Consumption of Native Fish Associated with a Potential Carcinogenic Risk for Indigenous Communities in the Peruvian Amazon
Abstract
:1. Introduction
2. Material and Methods
2.1. Fish Sampling
2.2. Sediment Sampling
2.3. Daily Fish Intake
2.4. Metal Concentration Analysis
2.5. QA/QC
2.6. Risk Assessment
2.6.1. Estimated Daily Intake (EDI)
2.6.2. Non-Carcinogenic Risk
2.6.3. Carcinogenic Risk (CRI)
2.7. Statistical Analysis
3. Results
3.1. Metal(loid)s in Fish Muscles
3.2. Sediments
3.3. Carcinogenic and Non-Carcinogenic Analysis
4. Discussion
4.1. Fish Muscle Analysis
4.2. Sediment Analysis
4.3. Human Health Risks
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Zoroddu, M.A.; Aaseth, J.; Crisponi, G.; Medici, S.; Peana, M.; Nurchi, V.M. The Essential Metals for Humans: A Brief Overview. J. Inorg. Biochem. 2019, 195, 120–129. [Google Scholar] [CrossRef] [PubMed]
- Biamont-Rojas, I.E.; Cardoso-Silva, S.; Alves de Lima Ferreira, P.; Alfaro-Tapia, R.; Figueira, R.; Pompêo, M. Chronostratigraphy Elucidates Environmental Changes in Lacustrine Sedimentation Rates and Metal Accumulation. Environ. Sci. Pollut. Res. 2023, 30, 72430–72445. [Google Scholar] [CrossRef]
- McClain, M.E.; Naiman, R.J. Andean Influences on the Biogeochemistry and Ecology of the Amazon River. Bioscience 2008, 58, 325–338. [Google Scholar] [CrossRef]
- Biamont-Rojas, I.E.; Cardoso-Silva, S.; Pompêo, M. Heterogeneidade Espacial e Ecotoxicidade de Metais No Sedimento Em Três Reservatorios Paulistas Aplicando Um Enfoque Geoestatístico. In Aspectos da Ecotoxicidade em Ambientes Aquáticos; Pompêo, M., Moschini-Carlos, V., López-Doval, J.C., Eds.; Instituto de Biociências, Universidade de São Paulo: São Paulo, Brazil, 2022; pp. 43–57. [Google Scholar]
- Martins, T.; Ferreira, K.; Rani-Borges, B.; Biamont-Rojas, I.; Cardoso-Silva, S.; Moschini-Carlos, V.; Pompêo, M. Land Use, Spatial Heterogeneity of Organic Matter, Granulometric Fractions and Metal Complexation in Reservoir Sediments. Acta Limnol. Bras. 2021, 33, e23. [Google Scholar] [CrossRef]
- Biamont-Rojas, I.E.; Mamani Villalba, B.A. Mercurio Derivado de La Actividad Minera Artesanal Evidencia Un Alto Potencial Tóxico En Una Subcuenca Del Lago Titicaca, Perú. In Minería, Mercurio y Salud. Aportes de la Comunidad Académica; Cabrera Jaramillo, A., Arango Ruiz, Á., Eds.; Editorial Lasallista: Caldas, Colombia, 2022; pp. 43–75. [Google Scholar]
- Khan, R.; Saxena, A.; Shukla, S. Evaluation of Heavy Metal Pollution for River Gomti, in Parts of Ganga Alluvial Plain, India. SN Appl. Sci. 2020, 2, 1451. [Google Scholar] [CrossRef]
- Brousett-Minaya, M.A.; Rondan-Sanabria, G.G.; Chirinos-Marroquín, M.; Biamont-Rojas, I. Impacto de La Minería En Aguas Superficiales de La Región Puno—Perú. Fides Ratio—Rev. Difusión Cult. Científica Univ. Salle Boliv. 2021, 21, 187–208. [Google Scholar]
- Biamont-Rojas, I.E.; Cardoso-Silva, S.; Figueira, R.C.L.; Kim, B.S.M.; Alfaro-Tapia, R.; Pompêo, M. Spatial Distribution of Arsenic and Metals Suggest a High Ecotoxicological Potential in Puno Bay, Lake Titicaca, Peru. Sci. Total Environ. 2023, 871, 162051. [Google Scholar] [CrossRef]
- Heilpern, S.A.; Sethi, S.A.; Barthem, R.B.; Batista, V.D.S.; Doria, C.R.C.; Duponchelle, F.; Vasquez, A.G.; Goulding, M.; Isaac, V.; Naeem, S.; et al. Biodiversity Underpins Fisheries Resilience to Exploitation in the Amazon River Basin. Proc. R. Soc. B Biol. Sci. 2022, 289, 20220726. [Google Scholar] [CrossRef]
- Passarelli, I.; Villacis Verdesoto, M.V.; Jiménez-Oyola, S.; Flores Huilcapi, A.G.; Mora-Silva, D.; Anfuso, G.; Esparza Parra, J.F.; Jimenez-Gutierrez, M.; Carrera Almendáriz, L.S.; Avalos Peñafiel, V.G.; et al. Analysis of Mercury in Aquifers in Gold Mining Areas in the Ecuadorian Amazon and Its Associated Risk for Human Health. Toxics 2024, 12, 162. [Google Scholar] [CrossRef]
- Mestanza-Ramón, C.; Cuenca-Cumbicus, J.; D’Orio, G.; Flores-Toala, J.; Segovia-Cáceres, S.; Bonilla-Bonilla, A.; Straface, S. Gold Mining in the Amazon Region of Ecuador: History and a Review of Its Socio-Environmental Impacts. Land 2022, 11, 221. [Google Scholar] [CrossRef]
- Sánchez-Vázquez, L.; Espinosa-Quezada, M.G.; Eguiguren-Riofrío, M.B. “Golden Reality” or the “Reality of Gold”: Artisanal Mining and Socio-Environmental Conflict in Chinapintza, Ecuador. Extr. Ind. Soc. 2016, 3, 124–128. [Google Scholar] [CrossRef]
- Villacís, S.; Ochoa, J.; Borja, M.O.; Josse, C.; Finer, M.; Mamani, N. MAAP #151: Minería Ilegal En La Amazonía Ecuatoriana. Available online: https://www.maaproject.org/2022/mineria-ecuador/ (accessed on 10 July 2024).
