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Race/ethnicity, neighborhood socioeconomic status and cardio-metabolic risk
Journal article   Open access   Peer reviewed

Race/ethnicity, neighborhood socioeconomic status and cardio-metabolic risk

Sharon Stein Merkin, Arun Karlamangla, Ana Diez Roux, Sandi Shrager, Karol Watson and Teresa Seeman
SSM - population health, v 11, 100634
Aug 2020
PMID: 32775593
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1016/j.ssmph.2020.100634View
Published, Version of Record (VoR)CC BY-NC-ND V4.0 Open

Abstract

Allostatic load Cardio-metabolic Neighborhood socioeconomic status Race/ethnic disparities
To determine the association between neighborhood socioeconomic status (NSES) and cardio-metabolic risk and whether this relationship differs by race/ethnicity. Participants in the Multi-Ethnic Study of Atherosclerosis (n = 5750), ages 45–84 years, from 6 US counties, including 5 examinations from 2000 to 2012. We calculated a modified allostatic load (AL) index, indicating cardio-metabolic risk. NSES score included census-derived measures at census tract of residence. Mixed effects growth curve models were used to assess linear and non-linear associations between NSES and AL at baseline and over time. Higher NSES was associated with lower AL across race/ethnic groups; considering NSES quintiles, significant associations were found only for the highest NSES quintiles (difference of -0.86 and -1.15 for white and Hispanic participants) vs. the lowest. We found no significant association between NSES and change in AL over time. Our findings suggest that the relationship between NSES and AL reflects the health benefits of living in the most advantaged neighborhoods. Understanding the impact of higher NSES on health effects may help identify interventions to effectively target high risk neighborhoods. •These findings confirm the association between high NSES and low AL; pattern is similar across race/ethnic groups.•The relationship between NSES and AL reflects the health benefits of living in the most advantaged neighborhoods.•Identifying neighborhood factors that impact health is crucial to effectively target high risk neighborhoods.

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17 citations in Scopus

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UN Sustainable Development Goals (SDGs)

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

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

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Collaboration types
Domestic collaboration
Web of Science research areas
Public, Environmental & Occupational Health
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