2014, reprinted with permission). Circles indicate 95% confidence limits for means of each seafood group and indicate the degree of difference among groups. Mercury and nutrient vectors (inset) represent the underlying structure of the axes. The position of circles relative to the direction of vectors indicates correlations between seafood groups and the concentration gradient of mercury or nutrients. Vector length indicates the overall contribution of mercury or nutrients in discriminating among seafood groups. Vector direction indicates the correlation of mercury or nutrient with each axis (vectors parallel to an axis are highly correlated with that axis). Angles between vectors represent correlations among mercury and nutrient concentrations. EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; Hg, mercury; Se, selenium.

Advice describing both the types and amounts of seafood consumption, while complex, is necessary to better manage risks and benefits of seafood consumption (Oken et al., Reference Oken, Wright, Kleinman, Bellinger, Amarasiriwardena, Hu, Rich-Edwards and Gillman2005; Gerber et al., Reference Gerber, Karimi and Fitzgerald2012). Seafood risk communication also requires risks and benefits to be considered together for appropriate context (Kuntz et al., Reference Kuntz, Ricco, Hill and Anderko2010; Turyk et al., Reference Turyk, Bhavsar, Bowerman, Boysen, Clark, Diamond, Mergler, Pantazopoulos, Schantz and Carpenter2012; Laird et al., Reference Laird, Goncharov, Egeland and Chan2013). Many fish advisories consider multiple chemical contaminants but provide minimal discussion of fish nutrients, focused on omega-3 fatty acids (Scherer et al., Reference Scherer, Tsuchiya, Younglove, Burbacher and Faustman2008). Compared with mercury concentrations, there are fewer studies quantifying fatty acids and selenium in seafood (Karimi et al., Reference Karimi, Fisher and Meliker2014). Therefore, to inform risk assessment more research is needed quantifying the risks and benefits associated with specific seafood consumption habits, such as considering the recommended daily consumption of seafood nutrients relative to reference doses (i.e. hazard quotients) of seafood contaminants (i.e. Gladyshev et al., Reference Gladyshev, Sushchik, Anishchenko, Makhutova, Kalachova and Gribovskaya2009).

To conduct appropriate human health risk assessment for contaminants such as mercury requires an understanding of how mercury, fish oils and selenium co-exposures affect the human body. This work can be informed by studies from marine biology and fisheries science, coupled with epidemiological biomonitoring, anthropological and food science investigations into the role of culinary preparation and gut processing on mercury and nutrient bioavailability (Laird et al., Reference Laird, Shade, Gantner, Chan and Siciliano2009; Moses et al., Reference Moses, Whiting, Bratton, Taylor and O'Hara2009a, Reference Moses, Whiting, Muir, Wang and O'Harab; Costa et al., Reference Costa, Afonso, Bandarra, Gueifão, Castanheira, Carvalho, Cardoso and Nunes2013). Acknowledging the concerns about contaminant exposure from seafood and its health benefits, the Joint FAO/WHO Expert Consultation on the Risks and Benefits of Fish Consumption (2010) recommended that government entities ‘Develop, maintain and improve existing databases on specific nutrients and contaminants, particularly methylmercury and dioxins, in fish consumed in their region’ and ‘Develop and evaluate risk management and communication strategies that both minimize risks and maximize benefits from eating fish’ (FAO/WHO, 2010, p. 33). Nevertheless, their general conclusions acknowledge fish as an important food source with clear benefits for reducing heart disease mortality and supporting optimal neurodevelopment in children.