Mercury Exposure and Health Effects in Indigenous People from the Brazilian Amazon—Literature-Scoping Review
Abstract
1. Background
2. Material and Methods
2.1. Search Strategy and Information Sources
2.2. Eligibility Criteria
2.3. Data Selection and Extraction Process
3. Results
3.1. Effects of Mercury on Adults
3.2. Effects of Mercury on Mothers and Children
3.3. Maternal–Fetal Risks
3.4. Risk of Bias
4. Discussion
4.1. Mercury Exposure
4.2. Genetics
4.3. Effects on Child Growth
4.4. Effects on Blood Pressure (BP)
4.5. Effects on Mental Health and the Central Nervous System
5. Limitations
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Author/Year | Location/ Indigenos/n | Hg (µg/g) Children | Hg (µg/g) Mother | Hg (µg/g) General Population | Percentage of Individuals Exposed | Clinical Outcome |
---|---|---|---|---|---|---|
Barbosa A. C. et al., 1998 [26] | (Pará) Kayapó (Kikretum): 251 | 6.55 (2.0–20.4) | 8.30 (0.8–13.1) | NI | 25% > 10 µg/g | NI |
Campos M. S. et al., 2002 [27] | (Rondônia)Wari Pacaa Novos: 13 | NI | NI | 12.1 ± 0.15 | NI | NI |
Santos E. C. O. et al., 2002 [25] | Munduruku Sai Cinza: 320 | X: 14.45 (7–12 anos) | X: 15.70 (14–44 anos) | X: 16 ± 18.9 | NI | NI |
Santos E. C. O. et al., 2003 [28] | (Rondônia) Pakaanova/910 | X: 10.54 (<2 anos) X: 9.34 3–5 anos | X: 8.91 | X: 8.37 (0.52–83.89) | NI | NI |
Dórea J. G. et al., 2005 [23] | (Pará) 3 vilas Munduruku (Rondônia) Kayabi: 47 | NI | NI | X: 2.3 ± 1.4–6.0 ± 2.9 X: 12.8 ± 7.0 | NI | NI |
Klautau-Guimarães M. N. et al., 2005 [24] | (Pará) Munduruku/117 (Rondônia) Kayabi/65 | NI | NI | 3.65 ± 1.88– 4.26 ± 2.16 11.97 ± 6.82– 17.86 ± 9.82 | NI | 0% GSTM1 null 26% GSTM1 null |
Vega C. M. et al., 2018 [15] | (Rondônia) Yanomami/239 | NI | NI | 0.4–22.1 | 92.3% Hg ≥ 6 | NI |
Basta P. C. et al., 2021 [3] | (Pará) Munduruku (3 villages)/197 | NI | NI | 1.4–23.9 | 57.9 Hg ≥ 6 | Association with hypertension in women |
Oliveira R. A. A. et al., 2021 [7] | (Pará) Munduruku (3 villages)/110 | NI | NI | XMeHg: 8.7 ± 4.5 7.4 (2.0–22.8) | NI | MeHg > 10 µg/g A two-fold increase in the likelihood of cognitive deficits and verbal impairment was observed in individuals aged 12 and older. |
Achatz R. W. et al., 2021 [5] | (Pará) Munduruku (3 villages)/109 | NI | NI | MeHg: 7.4 (2.0–22.8) | 70% MeHg ≥ 6 28% MeHg ≥ 10 | MeHg ≥ 10 Associated with worse mental health indicators. |
Kempton J. W. et al., 2021 [13] | (Pará) Munduruku/31 15 mothers 16 children | NI | 7.11 | NI | 62% MeHg ≥ 6 18.8 MeHg > 6.0 | Gross motor retardation and anemia |
Perini J. A. et al., 2021 [14] | (Pará) Munduruku/102 Under 15 years old | 7.0 ± 4.5 (1.4–23.9) | NI | NI | 49% MeHg ≥ 6 | ALAD polymorphism (2/102 children). Neurological disorders. |
Silva M. C. et al., 2023 [29] | (Pará) Munduruku /107 Sawré Muybu Poxo Muybu Sawré Aboy | NI | NI | 8.5 ± 4.3 6.9 ± 3.5 7.4 ± 2.3 13.5 ± 4.6 | NI | GSTP1 SNP (MAF) minor allele frequency G 57% 21% 15% 36.8% (total) |
Jacques A. D. et al., 2024 [30] | (Roraima) Yanomami/120 | 3.30 (0.16 ± 10.20) | NI | NI | NI | Negative Association: Lower TIQ score; increased age; Hg levels; fish consumption |
Rebouças B. H. et al., 2024 [31] | (Roraima) Yanomami/154 | NI | NI | NI | 3.9 ± 1.7 | Chronic exposure to HG can lead to significant neurotoxicity |
Study | Inclusion Criteria | Sampling | Exposure and Outcome Measures | Control of Confounding Factors | Statistical Methods Used | Bias Classification |
---|---|---|---|---|---|---|
Campos et al. (2002) [27] | Clear criteria but small sample; unclear criteria | Small and non-representative sample | Adequate hair samples but limited focus | No control for important confounding factors | Correlation analysis without multivariate adjustment | High |
Dórea et al. (2005) [23] | Clear criteria but non-probabilistic sampling | Small sample (249 Munduruku, 47 Kayabi) | Reliable mercury measurements but no multivariate evaluation | No explicit control for confounding factors | Pearson correlation; lack of multivariate analysis | Moderate |
Achatz et al. (2021) [5] | Clear criteria for the Munduruku population | Limited sample of 109 participants | Adequate hair samples; health evaluation subjective | No confounding control | Appropriate Poisson regression | Moderate |
Barbosa et al. (1998) [26] | Clear criteria focused on indigenous women and children | Limited representation; small sample size | Reliable mercury measurement methodology | No control for dietary and other confounding factors | Adequate variance testing | Moderate |
Klautau-Guimarães et al. (2005) [24] | Clear inclusion criteria for Kayabi and Munduruku | Adequate sampling of indigenous populations | Reliable mercury measures and genetic evaluation | Partial control; environmental factors not extensively covered | ANOVA and chi-square used appropriately | Moderate |