- Ulfe, M.E.; Vergara, R. Measuring Incommensurability: Compensations in Judicial Processes of Oil Spills in Northern Peruvian Amazon. Tapuya Lat. Am. Sci. Technol. Soc. 2022, 5, 2144004. [Google Scholar] [CrossRef]
- MINSA. Ministerio de Salud; Instituto Nacional de Salud. Niveles y Factores de Riesgo de Exposición a Metales Pesados e Hidrocarburos En Los Habitantes de Las Comunidades de Las Cuencas de Los Ríos Pastaza, Tigre, Corrientes y Marañón Del Departamento de Loreto; Ministerio de Salud: Lima, Peru, 2017.
- Jézéquel, C.; Tedesco, P.A.; Bigorne, R.; Maldonado-Ocampo, J.A.; Ortega, H.; Hidalgo, M.; Martens, K.; Torrente-Vilara, G.; Zuanon, J.; Acosta, A.; et al. A Database of Freshwater Fish Species of the Amazon Basin. Sci. Data 2020, 7, 96. [Google Scholar] [CrossRef] [PubMed]
- Al-Homaidan, A.A.; Al-Otaibi, T.G.; El-Sheikh, M.A.; Al-Ghanayem, A.A.; Ameen, F. Accumulation of Heavy Metals in a Macrophyte Phragmites Australis: Implications to Phytoremediation in the Arabian Peninsula Wadis. Environ. Monit. Assess. 2020, 192, 202. [Google Scholar] [CrossRef] [PubMed]
- Basallote, M.D.; Zarco, V.; Macías, F.; Cánovas, C.R.; Hidalgo, P.J. Metal Bioaccumulation in Spontaneously Grown Aquatic Macrophytes in Fe-Rich Substrates of a Passive Treatment Plant for Acid Mine Drainage. J. Environ. Manag. 2023, 345, 118495. [Google Scholar] [CrossRef] [PubMed]
- INEI. Censos Nacionales 2017. Resultados Definitivos de los Censos Nacionales 2017—Puno. Available online: https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1563/ (accessed on 30 July 2022).
- MINAM; Ministerio del Ambiente. Métodos de Colecta, Identificación y Análisis de Comunidades Biológicas: Plancton, Perifiton, Bentos (Macroinvertebrados) y Necton (Peces) En Aguas Continentales Del Perú; Zona Comunicaciones S.A.C.: Lima, Peru, 2014.
- INEI. Perú: Proyecciones de Población, Según Departamento, Provincia y Distrito, 2021-2022; McGraw-Hill Interamericana: Lima, Peru, 2020.
- López-Alvarenga, J.C.; Reding-Berrnal, A. Cálculo Del Tamaño de La Muestra: Enfoque Práctico de Sus Elementos Necesarios. In Introducción a la Metodología de la Investigación en Ciencias de la Salud; McGraw-Hill Interamericana: Ciudad de México, Mexico, 2011; pp. 67–76. [Google Scholar]
- Qin, D.; Jiang, H.; Bai, S.; Tang, S.; Mou, Z. Determination of 28 Trace Elements in Three Farmed Cyprinid Fish Species from Northeast China. Food Control 2015, 50, 1–8. [Google Scholar] [CrossRef]
- U.S. EPA. Method 3050B: Acid Digestion of Sediments, Sludges, and Soils, Revision 2; U.S. EPA: Washington, DC, USA, 1996.
- U.S. EPA. Method: 7471B Mercury in Solid or Semisolid Waste (Manual Cold-Vapor Technique); U.S. EPA: Washington, DC, USA, 2007.
