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Unequal Exposure or Unequal Vulnerability? Contributions of Neighborhood Conditions and Cardiovascular Risk Factors to Socioeconomic Inequality in Incident Cardiovascular Disease in the Multi-Ethnic Study of Atherosclerosis
Journal article   Open access   Peer reviewed

Unequal Exposure or Unequal Vulnerability? Contributions of Neighborhood Conditions and Cardiovascular Risk Factors to Socioeconomic Inequality in Incident Cardiovascular Disease in the Multi-Ethnic Study of Atherosclerosis

Mustafa Hussein, Ana V Diez Roux, Mahasin S Mujahid, Theresa A Hastert, Kiarri N Kershaw, Alain G Bertoni and Ana Baylin
American journal of epidemiology, v 187(7), pp 1424-1437
01 Jul 2018
PMID: 29186311
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1093/aje/kwx363View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze) Open

Abstract

Aged Aged, 80 and over Atherosclerosis - epidemiology Atherosclerosis - ethnology Cardiovascular Diseases - epidemiology Cardiovascular Diseases - ethnology Ethnic Groups - statistics & numerical data Female Health Status Disparities Humans Incidence Male Middle Aged Poisson Distribution Residence Characteristics - statistics & numerical data Risk Factors Social Environment Socioeconomic Factors United States - epidemiology
Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.

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Web of Science research areas
Public, Environmental & Occupational Health
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