Assessing cardiovascular disease risk and social determinants of health: A comparative analysis of five risk estimation instruments using data from the Eastern Caribbean Health Outcomes Research Network

Jeremy I. Schwartz, Equity Research and Innovation Center, Section of General Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
Christina Howitt, George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, The University of the West Indies, Barbados.
Sumitha Raman, Division of General Internal Medicine, George Washington University School of Medicine and Health Sciences, Washington, DC, United States of America.
Sanya Nair, Yale University, New Haven, Connecticut, United States of America.
Saria Hassan, Division of General Internal Medicine, Emory Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America.
Carol Oladele, Equity Research and Innovation Center, Section of General Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
Ian R. Hambleton, George Alleyne Chronic Disease Research Centre, Caribbean Institute for Health Research, The University of the West Indies, Barbados.
Daniel F. Sarpong, Section of General Internal Medicine and Office of Health Equity Research, Yale School of Medicine, New Haven, Connecticut, United States of America.
Oswald P. Adams, Department of Family Medicine, Faculty of Medical Sciences, University of the West Indies Cave Hill, Cave Hill, Barbados.
Rohan G. Maharaj, Department of Paraclinical Sciences, University of the West Indies, Saint Augustine, Trinidad and Tobago.
Cruz M. Nazario, Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan, Puerto Rico.
Maxine Nunez, School of Nursing, University of the Virgin Islands, St. Thomas, US Virgin Islands.
Marcella Nunez-Smith, Equity Research and Innovation Center, Section of General Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.

Document Type

Journal Article

Publication Date

1-1-2025

Journal

PloS one

Volume

20

Issue

1

DOI

10.1371/journal.pone.0316577

Abstract

BACKGROUND: Accurate assessment of cardiovascular disease (CVD) risk is crucial for effective prevention and resource allocation. However, few CVD risk estimation tools consider social determinants of health (SDoH), despite their known impact on CVD risk. We aimed to estimate 10-year CVD risk in the Eastern Caribbean Health Outcomes Research Network Cohort Study (ECS) across multiple risk estimation instruments and assess the association between SDoH and CVD risk. METHODS: Five widely used CVD risk estimation tools (Framingham and WHO laboratory, both laboratory and non-laboratory-based, and ASCVD) were applied using data from ECS participants aged 40-74 without a history of CVD. SDoH variables included educational attainment, occupational status, household food security, and perceived social status. Multivariable logistic regression models were used to compare differences in the association between selected SDoH and high CVD risk according to the five instruments. FINDINGS: Among 1,777 adult participants, estimated 10-year CVD risk varied substantially across tools. Framingham non-lab and ASCVD demonstrated strong agreement in categorizing participants as high risk. Framingham non-lab categorized the greatest percentage as high risk, followed by Framingham lab, ASCVD, WHO lab, and WHO non-lab. Fifteen times more people were classified as high risk by Framingham non-lab compared with WHO non-lab (31% vs 2%). Mean estimated 10-year risk in the sample was over 2.5 times higher using Framingham non-lab vs WHO non-lab (17.3% vs 6.6%). We found associations between food insecurity, those with the lowest level compared to the highest level of education, and non-professional occupation and increased estimated CVD risk. INTERPRETATION: Our findings highlight significant discrepancies in CVD risk estimation across tools and underscore the potential impact of incorporating SDoH into risk assessment. Further research is needed to validate and refine existing risk tools, particularly in ethnically diverse populations and resource-constrained settings, and to develop race- and ethnicity-free risk estimation models that consider SDoH.

Department

Medicine

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