- FAO. Heavy Metals Regulations Legal Notice No 66/2003; FAO: Rome, Italy, 2003. [Google Scholar]
- Hossain, M.B.; Ahmed, A.S.S.; Sarker, M.S.I. Human Health Risks of Hg, As, Mn, and Cr through Consumption of Fish, Ticto Barb (Puntius Ticto) from a Tropical River, Bangladesh. Environ. Sci. Pollut. Res. 2018, 25, 31727–31736. [Google Scholar] [CrossRef] [PubMed]
- Huang, X.; Qin, D.; Gao, L.; Hao, Q.; Chen, Z.; Wang, P.; Tang, S.; Wu, S.; Jiang, H.; Qiu, W. Distribution, Contents and Health Risk Assessment of Heavy Metal(Loid)s in Fish from Different Water Bodies in Northeast China. RSC Adv. 2019, 9, 33130–33139. [Google Scholar] [CrossRef]
- U.S. EPA. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisories, 3rd ed.; United States Environmental Protection Agency: Washington, DC, USA, 2000; Volume 2.
- Legendre, P.; Legendre, L. Numerical Ecology, 2nd ed.; Elsevier: Amsterdam, The Netherlands, 1998. [Google Scholar] [CrossRef]
- R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2023; Available online: https://www.R-project.org/ (accessed on 9 July 2024).
- WHO. Evaluation of Certain Food Additives and Contaminants: Thirty-Third Report of the Joint FAO/WHO Expert Committee on Food Additives; WHO: Geneva, Switzerland, 1989.
- GB2762-2017; National Food Safety Standard: Limits of Contaminants in Food. Office of Agricultural Affairs: Beijing, China, 2017.
- EU. Commission Regulation EC No. 629/2008. Setting Maximum Levels for Certain Contaminants in Foodstuffs; EU: Brussels, Belgium, 2008. [Google Scholar]
- ANVISA. Agência Nacional de Vigilância Sanitária. Decreto No. 55.871. Modifica o Decreto No 50.040, de 24 de Janeiro de 1961, Referente a Normas Reguladoras do Emprêgo de Aditivos para Alimentos, Alterado Pelo Decreto No 691, de 13 de Março de 1962; Presidencia da República: Brasília, Brazil, 1965.
- U.S. EPA. Regional Screening Level (RSL)—Generic Tables; U.S. EPA: Washington, DC, USA, 2024.
- EFSA. Scientific Opinion on Lead in Food. EFSA J. 2010, 8, 1570. [Google Scholar] [CrossRef]
- Vasco, C.; Sirén, A. Determinants of Wild Fish Consumption in Indigenous Communities in the Ecuadorian Amazon. Soc. Nat. Resour. 2019, 32, 21–33. [Google Scholar] [CrossRef]
- Islam, M.A.; Angove, M.J.; Morton, D.W. Recent Innovative Research on Chromium (VI) Adsorption Mechanism. Environ. Nanotechnol. Monit. Manag. 2019, 12, 100267. [Google Scholar] [CrossRef]
- Ullah, S.; Liu, Q.; Wang, S.; Jan, A.U.; Sharif, H.M.A.; Ditta, A.; Wang, G.; Cheng, H. Sources, Impacts, Factors Affecting Cr Uptake in Plants, and Mechanisms behind Phytoremediation of Cr-Contaminated Soils. Sci. Total Environ. 2023, 899, 165726. [Google Scholar] [CrossRef] [PubMed]
- Bolelli, G.; Steduto, D.; Kiilakoski, J.; Varis, T.; Lusvarghi, L.; Vuoristo, P. Tribological Properties of Plasma Sprayed Cr2O3, Cr2O3–TiO2, Cr2O3–Al2O3 and Cr2O3–ZrO2 Coatings. Wear 2021, 480–481, 203931. [Google Scholar] [CrossRef]
- Weber, P.; Behr, E.R.; Knorr, C.D.L.; Vendruscolo, D.S.; Flores, E.M.M.; Dressler, V.L.; Baldisserotto, B. Metals in the Water, Sediment, and Tissues of Two Fish Species from Different Trophic Levels in a Subtropical Brazilian River. Microchem. J. 2013, 106, 61–66. [Google Scholar] [CrossRef]
