Evidence map›Paper›PMID 38946989›Full record

ArticleResearch square2024

Assessing the Risk of Heart Attack: A Bayesian Kernel Machine Regression Analysis of Heavy Metal Mixtures.

Boubakari Ibrahimou, Kazi Tanvir Hasan, Shelbie Burchfield, Hamisu Salihu, Yiliang Zhu, Getachew Dagne, Mario De La Rosa, Assefa Melesse, Roberto Lucchini, Zoran Bursac

Abstract readPreprint
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In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Boubakari IbrahimouFlorida International University, Robert Stempel College of Public Health & Social Work, Department of Biostatistics.
Kazi Tanvir HasanFlorida International University, Robert Stempel College of Public Health & Social Work, Department of Biostatistics.
Shelbie BurchfieldFlorida International University, Robert Stempel College of Public Health & Social Work, Department of Biostatistics.
Hamisu SalihuBaylor College of Medicine, Center of Excellence in Health Equity, Training and Research.
Yiliang ZhuUniversity of New Mexico, Clinical and Translational Science Center.
Getachew DagneUniversity of South Florida, College of Public Health.
Mario De La RosaFlorida International University, Robert Stempel College of Public Health & Social Work, Center for Research on US Latino HIV/AIDS and Drug Abuse.
Assefa MelesseFlorida International University, College of Arts, Sciences & Education, Department of Earth and Environment.
Roberto LucchiniFlorida International University, Robert Stempel College of Public Health & Social Work, Department of Environmental Health Sciences.
Zoran BursacFlorida International University, Robert Stempel College of Public Health & Social Work, Department of Biostatistics.

Funding

Particulate Matter (PM) Metals and Racial Disparity in Cardiovascular (CVD) Risk FactorsK01HL146944 · NHLBI · FLORIDA INTERNATIONAL UNIVERSITY · PI IBRAHIMOU, BOUBAKARI · 2020 to 2024
$878k
NHLBI NIH HHS K01 HL146944
6 · The paper itself

Abstract

Background: The assessment of heavy metals' effects on human health is frequently limited to investigating one metal or a group of related metals. The effect of heavy metals mixture on heart attack is unknown. Methods: This study applied the Bayesian kernel machine regression model (BKMR) to the 2011-2016 National Health and Nutrition Examination Survey (NHANES) data to investigate the association between heavy metal mixture exposure with heart attack. 2972 participants over the age of 20 were included in the study. Results: Results indicate that heart attack patients have higher levels of cadmium and lead in the blood and cadmium, cobalt, and tin in the urine, while having lower levels of mercury, manganese, and selenium in the blood and manganese, barium, tungsten, and strontium in the urine. The estimated risk of heart attack showed a negative association of 0.0030 units when all the metals were at their 25 Conclusions: This study suggests a possible association between heavy metal mixture exposure and heart attack and, additionally, demonstrates how the BKMR model can be used to investigate new combinations of exposures in future studies.

Indexed as

Bayesian kernel machine regressionCardiovascular diseaseHeart attackHeavy metal mixturesNHANES

Identifiers

PMID38946989
PMCPMC11213216

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.