Back to Results

< Previous   Next >

Neighborhood socioeconomic status, Medicaid coverage and medical management of myocardial infarction: Atherosclerosis risk in communities (ARIC) community surveillance

Creators: Foraker, Randi E, Rose, Kathryn M, Whitsel, Eric A, Suchindran, Chirayath M, Wood, Joy L, Rosamond, Wayne D

File Type: pdf | Filesize: 410.2 KB | Date Added: 2012-08-23 | Date Created: 2010-10-21

Abstract Background Pharmacologic treatments are efficacious in reducing post-myocardial infarction (MI) morbidity and mortality. The potential influence of socioeconomic factors on the receipt of pharmacologic therapy has not been systematically examined, even though healthcare utilization likely influences morbidity and mortality post-MI. This study aims to investigate the association between socioeconomic factors and receipt of evidence-based treatments post-MI in a community surveillance setting. Methods We evaluated the association of census tract-level neighborhood household income (nINC) and Medicaid coverage with pharmacologic treatments (aspirin, beta [&#946;]-blockers and angiotensin converting enzyme [ACE] inhibitors; optimal therapy, defined as receipt of two or more treatments) received during hospitalization or at discharge among 9,608 MI events in the ARIC community surveillance study (1993-2002). Prevalence ratios (PR, 95% CI), adjusted for the clustering of hospitalized MI events within census tracts and within patients, were estimated using Poisson regression. Results Seventy-eight percent of patients received optimal therapy. Low nINC was associated with a lower likelihood of receiving &#946;-blockers (0.93, 0.87-0.98) and a higher likelihood of receiving ACE inhibitors (1.13, 1.04-1.22), compared to high nINC. Patients with Medicaid coverage were less likely to receive aspirin (0.92, 0.87-0.98), compared to patients without Medicaid coverage. These findings were independent of other key covariates. Conclusions nINC and Medicaid coverage may be two of several socioeconomic factors influencing the complexities of medical care practice patterns.