- Savassi, L.A.; Paschoalini, A.L.; Arantes, F.P.; Rizzo, E.; Bazzoli, N. Heavy Metal Contamination in a Highly Consumed Brazilian Fish: Immunohistochemical and Histopathological Assessments. Environ. Monit. Assess. 2020, 192, 542. [Google Scholar] [CrossRef] [PubMed]
- Meche, A.; Martins, M.C.; Lofrano, B.E.S.N.; Hardaway, C.J.; Merchant, M.; Verdade, L. Determination of Heavy Metals by Inductively Coupled Plasma-Optical Emission Spectrometry in Fish from the Piracicaba River in Southern Brazil. Microchem. J. 2010, 94, 171–174. [Google Scholar] [CrossRef]
- Vu, C.T.; Lin, C.; Yeh, G.; Villanueva, M.C. Bioaccumulation and Potential Sources of Heavy Metal Contamination in Fish Species in Taiwan: Assessment and Possible Human Health Implications. Environ. Sci. Pollut. Res. 2017, 24, 19422–19434. [Google Scholar] [CrossRef] [PubMed]
- Yi, Y.J.; Zhang, S.H. The Relationships between Fish Heavy Metal Concentrations and Fish Size in the Upper and Middle Reach of Yangtze River. Procedia Environ. Sci. 2012, 13, 1699–1707. [Google Scholar] [CrossRef]
- Ferreira da Silva, S.; de Oliveira Lima, M. Mercury in Fish Marketed in the Amazon Triple Frontier and Health Risk Assessment. Chemosphere 2020, 248, 125989. [Google Scholar] [CrossRef]
- Basta, P.C.; de Vasconcellos, A.C.S.; Hallwass, G.; Yokota, D.; Pinto, D.d.O.d.R.; de Aguiar, D.S.; de Souza, C.C.; Oliveira-da-Costa, M. Risk Assessment of Mercury-Contaminated Fish Consumption in the Brazilian Amazon: An Ecological Study. Toxics 2023, 11, 800. [Google Scholar] [CrossRef]
- Rengifo, P.D.; Reyes, L.W. Presencia de Mercurio En La Amazonía Peruana, Río Napo. In Memoria del Primer Encuentro de Investigadores Ambientales; Ministerio del Ambiente, Dirección General de Investigación e Información Ambiental: Iquitos, Peru, 2012; pp. 1–6. [Google Scholar]
- National Research Council (US). Subcommittee on the Tenth Edition of the Recommended Dietary Allowances, 10th ed.; National Academies Press (US): Washington, DC, USA, 1989. [Google Scholar]
- da Silva Costa, M.; Viana, L.F.; Lima Cardoso, C.A.; Gonar Silva Isacksson, E.D.; Silva, J.C.; Florentino, A.C. Landscape Composition and Inorganic Contaminants in Water and Muscle Tissue of Plagioscion Squamosissimus in the Araguari River (Amazon, Brazil). Environ. Res. 2022, 208, 112691. [Google Scholar] [CrossRef] [PubMed]
- Souza-Araujo, J.; Souza-Junior, O.G.; Guimarães-Costa, A.; Hussey, N.E.; Lima, M.O.; Giarrizzo, T. The Consumption of Shark Meat in the Amazon Region and Its Implications for Human Health and the Marine Ecosystem. Chemosphere 2021, 265, 129132. [Google Scholar] [CrossRef] [PubMed]
- Instituto Geológico, Minero y Metalúrgico (INGEMMET). Mapa Metalogenético del oro del Perú: Operaciones y Proyectos Mineros; Instituto Geológico, Minero y Metalúrgico (INGEMMET): Lima, Peru, 2023; Available online: https://hdl.handle.net/20.500.12544/3839 (accessed on 19 July 2024).
- Mestanza-Ramón, C.; Jiménez-Oyola, S.; Montoya, A.V.G.; Vizuete, D.D.C.; D’Orio, G.; Cedeño-Laje, J.; Straface, S. Assessment of Hg Pollution in Stream Waters and Human Health Risk in Areas Impacted by Mining Activities in the Ecuadorian Amazon. Environ. Geochem. Health 2023, 45, 7183–7197. [Google Scholar] [CrossRef] [PubMed]
Site | Small Town or Village | No. of Fish Specimens per Pool | River | District/Province | Human Daily Fish Intake (g/Person/Day) |
---|---|---|---|---|---|
C1 | Nueva Valencia | 18 | Corrientes | Trompeteros/Loreto | 103.00 |
