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Comparative Study
. 2025 Jan 24;20(1):e0316577.
doi: 10.1371/journal.pone.0316577. eCollection 2025.

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  1 , Christina Howitt  2 , Sumitha Raman  3 , Sanya Nair  4 , Saria Hassan  5 , Carol Oladele  1 , Ian R Hambleton  2 , Daniel F Sarpong  6 , Oswald P Adams  7 , Rohan G Maharaj  8 , Cruz M Nazario  9 , Maxine Nunez  10 , Marcella Nunez-Smith  1
Affiliations
Comparative Study

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 et al. PLoS One. .

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flowchart of sample composition.
Fig 2
Fig 2. Bar chart showing 10-year CVD risk categorization in the ECHORN cohort according to five different risk estimator tools.
Fig 3
Fig 3. Agreement between high-risk categories of five cardiovascular risk estimator tools in the ECHORN cohort.
See this image and copyright information in PMC

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