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220 THE EFFECTS OF RACE AND SOCIOECONOMIC FACTORS ON SUBCLINICAL CARDIOVASCULAR DISEASE IN THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS.
  1. S. L. Tam1,
  2. K. E. Watson1,
  3. P. Srikanthan1
  1. 1Department of Medicine/Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, CA.

Abstract

Purpose The purpose of this study is to assess the effects of race and socioeconomic factors on subclinical cardiovascular disease (coronary calcium score [CCS], common carotid intimal-medial thickness [ccIMT], and ankle-brachial index [ABI]).

Methods The Multi-Ethnic Study of Atherosclerosis (MESA) is a prospective, observational study with 6,814 adults without clinical cardiovascular disease. Information on socioeconomics, lifestyle, biological variables, and measurements of subclinical cardiovascular disease were obtained from the baseline visit.

Results Differences in the outcome measures of CCS ≥ 75th percentile for age and gender, ccIMT > 1 mm, and ABI < 1 were observed after stratifying by race, socioeconomic, lifestyle, and biological factors and assessment using t-tests and chi-square tests. After controlling for socioeconomic, lifestyle, and biological factors in a multiple logistic regression model, being African American or Hispanic was protective against a CCS ≥ 75th percentile (OR = 0.54 and OR = 0.73, respectively). Modeling showed that not having health insurance and being African American increased the odds of a ccIMT > 1 mm (OR = 1.48 and OR = 1.29, respectively). Modeling also showed that education and being Chinese or Hispanic were protective against an ABI < 1 (OR = 0.79, OR = 0.49, and OR = 0.42, respectively), whereas unemployment and being African American increased the odds (OR = 1.50 and OR = 1.50, respectively). Associations were also found between traditional risk factors for cardiovascular disease (gender, age, interleukin-6, pack-years of cigarette smoking, LDL cholesterol, family history of heart attack, diabetes, hypertension, BMI, alcohol consumption, triglycerides, waist circumference, and MET-min/week) and the three outcomes (OR ≠ 1). After modeling with and without socioeconomic variables, such variables (race, income, education, employment, insurance, and birthplace) contribute significant information to all models (CCS, ccIMT, and ABI) using the log-likelihood test (p < .001).

Conclusions This study shows that race and socioeconomic factors impact subclinical cardiovascular disease. In a multicultural society, these nonbiological factors need to be acknowledged to add a crucial perspective to the current biological model of cardiovascular disease risk.

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