C3 | Pucacuro | 19 | Corrientes | Trompeteros/Loreto | 103.23 |
C4 | Trompeteros | 17 | Corrientes | Trompeteros/Loreto | 82.94 |
C6 | Providencia | 31 | Corrientes | Trompeteros/Loreto | 60.00 |
T1 | Paiche Playa | 16 | Tigre | Tigre/Loreto | 146.14 |
T4a | Intuto | 19 | Tigre | Tigre/Loreto | 122.45 |
T4b | 28 de Julio | 28 | Tigre | Tigre/Loreto | 175.68 |
T6 | Piura | 11 | Tigre | Tigre/Loreto | 134.46 |
T7 | Nueva York | 30 | Tigre | Tigre/Loreto | 56.62 |
M1 | Inka Roca-Tigreyacu | 10 | Morona | Morona/Datém del Marañón | 302.36 |
M2 | Caballito-Tipishcacocha | 19 | Morona | Morona/Datém del Marañón | 383.00 |
M3 | Shoroya nuevo | 10 | Morona | Morona/Datém del Marañón | 382.11 |
M4 | Pinshacocha | 17 | Morona | Morona/Datém del Marañón | 63.01 |
M5 | San Martin | 41 | Morona | Morona/Datém del Marañón | 62.53 |
M6 | Puerto Alegría | 13 | Morona | Morona/Datém del Marañón | 63.15 |
M7 | Puerto América | 15 | Morona | Morona/Datém del Marañón | 64.24 |
P1 | Nuevo Soplín | 13 | Pastaza | Morona/Datém del Marañón | 60.00 |
P2 | Loboyacu | 18 | Pastaza | Morona/Datém del Marañón | 302.37 |
P3 | Sungache | 18 | Pastaza | Morona/Datém del Marañón | 100.00 |
P4 | San Fernando | 10 | Pastaza | Morona/Datém del Marañón | 101.20 |
P5 | Musakarusha | 12 | Pastaza | Morona/Datém del Marañón | 82.41 |
P6 | Nueva Alianza | 8 | Pastaza | Morona/Datém del Marañón | 84.43 |
Scientific Name | Name | River | Total | Feeding Regime | Habitat | |||
---|---|---|---|---|---|---|---|---|
Corrientes | Tigre | Morona | Pastaza | |||||
Acestrorhynchus falcirostris | Big-eyed cachorro | 1 | 2 | 1 | 4 | Piscivorous | Benthopelagic | |
Adontosternarchus balaenops | Ghost knifefish | 4 | 4 | Carnivorous | Benthopelagic | |||
Ageneiosus inermis | Manduba | 1 | 2 | 1 | 4 | Piscivorous | Pelagic | |
Amblydoras affinis | Rego rego | 7 | 7 | Omnivore | Demersal | |||
Ancistrus dolichopterus | Bushymouth catfish | 1 | 1 | Omnivore | Demersal | |||
Ancistrus temminckii | Carachama | 4 | 4 | Omnivore | Demersal | |||
Anodus elongatus | Yulilla | 1 | 3 | 4 | Omnivore | Pelagic | ||
Astronatus ocellatus | Oscar | 2 | 2 | Omnivore | Benthopelagic | |||
Biotodoma cupido | Greenstreaked eartheater | 1 | 2 | 3 | Omnivore | Benthopelagic | ||
Brachyplatytoma vaillantii | Laulao catfish | 1 | 1 | Piscivorous | Demersal | |||
Brycon amazonicus | Sábalo | 1 | 3 | 4 | Omnivore | Benthopelagic | ||
Bunocephalus coraoideus | Banjo catfish | 1 | 1 | Omnivore | Demersal | |||
Calophysus macropterus | Zamurito | 1 | 1 | Carnivorous | Demersal | |||
Chaetobranchus flavescens | Bujurqui vaso | 15 | 1 | 5 | 21 | Omnivore | Benthopelagic | |
Cheirodon interruptus | Uruguay tetra | 2 | 2 | Omnivore | Benthopelagic | |||
Chilodus punctatus | Spotted headstander | 5 | 5 | Omnivore | Pelagic | |||
Cichla monoculus | Peacock bass | 1 | 2 | 3 | Carnivorous | Benthopelagic | ||
Cichla ocellaris | Peacock cichlid | 1 | 1 | Carnivorous | Benthopelagic | |||
Corydoras arcuatus | Skunk corydoras | 1 | 1 | Detritivore | Demersal | |||
Curimatella meyeri | Yahuarachi | 1 | 1 | Detritivore | Benthopelagic | |||
Cynodon gibbus | Chambira | 1 | 1 | Carnivorous | Pelagic | |||
Hemiodus microlepis | Yulilla | 1 | 1 | Omnivore | Benthopelagic | |||
Hemisorubim platyrhynchos | Porthole shovelnose catfish | 1 | 1 | Carnivorous | Demersal | |||
