Evidence map›Paper›PMID 41018681›Full record

ArticleHealth information science and systems2025

Clustering environmental pollutants associated with increased risk of metabolic disease: a hierarchical analysis.

Brooke Scardino, Akshat Agrawal, Diensn G Xing, Jackson L St Pierre, Md Mostafizur Rahman Bhuiyan, Kanon Kamronnaher, Md Shenuarin Bhuiyan, Oren Rom, Steven A Conrad, John A Vanchiere and 3 more

Abstract read
In one paragraph

Article in Health information science and systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Brooke Scardino *Division of Clinical Informatics, Department of Medicine, Louisiana State University Health Sciences Center at Shreveport, PO Box 33932, Shreveport, LA 71130-3932 USA.
Akshat Agrawal *Division of Clinical Informatics, Department of Medicine, Louisiana State University Health Sciences Center at Shreveport, PO Box 33932, Shreveport, LA 71130-3932 USA.
Diensn G XingDivision of Clinical Informatics, Department of Medicine, Louisiana State University Health Sciences Center at Shreveport, PO Box 33932, Shreveport, LA 71130-3932 USA.
Jackson L St PierreDepartment of Medicine, New York Institute of Technology College of Osteopathic Medicine, Jonesboro, AR 72401 USA.
Md Mostafizur Rahman BhuiyanDepartment of Pediatric Cardiology, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh.
Kanon KamronnaherDepartment of Mathematical and Statistical Science, Clemson University, Clemson, SC 29634 USA.
Md Shenuarin BhuiyanDepartment of Pathology and Translational Pathobiology, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103 USA.
Oren RomDepartment of Pathology and Translational Pathobiology, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103 USA.
Steven A ConradDivision of Clinical Informatics, Department of Medicine, Louisiana State University Health Sciences Center at Shreveport, PO Box 33932, Shreveport, LA 71130-3932 USA.
John A VanchiereDivision of Clinical Informatics, Department of Medicine, Louisiana State University Health Sciences Center at Shreveport, PO Box 33932, Shreveport, LA 71130-3932 USA.
A Wayne OrrDepartment of Pathology and Translational Pathobiology, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103 USA.
Christopher G KevilDepartment of Pathology and Translational Pathobiology, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103 USA.
Mohammad Alfrad Nobel BhuiyanDivision of Clinical Informatics, Department of Medicine, Louisiana State University Health Sciences Center at Shreveport, PO Box 33932, Shreveport, LA 71130-3932 USA.ORCID 0000-0002-6011-2624

Funding

Nck Adaptor Proteins in Atherogenic Endothelial ActivationR01HL133497 · NHLBI · LOUISIANA STATE UNIV HSC SHREVEPORT · PI ORR, ANTHONY WAYNE · 2016 to 2024
$3.8M
Sigmar1 in lipid metabolismR01HL145753 · NHLBI · LOUISIANA STATE UNIV HSC SHREVEPORT · PI BHUIYAN, MD. SHENUARIN · 2019 to 2023
$2.6M
EphA2 regulation of atherosclerotic smooth muscle phenotypeR01HL173972 · NHLBI · LOUISIANA STATE UNIV HSC SHREVEPORT · PI Anthony Wayne Orr · 2024 to 2026
$2.1M
Lipidated Amino Acids in Cardiometabolic DiseasesR01DK134011 · NIDDK · LOUISIANA STATE UNIV HSC SHREVEPORT · PI Oren Rom · 2022 to 2026
$2.1M
Dysregulated Oxalate Metabolism in Cardiometabolic DiseasesR01DK136685 · NIDDK · LOUISIANA STATE UNIV HSC SHREVEPORT · PI Oren Rom · 2023 to 2026
$1.7M
Mechanisms of glycine-based therapy for atherosclerosisR00HL150233 · NHLBI · LOUISIANA STATE UNIV HSC SHREVEPORT · PI ROM, OREN SHALOM · 2021 to 2023
$747k
NHLBI NIH HHS R00 HL150233NHLBI NIH HHS R01 HL133497NHLBI NIH HHS R01 HL145753NHLBI NIH HHS R01 HL173972NIDDK NIH HHS R01 DK134011NIDDK NIH HHS R01 DK136685
6 · The paper itself

Abstract

Background: Metabolic syndrome (MetS), which affects one-third of the population of the United States, is a risk factor for chronic diseases such as cardiovascular diseases, stroke, and type 2 diabetes mellitus. Heavy metals (HM) and volatile organic compounds (VOC) are environmental factors typically occurring as mixtures. Although exposures to these substances have been studied separately, the impact of combined HM and VOC exposure on humans and their subsequent risk of developing MetS has not been explored. This study investigates whether combined exposure to HMs and VOCs affects the risk of developing MetS. Methods: The National Health and Nutrition Examination Survey database from 2011 to 2020 was used to determine exposure to HMs and VOCs detected in urine samples from individuals with MetS. Multiple Chi-squared and t-tests were performed to identify variables significantly associated with MetS. Logistic regression analysis was performed on unmatched and age-matched 1:1 case-control data to evaluate whether an association exists among HMs, VOCs, and demographic factors and MetS. A hierarchical cluster analysis was performed to identify combinations of HMs and VOCs linked with an increased risk of MetS. Results: Logistic regression analysis on unmatched and matched data showed that increasing age and female sex were significantly associated ( Conclusion: This study revealed that age, lower socioeconomic status, and multiple exposures to combined HM and VOC may have a greater impact with an increased risk of MetS. Cluster analysis highlighted the potential combination of the exposures linked to MetS and the likelihood that demographic factors affect MetS more than exposure to HMs and VOCs. However, further research is needed. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-025-00375-1.

Indexed as

Heavy metalsMetabolic syndromeVolatile organic compounds

Identifiers

PMID41018681
PMCPMC12460862

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.