OBJECTIVE: To evaluate the association of neighborhood-level income and individual-level education with post-myocardial infarction (MI) mortality in community patients. PARTICIPANTS AND METHODS: From November 1, 2002, through May 31, 2006, 705 (mean+/-SD age, 69+/-15 years; 44% women) residents of Olmsted County, MN, who experienced an MI meeting standardized criteria were prospectively enrolled and followed up. The neighborhood's median household income was estimated by census tract data; education was self-reported. Demographic and clinical variables were obtained from the medical records. RESULTS: Living in a less affluent neighborhood and having a low educational level were both associated with older age and more comorbidity. During follow-up (median, 13 months), 155 patients died. Neighborhood income (hazard ratio [HR], 2.10; 95% confidence interval [CI], 1.42-3.12; for lowest [median, $34,205] vs highest [median, $60,652] tertile) and individual education (HR, 2.21; 95% CI, 1.47-3.32; for <12 vs >12 years) were independently associated with mortality risk. Adjustment for demographics and various post-MI prognostic indicators attenuated these estimates, yet excess risk persisted for low neighborhood income (HR, 1.62; 95% CI, 1.08-2.45). Modeled as a continuous variable, each $10,000 increase in annual income was associated with a 10% reduction in mortality risk (adjusted HR, 0.90; 95% CI, 0.82-0.99). CONCLUSION: In this geographically defined cohort of patients with MI, low individual education and poor neighborhood income were associated with a worse clinical presentation. Poor neighborhood income was a powerful predictor of mortality even after controlling for a variety of potential confounding factors. These data confirm the socioeconomic disparities in health after MI.
OBJECTIVE: To evaluate the association of neighborhood-level income and individual-level education with post-myocardial infarction (MI) mortality in community patients. PARTICIPANTS AND METHODS: From November 1, 2002, through May 31, 2006, 705 (mean+/-SD age, 69+/-15 years; 44% women) residents of Olmsted County, MN, who experienced an MI meeting standardized criteria were prospectively enrolled and followed up. The neighborhood's median household income was estimated by census tract data; education was self-reported. Demographic and clinical variables were obtained from the medical records. RESULTS: Living in a less affluent neighborhood and having a low educational level were both associated with older age and more comorbidity. During follow-up (median, 13 months), 155 patients died. Neighborhood income (hazard ratio [HR], 2.10; 95% confidence interval [CI], 1.42-3.12; for lowest [median, $34,205] vs highest [median, $60,652] tertile) and individual education (HR, 2.21; 95% CI, 1.47-3.32; for <12 vs >12 years) were independently associated with mortality risk. Adjustment for demographics and various post-MI prognostic indicators attenuated these estimates, yet excess risk persisted for low neighborhood income (HR, 1.62; 95% CI, 1.08-2.45). Modeled as a continuous variable, each $10,000 increase in annual income was associated with a 10% reduction in mortality risk (adjusted HR, 0.90; 95% CI, 0.82-0.99). CONCLUSION: In this geographically defined cohort of patients with MI, low individual education and poor neighborhood income were associated with a worse clinical presentation. Poor neighborhood income was a powerful predictor of mortality even after controlling for a variety of potential confounding factors. These data confirm the socioeconomic disparities in health after MI.
Authors: S S Rathore; A K Berger; K P Weinfurt; M Feinleib; W J Oetgen; B J Gersh; K A Schulman Journal: Circulation Date: 2000-08-08 Impact factor: 29.690
Authors: Russell V Luepker; Fred S Apple; Robert H Christenson; Richard S Crow; Stephen P Fortmann; David Goff; Robert J Goldberg; Mary M Hand; Allan S Jaffe; Desmond G Julian; Daniel Levy; Teri Manolio; Shanthi Mendis; George Mensah; Andrzej Pajak; Ronald J Prineas; K Srinath Reddy; Veronique L Roger; Wayne D Rosamond; Eyal Shahar; A Richey Sharrett; Paul Sorlie; Hugh Tunstall-Pedoe Journal: Circulation Date: 2003-11-10 Impact factor: 29.690
Authors: Sunil V Rao; Padma Kaul; L Kristin Newby; A Michael Lincoff; Judith Hochman; Robert A Harrington; Daniel B Mark; Eric D Peterson Journal: J Am Coll Cardiol Date: 2003-06-04 Impact factor: 24.094
Authors: V Salomaa; H Miettinen; M Niemelä; M Ketonen; M Mähönen; P Immonen-Räihä; S Lehto; T Vuorenmaa; S Koskinen; P Palomäki; H Mustaniemi; E Kaarsalo; M Arstila; J Torppa; K Kuulasmaa; P Puska; K Pyörälä; J Tuomilehto Journal: J Epidemiol Community Health Date: 2001-07 Impact factor: 3.710
Authors: A V Diez Roux; S S Merkin; D Arnett; L Chambless; M Massing; F J Nieto; P Sorlie; M Szklo; H A Tyroler; R L Watson Journal: N Engl J Med Date: 2001-07-12 Impact factor: 91.245
Authors: Carina Wennerholm; Björn Grip; Annakarin Johansson; Hans Nilsson; Marja-Liisa Honkasalo; Tomas Faresjö Journal: Int J Health Geogr Date: 2011-01-12 Impact factor: 3.918
Authors: William M Schultz; Heval M Kelli; John C Lisko; Tina Varghese; Jia Shen; Pratik Sandesara; Arshed A Quyyumi; Herman A Taylor; Martha Gulati; John G Harold; Jennifer H Mieres; Keith C Ferdinand; George A Mensah; Laurence S Sperling Journal: Circulation Date: 2018-05-15 Impact factor: 29.690
Authors: Merete Osler; Eva Prescott; Ida Kim Wium-Andersen; Else Helene Ibfelt; Martin Balslev Jørgensen; Per Kragh Andersen; Terese Sara Høj Jørgensen; Marie Kim Wium-Andersen; Solvej Mårtensson Journal: PLoS One Date: 2015-10-29 Impact factor: 3.240
Authors: Duk Won Bang; Sheila M Manemann; Yariv Gerber; Veronique L Roger; Christine M Lohse; Jennifer Rand-Weaver; Elizabeth Krusemark; Barbara P Yawn; Young J Juhn Journal: Int J Environ Res Public Health Date: 2014-11-12 Impact factor: 3.390
Authors: Inge Kirchberger; Christa Meisinger; Hildegard Golüke; Margit Heier; Bernhard Kuch; Annette Peters; Philip A Quinones; Wolfgang von Scheidt; Andreas Mielck Journal: Int J Equity Health Date: 2014-02-19