Heros efasciatus | Bujurqui acha vieja | 1 | 1 | Omnivore | Benthopelagic | |||
Heros severus | Banded cichlid | 1 | 1 | Omnivore | Benthopelagic | |||
Hoplerythrinus unitaeniatus | Aimara | 2 | 1 | 9 | 12 | Carnivorous | Pelagic | |
Hoplias malabaricus | Trahira | 3 | 5 | 7 | 7 | 22 | Carnivorous | Benthopelagic |
Hoplosternum littorale | Atipa | 4 | 4 | Detritivore | Demersal | |||
Hyphessobrycon copelandi | Wira mojara | 5 | 5 | Omnivore | Benthopelagic | |||
Hypophthalmus edentatus | Highwaterman catfish | 16 | 1 | 17 | Herbivore | Pelagic | ||
Hypselecara temporalis | Emerald cichlid | 5 | 5 | Omnivore | Benthopelagic | |||
Lamontichthys stibaros | Shitari | 1 | 1 | Detritivore | Demersal | |||
Leporinus friderici | Threespot leporinus | 6 | 6 | Omnivore | Benthopelagic | |||
Megaleporinus trifasciatus | Lisa | 1 | 1 | 2 | Omnivore | Benthopelagic | ||
Myleus rubripinnis | Redhook myleus | 10 | 7 | 1 | 6 | 24 | Omnivore | Benthopelagic |
Pimelodus blochii | Bloch’s catfish | 1 | 2 | 1 | 4 | Omnivore | Benthopelagic | |
Pinirampus pirinampu | Flatwhiskered catfish | 1 | 1 | Carnivorous | Demersal | |||
Potamorhina altamazonica | Yahuarachi | 6 | 22 | 5 | 4 | 37 | Detritivore | Benthopelagic |
Potamotrygon magdalenae | Magdalena river stingray | 2 | 2 | Detritivore | Benthopelagic | |||
Prochilodus nigricans | Black prochilodus | 1 | 11 | 21 | 12 | 45 | Detritivore | Benthopelagic |
Psalidodon fasciatus | Banded astyanax | 1 | 1 | Omnivore | Benthopelagic | |||
Psectrogaster amazonica | Chio Chio | 11 | 26 | 4 | 41 | Detritivore | Benthopelagic | |
Pseudorinelepis genibarbis | Carachama negra | 1 | 1 | Detritivore | Benthopelagic | |||
Pterodoras granulosus | Granulated catfish | 2 | 2 | 4 | Omnivore | Demersal | ||
Pterygoplichthys pardalis | Amazon sailfin catfish | 16 | 16 | Detritivore | Demersal | |||
Pygocentrus nattereri | Red piranha | 4 | 1 | 5 | Carnivorous | Pelagic | ||
Rhaphiodon vulpinus | Biara | 1 | 1 | Carnivorous | Pelagic | |||
Rhytiodus microlepis | Lisa | 1 | 1 | Herbivorous | Benthopelagic | |||
Roeboides myersii | Dentón | 2 | 1 | 4 | 1 | 8 | Carnivorous | Benthopelagic |
Satanoperca jurupari | Demon eartheater | 5 | 5 | Carnivorous | Benthopelagic | |||
Schizodon fasciatus | Characin | 5 | 4 | 9 | Omnivore | Benthopelagic | ||
Semaprochilodus insignis | Kissing prochilodus | 1 | 2 | 2 | 5 | Detritivore | Benthopelagic | |
Serrasalmus rhombeus | Red-eye piranha | 1 | 10 | 3 | 14 | Carnivorous | Benthopelagic | |
Squaliforma emarginata | Carachama blanca | 2 | 2 | Detritivore | Demersal | |||
Trachelyopterus galeatus | Novia cunchi | 2 | 2 | 4 | 8 | Omnivore | Demersal | |
Triportheus angulatus | Sardina | 3 | 3 | 4 | 7 | 17 | Omnivore | Benthopelagic |
Element | Tigre (n = 104) | Morona (n = 125) | Corrientes (n = 85) | Pastaza (n = 79) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean ± SD | Range | CV | Mean ± SD | Range | CV | Mean ± SD | Range | CV | Mean ± SD | Range | CV | |
Cr | 0.73 ± 0.34 | 0.32–1.29 | 51.95 | 0.46 ± 0.24 | 0.23–0.93 | 53.2 | 0.53 ± 0.10 | 0.43–0.67 | 19.01 | 0.40 ± 0.16 | 0.29–0.72 | 40.88 |
Ni | 0.22 ± 0.19 | 0.04–0.64 | 94.74 | 0.10 ± 0.03 | 0.04–0.13 | 32.07 | 0.19 ± 0.09 | 0.08–0.32 | 45.8 | 0.06 ± 0.05 | 0.02–0.13 | 92.2 |
Cu | 0.54 ± 0.19 | 0.22–0.89 | 33.36 | 0.46 ± 0.13 | 0.22–0.67 | 28.89 | 0.47 ± 0.11 | 0.32–0.68 | 24.31 | 0.41 ± 0.13 | 0.28–0.59 | 32.74 |
