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Development and validation of a polysocial risk score for atherosclerotic cardiovascular disease
Journal article   Open access   Peer reviewed

Development and validation of a polysocial risk score for atherosclerotic cardiovascular disease

Zulqarnain Javed, Javier Valero-Elizondo, Ramzi Dudum, Safi U. Khan, Prachi Dubey, Adnan A. Hyder, Jiaqiong Xu, Usama Bilal, Bita A. Kash, Miguel Cainzos-Achirica, …
American journal of preventive cardiology, v 8, 100251
Dec 2021
DOI: https://doi.org/10.1016/j.ajpc.2021.100251
PMID: 34553187
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1016/j.ajpc.2021.100251View
Published, Version of Record (VoR)CC BY-NC-ND V4.0,  Open

Abstract

ASCVD Cardiovascular disease Polysocial risk score Social determinants of health
•Social determinants of health may improve identification of atherosclerotic cardiovascular disease – beyond traditional risk factors.•We provide the first, validated, polysocial risk score – the PsRS – for atherosclerotic cardiovascular disease.•PsRS is a robust tool to quantify cumulative social disadvantage.•PsRS offers unique opportunities to improve cardiovascular risk prediction algorithms.•Our findings may help highlight, and address disparities in cardiovascular disease. To date, the extent to which social determinants of health (SDOH) may help identify individuals with atherosclerotic cardiovascular disease (ASCVD) – beyond traditional risk factors – has not been quantified using a cumulative social disadvantage approach. The objective of this study was to develop, and validate, a polysocial risk score (PsRS) for prevalent ASCVD in a nationally representative sample of adults in the United States (US). We used data from the 2013–2017 National Health Interview Survey. A total of 38 SDOH were identified from the database. Stepwise and criterion-based selection approaches were applied to derive PsRS, after adjusting for traditional risk factors. Logistic regression models were fitted to assign risk scores to individual SDOH, based on relative effect size magnitudes. PsRS was calculated by summing risk scores for individual SDOH, for each participant; and validated using a separate validation cohort. Final sample comprised 164,696 adults. PsRS included 7 SDOH: unemployment, inability to pay medical bills, low income, psychological distress, delayed care due to lack of transport, food insecurity, and less than high school education. PsRS ranged from 0–20 and exhibited excellent calibration and discrimination. Individuals with the highest PsRS (5th quintile) had nearly 4-fold higher ASCVD prevalence, relative to those with the lowest risk scores (1st quintile). Area under receiver operating curve (AU-ROC) for PsRS with SDOH alone was 0.836. Addition of SDOH to the model with only demographic and clinical risk factors (AU-ROC=0.852) improved overall discriminatory power, with AU-ROC for final PsRS (demographics + clinical + SDOH) = 0.862. Cumulatively, SDOH may help identify individuals with ASCVD, beyond traditional cardiovascular risk factors. In this study, we provide a unique validated PsRS for ASCVD in a national sample of US adults. Future study should target development of similar scores in diverse populations, and incorporate longitudinal study designs.

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56 citations in Web of Science
49 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being
#10 Reduced Inequalities

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Collaboration types
Domestic collaboration
Web of Science research areas
Cardiac & Cardiovascular Systems
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