Environmental toxic metal contaminants and risk of cardiovascular disease: systematic review and meta-analysis
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OBJECTIVE: To conduct a systematic review and meta-analysis of epidemiological studies investigating the association of arsenic, lead, cadmium, mercury, and copper with cardiovascular disease. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Embase, and Web of Science searched up to December 2017. REVIEW METHODS: Studies reporting risk estimates for total cardiovascular disease, coronary heart disease, and stroke for levels of arsenic, lead, cadmium, mercury, or copper were included. Two investigators independently extracted information on study characteristics and outcomes in accordance with PRISMA and MOOSE guidelines. Relative risks were standardised to a common scale and pooled across studies for each marker using random effects meta-analyses. RESULTS: The review identified 37 unique studies comprising 348 259 non-overlapping participants, with 13 033 coronary heart disease, 4205 stroke, and 15 274 cardiovascular disease outcomes in aggregate. Comparing top versus bottom thirds of baseline levels, pooled relative risks for arsenic and lead were 1.30 (95% confidence interval 1.04 to 1.63) and 1.43 (1.16 to 1.76) for cardiovascular disease, 1.23 (1.04 to 1.45) and 1.85 (1.27 to 2.69) for coronary heart disease, and 1.15 (0.92 to 1.43) and 1.63 (1.14 to 2.34) for stroke. Relative risks for cadmium and copper were 1.33 (1.09 to 1.64) and 1.81 (1.05 to 3.11) for cardiovascular disease, 1.29 (0.98 to 1.71) and 2.22 (1.31 to 3.74) for coronary heart disease, and 1.72 (1.29 to 2.28) and 1.29 (0.77 to 2.17) for stroke. Mercury had no distinctive association with cardiovascular outcomes. There was a linear dose-response relation for arsenic, lead, and cadmium with cardiovascular disease outcomes. CONCLUSION: Exposure to arsenic, lead, cadmium, and copper is associated with an increased risk of cardiovascular disease and coronary heart disease. Mercury is not associated with cardiovascular risk. These findings reinforce the importance of environmental toxic metals in cardiovascular risk, beyond the roles of conventional behavioural risk factors.
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Toxic metals such as As, Cd, Pb, and Hg are associated with cancer, cognitive impairment, cardiovascular diseases, and other chronic health conditions.
“Toxic metals such as As, Cd, Pb, and Hg are associated with cancer, cognitive impairment, cardiovascular diseases, and other chronic health conditions [228,229].”
From Navigating the potential of algal peptides: health effects, market applications, and scientific challenges (2026) · cites this paper as [229]
The Introduction links chronic exposure to arsenic, cadmium, and other toxic metals with cancer, while the Results link arsenic, cadmium, and lead with cardiovascular disease. The paper does not address cognitive impairment in the supplied passages, and its Discussion conclusion says mercury was not associated with cardiovascular risk. It therefore does not support the full claim for all four metals and conditions. (LLM, conf=0.89)
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Pollution and health: a progress update
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“Toxic metals such as As, Cd, Pb, and Hg are associated with cancer, cognitive impairment, cardiovascular diseases, and other chronic health conditions [228,229].”
- Authors
- Chowdhury, R., Ramond, A., O’Keeffe, L. M., Shahzad, S., Kunutsor, S. K., Muka, T., Gregson, J., Willeit, P., Warnakula, S., Khan, H., Chowdhury, S., Gobin, R., Franco, O. H., & Di Angelantonio, E.
- Affiliations
- University of Cambridge (GB)
- University of Bristol (GB)
- University Hospitals Bristol NHS Foundation Trust (GB)
- Institute of Social and Preventive Medicine (CH)
- London School of Hygiene & Tropical Medicine (GB)
- Innsbruck Medical University (AT)
- Emory University (US)
- University of Guyana (GY)
- Corresponding author
- Shahzad, Sara
- ORCID
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2018-08-29
- Volume
- 362
- Pages
- k3310
- ISSN
- 1756-1833 (ISSN-L)
- 0959-8138
- PMC
- PMC6113772
- OpenAlex
- W2888857894
- Cited by
- 638
- References
- 114
- Citations by year
- 2026: 56 · 2025: 92 · 2024: 106 · 2023: 136 · 2022: 79 · 2021: 84 · 2020: 52 · 2019: 28 · 2018: 5
- FWCI
- 4.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- BMJ (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by-nc)
- Bern Open Repository and Information System (University of Bern) (submittedVersion, cc-by-nc)
- HighWire Press Open Archive (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion, cc-by-nc)
- Apollo
- Funders
- National Institute for Health and Care Research (NF-SI-0617-10113, NF-SI-0512-10165)
- British Heart Foundation (RG/13/13/30194)
- Medical Research Council (MR/M014509/1, MR/L003120/1, MR/N015959/1)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Heavy Metal Exposure and Toxicity
- Physical Sciences › Environmental Science › Pollution › Heavy metals in environment
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Environmental Toxicology and Ecotoxicology
- Keywords
- toxic metals, heavy metal exposure, cardiovascular disease, coronary artery disease, stroke, arsenic, lead, cadmium, mercury, copper, dose-response relationship, environmental pollution, cardiovascular risk factors, biomarkers of exposure, occupational exposure, dietary exposure, air pollution, water pollution, leaded gasoline, cardiovascular hospitalization
- MeSH terms
- Cardiovascular Diseases, Environmental Exposure, Environmental Monitoring, Environmental Pollutants, Environmental Pollution, Humans, Risk Factors, Risk Assessment, Metals, Heavy
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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