Zn | 6.30 ± 1.76 | 3.91–9.88 | 25.19 | 5.34 ± 0.96 | 4.37–7.42 | 15.79 | 6.58 ± 0.85 | 5.60–7.64 | 12.98 | 5.49 ± 1.32 | 4.17–7.72 | 24.03 |
As | 0.02 ± 0.02 | ND–0.07 | 109.67 | 0.02 ± 0.02 | ND–0.07 | 104.79 | 0.02 ± 0.01 | ND–0.03 | 60.61 | 0.01 ± 0.002 | ND–0.01 | 21.02 |
Cd | 0.006 ± 0.002 | 0.002–0.01 | 40.53 | 0.006 ± 0.01 | 0.001–0.02 | 94.68 | 0.005 ± 0.002 | 0.003–0.01 | 31.11 | 0.01 ± 0.004 | 0.004–0.01 | 32.6 |
Pb | 0.05 ± 0.02 | 0.03–0.07 | 31.91 | 0.04 ± 0.02 | 0.01–0.07 | 54.98 | 0.06 ± 0.04 | 0.02–0.12 | 70.6 | 0.06 ± 0.03 | 0.03–0.13 | 53.29 |
Hg | 0.31 ± 0.10 | 0.20–0.43 | 33.43 | 0.18 ± 0.10 | 0.10–0.39 | 54.9 | 0.11 ± 0.01 | 0.10–0.13 | 11.24 | 0.28 ± 0.14 | 0.12–0.52 | 50.02 |
Guideline/Reference | Cr | Ni | Cu | Pb | Zn | Hg | As | Cd |
---|---|---|---|---|---|---|---|---|
FAO [27] | 0.2 | 50 | 0.5 | 0.05 | ||||
FAO/WHO [33] | 0.05 | 8.97 | 30 | 0.05 | 0.015 | |||
China QS [34] | 2.0 | 0.5 | 0.5 | 0.1 | ||||
European Union [35] | 0.5 | 0.3 | 0.5 | 0.05 | ||||
ANVISA [36] | 0.1 | 5.0 | 30 | 50 | 0.5 | 0.5 |
Element | Tigre (n = 12) | Morona (n = 14) | Corrientes (n = 12) | Pastaza (n = 12) | Guidelines | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean ± SD | Range | CV | Mean ± SD | Range | CV | Mean ± SD | Range | CV | Mean ± SD | Range | CV | NOAAA | ISQG | SQG-EPA | |
Cr | 7.53 ± 1.77 | 1.90–16.00 | 63.34 | 12.74 ± 1.51 | 8.30–21.80 | 35.43 | 11.58 ± 2.23 | 3.20–35.30 | 79.65 | 17.85 ± 3.06 | 12.50–24.00 | 22.77 | 13 | 37.2 | 43.4 |
Ni | 7 ± 1.28 | 3.60–10.40 | 32.63 | 10.83 ± 2.39 | 7.20- 18.0 | 31.28 | 10.57 ± 5.77 | 3.10–21.10 | 54.59 | 47.10 ± 8.67 | 27.5–95.10 | 39.62 | 9.9 | 18 | 22.7 |
Cu | 4.24 ± 0.49 | 2.20–8.40 | 58.67 | 7.48 ± 1.25 | 1.90–21.00 | 96.95 | 4.58 ± 1.98 | 2.10–8.70 | 65.05 | 9.31 ± 1.95 | 5.80–18.00 | 42.42 | 25 | 35.7 | 31.6 |
Zn | 16.89 ± 2.52 | 5.40–38.40 | 62.26 | 52.19 ± 13.58 | 29.70–99.80 | 45.18 | 20.78 ± 2.32 | 8.90–37.60 | 44.86 | 31.94 ± 3.19 | 25.0–39.50 | 13.13 | 38 | 123 | 121 |
Al | 2523.78 ± 378.2 | 626.6–7447.0 | 79.45 | 9489.71 ± 1239.4 | 4467.0–21,160.0 | 62.98 | 2988.03 ± 206.5 | 941.4–7365 | 63.71 | 5714.92 ± 379.2 | 3404.0–8674.0 | 25.76 | 2600 | ||
Fe | 5671.50 ± 424.1 | 1911.0–12,585.0 | 62.94 | 14,114.14 ± 2921.6 | 8664.0–23,352.0 | 34.65 | 7160.2 ± 322.2 | 2366–14,375 | 56.69 | 15,543.0 ± 1077.5 | 12,993.0–19,773.0 | 12.99 | 18,000 | 20,000 | |
Ba | 26.80 ± 2.1 | 8.60–71.8 | 71.48 | 89.93 ± 11.55 | 52.7–158.1 | 38.86 | 35.9 ± 2.88 | 16.9–51.7 | 35.88 | 34.97 ± 7.1 | 19.40–47.70 | 22.58 | 0.70 | ||
As | <3.6 | 0 | 0.00 | <3.6 | 0 | 0 | <3.6 | 0 | 0 | <3.6 | 0 | 0 | 1.1 | 5.9 | <3 |
Cd | <0.3 | 0 | 0.00 | <0.3 | 0 | 0 | <0.3 | 0 | 0 | <0.3 | 0 | 0 | 0.3 | 0.6 | 0.99 |
Pb | <3.0 | 0 | 0.00 | <3.0 | 0 | 0 | <3.0 | 0 | 0 | <3.0 | 0 | 0 | 17 | 35 | 35.8 |
Hg | 0.02 ± 0.01 | 0.01–0.06 | 70.46 | 0.04 ± 0.02 | 0.01–0.07 | 55.22 | 0.02 ± 0.01 | 0.01–0.03 | 50.65 | 0.02 ±0.01 | 0.01–0.04 | 83.85 | 0.05 | 0.17 | 0.18 |
Elements | RfDs | Tigre | Morona | Corrientes | Pastaza | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
EDI | THQ | CRI | EDI | THQ | CRI | EDI | THQ | CRI | EDI | THQ | CRI | ||
Cr | 1 | 1.33 | 0.44 | 6.6 (1.3–13.1) | 1.58 | 0.53 | 7.8 (1.01–21.5) | 0.68 | 0.23 | 3.3 (1.8–4.8) | 0.72 | 0.24 | 3.5 (1.3–9) |
