Impairment in Working Memory and Executive Function Associated with Mercury Exposure in Indigenous Populations in Upper Amazonian Peru
Abstract
:1. Introduction
2. Materials and Methods
Data Analysis
3. Results
3.1. Demographics and Health Indicators
3.2. Hair Mercury Levels
3.3. Cognitive Tasks
3.3.1. Word Span
3.3.2. Corsi Block
3.3.3. Self-Ordered Pointing Test
3.3.4. Trail Making Task A and B
3.4. Correlations among Demographic Variables, Health, and Diet Indicators
3.5. Correlations among Demographic Variables and Cognitive Tasks
3.6. Correlations between Cognitive Tasks and Hair Hg Levels
4. Discussion
4.1. Hg Levels
4.2. Hg Levels and Working Memory Tasks
4.2.1. Verbal Short-Term Memory and Cultural Considerations
If he says he has three needles, he has three. He begins to lose count only as numbers mount above five; like all his neighbors, he tends to remember in increments of five or ten and he can indicate these increments by opening his fists and flashing his fingers the right number of times.([84]. Families of the Forest, 2003, p. 153)
4.2.2. Visuospatial Short-Term Memory
4.2.3. Executive Functions
4.3. Limitations and Future Directions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Pirrone, N.; Cinnirella, S.; Feng, X.; Finkelman, R.B.; Friedli, H.R.; Leaner, J.; Mason, R.; Mukherjee, A.B.; Stracher, G.B.; Streets, D.G.; et al. Global mercury emissions to the atmosphere from anthropogenic and natural sources. Atmos. Chem. Phys. 2010, 10, 5951–5964. [Google Scholar] [CrossRef]
- Singer, M.B.; Aalto, R.; James, L.A.; Kilham, N.E.; Higson, J.L.; Ghoshal, S. Enduring legacy of a toxic fan via episodic redistribution of California gold mining debris. Proc. Natl. Acad. Sci. USA 2013, 110, 18436–18441. [Google Scholar] [CrossRef] [PubMed]
- Driscoll, D.; Sorensen, A.; Deerhake, M. A multidisciplinary approach to promoting healthy subsistence fish consumption in culturally distinct communities. Health Promot. Pract. 2012, 13, 245–251. [Google Scholar] [CrossRef] [PubMed]
- Chen, C.Y.; Driscoll, C.T. Integrating mercury research and policy in a changing world. Ambio 2018, 47, 111–115. [Google Scholar] [CrossRef] [PubMed]
- Driscoll, C.T.; Mason, R.P.; Chan, H.M.; Jacob, D.J.; Pirrone, N. Mercury as a Global Pollutant: Sources, Pathways, and E ffects. Environ. Sci. Technol. 2013, 47, 4967–4983. [Google Scholar] [CrossRef] [PubMed]
- Hsu-Kim, H.; Kucharzyk, K.H.; Zhang, T.; Deshusses, M.A. Mechanisms regulating mercury bioavailability for methylating microorganisms in the aquatic environment: A critical review. Environ. Sci. Technol. 2013, 47, 2441–2456. [Google Scholar] [CrossRef]
- Ullrich, S.M.; Tanton, T.W.; Abdrashitova, S.A. Mercury in the aquatic environment: A review of factors affecting methylation. Crit. Rev. Environ. Sci. Technol. 2001, 31, 241–293. [Google Scholar] [CrossRef]
- Azevedo-Silva, C.E.; Almeida, R.; Carvalho, D.P.; Ometto, J.P.; de Camargo, P.B.; Dorneles, P.R.; Azeredo, A.; Bastos, W.R.; Malm, O.; Torres, J.P. Mercury biomagnification and the trophic structure of the ichthyofauna from a remote lake in the Brazilian Amazon. Environ. Res. 2016, 151, 286–296. [Google Scholar] [CrossRef]
- Bastos, W.R.; Dórea, J.G.; Bernardi, J.V.E.; Lauthartte, L.C.; Mussy, M.H.; Lacerda, L.D.; Malm, O. Mercury in fish of the Madeira river (temporal and spatial assessment), Brazilian Amazon. Environ. Res. 2015, 140, 191–197. [Google Scholar] [CrossRef]
