PURPOSE: Low socioeconomic status (SES) predicts coronary artery disease (CAD) onset, but its value among patients with CAD is uncertain. Geographic measures (e.g., residential neighborhood) may predict risk, but this requires further evaluation. METHODS: A cohort of 3410 patients with significant, angiographically-defined CAD (> or =1 lesion of > or =70% stenosis) joined a registry during the period between 1993 and 2000 and was followed for 6.7 years (median 3.7 years). A geographic SES measure-residential economic status (RES)-and insurance type were examined for association with mortality or myocardial infarction (MI). RESULTS: In Cox regression adjusting for 17 covariates, lower RES quartile was associated with increased death/MI (p-trend<0.001), death (p-trend=0.001), and MI (p-trend=0.07). First RES quartile (vs. fourth) predicted death/MI (hazard ratio [HR]=1.32, 95% confidence interval [CI]=1.07-1.62, p=0.01) and death (HR=1.46, CI=1.12-1.91, p=0.006), but not MI (HR=1.18, p=0.31). Compared with private insurance, self-pay (HR=1.88, p=0.053), charity care (HR=1.71, p<0.001), and Medicaid (HR=1.43, p=0.24), but not Medicare (HR=0.95, p=0.68), were associated with death/MI. CONCLUSIONS: Both geographic (RES) and economic (insurance) measures of SES independently predicted risk of death/MI in a large population with angiographically-defined CAD. This suggests that SES remains a significant predictor of health outcomes after CAD has developed, and that geographic measures of SES deserve further evaluation.
PURPOSE: Low socioeconomic status (SES) predicts coronary artery disease (CAD) onset, but its value among patients with CAD is uncertain. Geographic measures (e.g., residential neighborhood) may predict risk, but this requires further evaluation. METHODS: A cohort of 3410 patients with significant, angiographically-defined CAD (> or =1 lesion of > or =70% stenosis) joined a registry during the period between 1993 and 2000 and was followed for 6.7 years (median 3.7 years). A geographic SES measure-residential economic status (RES)-and insurance type were examined for association with mortality or myocardial infarction (MI). RESULTS: In Cox regression adjusting for 17 covariates, lower RES quartile was associated with increased death/MI (p-trend<0.001), death (p-trend=0.001), and MI (p-trend=0.07). First RES quartile (vs. fourth) predicted death/MI (hazard ratio [HR]=1.32, 95% confidence interval [CI]=1.07-1.62, p=0.01) and death (HR=1.46, CI=1.12-1.91, p=0.006), but not MI (HR=1.18, p=0.31). Compared with private insurance, self-pay (HR=1.88, p=0.053), charity care (HR=1.71, p<0.001), and Medicaid (HR=1.43, p=0.24), but not Medicare (HR=0.95, p=0.68), were associated with death/MI. CONCLUSIONS: Both geographic (RES) and economic (insurance) measures of SES independently predicted risk of death/MI in a large population with angiographically-defined CAD. This suggests that SES remains a significant predictor of health outcomes after CAD has developed, and that geographic measures of SES deserve further evaluation.
Authors: Gina S Lovasi; Anne Vernez Moudon; Nicholas L Smith; Thomas Lumley; Eric B Larson; Dong W Sohn; David S Siscovick; Bruce M Psaty Journal: Health Place Date: 2007-09-21 Impact factor: 4.078
Authors: Sheena Kayaniyil; Chris I Ardern; Jane Winstanley; Cynthia Parsons; Stephanie Brister; Paul Oh; Donna E Stewart; Sherry L Grace Journal: Patient Educ Couns Date: 2008-10-25
Authors: Damien J LaPar; George J Stukenborg; Richard A Guyer; Matthew L Stone; Castigliano M Bhamidipati; Christine L Lau; Irving L Kron; Gorav Ailawadi Journal: Circulation Date: 2012-09-11 Impact factor: 29.690
Authors: Kathryn M Rose; Chirayath M Suchindran; Randi E Foraker; Eric A Whitsel; Wayne D Rosamond; Gerardo Heiss; Joy L Wood Journal: Ann Epidemiol Date: 2009-10-07 Impact factor: 3.797