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Racial/ethnic Heterogeneity in the Socioeconomic Patterning of CVD Risk Factors: in the United States: The Multi-Ethnic Study of Atherosclerosis
Journal article   Open access   Peer reviewed

Racial/ethnic Heterogeneity in the Socioeconomic Patterning of CVD Risk Factors: in the United States: The Multi-Ethnic Study of Atherosclerosis

Shawn Boykin, Ana V. Diez-Roux, Mercedes Carnethon, Sandi Shrager, Hanyu Ni and Melicia Whitt-Glover
Journal of health care for the poor and underserved, v 22(1)
01 Feb 2011
DOI: https://doi.org/10.1353/hpu.2011.0001
PMID: 21317510
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3312013View
Accepted (AM)Open Access (License Unspecified),  Open

Abstract

Cardiovascular disease ethnicity race risk factors socioeconomic status
Many studies document racial variation, gender differences, and socioeconomic status (SES) patterning in cardiovascular disease (CVD) risk factors but few studies have investigated heterogeneity in SES differences by race/ethnicity or gender. Using data from the Multi-Ethnic Study of Atherosclerosis (N = 6,814) and stratified regression models, we investigated race/ethnic differences in the SES patterning of diabetes, hypertension, smoking, and body mass index (BMI). Inverse socioeconomic gradients in hypertension, diabetes, smoking, and BMI were observed in White and Black women but associations were weaker or absent in Hispanic and Chinese women (except in the case of diabetes for Hispanic women). Even greater heterogeneity in social patterning of risk factors was observed in men. In White men all four risk factors were inversely associated with socioeconomic position, although often associations were only present or were stronger for education than for income. The inverse socioeconomic patterning was much less consistent in men of other races/ethnic groups, and higher SES was associated with higher BMI in non-White men. These findings have implications for understanding the causes of social patterning, for the analysis of SES adjusted race/ethnic differences, and for the targeting of interventions.

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55 citations in Web of Science
56 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
Health Policy & Services
Public, Environmental & Occupational Health
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