- Callister, S.M.; Winfrey, M.R. Microbial methylation of mercury in upper Wisconsin river sediments. Water Air Soil Pollut. 1986, 29, 453–465. [Google Scholar] [CrossRef]
- Hacon, S.D.S.; Oliveira-Da-Costa, M.; Gama, C.D.S.; Ferreira, R.; Basta, P.C.; Schramm, A.; Yokota, D. Mercury exposure through fish consumption in traditional communities in the Brazilian northern Amazon. Int. J. Environ. Res. Public Health 2020, 17, 5269. [Google Scholar] [CrossRef] [PubMed]
- Basu, N.; Horvat, M.; Evers, D.C.; Zastenskaya, I.; Weihe, P.; Tempowski, J. A state-of-the-science review of mercury biomarkers in human populations worldwide between 2000 and 2018. Environ. Health Perspect. 2018, 126, 106001. [Google Scholar] [CrossRef] [PubMed]
- Dufour, D.L.; Piperata, B.A.; Murrieta, R.S.S.; Wilson, W.M.; Williams, D.D. Amazonian foods and implications for human biology. Ann. Hum. Biol. 2016, 43, 330–348. [Google Scholar] [CrossRef] [PubMed]
- Ohl-Schacherer, J.; Shepard, G.H.; Kaplan, H.; Peres, C.A.; Levi, T.; Yu, D.W. The sustainability of subsistence hunting by matsigenka native communities in Manu National Park, Peru. Conserv. Biol. 2007, 21, 1174–1185. [Google Scholar] [CrossRef]
- Bunce, J.; Minaya, C. Matsigenka and Colonos-Lowland, Peru. 2022. Available online: https://www.eva.mpg.de/ecology/fieldwork/matsigenka-and-colonos/ (accessed on 1 June 2022).
- Diringer, S.E.; Feingold, B.J.; Ortiz, E.J.; Gallis, J.A.; Araújo-Flores, J.M.; Berky, A.; Pan, W.K.Y.; Hsu-Kim, H. River transport of mercury from artisanal and small-scale gold mining and risks for dietary mercury exposure in Madre de Dios, Peru. Environ. Sci. Process. Impacts 2014, 17, 478–487. [Google Scholar] [CrossRef]
- Shepard, G.H.; Rummenhoeller, K.; Ohl-Schacherer, J.; Yu, D.W. Trouble in paradise: Indigenous populations, anthropological policies, and biodiversity conservation in Manu National Park, Peru. J. Sustain. For. 2010, 29, 252–301. [Google Scholar] [CrossRef]
- Reuben, A.; Frischtak, H.; Berky, A.; Ortiz, E.J.; Morales, A.M.; Hsu-Kim, H.; Pendergast, L.L.; Pan, W.K. Elevated hair mercury levels are associated with neurodevelopmental deficits in children living near artisanal and small-scale gold mining in Peru. Geohealth 2020, 4, e2019GH000222. [Google Scholar] [CrossRef]
- Dos Santos-Lima, C.; Mourão, D.D.S.; de Carvalho, C.F.; Souza-Marques, B.; Vega, C.M.; Gonçalves, R.A.; Argollo, N.; Menezes-Filho, J.A.; Abreu, N.; Hacon, S.D.S. Neuropsychological effects of mercury exposure in children and adolescents of the Amazon region, Brazil. NeuroToxicology 2020, 79, 48–57. [Google Scholar] [CrossRef]
- Debes, F.; Weihe, P.; Grandjean, P. Cognitive deficits at age 22 years associated with prenatal exposure to methylmercury. Cortex 2016, 74, 358–369. [Google Scholar] [CrossRef]
- Crump, K.S.; Kjellström, T.; Shipp, A.M.; Silvers, A.; Stewart, A. Influence of prenatal mercury exposure upon scholastic and psychological test performance: Benchmark analysis of a New Zealand cohort. Risk Anal. 1998, 18, 701–713. [Google Scholar] [CrossRef]
- Grandjean, P.; Weihe, P.; White, R.F.; Debes, F.; Araki, S.; Yokoyama, K.; Murata, K.; Sørensen, N.; Dahl, R.; Jørgensen, P.J. Cognitive deficit in 7-year-old children with prenatal exposure to methylmercury. Neurotoxicol. Teratol. 1997, 19, 417–428. [Google Scholar] [CrossRef]