Ni | 20 | 0.40 | 0.02 | 0.26 | 0.01 | 0.22 | 0.01 | 0.14 | 0.01 | ||||
Cu | 40 | 0.97 | 0.02 | 1.38 | 0.03 | 0.57 | 0.01 | 0.67 | 0.02 | ||||
Zn | 300 | 11.31 | 0.04 | 14.66 | 0.05 | 8.11 | 0.03 | 9.08 | 0.03 | ||||
As | * 0.3 | 0.05 | 0.16 | 71.6 (8.6–183.8) | 0.05 | 0.17 | 78.4 (2.99–312.9) | 0.02 | 0.08 | 35.5 (5.47–64.4) | 0.02 | 0.07 | 30.3 (14.9–85.2) |
Cd | 1 | 0.01 | 0.01 | 4.6 (0.7–7.6) | 0.01 | 0.01 | 4.8 (0.8–14.6) | 0.01 | 0.01 | 2.2 (1.7–2.7) | 0.02 | 0.02 | 8.2 (1.4–24.1) |
Pb | 1.5 | 0.09 | 0.06 | 0.10 | 0.07 | 0.09 | 0.06 | 0.11 | 0.07 | ||||
Hg | ** 0.3 | 0.57 | 1.92 | 0.55 | 1.83 | 0.14 | 0.45 | 0.45 | 1.50 |
River | Country | Cr | Ni | Cu | Zn | As | Cd | Pb | Hg | References |
---|---|---|---|---|---|---|---|---|---|---|
Tigre | Peru | 0.32–1.29 | 0.04–0.49 | 0.28–0.75 | 4.14–8.28 | 0.003–0.06 | 0.002–0.01 | 0.03–0.07 | 0.20–0.41 | This study |
Pastaza | Peru | 0.29–0.72 | 0.02–0.13 | 0.28–0.59 | 4.17–7.72 | ND–0.01 | 0.004–0.01 | 0.03–0.13 | 0.12–0.52 | This study |
Abaeté and Paraopeba | Brazil | 0.42–1.7 | 5.62–32.2 | 8.88–21.1 | 0.02–0.33 | 0.17–2.11 | [44] | |||
Piracicaba | Brazil | 0.05- 1.11 | 0.05–2.83 | 0.03–4.18 | 0.73–0.93 | 0.02–0.92 | 0.66–3.25 | [45] | ||
Sinos | Brazil | 0.09–0.38 | - | 1.43–5.4 | 22.9–34.6 | 1.47–8.79 | 0.07–0.8 | 1.2–2.5 | - | [43] |
Northeast of China | China | ND–0.49 | ND–0.78 | 0.067–0.97 | 2.49–51.38 | ND–0.39 | ND–0.009 | ND–0.70 | ND–0.82 | [29] |
Yangtze | China | 0.10–0.24 | - | 0.77–1.22 | 2.8–7.55 | - | 0.046–0.12 | 0.21–0.81 | - | [47] |
Houjin | Taiwan | ND–83.44 | ND–34.59 | ND–380 | ND–107 | ND–3.11 | ND–14.5 | ND–13.5 | ND–0.38 | [46] |
Gomti | Bangladesh | 0.004 | - | - | - | 0.002 | BDL | BDL | 0.006 | [28] |
Alto Solimões | Brazil | 0.081–0.33 | [48] | |||||||
Rio Amazonas–Manaos | Brazil | 0.0–2.18 | [49] | |||||||
Bajo Napo–Loreto | Perú | 0.04–1.94 | [50] |
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Brousett-Minaya, M.A.; Chu-Koo, F.W.; Napuchi-Linares, J.; Zambrano Panduro, C.E.; Reyes-Larico, J.A.; Larrea-Valdivia, A.E.; Biamont-Rojas, I.E. Consumption of Native Fish Associated with a Potential Carcinogenic Risk for Indigenous Communities in the Peruvian Amazon. Toxics 2024, 12, 552. https://doi.org/10.3390/toxics12080552
Brousett-Minaya MA, Chu-Koo FW, Napuchi-Linares J, Zambrano Panduro CE, Reyes-Larico JA, Larrea-Valdivia AE, Biamont-Rojas IE. Consumption of Native Fish Associated with a Potential Carcinogenic Risk for Indigenous Communities in the Peruvian Amazon. Toxics. 2024; 12(8):552. https://doi.org/10.3390/toxics12080552
Chicago/Turabian StyleBrousett-Minaya, Magaly Alejandra, Fred William Chu-Koo, Juvenal Napuchi-Linares, Cynthia Elizabeth Zambrano Panduro, Juan Amilcar Reyes-Larico, Adriana Edith Larrea-Valdivia, and Ivan Edward Biamont-Rojas. 2024. "Consumption of Native Fish Associated with a Potential Carcinogenic Risk for Indigenous Communities in the Peruvian Amazon" Toxics 12, no. 8: 552. https://doi.org/10.3390/toxics12080552
APA StyleBrousett-Minaya, M. A., Chu-Koo, F. W., Napuchi-Linares, J., Zambrano Panduro, C. E., Reyes-Larico, J. A., Larrea-Valdivia, A. E., & Biamont-Rojas, I. E. (2024). Consumption of Native Fish Associated with a Potential Carcinogenic Risk for Indigenous Communities in the Peruvian Amazon. Toxics, 12(8), 552. https://doi.org/10.3390/toxics12080552