Jacques et al. (2024) [30] | Clear criteria focused on Yanomami children | Representative sampling from eight villages | Reliable mercury measurements; cultural limitations in cognition assessment | Partial control for age and fish consumption | Robust analysis of mercury levels and IQ | Moderate |
Vega et al. (2018) [15] | Clear criteria but limited availability of participants | Representative sampling across various villages | Reliable mercury measurements; direct measurement methods | No adequate control of confounding factors | Appropriate Poisson and Kruskal–Wallis analysis | Moderate |
Oliveira et al. (2021) [7] | Well-established criteria | Small sample from three villages | Reliable hair sample measurements | No explicit control of confounding factors | Kruskal–Wallis test adequate but limited by sample size | Moderate |
Kempton et al. (2021) [13] | Well-defined criteria focusing on women and children | Small sample size; no probabilistic sampling | Reliable mercury measures; limited sample | No adequate control of confounding factors | Wilcoxon and Kruskal–Wallis adequate but limited power | Moderate |
Santos et al. (2002) [25] | Clear criteria but no probabilistic sampling | Small sample; limited representativeness | Reliable hair samples; limited health evaluation focus | No control of important confounding factors | Kruskal–Wallis and Spearman analysis appropriate | Moderate |
Basta et al. (2021) [3] | Well-defined criteria focusing on five regions | Representative sample from various fish species | Robust mercury measurements | Adequate control of age and type of fish | Well-conducted toxicological risk analysis | Low |
Perini et al. (2021) [14] | Clear criteria focusing on children under 15 | Representative sample; no refusals | Accurate mercury measurements and genotyping | Adequate control for age and fish consumption | Genetic analyses and associations with clinical outcomes | Low |
Rebouças et al. (2024) [31] | Clear and comprehensive criteria | Adequate and representative sample | Robust hair sample measurements | Control of confounding factors like age and health | Robust analysis with Poisson and ROC | Low |
Silva et al. (2023) [29] | Clear criteria for Indigenous Munduruku | Specific sampling; no refusals | Reliable mercury and GSTP1 assessments | Partial control for age; dietary factors not discussed | Logistic regression analysis used appropriately | Low |
Type of Exposure | Symptoms in Adults | Symptoms in Children | Fetal Risks |
---|---|---|---|
Acute Exposure | Tremors | Irritability | Premature birth |
Headache | Concentration difficulties | Low birth weight | |
Nausea and vomiting | Skin rashes | Fetal death | |
Dizziness | Loss of appetite | ||
Respiratory difficulty | |||
Gastrointestinal disorders | |||
Chronic Exposure | Cognitive impairments | Cognitive development deficits | Congenital malformations |
Peripheral neuropathy | Motor delays | Delayed neuropsychomotor development | |
Memory loss | Learning difficulties | Permanent cognitive disabilities | |
Motor difficulties | Persistent neurological deficiencies | Risk of cerebral palsy | |
Visual and auditory changes | |||
Chronic fatigue |
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da Conceição Nascimento Pinheiro, M.; Cardoso, F.C.; do Nascimento de Aviz, L.B.; de Freitas Junior, J.A.B.; da Silva, M.C.F.; Silva, M.T.; Pinheiro, D.N.; Carneiro, S.R.; Pinheiro, E.R.; Corvelo, T.C.O. Mercury Exposure and Health Effects in Indigenous People from the Brazilian Amazon—Literature-Scoping Review. Int. J. Environ. Res. Public Health 2025, 22, 1159. https://doi.org/10.3390/ijerph22081159
da Conceição Nascimento Pinheiro M, Cardoso FC, do Nascimento de Aviz LB, de Freitas Junior JAB, da Silva MCF, Silva MT, Pinheiro DN, Carneiro SR, Pinheiro ER, Corvelo TCO. Mercury Exposure and Health Effects in Indigenous People from the Brazilian Amazon—Literature-Scoping Review. International Journal of Environmental Research and Public Health. 2025; 22(8):1159. https://doi.org/10.3390/ijerph22081159
Chicago/Turabian Styleda Conceição Nascimento Pinheiro, Maria, Fabiana Costa Cardoso, Leonardo Breno do Nascimento de Aviz, José Aglair Barbosa de Freitas Junior, Márcia Cristina Freitas da Silva, Margareth Tavares Silva, Dirce Nascimento Pinheiro, Saul Rassy Carneiro, Elaine Rodrigues Pinheiro, and Tereza Cristina Oliveira Corvelo. 2025. "Mercury Exposure and Health Effects in Indigenous People from the Brazilian Amazon—Literature-Scoping Review" International Journal of Environmental Research and Public Health 22, no. 8: 1159. https://doi.org/10.3390/ijerph22081159
APA Styleda Conceição Nascimento Pinheiro, M., Cardoso, F. C., do Nascimento de Aviz, L. B., de Freitas Junior, J. A. B., da Silva, M. C. F., Silva, M. T., Pinheiro, D. N., Carneiro, S. R., Pinheiro, E. R., & Corvelo, T. C. O. (2025). Mercury Exposure and Health Effects in Indigenous People from the Brazilian Amazon—Literature-Scoping Review. International Journal of Environmental Research and Public Health, 22(8), 1159. https://doi.org/10.3390/ijerph22081159