- Davidson, P.W.; Myers, G.J.; Cox, C.; Axtell, C.; Shamlaye, C.; Sloane-Reeves, J.; Cernichiari, E.; Needham, L.; Choi, A.; Clarkson, T.W.; et al. Effects of prenatal and postnatal methylmercury exposure from fish consumption on neurodevelopment: Outcomes at 66 months of age in the Seychelles Child Development Study. JAMA 1998, 280, 701–707. [Google Scholar] [CrossRef] [PubMed]
- Myers, G.J.; Davidson, P.W.; Cox, C.; Shamlaye, C.F.; Palumbo, D.; Cernichiari, E.; Sloane-Reeves, J.; Wilding, G.E.; Kost, J.; Huang, L.-S.; et al. Prenatal methylmercury exposure from ocean fish consumption in the Seychelles child development study. Lancet 2003, 361, 1686–1692. [Google Scholar] [CrossRef]
- Wang, Y.; Chen, A.; Dietrich, K.N.; Radcliffe, J.; Caldwell, K.L.; Rogan, W.J. Postnatal exposure to methyl mercury and neuropsychological development in 7-year-old urban inner-city children exposed to lead in the United States. Child Neuropsychol. 2014, 20, 527–538. [Google Scholar] [CrossRef] [PubMed]
- Walker, A.J.; Batchelor, J.; Shores, E.A. Effects of education and cultural background on performance on WAIS-III, WMS-III, WAIS-R and WMS-R measures: Systematic review. Aust. Psychol. 2009, 44, 216–223. [Google Scholar] [CrossRef]
- Ortiz, S.; Ochoa, S.H.; Dynda, A.M. Testing with culturally and linguistically diverse populations: Moving beyond the verbal-performance dichotomy into evidence-based practice. In Contemporary Intellectual Assessment: Theories, Tests, and Issues; Guilford Press: New York, NY, USA, 2012; pp. 526–552. [Google Scholar]
- Aben, B.; Stapert, S.; Blokland, A. About the distinction between working memory and short-term memory. Front. Psychol. 2012, 3, 301. [Google Scholar] [CrossRef]
- Shepard, G. Ethnozoological classification in Machiguenga, an Arawakan language. In The Journal Of Amazonian Languages; Ladefoged, P., Kaufman, T., Payne, D., Pullum, G., Rodrigues, A.D.I., Faco, M., Wetzels, L., Eds.; University of Pittsburgh: Pittsburgh, PA, USA, 1997. [Google Scholar]
- Everett, C.; Madora, K. Quantity recognition among speakers of an anumeric language. Cogn. Sci. 2012, 36, 130–141. [Google Scholar] [CrossRef] [PubMed]
- Counter, S.A.; Buchanan, L.H.; Ortega, F. Neurocognitive screening of mercury-exposed children of andean gold miners. Int. J. Occup. Environ. Health 2006, 12, 209–214. [Google Scholar] [CrossRef]
- Chevrier, C.; Sullivan, K.; White, R.F.; Comtois, C.; Cordier, S.; Grandjean, P. Qualitative assessment of visuospatial errors in mercury-exposed Amazonian children. Neurotoxicology 2009, 30, 37–46. [Google Scholar] [CrossRef]
- Tavares, L.M.B.; Câmara, V.M.; Malm, O.; Santos, E.C.D.O. Performance on neurological development tests by riverine children with moderate mercury exposure in Amazonia, Brazil. Cad. Saúde Pública 2005, 21, 1160–1167. [Google Scholar] [CrossRef] [Green Version]
- Miyake, A.; Shah, P. Models of Working Memory: Mechanisms of Active Maintenance and Executive Control; Cambridge University Press: Cambridge, UK, 1999. [Google Scholar]
- Logie, R.; Camos, V.; Cowan, N. Working Memory: State of the Science; Oxford University Press: Oxford, UK, 2021. [Google Scholar]
- Cowan, N. The many faces of working memory and short-term storage. Psychon. Bull. Rev. 2017, 24, 1158–1170. [Google Scholar] [CrossRef] [PubMed]
- Barrouillet, P.; Camos, V. The time-based resource-sharing model of working memory. In Working Memory; Oxford University Press: Oxford, UK, 2020; pp. 85–115. [Google Scholar] [CrossRef]
- Engle, R.W. Working memory capacity as executive attention. Curr. Dir. Psychol. Sci. 2002, 11, 19–23. [Google Scholar] [CrossRef]
