Medical Care

Skip Navigation LinksHome > February 2013 - Volume 51 - Issue 2 > Ethnicity and Long-term Prognosis After Myocardial Infarctio...
Medical Care:
doi: 10.1097/MLR.0b013e318270bab5
Original Articles

Ethnicity and Long-term Prognosis After Myocardial Infarction: A Population-based Cohort Study

Nakash, Ora PhD*; Gerber, Yariv PhD; Goldbourt, Uri PhD; Benyamini, Yael PhD; Drory, Yaacov MD§; for the Israel Study Group on First Acute Myocardial Infarction

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Background: Health disparities are systematic differences in health, favoring members of advantaged over disadvantaged groups in the society. This study examines the contribution of multiple socioeconomic status (SES) measures to ethnic differences in after myocardial infarction (MI) prognosis.

Methods: Patients aged 65 years and younger (n=1040) belonging to Ashkenazi and Mizrahi advantaged and disadvantaged ethnic groups discharged from 8 hospitals in central Israel after incident MI in 1992–1993, were followed up through 2005 for all-cause mortality, recurrent MI, heart failure, and ischemic stroke.

Results: Advantaged Ashkenazi had higher education, income, employment, and neighborhood SES compared with disadvantaged Mizrahi. Cardiovascular risk factors varied among the different ethnic groups. Results showed that the association between ethnic group and all outcomes differed substantially between models that included a single SES measure and those that included multiple measures. For example, the hazard ratio for mortality in disadvantaged Mizrahi compared with advantaged Ashkenazi was 1.87 [95% confidence interval (CI), 1.40–2.48] in a model adjusting only for demographic variables; 1.58 (95% CI, 1.18–2.12) in a model adjusting also for income; and 1.03 (95% CI, 0.74–2.04) in a model adjusting for all measured SES indicators. Further adjustment for clinical variables did not appreciably change the results.

Conclusions: Findings show that a wide array of modifiable social factors shaped by income, education, and neighborhood socioeconomic conditions can explain ethnic health differences and highlight the importance of using multivariable models of SES.

© 2013 Lippincott Williams & Wilkins, Inc.


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