NDLI: Use of biomarkers of metals to improve prediction performance of cardiovascular disease mortality

Content Provider	Springer Nature : BioMed Central
Author	Fansler, Samuel D. Bakulski, Kelly M. Park, Sung Kyun Walker, Erika Wang, Xin
Abstract	Background Whether including additional environmental risk factors improves cardiovascular disease (CVD) prediction is unclear. We attempted to improve CVD mortality prediction performance beyond traditional CVD risk factors by additionally using metals measured in the urine and blood and with statistical machine learning methods. Methods Our sample included 7,085 U.S. adults aged 40 years or older from the National Health and Nutrition Examination Survey 2003–2004 through 2015–2016, linked with the National Death Index through December 31, 2019. Data were randomly split into a 50/50 training dataset used to construct CVD mortality prediction models (n = 3542) and testing dataset used as validation to assess prediction performance (n = 3543). Relative to the traditional risk factors (age, sex, race/ethnicity, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol, hypertension, and diabetes), we compared models with an additional 17 blood and urinary metal concentrations. To build the prediction models, we used Cox proportional hazards, elastic-net (ENET) penalized Cox, and random survival forest methods. Results 420 participants died from CVD with 8.8 mean years of follow-up. Blood lead, cadmium, and mercury were associated (p < 0.005) with CVD mortality. Including these blood metals in a Cox model, initially containing only traditional risk factors, raised the C-index from 0.845 to 0.847. Additionally, the Net Reclassification Index showed that 23% of participants received a more accurate risk prediction. Further inclusion of urinary metals improved risk reclassification but not risk discrimination. Conclusions Incorporating blood metals slightly improved CVD mortality risk discrimination, while blood and urinary metals enhanced risk reclassification, highlighting their potential utility in improving cardiovascular risk assessments.
Related Links	https://ehjournal.biomedcentral.com/counter/pdf/10.1186/s12940-024-01137-4.pdf
Ending Page	10
Page Count	10
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s12940-024-01137-4
Journal	Environmental Health
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2024-11-07
Access Restriction	Open
Subject Keyword	Occupational Medicine Industrial Medicine Public Health Environmental Health Metal mixtures Cardiovascular Disease Mortality Machine learning Environmental exposures NHANES Occupational Medicine/Industrial Medicine
Content Type	Text
Resource Type	Article
Subject	Health, Toxicology and Mutagenesis Public Health, Environmental and Occupational Health
Journal Impact Factor	5.4/2023
5-Year Journal Impact Factor	6.7/2023

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES

Prenatal metal exposures and kidney function in adolescence in Project Viva

Potential benefits of joint hypothetical interventions on diet, lead, and cadmium on mortality in US adults

Low-level plasticizer exposure and all-cause and cardiovascular disease mortality in the general population

A family of partial-linear single-index models for analyzing complex environmental exposures with continuous, categorical, time-to-event, and longitudinal health outcomes

Urinary fluoride levels and metal co-exposures among pregnant women in Los Angeles, California

Urinary trace metals, maternal circulating angiogenic biomarkers, and preeclampsia: a single-contaminant and mixture-based approach

Blood cadmium levels and Alzheimer’s disease mortality risk in older US adults

Metal biomarker mixtures and blood pressure in the United States: cross-sectional findings from the 1999-2006 National Health and Nutrition Examination Survey (NHANES)

Use of biomarkers of metals to improve prediction performance of cardiovascular disease mortality

Similar Documents

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES

Prenatal metal exposures and kidney function in adolescence in Project Viva

Potential benefits of joint hypothetical interventions on diet, lead, and cadmium on mortality in US adults

Low-level plasticizer exposure and all-cause and cardiovascular disease mortality in the general population

A family of partial-linear single-index models for analyzing complex environmental exposures with continuous, categorical, time-to-event, and longitudinal health outcomes

Urinary fluoride levels and metal co-exposures among pregnant women in Los Angeles, California

Urinary trace metals, maternal circulating angiogenic biomarkers, and preeclampsia: a single-contaminant and mixture-based approach

Blood cadmium levels and Alzheimer’s disease mortality risk in older US adults

Metal biomarker mixtures and blood pressure in the United States: cross-sectional findings from the 1999-2006 National Health and Nutrition Examination Survey (NHANES)

Use of biomarkers of metals to improve prediction performance of cardiovascular disease mortality