- Baddeley, A.D.; Hitch, G. Working memory. In Psychology of Learning and Motivation—Advances in Research and Theory; Elsevier: Amsterdam, The Netherlands, 1974; Volume 8, pp. 47–89. [Google Scholar] [CrossRef]
- Baddeley, A.D. Essentials of Human Memory. Taylor & Francis; Psychology Press: London, UK, 1999. [Google Scholar]
- Baddeley, A.D.; Hitch, G.J.; Allen, R.J. A multicomponent model of working memory. In Working Memory: State of the Science; Logie, R., Camos, V., Cowan, N., Eds.; Oxford University Press: Oxford, UK, 2021. [Google Scholar]
- Engle, R.W.; Laughlin, J.E.; Tuholski, S.W.; Conway, A.R.A. Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. J. Exp. Psychol. Gen. 1999, 128, 3091999. [Google Scholar] [CrossRef] [PubMed]
- Kane, M.J.; Bleckley, M.K.; Conway, A.R.A.; Engle, R.W. A controlled-attention view of working-memory capacity. J. Exp. Psychol. Gen. 2001, 130, 169–183. [Google Scholar] [CrossRef]
- Shipstead, Z.; Yonehiro, J. The domain-specific and domain-general relationships of visuospatial working memory to reasoning ability. Psychon. Bull. Rev. 2016, 23, 1504–1512. [Google Scholar] [CrossRef]
- Süß, H.-M.; Oberauer, K.; Wittmann, W.W.; Wilhelm, O.; Schulze, R. Working-memory capacity explains reasoning ability and a little bit more. Intelligence 2002, 30, 261–288. [Google Scholar] [CrossRef]
- Conway, A.R.; Kane, M.J.; Engle, R.W. Working memory capacity and its relation to general intelligence. Trends Cogn. Sci. 2003, 7, 547–552. [Google Scholar] [CrossRef] [PubMed]
- Shipstead, Z.; Harrison, T.L.; Engle, R.W. Working memory capacity and fluid intelligence. Perspect. Psychol. Sci. 2016, 11, 771–799. [Google Scholar] [CrossRef] [Green Version]
- Kane, M.J.; Hambrick, D.Z.; Tuholski, S.W.; Wilhelm, O.; Payne, T.W.; Engle, R.W. The generality of working memory capacity: A latent-variable approach to verbal and visuospatial memory span and reasoning. J. Exp. Psychol. Gen. 2004, 133, 189–217. [Google Scholar] [CrossRef]
- Rudkin, S.J.; Pearson, D.G.; Logie, R.H. Executive processes in visual and spatial working memory tasks. Q. J. Exp. Psychol. 2007, 60, 79–100. [Google Scholar] [CrossRef]
- Hamilton, C.; Coates, R.; Heffernan, T. What develops in visuo-spatial working memory development? Eur. J. Cogn. Psychol. 2003, 15, 43–69. [Google Scholar] [CrossRef]
- Petrides, M.; Milner, B. Deficits on subject-ordered tasks after frontal-and temporal-lobe lesions in man. Neuropsychologia 1982, 20, 249–262. [Google Scholar] [CrossRef]
- Ardila, A.; Moreno, S. Neuropsychological test performance in Aruaco Indians: An exploratory study. J. Int. Neuropsychol. Soc. 2001, 7, 510–515. [Google Scholar] [CrossRef] [PubMed]
- Fonseca, M.D.F.; Dórea, J.G.; Bastos, W.R.; Marques, R.C.; Torres, J.P.; Malm, O. Poor psychometric scores of children living in isolated riverine and agrarian communities and fish-methylmercury exposure. NeuroToxicology 2008, 29, 1008–1015. [Google Scholar] [CrossRef] [PubMed]
- Berglund, M.; Lind, B.; Björnberg, K.A.; Palm, B.; Einarsson, Ö.; Vahter, M. Inter-individual variations of human mercury exposure biomarkers: A cross-sectional assessment. Environ. Health 2005, 4, 20. [Google Scholar] [CrossRef] [PubMed]
- Schrank, F.; Decker, S.; Garruto, J. Essentials of WJ IV Cognitive Abilities Assessment; John Wiley & Sons: New York, NY, USA, 2016. [Google Scholar]
- Corsi, P.M. Short Title Memory and the Medial Temporal Region of the Brain. Ph.D. Thesis, McGill University, Montreal, QC, Canada, 1972. [Google Scholar]
- Milner, B. Interhemispheric differences in the localization of psychological processes in man. Br. Med. Bull. 1971, 27, 272–277. [Google Scholar] [CrossRef] [PubMed]
- Kessels, P.R.C.; van Zandvoort, M.J.E.; Postma, A.; Kappelle, L.J.; de Haan, E.H.F. The Corsi Block-Tapping Task: Standardization and Normative Data the corsi block-tapping task. Appl. Neuropsychol. 2000, 7, 252–258. [Google Scholar] [CrossRef]
- Ross, T.P.; Hanouskova, E.; Giarla, K.; Calhoun, E.; Tucker, M. The reliability and validity of the self-ordered pointing task. Arch. Clin. Neuropsychol. 2007, 22, 449–458. [Google Scholar] [CrossRef] [Green Version]
- Ardila, A. Cultural values underlying psychometric cognitive testing. Neuropsychol. Rev. 2005, 15, 185–195. [Google Scholar] [CrossRef]
- Attneave, F.; Arnoult, M.D. The quantitative study of shape and pattern perception. Psychol. Bull. 1956, 53, 452–471. [Google Scholar] [CrossRef]
- Rock, D.; Price, I.R. Identifying culturally acceptable cognitive tests for use in remote northern Australia. BMC Psychol. 2019, 7, 62. [Google Scholar] [CrossRef] [PubMed]
- Bowie, C.R.; Harvey, P.D. Administration and interpretation of the trail making test. Nat. Protoc. 2006, 1, 2277–2281. [Google Scholar] [CrossRef] [PubMed]
- Kortte, K.B.; Horner, M.D.; Windham, W.K. The trail making test, part B: Cognitive flexibility or ability to maintain set? Appl. Neuropsychol. 2002, 9, 106–109. [Google Scholar] [CrossRef]
- Arbuthnott, K.; Frank, J. Trail making test, part B as a measure of executive control: Validation using a set-switching paradigm. J. Clin. Exp. Neuropsychol. 2000, 22, 518–528. [Google Scholar] [CrossRef]
- Stuss, D.T.; Bisschop, S.M.; Alexander, M.P.; Levine, B.; Katz, D.; Izukawa, D. The trail making test: A study in focal lesion patients. Psychol. Assess. 2001, 13, 230–239. [Google Scholar] [CrossRef] [PubMed]
- Barncord, S.W.; Wanlass, R.L. The symbol trail making test: Test development and utility as a measure of cognitive impairment. Appl. Neuropsychol. 2001, 8, 99–103. [Google Scholar] [CrossRef]
- Weinhouse, C.; Ortiz, E.J.; Berky, A.J.; Bullins, P.; Hare-Grogg, J.; Rogers, L.; Morales, A.-M.; Hsu-Kim, H.; Pan, W.K. Hair mercury level is associated with anemia and micronutrient status in children living near artisanal and small-scale gold mining in the Peruvian Amazon. Am. J. Trop. Med. Hyg. 2017, 97, 1886–1897. [Google Scholar] [CrossRef]
- Anticona, C.; Sebastian, M.S. Anemia and malnutrition in indigenous children and adolescents of the Peruvian Amazon in a context of lead exposure: A cross-sectional study. Glob. Health Action 2014, 7, 22888. [Google Scholar] [CrossRef] [Green Version]
- Rice, K.M.; Walker, E.M., Jr.; Wu, M.; Gillette, C.; Blough, E.R. Environmental mercury and its toxic effects. J. Prev. Med. Public Health 2014, 47, 74–83. [Google Scholar] [CrossRef]
- Pizzol, D.; Tudor, F.; Racalbuto, V.; Bertoldo, A.; Veronese, N.; Smith, L. Systematic review and meta-analysis found that malnutrition was associated with poor cognitive development. Acta Paediatr. 2021, 110, 2704–2710. [Google Scholar] [CrossRef]
- WHO. Evaluations of the Joint FAO/WHO Expert Committee on Food Additives (JECFA). Available online: https://apps.who.int/food-additives-contaminants-jecfa-database/Home/Chemical/3083 (accessed on 1 August 2022).
- Joint FAO/WHO Expert Committee on Food Additives (JECFA). Methylmercury. Summary and conclusions. In Proceedings of the 67th Joint FAO/WHO Expert Committee on Food Additives, Rome, Italy, 20–29 June 2006. [Google Scholar]
- Salthouse, T.A. What cognitive abilities are involved in trail-making performance? Intelligence 2011, 39, 222–232. [Google Scholar] [CrossRef] [PubMed]
- Salthouse, T.A. The aging of working memory. Neuropsychology 1994, 8, 535–543. [Google Scholar] [CrossRef]
- Cook, R.D.; Weisberg, S. Residuals and Influence in Regression; Chapman and Hall: New York, NY, USA, 1982. [Google Scholar]
- Langeland, A.L.; Hardin, R.D.; Neitzel, R.L. Mercury levels in human hair and farmed fish near artisanal and small-scale gold mining communities in the Madre de Dios River Basin, Peru. Int. J. Environ. Res. Public Health 2017, 14, 302. [Google Scholar] [CrossRef]
- Cowan, N.; Elliott, E.M.; Saults, J.S.; Morey, C.C.; Mattox, S.; Hismjatullina, A.; Conway, A.R. On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cogn. Psychol. 2005, 51, 42–100. [Google Scholar] [CrossRef] [PubMed]
- Miller, G.A. The magical number seven, plus-or-minus two or some limits on our capacity for processing information. Psychol. Rev. 1956, 2, 175–202. [Google Scholar] [CrossRef]
- Cowan, N. The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behav. Brain Sci. 2001, 24, 87–114. [Google Scholar] [CrossRef] [PubMed]
- Elliott, J.M. Forward digit span and articulation speed for Malay, English, and two Chinese dialects. Percept. Mot. Ski. 1992, 74, 291–295. [Google Scholar] [CrossRef]
- Naveh-Benjamin, M.; Ayres, T.J. Digit span, reading rate, and linguistic relativity. Q. J. Exp. Psychol. Sect. A 1986, 38, 739–751. [Google Scholar] [CrossRef]
- Ellis, N.C.; Hennelly, R.A. A bilingual word-length effect. Br. J. Psychol. 1980, 71, 43–51. [Google Scholar] [CrossRef]
- Johnson, A. Families of the Forest: The Matsigenka Indians of the Peruvian Amazon; University of California Press: Berkeley, CA, USA, 2003. [Google Scholar] [CrossRef]
- Donolato, E.; Giofrè, D.; Mammarella, I.C. Differences in verbal and visuospatial forward and backward order recall: A review of the literature. Front. Psychol. 2017, 8, 663. [Google Scholar] [CrossRef]
- Debes, F.; Budtz-Jørgensen, E.; Weihe, P.; White, R.F.; Grandjean, P. Impact of prenatal methylmercury exposure on neurobehavioral function at age 14 years. Neurotoxicol. Teratol. 2006, 28, 363–375. [Google Scholar] [CrossRef] [PubMed]
- Martin, T.A.; Hoffman, N.M.; Donders, J. Clinical utility of the trail making test ratio score. Appl. Neuropsychol. 2003, 10, 163–169. [Google Scholar] [CrossRef] [PubMed]
- Grandjean, P.; Weihe, P.; White, R.F.; Debes, F.P. Cognitive Performance of Children Prenatally Exposed to “Safe” Levels of Methylmercury; Elsevier: Amsterdam, The Netherlands, 1998. [Google Scholar]
- Stebbins, G.T. Neuropsychological testing. In Textbook of Clinical Neurology, 3rd ed.; Elsevier: Amsterdam, The Netherlands, 2007; pp. 539–557. [Google Scholar] [CrossRef]
- Gonzalez, D.J.X.; Arain, A.; Fernandez, L.E. Mercury exposure, risk factors, and perceptions among women of childbearing age in an artisanal gold mining region of the Peruvian Amazon. Environ. Res. 2019, 179 Pt A, 108786. [Google Scholar] [CrossRef] [PubMed]
Community | All Participants | Cacaotal | Maizal | Yomibato | |
---|---|---|---|---|---|
n | 30 | 11 | 3 | 16 | |
Gender | F (M) | 18 (12) | 6 (05) | 3 (0) | 9 (7) |
Age | average years (sd) | 29 (13.8) | 28 * (9.6) | 45 (16.2) | 26 (14.7) |
Education | |||||
none | 8 | 3 | 2 | 4 | |
primary | 12 | 6 | 1 | 5 | |
secondary | 10 | 2 | 0 | 7 | |
mean years | 4.77 (3.8) | 4.82 (3.68) | 1.33 (2.31) | 5.38 (3.99) | |
Fish Consumption | |||||
Total per Week | 4.10 (2.4) | 4.58 (1.8) | 3.73 (2.9) | 3.98 (2.5) | |
Body Mass Index | |||||
mean (sd) | 22.93 (2.72) | 22.8 (2.42) | 24.38 (3.25) | 22.75 (2.92) | |
<20 | 4 | 1 | 0 | 3 | |
Anemia | |||||
Hemoglobin | 11.77 (1.42) | 11.8 (1.56) | 11.5 (1.65) | 12.15 (1.25) | |
Males < 13.5, Females < 12 | 22 | 6 | 1 | 12 | |
Hg (ppm) | |||||
mean (sd) | 7.05 (2.40) | 6.04 (2.43) | 11.49 (2.40) | 3.61 (2.38) | |
min | 1.81 | 2.84 | 9.67 | 1.81 | |
max | 14.21 | 11.42 | 14.21 | 11.43 | |
Word Span | |||||
mean accuracy (sd) | 0.52 (0.19) | 0.45 (0.19) | 0.30 (0.11) | 0.60 (0.16) | |
Corsi Block Span | |||||
mean accuracy (sd) | 0.59 (0.27) | 0.47 (0.25) | 0.25 (0.14) | 0.73 (0.25) | |
SOPT Errors | |||||
mean errors (sd) | 4.23 (1.65) | 4.72 (1.38) | 4.67 (0.55) | 3.81 (1.90) |
Community | All Participants * | Yomibato | Cacaotal | |
---|---|---|---|---|
n | 19 | 14 | 5 | |
Gender | F (M) | 10 (9) | 7 (7) | 3 (2) |
Age | mean years | 23 (12.9) | 22 (12.61) | 21 (5.58) |
Education | ||||
mean years | 6.63 (3.50) | 6.29 (3.85) | 7.6 (2.30) | |
Hg (ppm) | ||||
mean (sd) | 4.63 (2.92) | 3.56 (2.54) | 7.12 (2.64) | |
min | 1.92 | 1.92 | 4.75 | |
max | 11.43 | 11.43 | 11.42 | |
Trail Making Test A “Shades” | ||||
mean percent accuracy (sd) | 0.68 (0.35) | 0.66 (0.34) | 0.68 (0.42) | |
Trail Making Test B “Shapes & Shades” | ||||
mean percent accuracy (sd) | 0.31 (0.32) | 0.34 0(.29) | 0.08 (0.11) |
Age | Education | BMI | Hemoglobin | Fish Consumption | Hg | Word Span | Corsi Block | SOPT Errors | |
---|---|---|---|---|---|---|---|---|---|
Age | 1.00 | ||||||||
Education | −0.47 * | 1.00 | |||||||
BMI | 0.26 | 0.29 | 1.00 | ||||||
Hemoglobin | −0.01 | 0.04 | 0.16 | 1.00 | |||||
Fish Consumption | 0.04 | 0.12 | −0.14 | −0.02 | 1.00 | ||||
Hg | 0.50 * | −0.21 | 0.11 | −0.13 | −0.13 | 1.00 | |||
Word Span | −0.56 * | 0.63 * | −0.08 | 0.31 | −0.13 | −0.38 * | 1.00 | ||
Corsi Block | −0.44 * | 0.59 * | −0.01 | 0.28 | −0.04 | −0.56 * | 0.62 * | 1.00 | |
SOPT Errors | 0.10 | −0.33 | −0.20 | −0.28 | 0.21 | 0.41 * | −0.34 | −0.31 | 1.00 |
y | Model Fit | x | b | 95% CI | p |
---|---|---|---|---|---|
Word Span Accuracy | R2 = 0.50, Adj R2 = 0.44 | Age | −0.00 | (−0.01, 0.00) | 0.16 |
F(3,26) = 8.65, p < 0.01 | Education | 0.02 | (0.01, 0.04) | 0.01 | |
Hg | −0.01 | (−0.03, 0.01) | 0.35 | ||
Corsi Block Accuracy | R2 = 0.55, Adj R2 = 0.49 | Age | 0.00 | (−0.01, 0.01) | 0.83 |
F(3,26) = 10.44, p < 0.01 | Education | 0.04 | (0.01, 0.06) | 0.00 | |
Hg | −0.04 | (−0.06, −0.01) | 0.01 | ||
SOPT Errors | R2 = 0.29, Adj R2 = 0.21 | Age | −0.04 | (−0.09, 0.01) | 0.14 |
F(3,26) = 3.57, p = 0.03 | Education | −0.16 | (−0.32, 0.00) | 0.05 | |
Hg | 0.23 | (0.05, 0.42) | 0.02 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Silman, A.K.; Chhabria, R.; Hafzalla, G.W.; Giffin, L.; Kucharski, K.; Myers, K.; Culquichicón, C.; Montero, S.; Lescano, A.G.; Vega, C.M.; et al. Impairment in Working Memory and Executive Function Associated with Mercury Exposure in Indigenous Populations in Upper Amazonian Peru. Int. J. Environ. Res. Public Health 2022, 19, 10989. https://doi.org/10.3390/ijerph191710989
Silman AK, Chhabria R, Hafzalla GW, Giffin L, Kucharski K, Myers K, Culquichicón C, Montero S, Lescano AG, Vega CM, et al. Impairment in Working Memory and Executive Function Associated with Mercury Exposure in Indigenous Populations in Upper Amazonian Peru. International Journal of Environmental Research and Public Health. 2022; 19(17):10989. https://doi.org/10.3390/ijerph191710989
Chicago/Turabian StyleSilman, Alycia K., Raveena Chhabria, George W. Hafzalla, Leahanne Giffin, Kimberly Kucharski, Katherine Myers, Carlos Culquichicón, Stephanie Montero, Andres G. Lescano, Claudia M. Vega, and et al. 2022. "Impairment in Working Memory and Executive Function Associated with Mercury Exposure in Indigenous Populations in Upper Amazonian Peru" International Journal of Environmental Research and Public Health 19, no. 17: 10989. https://doi.org/10.3390/ijerph191710989
APA StyleSilman, A. K., Chhabria, R., Hafzalla, G. W., Giffin, L., Kucharski, K., Myers, K., Culquichicón, C., Montero, S., Lescano, A. G., Vega, C. M., Fernandez, L. E., Silman, M. R., Kane, M. J., & Sanders, J. W. (2022). Impairment in Working Memory and Executive Function Associated with Mercury Exposure in Indigenous Populations in Upper Amazonian Peru. International Journal of Environmental Research and Public Health, 19(17), 10989. https://doi.org/10.3390/ijerph191710989